understanding the genetics of potato tuber calcium and its

Understanding the Genetics of Potato Tuber Calcium and its Implications in Breeding for Improved Quality

By Cinthya Zorrilla Cisneros

A dissertation submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy (Plant Breeding and Plant Genetics)

at the UNIVERSITY OF WISCONSIN-MADISON

2013

Date of final oral examination: 08/26/13 The dissertation is approved by the following members of the Final Oral Committee: Jiwan P. Palta, Professor, Horticulture Michael Havey, Professor (USDA), Horticulture Shelley Jansky, Associate Professor (USDA), Horticulture John Bamberg, Professor (USDA), Horticulture Shawn Kaeppler, Professor, Agronomy

i

GENERAL ABSTRACT

Calcium is a nutrient that plays an important signaling and structural roles in plants. The goal of

this research was to understand the relationship between tuber calcium and tuber quality using

two approaches. The first approach was the development of two reciprocal populations

segregating for specific gravity, yield, chip quality, internal quality, common scab, and tuber

calcium at the tetraploid level. This was accomplished by crossing Atlantic and Superior, two

cultivars that differ for all these traits. The broad-sense heritabilities and genetic correlations for

these traits were evaluated using data from field performances during 2009 to 2012 seasons.

Hollow heart incidence and incidence and severity of pitted scab were negatively correlated to

tuber calcium. Calcium was also negatively correlated to specific gravity, yield, and chip

lightness; and positively correlated. Quantitative trait loci that control tuber calcium, tuber

quality and pitted scab tolerance in the Atlantic x Superior population were identified. The

inheritance of tuber calcium has an important genetic component and is controlled by several

QTL located throughout the genome. The second approach, in the present investigation was to

study the effects of the expression of the calcium vacuolar antiporter CAX1 from Arabidopsis

under the control of the CaMV35S and the cdc2a promoters in the potato cultivar Atlantic. This

cultivar has low tuber calcium and poor tuber quality. Ou results suggest that an increased

transport of calcium into the vacuoles of these transgenic lines caused calcium deficiency

symptoms, compromised plant heath and increased tuber defects by a reduction of apoplastic

calcium and cell wall damage. These deficiency symptoms were partially ameliorated under

higher calcium treatments. Our results show that the calcium stored in the vacuoles of these

transgenics is in the form of calcium oxalate crystals which trap calcium and make it unavailable

to maintain proper membrane and cell wall functions. The new knowledge generated about the

ii

genetics and physiology of tuber calcium and its relationship with tuber quality could help in the

breeding effort to produce potato cultivars with improved tuber internal quality and scab

tolerance.

iii

DEDICATION

This dissertation is dedicated

to my family: Percy, Raymi and Illary;

to my parents Pedro and Marta;

and to my siblings Gina and Daniel.

for your love and support that gave me the strength to finish this journey.

iv

ACKNOWLEDGEMENTS

Thanks to Dr. Jiwan Palta for the opportunity to study the PhD. at UW Madison.

Thanks to all the professors in my Committee: Shelley Jansky, John Bamberg, Mike Havey and Shawn Kaeppler for the constructive criticism of my work. Thanks for allocating some of your

precious time to read my manuscript and listen to me.

Thanks to the current and past members of the Palta lab, especially to Felix Navarro, Sandra Vega, Kyle Rak, Justin Schabow, Zienab Fawsi, Amr Hassan, Nesse Okut, Fei Li, Vladimir

Chernov, and Young Suk Chung that collaborated with me to record the phenotypic data.

Thanks also to every person in the Agronomy, Botany, Horticulture and Plant Pathology departments that ever lend me a reagent, a piece of equipment, or a tool.

Thanks to all the staff at Walnut street greenhouses as well as the Agricultural Research stations at Hancock, Rhinelander, and Arlington.

Thanks to Kendall Hirschi from the Baylor College of Medicine at Texas A&M University for sharing the CAX1 constructs and the positive controls.

Thanks to Christine Hackett from the James Hutton Institute for her support with the TetraploidMap software.

Thanks to the SolCAP project for selecting my population for genotyping with the SNP chip, especially to Joseph Coombs and David Douches.

Thanks to the USDA National Institute of Food and Agriculture and the HATCH grant by the University of Wisconsin, College of Agricultural and Life Sciences that partially funded this

research.

v

TABLE OF CONTENTS

ABSTRACT………………………………………………………………………………... i

DEDICATION…………………………………………………………………………...... iii

ACKNOWLEDGEMENTS………………………………………………………………... iv

TABLE OF CONTENTS…………………………………………………………..………. v

CHAPTER 1: General Introduction and Research Objectives………………………….…. 1

GENERAL INTRODUCTION……………………………………………………………. 1

RESEARCH OBJECTIVES……………………………………………………………….. 17

BIBLIOGRAPHY………………………………………………………………………….. 18

CHAPTER 2: The Atlantic x Superior reciprocal populations segregating for yield, specific gravity, tuber calcium, internal tuber quality, chip quality and common scab: opportunities to study the genetics of these traits at the tetraploid level………………..…..

32

ABSTRACT………………………………………………………………………………. 32

INTRODUCTION………………………………………………………………………… 35

MATERIAL AND METHODS…………………………………………………………… 39

RESULTS AND DISCUSSION…………………………………………………………… 42

CONCLUSIONS..………………………………………………………………………… 54

BIBLIOGRAPHY…………………………………………………………………………. 55

TABLES…………………………………………………………………………………… 62

FIGURES………………………………………………………………………………… 67

CHAPTER 3: Correlations and heritabilities of tuber quality, pitted scab and tuber calcium: Implications for selection of potatoes with improved tuber quality…...…………

69

ABSTRACT……………………………………………………………………………..... 69

vi

INTRODUCTION………………………………………………………………………… 70



CONCLUSIONS…………………………………………………………………………… 94

BIBLIOGRAPHY…………………………………………………………………………. 96

TABLES…………………………………………………………………………………… 102

FIGURES………………………………………………………………………………… 108

CHAPTER 4: Mapping QTL for Tuber Calcium, Tuber Quality and Pitted Scab in a Tetraploid Population of Potato (Solanum tuberosum) derived from Atlantic x Superior…

113

ABSTRACT……………………………………………………………………………… 113

INTRODUCTION………………………………………………………………………… 114



CONCLUSIONS…………………………………………………………………………… 143

BIBLIOGRAPHY…………………………………………………………………………. 144

TABLES…………………………………………………………………………………… 151

FIGURES………………………………………………………………………………… 159

CHAPTER 5: Over-expressing the Vacuolar Antiporter CAX1 in the Potato Cultivar Atlantic: Phenotype of the Transformed Clones and Implications to Understand the Role of Calcium on Tuber Quality and Plant Health……………………………………………

177

ABSTRACT……………………………………………………………………………… 177

INTRODUCTION………………………………………………………………………… 178


vii


SUMMARY AND CONCLUSIONS……………………………………………………… 200

BIBLIOGRAPHY…………………………………………………………………………. 203

TABLES…………………………………………………………………………………… 209

FIGURES…………………………………………………………………………………. 214

CHAPTER 6: General Discussion and Conclusions……………………………………… 233

DISCUSSION…………………………………………………………………………….. 233

CONCLUSSIONS………………………………………………………………………… 244

BIBLIOGRAPHY…………………………………………………………………………. 249

1

CHAPTER 1

General Introduction and Research Objectives

GENERAL INTRODUCTION

Role of calcium at the cellular and whole plant level

Calcium has been established as regulator of plant growth and development because changes

in cellular Ca2+ acting through Ca2+-modulated proteins and their targets regulate an

astonishing variety of cellular processes (Bush 1995, Reddy and Reddy 2004, Harper et al.

2004, Hepler 2005). Calcium concentrations vary within cell compartments. Cytoplasmic

Ca2+ concentrations are tightly regulated at 100-200nM but in the organelles can be in the µM

to mM range. The vacuoles are important repositories of Ca2+ with concentrations in the

millimolar range (Gilroy et al. 1993). Calcium also plays important structural roles in plants.

Calcium maintains membrane stability and cell integrity (Epstein 1972). Calcium stabilizes

cell membranes by connecting adjacent polar head groups of membrane lipids (Legge et al.

1982, Palta 1996, Hirschi 2004). An extracellular Ca2+ concentration of 0.1 to 1.0 mM was

found to be necessary to maintain the integrity and selective ion transport of the plasma

membrane (Hanson 1960). Calcium is also known to stabilize cell wall structure (Demarty et

al. 1984). The natural pectic acids found in cell walls are most often in the form of Ca2+ salts

(Preston 1979). Cell walls form stiff gels through Ca+2-mediated crosslinking of its carboxyl

2

groups through ionic and coordinate bonds with a pectin component called homogalacturonan

or polygalacturonic acid (Cosgrove 2005).

Calcium in the plant is taken up at the root level and transported across the root with water in

the xylem to the aerial part of the plant (Demarty et al. 1984). The movement of calcium is

mainly via the apoplast similar to the movement of water but some degree of Ca2+ transport

through the symplast has also been demonstrated (Gilliham et al. 2011). A study in onion

roots demonstrated that the radial movement of Ca2+ through the exodermis and endodermis

is primarily symplastic (Cholewa and Peterson 2004).

The storage of Ca2+ across plant tissues and cell types is heterogenous because some cell

types accumulate more calcium than others (Oparka and Davies 1988, Fricke et al. 1994,

Karley et al. 2000, Conn and Gilliham 2010). Calcium delivery to shoots is linked to the

transpiration rate and once it is deposited in the vacuole it is rarely re-distributed. Therefore

organs with high transpiration rates accumulate more calcium and low transpiring organs can

suffer calcium deficiencies (Gilliham et al. 2011). In plant tissues growing under calcium

deficiency, the nuclear envelope, plasma membrane and cell walls disintegrate and tissue

collapses resulting in necrosis (Marinos 1962, Kirkby and Pilbeam 1984).

Role of calcium in response to stress

Calcium has been shown to play an important role of plant responses to biotic and abiotic

stresses (Palta 1996, 2013). Endoplasmic reticulum signals are transduced by membrane-

bound transcription factors which are activated and mobilized under environmental stress

conditions (Liu and Howell 2010). Calcium is an important factor in the ability of plants to

resist salt stress possibly because of its role in maintaining membrane integrity (Lynch et al.

1987). Sodium content decreases slightly at higher calcium levels (Basset 1980).

3

Nevertheless there is variability between plant species in the response of supplemental

calcium under salinity (Cramer 2004). Recently a protective effect of calcium that limited the

impact of salinization on metabolic ripening process and induced plant salt tolerance has been

demonstrated by evaluating the tomato proteome (Manaa et al. 2013).

Calcium has been shown to play an important role in freezing injuries (Minorsky 1985, Arora

and Palta 1988, Palta 1996, Piotrowska 1998, Palta 2013). Calcium is reduced in the plasma

membrane when subjected to freezing injury initiating the injury process (Arora and Palta

1988). Calcium induces the expression of cold acclimation genes (Monroy and Dhindsa 1995,

Knight et al. 1996). Some of the approaches to reduce chilling injury in fruits and vegetables

includes the post-harvest use of calcium application (Wang 1993).

Calcium is also a primary sensory molecule in response to heat stress (Saidi et al. 2011,

Mittler et al. 2012). Reduced thermo-tolerance was observed when the extracellular calcium

was artificially reduced in various plant species (Gong et al. 1998, Liu et al. 2005, Wu and

Jinn 2010) and moss (Saidi et al. 2009). In potato the impact of heat stress is mitigated by

increasing soil applied calcium (Tawfik et al. 1996, Kleinhenz and Palta 2002). Calcium

influx into the cytoplasm in response to heat stress is regulated by plasma membrane cyclic

nucleotide gated calcium channels (Finka et al. 2012). Calcium has also been involved in the

protection against heat stress-induced oxidative stress (Larkindale and Knight 2002).

In addition calcium has a role in senescence (Poovaiah 1979). For instance senescence of

several plant tissues and organs has been shown to be retarded by calcium (Poovaiah and

Leopold 1973, Ferguson et al. 1983, Chéour et al. 1992, among others). Calcium regulates

senescence by regulating antioxidant enzyme activity (Sairam et al. 2011).

4

Calcium also has a role in biotic stress signaling. The calcium-mediated pathogen defense

programs have been recently reviewed by Ma and Berkowitz (2012). The plant defense

responses are triggered by increased cytosolic Ca2+. Recent reports have found conserved and

unique responses of calcium regulated genes to biotic and abiotic stresses (Narsai et al. 2013,

Yang et al. 2013). Higher tuber calcium has been shown to provide protection against soft-rot

caused by Pectobacterium (McGuire and Kelman 1984, 1986).

Candidate genes to increase calcium content in crops

There are numerous proteins of diverse function that interact with calcium (Boudsocq and

Sheen 2010). Therefore it is a complex system to study and a single gene may not be

responsible of regulating potato tuber calcium. The efforts to genetically modify plants for

increasing calcium content to improve stress tolerance and nutritional value are shortly

reviewed below. Calreticullin (CRT) is a conserved protein that has several functions in

plants (Jia et al. 2009) including intracellular Ca2+ homeostasis and Ca2+-dependant signal

pathways (Gelebart et al. 2005), molecular chaperone activity in the endoplasmic reticulum

(Denecke et al. 1995, Gelebart et al. 2005, Williams 2006), control of cell adhesion (Johnson

et al. 2001, Opas et al. 1996), immune system and apoptosis (Waterhouse and Pinkoski 2007)

and wound healing and pathogenesis (Qiu and Michalak 2009). The CRT protein is a

signalling molecule localized in the cytoplasm and the endoplasmic reticulum (Corbett and

Michalak 2000). Three CRT have been identified in Arabidopsis. CRT1a and CRT1b are

mainly related to general protein folding events whereas CRT3 is involved in pathogen

responses (Christensen et al. 2008, 2010). One approach to increase calcium concentration

has been to over-express CRT. The over-expression of CRT resulted in increased calcium

content and increased tolerance to abiotic stress in wheat (Jia et al. 2008). Another approach

5

is to alter calcium transporters. The H+/ Ca2+ antiporter 1 designated as CAX1 is a tonoplast

calcium antiporter was identified in Arabidopsis thaliana by suppressing yeast mutants

defective in vacuolar Ca2+ transport (Hirschi et al. 1996). Several CAX antiporters have been

identified in Arabidopsis with different ion specificities such as CAX2 that transports heavy

metals (Hirschi et al. 2000), CAX3 that transports Ca2+ mainly in roots (Manohar et al. 2011)

and CAX4 (Cheng et al. 2002) among others. The over-expression of a short version of the

Cation Exchanger 1 (sCAX1) has been found to increase calcium content in Arabidopsis

(Hirschi et al. 1996), potato (Park et al. 2005a), tomato (Park et al. 2005b) and carrots

(Morris et al. 2008). However, the increase in calcium content in the potato tuber was not

significant for the purpose of improving the nutritional value of potatoes for human

consumption (Park et al. 2005a). The expression of sCAX1 was shown to reduce apoplastic

Ca2+ levels which increased membrane leakiness and increased blossom end defect in tomato

(de Freitas et al. 2011). These studies suggest that the calcium transported into vacuoles by

CAX1 is unavailable in the apoplast. Coexpression of CRT1 resulted in a significant decrease

in Ca2+ deficiency symptoms in both tomato and tobacco without the addition of

supplemental Ca2+ (Wu et al. 2012). This effect of CRT on sCAX1-expressing lines might

have been caused by its calcium storage release function observed in Arabidopsis (Wyatt et

al. 2002). These studies suggest that the genetic control of calcium stored in organs is

controlled by several genes with complex interactions.

The potato plant

Potato is the most important non-grain crop in the world. The most commonly cultivated

potato species is the autotetraploid Solanum tuberosum with a basic number of 12

6

chromosomes. The size of the potato genome is 844 Mb and 86% of this genome has been

sequenced and assembled (Potato Genome Sequencing Consortium 2011). In addition, a

study of the transcriptome of potato found tissue-specific gene expression and genes with

tissue or condition restricted expression (Massa et al. 2011). Linkage disequilibrium decay to

r2<0.1 evaluated in a set of cultivated potato was approximately 5.3 Kb (D’Hoop et al. 2010).

This characteristic has been considered as promising because the required marker density is

not a limiting factor to do association mapping (Björn et al. 2010).

Why study calcium in potato?

Potato tubers have some important characteristics that make potato a good model to study the

role of calcium in plants. The transpiration of potato tubers is low because they are under the

soil and therefore the movement of water and calcium to the tubers is low (Palta 1996).

Potatoes are rich in potassium and phosphorus but are rather poor sources of sodium and

calcium (Lampitt and Goldenberg 1940). Calcium taken up by the main root system is

transported into the plant foliage but not into the tubers and only the calcium taken in by

tuber roots and stolon roots is transported into the tuber (Kratzke and Palta 1986). Phenotypic

variation for the amount of calcium has been observed in wild and cultivated potatoes

(Bamberg et al. 1993, Karlsson et al. 2006). Tuber calcium concentrations between 119.2 -

295.1 μg/g dry weight were reported in cultivated potatoes grown in soils without

supplemental calcium whereas this concentrations increased to 142.9 - 338.4 μg/g dry weight

after application of supplemental calcium (Karlsson et al. 2006). These characteristics make

the study of calcium in potato tubers an interesting subject.

7

Breeding potato chipping varieties

Potato chips are very popular snack foods in the western diet. Yearly about 30 million MT of

potatoes or almost 10% of the global potato crop are converted into consumer products,

mainly in the European Union and North America where one to two thirds of the daily potato

consumption is in processed form such as French fries and potato chips (Keijbets 2008).

Processed potato consumption in the United States has steadily increased over the past five

decades from 11.48 kg per person in 1960 to an estimated 37 kg per person based on potato

fresh weight (Lucier and Dettmann 2007, Keijbets 2008). The increasing demand of this

snack food has been accompanied by the growth of the potato chip industry and thus

increasing the need for varieties with high yields that are suitable for chipping. In the last 50

years significant progress has been made towards breeding varieties with better chipping

quality containing higher tuber solids, lower levels of reducing sugars and lighter chip color.

Historically, the development of Lenape has been identified as a landmark for the

development of modern chipping varieties with higher tuber solids (Love et al. 1998).

Snowden, Pike and Atlantic are the most popular varieties used for chip production (Lucier

and Dettmann 2007). However chipping varieties still have some problems with internal

defects such as hollow heart, brown center, internal brown spot and black spot bruise. Chip

quality of potatoes is measured mainly by chip color. Chip color is affected by several factors

including the composition of the tubers (Rodriguez-Saona and Wrostald 1997). Chip color is

also affected by the storage temperature and age of the tubers that trigger the breakage of

starch into reducing sugars (Hyde and Morrison 1964). A high amount of reducing sugars

will turn into darker chips due to a chemical reaction called Maillard reaction which is a non-

enzymatic browning (Danehy 1986). In addition enzymatic browning or darkening of cut

8

potatoes is a result of the oxidation of various organic compounds (Makower 1964, Matheis

1983, Friedman 1997) and is considered a negative trait that reduces chip quality.

Evaluation of cytoplasmic inheritance in reciprocal populations of potato

Studies trying to understand cytoplasmic inheritance in potato have been performed in

reciprocal populations. Differences between reciprocal populations of potato have been

reported for male sterility and other traits. De la Puente and Peloquin (1968) studied

cytoplasmic male sterility in potato in relation to the tetraploid Groups Andigena and

Tuberosum. In addition, large reciprocal differences were observed in when clones of Group

Phureja and Group Stenotomum were reciprocally crossed to Group Tuberosum haploids.

These populations differed for several characteristics including tuber initiation, tuber set, vine

senescence, tuber yield, flowering, and male fertility generated by the difference in

photoperiod. Cytoplasmic inheritance was considered one of the possible explanations for

this difference in photoperiod reaction (Sanford and Hanneman 1979). A report of significant

yield differences between reciprocal populations of potato was observed when parents of

opposite maturities were crossed. The higher-yielding reciprocal always had the higher-

yielding parent as the maternal parent (Sanford and Hanneman 1982). Differences in chip

color performance between reciprocal populations were observed in diploid populations

(Lauer and Shaw 1970, Jakuczun and Zimnoch-Guzowska 2004) but not in tetraploid

populations (Coffin et al. 1988, Ehlenfeldt et al. 1990, and Pereira et al. 1993).

9

Internal defects of potato

Absence of internal defects is critical for acceptable tuber quality for potato processing.

Internal tuber defects such as hollow heart, brown center, internal brown spot and black spot

bruise can reduce the value of potatoes; and thus cause huge losses to growers (Tucker 2013).

Current popular chipping varieties namely Atlantic (Webb et al. 1978) and Snowden suffer

from poor internal quality. Consequently, breeding efforts are needed to generate new chip

varieties with reduced defects and good tuber quality.

Hollow heart is a physiological disorder characterized by a star-like or irregularly-shaped

cavity in the pith region of the tuber (Levitt 1942). This defect arises when growing

conditions abruptly change during the season or when the potato plants recover too quickly

after a period of environmental or nutritional stress (Rex and Massa 1989). After recovery the

tubers begin to grow rapidly that results in the tuber pith necrosis or tissue pulling apart

leaving a void in the center (Hutchinson 2003). Brown center is another common internal

defect of the potato tuber pith characterized by a region of cell necrosis which results in

brown tissue that frequently precedes the development of hollow heart (Hutchinson 2003).

Some methods have been developed to detect hollow heart without destroying the tuber

including an acoustic impact method that measures the resonant frequencies of the tubers that

detected hollow heart with an R2=0.97 (Elbatawi 2008), and X-rays analysis (Finney and

Norris 1978). However, these methods are useful for the industry, but they do not prevent

losses for the growers.

Another severe physiological disorder called internal brown spot (IBS) in the mid-western

US and called internal heat necrosis (IHN) in the eastern US is a non-pathogenic internal

necrosis. The expression of symptoms varies significantly by genotype-environment

interactions (Sterret and Heninger 1997, Yencho et al. 2008). This defect is characterized by

10

brown spots or blotches that first appear toward the apical end of the tuber parenchyma but in

severe cases may involve most of the parenchyma (Henninger et al. 2000). The application of

calcium to plants in a nutrient solution was shown to decrease internal brown spot (Olsen et

al. 1996, Ozgen et al. 2006). However, some contradictory data have been found in other

studies that indicated that neither lime nor gypsum were effective to reduce internal heat

necrosis (Sterret and Henninger 1991).

Blackspot bruise is a physiological disorder that results from the mechanical stress during

harvesting and handling (Baritelle et al. 2000, Lærke et al. 2002). This type of lesion is

normally recognised as a 1-2 mm zone with a bluish-grey to black colored region beneath the

skin without visible cell wall fractures (Hughes 1980). This defect is not detected either

visually or chemically on the surface (Baritelle et al. 2000). The color of blackspots results

from polyphenol oxidase mediated oxidation of phenols to the black pigment melanin

(Matheis 1987). The disruption of intracellular membranes is an immediate effect of the

impact; and the consequent contact between the polyphenol oxidase located in the

amyloplasts and its substrates located in the vacuole may be the explanation for the

development of blackspots (Lærke et al. 2000). The susceptibility to bruising has been related

with high specific gravity (Baritelle and Hyde 2003). Therefore the structural properties of

the tuber are crucial for its resistance to blackspot formation caused by impact. In addition

recent studies suggest that the incidence of bruise goes down dramatically once the tuber

calcium concentration is above 200 μg/g (Karlsson et al. 2006).

11

Common scab of potato

Another disease that affects tuber quality is common scab caused by several species of the

bacterial genus Streptomyces. that belong to the Actinomycetes (Bjor and Roer 1980). The

lesions caused by Streptomyces spp. in potato tubers range from superficial to deep cavities

on the potato surface (Loria et al. 1997). The characterization of strains that cause pitted scab

show that they are a homogenous group with high cellulolytic and proteolytic activities

(Faucher et al. 1995). Higher incidences of common scab have been observed in soils with

higher pH (Blodgett and Cowan 1935). Tubers of scab susceptible cultivars have been found

to contain more reducing sugars in the tuber peel (Goto 1981). Resistance to common scab is

usually tested in fields where scab is known to occur frequently and a natural inoculum is

available (Goth et al. 1993, Mishra and Srivstava 2001). No cultivars are known to be

immune to common scab and differences in resistance and susceptibility are quantitative

(McKee 1958, Harrison 1962, Scholte and Labruyere 1985). The most practical method of

reducing losses caused by common scab is to use resistant varieties and cultural practices that

make conditions unfavorable for scab development (Loria 2001, Haynes et al. 2010).

Tuber calcium and its relationship with internal defects of potato and disease tolerance

Calcium has a very important nutrient that has signaling and structural roles in plants.

Transport of calcium is associated with water flow and therefore transpiration (Gilliham et al.

2011). Tubers are structures that do not transpire as much as the foliage (Baker and Moorby

1969) and thus can experience calcium deficiency even at optimal calcium levels in the soil.

Localized tissue calcium deficiencies are implicated as mechanisms initializing cell death and

tissue necrosis leading to internal brown spot and hollow heart in potatoes (Bangerth 1979,

12

Collier et al. 1980, Olsen et al. 1996, Palta 1996, Levitt 1942, Arteca et al. 1980).

Physiological studies have been conducted that demonstrate that in-season fertilization with

calcium results in an increase in tuber calcium (Clough 1994). This increase in tuber calcium

was correlated to a decrease in the incidence of internal defects such as blackspot bruise

(Karlsson et al. 2006) hollow heart and internal brown spot (Clough 1994, Kleinhenz et al.

1999, Ozgen et al. 2006) internal brown spot as well as sub-apical necrosis (Tzeng et al.

1986).

A good supply of calcium contributes to reduce favorable conditions for pathogen

development. For example pathogen populations of Pseudomonas solanacearum decreased in

tomato stems with increased calcium concentrations (Yamazaki and Hoshina 1995). Also a

negative correlation has been observed between calcium and severity of bacterial wilt

induced by Ralstonia solanacearum in tomato (Jiang et al. 2013). Potato and tomato are

related species and therefore we can expect similar effects of calcium on potato pathogens.

McGuire and Kelman (1984, 1986) demonstrated reduced severity of soft rot caused by

Pectobacterium carotovorum and improved storage quality of potatoes with increased

calcium concentration. Subsequent studies by Flego et al. (1997) demonstrated that an

increase in extracellular calcium concentration in the plant repressed pehA expression a pectic

enzyme-encoding gene by the pathogen. Another disease that has been studied in relation to

calcium is the common scab of potato. Studies of the correlation between tuber calcium and

the incidence of common scab have shown contradictory results. Whereas some of them have

indicated a positive correlation (Davis et al. 1974), others showed no correlation (Blodgett

and Cowan 1935, Lambert and Manzer 1991). The discrepancy in their results may be caused

by differences the type of calcium product applied and the time of application.

13

Approaches to identify quantitative trait loci (QTL)

Mapping quantitative trait loci (QTL) is a procedure that helps breeders to identify regions in

the chromosomes that are associated with simple and quantitative traits (Collard et al. 2005).

The identification of QTL allows breeders to detect regions associated with traits and in some

cases the identification of the actual genes that control traits. QTL mapping is usually

performed in diploid populations coming from F2 or recombinant inbred lines (Collard et al.

2005, Broman and Sen 2009). F2 populations also called intercross are generated by selfing

the F1 of two inbred lines so that all marker classes AA AB and BB will be found in the

population. Recombinant inbred lines (RIL) are generated by crossing two inbred strains

followed by repeated selfing or sibling mating to create a new inbred line whose genome is a

mosaic of the parental genomes (Broman and Sen 2009). Population size is an important

factor that affects QTL detection. A small population size can cause the over-estimation of

QTL effects and the loss of power to detect QTL (Xu 2003). Another important factor on

QTL detection is heritability; analytical methods locate QTL with poor precision (10–30 cM)

unless the heritability of an individual QTL is high (Kearsey and Farquhar 1998). The largest

benefit from the application of MAS would be observed for traits that exhibit low heritability

(Beavis 1998). Unfortunately, there is little power to identify markers linked to QTL or

accurately estimate their effects on traits with low heritability (Beavis 1994, 1998).

There are several methods to identify QTL in a linkage map; these methods can be classified

in single-QTL and multiple-QTL mapping methods. Interval mapping is the most popular

single-QTL mapping method that estimates the location of a QTL relative to its flanking

markers. A disadvantage of interval mapping is that QTL outside the interval under

consideration could lead to false positive or negative results (Rodriguez-Zas et al. 2002). An

approach that allows a more precise detection of QTL by accounting for the effects of

14

neighboring QTL is called composite interval mapping. Composite interval mapping (Zeng

1993, Jansen 1993) involves the use of interval mapping to locate a QTL between a pair of

markers and the use of multiple regression to estimate the effects of the QTL using a selected

set of markers as cofactors (Bernardo 2010). These cofactors, also called covariates, are a

predetermined number of markers that reduce the residual sum of squares of the multiple

regression models that best predict the phenotype (Broman and Sen 2009). The covariates are

searched outside a predetermined window size. The optimal window size depends on the

linkage disequilibrium of the mapping population so that the larger the number of breakpoints

the smaller the window size should be (Broman and Sen 2009). The advantages of using

composite interval mapping compared to interval mapping are an increase in the precision of

the detection by reducing the residuals detection of loci with modest effect and separation of

linked QTL (Zeng 1993, Jansen 1993). The use of near markers as covariates is a useful

exploratory strategy; however it turns a multidimensional search into a single dimensional

search that can overestimate the precision of the QTL detected. The choice of the number of

covariates used is a critical step in the process because too few or too many covariates can

cause a loss of power to detect QTL (Broman and Sen 2009). Currently there are several

methods that use a multiple QTL mapping approach such as multiple interval mapping (Kao

et al. 1999) and Bayesian QTL mapping (Ball 2001). Multiple QTL mapping can be

accomplished by using different model selection procedures from complete additivity to

multi-way interaction models. The models used to fit the QTL model include the Haley-Knott

regression extended Haley-Knott regression and multiple interval mapping; and different

model search approaches such as forward selection backward elimination and stepwise model

search (Broman and Sen 2009). Another approach is association mapping that uses an

association mapping panel that represents the historical recombination and natural genetic

15

diversity instead of the classical population structures used for interval mapping. Association

mapping enables researchers to use modern genomic technologies to exploit natural diversity

using genomic data (Zhu et al. 2008).

Mapping QTL in tetraploid potato populations

Since the first high density map of tomato and potato was constructed (Tanksley 1992) many

studies attempting to map QTL in potatoes have been published (Douches and Freyre 1994,

Menéndez et al. 2002, among others). Most of these studies involve diploid populations. The

densest diploid map is the RH-DH ultra-high density map constructed with 10000 AFLP

markers developed by van Os et al. (2006). This map has been used for example for high

resolution mapping of the H1 locus harboring resistance to the cyst nematode Globodera

(Bakker 2004). The methodology and software for tetraploid linkage maps have been

developed more slowly compared to diploid maps due to the complex inheritance in

tetraploid genomes (Hackett et al. 2007). New statistical approaches to deal with these

complex models of segregation and software that uses these approaches have been developed

in the last decade. Methodologies to perform interval mapping has been developed for

tetraploids (Hackett et al. 2001, Cao et al. 2005, Li et al. 2011) and implemented in

TetraploidMap (Hackett et al. 2007). This software was developed to deal with simple

sequence repeats (SSR) and amplified fragment length polymorphisms (AFLP) but can be

adapted to use with single nucleotide polymorphisms (SNP). Furthermore, the availability of

genome-wide genotyping tools such as the Illumina Infinium Bead Chip developed by the

SolCAP that evaluates simultaneously 8303 SNP (Hamilton et al. 2011) is allowing the

generation of high density maps. The advantages of using SNP markers for tetraploid

mapping are that polymorphisms can be detected ideally in every position of the genome and

16

the possibility to detect dosage. Recently a tetraploid map with 3839 mapped SNP markers

was constructed for the Stirling x 12601ab1 population (Hackett et al. 2013) which is the

densest tetraploid potato map to this date. Previous QTL maps in tetraploid populations

include those developed by Meyer et al. (1998) for late blight (Phytophtora infestans (Mont.)

de Bary), Simko et al. (2004) for Verticillium dahliae, Sagredo et al. (2009) for Colorado

potato beetle (Leptinotarsa decemlineata [Say]), Bradshaw et al. (2008) for yield agronomic

traits and quality traits and by McCord et al. (2011a, b) for agronomic traits and internal heat

necrosis. All these populations are generated by bi-parental crosses. Therefore the QTL

detected are mostly relevant to those particular populations. The association mapping

approach is much more powerful to detect genetic variants across natural populations.

However, it is complex in tetraploids because the genotyping system used should distinguish

among alleles and quantify the allele copy number. Association mapping using genomic data

is starting to become a reality for tetraploid potato. A study by Urbany et al. (2011) found

several markers associated with bruising and enzyme discoloration using SSR and markers

targeting candidate genes. Also a recent study by Uitdewilligen et al. (2013) demonstrated the

accuracy of genotyping-by sequencing (GBS) of a large collection of autotetraploid potato

cultivars using next-generation sequencing.

Marker assisted selection in potato

One of the applications of the knowledge generated by QTL mapping is the development of

markers for marker assisted selection (MAS). MAS in potato offers great opportunities to use

currently available genetic data (Barone 2004) but it has not been extensively exploited. Most

of the reports of markers for MAS in potato are related to pathogen resistance (Pineda et al.

1993, Hämäläinen et al. 1997, Oberhagemann et al. 1999, Colton et al. 2006, Gebhardt 2006,

17

Śliwka et al. 2010). Some cases are related to tuber quality (Freyre and Douches 1994, Li et

al. 2013). Lopez-Pardo et al. (2013) reported the successful application of MAS to select for

resistance to PVY and Globodera pallida. Li et al. (2013) indicate that their MAS

experiments to select for tuber quality were only partially successful probably due to GxE

affecting marker-trait associations. Only the Pain1-8c marker showed a consistent positive

effect on chip quality in two years of evaluation. These studies suggest that there are some

benefits that can be expected from the application of MAS in potato but these markers have

to be tested in several environments and genetic backgrounds. The cost-effectiveness of the

large scale application of these markers for MAS has been discussed recently by Slater et al.

(2013). This study determined that MAS could be applied cost-effectively in the second

clonal generation for all models currently employed in potato breeding.

The advance in QTL mapping analysis genotyping methods and the availability of the potato

genome sequence promise to generate accelerated progress on potato breeding and genetics in

the coming years.

RESEARCH OBJECTIVES

The objectives of the research presented in this thesis include: (a) the generation of reciprocal

tetraploid populations that segregate for tuber calcium, yield, specific gravity, internal

defects, chip quality, and tolerance to common scab; (b) the evaluation of the genetic

correlation between tuber calcium and internal tuber defects, tuber calcium and chip quality

traits and tuber calcium and common scab; (c) the identification of promising clones with

good chipping quality, at least as good as Atlantic, that have improved internal tuber quality

18

compared to Atlantic (select for an Atlantic replacement); (d) the identification of QTL

regions that control tuber calcium, yield, specific gravity, internal quality, chip quality and

pitted scab as well as markers that could potentially be used for marker assisted selection; (e)

the investigatation of the role of CAX1, a vacuolar Ca+2 antiporter, in tuber calcium uptake,

plant health and tuber quality.

BIBLIOGRAPHY

Arora, R. and J.P. Palta. 1988. In vivo perturbation of membrane-associated calcium by freeze-thaw stress in onion bulb cells: Simulation of this perturbation in extracellular KCl and alleviation by calcium. Plant Physiology 87: 622-628. Arteca, R.N., B.W. Poovaiah, and L.K. Hiller. 1980. Electron microprobe and neutron activation analysis for the determination of elemental distribution in hollow heart potato tubers. American Journal of Potato Research 57:241-247. Baker, D.A. and J. Moorby. 1969. The transport of sugar, water, and ions into developing potato tubers. Annals of Botany 33: 729-741. Bakker, E., U. Achenbach, J. Bakker, J. van Vliet, J. Peleman, B. Segers, S. van der Heijden, P. van der Linde, R. Graveland, R. Hutten, H. van Eck, E. Copoolse, E. van der Voosen, J. Bakker and A. Goverse. 2004. A high-resolution map of the H1 locus harbouring resistance to the potato cyst nematode Globodera rostochiensis. Theoretical and Applied Genetics 109: 146-152. Ball, R.D. 2001. Bayesian methods for quantitative trait loci mapping based on model selection: Approximate analysis using the Bayesian information criterion. Genetics 59: 1351–1364. Bamberg, J.B., J.E. Palta, L.A. Peterson, M. Martin, and A.R. Krueger. 1993. Screening tuber-bearing Solanum (potato) germplasm for efficient accumulation of tuber calcium. American Journal of Potato Research 70: 219-226. Bangerth, F. 1979. Calcium-related physiological disorders of plants. Annual Review of Phytopathology 17: 97-122. Baritelle, A., G. Hyde, R. Thornton, and R. Bajema. 2000. A classification system for impact-related defects in potato tubers. American Journal of Potato Research 77: 143-148.

19

Baritelle, A.L. and G.M. Hyde. 2003. Specific gravity and cultivar effects on potato tuber impact sensitivity. Postharvest Biology and Technology 29: 279-286. Barone, A. 2004. Molecular marker-assisted selection for potato breeding. American Journal of Potato Research 81: 111-117. Bassett, P.A. 1980. The effect of soil salinity and calcium levels on the growth of Bromus mollis in the Camargue, France. Oikos: 353-358. Beavis, W.D. 1994. The power and deceit of QTL experiments: lessons from comparative QTL studies. In Proceedings of the Forty-Ninth Annual Corn and Sorghum Industry Research Conference, 250-266. Washington, DC: American Seed Trade Assoc. Beavis, W.D. 1998. QTL analyses: power, precision, and accuracy in molecular dissection of complex traits, ed A.H. Paterson, 145-162. Boca Raton, FL: CRC. Bernardo, R. 2010. Breeding for quantitative traits in plants. Second Edition. Minnnesota, USA: Stemma Press. Bjor, T., and L. Roer, 1980. Testing the resistance of potato varieties to common scab. Potato Research 23: 33-47. Blodgett, F.M. and E.K. Cowan. 1935. Relative effects of calcium and acidity of the soil on the occurrence of potato scab. American Potato Journal 12: 265-274. Boudsocq, M., and J. Sheen. 2010. Stress signaling II: calcium sensing and signaling. In Abiotic Stress Adaptation in Plants, 75-90. Springer Netherlands. Bradshaw, J.E., C.A. Hackett, B. Pande, R. Waugh, and G.J. Bryan. 2008. QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Theoretical and Applied Genetics 116: 193–211. Broman, K.W., and S. Sen. 2009. A Guide to QTL mapping with R/qtl. New York: Springer. Bush, D.S. 1995. Calcium regulation in plant cells and its role in signaling. Annual review of plant biology 46: 95-122. Cao, D., B.A. Craig and R.W. Doerge. 2005. A model selection-based interval-mapping method for autopolyploids. Genetics 169: 2371-2382. Cheng, N.H., J.K. Pittman, T. Shigaki and K.D. Hirschi. 2002. Characterization of CAX4, an Arabidopsis H+/cation antiporter. Plant Physiology 128: 1245-1254. Cholewa, E., and C.A. Peterson, 2004. Evidence for symplastic involvement in the radial movement of calcium in onion roots. Plant Physiology 134: 1793-1802. Clough, G.H. 1994. Potato tuber yield, mineral concentration, and quality after calcium fertilization. Journal of the American Society of Horticultural Science 119: 175-179.

20

Coffin R, MK Keenan, R Yada, G Tai, M Slavnik, and G Johnston. 1988. Inheritance of genetic factors controlling chip processing quality after tuber storage at low temperatures [Abstract]. American Journal of Potato Research 65:474. Collard, B.C.Y., M.Z.Z. Jahufer, J.B. Brouwer and E.C.K. Pang. 2005. An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts. Euphytica 142: 169-196. Collier, G.F., D.C.E. Wurr, and V.C. Huntington. 1980. The susceptibility of potato varieties to internal rust spot in the potato. Journal of Agricultural Science Cambridge 94: 407-410. Colton, L. M., H.I. Groza, S.M. Wielgus and J. Jiang. 2006. Marker-assisted selection for the broad-spectrum potato late blight resistance conferred by gene Rb derived from a wild potato species. Crop Sciences 46: 589-594. Conn, S., and M. Gilliham. 2010. Comparative physiology of elemental distributions in plants. Annals of Botany 105: 1081-1102. Corbett, E.F., and M. Michalak. 2000. Calcium, a signaling molecule in the endoplasmic reticulum?. Trends in Biochemical Sciences 25: 307-311. Cosgrove, D. 2005. Growth of the plant cell wall. Nature Reviews 6: 850-861. Cramer, G.R. 2004. Sodium-calcium interactions under salinity stress. In Salinity: environment-plants-molecules, eds. A. Läucli and U. Luttge, 205-227. Netherlands: Springer. Chéour, F., J. Arul, J. Makhlouf, and C. Willemot. 1992. Delay of membrane lipid degradation by calcium treatment during cabbage leaf senescence. Plant Physiology 100: 1656-1660. Christensen, A., K. Svensson, S. Persson, M. Michalak, J. Jung, M. Michalak, S. Widell, and M. Sommarin. 2008. Functional characterization of Arabidopsis Calreticulin1a; a key alleviator of endoplasmic reticulum stress. Plant Cell Physiol 49: 912-924.

Christensen, A., K.Svensson, L.Thelin, W. Zhang, N. Tintor , D. Prins and S. Persson. 2010. Higher plant calreticulins have acquired specialized functions in Arabidopsis. PLoS One 5: e11342. D’Hoop, B.B., M.J. Paulo, K. Kowitwanich, M. Sengers, R.G. Visser, H.J. van Eck, and F.A. van Eeuwijk. 2010. Population structure and linkage disequilibrium unravelled in tetraploid potato. Theoretical and Applied Genetics 121: 1151-1170. Danehy, J.P. 1986. Maillard reactions: nonenzymatic browning in food systems with special reference to the development of flavor. In: Advances in food research 30, ed. C.O. Chichester, 77-138. Florida: Academic Press Inc.

21

Davis, J.R., G.M. McMaster, R.H. Callihan, J.G. Garner, and R.E. McDole. 1974. The relationship of irrigation timing and soil treatments to control potato scab. Phytopathology 64: 1404-1410. De la Puente, F. and S.J. Peloquin. 1968. Male fertility of selected 24 chromosome S. tuberosum hybrids. American Journal of Potato Research 45:436-437. Demarty, M., C. Morvan, and M. Thellier. 1984. Calcium and the cell wall. Plant, Cell & Environment 7: 441-448. Denecke, J., L.E. Carlsson, S.Vidal, A.S. Hoglund, B. Ek, M.J. van Zeijl, K.M. Sinjorgo, and E.T. Palva. 1995. The tobacco homolog of mammalian calreticulin is present in protein complexes in vivo. Plant Cell 7: 391-406. Douches, D.S., and R. Freyre. 1994. Identification of genetic factors influencing chip color in diploid potato (Solanum spp.). American Potato Journal 71: 581-590. Elbatawi, I.E. 2008. An acoustic impact method to detect hollow heart of potato tubers. Biosystems Engineering 100: 206-213. Ehlenfeldt M.K., D.F. Lopez-Portilla, A.A. Boe, and R.H. Johansen. 1990. Reducing sugar accumulation in progeny families of cold chipping potato clones. American Journal of Potato Research 67: 83-91. Epstein, E. 1972. Mineral nutrition of plants. Principles and Perspectives. New York: John Wiley and Sons. Faucher, E., E. Paradis, C. Goyer, N.C. Hodge, R. Hogue, R.E. Stall and C. Beaulieu. 1995. Characterization of Streptomycetes causing deep-pitted scab of potato in Quebec, Canada. International Journal of Systematic Bacteriology 45: 222-225. Ferguson, I.B., C.B. Watkins, and J.E. Harman. 1983. Inhibition by calcium of senescence of detached cucumber cotyledons effect on ethylene and hydroperoxide production. Plant Physiology 71: 182-186. Finka, A., A.F.H. Cuendet, F.J. Maathuis, Y. Saidi, and P. Goloubinoff. 2012. Plasma membrane cyclic nucleotide gated calcium channels control land plant thermal sensing and acquired thermotolerance. The Plant Cell Online 24: 3333-3348. Finney, E.E. and K.H. Norris. 1978. X-ray scans for detecting hollow heart in potatoes. American Potato Journal 55: 95-105. Flego, D., M. Pirhonen, H. Saarilahti, T.K. Palva, and E.T. Palva. 1997. Control of virulence gene expression by plant calcium in the phytopathogen Erwinia carotovora. Molecular Microbiology 25: 831-838. de Freitas, S.T., M. Padda, Q. Wu, S. Park, and E.J. Mitcham. 2011. Dynamic alternations in cellular and molecular components during blossom-end rot development in tomatoes

22

expressing sCAX1, a constitutively active Ca2+/H+ antiporter from Arabidopsis. Plant

Physiology 156: 844-855. Freyre, R., and D.S Douches.1994. Development of a model for marker-assisted selection of specific gravity in diploid potato across environments. Crop Science 34: 1361-1368. Fricke, W., R.A. Leigh, and A.D. Tomos. 1994. Concentrations of inorganic and organic solutes in extracts from individual epidermal, mesophyll and bundle-sheath cells of barley leaves. Planta 192: 310-316. Friedman, M. 1997. Chemistry, biochemistry, and dietary role of potato polyphenols. A review. Journal of Agricultural and Food Chemistry 45: 1523-1540. Gebhardt, C., D. Bellin, H. Henselewski, W. Lehmann, J. Schwarzfischer, and J. P.T. Valkonen. 2006. Marker-assisted combination of major genes for pathogen resistance in potato. Theoretical and Applied Genetics 112: 1458–1464. Gelebart, P., M. Opas M. Michalak. 2005. Calreticulin, a Ca2+-binding chaperone of the endoplasmic reticulum. International Journal of Biochemistry and Cell Biology 37: 260-266. Gilroy, S., P.C. Bethke and R.L. Jones. 1993. Calcium homeostasis in plants. Journal of Cell Science 106: 453-461. Gilliham, M., M. Dayod, B.J. Hocking, B. Xu, S.J. Conn, B.N. Kaiser, and S.D. Tyerman. 2011. Calcium delivery and storage in plant leaves: Exploring the link with water flow. Journal of Experimental Botany 62: 2233-2250. Gong, M., A.H. van der Luit, M.R. Knight, and A.J. Trewavas. 1998. Heat-shock-induced changes in intracellular Ca2+ level in tobacco seedlings in relation to thermotolerance. Plant Physiology 116: 429-437. Goto, K. 1981. The relationship between common scab severity and reducing sugar contents in the peel of potato tubers. Potato Research 24: 171-176. Goth, R W, Haynes K G, Wilson D R. 1993. Evaluation and characterization of advanced potato breeding clones for resistance to scab by cluster analysis. Plant Disease 77: 911-914. Hackett, C.A., J.E. Bradshaw, and J.W. McNicol, 2001. Interval mapping of QTLs in autotetraploid species. Genetics 159: 1819-1832. Hackett, C.A., I. Milne, J.E. Bradshaw, and Z. Luo. 2007. TetraploidMap for Windows: linkage map construction and QTL mapping in autotetraploid species. Journal of Heredity 98: 727-729 Hackett, C. A., K. McLean and G.J. Bryan. 2013. Linkage analysis and QTL mapping using SNP dosage data in a tetraploid potato mapping population. PloS One 8: e63939. Hämäläinen, J. H, K.N. Watanabe, J.P.T. Valkonen, A. Arihara, R.L. Plaisted, E. Pehu, L.

23

Miller, and S.A. Slack. 1997. Mapping and marker-assisted selection for a gene for extreme resistance to potato virus Y. Theoretical and Applied Genetics 94: 192–197. Hamilton, J.P., C. N. Hansey, B. R. Whitty, K. Stoffel, A. N. Massa, A. Van Deynze, W.S. De Jong, D.S. Douches, and C.R. Buell. 2011. Single nucleotide polymorphism discovery in elite North American potato germplasm. BMC Genomics 12: 302-312 Hanson, J.B. 1960. Impairment of respiration ion accumulation and ion retention in root tissue treated with ribonuclease and ethylenediamine tetraacetic acid. Plant Physiology 35: 372–379. Harrison, M.D. 1962. Potato russet scab, its cause and factors affecting its development. American Journal of Potato Research 39: 368-387. Harper, J.F., G. Breton, and A. Harmon. 2004. Decoding Ca2+ signals through plant protein kinases. Annual Review of Plant Biology 55: 263-288. Haynes, K.G., L.A. Wanner, C.A. Thill, J.M. Bradeen, J. Miller, R.G. Novy, L. Jonathan, D. Whitworth, L. Corsini, and B.T. Vinyard. 2010. Common scab trials of potato varieties and advanced selections at three US locations. American Journal of Potato Research 87: 261-276. Henninger, M.R., S.B. Sterret and K.G. Haynes. 2000. Broad-sense heritability and stability of internal heat necrosis and specific gravity in tetraploid potatoes. Crop Science 40: 977–984. Hepler, P.K. 2005. Calcium: A central regulator of plant growth and development. The Plant Cell 17: 2142-2155. Hirschi, K.D., R.G. Zhen, K.W. Cunningham, P.A. Rea, and G.R. Fink. 1996. CAX1, an H+/Ca2+ antiporter from Arabidopsis. Proceedings of the National Academy of Sciences 93: 8782-8786. Hirschi, K.D., V.D. Korenkov, N.L. Wilganowski, and G.J. Wagner. 2000. Expression of Arabidopsis CAX2 in tobacco. Altered metal accumulation and increased manganese tolerance. Plant Physiology 124: 125-134. Hirschi, K.D. 2004. The calcium conundrum. Both versatile nutrient and specific signal. Plant Physiology 136: 2438-2442. Hughes, J.C. 1980. Potatoes I: Factors affecting susceptibility of tubers to damage. Span 23:65-75. Hutchinson, C.M., J.M. White, D.M. Gergela, P.A. Solano, K.G. Haynes, R. Wenrich, and C.S. Lippi. 2003. Performance of chip processing potato varieties in northeastern Florida. HortTechnology 13: 706-711.

24

Hyde, R. B., and J.W. Morrison. 1964. The effect of storage temperature on reducing sugars, pH, and phosphorylase enzyme activity in potato tubers. American Journal of Potato Research 41: 163-168. Jakuczun, H. and E. Zimnoch-Guzowska. 2004. Inheritance of glucose content in tubers of diploid potato families. American Journal of Potato Research 81: 359-370. Jansen, R.C. 1993. Interval mapping of multiple quantitative trait loci. Genetics 135: 205-211. Jia, X.Y., C.Y. Xu, R.L. Jing, R.Z. Li, X.G. Mao, J.P. Wang and X.P. Chang. 2008. Molecular cloning and characterization of wheat calreticulin (CRT) gene involved in drought-stressed responses. Journal of Experimental Botany 59: 739-751. Jia, X.Y., L. H. He, R.L. Jing, and R.Z. Li. 2009. Calreticulin: conserved protein and diverse functions in plants. Physiologia Plantarum 136: 127-138. Jiang, J.F., J.G. Li, and Y.H Dong. 2013. Effect of calcium nutrition on resistance of tomato against bacterial wilt induced by Ralstonia solanacearum. European Journal of Plant Pathology 136: 547-555. Johnson, S., M. Michalak, M. Opas, P. Eggleton. 2001. The ins and outs of calreticulin: from the ER lumen to the extracellular space. Trends Cell Biol 11: 122-129. Kao C.H., Z.B Zeng, and R.D. Teasdale. 1999. Multiple interval mapping for quantitative trait loci. Genetics 152: 1203-1216. Karley, A.J., R.A. Leigh, and D. Sanders. 2000. Where do all the ions go? The cellular basis of differential ion accumulation in leaf cells. Trends in Plant Science 5: 465-470. Karlsson B.H., J.P. Palta, and P.M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. Hort Science 41: 1213-1221. Kleinhenz, M.D., J.P. Palta, C.C. Gunter, and K.A. Kelling. 1999. Impact of source and timing of calcium and nitrogen applications onatlantic'potato tuber calcium concentrations and internal quality. Journal of the American Society for Horticultural Science 124: 498-506. Kleinhenz, M.D. and J.P. Palta. 2002. Root calcium modulates the response of potato plants to heat stress. Physiologia Plantarum 115: 111-118. Kearsey, M.J. and A.G.L. Farquhar. 1998. QTL analysis in plants; where are we now?. Heredity 80: 137-142. Keijbets, M.J.H. 2008. Potato processing for the consumer: Developments and future challenges. Potato Research 51: 271-281. Kirkby, E.A., and D.J. Pilbeam. 1984. Calcium as a plant nutrient. Plant, Cell & Environment 7: 397-405.

25

Knight, H., A.J. Trewavas, and M.R. Knight. 1996. Cold calcium signaling in Arabidopsis involves two cellular pools and a change in calcium signature after acclimation. The Plant Cell Online 8: 489-503. Kratzke, M.G. and Palta, J.P. 1986. Calcium accumulation in potato tubers: Role of the basal roots. HortScience 21: 1022-1024.

Lampitt, L.H., and N. Goldenberg. 1940. The potato as food. Chemistry & Industry 1940: 748–761.

Lærke, P.E., J. Christiansen, M.N. Andersen, and B. Veierskov. 2002. Blackspots bruise susceptibility of potato tubers during tuber growth and storage determined by two different test methods. Journal of the Science of Food and Agriculture 80: 1332-1338. Lambert, D. H., and F. E. Manzer.1991. Relationship of calcium to potato scab. Phytopathology, 81: 632-636. Larkindale, J., and M.R Knight. 2002. Protection against heat stress-induced oxidative damage in Arabidopsis involves calcium abscisic acid ethylene and salicylic acid. Plant Physiology 128: 682-695. Lauer, F. and R. Shaw. 1970. A possible genetic source for chipping potatoes from 40 F storage. American Journal of Potato Research 47: 275-278. Legge, R.L., J.E. Thompson, J.E. Baker, and M. Lieberman. 1982. The effect of calcium on the fluidity and phase properties of microsomal membranes isolated from postclimacteric Golden Delicious apples. Plant and Cell Physiology 23: 161-169. Levitt, J. 1942. A historical study of hollow heart potatoes. American Journal of Potato Research 19: 134-143. Li, J., K. Das, G. Fu, C.Tong, Y. Li, C. Tobias and R. Wu. 2011. EM algorithm for mapping quantitative trait Loci in multivalent tetraploids. International Journal of Plant Genomics. Article ID 216547. doi:10.1155/2010/216547. Li, L.,E. Tacke, H.R. Hofferbert, J. Lübeck, J. Strahwald, A.M. Draffehn, B. Walkemeier, and C. Gebhardt. 2013. Validation of candidate gene markers for marker-assisted selection of potato cultivars with improved tuber quality. Theoretical and Applied Genetics 126: 1039-1052. Liu, J.X., and S.H. Howell. 2010. Endoplasmic reticulum protein quality control and its relationship to environmental stress responses in plants. The Plant Cell Online 22: 2930-2942. Liu, H.T., D.Y. Sun, and R.G. Zhou. 2005. Ca2+ and AtCaM3 are involved in the expression of heat shock protein gene in Arabidopsis. Plant, Cell & Environment 28: 1276-1284.

26

Lopez-Pardo, R., L. Barandalla, E. Ritter and J.I. Ruiz de Galarreta. 2013. Validation of molecular markers for pathogen resistance in potato. Plant Breeding 132: 246-251. Loria, R., R.A. Bukhalid, B.A. Fry, and R.R. King. 1997. Plant pathogenicity in the genus Streptomyces. Plant Disease 81: 836-846 Loria, R. 2001. Diseases caused by bacteria: Common scab. In Compendium of potato diseases ed. W.R. Stevenson R. Loria G.D. Franc and D.P. Weingartner 14–15. St. Paul: American Phytological Society. Love, S.L., J.J. Pavek, A. Thompson-Johns, and W. Bohl. 1998. Breeding progress for potato chip qQuality in North American cultivars. American Journal of Potato Research 75: 27–36. Lucier, G. and R. Dettmann. 2007. Vegetables and Melons Outlook. United States Department of Agriculture. Economic Research Service, VGS, 320, 49. Lynch, J., G.R. Cramer, and A. Läuchli. 1987. Salinity reduces membrane-associated calcium in corn root protoplasts. Plant Physiology 83: 390-394. Ma, Y., and G.A. Berkowitz. 2012. Biotic Stress Signalling: Calcium-Mediated Pathogen Defence Programmes. In: Plant Stress Physiology. Sergey Shabala Ed. Cambridge USA.CAB International. 291. Makower, R.U. 1964. Effect of Nucleotides on Enzymic Browning in Potato Slices. Effect of Nucleotides on Enzymic Browning in Potato Slices. Plant Physiology 39: 956-959. Manohar, M., T. Shigaki, and K.D. Hirschi. 2011. Plant cation/H+ exchangers (CAXs): biological functions and genetic manipulations. Plant Biology 13: 561-569. Manaa, A., M. Faurobert, B. Valot, J.P. Bouchet, D. Grasselly, M. Causse, and H.B Ahmed. 2013. Effect of salinity and calcium on tomato fruit proteome. Omics: A Journal of Integrative Biology 17: 338-352. Marinos, N.G. 1962. Studies on submicroscopic aspects of mineral deficiencies. I. Calcium deficiency in the shoot apex of barley. American Journal of Botany 49: 834-841. Massa, A.N., K.L. Childs, H. Lin, G.J. Bryan, G. Giuliano, and C.R. Buell. 2011. The transcriptome of the reference potato genome Solanum tuberosum Group Phureja clone DM1-3 516R44. PLoS One 6(10): e26801. Matheis, G. 1983. Enzymatic browning of foods. Zeitschrift für Lebensmittel-Untersuchung und Forschung 176: 454-462. Matheis, G. 1987. Polyphenol oxidase and enzymatic browning of potatoes (Solanum tuberosum). II. Enzymatic browning and potato constituents. Chemie Mikrobiologie Technologie der Lebensmittel 11: 67-70.

27

McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011a. Linkage mapping and QTL analysis of agronomic traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Crop Science 51: 771-785. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011b. QTL mapping of internal heat necrosis in tetraploid potato. Theoretical and Applied Genetics 122: 129–142. McGuire, R.G., and A. Kelman. 1984. Reduced severity of Erwinia soft rot in potato tubers with increased calcium content. Phytopathology 74: 1250-1256. McGuire, R. and A. Kelman. 1986. Calcium in potato tuber cell walls in relation to tissue maceration by Erwinia carotovora pv. atroseptica. Physiology and Biochemistry 7: 401-406. McKee, R.K. 1958. Assessment of the resistance of potato varieties to common scab. Potato Research 1: 65-80. Menéndez, C.M., E. Ritter, R. Schäfer-Pregl, B. Walkemeier, A. Kalde, F. Salamini, and C. Gebhardt. 2002. Cold sweetening in diploid potato: Mapping quantitative trait loci and candidate genes. Genetics 162: 1423-1434. Meyer, R.C., D. Milbourne, C.A. Hackett, J.E. Bradshaw, J.W. McNichol, and R. Waugh. 1988. Linkage analysis in tetraploid potato and association of markers with quantitative resistance to late blight (Phytophthora infestans). Molecular and General Genetics 259: 150-160. Mishra, K. K. and J.S. Srivastava. 2001. Screening potato cultivars for common scab of potato in a naturally infested field. Potato Research 44: 19-24. Mittler, R., A. Finka, and P. Goloubinoff. 2012. How do plants feel the heat?. Trends in Biochemical Sciences 37: 118-125. Minorsky, P.V. 1985. A heuristic hypothesis of chilling injury in plants: A role for calcium as the primary physiological transducer of injury. Plant Cell & Environment 8: 75-94. Monroy, A.F., and R.S. Dhindsa. 1995. Low-temperature signal transduction: induction of cold acclimation-specific genes of alfalfa by calcium at 25 degrees C. The Plant Cell Online 7: 321-331. Morris, J., K.M. Hawthorne, T. Hotze, S.A. Abrams, and K.D. Hirschi. 2008. Nutritional impact of elevated calcium transport activity in carrots. Proceedings of the National Academy of Sciences 105: 1431-1435. Narsai, R., C. Wang, J. Chen, J. Wu, H. Shou, and J. Whelan. 2013. Antagonistic, overlapping and distinct responses to biotic stress in rice (Oryza sativa) and interactions with abiotic stress. BMC genomics 14: 93. doi:10.1186/1471-2164-14-93.

28

Oberhagemann, P., C. Chatot-Balandras, R. Schäfer-Pregl, D. Wegener, C. Palomino, F. Salamini, and C. Gebhardt. 1999. A genetic analysis of quantitative resistance to late blight in potato: Towards marker-assisted selection. Molecular Breeding 5: 399-415. Olsen N.L., L.K. Hiller, and L.J. Mikitzel. 1996. The dependence of internal brown spot development upon calcium fertility in potato tubers. Potato Research 39: 165-178. Oparka, K.J., and H.V. Davies. 1988. Subcellular localisation of calcium in potato tubers. Potato Research 31: 297-304. Opas, M., M. Szewczenko-Pawlikowski, G.K. Jass, N. Mesaeli, and M. Michalak. 1996. Calreticulin modulates cell adhesiveness via regulation of vinculin expression. Journal of Cell Biology 135: 1913-1923. van Os, H., S. Andrzejewski, E. Bakker, I. Barrena, G.J. Bryan, B. Caromel and van H.J. Eck. 2006. Construction of a 10,000-marker ultradense genetic recombination map of potato: providing a framework for accelerated gene isolation and a genomewide physical map. Genetics 173: 1075-1087. Ozgen S., B.H. Karlsson, and J.P. Palta. 2006. Response of potatoes (cv. ‘Russet Burbank’) to supplemental calcium applications under field conditions. Tuber calcium yield and incidence of brown spot. Journal American Potato Research 83: 195-204. Palta, J.P. 1996. Role of calcium in plant responses to stresses: Linking basic research to the solution of practical problems. HortScience 31: 51-57. Palta, J.P. 2013. Merging physiological and genetic approaches to improve abiotic stress resistance. In Combating climate change: An agricultural perspective, eds. M.S. Kang and S.S. Banga, 237-270. Boca Raton, US: CRC Press. Park S., T. Kang, C. Kim, J. Han, S. Kim, R.H. Smith, L.M. Pike, and K.D. Hirschi. 2005a. Genetic manipulation for enhancing calcium content in potato tuber. Journal of Agricultural and Food Chemistry 53: 5598-5603. Park S., N.H. Cheng, J.K. Pittman, K.S. Yoo, J. Park, R.H. Smith, and K.D. Hirschi. 2005b. Increased calcium levels and prolonged shelf life in tomatoes expressing Arabidopsis H/Ca2 transporters. Journal of Agricultural and Food Chemistry 139: 1194-1206. Pereira, A.D.S., R.H. Coffin, R.Y. Yada and V.S. Machado. 1993. Inheritance patterns of reducing sugars in potato tubers after storage at 12C and 4C followed by reconditioning. American Potato Journal 70: 71-76. Pineda, O., M.W. Bonierbale, R.L. Plaisted, B.B. Brodie and S.D. Tanksley. 1993. Identification of RFLP markers linked to the H1 gene conferring resistance to the potato cyst nematode Globodera rostochiensis. Genome 36: 152-156.

29

Piotrowska, G. 1998. The role of calcium ions in freezing injuries of winter oilseed rape leaves. Effects of calcium channel blockers and mimesis by calcium ionophore. Acta Physiologiae Plantarum 20: 257-261. Poovaiah, B.W. 1979. Role of calcium in ripening and senescence. Communications in Soil Science and Plant Analysis 10: 83-88. Poovaiah, B.W. and A.C. Leopold. 1973. Deferral of leaf senescence with calcium. Plant Physiology 52: 236-239. Potato Genome Sequencing Consortium. 2011. Genome sequence and analysis of the tuber crop potato. Nature 475: 189-195. Preston, R.D. 1979. Polysaccharide formation and cell wall function. Annual Review of Plant Biology. 30: 55-78. Qiu, Y., and M. Michalak. 2009. Transcriptional control of the calreticulin gene in health and disease. International Journal of Biochemistry & Cell Biology 41: 531-538. Reddy, V.S., and A.S.N. Reddy. 2004. Proteomics of calcium-signaling components in plants. Phytochemistry 65: 1745-1776. Rex, B.L. and G. Massa. 1989. Cause, control and detection of hollow heart in potatoes: A review. American Journal of Potato Research 66: 165-183. Rodriguez-Saona, L.E. and R. Wrostald. 1997. Influence of potato composition on chip color quality. American Journal of Potato Research 74: 87-106. Rodriguez-Zas, S. L., B.R. Southey, D.W. Heyen and H.A. Lewin. 2002. Interval and composite interval mapping of somatic cell score, yield, and components of milk in dairy cattle. Journal of Dairy Science 85: 3081-3091. Sagredo, B., N. Balbyshev, A. Lafta, H. Casper, and J. Lorenzen. 2009. A QTL that confers resistance to Colorado potato beetle (Leptinotarsa decemlineata [Say]) in tetraploid potato populations segregating for leptine. Theoretical and Applied Genetics 119: 1171-1181. Saidi, Y., A. Finka, M. Muriset, Z. Bromberg, Y.G. Weiss, F.J. Maathuis, and P. Goloubinoff. 2009. The heat shock response in moss plants is regulated by specific calcium-permeable channels in the plasma membrane. The Plant Cell Online 21: 2829-2843. Saidi, Y., A. Finka, and P. Goloubinoff. 2011. Heat perception and signalling in plants: A tortuous path to thermotolerance. New Phytologist 190: 556-565. Sairam, R.K. B. Vasanthan, and A. Arora. 2011. Calcium regulates Gladiolus flower senescence by influencing antioxidative enzymes activity. Acta Physiologiae Plantarum 33: 1897-1904.

30

Sanford, J.C., and R.E. Hanneman,. 1979. Reciprocal differences in the photoperiod reaction of hybrid populations inSolanum tuberosum. American Potato Journal 56: 531-540. Sanford, J.C. and R.E. Hanneman Jr. 1982. Large yield differences between reciprocal families of Solanum tuberosum. Euphytica 31: 1-12. Simko, I, S. Costanzo, K.G. Haynes, B.J. Christ, R.W. Jones. 2004. Linkage disequilibrium mapping of a Verticillium dahliae resistance quantitative trait locus in tetraploid potato (Solanum tuberosum) through a candidate gene approach. Theoretical and Applied Genetics 108: 217–224. Slater, A.T., N.O. Cogan, and J.W. Forster. 2013. Cost analysis of the application of marker-assisted selection in potato breeding. Molecular Breeding 1: 12 Śliwka, J., H. Jakuczun, P. Kamiński, and E. Zimnoch-Guzowska. 2010. Marker-assisted selection of diploid and tetraploid potatoes carryingRpi-phu1, a major gene for resistance to Phytophthora infestans. Journal of Applied Genetics 51: 133-140. Scholte, K., and R.E. Labruybre. 1985. Netted scab: a new name for an old disease in Europe. Potato Research 28: 443-448. Sterrett, S.B. and M.R. Henninger. 1991. Influence of calcium on internal heat necrosis of Atlantic potato. American Potato Journal 68: 467-477. Sterrett, S. B. and M.R. Henninger, 1997. Internal heat necrosis in the Midatlantic region: Influence of environment and cultural management. American Journal of Potato Research 74: 233-243. Tanksley, S.D., M.W. Ganal, J.P. Prince, M.C. De Vicente, M.W. Bonierbale, P. Broun and G.B. Martin. 1992. High density molecular linkage maps of the tomato and potato genomes. Genetics 132: 1141-1160. Tawfik, A.A., M.D. Kleinhenz, and J.P. Palta. 1996. Application of calcium and nitrogen for mitigating heat stress effects on potatoes. American Journal of Potato Research 73: 261-273. Tucker, R.E.. 2013. A potato glossary. Tucker Farms Inc. Published on 6/26/13. http://www.tuckertaters.com/potato-glossary.pdf Tzeng, K.C., A. Kelman, K.E. Simmons, and K.A. Kelling. 1986. Relationship of calcium nutrition to internal brown spot of potato tubers and sub-apical necrosis of sprouts. American Journal of Potato Research 63: 87-97. Urbany, C., B. Stich, L. Schmidt, L. Simon, H. Berding, H. Junghans, K-H. Niehoff, A. Braun, E Tacke, H-R. Hofferbert, J. Lübeck, J. Strahwald, and C. Gebhardt. 2011. Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration. BMC Genomics 12: 7.

31

Uitdewilligen, J.G., A.M.A. Wolters, B. Bjorn, T.J. Borm, R.G. Visser, and H.J. van Eck. 2013. A next-generation sequencing method for genotyping-by-sequencing of highly heterozygous autotetraploid potato. PloS ONE 8: e62355. Wang, C.Y. 1993. Approaches to reduce chilling injury of fruits and vegetables. Hort. Rev 15: 63-95. Waterhouse, N.J., and M.J. Pinkoski. 2007. Calreticulin: raising awareness of apoptosis. Apoptosis 12: 631-634. Webb, R.E., D.R. Wilson, J.R. Shumaker, B. Graves, M.R. Henninger, J. Watts, J.A. Frank, and H.J. Murphy. 1978. Atlantic: A new potato variety with high solids, good processing quality and resistance to pests. American Journal of Potato Research 55: 141-145. Williams, D.B. 2006. Beyond lectins: the calnexin/calreticulin chaperone system of the endoplasmic reticulum. Journal of Cell Science 119: 615–623. Wu, H.C., and T.L. Jinn. 2010. Heat shock-triggered Ca2+ mobilization accompanied by pectin methylesterase activity and cytosolic Ca2+ oscillation are crucial for plant thermotolerance. Plant Signaling & Behavior 5: 1252-1256. Wu, Q., T. Shigaki, J.S. Han, C.K. Kim, K.D. Hirschi, and S. Park. 2012. Ectopic expression of a maize calreticulin mitigates calcium deficiency-like disorders in sCAX1-expressing tobacco and tomato. Plant Molecular Biology 80: 609-619. Wyatt, S.E., P.L. Tsou and D. Robertson. 2002. Expression of the high capacity calcium-binding domain of calreticulin increases bioavailable calcium stores in plants. Transgenic Research 11: 1-10. Xu S. 2003. Estimating polygenic effects using markers of the entire genome. Genetics 163: 789−801. Yamazaki, H., and T. Hoshina. 1995 . Calcium nutrition affects resistance of tomato seedlings to bacterial wilt. HortScience 30: 91-93. Yang, T., H. Peng, B.D. Whitaker, W.M. and Jurick. 2013. Differential expression of calcium/calmodulin-regulated SlSRs in response to abiotic and biotic stresses in tomato fruit. Physiologia Plantarum 148: 445–455. Yencho, G.C., P.H. McCord, K.G. Haynes and S.R.Sterrett. 2008. Internal heat necrosis of potato: A review. American Journal of Potato Research 85: 69-76. Zeng, Z-B. 1993. Theoretical basis for separation of multiple linked gene effects in mapping of quantitative trait loci. Proceedings of the National Academy of Sciences 90: 10972–10976. Zhu, C., M. Gore, E.S. Buckler, and J. Yu. 2008. Status and prospects of association mapping in plants. The Plant Genome 1: 5-20.

32

CHAPTER 2

The Atlantic x Superior reciprocal populations segregating for yield, specific gravity,

tuber calcium, internal tuber quality, chip quality and common scab: opportunities to

study the genetics of these traits at the tetraploid level

ABSTRACT

Tuber quality traits are a major interest for breeders and the potato chip industry. This study

intended to generate populations that can be suiTable 2.for the genetic study of specific

gravity, yield, chip quality, internal quality, common scab, and tuber calcium at the tetraploid

level. Two populations were generated by reciprocally crossing Atlantic and Superior, two

cultivars contrasting for these traits. Trait segregation was assessed in both reciprocal

populations during 2009 to 2012 at Hancock, Wisconsin. A bell-shaped segregation was

observed for tuber yield, specific gravity, enzymatic browning, chip color using a visual

rating, chip color in agtron units, chip lightness, chip redness, chip yellowness, and tuber

calcium. However, the distributions were skewed towards resistance for the incidence of

hollow heart, internal brown spot, blackspot bruise, as well as pitted scab incidence and

severity. Atlantic and Superior had significantly different phenotypic performance for most

traits. In addition, the reciprocal populations differed significantly for tuber yield, internal

brown spot and tuber calcium suggesting parent-of origin effects influencing these traits. The

characteristics of these reciprocal populations offer opportunities to study the genetics of

quality traits in tetraploid potato and breed varieties that combine commercially desired traits.

33

INTRODUCTION

Commercial potato cultivars are mostly tetraploid. Potato breeding and selection of new

varieties is typically done at the tetraploid level. However, studies aimed at understanding the

genetics of various traits are conducted at the diploid level (Potato Genome Sequencing

Consortium, 2011). Therefore, taking advantage of new genetic knowledge generated in

diploid potatoes to generate breeding strategies towards new improved commercial varieties

may be a slow process. Nevertheless, genetic studies at the tetraploid level are becoming

more feasible with the development of whole genome SNP-based marker technologies for

potato (Hamilton et al. 2011), and the use of statistical approaches and software tools such as

TetraploidMap (Hackett et al. 2007) that allow quantitative genetic analyses at the tetraploid

level. Consequently, we expect that in the future of potato breeding tetraploid populations

could be used for genetic studies and selection speeding up the breeding process.

Genetic variation for agronomic traits (Freyre et al. 1994, Bradshaw et al. 2008, Haynes

2008), chip color (Pereira et al. 1995, Li et al. 2008), internal quality (Jansky and Thompson

1990, McCord et al. 2011a), common scab (McKee 1963, Bjor and Roer 1980, Haynes et al.

2010) and mineral content (Karlsson et al. 2006, Andre et al. 2007, Brown et al. 2012) has

been found among tetraploid potatoes suggesting that there is a potential for selecting

improved varieties for these traits.

Internal defects such as hollow heart, brown center, internal brown spot and black spot bruise

reduce the quality and thus the value of potatoes. Brown center is characterized as a region of

cell necrosis in the tuber pith that results in brown necrotic tissue (Bartholomew 1914).

34

Hollow heart is characterized by a cavity, usually star-shaped, in the center of the tuber that

may arise at a higher incidence under environmental or nutritional stresses (Levitt 1942; Rex

and Mazza 1989). Internal Brown Spot is an internal necrosis that first appears toward the

apical end of the tuber but in severe cases may include most of the parenchyma (Henninger et

al. 2000). Blackspot bruise is a bluish-grey to black zone beneath the skin that results from

the mechanical stress during harvesting and handling (Hughes 1980, Lærke, at al. 2002).

Internal defects such as hollow heart and brown center are more likely to appear in larger size

tubers (Nelson et al. 1979, Jansky and Thompson 1990). However, most diploid clones tend

to produce very small tubers. Thus, studies aimed at understanding the genetics of tuber

internal quality may not be feasible at the diploid level. The present study was undertaken to

develop progenies segregating for tuber quality traits using tetraploid cultivars.

Chip quality is measured using different parameters, chip color being the most important

among them. Chip color is influenced by the composition of the tubers (Rodriguez-Saona and

Wrostald 1997). This trait has been studied using visual color ratings (Work et al 1981),

three-dimensional colorimeters (Parkin and Shwobe 1990), and agtron refractance

colorimeters (Coles et al. 1993). In addition, enzymatic browning is another important trait

for chip quality. Enzymatic browning is the darkening of cut potatoes as a result of the

oxidation of various organic compounds (Makower 1964, Matheis 1983, Friedman 1996).

High enzymatic browning is considered a negative trait that reduces tuber processing quality.

Common scab is caused by several species of Streptomyces spp.; among them the

predominant species is Streptomyces scabies Thaxter (Bjor and Roer 1980, Lambert and

Loria 1989). The lesions caused by common scab range from superficial, raised, or deep

cavities (also called pits); the specific type of lesion present in a cultivar depends on the

pathogen strain and cultivar susceptibility (Loria et al. 1997, Kreuze et al. 1999). Tubers with

35

deep pitted scab cannot be used for processing (Archuleta and Easton 1981). No cultivars are

known to be immune to common scab and the difference in resistance and susceptibility is

quantitative (McKee 1958, Harrison 1962, Scholte and Labruyère 1985).

The mineral content of potato tubers is important not only for human nutrition, but also for

tuber health. Calcium has been shown to play an important role in potatoes response to biotic

(McGuire and Kelman 1986) and abiotic stresses (Palta 1996, Vega et al. 1996, Tawfik et al.

1996, Kleinhenz and Palta 2002). High levels of calcium applications have been associated to

reduced impact of soft-rot caused by Pectobacterium carotovorum (Jones) Waldee (McGuire

and Kelman 1986). Previous research has also demonstrated that application of calcium

increases tuber calcium levels (Kratzke and Palta, 1986, Clough 1994) and reduce the

incidence of internal defects (Tzeng et al. 1986, Olsen et al. 1996, Palta 1996, Ozgen et al.

2006, Karlsson et al. 2006).

Our strategy is to study the genetics of tuber quality traits and tuber calcium at the tetraploid

level using the progenies of Atlantic and Superior, two varieties with contrasting

characteristics for these traits. Atlantic is the standard variety for chipping from the field or

from very short-term storage. It has many traits that make it fit well to the chip industry needs

such as uniformity, high specific gravity, and high yield (Webb et al. 1978). Atlantic potatoes

are much less subject to enzymatic browning on cut and peeled surfaces compared to other

cultivars such as Russet Burbank (Sapers et al 1989). Conversely, Superior is a chipping

variety with low yield, low specific gravity and dark chips. Superior has higher content of

ascorbic acid and soluble proteins at harvest, and higher content of ascorbic acid, glucose,

fructose and total sugars after cold storage compared to Atlantic (Okeyo and Kushad 1995);

which might be related to its darker chip color. Superior has been reported to be resistant or

moderately resistant to internal defects and diseases for which Atlantic has been found

36

susceptible. Superior is resistant to net necrosis and relatively resistant to internal heat

necrosis (Rieman 1962). Atlantic tubers are known to be susceptible to internal heat necrosis,

particularly in sandy soils in warm, dry seasons; also, hollow heart can be serious in the

larger diameter tubers (> 10.2 cm) of Atlantic when moisture and nutrition conditions over

the season fluctuate (Webb et al. 1978). Superior is known to have less severe internal defects

and common scab. Superior has been classified as a moderately resistant and Atlantic as

moderately susceptible to common scab (Haynes et al. 2010). In addition, previous studies

have also revealed that Superior has higher tuber calcium compared to other well-known

varieties such as Russet Burbank, Snowden and Atlantic (Karlsson et al. 2006).

This research aims to assess the performance of Atlantic and Superior, and the segregation of

their progenies for tuber calcium, tuber yield, specific gravity, chip color, internal defects and

incidence of pitted scab. The potential uses of these populations for the study of potato

genetics and selection of new varieties is also discussed. Our results show not only that these

progenies produce good size tubers allowing the study of tuber internal defects, but the

progenies also provide the opportunity for selection of new varieties that could combine the

desired tuber quality with commercially important agronomic traits.

MATERIAL AND METHODS

Reciprocal populations

Reciprocal crosses of potato cultivars Atlantic and Superior were obtained in the Biotron of

the University of Wisconsin-Madison, USA in order to evaluate maternal effects on tuber

calcium and quality traits. Seeds were extracted two months after pollination, rinsed with

distilled water, air-dried, and treated with 1500 mg/Kg gibberellic acid for 24 hours at room

37

temperature to break dormancy and allow germination. The treated seeds were grown in

Murashige-Skoog media to obtain plantlets in order to multiply them clonally after

germination to perform a preliminary evaluation in greenhouse conditions reported by Vega

et al. (2006). These plantlets were then used to produce tubers that were subsequently

maintained as breeders’ seed in field conditions at the Rhinelander and Arlington Agricultural

Research Stations of the University of Wisconsin - Madison. The number of clones from each

reciprocal cross used in the experiments is indicated in Table 2.1.

Location and Experimental Design

Field trials were conducted under standard production practices for nutrient applications as

well as pest and disease control at the Hancock Agricultural Research Station located in the

commercial potato production area of Central Wisconsin, USA during 2009 to 2012 (Table

2.1). Fertilizer and pesticides were applied as needed during the season. No supplemental

calcium fertilizer was used in these trials. In the absence of rain, irrigation was scheduled

every other day. All trials were conducted under standard commercial production practices of

Central Wisconsin. In addition, a high disease pressure field, in other words a field that has

been used continuously to grow potatoes without rotation for several years and is known to

have high amounts of common scab inoculum, was used to evaluate pitted scab incidence and

severity. The standard field was used to evaluate tuber calcium, agronomic traits, internal

defects, chip quality, and pitted scab incidence; and the high disease pressure field was used

to evaluate pitted scab incidence and severity. The experimental design for the 2009 and 2010

trials in the standard field was an incomplete randomized block design (Yates, 1936) with 8-

hill plots and two or three replications for each clone depending on seed availability;

38

complete randomized block design (Fisher 1935) with 8-hill plots and three replications in

the 2011 trial in the standard field; and incomplete block design with 4-hill plots and three

replications for the 2011 and 2012 trials in the high disease pressure field. Separation

between plots was 91.4 cm and spacing between seed pieces within each plot was 30.5 cm.

The incomplete block design was structured in groups of 26 clones plus the two parents

randomized within the group, groups were as well randomized whitin replicates in one, two

or three years depending on the trait evaluated. The details of the field experiemnts, panting

and harvesting dates are presented in Table 2.1.

Tuber yield and specific gravity evaluation

Plots were harvested using a single-row digger and hand-picked to avoid mixing. All the

tubers were graded in three categories: A-grade (>4.8cm), B-grade (≤4.8cm) and culls (rotten

or green); and weighed immediately after harvest. The total tuber yield was expressed in tons

per hectare (ton/ha) and will be referred to as tuber yield. Specific gravity was determined by

the following formula: SG = Weightair/(Weightair-Weightwater), using a basket containing

approximately 2 kilograms of tubers and a scale PW-2050 (Weltech International, UK).

Tubers were stored at 12.8C until further evaluations.

Chip quality and enzymatic browning evaluation

Sixteen to twenty potato slices 1mm wide were sampled from 8 to 10 tubers, and fried in

cotton seed oil at 360ºF for 2 minutes and 20 seconds. Chip quality measurements included:

visual ratings of chip color, chip reflectance in agtron units, lightness, redness and

yellowness. Visual chip color ratings (CC) used a color scale from 1 to 5, where 1 is very

light and 5 is very dark. The chips were crushed to provide an even distribution of the sample

39

in the cup positioned on the viewer. Chips were read in triplicate and means calculated for

each plot. Agtron values (AG) were measured in the 2009 trial were performed in the USDA-

ARS Potato Worksite in East Grand Forks using an agtron M-300 reflectance

spectrophotometer (Fillper Magnuson, Rent, Nevada, US); the readings. Chip lightness (L),

redness (A), and yellowness (B) were measured in the 2010 and 2011 trials using a Hunter

Lab D25L colorimeter (Hunter Associates Laboratory, Inc., Virginia, US).

Enzymatic browning (EB) was measured as the intensity of darkening of the fresh tuber pith

tissue one hour after chopping in a visual scale from 1 to 5, 1 being light and 5 being very

dark, in 2010 and 2011.

Internal quality evaluation

The internal quality traits were evaluated immediately after harvest. All A-grade tubers were

cut in longitudinal sections to record the number of tubers with hollow heart (HH), brown

center (BC), internal brown spot (IBS) and bruise (BB). The number of tubers with internal

defects and the total number of tubers evaluated were recorded. For the data analysis, the

incidence of defects was expressed as proportions or percentages of defective tubers over the

total number of tubers depending on the analysis. The number of tubers cut depended on the

yield of A-grade tubers from a given clone; the minimum number of tubers cut for internal

evaluation was 8 tubers per plot.

Pitted scab evaluation

Deep scab lesions or pits were evaluated under standard and high disease pressure conditions.

The number of tubers with pits and the total number of tubers evaluated were recorded per

plot in the standard field (PS) and under high disease pressure (PS-E). Severity of pitted scab

40

(SPS-E) was measured as the average number of pits in the set of tubers evaluated per plot in

a high disease pressure field. Pitted scab incidence is treated as a binomial variable and

expressed as percentages or proportions of tubers having pitted scab depending on the

analysis. As noted above, the total number of tubers evaluated varied depending upon the

yield of a given clone; however, a minimum number of 8 tubers were evaluated for pitted

scab.

Estimation of calcium concentration in tuber tissue

Tuber calcium (TC) was quantified using the method described by Kratzke and Palta (1986).

For this purpose, two 1-mm-thick longitudinal slices were collected from the center of ten A-

grade tubers. The medullary tissue of the tuber was removed and dried in an oven at 60ºC,

ground to pass a 20-mesh screen, and ashed at 550 ºC. The ash was dissolved in 5 ml of 2 N

HCl. This solution was diluted with a lanthanum chloride solution to obtain a resulting

solution in 0.2 N HCl and LaCl3 at 2000 mg liter-1. The calcium concentration was

determined using an atomic absorption spectrophotometer (Varian SpectrAA 55B). Tuber

calcium was expressed in micrograms of calcium per gram of dry weight of tuber (µg/g).

Analysis of variance (ANOVA) and analysis of deviance (ANODE)

Data normality was tested using Q-Q plots, homogeneity of variances was assessed by

residuals versus fitted plots, and statistical independence was assumed. Datasets were

transformed to obtain a normal distribution when needed. Differences between parents and

reciprocal populations were assessed using multivariate models that reflect the experimental

design.

41

The models used in this study were the following:

Model I: y = μ + G + R + ε (randomized block design model)

Model II: y = μ + G + B(R) + ε (incomplete block design model)

Where, y is the observed trait measurement, μ is the overall mean, G is the genotypes, B is the

group, R is the replicate, B(R) is the group nested in replicates, and ε is the residual error.

Differences between parents were evaluated using Models I and II. The differences between

reciprocal populations were tested using a constrast between the mean of the genotypes that

belong to Atlantic x Superior versus the mean of the genotypes that belong to Superior x

Atlantic. For binomial data, which includes all incidence measurements (pitted scab and

internal defects) expressed as percentages, a Mann-Whitney test for pair-wise comparison

(Mann and Whitney 1947). This test is a non-parametric analysis and can be performed

without the assumption of normality (Holander and Wolfe 1973).

For normally distributed data, a linear model and the F-test were used for the analysis of

variance (ANOVA). For binomial data, a generalized linear model and a Chi-square test were

used for the analysis of deviance (ANODE). Visual scales were treated as numeric variables

instead of categorical variables to facilitate the analysis. Mean performances were estimated

for each clone and density plots were plotted to depict segregation for each reciprocal

population. The statistical analysis and plots were obtained using the stats and ggplot2

packages of R version 3.0.0, respectively (R Development Core Team, 2013).

42

RESULTS AND DISCUSSION

Performance of the parents: Atlantic and Superior

The mean performance of each parent was evaluated and compared in all trials (Tables 2.2

and 2.3). The two parents of the reciprocal populations used in this study, Atlantic and

Superior, were chosen due to their contrasting characteristics for several traits. One of those

traits is tuber calcium. Atlantic had tuber calcium concentrations of 130, 173 and 227 µg/g;

meanwhile, Superior had values of 182, 257 and 289 µg/g during the 2009, 2010 and 2011

trials, respectively (Table 2.2). Karlsson et al. (2006) reported concentrations of 119, 131 and

144 µg/g for Atlantic and 212, 188 and 295 µg/g for Superior in three years of evaluation,

respectively. Compared to previous reports, our estimations of tuber calcium are slightly

higher for Atlantic but it is still consistently lower than Superior by a difference of up to 80

µg/g in 2010.

The parents also differed in tuber yield (Table 2.2). Yield was constantly higher for Atlantic

with means of 73, 49, and 60 ton/ha; while, Superior had tuber yield of 60, 37 and 47 ton/ha

in 2009, 2010 and 2011, respectively. These yield values are in general higher than previous

reports that indicate mean yield of 44.8 and 32.4 ton/ha for Atlantic and Superior,

respectively (Love et al. 1998).

Atlantic and Superior also differed in specific gravity (Table 2.2). Atlantic had specific

gravities of 1.081, 1.077 and 1.079; in contrast, Superior had specific gravities of 1.073,

1.063 and 1.061 in 2009, 2010 and 2011, respectively. Specific gravities in our trials were in

the low range for both parents as compared to previous reports; for example, specific gravity

for Superior has been reported to be 1.056-1.089 (Rieman 1962); and for Atlantic 1.079-

43

1.100 (Sinha et al. 1992, Baritelle and Hyde 2002). However, as expected in our trials

Atlantic had consistently higher specific gravity than Superior.

In general, Atlantic had consistently lighter chips than Superior (Table 2.2). This difference

may be due to the fact that Atlantic is a descendant of Lenape (Webb et al. 1978); and Lenape

has been used to breed for good chipping quality in most of the current chipping varieties

(Love et al, 1998). Superior on the other hand is an old chipping variety which is now

primarily used for fresh market because of its low specific gravity and poor chip quality. The

lighter chip color of Atlantic is also shown by the higher agtron values, chip lightness and

chip yellowness but lower chip redness and visual rating compared to Superior. For chip

lightness, Atlantic had values of 48.1 and 56.6 versus 41.8 and 53.7 for Superior in 2010 and

2011, respectively. For chip yellowness, Atlantic had 20.4 and 22.9 compared to 17.8 and

21.9 for Superior. For chip redness, Atlantic had means of 8.6 and 2.1 versus 10.0 and 3.7 for

Superior (Table 2.2). The visual ratings in a scale from 1 to 5 were 3.1, 2.9 and 1.5 for

Atlantic and 3.5, 3.8 and 3.0 in a scale of 1 to 5 (light to dark) for Superior, respectively for

three years of trials. Chip color as measured in agtron units was 46.7 and 44.8 for Atlantic

and Superior, respectively (Table 2.2). These values are similar to previous reports; for

example, for Atlantic, chip lightness was 40 in the North Central Regional Trial (Navarro et

al. 2012), chip color in agtron units was reported to be between 54 - 62 (Orr and Sacks 1992,

Thompson et al. 2008), and average chip color rating of 3.0 - 3.3 on a 1 to 10 scale (light to

dark) have been reported (Webb et al. 1978, Hutchinson et al. 2003). Similarly, chip color for

Superior was reported to be 3.0 - 5.1 in a 1 to 10 scale, 1 being light and 10 being dark

(Bryan and Durre 1968, Webb et al. 1978).

44

Visual color ratings of enzymatic browning measured on a 1 – 5 scale on raw cut-potatoes

after one hour incubation at room temperature were also different for the parents (Table 2.2).

Scores of 1.04 and 1.5 were obtained for Atlantic compared to 2.14 and 3.0 for Superior in

the 2010 and 2011 trials, respectively. Sapers et al. (1989) measured enzymatic browning in

terms of the change in chip lightness; these authors reported that Atlantic had less enzymatic

browning than Russet Burbank. In another study, Atlantic showed the lowest value in

browning rate, total phenol content, and PPO activity in pre-peeled potatoes compared to

other varieties including Shepody (Jeong et al. 2005). All previous reports support our result

that Atlantic has low enzymatic browning. However, Superior was not tested for this trait by

these authors.

Atlantic and Superior also differed in the incidence of internal defects (Table 2.3). For

example, incidence of hollow heart was lower in superior compared to Atlantic. For hollow

heart, Atlantic had values of 12.0, 19.3 and 1.6% whereas Superior had values of 0.7, 0.6 and

0.6% in the 2009, 2010 and 2011 trials, respectively. Incidences varied among seasons but

were always higher for Atlantic. The Wisconsin Potato Breeding Program reported 5%

incidence of hollow heart for Atlantic in 2012 (Navarro et al. 2012).

For internal brown spot, Atlantic had incidences of 4.8, 12.8 and 0.8%; meanwhile, Superior

had mean incidences of 5.4, 13.5 and 0.0% evaluated in 2009, 2010 and 2011. Incidences

were slightly lower in Atlantic compared to Superior in 2009 and 2010, but higher in 2011. In

general, our results show similar incidences for both parents, but variable from year to year as

reported previously by Henninger et al. (2000) for internal heat necrosis, a defect related to

internal brown spot. In a study by McCord et al. (2011a), internal heat necrosis showed

incidences of 59, 15 and 20% in 2006, 2007 and 2008, respectively; however, these are much

45

higher than the incidences observed in our trials. Previous reports have shown that internal

brown spot is not very common in Wisconsin (Karlsson et al. 2006). It might be possible that

the environment in our trials was not harsh enough to observe clear differences between the

parents.

For blackspot bruise, Atlantic showed consistently higher incidence compared to Superior

with values of 12.0, 3.4, and 3.8% compared to 2.9, 2.2 and 0.6% in 2009, 2010 and 2011,

respectively (Table 2.3). Previous reports indicate that the incidence of blackspot bruise in

Atlantic was 32.6, 45.2 and 44.7% versus 9.1, 11.5 and 6.1% for Superior in 1999, 2000 and

2001, respectively (Karlsson et al. 2006). Our results also indicate higher incidences in

Atlantic than Superior, but the incidence were generally lower in our evaluations. This

difference is likely due to hand harvesting in our trials that reduced the amount of impact

damage. The earlier studies reporting higher incidences of blackspot bruise in Atlantic

compared to Superior (Karlsson et al. 2006) were machine harvested and collected in crates

where tubers fall from about 50 cm distance creating more impact damage. According to

previous research (Karlsson et al. 2006) relating high tuber calcium content with lower

internal defects, we expected that Superior would be more resistant to all internal defects

compared to Atlantic. Our observed differences in mean incidences of internal defects agree

with our expectations for hollow heart and back spot bruise, but not for internal brown spot.

As expected pitted scab incidence and severity were consistently higher in Atlantic than

Superior, with a greater difference among these cultivars when evaluated in a high disease

pressure field (Table 2.3). Mean pitted scab incidences in the standard field were 7.3, 28.0

and 10.0% for Atlantic versus 2.2, 4.0 and 3.3% for Superior for the 2009, 2010 and 2011

trials, respectively. Pitted scab incidence in the high disease field was 80.0 and 71.4% for

Atlantic compared to 3.3 and 1.5% for Superior in the 2011 and 2012 trials, respectively.

46

Pitted scab severity in the high disease pressure field was 4.6 and 2.8% for Atlantic and only

0.1 and 0% for Superior in the 2011 and 2012 evaluations, respectively. From several on-

farm trials, Pavlista (2005) reported a high incidence of scab, 24 - 35%. In addition, Haynes

et al. (2010) found an incidence of 75% for Atlantic and 55% for Superior across six years

and three locations. These previous reports agree with our results in the sense that Atlantic

and Superior differ in pitted scab tolerance and Atlantic is more susceptible.

In summary, we found that the parents were significantly different for most traits in the 2009

and 2010 evaluations (Tables 2 and 3). However, Atlantic and Superior were significantly

different only for specific gravity and pitted scab in the 2011 evaluations. It should be noted

that 2011 was an exceptionally good year for Wisconsin potato production with a very low

incidence of internal defects state-wide. Also, the trial in 2011 in the standard field included

few clones. We speculate that the lack of significant differences between the parents for

several traits in our 2011 standard field trial might be a combination of the environmental

conditions that favored low overall internal defects, the complete block design used only that

year that did not capture the spatial variability in the field as well as the incomplete block

design, and the small sample size. The difference between the complete block design and the

incomplete block design is that the latter takes into account the differences between smaller

areas of the field where the incomplete blocks or groups are grown (26 clones plus the

parents for this study); while, the complete block design takes into account only the

differences between larger areas where the complete blocks or replicates are grown (49

clones plus the parents for this study).

47

Performance of the reciprocal populations and influence of the maternal parent

For each trait, the mean values per reciprocal population were estimated and the significance

of their differences compared. The analysis of variance (ANOVA) and the analysis of

deviance (ANODE) were used to find significant differences between reciprocal crosses and

the significance level was set at p<0.05. The results indicate that there were significant

differences between reciprocal crosses for several traits including tuber calcium, tuber yield,

hollow heart incidence, internal brown spot incidence, enzymatic browning, and pitted scab

(Tables 2.4 and 2.5).

For tuber calcium, the differences between reciprocal populations were significant in three

years of evaluation and AxS had consistently lower tuber calcium compared to SxA

indicating that in average the progenies of Atlantic and Superior had tuber calcium

concentrations more similar to their female parent (Table 2.4). To our knowledge, there are

no previous reports about significant differences between reciprocal populations in mineral

content of potatoes. This relationship should be tested in several crosses using reciprocal

populations generated by crossing the high calcium cultivar Superior and other low calcium

cultivars.

For tuber yield, the reciprocal populations differed significantly only in 2009 but yields were

higher for AxS than SxA in all trials (Table 2.4). Large yield differences between reciprocal

populations in populations of Solanum tuberosum when intergroup hybrids were reported by

Sanford and Hanneman (1982). This study determined that the differences were mostly

associated to the maturity of the female parent. The maturity of Superior is medium (Rieman

1962) and Atlantic is medium-late (Webb et al. 1978); therefore, the differences in maturity

may not be the explanation for the difference in yield of our progenies.

48

The reciprocal populations also differed significantly for enzymatic browning, the visual

scale of chip color, chip color in agtron units and chip lightness only in one year of

evaluation, where population means were similar to the maternal parent (Table 2.4). Previous

studies have reported differences in chip color between reciprocal populations in diploid

populations (Lauer and Shaw 1970, Jakuczun and Zimnoch-Guzowska 2004).

On the other hand, the incidence of hollow heart was significantly different between

reciprocal populations only in one year of evaluation (Table 2.5). Similarly, significant

differences for internal brown spot between AxS and SxA was observed in 2010, a year when

internal brown spot was higher (Table 2.5). For pitted scab incidence, the differences

between reciprocal populations were significant in one year of evaluation in both standard

and high disease pressure fields (Table 2.5).

Significant differences between reciprocal populations were identified for tuber calcium,

tuber yield, enzymatic browning, visual rating of chip color, chip color in agtron units, chip

lightness, hollow heart, internal brown spot, and pitted scab incidence in the standard and the

high disease pressure field. However, a consistent relationship between reciprocal

populations was observed only for tuber calcium. This trait showed significant differences in

all years of evaluation and means closer to the maternal parent.

These results suggest that there might be some kind of parent-of-origin effects acting on tuber

calcium and quality traits of potato. In seed plants, cytoplasmic genes, chloroplast and

mitochondrial, are primarily maternally transmitted (Mogensen 1996). Reciprocal crosses

that show phenotypic differences have been used to study maternal effects (Roach and Wulff

1987). These effects have been observed for several traits in plant species such as maize

(Kollipara et al. 2002, Mach et al. 2011, Waters et al. 2011) and Arabidopsis (Duszynska et

al. 2013). In potato, differences between reciprocal populations have been previously

49

observed for several traits including male sterility, photoperiod, tuber initiation, tuber set,

vine senescence, tuber yield, flowering, male fertility and chip color (Lauer and Shaw 1970,

De la Puente and Peloquin 1968, Sanford and Hanneman 1979, 1982, Jakuczun and

Zimnoch-Guzowska 2004).

From a breeding standpoint, the identification of traits influenced by parent-of-origin effects

is not only an interesting phenomenon to study, but may also have practical applications

enabling breeders to predict which progenitors are more likely to produce offspring with the

desired phenotype when used as male or female parent.

From this study, we can conclude that for crosses between Atlantic and Superior, when

Atlantic is used as the maternal parent, the progenies will have higher tuber yields in average

than the reciprocal. On the other hand, if Superior is the maternal parent the progenies will

have less internal brown spot and higher tuber calcium. The reciprocal populations of

Atlantic x Superior could be of great value to understanding the genetic and epigenetic causes

of phenotypic differences in reciprocal populations. Future studies in reciprocal populations

will contribute to the better understanding of parent-of-origin effects, and the biological

reasons behind the differences between reciprocal populations. For this particular population,

the significant differences between reciprocal populations for tuber calcium, tuber yield and

internal brown spot incidence suggest that further analysis and conclusions generated by the

quantitative genetic analysis of these reciprocal populations should be made independently

for each population.

Segregation for tuber yield, specific gravity and chip quality

Tuber yield and specific gravity of both reciprocal populations had distributions that are

approximately normal (Figure 2.1). Most clones had intermediate or lower yield than the

50

parents and only few clones had higher yields than the parents. Atlantic was consistently

among the highest yielding clones. A similar distribution for yield was previously observed in

tetraploid populations by Bradshaw et al. (2008) in the 12601ab1 x Stirling population and

also by McCord et al. (2011a) in the Atlantic x B1829-5 population.

In the case of specific gravity, the distribution of the progeny was close to normal with

contrasting parental performances (Figure 2. 1). This distribution is similar to the distribution

presented by Haynes (2008) in a long-day adapted S. phureja x S. stenotomum diploid

population, and comparable to the distribution presented by McCord et al. (2011b) for a

tetraploid population even though their parental clones had similar values of specific gravity.

Performances for visual ratings of chip color, chip color measured as agtron units, chip

lightness (L values), chip redness (A values), and chip yellowness (B values) resemble

normal distributions with some clones with lighter chips than Atlantic (Figure 2. 1). The

normal distribution observed for the visual scale and agtron values is similar to reports from

other authors including Douches and Freyre (1994) that evaluated a diploid population of S.

tuberosum x S. chacoense; Haynes (2008) that used the 1 to 10 scale of the National Potato

Chip Institute Color Chart and evaluated a diploid S. phureja x S. stenotomum population;

and Bradshaw et al. (2008) that evaluated a tetraploid (12601ab1 x Stirling) population.

Segregation of tuber calcium

For tuber calcium, most progenies were intermediate between both parents. The performance

of both parents was contrasting for this trait (Figure 2. 1). Atlantic was consistently among

the clones with lowest tuber calcium and Superior was the highest. Tuber calcium has only

been investigated in commercial cultivars (Karlsson et al. 2006; Brown et al. 2012) and wild

51

potato germplasm (Bamberg et al. 1993), but not in segregating bi-parental populations. The

close to normal segregation for tuber calcium content in both reciprocal populations is

indicating the quantitative nature of this trait. These results are consistent with preliminary

evaluations of this population (Vega et al. 2006). This bell-shaped distribution is consistent

with a quantitative nature of the trait.suggesting that calcium concentration in the tuber may

be controlled by several genes as it has been found in soybean seeds (Zhang et al. 2009).

Segregation of internal defects

The distributions of the incidences of internal defects including hollow heart, internal brown

spot, and black spot bruise were skewed towards resistance in both reciprocal populations of

Atlantic and Superior (Figure 2. 2). These skewed distributions indicate that most progenies

have low incidence and few progenies have very high incidence of defects. These results

suggest that there might be some major resistance genes in the resistant parent Superior that

are segregating in these reciprocal populations. These skewed phenotypic segregations of

internal defects have been previously reported for the incidence of internal heat necrosis

(McCord et al. 2011a) and as a combined internal condition score (Bradshaw et al. 2008).

McCord et al. (2011a) found a skewed segregation towards lower incidence values in the

Atlantic x ‘B1829-5’ tetraploid population for internal heat necrosis (IHN). This defect has

been reported in eastern US where plants are subjected to heat stress during late season

(Sterret and Henninger 1997). On the other hand, Bradshaw et al. (2008) evaluated the

internal condition (IC), a visual score in a 1 to 9 scale, in the 12601ab1 x Stirling population.

This IC score was skewed towards higher scores (fewer defects); these results were also

similar to our results even though they performed a simultaneous evaluation of several

52

internal defects in one single score. The parents evaluated for internal heat necrosis by

McCord et al. (2011a), Atlantic and ‘B1829-5’, had contrasting values of incidence. On the

other hand, the parents evaluated for IC by Bradshaw et al. (2008), 12601ab1 and Stirling,

had similarly high internal scores which means few internal defects. However, both

populations studied by these authors showed skewed distributions. These results suggest that

the skewness of the segregation for internal defects does not depend on the difference

between parents and might be related to the genetics of these traits. The phenotypic

distribution is the result of the action of major and minor genes (Bernardo 2010); in other

words, the amount of variation explained by each gene varies and could be high or very low.

Skewed distributions observed in the distribution of a segregating population may indicate

the action of a major dominant gene; however, skewness can also exist due to the type of data

and its natural boundaries (Jansen 2007). In this study, the incidences of internal defects

expressed as proportions only can have values between 0 and 1; these values are a summary

of the presence or absence of defects in a certain number of tubers; therefore, the incidences

of internal defects follow a binomial distribution not a normal distribution. Therefore, the

skewness observed in the segregation of internal defects in this study are due to the type of

data used and may also indicate the presence of dominant major genes in the population.

Segregation of pitted scab

Pitted scab was evaluated in place of a general common scab evaluation because the

occurrence of pits reduces the value of potatoes while shallow lesions are still accepTable

2.for processing (Archuleta and Easton 1981). The evaluation of pitted scab was performed

by determining the proportion of tubers with pits evaluated as a measure of incidence and the

53

average number of pits per tuber in a plot as an indicator of severity. Pitted scab incidence

was expressed as percentages and plotted in a density plot (Figure 2.2). Incidence was

skewed towards low incidence resembling the distributions observed for incidence of internal

defects. The severity of pitted scab measured as the average number of pits per tuber had a

skewed distribution where low-values were more frequent (Figure 2.2). These values had to

be transformed by taking the square root of the values for normalization (Figure 2.2). In the

reciprocal populations of Atlantic (moderately susceptible) x Superior (moderately resistant)

most clones had lower incidences of pitted scab than Atlantic and some clones performed

similarly to Superior indicating that there is some potential for selecting clones with

improved resistance to the incidence and severity of common scab comparable to Atlantic.

In previous studies common scab severity was measured as an index from 0 to 5 (low to high)

in the Jacqueline Lee (susceptible) x MSG227-2 (tolerant) tetraploid population (Driscoll et

al. 2009). Using this severity index the population distribution was found to be skewed

towards susceptibility. In both our measurements, the proportion of tubers with disease and

the number of pits per tuber, the segregation was also skewed but towards resistance.

Therefore, we hypothesize that the skewed distribution observed for the incidence and

severity of pitted scab might be related to the mode of inheritance of scab tolerance;

specifically, the presence of major dominant genes. It is also important to note that the

incidence of pitted scab follows a binomial distribution because it is the summary of the

presence and absence of pits in a certain number of tubers.

54

CONCLUSIONS

By crossing Atlantic and Superior, we have produced reciprocal populations with clones that

have variable phenotypes for tuber calcium with values between the parents and some with

extremely high and extremely low values. Atlantic and Superior were different for most tuber

quality and pitted scab traits except for brown center or internal brown spot. Also, internal

brown spot was not different between the parents probably because this defect was generally

low; thus, this data will not be further used.

In brief, Atlantic and Superior contrast for several tuber quality traits such as yield, specific

gravity, chip quality, internal quality and pitted scab tolerance; therefore, the genetic

variation of the reciprocal populations generated by the cross of these two cultivars could be

used for the genetic study these traits.

This study demonstrates that Atlantic and Superior have contrasting phenotypes for tuber

yield, specific gravity, enzymatic browning, chip color using visual ratings, chip color as

measured in agtron units, colorimetric measurements of chip color, tuber calcium, incidence

of hollow heart and blackspot bruise, as well as incidence and severity of pitted scab. The

populations generated by reciprocal crosses between Atlantic and Superior show phenotypic

variation for all these traits. Most traits followed distributions that resemble a normal

distribution including the segregation for tuber yield, specific gravity, enzymatic browning,

chip color using visual ratings, chip color in agtron units, colorimetric measurements of chip

color and tuber calcium. However, skewed distributions were found for the incidence of

hollow heart, blackspot bruise, and pitted scab incidence and severity. The characteristics of

the reciprocal populations of Atlantic and Superior can be used to: (i) perform quantitative

genetic analyses such as broad-sense heritabilities and between-trait correlations for yield,

55

specific gravity, tuber calcium, tuber quality, chip quality, and internal quality, but also for

other traits these cultivars may differ; (ii) identify QTL for traits of commercial interest; (iii)

and identify desired clones that combine the desired traits of Atlantic and Superior to develop

new improved Atlantic-type chipping varieties. Further investigation of this population has

the potential to provide genetic and biological explanation for the variation of important

commercial desired traits of potato. This information could greatly enhance breeding efforts

to improve traits such as scab resistance, internal quality, and processing quality of potatoes.

BIBLIOGRAPHY

Andre, C.M., M. Ghislain, P. Bertin, M. Oufir, M. del R. Herrera, L. Hoffmann, J.F. Hausman, Y. Larondelle, and D. Evers. 2007. Andean potato cultivars (Solanum tuberosum l.) as a source of antioxidant and mineral micronutrients. Journal of Agricultural and Food Chemistry 55: 366-378. Archuleta, J.G. and G.D. Easton. 1981. The cause of deep- pitted scab of potatoes. American Potato Journal 58: 385-392. Bamberg, J.B., J.E Palta, L.A. Peterson, M. Martin, and A.R. Krueger. 1993. Screening tuber-bearing Solanum (potato) germplasm for efficient accumulation of tuber calcium. American Potato Journal 70: 219-226. Baritelle, A.L. and G.M. Hyde. 2003. Specific gravity and cultivar effects on potato tuber impact sensitivity. Postharvest Biology and Technology 29: 279-286. Bartholomew, E.T. 1914. A pathological and physiological study of the black heart of potato tubers. Thesis (Ph.D.) University of Wisconsin - Madison.

Bernardo, R. 2010. Breeding for Quantitative Traits in Plants. Minnnesota, US: Stemma Press. Bjor, T. and L. Roer. 1980. Testing the resistance of potato varieties to common scab. Potato Research 23: 33-47.

56

Bradshaw, J.E., C.A. Hackett; B. Pande; R. Waugh, and G.J. Bryan. 2008. QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Theoretical and Applied Genetics 116: 193-211. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller Jr. 2012. Stability and broad-sense heritability of mineral content in potato: Calcium and magnesium. American Journal of Potato Research 89: 255-261. Bryan, H.H. and N.L. Durre. 1968. White potatoes for marl soils in Dade County. In Proc. Fla. State Hort. Soc. 81: 159-163. Clough, G.H. 1994. Potato tuber yield, mineral concentration, and quality after calcium fertilization. Journal of the American Society of Horticultural Science 119: 175-179. Coles, G.D., J.P. Lammerink and A.R. Wallace. 1993. Estimating potato crisp colour variability using image analysis and a quick visual method. Potato Research 36: 127-134. De la Puente, F., and S.J. Peloquin. 1968. Male fertility of selected 24 chromosome S. tuberosum hybrids. American Potato Journal 45: 436-437. Douches, D.S. and R. Freyre. 1994. Identification of genetic factors influencing chip color in diploid potato (Solanum spp.). American Potato Journal 71: 581-590. Driscoll, J., J. Coombs, R. Hammerschmidt, W. Kirk, L. Wanner, and D. Douches. 2009. Greenhouse and field nursery evaluation for potato common scab tolerance in a tetraploid population. American Journal of Potato Research 86: 96-101. Duszynska, D., P.C. McKeown, T.E. Juenger, A. Pietraszewska‐Bogiel, D. Geelen, and C. Spillane. 2013. Gamete fertility and ovule number variation in selfed reciprocal F1 hybrid triploid plants are heritable and display epigenetic parent‐of‐origin effects. New Phytologist 198: 71-81. doi: 10.1111/nph.12147 Fisher, R.A. 1935. The design of experiments. First Edition. Oxford, England: Oliver and Boyd. Freyre, R., S. Warnke, B. Sosinski, D.S. Douches. 1994. Quantitative trait locus analysis of tuber dormancy in diploid potato (Solanum spp.). Theoretical and Applied Genetics 89: 474-480 Friedman, M. 1996. Food browning and its prevention: An overview. Journal of Agricultural and Food Chemistry 44: 631-653. Hackett, C.A., I. Milne, J.E. Bradshaw, Z. Luo. 2007. TetraploidMap for Windows: linkage map construction and QTL mapping in autotetraploid species. Journal of Heredity 98: 727-729. Hamilton, J.P., C.N. Hansey, B. R. Whitty, K. Stoffel, A.N. Massa, A. Van Deynze, W.S. De Jong, D.S. Douches, and C.R. Buell. 2011. Single nucleotide polymorphism discovery in elite North American potato germplasm. BMC Genomics 12: 302-312.

57

Harrison, M.D. 1962. Potato russet scab, its cause and factors affecting its development. American Journal of Potato Research 39: 368-387. Haynes, K.G. 2008. Heritability of chip color and specific gravity in a long-day adapted Solanum phureja x S. stenotomum population. American Journal of Potato Research 85: 361-366. Haynes, K.G., L.A. Wanner, C.A. Thill, J.M. Bradeen, J. Miller, R.G. Novy, J.L. Whitworth, D. L. Corsini, and B.T. Vinyard. 2010. Common scab trials of potato varieties and advanced selections at three U.S. locations. American Journal of Potato Research 87: 261-276. Henninger, M.R., S.B. Sterret, and K.G. Haynes. 2000. Broad-sense heritability and stability of internal heat necrosis and specific gravity in tetraploid potatoes. Crop Science 40: 977-984. Hughes, J.C. 1980. Potatoes I: Factors affecting susceptibility of tubers to damage. Span 23: 65-75. Hutchinson, C.M., J.M. White, D.M. Gergela, P.A. Solano, K.G. Haynes, R. Wenrich, and C.S. Lippi. 2003. Performance of Chip Processing Potato Varieties in Northeastern Florida. HortTechnology 13: 706-711. Jakuczun, H., and E. Zimnoch-Guzowska. 2004. Inheritance of glucose content in tubers of diploid potato families. American Journal of Potato Research 81: 359-370. Jansen, R.C. 2007. Quantitative Trait Loci in Inbred Lines. In Handbook of Statistical Genetics Vol. 1. eds. D.J. Balding, M. Bishop, C. Cannings, 595-596. Chichester, UK: John Wiley and Sons Ltd. Jansky, S.H. and Thompson D.M. 1990. Expression of Hollow Heart in segregating tetraploid potato families. American Potato Journal 67: 695-793. Jeong, J.C., H.C. Ok, O.S. Hur, C.G. Kim, C.S. Park,S.Y. Kim. 2005. Raw material characteristics affect enzymatic browning of pre-peeled potato tubers. Journal of the Korean Society for Horticultural Science 46: 246-249. Karlsson, B., J.P. Palta and P.M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. HortScience 41: 1213-1221. Kleinhenz, M.D. and J.P. Palta. 2002. Root calcium modulates the response of potato plants to heat stress. Physiologia Plantarum 115: 111-118. Kratzke, M.G. and Palta, J.P. 1986. Calcium accumulation in potato tubers: Role of the basal roots. HortScience 21:1022-1024. Kreuze, J.F., S. Suomalainen, L. Paulin, and J.P. Valkonen. 1999. Phylogenetic analysis of 16S rRNA genes and PCR analysis of the nec1 gene from Streptomyces spp. causing common scab, pitted scab, and netted scab in Finland. Phytopathology 89: 462-469.

58

Kollipara, K.P., I.N. Saab, R.D. Wych, M.J. Lauer, and G.W. Singletary. 2002. Expression profiling of reciprocal maize hybrids divergent for cold germination and desiccation tolerance. Plant Physiology 129: 974-992. Lærke, P.E., J. Christiansen, M.N. Andersen, and B. Veierskov. 2002. Blackspot bruise susceptibility of potato tubers during growth and storage determined by two different test methods. Potato Research 45: 187-202. Lambert, D.H. and R. Loria. 1989. Streptomyces scabies sp. nov., nom. rev. International Journal of Systematic Bacteriology 39: 387-392. Lauer, F., and R. Shaw. 1970. A possible genetic source for chipping potatoes from 40 F storage. American Potato Journal 47: 275-278. Levitt, J. 1942. A historical study of hollow heart potatoes. American Journal of Potato Research 19: 134-143. Li, L., M.J. Paulo, J. Strahwald, J. Lübeck, H.R. Hofferbert, E. Tacke, H. Junghans, J. Wunder, A. Draffehn, F. van Eeuwijk, and C. Gebhardt. 2008. Natural DNA variation at candidate loci is associated with potato chip color, tuber starch content, yield and starch yield. Theorethical and Applied Genetics 116: 1167-1181. Loria, R., R.A. Bukhalid, B.A. Fry, and R.R. King. 1997. Plant pathogenicity in the genus Streptomyces. Plant Disease 81: 836-846. Love, S.L., J.J. Pavek, A. Thompson-Johns, and W. Bohl. 1998. Breeding progress for potato chip quality in North American cultivars. American Journal of Potato Research 75: 27-36. Mach, J. 2011. Large-scale rna sequencing to identify maize genes with parent-of-origin expression effects. The Plant Cell Online 23(12): 4166-4166. Makower, R.U. 1964. Effect of nucleotides on enzymic browning in potato slices. Effect of nucleotides on enzymic browning in potato slices. Plant Physiology 39: 956-959. Matheis, G. 1983. Enzymatic browning of foods. Zeitschrift für Lebensmittel-Untersuchung und Forschung 176: 454-462. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011a. QTL mapping of internal heat necrosis in tetraploid potato. Theoretical and Applied Genetics 122: 129-142. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011b. Linkage Mapping and QTL Analysis of Agronomic Traits in Tetraploid Potato (Solanum tuberosum subsp. tuberosum). Crop Science 51:771-785. McGuire, R. and A. Kelman. 1986. Calcium in potato tuber cell walls in relation to tissue maceration by Erwinia carotovora pv. atroseptica. Physiology and Biochemistry 7: 401-406.

59

McKee, R.K. 1958. Assessment of the resistance of potato varieties to common scab. Potato Research 1: 65-80. McKee, R.K. 1963. Scab resistance of potato varieties. Plant Pathology 12: 106-109. Mogensen, H. L. The hows and whys of cytoplasmic inheritance in seed plants. American Journal of Botany 83:383-404. Navarro, F., B. Bowen, and J. Palta. 2012. Potato breeding program research update field year 2012. Proceedings of the Wisconsin Potato and Vegetable Growers Association (WPVGA). 36 pages. Nelson, D.C., M.C. Thoreson, D.A. Jones. 1979. The relationship between tuber size and hollow heart in Norgold Russet potatoes. American Journal of Potato Research 56: 329-337. Okeyo, J.A. and M.M. Kushad. 1985. Composition of four potato cultivars in relation to cold storage and reconditioning. HortTechnology 5: 250-253. Olsen, N.L., L.K. Hiller, and L.J. Mikitzel. 1996. The dependence of internal brown spot development upon calcium fertility in potato tubers. Potato Research 39: 165-178. Orr, P.H., and J.M. Sacks. 1992. Chipping responses of stored potatoes after handling. Transactions of the ASAE 35. Ozgen, S., B.H. Karlsson and J.P. Palta. 2006. Response of potatoes (cv. ‘Russet Burbank’) to supplemental calcium applications under field conditions. Tuber calcium, yield, and incidence of brown spot. American Journal of Potato Research 83: 195-204. Palta, J.P. 1996. Role of calcium in plant responses to stresses: Linking basic research to the solution of practical problems. HortScience 31: 51-57. Pavlista, A.D. 2005. Early-season applications of sulfur fertilizers increase potato yield and reduce tuber defects. Agronomy Journal, 97: 599-603. Parkin, K.L., and M.A. Schwobe. 1990. Effects of low temperature and modified atmosphere on sugar accumulation and chip color in potatoes (Solanum tuberosum). Journal of Food Science 55: 1341-1344. Pereira, A., G.C.C. Tai, R.Y. Yada, R.H. Coffin and V. Souza-Machado. Genetic advance for chip colour of potatoes. Euphytica 84: 133-138. Potato Genome Sequencing Consortium. 2011. Genome sequence and analysis of the tuber crop potato. Nature 475: 189-195. R Development Core Team. 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org.

60

Rex, B. L. and G. Mazza. 1989. Cause, control and detection of hollow heart in potatoes: A review. American Potato Journal 66: 165-183. Rieman, G.H. 1962. Superior: A new white, medium-maturing, sab resistant potato variety with high chipping quality. American Journal of Potato Research 39: 19-28. Roach D.A. and R. Wulff. 1987. Maternal effects in plants. Annual Review of Ecology and Systematics 18: 209-235. Rodriguez-Saona, L.E. and R. Wrostald. 1997. Influence of potato composition on chip color quality. American Journal of Potato Research 74: 87-106. Sanford, J.C., and R.E. Hanneman Jr. 1982. Large yield differences between reciprocal families of Solanum tuberosum. Euphytica 31: 1-12. Sapers, G.M., F.W. Douglas, A. Bilyk, A.F. Hsu, H.W. Dower, L. Garzarella, and M. Kozempel. 1989. Enzymatic browning in Atlantic potatoes and related cultivars. Journal of Food Science 54: 362-365. Scholte, K. and R.E. Labruyère. 1985. Netted scab: a new name for an old disease in Europe. Potato Research 28: 443-448. Sinha, N.K., J.N. Cash and R.W. Chase. 1992. Differences in sugars, chip color, specific gravity and yield of selected potato cultivars grown in Michigan. American Journal of Potato Research 69: 385-389. Sterret, S.B. and M.R. Henninger 1997. Internal heat necrosis in the midatlantic region-influence of environment and cultural management. American Journal of Potato Research 74: 233-243. Tawfik, A.A., M.D. Kleinhenz, and J.P. Palta. 1996. Application of calcium and nitrogen for mitigating heat stress effects on potatoes. American Journal of Potato Research 73: 261-273. Thompson, A. L., B.L. Farnsworth, N.C. Gudmestad, G.A. Secor, D.A. Preston, J.R. Sowokinos, and H. Hatterman-Valenti. 2008. Dakota Diamond: An exceptionally high yielding, cold chipping potato cultivar with long-term storage potential. American Journal of Potato Research 85: 171-182. Tzeng, K.C., A. Kelman, K.E. Simmons, and K.A. Kelling. 1986. Relationship of calcium nutrition to internal brown spot of potato tubers and sub-apical necrosis of sprouts. American Journal of Potato Research 63: 87-97. Vega, S.E., Bamberg, J.B. and Palta, J.P. 1996. Potential for improving freezing stress tolerance of wild potato germplasm by supplemental calcium fertilization. American Journal of Potato Research 73: 397-409.

61

Vega, S.E., J.P. Palta, and J.B. Bamberg. 2006. Exploiting cultivated germplasm to breed for enhanced tuber calcium accumulation ability [Abstract]. American Journal of Potato Research 83:136. Waters, A.J., I. Makarevitch, S.R. Eichten, R.A. Swanson-Wagner, C.T. Yeh, W. Xu, S.P., Schnablec, M.W. Vaughne, M. Gehringf, and N.M. Springer. 2011. Parent-of-origin effects on gene expression and DNA methylation in the maize endosperm. The Plant Cell Online 23: 4221-4233. Webb, R.E., D.R. Wilson, J.R. Shumaker, B. Graves, M.R. Henninger, J. Watts, J.A. Frank, and H.J. Murphy. 1978. Atlantic: A new potato variety with high solids, good processing quality and resistance to pests. American Journal of Potato Research 55: 141-145. Work, T.H., A.S. Kesis, and R.H. True. 1981. Factors determining potato chipping quality. Potato Chip/Snack Food Association standard color manual. Life sciences and agriculture experiment station University of Maine at Orono. Technical Bulletin 103, September 1981. Yates, F. 1936. Incomplete randomized blocks. Annals of Eugenics 7: 121-140. Zhang, B., P. Chen, A. Shi, A. Hou, T. Ishibashi, and D. Wang. 2009. Putative quantitative trait loci associated with calcium content in soybean seed. Journal of Heredity 100: 263-269.

62

TABLES Table 2.2.1. Information on the clones evaluated, experimental design and trial conditions in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations

Trials 2009 2010 2011 2011‡ 2012‡

Number of clones evaluated by reciprocal population AxS (189 clones)† 121 158 40 128 87

SxA (123 clones)† 64 107 9 86 78

Experimental design Design IBD IBD CBD IBD IBD

Plot size 8-hill 8-hill 8-hill 4-hill 4-hill

Replicates 3 2 or 3 3 3 3

Field conditions Field location C-field C-field C-field E-field E-field

Disease pressure standard standard standard high high

K application ( kg/ha) 170.1 172.4 181.4 181.4 181.4

N, P, K starter fertilizer at planting impregnated with platinum (249.5 kg/ha)

6-24-24 6-30-22-4S 6-30-22-4S 6-30-22-4S 6-30-22-4S

Season information Planting 05/01 04/29 04/28 05/10 05/18

Harvest (vines killed 10 days before harvest)

10/06 08/30 08/29 09/09 09/10

IBD=randomized incomplete block design, CBD=randomized complete block design, 4-hill= 4 tuber-seed pieces separated by 30.5 cm, 8-hill=8 tuber-seed pieces separated by 30.5 cm †In parenthesis are the total number of clones evaluated across all trials.The number of clones evaluated varies from season to season because not all the genotypes had enough seedto be used in the experiments. ‡Trials in the high disease pressure field.

63 Table 2. 2.2. Means by parent and population during 2009-2011 in the standard field for tuber calcium (TC), tuber yield (TY), specific gravity (SG), visual rating of chip color (CC), chip color as measured in agtron units (AG), chip lightness (L), chip redness (A), and chip yellowness (B). Evaluations made at Hancock Agricultural Research Station.

ATL‡ SUP‡

Trait units Year mean SD mean SD

TC 2009 130.4 31.3 182.4 41.0

2010 173.1 33.9 257.9 45.6

2011 227.1 41.0 289.3 26.5

TY µg/g 2009 73.6 11.7 60.0 7.6

µg/g 2010 49.6 11.5 37.1 12.6

µg/g 2011 60.6 5.6 47.1 10.2

SG g/g 2009 1.081 0.008 1.073 0.007

g/g 2010 1.077 0.004 1.063 0.007

g/g 2011 1.079 0.003 1.061 0.007

EB† 1 to 5 2010 1.04 0.19 2.14 0.52

1 to 5 2011 1.50 0.71 3.00 0.00

AG agtron 2009 46.7 2.6 44.8 2.6

CC† 1 to 5 2009 3.1 0.4 3.5 0.5

1 to 5 2010 2.9 0.6 3.8 0.7

1 to 5 2011 1.5 0.5 3.0 0.9

L L values 2010 48.1 4.6 41.8 3.3

2011 56.6 0.7 53.7 1.9

A A values 2010 8.6 2.1 10.0 1.8

2011 2.1 2.0 3.7 1.6

B B values 2010 20.4 1.7 17.8 1.7

2011 22.9 0.2 21.9 1.0 ATL=Atlantic, SUP=Superior, SD=standard deviation

† Enzymatic browning and chip color were measured using a visual rating from 1 to 5 (light to dark).

‡Significant differences between parents in a year of evaluation (rows) at p< 0.05 as indicated by the F-test of the ANOVA are indicated in bold.

64 Table 2.2.3. Means by parent and population during 2009-2012 for the incidences of hollow heart (HH), internal brown spot (IBS), black spot bruise (BB), pitted scab in the standard field (PS), pitted scab in the high disease pressure field (PS-E), and severity of pitted scab in the high disease pressure field (SPS-E). Evaluations made at Hancock Agricultural Research Station.

ATL SUP

Trait units Year mean SD mean SD

HH % 2009 12.0 8.8 0.7 1.3

% 2010 19.3 17.7 0.6 1.3

% 2011 1.6 2.8 0.6 1.1

IBS % 2009 4.8 3.2 5.4 4.6

% 2010 12.8 11.1 13.5 13.6

% 2011 0.8 0.7 0.0 0.0

BB % 2009 12.0 7.4 2.9 2.7

% 2010 3.0 3.0 2.2 4.0

% 2011 3.8 4.6 0.6 1.1

PS % 2009 7.3 12.9 2.2 5.5

% 2010 28.0 24.1 4.0 4.2

% 2011 10.0 17.3 3.3 5.8

PS-E % 2011 80.0 16.9 3.3 4.8

% 2012 71.4 14.1 1.5 2.8

SPS-E† pits/tuber 2011 4.58 1.47 0.07 1.62

pits/tuber 2012 2.80 0.83 0.03 0.84 ATL=Atlantic, SUP=Superior, SD=standard deviation

†A square-root transformation was used for pitted scab severity data to normalize the data before the statistical test.

‡Significant differences between parents in a year of evaluation (rows) at p< 0.05 as indicated by the Chi-square test of the ANODE for incidence data, and the F-test of the ANOVA for pitted scab severity are indicated in bold.

§Estimated mean difference between reciprocal populations in ayear of evaluation (rows). Significance at p< 0.05 is indicated in bold.

65

Table 2. 2.4. Means by parent and population during 2009-2011 in the standard field for tuber calcium (TC), tuber yield (TY), specific gravity (SG), visual rating of chip color (CC), chip color as measured in agtron units (AG), chip lightness (L), chip redness (A), and chip yellowness (B). Evaluations made at Hancock Agricultural

Research Station.

AxS SxA

Trait units Year mean SD mean SD Contrasts‡

AxS vs. SxA p-value (T test)

TC µg/g 2009 153.6 50.6 159.1 52.0 -11.3 0.03

µg/g 2010 197.1 50.8 201.5 43.7 -12.3 0.03

µg/g 2011 268.9 65.1 291.8 62.2 -24.0 0.04

TY tons/ha 2009 51.5 15.7 48.5 14.2 5.01 0.0004

tons/ha 2010 37.2 13.5 36.4 12.3 0.55 0.36

tons/ha 2011 39.5 10.9 39.4 9.5 0.093 0.59

SG g/g 2009 1.074 0.009 1.073 0.01 -0.0009 0.4

g/g 2010 1.068 0.007 1.068 0.008 0.0007 0.1

g/g 2011 1.072 0.01 1.069 0.008 0.003 0.054

EB† 1 to 5 2010 2.09 0.99 1.92 0.85 0.17 0.002

1 to 5 2011 1.92 1.01 2.00 0.76 -0.07 0.65

AG agtron 2009 42.8 4.7 42.4 4.8 0.97 0.028

CC† 1 to 5 2009 3.5 0.6 3.5 0.6 -0.15 0.055

1 to 5 2010 3.3 0.9 3.4 0.8 -0.12 0.036

1 to 5 2011 2.1 0.9 2.0 0.8 0.07 0.54

L L values 2010 45.4 5.9 44.8 5.9 0.86 0.034

2011 55.8 4.4 55.8 3.8 -0.067 0.9

A A values 2010 9.4 1.5 9.4 1.3 -0.013 0.93

2011 3.3 0.8 3.5 1.0 -0.12 0.68

B B values 2010 18.9 2.8 18.8 2.5 -0.08 0.68

2011 23.0 1.2 23.2 1.1 -0.19 0.25 AxS =Atlantic x Superior, SxA=Superior x Atlantic, SD=standard deviation

†Enzymatic browning and chip color were measured using a visual rating from 1 to 5 (light to dark).

‡Estimated mean difference between reciprocal populations in a year of evaluation (rows). Significance at p< 0.05 is indicated in bold.

66 Table 2.2.5. Means by parent and population during 2009-2012 for the incidences of hollow heart (HH), internal brown spot (IBS), black spot bruise (BB), pitted scab in the standard field (PS), pitted scab in the high disease pressure field (PS-E), and severity of pitted scab in the high disease pressure field (SPS-E). Evaluations made at Hancock Agricultural Research Station.

AxS SxA

Trait units Year mean SD mean SD Contrasts‡

AxS vs. SxA p-val

(T test) KW test§

(p-val) HH % 2009 11.4 14.5 15.1 17.7 0.036

% 2010 5.9 10.8 5.1 10.1 0.23

% 2011 4.2 6.7 3.0 5.2 0.43

IBS % 2009 9.3 11.1 8.9 10.9 0.48

% 2010 10.6 14.9 7.0 11.1 0.0006

% 2011 4.1 9.1 3.1 4.3 0.95

BB % 2009 5.0 5.7 5.5 5.7 0.27

% 2010 1.3 3.2 1.5 4.1 0.78

% 2011 2.8 3.9 2.6 3.9 0.40

PS % 2009 6.2 9.8 6.3 8.9 0.69

% 2010 16.6 16.4 17.1 17.4 0.89

% 2011 7.7 10.3 6.9 16.2 0.26

PS-E % 2011 32.4 27.2 31.1 28.4 0.35

% 2012 19.9 22.5 23.7 25.5 0.21

SPS-E† pits/tuber 2011 1.23 1.91 1.20 0.12 0.096 0.37

pits/tuber 2012 0.54 1.29 0.58 0.05 0.034 0.67 AxS =Atlantic x Superior, SxA=Superior x Atlantic, SD=standard deviation

†A square-root transformation was used for pitted scab severity data to normalize the data before the statistical test.

‡Estimated mean difference between reciprocal populations in ayear of evaluation (rows). Significance at p< 0.05 is indicated in bold.

§Significance at p< 0.05 for the Chi-square test of a mean comparison between reciprocal populations using the Kruskal Wallis test.

67

FIGURES

Figure 2.2.1. Segregation for normally distributed traits including tuber yield, specific gravity, enzymatic browning, chip color as measured in agtron units, visual rating of chip color, and chip lightness, for chip redness, and chip yellowness, and tuber calcium in the reciprocal populations of Atlantic and Superior. Figures show density plots for one year of evaluation in Hancock, Wisconsin.

68 Figure 2.2.2. Segregation for traits with skewed distributions including the incidence of hollow heart, internal brown spot, black spot bruise, pitted scab in the standard field, pitted scab in the high disease pressure field, and severity of pitted scab in the high disease pressure field. Figures show density plots for one year of evaluation in Hancock, Wisconsin.

69

CHAPTER 3

Correlations and heritabilities of tuber quality, pitted scab and tuber calcium: Implications for selection of potatoes with improved tuber quality

ABSTRACT

A better understanding of the genetic basis of commercial traits of potato (Solanum

tuberosum) is a priority for potato breeders in order to supply growers with improved

varieties for the potato industry. Previous studies have related improved quality such as less

internal defects and reduced soft rot with field applications of calcium. However, little is

known about the genetic basis of tuber calcium content and its relationship to tuber quality. In

the present study, we estimated the correlations between tuber calcium, yield, chip quality,

internal quality and pitted scab in reciprocal populations derived from the cross of two

commercial varieties, Atlantic and Superior. Our results show significant genotype effects for

all traits evaluated indicating that the phenotypic differences observed between genotypes

have a genetic component. The broad-sense heritabilities of most traits differed among years

of evaluation and ranged between 0.19 to 0.85 for Atlantic x Superior and from 0.22 to 0.92

for Superior x Atlantic. Tuber calcium was negatively correlated to hollow heart, black spot

bruise and pitted scab. Nevertheless, tuber calcium was also negatively correlated to specific

gravity, yield, and chip yellowness; and positively correlated to chip color. Understanding the

correlations between tuber calcium and tuber quality traits as well as their heritabilities can

help potato breeders develop strategies for selection of new potato varieties with desired

phenotypes.

70

INTRODUCTION

Quantitative genetic analysis of phenotypic data helps bridge the gap between genes and

phenotypic traits. Some of the most important parameters measured in quantitative genetics

are the analysis of variances, heritabilities and correlations. The amount of variation is

measured and expressed as the variance. The analysis of variance (ANOVA) allows the

breeder to analyze data that depend on several kinds of effects, and these effects operate

simultaneously. This analysis helps breeders to decide which kinds of effects are important,

and to estimate these effects (Acquaah 2007). The assumptions of the data distribution to

apply ANOVA are the normality of the data, homogeneity of variances and independence of

observations (Falconer and Mackay 1996). Similarly, the analysis of deviance (ANODE)

measures the significance of the different effects influencing traits that follow a binomial

distribution (Jorgensen 1997). By partitioning phenotypic variance into its components one

can estimate the relative importance of the various determinants of the phenotype, in

particular the role of heredity versus environment (Falconer and Mackay 1996). Broad-sense

heritability can be defined as the ratio of the genotypic variance over the phenotypic variance

(Fehr 1987). The phenotypic variance is the sum of genotypic variance plus the residual

variance. The genotypic variance results from the differences among individuals and the

residuals variance results from the differences among genotypes caused by the failure to treat

each genotype exactly alike (Fehr 1987). The variance components can be estimated using a

multivariate analysis of variance (MANOVA), maximum likelihood (ML), restricted

maximum likelihood (REML), or Bayesian methods (Fisher 1918, Corbeil and Searle 1976,

Searle et al. 1992, Abney et al. 2000, Silva et al. 2013). The REML procedure is especially

important to deal with unbalanced datasets because by this procedure one can calculate the

71

estimators and their variances free of fixed effects (Corbeil and Searle 1976). In addition, the

estimation of genotypic correlations using REML has shown higher power of detection than a

MANOVA when there are missing data (Holland 2006).

Correlations are relationships between two or more variables or sets of variables and they

have three fundamental dimensions: significance, direction, and magnitude (Cohen and

Cohen 1983). Understanding the correlations between traits is very important information to

make decisions about selection methods in plant breeding. Correlations between characters

seriously complicate the prediction of response to phenotypic selection, because selection on

a particular trait produces not only a direct effect on the distribution of that trait in a

population, but also produces indirect effects on the distribution of correlated traits (Lande

and Arnold 1983). Correlations are due to pleiotropy, genes that affect two characters

simultaneously, but also due to linkage in crosses derived from divergent strains (Falconer

and Mackay 1996). In genetic studies, it is necessary to distinguish two causes of correlation

between characters: genetic and environmental (Falconer and Mackay 1996). Genetically

correlated traits respond to indirect selection pressures resulting from selection on other traits.

Indirect selection can be advantageous if the indirect character can be measured with more

accuracy than the primary trait (Wricke and Weber 1986).

Correlations among traits in potato have been reported for dormancy, emergence and dry

matter (Rashid and Carpena 1997); yield components (Ruiz de Galarreta et al. 2006); yield,

dry matter and plant characteristics (Felenji et al. 2011); tuber shape and weight (Bisognin et

al. 2012); yield, taste, tuber characteristics and mineral content (Flis et al. 2012). However,

most studies evaluating correlations only perform simple correlations using the phenotypic

data and evaluate one or few traits in a given population.

72

Previous research has demonstrated that in-season application of calcium increases tuber

calcium levels (Clough 1994, Kratzke and Palta 1986) and reduces the incidence of internal

defects (Tzeng et al. 1986, Olsen et al. 1996, Palta 1996, Kleinhenz et al. 1999, Ozgen et al.

2006, and Karlsson et al. 2006). For example, data from several cultivars collected over three

seasons showed that once the tuber calcium reaches more than 200ppm the incidence of

blackspot bruise is reduced dramatically (Karlsson et al. 2006). Furthermore, the incidence of

internal brown spot and sub-apical necrosis of sprouts was negatively correlated with tuber

peel calcium levels (Tzeng et al. 1986). These studies relating tuber calcium and internal

defects have been performed in a single variety or few varieties and not in segregating

populations. Therefore, the genetic basis of the relationship between calcium and internal

defects has not been explored yet.

In the present study we evaluated two reciprocal populations generated by crossing Atlantic,

a potato cultivar that has high specific gravity, high yield, light chip color, but high incidence

of internal defects and low calcium; with Superior, a potato cultivar that has low specific

gravity, low yield, dark chip color, but low internal defects and high calcium. The population

derived from these crosses contain clones that include all possible phenotypes in between the

parents for these traits. Our aims are to identify the main sources of phenotypic variance;

estimate the traits broad-sense heritabilities for tuber calcium, agronomic traits, internal

defects, chip quality and pitted scab; and estimate the degree of correlation between tuber

calcium and tuber quality traits. In addition, we discuss a strategy to select for reduced

internal defects and pitted scab by selecting for higher tuber calcium concentration, and also

discuss the effects of the correlated response to selection in case of highly correlated traits.

73


Populations, location and experimental design

Two reciprocal bi-parental populations were used in this study, the Atlantic x Superior (AxS)

and the Superior x Atlantic (SxA) populations that include 189 and 123 clones, respectively.

The trials were grown in a standard field and in a high disease pressure field in the Hancock

Agricultural Research Station, Central Wisconsin, USA during 2009 to 2012 seasons. A

standard field was used to evaluate tuber calcium, agronomic traits, internal defects, chip

quality as well as pitted scab incidence. In addition, a high disease pressure field was also

used to evaluate pitted scab incidence and severity. Herbicide, fungicide and insecticide were

used as needed during the season and irrigation was scheduled every other day in the absence

of rain. The experimental design was a complete randomized block design in the standard

field in 2011. All other trials used an incomplete randomized block design with 3

replications. The clones evaluated were randomly sampled from the populations based on

seed availability. Groups of 28 clones that included the two parents and 26 randomly chosen

clones were formed and randomized within replicates for the incomplete randomized block

design.

Phenotypic evaluations

Tuber calcium was evaluated using the method described by Kratzke and Palta (1986) using

two 1mm-thick slices per tuber from 8 to 10 tubers, only the medullary tissue was removed,

oven-dried, ground and ashed. Tuber calcium was measured in µg/g dry weight using an

74

atomic absorption spectrophotometer (Varian SpectrAA 55B). The total tuber yield was

evaluated immediately after harvest and expressed in tons per hectare (ton/ha). Specific

gravity was determined by the following formula: SG=Weightair/(Weightair-Weightwater),

using a basket containing approximately 2 kilograms of tubers on a potato weigher PW-2050

(Weltech International, UK). Chip color was evaluated immediately after harvest and

included several measurements such as visual ratings of chip color (CC) in a scale from 1 to 5

(light to dark), agtron values (AG), chip lightness (L), chip redness (A), and chip yellowness

(B). The AG measurements were obtained with an M-300 reflectance spectrophotometer

(Fillper Magnuson, Rent, Nevada, US). The L, A and B measurements were obtained using a

Hunter Lab D25L colorimeter (Hunter Associates Laboratory, Inc., Virginia, US). Enzymatic

browning (EB) was also measured one hour after the tuber medullary tissue was chopped

using a visual rating scale from 1 to 5 (light to dark). Internal defects and pitted scab were

also evaluated immediately after harvest. A-grade tubers (diameter > 4.8cm) were cut in

longitudinal sections to record the proportion of tubers with hollow heart (HH) and black spot

bruise (BB). Pitted scab incidence was measured in the standard field (PS) and the high

disease pressure field (PS-E) as the proportion of tubers with pitted lesions. Pitted scab

severity (SPS-E) was measured as the average number of pits per tuber in the high disease

pressure field. A detailed description of the phenotypic evaluations was presented in Chapter

2.

Significance of the sources of phenotypic variation

The analysis of variance (ANOVA) and the analysis of deviance (ANODE) were used to test

the significance of all variables affecting the traits under evaluation using multivariate models

with fixed effects that reflect the experimental design. Linear models and generalized linear

75

models were used for normally distributed data and binomial data, respectively. These

models were the following:

Model I: y = μ + G + R + ε (complete randomized block design model in a single year)

Model II: y = μ + G + B(R) + ε (incomplete randomized block design model in a single year)

Model III: y = μ + G + B(R(Y)) + GxY+ ε (multiple years)

Where, y is the observed trait measurement, μ is the overall mean, G is the genotype, R is the

replicate, B are the groups, B(R) is the group nested in replicates, B(R(Y)) is the group nested

in replicates and replicates nested in years, GxY is the interaction between genotypes and

years, and ε is the residual error. ANOVA and ANODE tables were obtained using an F-test

for normally distributed data and a Chi-square test for binomial data. Visual scales were used

as numeric variables.

Estimation of variance components and best linear unbiased predictions (BLUP)

Best linear unbiased predictions (BLUP) are predictions of breeding values obtained from

mixed models (Henderson, 1974) where variances and co-variances are estimated with

restricted maximum likelihood (REML) (Paterson and Thompson 1971, Corbeil and Searle

1976). The major properties of BLUP include the shrinkage of predictions towards the overall

mean, the possibility to analyze unbalanced data, and the ability to use information from the

relatives by exploiting genetic correlation arising from the pedigree and/or genetic

relatedness (Bernardo 2010). In our study, the property of BLUP and REML to work with

unbalanced data was exploited to estimate breeding values and variance components. BLUP

and variance components were obtained from the models used for ANOVA and ANODE but

76

considering all the variables as random effects. BLUP were estimated for each year and for

pooled data using a procedure without relatedness information. For normally distributed data,

linear mixed models were used; however, for incidence data, generalized linear mixed models

following a binomial distribution were used in the R package lme4 (Bates et al. 2011, Bates

2012) of R version 2.15.3 (R Development Core Team 2013).

Estimation of broad-sense heritability

Broad-sense heritability on an entry-mean basis was calculated using two approaches

depending on the type of variable studied. For normally distributed data, mean-basis broad-

sense heritability was calculated using the formula presented by Fehr (1987):

; where is broad-sense heritability, is the genotypic variance,

is the variance of the genotype x year interaction, is the residuals variance, y is the

number of years, and r is the number of replicates. For proportions data collected as

incidence traits such as the incidence of internal defects and pitted scab, mean-basis broad-

sense heritability in the logit link scale was calculated using a formula for proportions data

adapted from Nakagawa and Schielzeth (2010): ; where is

broad-sense heritability, is the genotype variance in the logit link scale, is the

variance of the genotype x year interaction in the link scale, , is the

residuals variance in the logit link scale, is the dispersion parameter which equals to 1 in a

binomial distribution, is the distribution specific variance for the logit model (Fahmeir

and Tutz 1994), y is the number of years, and r is the number of replicates.

77

Spearman’s rank correlation

The Spearman’s rank correlation (Spearman 1904) was used to evaluate the correlation

between trials when a trait was evaluated in more than one year. In addition, the Spearman’s

rank correlation of BLUP values were used to assess the genetic correlations between traits.

These correlations were calculated in a pair-wise manner using only genotypes that had been

evaluated for both traits. Spearman’s rank correlations were estimated for each reciprocal

population. Pairs of traits with -0.05< rS<0.05 were considered as uncorrelated.

Logistic and linear regression for the evaluation of tuber quality traits and pitted scab

in relationship with calcium

Logistic regression was used to study the relationship between incidence data, internal

defects and pitted scab with tuber calcium using a generalized linear model with a binomial

distribution due to the skewed nature of these data (See Chapter 2). For internal defects,

including incidence of hollow heart and blackspot bruise, the logistic regression used had the

following form: P{defect} = e /(1+e ) = 1/(1+e- ), where = 0 + 1*calcium + 2(if

medium) + 3(if large), is the log link function, 0, 1, 2, and 3 are the estimated

coefficients. This logistic regression was also used for the incidence of pitted scab but only

considering the tuber calcium variable. In addition a linear regression was used for total yield,

specific gravity, chip color measurements, and severity of pitted scab normalized using a

squared-root transformation. The linear regression had the form: y= 0 + 1*calcium, where

y is the response, 0 and 1 are the estimated coefficients. These relationships were studied

using the best linear unbiased predictions of the pooled evaluations with the highest

heritabilities. Barplots of probabilities for specific tuber calcium concentrations were plotted

78

in order to assess the relationships graphically. Statistical analysis and graphics were

performed using R version 3.0.0 (R Development Core Team 2013).


Genotypic effects for tuber calcium and tuber quality traits

The traits evaluated in our study include tuber calcium concentration, total yield, specific

gravity, enzymatic browning, chip color in agtron units, chip color using a visual rating, chip

lightness, chip redness, chip yellowness, incidence of hollow heart, blackspot bruise, pitted

scab in the standard field, pitted scab in the high disease field, and severity of pitted scab in

the high disease pressure field. The Spearman’s rank correlation analysis between years of

evaluation indicates that the correlations between ranks were positive and significant for the

visual rating of enzymatic browning, pitted scab incidence and severity evaluated in the high

disease pressure field. These traits showed correlations of 0.7, 0.69 and 0.67, for the two

years they were evaluated, respectively (Table 3.1). However, only hollow heart had

significant correlations between all years of evaluations; most traits showed significant

correlations between two out of three years of evaluation and for other traits such as

blackspot bruise all years were uncorrelated. This lack of correlation for blackspot bruise

incidence is an indication that performance of the populations were significantly different

between years and therefore further analysis and conclusions drawn from the evaluation of

this trait have to be made for each year independently. This analysis of correlations between

years of evaluation was also used to identify correlated years that could be pooled for further

global analysis.

79

The sources of variation were modeled according to the experimental design including:

Genotype, Replicate and Group for each year of evaluation and adding Year and Genotype x

Year interactions for pooled data. The ANOVA and ANODE indicate that all traits have

significant genotype effects (Tables 3.2 and 3.3). These results indicate that tuber calcium

and tuber quality traits have an important genetic component. In addition, significant replicate

and group effects were observed in most traits indicating that the variation within the field

had some influence on the phenotypic variation. Also, when data from multiple years was

analyzed, significant Genotype x Year interactions (GxY) were identified for all traits in at

least one of the reciprocal populations indicating that most quality traits of potato are

influenced by Genotype x Environment (GxE) interactions. Therefore, we can say that the

genotypes performance and their relative ranking varied from year to year. These results are

in agreement with previous reports; for example, Brown et al. (2012) also detected significant

GxE interaction for tuber calcium.

Previous research has also found significant genotypic variation in tetraploid segregating

populations for yield and specific gravity (Bradshaw et al. 2008; McCord et al. 2011a), chip

quality (Bradshaw et al. 2008), internal defects (Jansky and Thompson 1990; Henninger et al.

2000, McCord et al. 2011b) and common scab (Driscoll et al. 2009). Ours is the first report of

genetic variability for tuber calcium in a tetraploid bi-parental population. We have found

significant genotypic variation for tuber calcium and tuber quality traits that can be exploited

to select for cultivars with improved yield and specific gravity, improved chip quality and

internal quality, and tolerant to pitted scab.

80

Broad-sense heritabilities for tuber calcium, tuber quality traits, and pitted scab

The broad-sense heritabilities for tuber calcium and tuber quality traits were evaluated in

each reciprocal population per year of evaluation and using pooled data (Tables 3.2 and 3.3).

For the sake of discussion the values of heritabilities were classified as low (0.00-0.20),

moderately low (0.21-0.40), intermediate (0.41-0.60), moderately high (0.61-0.80), and high

(0.81-1.00). In general, the evaluated traits had heritabilities from moderately low to high

except for blackspot bruise that had a low heritability in 2011 (Tables 3.2 and 3.3). This

result indicates that most of the phenotypic variation for tuber calcium and tuber quality in

this population can be explained by differences between genotypes. Unfortunately, we cannot

separate the additive variance component from the total genotypic variance using bi-parental

populations but we know that the broad-sense heritability indicates the maximum value the

additive variance can reach. Therefore, the higher the broad-sense heritability, the most

reliable the conclusions we can draw about these traits.

The broad-sense heritability of tuber calcium ranged between moderately low to moderately

high with values between 0.44-0.61 for AxS and between 0.39-0.68 for SxA population

(Tables 3.2 and 3.3). Brown et al. (2012), estimated the broad-sense heritability of tuber

calcium concentration in 10 to 13 cultivars in a Tri-State, Western Regional, and Western

Regional Red/Specialty Trials obtaining values of 0.65, 0.37 and 0, respectively. Compared

to our results, the results reported were similar but we did not find values lower than 0.39 for

tuber calcium. The reason for obtaining not so low heritabilities in our case is that we are

using segregating populations of more than a hundred and fifty individuals whereas this other

study was performed in a limited number of unrelated clones. In addition, our reciprocal

populations are segregating for this trait showing a wide range of phenotypic variation

(Chapter 2). Furthermore, the experimental design used for our populations was an

81

incomplete randomized block design which is a powerful design to detect variation,

especially for traits like calcium that are influenced by soil conditions.

For tuber yield, the broad-sense heritability ranged between intermediate to moderately high

values between 0.66-0.85 for AxS and 0.51-0.82 for SxA (Tables 3.2 and 3.3). Haynes

(2001) reported a narrow-sense heritability for yield of 0.06-0.6 and a broad-sense heritability

of 0.56-0.76 (estimated using the reported variance components) in a diploid hybrid

population of S. phureja x S. stenotomum. These estimated broad-sense heritabilities were

comparable to our results.

For specific gravity, the broad-sense heritability was between low to moderately high with

values between 0.54-0.78 for AxS and 0.29-0.92 for SxA (Tables 3.2 and 3.3). A previous

report by Haynes et al. (2008) estimated the broad-sense heritability of specific gravity in a

diploid S. phureja x S. stenotomum population as 0.78, which is within the range of values for

broad-sense heritabilities that we found in our tetraploid populations. These results indicate

that our trials have been able to detect an important proportion of the genetic variation.

Compared to previous studies, we can say that a similar proportion of the phenotypic

variation for tuber yield and specific gravity is due to genotypic differences in diploid and

tetraploid potato.

The broad-sense heritability of enzymatic browning was moderately high or high with values

between 0.73-0.74 for AxS and 0.65-0.81 for SxA (Tables 3.2 and 3.3). A previous study

reported the broad-sense heritability value for enzymatic discoloration (ED), a similar

measurement to our enzymatic browning, was 0.84 for the CxD diploid population (Werij et

al. 2007). This value is close to the values estimated from our research. This result confirms

that using a visual rating scale to evaluate enzymatic browning was a good approach to detect

genetic variation and that the proportion of this genetic variation over the phenotypic

82

variation is similar in diploid and tetraploid potatoes. It is also interesting to note that

enzymatic browning had higher heritabilities than all other traits.

For chip color measured using a visual rating, the broad-sense heritability was between

intermediate and high with values between 0.42-0.83 for AxS and 0.54-0.83 for SxA (Tables

3.2 and 3.3). These results are similar to those reported by Haynes et al. (2008) who

estimated a narrow-sense heritability of 0.68 for this trait using a visual rating in a diploid

population. These results indicate that the evaluation of chip color using a visual rating has a

very important genetic component.

For the other measurements of chip color in the agtron and colorimetric scales, the values of

broad-sense heritability were similar as the visual rating for chip color. However, these

values were slightly lower for chip redness and chip yellowness indicating that these

parameters are much more influenced by the environment. The broad-sense heritability of

chip color in agtron values evaluated only the 2009 season was high, 0.81 for AxS and 0.82

for SxA (Tables 3.2 and 3.3). The broad-sense heritability of chip lightness was between

moderately high to high with values between 0.63-0.85 for AxS and 0.63-0.77 for SxA

(Tables 3.2 and 3.3). The broad-sense heritability of chip redness was between moderately

low to moderately high with values between 0.40-0.73 for AxS and 0.45-0.68 for SxA

(Tables 3.2 and 3.3). Chip yellowness broad-sense heritability was between moderately low

and high with values ranging between 0.29-0.71 for AxS and values between 0.62-0.77 for

SxA (Tables 3.2 and 3.3).

In addition, we estimated the estimated the broad-sense heritability of internal defects

including hollow heart and blackspot bruise. The broad-sense heritabilities for the incidence

of hollow heart were intermediate to moderately high. These values were between 0.59-0.74

for AxS and between 0.50-0.73 for SxA (Tables 3.2 and 3.3) which are slightly lower

83

compared to those reported by Henninger et al. (2000) for internal heat necrosis another type

of internal defect that had broad-sense heritabilities in the range of 0.83-0.88. The values of

broad-sense heritability observed for hollow heart indicate that an important proportion of the

phenotypic variance is due the genotype variation.

The broad-sense heritability of blackspot bruise incidence was between low and moderately

low within seasons with values between 0.19-0.30 for AxS and 0.22-0.41 for SxA (Tables

3.2 and 3.3). These values were low compared to previous reports; for example, Pavek et al.

(1993) found a narrow-sense heritability of 0.85 using a five-parent half diallel. Another

study reported broad-sense heritability of bruise as 0.73 and in this study bruise was

evaluated by subjecting tubers to impact damage using a drum in diploid hybrids (Hara-

Skrzypiec and Jakuczun 2013). In our study, we found low broad-sense heritability for bruise,

which is caused by the generally low incidence of this defect in our reciprocal populations.

The reason for the low defect may be that plots were hand-picked and that the incidence of

bruising was evaluated after regular handling of the plots without an external source of

impact damage. Thus, our harvest and handling method was not harsh enough to reveal the

genotypic variation between clones.

The broad-sense heritability of pitted scab incidence evaluated under standard conditions was

between moderately low to moderately high with values between 0.34-0.39 for AxS and 0.31-

0.65 for SxA (Tables 3.2 and 3.3). However, the broad-sense heritabilities for the incidence

and severity of pitted scab incidence evaluated under high disease pressure were higher.

These values were between 0.57-0.69 for AxS and 0.56-0.78 for SxA for the incidence of

pitted scab and values between 0.74-0.82 for AxS and 0.80-0.86 for SxA for the severity of

pitted scab (Tables 3.2 and 3.3). The broad-sense heritabilities estimated in the high disease

pressure field were in agreement with those reported previously by Haynes et al. (2010) for

84

the proportion of scabby tubers, 0.3 - 0.8; and for the severity of common scab measured as

and an area index, 0 - 0.78, and a lesion index, 0.49 - 0.90, for a set of 17 to 23 tetraploid

cultivars and advanced selections that represented a wide variety of genotypes. Our study

instead used segregating populations with all degrees of scab tolerance and obtained a similar

proportion of variance due to genotypic variation in the high disease pressure field. A

possible explanation of the low heritability for the pitted scab evaluation in the standard field

is that the conditions were variable and usually mild; therefore, the differences between the

progenies for scab tolerance were not evidenced or at least were not as high as the

environmental and residual variance.

In summary, most traits showed broad-sense heritabilities between moderately low and high,

except for black spot bruise that showed low broad-sense heritability in the 2011 evaluation.

Therefore, the phenotypic variation for all traits evaluated in this study has an important

genetic component.

Broad-sense heritability of internal quality traits and pitted scab in mild and harsh

environments

Based on the observed broad-sense heritabilities, we can say that for most traits the

proportions of the observed phenotypic variances that can be explained by the genotypic

differences is important with the exception of black spot bruise in 2011. The low broad-sense

heritability of black spot bruise is explained by the low incidence caused by hand-harvesting

and a gentle post-harvest manipulation that does not reveal the differences in impact

resistance between genotypes. Therefore, the variability in the amount of impact each plot

received may have obscured genotypic differences when damage is generally low. Results of

85

our study suggest that future studies of black spot bruise should be made subjecting each plot

to a uniform external source of impact that can reveal differences to withstand impact damage

among cultivars. Similarly, the higher heritabilities of the pitted scab evaluations in the high

disease pressure field indicate that clones have to be exposed to a harsh environment in order

to reveal the genotypic variation for tolerance. These results again suggest that future studies

trying to find variability for common scab tolerance should be made in fields where the

disease is known to occur or by inoculating the pathogen in the soil. Previous research has

used greenhouse evaluations where Streptomyces spp. were inoculated (Wiersema 1970,

Driscoll et al. 2009). These greenhouse evaluations were correlated to field grown

evaluations (Driscoll et al. 2009).

Correlations between tuber calcium and internal quality

In order to capture most genetic variation, we are using the best linear unbiased predictions to

estimate genetic correlations between traits. Spearman’s rank correlations were estimated for

all traits evaluated in this population in order to predict correlations regardless of the type of

trait distribution (Table 3.4). Tuber calcium was negatively correlated to the incidence of

hollow heart and black spot bruise in both reciprocal populations. The incidence of hollow

heart was correlated to tuber calcium with rs = -0.38 and rs = -0.35 in AxS and SxA

populations, respectively. This correlation was significant only in AxS population. This

negative genetic correlation between tuber calcium and hollow heart supports our hypothesis

that the incidence of hollow heart is reduced in cultivars with higher tuber calcium. The

development of hollow heart is caused by rapid growth after a variety of abiotic stresses such

as water and nutritional stress (Rex and Mazza 1989, Mc Cann and Stark 1989). Under rapid

growth situations, cell wall extension is correlated to growth rate (Taiz 1984). Cell wall

86

extension requires calcium as a component of cell walls. Therefore, if an adequate amount of

calcium is available, cell expansion and growth can adjust to the faster rate; otherwise, cell

necrosis occurs generating hollow heart.

Also, tuber calcium was negatively correlated to the incidence of black spot bruise with rs = -

0.79 in AxS and rs = -0.63 in SxA. This negative correlation between tuber calcium and black

spot bruise supports our hypothesis that impact damage is low in cultivars with high tuber

calcium. The color of blackspots is a result of phenols oxidation to the black pigment melanin

mediated by polyphenol oxidase (PPO) (Matheis 1987). Lærke et al. (2002a, 2002b)

explained the development of blackspots by the disruption of intracellular membranes as an

immediate effect of the impact; and the consequent contact between the PPO located in the

amyloplasts and its substrates located in the vacuole. This means that the structural properties

of the tuber cells are crucial for its resistance to blackspot formation caused by impact.

Calcium contributes to cellular structural properties such as stiffening of cell walls and cell

wall strength (Taiz 1984); and therefore, to the resistance to impact damage. Karlsson et al.

(2006) also found a negative relationship between tuber calcium content and the incidence of

black spot bruise when tubers of the same variety were subjected to calcium treatment. Our

results support the notion that there is a negative correlation between tuber calcium content

and the incidence of black spot bruise in a segregating population where supplemental

calcium has not been applied.

Correlations between tuber calcium and pitted scab

An early study by Horsfall et al. (1954) reported calcium in tuber peelings to be positively

correlated to common scab severity. Also, Davis et al. (1974) found that after gypsum

application to potatoes, calcium levels in tuber peel were positively correlated with scab

87

susceptibility. Later, Lambert and Manzer (1991) concluded that high calcium in the

periderm was a consequence rather than a cause of increased scab. Our study relates common

scab, specifically in terms of pitted scab lesions, incidence and severity with the natural

variation for tuber calcium concentration without external calcium application. Our results

indicate a negative correlation between tuber calcium and pitted scab incidence and severity

under high disease pressure (Table 3.4). Tuber calcium was negatively correlated to pitted

scab incidence and severity in the high disease pressure field with rs = -0.43 for both traits in

both reciprocal populations but significant only in SxA. However, tuber calcium was

positively correlated to pitted scab incidence in the standard field with rs = 0.21 and rs = 0.22

in AxS and SxA, correspondingly. However, these correlations were not significant.

Consequently, selecting for high tuber calcium under high disease pressure may be a good

approach to select varieties with resistance to pitted scab. As stated above, reports of higher

periderm calcium as a consequence of increased scab infection had been reported (Lambert

and Manzer 1991). We tested calcium in the medullary tissue of the tuber instead of the

periderm to avoid any change in the composition after contact with the pathogen. From our

experience evaluating calcium concentration in tubers, in general we expect that cultivars

with higher medullar calcium also have higher periderm calcium (Kleinhenz et al. 1999).

Higher tuber calcium contributes to strengthen cell wall structure and cell health (Palta 1996)

which could explain increased tolerance to Streptomyces spp. infection. In support of this

idea, higher tuber calcium was reported to provide higher tolerance to pathogens such as

Pectobacterium spp. that cause soft rot of potato tubers (McGuire and Kelman 1986).

88

Correlations of tuber calcium with agronomic traits, chip color measurements, and

enzymatic browning

Tuber calcium was negatively correlated to yield and specific gravity in both reciprocal

populations (Table 3.4). The correlation between tuber calcium and tuber yield was rs = -0.71

and rs = -0.60 in the AxS and SxA populations, respectively; and the correlation between

tuber calcium and specific gravity was rs = -0.66 and rs = -0.61 in the AxS and SxA

populations, correspondingly. These correlations were significant except for tuber calcium

and tuber yield in AxS. These results indicate that selecting cultivars for higher tuber calcium

may reduce yield and specific gravity in these populations if their correlation is due to

linkage. We have not found other evidence that indicates a cause-effect relationship.

In addition, the correlation between tuber calcium with the various measurements of chip

color and enzymatic browning varied between reciprocal populations. First, tuber calcium

was negatively correlated to agtron values (rs = -0.26 in AxS and SxA), chip lightness (rs = -

0.48 and rs = -0.53 in AxS and SxA), chip yellowness (rs = -0.22 and -0.37 in AxS and SxA)

but positively correlated to the visual rating of chip color (rs = 0.52 and rs = 0.55 in AxS and

SxA), and chip redness (rs = 0.43 and rs = 0.50 in AxS and SxA), and enzymatic browning (rs

= 0.55 and rs = 0.42 in AxS and SxA) in both reciprocal populations (Table 3.4). These

results indicate that selecting for high calcium, we may be indirectly selecting for darker

chips, reddish color, and higher enzymatic browning.

These correlations between tuber calcium and tuber quality could be explained by pleiotropy,

some genes controlling tuber calcium also control tuber quality, or linkage, some genes

controlling these traits are located closely in the genome. Another explanation could be a

cause-effect relationship supported by the previous reports on tuber calcium improving

internal quality of potato.

89

Correlations between different measurements of chip color and pitted scab

Chip color is the trait of most interest in a chipping variety. Therefore, it is important to know

what type of chip color measurement may work better for selection. We have evaluated

several types of chip color measurements including a visual rating of chip color, chip color in

agtron units, chip lightness, chip redness, and chip yellowness. The visual rating of chip color

was significantly correlated to most measurements of chip quality indicating that the visual

rating summarizes all the chip quality properties evaluated (Table 3.4). The visual rating of

chip color was negatively correlated to chip color in agtron units (rs = -0.08), chip lightness

(rs = -0.79) and chip yellowness (rs = -0.65); and positively correlated to chip redness (rs =

0.76), all significant at p <0.05. The negative correlation between the visual rating with chip

color in agtron units, chip lightness and chip yellowness is expected because higher visual

scores indicate darker chip color while higher agtron and L values indicate lighter chip color.

Furthermore, higher chip redness indicates the presence of dark spots in the chips and

therefore higher visual scores.

Chip color was also positively correlated to enzymatic browning, rs = 0.26 in AxS and rs =

0.25 in SxA, significant only for AxS population (Table 3.4). The visual color scale of

enzymatic browning is not a chip trait but enzymatic browning may influence the color of the

slice before it enters to the fryer and thus indirectly influence chip color.

The recommended measurement of chip color for selection is the evaluation of chip lightness,

because it is an objective measurement estimated by a colorimeter and this parameter was

significantly correlated to the other chip color measurements. A second option, when the

colorimeter is not available is the visual rating of chip color that is also significantly

correlated to all other chip color measurements. This rating does not require specialized

90

equipment and it is not as time consuming. Nevertheless, this visual rating is challenging due

to its subjective nature requiring training and experience of the evaluator for consistency.

Different types of measurements have been used to study incidence and severity of common

scab. Scab incidence has been studied by classifying tubers as diseased or healthy (Hiltunen

et al. 2005). Scab severity was evaluated by the type of lesion: superficial, raised or deep; and

percentage of scab lesion (Hiltunen et al. 2005). In addition, a visual rating or scab index has

also been used (Driscoll et al. 2009). A thorough review of common scab of potato was

presented by Dees and Wanner (2012). In our study pitted scab incidence was measured as

the proportion of tubers with pits and severity measured as the average number of pits per

tuber. All measurements of pitted scab were highly correlated in both reciprocal populations

(Table 3.4). The incidence of pitted scab in the standard field was significantly correlated to

the incidence of pitted scab in the high disease pressure field with rs = 0.74 in AxS and rs =

0.70 in SxA; and the severity of pitted scab in the high disease pressure field with rs = 0.64 in

AxS and rs = 0.62 in SxA. However, the highest correlations were observed between pitted

scab incidence and severity under high disease pressure, rs =0.93 in AxS and rs =0.95 in SxA,

suggesting that the mechanisms of resistance for incidence and severity of pitted scab might

be controlled by the same or related genetic mechanisms of plant-pathogen interaction.

Correlations between tuber quality traits and pitted scab with tuber calcium:

implications for selection

The relationship between tuber calcium and internal quality reported by previous studies

(Tzeng et al. 1986, Olsen et al. 1996, Palta 1996, Ozgen et al. 2006, Karlsson et al. 2006)

suggested that tuber calcium may be a good candidate for indirect selection for internal

91

quality without having to cut large numbers of tubers. The results presented in our study can

be used to answer the question that if there is a genetic correlation between tuber calcium and

internal defects and pitted scab, we can use this relationship to select for higher tuber calcium

and indirectly select for internal quality. This indirect selection would reduce the number of

tubers that have to be used in the evaluation and eliminate the need to cut several tubers. We

have found that high tuber calcium is negatively correlated to internal defects incidence such

as hollow heart and blackspot bruise, as well as yield, specific gravity, and chip lightness. A

consequence of these correlations would be that selecting for high tuber calcium may

generate cultivars with low incidence of internal defects but with low yield, low specific

gravity and dark chip color. One of the causes for correlated traits is linkage between the

genes controlling them or same gene controlling both traits (pleiotropy) and the other one is

linkage (Falconer and Mackay 1996). The negative correlation between tuber calcium and

hollow heart, blackspot bruise and incidence and severity of pitted scab are consistent with

previous studies that relate high tuber calcium concentration as a consequence of

supplemental calcium application with improved tuber quality. Our results suggest that

genotypes with naturally high tuber calcium concentrations are less likely to suffer from

internal defects. Tuber calcium appears to have a very important role in the prevention of

hollow heart, blackspot bruise, and pitted scab. In addition, the application of supplemental

calcium may reduce internal defects by increasing tuber calcium content. Future studies in the

reciprocal populations of Atlantic and Superior should determine whether there is genetic

variation for the increase in tuber calcium as an effect of calcium supplementation.

Light chip color, high specific gravity and high yield are desirable traits in a chipping variety;

however, these must be accompanied by satisfactory internal quality and disease resistance.

92

We can avoid obtaining good chipping varieties that will not be adopted due to internal

quality and scab issues by selecting for all these traits simultaneously at early stages of the

breeding process in large populations.

Relationship of tuber quality traits and pitted scab with tuber calcium and tuber size

The relationship between internal defects and tuber calcium was evaluated in both reciprocal

populations using a logistic regression that related tuber calcium concentration and tuber size

classified in small, medium and large categories with the incidence of internal defects

expressed as proportions (Figure 3.1). The datasets used in this analysis were the same used

to study the genetic correlations between traits. The probability of hollow heart was similar

for small and medium tubers but significantly higher in genotypes with large tubers. Also, the

probability of hollow heart decreased at higher calcium concentrations in all tuber size

categories (Figure 3.1) following the equations indicated in Table 3.5. In addition, the

probability of blackspot bruise was also similar for small and medium tubers but significantly

higher in genotypes with large tubers. This relationship may be explained because large

tubers have larger surface area that can be affected by impact; however, Skrobacki et al.

(1989) demonstrated that larger mass was not correlated to blackspot bruise. As well, the

probability of blackspot bruise decreased at higher calcium concentrations in all tuber size

categories (Figure 3.1) following the equations indicated in Table 3.5. These results are in

agreement with previous reports that found the incidences of internal defects can be reduced

by tuber calcium concentration (Karlsson et al. 2006) and increased with tuber size (Jansky

and Thompson 1990). The plots for the relationship of calcium and pitted scab incidence and

severity reveal differences between reciprocal populations for these traits, a higher positive

effect of calcium on tolerance to pitted scab is observed in Superior x Atlantic (Figure 3.2).

93

In our study, we are calculating this relationship in terms of a numerical estimation of the

effects of each variable in these reciprocal populations. Only internal defects were evaluated

by their relationship with both tuber calcium and tuber size, all other traits were tested for

their relationship with tuber calcium. A logistic regression was also applied to determine the

probability of pitted scab in relation to tuber calcium. The results of these analyses indicated

that higher tuber calcium decreased the probability of getting tubers with pitted scab under

the high disease field conditions (Figure 3.2); however, the probability of having tubers with

pitted scab in the standard field was positively but not significantly correlated with tuber

calcium (Table 3.4). Linear regressions were used to evaluate the relationship between tuber

calcium with severity of pitted scab (square-root transformed). Pitted scab severity decreased

at higher calcium concentrations in the tuber (Figure 3.2). In addition, total yield, specific

gravity, chip lightness and chip yellowness showed a decrease at higher calcium

concentrations in the tubers (Figures 3.3 and 3.4). These results indicate that, in this

population, clones with higher tuber calcium tend to have low tuber yield and specific gravity

as well as bad chip quality.

Selection of promising clones from the reciprocal populations of Atlantic x Superior

Promising clones were selected based on their performance using a culling method that

selected first for chip color, then for incidence of hollow heart and other internal defects, next

for common scab, and finally for total yield. Clones were ranked for each trait sequentially.

Only clones with lighter chip color compared to Atlantic, less hollow heart than Atlantic; and

less than 10% incidence of pitted scab in the high disease pressure field were selected as

promising clones. Finally, clones with yields less than 35 tons/ha were excluded. Four

promising clones were identified using the pooled data with the highest heritability, the same

94

used for the analysis of correlations (Table 3.6). Two promising clones were identified in the

Atlantic x Superior population (B-032 and B-167), and two more from the Superior x

Atlantic population (C-062 and C205). All clones selected as promising have L values higher

than 50; values lower than 40 are considered unacceptable (Parkin and Shwobe 1981); and

higher tuber calcium compared to Atlantic (Table 3.6). In addition, their external appearance

and size was comparable to the parents (Figure 3.5). The identification of these promising

clones supports our initial hypothesis that we could improve internal quality by crossing

Atlantic with the high calcium cultivar Superior and obtain Atlantic-like cultivars. However,

these clones are not as high yielding as Atlantic due to the high correlation between tuber

yield and tuber calcium. Higher number of progenies of the reciprocal populations of Atlantic

and Superior might be used to find recombinant genotypes that combine the good tuber

quality of Superior and the high yield and good chipping quality of Atlantic.

CONCLUSIONS

From the evaluation of the reciprocal populations of Atlantic x Superior for broad-sense

heritability, genetic correlations and the estimation of relationships between tuber calcium,

tuber quality and pitted scab tolerance, we can draw the following conclusions:

1. In this study, we demonstrated that the phenotypic variation for tuber calcium, tuber

quality traits, and pitted scab observed in the reciprocal populations of Atlantic and

Superior has an important genetic component due to the significant genotypic effects

for all traits. These genotypic variations can be exploited to select for cultivars with

95

improved yield and specific gravity, improved chip quality and internal quality, and

tolerance to pitted scab.

2. The data also indicate that tuber quality traits, pitted scab tolerance and tuber calcium

are influenced by environmental effects, including the year of evaluation and the

spatial distribution within the field as well as significant Genotype x Environment

(year) interactions for all traits in at least one the reciprocal populations.

3. The broad-sense heritabilities of most traits varied from year to year and ranged

between 0.19 to 0.85 for Atlantic x Superior and from 0.22 to 0.92 for Superior x

Atlantic.

4. The highest broad-sense heritabilities were observed for tuber yield, followed by

pitted scab severity and incidence and enzymatic browning.

5. Black spot bruise had the lowest broad-sense heritabilities. This can be explained by

the low overall blackspot bruise incidence caused by hand-harvesting and a gentle

post-harvest manipulation that did not reveal the differences in impact resistance

between genotypes.

6. Pitted scab evaluations of incidence and severity in the high disease pressure field had

higher heritabilities compared to the pitted scab incidence evaluation in the standard

field indicating that clones have to be exposed to a harsh pathogen pressure in order to

reveal the genotypic variation for tolerance.

7. Most traits showed significant correlations between two out of three years of

evaluation and other traits such as blackspot bruise were uncorrelated for all years.

Only for hollow heart, the rankings of all years of evaluations were correlated.

Correlated years were pooled for further global analyses.

96

8. Negative Spearman’s rank correlations between the best linear unbiased predictions

(BLUP) for hollow heart, blackspot bruise as well as pitted scab incidence and

severity with tuber calcium were identified. These genetic correlations suggest that

some genes that control these traits might be the same (pleiotropy), closely linked

(linkage), or a cause-effect relationship.

9. Tuber calcium was also negatively correlated to yield, specific gravity and chip

quality. The use of tuber calcium for indirect selection of improved tuber quality may

be performed with caution by evaluating large populations in order to identify the

desired phenotypes.

10. Most chip color measurements were significantly correlated. Our results show that

chip lightness and the visual rating of chip color are correlated to all other

measurements of chip color suggesting that these traits can be used to select for chip

quality.

11. High correlations were observed between pitted scab incidence and severity under

high disease pressure suggesting that the mechanisms of tolerance to both these traits

might be controlled by the related genetic mechanisms of plant-pathogen interaction.

12. In addition, four promising clones that have good chipping quality, good internal

quality, reduced pitted scab incidence and severity as well as acceptable yield

compared to Atlantic were selected from the reciprocal populations.

BIBLIOGRAPHY

Abney, M., M.S. McPeek and C. Ober. 2000. Estimation of variance components of quantitative traits in inbred populations. The American Journal of Human Genetics 66: 629-650.

97

Acquaah, 2007. Principles of plant genetics and breeding. Oxford, UK: Blackwell Publishing. Bates, D., M. Maechler and B. Bolker. 2011. Linear mixed-effects models using S4 classes. R version 0.999375-42. http://lme4.r‐forge.r‐project.org/. Accessed on November 2012. Bates, D. 2012. Linear mixed model implementation in lme4. University of Wisconsin – Madison. http://cran.r‐project.org/web/packages/lme4/vignettes/Implementation.pdf. Accessed on November 2012. Bernardo, R. 2010. Chapter 10: Best Linear Unbiased Prediction. In Breeding for Quantitative Traits in Plants. Second Edition, 211–238. Minnnesota, US: Stemma Press. Bisognin, D.A, M.H. Rigão, S.J. Lopes, and L. Storck. 2012. Heritability and correlation among potato tuber traits. Crop Breeding and Applied Biotechnology 12: 215-219. Bradshaw, J.E., C.A. Hackett, B. Pande, R. Waugh, G.J. Bryan. 2008. QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Theor Appl Genet 116: 193–211. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller Jr. 2012. Stability and broad-sense heritability of mineral content in potato: Calcium and magnesium. American Journal of Potato Research 89: 255-261. Cohen, J. and P. Cohen. 1983. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (Second Edition). Hillsdale, NJ: Erlbaum. Clough, G.H. 1994. Potato tuber yield, mineral concentration, and quality after calcium fertilization. Journal of the American Society of Horticultural Science 119: 175-179. Corbeil, R.R., and S.R. Searle. 1976. Restricted maximum likelihood (REML) estimation of variance components in the mixed model. Technometrics 18: 31-38. Davis, J.R., J.E. Garner, and R.H. Callihan. 1974. Effects of gypsum, sulfur, terraclor, and terraclor super-X for potato scab control. American Journal of Potato Research 51: 35-43. Dees, M.W., and L.A. Wanner. 2012. In Search of Better Management of Potato Common Scab. Potato Research 55: 249-268. Driscoll, J., J. Coombs, R. Hammerschmidt, W. Kirk, L. Wanner, and D. Douches. 2009. Greenhouse and field nursery evaluation for potato common scab tolerance in a tetraploid population. American Journal of Potato Research 86: 96–101. Fahmeir L., and G. Tutz, 1994. Multivariate Statistical Modelling Based on Generalized Linear Models. München, Germany: Springer Series in Statistics. Falconer, D.S., and T.F.C. Mackay. 1996. Introduction to Quantitative Genetics, Fourth Edition. Essex, UK: Longman, Harlow.

98

Fehr, W. 1987. Principles of Cultivar Development, vol1: Theory and Techniques. Macmillan Publishing Co., New York, USA. Felenji, H., S. Aharizad, G.R. Afsharmanesh, and M. Ahmadizadeh. 2011. Evaluating correlation and factor analysis of morphological traits in potato cultivars in fall cultivation of jiroft area. American-Eurasian Journal of Agricultural & Environmental Sciences 11: 679-684. Fisher R.A. 1918. The correlation between relatives on the supposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh 52: 399–433 Flis, B., E. Zimnoch-Guzowska, and D. Mankowski. 2012. Correlations among yield, taste, tuber characteristics and mineral contents of potato cultivars grown at different growing conditions. Journal of Agricultural Science 4: 197-207. Haynes, K. G. 2001. Variance components for yield and specific gravity in a diploid potato population after two cycles of recurrent selection. Potato Research 78: 69-75. Haynes, K. G. 2008. Heritability of chip color and specific gravity in a long-day adapted Solanum phureja–S. stenotomum population. American Journal of Potato Research 85: 361-366. Haynes, K. G., L.A. Wanner, C.A. Thill, J.M. Bradeen, J. Miller, R.G. Novy, J.L. Whitworth, D.L. Corsini and B.T. Vinyard. 2010. Common scab trials of potato varieties and advanced selections at three US locations. American Journal of Potato Research 87: 261-276. Hara-Skrzypiec, A., and H. Jakuczun. 2013. Diploid Potato Hybrids as Sources of Resistance to Blackspot Bruising. American Journal of Potato Research, 1-9. DOI 10.1007/s12230-013-9319-y. Henderson, C.R. 1974. General flexibility of linear model techniques for sire evaluation. Journal of Dairy Science 57: 963–972. Henninger, M.R., S.B. Sterrett, and K.G. Haynes. 2000. Broad-sense heritability and stability of internal heat necrosis and specific gravity in tetraploid potatoes. Crop science. 40: 977–984.

Hiltunen, L.H., A. Weckman, A. Ylhäinen, H. Rita, E. Richter, and J.P.T. Valkonen. 2005. Responses of potato cultivars to the common scab pathogens, Streptomyces scabies and S. turgidiscabies. Annals of Applied Biology 146: 395–403. Holland, J.B. 2006. Estimating genotypic correlations and their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop Science 46: 642-654. Horsfall, J.G., J.P. Hollis, and H.G.M. Jacobson. 1954. Calcium and potato scab. Phytopathology 44: 19-24.

99

Jansky, S.H. and Thompson D.M. 1990. Expression of Hollow Heart in segregating tetraploid potato families. American Potato Journal 67: 695–793. Jorgensen, B. 1997. The theory of dispersion models.Monographs on Statistics and applied probability 76. London, UK: Chapman and Hall. Karlsson, B.H., J.P. Palta and P.M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. Hort Science 41: 1213-1221. Kleinhenz, M.D., J.P. Palta, C.C. Gunter, and K.A. Kelling. 1999. Impact of source and timing of calcium and nitrogen applications on Atlantic potato tuber calcium concentrations and internal quality. Journal of the American Society for Horticultural Science 124: 498–506. Kratzke, M.G. and J.P Palta. 1986. Calcium uptake by potato tubers: Role of the basal roots. Hort Science 21: 1022-1024. Lærke, P.E., J. Christiansen, M N. Andersen, and B. Veierskov. 2002a. Blackspot bruise susceptibility of potato tubers during growth and storage determined by two different test methods. Potato Research 45: 187-202. Lærke, P.E., J. Christiansen, and B. Veierskov 2002b. Colour of blackspot bruises in potato tubers during growth and storage compared to their discolouration potential. Postharvest Biology and Technology 26: 99-101. Lambert, D.H., and F.E. Manzer. 1991. Relationship of calcium to potato scab. Phytopathology 81: 632-636. Lande, R., and S.J. Arnold. 1983. The measurement of selection on correlated characters. Evolution 37: 1210-1226. Matheis, G. 1987. Polyphenol oxidase and enzymatic browning of potatoes (Solanum tuberosum). II. Enzymatic browning and potato constituents. Chem. Mikrobiol. Technol. Lebensm. 11: 33–41. Mc Cann, L.R., and J.C. Stark, 1989. Irrigation and nitrogen management effects on Potato Brown Center and Hollow Heart. HortScience 24: 950-952. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011a. Linkage Mapping and QTL Analysis of Agronomic Traits in Tetraploid Potato (Solanum tuberosum subsp. tuberosum). Crop Science 51: 771-785. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011b. QTL mapping of internal heat necrosis in tetraploid potato. Theoretical and Applied Genetics 122: 129–142. McGuire, R. and A. Kelman. 1986. Calcium in potato tuber cell walls in relation to tissue maceration by Erwinia carotovora pv. atroseptica. Physiology and Biochemistry 7: 401-406.

100

Nakagawa, S. and H. Schielzeth. 2010. Repeatability for Gaussian and non-Gaussian data: A practical guide for biologists. Biological Reviews 85: 935–956. Olsen, N.L., L.K. Hiller, and L.J. Mikitzel. 1996. The dependence of internal brown spot development upon calcium fertility in potato tubers. Potato Research 39: 165-178. Ozgen, S., B.H. Karlsson and J.P. Palta. 2006. Response of potatoes (cv. ‘Russet Burbank’) to supplemental calcium applications under field conditions. Tuber calcium, yield, and incidence of brown spot. American Journal of Potato Research 83: 195-204. Palta, J.P. 1996. Role of calcium in plant responses to stresses: Linking basic research to the solution of practical problems. HortScience 31: 51-57.

Parkin, K.L., and M.A. Schwobe. 1990. Effects of low temperature and modified atmosphere on sugar accumulation and chip color in potatoes (Solanum tuberosum). Journal of Food Science 55: 1341-1344. Paterson, H.D., and R. Thompson, 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58: 545–554. Pavek, J.J., C.R. Brown, M.W. Martin, and D.L. Corsisni. 1993. Inheritance of blackspot bruise resistance in potato. American Journal of Potato Research 70: 43-48. R Development Core Team. 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R‐project.org. Rashid, M.H.O., and A.L. Carpena. 1997. Genetic variability for tuber dormancy and associated traits in potato (Solanum tuberosum L.). Philippine Journal of Crop Science 22: 125-130. Rex, B.L., and G. Mazza. 1989. Cause, control and detection of hollow heart in potatoes: A review. American Journal of Potato Research 66: 165-183. Ruiz de Galarreta, J.I., B. Ezpeleta, J. Pascualena, and E. Ritter. 2006. Combining ability for yield components in early generations of plant breeding. Plant Breeding 125: 183-186. Searle, S.R., G. Casella, and C.E. McCulloch. 1992. Variance components. Wiley Series in Probability and Statistics Vol. 391. New Jersey, USA: Wiley-Interscience. 528 pages Silva, E., J.M.S. Viana, V.R., Faria, and M.D.V. de Resende. 2013. Bayesian inference of mixed models in quantitative genetics of crop species. Theoretical and Applied Genetics 126: 1749-1761. Spearman C. 1904. The proof and measurement of association between two things. The American Journal of Psychology 15: 72–101.

101

Taiz, L. 1984. Plant cell expansion: Regulation of cell wall chemical properties. Annual Reviews of Plant Physiology 35: 585-657. Tzeng, K.C., A. Kelman, K.E. Simmons, and K.A. Kelling. 1986. Relationship of calcium nutrition to internal brown spot of potato tubers and sub-apical necrosis of sprouts. American Journal of Potato Research 63: 87-97. Werij, J.S., B. Kloosterman, C. Celis-Gamboa, C.R. de Vos, T. America, R.G. Visser, and C.W. Bachem. 2007. Unravelling enzymatic discoloration in potato through a combined approach of candidate genes, QTL, and expression analysis. Theor Appl Genet, 115:245–252. Wiersema, H.T. 1970. A reliable method for testing scab resistance in the green house. In Proceedings of the 4th Triennial Conference of the European Association for Potato Research. Brest, France. 8-13 Sept. 1969. 210–212. Paris: Inst. Natl. de la Recherché Agronomique Publ. 70-5. Wricke, G., and E. Weber. 1986. Quantitative Genetics and Selection in Plant Breeding. Walter de Gruyter, Berlin, Germany. Page 167.

102

TABLES

Table 3.1. Spearman’s rank correlation between years of evaluation for total yield (TY), specific gravity (SG), visual rating of chip color (CC), chip color in agtron units (AG), chip lightness (L), chip redness (A), chip yellowness, (B) for tuber calcium (TC), incidences of hollow heart (HH), black spot bruise (BB), pitted scab in the standard field (PS), pitted scab in the high disease pressure field (PS-E), and severity of pitted scab in the high disease pressure field (SPS-E) in the reciprocal populations of Atlantic x Superior and Superior x Atlantic.

Trait Field Spearman’s rank correlation Years to pool 2009-2010 2010-2011 2009-2011 2011-2012

TC C 0.25** 0.22 0.01 2009, 2010 TY C 0.40 *** 0.2 0.07 2009, 2010 SG C 0.38*** 0.35* 0.23 2009, 2010 and 2010, 2011 EB C 0.70*** 2010, 2011 CC C 0.29*** 0.47** 0.18 2009, 2010 and 2010, 2011 L C 0.41* 2010, 2011 A C 0.26 - B C 0.47* 2010, 2011

HH C 0.59*** 0.30* 0.32* 2009, 2010, 2011 BB C 0.11 0.13 0.19 - PS C 0.32*** 0.01 0.03 2009, 2010

PS-E E 0.69*** 2011, 2012 SPS-E E 0.67*** 2011, 2012

C=standard field, E=high disease pressure field. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***)

103 Table 3.2. Sources of phenotypic variation, best linear unbiased predictions and heritabilities for total yield (TY), specific gravity (SG), enzymatic browning (EB), chip color in agtron units (AG), chip color visual rating (CC), chip lightness (L), redness (A), yellowness (B), tuber calcium (TC), incidences of hollow heart (HH), blackspot bruise (BB), pitted scab in the standard field (PS), pitted scab in the high disease pressure field (PS-E), and pitted scab severity in the high disease pressure field (SPS-E) in the Atlantic x Superior population.

Trait Years G Y GxY R B Mean Min Max H2 TC 2009 *** *** *** 156.24 123.77 208.95 0.61

2010 *** *** *** 192.17 148.24 236.15 0.59 2011 * *** 268.37 234.83 324.81 0.44

2009, 2010 *** *** *** *** *** 176.15 148.34 215.91 0.61 TY 2009 *** *** *** 51.62 22.69 78.10 0.85

2010 *** ** *** 36.87 11.23 61.55 0.85 2011 *** NS 40.21 29.39 63.64 0.77

2009, 2010 *** *** *** *** ** 44.12 26.52 61.50 0.66 SG 2009 *** NS NS 1.074 1.058 1.088 0.68

2010 *** *** *** 1.068 1.056 1.079 0.76 2011 *** NS 1.072 1.060 1.087 0.78

2009, 2010 *** *** *** *** . 1.071 1.063 1.077 0.54 2010, 2011 *** *** *** ** *** 1.070 1.063 1.076 0.54

EB 2010 *** . * 2.08 1.20 3.70 0.73 2011 *** NS 1.94 1.24 3.46 0.74

2010, 2011 *** NS * * * 2.06 1.27 3.41 0.74 AG 2009 *** NS NS 42.83 35.71 50.23 0.81 CC 2009 *** * NS 3.47 3.08 3.89 0.48

2010 *** *** NS 3.36 2.37 4.22 0.62 2011 *** NS 2.10 0.78 3.53 0.83

2009, 2010 *** ** *** *** NS 3.40 2.97 3.81 0.42 2010, 2011 *** *** ** *** NS 2.77 1.83 3.42 0.64

L 2010 *** *** NS 45.43 36.63 52.34 0.67 2011 *** NS 55.73 48.73 62.39 0.85

2010, 2011 *** *** ** *** NS 50.38 44.32 55.80 0.63 A 2010 *** NS NS 9.36 7.88 10.94 0.40

2011 *** NS 3.30 0.50 5.94 0.73 B 2010 *** * NS 18.82 13.49 21.70 0.67

2011 *** NS 22.98 21.00 24.80 0.81 2010, 2011 *** *** *** ** NS 20.85 19.81 21.57 0.29

HH 2009 *** *** *** 6.76 0.73 50.65 0.59 2010 *** *** *** 1.89 0.24 49.35 0.74 2011 *** NS 1.30 0.28 25.29 0.73

2009, 2010 *** *** *** *** *** 3.66 0.44 36.06 0.67 2009, 2010, 2011 *** *** *** *** *** 2.86 0.45 25.94 0.72

BB 2009 *** *** *** 3.95 1.23 18.50 0.30 2010 *** NS ** 0.88 0.51 4.31 0.30 2011 *** NS 2.35 1.39 6.18 0.19

PS 2009 *** *** *** 3.45 0.69 13.81 0.34 2010 *** *** *** 11.82 1.03 64.90 0.49 2011 *** *** 5.72 1.46 27.40 0.38

2009, 2010 *** *** *** *** *** 6.68 1.37 18.20 0.42 PS-E 2011 *** *** *** 26.87 4.17 74.81 0.57

2012 *** *** *** 24.85 3.41 77.06 0.652011, 2012 *** *** *** *** *** 14.29 1.69 80.74 0.69

√SPS-E 2011 *** ** NS 0.80 0.05 3.45 0.74 2012 *** * . 0.31 0.01 2.32 0.80

2011, 2012 *** *** * *** NS 0.53 0.03 2.81 0.82 G=Genotype, Y=year, GxY=Genotype x Year, R=Replicate, B= Group. Mean, Min, Max are the mean, minimum and maximum BLUP. H2 =broad-sense heritability.

104 Table 3.3. Sources of variance and deviance, best linear unbiased predictions and heritabilities for total yield (TY), specific gravity (SG), enzymatic browning (EB), chip color in agtron units (AG), visual rating of chip color (CC), chip lightness (L), redness (A), yellowness (B), tuber calcium (TC), incidences of hollow heart (HH), black spot bruise (BB), pitted scab in the standard field (PS), pitted scab in the high disease pressure field (PS-E), and pitted scab severity in the high disease pressure field (SPS-E) in the Superior x Atlantic population.

Trait Years G Y GxY R B Mean Min Max H2 TC 2009 ** *** ** 159.36 136.00 179.48 0.45

2010 *** *** *** 195.44 133.81 258.48 0.68 2011 * *** 285.89 268.83 309.63 0.39

2009, 2010 *** *** *** *** *** 179.30 148.34 215.91 0.50 TY 2009 *** . * 49.34 26.76 66.65 0.82

2010 *** * *** 36.36 19.24 62.83 0.80 2011 ** NS 42.06 28.19 50.54 0.51

2009, 2010 *** *** *** * *** 43.21 32.13 54.38 0.53 SG 2009 *** ** NS 1.074 1.056 1.087 0.72

2010 *** *** *** 1.068 1.056 1.082 0.77 2011 *** NS 1.068 1.060 1.087 0.92

2009, 2010 *** *** *** *** ** 1.071 1.067 1.075 0.29 2010, 2011 *** NS NS *** *** 1.068 1.056 1.082 0.92

EB 2010 *** ** ** 1.91 1.32 3.05 0.65 2011 ** NS 2.05 1.46 2.83 0.82

2010, 2011 *** NS NS ** ** 1.95 1.45 2.92 0.71 AG 2009 *** NS NS 42.61 31.72 49.49 0.82 CC 2009 *** NS NS 3.51 2.97 4.47 0.64

2010 *** . NS 3.41 2.70 4.04 0.50 2011 *** * 2.06 1.05 2.84 0.83

2009, 2010 *** NS NS . NS 3.45 2.92 4.11 0.54 2010, 2011 *** *** . NS NS 2.76 2.01 3.43 0.70

L 2010 *** NS NS 44.80 37.66 50.67 0.63 2011 *** NS 55.70 52.52 59.01 0.67

2010, 2011 *** *** NS NS NS 50.37 43.25 56.22 0.77 A 2010 ** NS NS 9.30 8.10 10.55 0.45

2011 *** NS 3.35 1.79 4.46 0.68 B 2010 *** NS NS 18.87 15.70 21.65 0.62

2011 *** NS 23.06 22.53 23.73 0.62 2010, 2011 *** *** NS NS NS 20.89 17.64 23.74 0.77

HH 2009 *** *** *** 5.01 0.31 42.44 0.70 2010 *** *** *** 1.65 0.31 52.29 0.73 2011 *** NS 1.07 0.36 10.13 0.63

2009, 2010 *** *** *** *** *** 2.78 0.61 15.54 0.50 2009, 2010, 2011 *** *** *** *** *** 2.40 0.70 10.53 0.53

BB 2009 *** ** ** 4.41 2.09 13.72 0.22 2010 *** NS . 0.95 0.44 6.65 0.41 2011 *** NS 1.77 0.92 4.15 0.31

PS 2009 *** *** *** 3.30 0.67 19.00 0.42 2010 *** *** *** 12.34 1.58 55.45 0.48 2011 *** *** 2.95 0.53 21.02 0.65

2009, 2010 *** *** *** *** *** 6.93 2.64 14.86 0.31 PS-E 2011 *** *** *** 24.85 3.41 77.06 0.65

2012 *** *** *** 15.38 1.81 75.86 0.562011, 2012 *** *** *** *** *** 19.42 2.00 66.91 0.78

√SPS-E 2011 *** ** NS 0.73 0.03 4.31 0.80 2012 *** * NS 0.32 0.01 2.28 0.83

2011, 2012 *** *** * *** NS 0.51 0.02 3.04 0.86 G=Genotype, Y=year, GxY=Genotype x Year, R=Replicate, B= Group. Mean, Min, Max are the mean, minimum and maximum BLUP. H2 =broad-sense heritability.

105 Table 3.4. Pair-wise Spearman’s rank correlations between best linear unbiased predictions in the Atlantic x Superior reciprocal populations for tuber calcium (TC), tuber yield (TY), specific gravity (SG), enzymatic browning (EB), chip color in agtron units (AG), visual rating of chip color (CC), chip lightness (L), chip redness (A), and chip yellowness (B), incidences of hollow heart (HH), blackspot bruise (BB), pitted scab in the standard field (PS), pitted scab incidence in the high disease pressure field (PS-E), and pitted scab severity in the high disease pressure field (SPS-E) using the datasets with the highest heritabilities from the 2009-2012 evaluations in Hancock, Wisconsin, USA.

Superior

x Atla

ntic200

9, 20

10200

9, 20

10200

9, 20

10, 2

011

2009,

2010

, 201

1

2009

2010,

2011

2011

2010,

2011

2010,

2011

2009,

2010

, 201

1

2010

2010

2011,

2012

2011,

2012

Atlantic x Superior TC TY SG EB AG L A B CC HH BB PS PS-E SPS-E

2009, 2010 TC -0.60 -0.61 0.42 -0.26 -0.53 0.50 -0.37 0.55 -0.35 -0.63 0.22 -0.43 -0.43

2009, 2010 TY -0.71 0.31 -0.57 0.12 0.47 -0.28 0.08 -0.18 -0.03 0.37 -0.22 0.13 0.15

2009, 2010, 2011 SG -0.66 0.32 -0.80 0.00 0.66 -0.49 0.54 -0.61 0.66 0.46 0.19 0.78 0.86

2009, 2010, 2011 EB 0.55 -0.38 -0.87 -0.03 -0.53 0.12 -0.40 0.25 -0.50 -0.50 -0.37 -0.75 -0.75

2009 AG -0.26 0.48 0.11 -0.37 0.35 0.16 0.65 -0.05 0.48 -0.09 0.06 0.14 -0.07

2010, 2011 L -0.48 0.48 0.66 -0.57 0.49 -0.60 0.83 -0.83 0.50 -0.12 0.27 0.60 0.65

2011 A 0.43 -0.38 -0.51 0.21 0.19 -0.62 -0.23 0.80 -0.23 -0.02 0.15 -0.18 -0.42

2011 B -0.22 -0.04 0.32 -0.12 0.43 0.61 -0.12 -0.65 0.68 -0.17 0.47 0.68 0.60

2010, 2011 CC 0.52 -0.19 -0.57 0.26 -0.08 -0.79 0.76 -0.65 -0.33 0.08 -0.23 -0.57 -0.68

2009, 2010, 2011 HH -0.38 0.19 0.80 -0.95 0.40 0.62 -0.14 0.23 -0.31 0.27 0.35 0.62 0.60

2009 BB -0.79 0.29 0.61 -0.38 -0.12 0.40 -0.64 0.16 -0.74 0.31 -0.10 0.37 0.33

2010 PS 0.21 -0.43 0.16 -0.33 0.24 0.29 0.07 0.19 -0.24 0.57 0.12 0.70 0.62

2011, 2012 PS-E -0.43 -0.02 0.72 -0.76 0.34 0.57 -0.19 0.41 -0.55 0.86 0.57 0.74 0.95

2011, 2012 SPS-E -0.43 0.00 0.83 -0.76 0.08 0.64 -0.48 0.31 -0.67 0.83 0.67 0.64 0.93

Significant Spearman’s rank correlations at p < 0.05 are indicated in bold. Correlations below the diagonal belong to the Atlantic x Superior population and correlation above the diagonal belong to the Superior x Atlantic population

106

Table 3.5. Relationship between tuber calcium concentration and its significantly correlated traits at p<0.05 including the incidences of hollow heart (HH), blackspot bruise (BB), pitted scab incidence in the high disease pressure field (PS-E), severity of pitted scab in the high disease pressure field (SPS-E), tuber yield (TY), specific gravity (SG), chip lightness (L), and chip yellowness (B) in the Atlantic x Superior reciprocal populations.

Trait Size Relationship with tuber calcium Probabilities in percentages and reponses at specific tuber calcium concentrationsǂ

Atlantic x Superior

100 μg/g

150 μg/g

200 μg/g

250 μg/g

300 μg/g

HH† S P=1/(1+exp(-0.4508 -0.01535 * calcium)) 12.1 6.0 2.9 1.4 0.6

M P=1/(1+exp(-0.4508 -0.01535 * calcium +

0.04619)) 12.6 6.3 3.0 1.4 0.7

L

P=1/(1+exp(-0.4508 -0.01535 * calcium + 0.4717))

18.0 9.3 4.5 2.2 1.0

BB† S P=1/(1+exp(-0.6643 -0.01397 * calcium)) 11.3 6.0 3.1 1.5 0.8

M

P=1/(1+exp(-0.6643 -0.01397 * calcium + 0.07460))

12.1 6.4 3.3 1.7 0.8

L

P=1/(1+exp(-0.6643 -0.01397 * calcium + 0.3559))

15.4 8.3 4.3 2.2 1.1

PS-E† P=1/(1+exp (-0.3180 -0.004838 * calcium)) 31.0 26.0 21.7 17.8 14.6

√SPS-E √y=0.9719 -0.001341 * calcium 0.70 0.59 0.50 0.41 0.32

TY y=50.2177 -0.03462 * calcium 46.76 45.03 43.29 41.56 39.83

SG y=1.083 -0.00006597 * calcium 1.076 1.073 1.070 1.067 1.063

L y=51.7387 -0.007749 * calcium 50.96 50.58 50.19 49.80 49.41

B y=24.3703 -0.007628 * calcium 23.61 23.23 22.85 22.46 22.08

Superior x Atlantic

100 μg/g

150 μg/g

200 μg/g

250 μg/g

300 μg/g

HH† S P=1/(1+exp(-1.5157 -0.01124 * calcium)) 6.7 3.9 2.3 1.3 0.7

M

P=1/(1+exp(-1.5157 -0.01124 * calcium - 0.01461))

6.6 3.9 2.2 1.3 0.7

L

P=1/(1+exp( -1.5157 -0.01124 * calcium + 0.2055))

8.1 4.8 2.8 1.6 0.9

BB† S P=1/(1+exp(-3.5683 -0.005602 * calcium)) 1.6 1.2 0.9 0.7 0.5

M

P=1/(1+exp(-3.5683 -0.005602 * calcium + 0.1855))

1.9 1.4 1.1 0.8 0.6

L

P=1/(1+exp(-3.5683 -0.005602 * calcium + 0.6491))

3.0 2.3 1.7 1.3 1.0

PS-E† P=1/(1+exp (3.0830 -0.02355 * calcium)) 67.4 39.0 16.4 5.7 1.8

√SPS-E √y=2.6476 -0.01085 * calcium 2.44 1.04 0.23 0.01 0.00

TY y=59.0912 -0.08855 * calcium 50.24 45.81 41.38 36.95 32.53

SG y=1.082 -0.00006477 * calcium 1.076 1.072 1.069 1.066 1.063

L y=58.8791 -0.04745 * calcium 54.13 51.76 49.39 47.02 44.64

B y=25.1295 -0.02362 * calcium 22.77 21.59 20.41 19.23 18.04 Tuber size categories: S=small, M=medium, L=large

† Relationship estimated by logistic regression. Other traits estimated using linear regressions.

ǂ Estimated probability or response for the indicated tuber calcium concentrations estimated using the relationship equation. Values were transformed to the regular scale for the severity of pitted scab.

P=probability, y=response, μg/g=micrograms per gram of dry weight.

107 Table 3.6. Best linear unbiased predictions of four promising clones selected from the reciprocal populations of Atlantic x Superior for tuber calcium (TC), yield (TY), specific gravity (SG), enzymatic browning (EB), chip color using a visual rating (CC), chip color in agtron units (AG), chip lightness (L), chip redness (A), chip yellowness (B), incidence of hollow heart (HH), incidence of black spot bruise (BB), incidence of pitted scab in the standard field (PS), incidence of pitted scab in the high disease pressure field (PS-E), and severity of pitted scab in the high disease pressure field (SPS-E). The parents were included for comparison.

Clone TC TY SG EB CC AG L A B HH BB PS PS-E SPS-E

Atlantic x Superior

B-032 186.5 47.5 1.070 2.01 1.83 42.97 53.91 5.09 23.49 2.94 3.72 2.22 2.84 0.03B-167 175 37.5 1.074 1.44 1.99 42.97 55.8 5.39 23.81 2.11 2.2 6.12 5.62 0.08

Superior x Atlantic

C-205 167.9 37.3 1.069 1.75 2.23 43.75 54.29 5.65 22.58 2.07 0.51 8.01 0.02 2.65C-062 177.9 45.8 1.069 2.53 2.17 42.93 52.2 5.21 21.32 0.7 0.95 9.65 0.38 15.92

Parents

ATL 153.5 55.6 1.076 1.29 2.35 46.64 52.46 5.69 22.55 5.02 7.12 23.71 34.83 36.93SUP 204 46.9 1.068 2.31 3.17 44.77 47.98 6.74 21.05 0.83 2.14 3.49 1.74 1.42

ATL=Atlantic, SUP=Superior. Favorable values in green and non-favorable values in red.

108

FIGURES

Figure 3.1. Predicted probabilities of hollow heart and blackspot bruise at different tuber calcium concentrations in relation to tuber size in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations

100 150 200 250 300

SmallMediumLarge

tuber calcium (µg/g)

pro

bab

ility

0.00

0.05

0.10

0.15

0.20

Probability of Hollow HeartAxS

100 150 200 250 300

SmallMediumLarge

tuber calcium (μg/g)

pro

bab

ility

0.00

0.05

0.10

0.15

Probability of Blackspot BruiseAxS

A

C

100 150 200 250 300

SmallMediumLarge


pro

bab

ility

0.00

0.04

0.08

Probability of Hollow HeartSxA

100 150 200 250 300

SmallMediumLarge


pro

bab

ility

0.00

0.02

0.04

Probability of Blackspot BruiseSxA

B

D

A, B. Probability of hollow heart estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations. C, D. Probability of blackspot bruise estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations.

109 Figure 3.2. Predicted probabilities of pitted scab incidence and predicted severity in the high disease pressure field at different tuber calcium concentrations in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations

in the high disease pressure field

100 150 200 250 300


pro

bab

ility

0.0

0.2

0.4

0.6

Probability of Pitted Scabin the high disease

pressure field

AxS

100 150 200 250 300


pro

bab

ility

0.0

0.2

0.4

0.6

Probability of Pitted Scab

SxA

100 150 200 250 300


pit

s p

er t

ub

er

0.0

0.5

1.0

1.5

2.0

2.5

Severity of Pitted Scabin the high disease

pressure field

AxS

100 150 200 250 300


pit

s p

er

tub

er

0.0

0.5

1.0

1.5

2.0

2.5

Severity of Pitted Scabin the high disease

pressure field

SxA

A

C

B

D

A, B. Probability of pitted scab estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations. C, D. Severity of pitted scab estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations.

110 Figure 3.3. Predicted predicted yield and specific gravity at different tuber calcium concentrations in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations

100 150 200 250 300


ton

s/h

a

010

2030

4050

Total YieldAxS

100 150 200 250 300


ton

s/h

a

010

2030

4050

Total YieldSxA

100 150 200 250 300


g/g

1.04

1.05

1.06

1.07

1.08

Specific GravityAxS

100 150 200 250 300


g/g

1.04

1.05

1.06

1.07

1.08

Specific GravitySxA

A

C

B

D

A, B. Total yield estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations. C, D. Specific gravity estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations.

111 Figure 3.4. Predicted chip lightness and chip yellowness at different tuber calcium concentrations in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations

100 150 200 250 300


L v

alu

es

010

2030

4050

60

Chip LightnessAxS

100 150 200 250 300


Lva

lues

010

2030

4050

60

Chip LightnessSxA

100 150 200 250 300


B v

alu

es

05

1015

20

Chip YellownessAxS

100 150 200 250 300


B v

alu

es

05

1015

20

Chip YellownessSxA

A

C

B

D

A, B. Chip lightness estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations. C, D. Chip yellowness estimated at 100, 150, 200, 250 and 300 µg/g in the Atlantic x Superior (AxS) and Superior x Atlantic (SxA) populations.

112 Figure 3.5. External appearance and chips of the promising clones identified in the Atlantic x Superior reciprocal populations compared to the parents

113

CHAPTER 4

Mapping QTL for Tuber Calcium, Tuber Quality and Pitted Scab in a Tetraploid

Population of Potato (Solanum tuberosum) derived from Atlantic x Superior

ABSTRACT

The population generated by a cross of potato cultivars Atlantic x Superior was used to develop a

map for internal quality, tuber calcium; specific gravity, total yield, chipping quality, internal

defects incidence as well as incidence and severity of pitted scab. This population was genotyped

using the SolCAP 8300 Infinium Chip. After data quality assessment, 600 single nucleotide

polymorphisms markers with simplex x nulliplex and nulliplex x simplex dosages in the parents

from 151 genotypes were used to build a tetraploid linkage map that covered 1254 cM for

Atlantic and 939 cM for Superior. Phenotypic evaluations were performed during 2009-2012

seasons at the Hancock Agricultural Research Station of the University of Wisconsin-Madison.

Using an interval mapping approach, we identified a total of 75 QTL from both parents including

8 for tuber calcium, 10 for specific gravity, 6 for yield, 5 for enzymatic browning, 5 for chip

color in agtron scale, 8 for chip color using a visual scale, 2 for chip lightness, 2 for chip redness,

2 for chip yellowness, 7 for hollow heart, 2 for blackspot bruise, 4 for pitted scab incidence in a

standard field, 7 for pitted scab incidence in a high disease pressure field, and 7 for pitted scab

severity in a high disease pressure field. Some correlated traits had QTL located on the same

chromosome and at close positions. Differences in QTL detection and position between years

were observed.

114

INTRODUCTION

Tuber quality is the most important characteristic in processing potatoes. For chipping varieties,

good tuber quality means high specific gravity, light chip color, and low incidence of internal

and external defects. As well, low incidence and severity of diseases that cause deformities in

tubers such as pitted scab are desired. Tuber calcium has previously found to be associated with

reduced internal defects (Tzeng et al., 1986; Olsen et al. 1996, Palta 1996, Kleinhenz et al. 1999,

Karlsson et al. 2006, Ozgen et al. 2006), and resistance to soft-rot during storage (McGuire and

Kelman 1984). Tuber calcium concentration is a heritable trait as demonstrated in Chapter 3 and

genetic variation for this trait has been observed in both cultivated and wild potatoes (Bamberg

et al. 1993, Karlsson et al. 2006, Vega et al. 2006). Therefore, higher tuber calcium is a desirable

trait. A better understanding of the genetics of tuber quality traits and tuber calcium by the

identification of quantitative trait loci (QTL) associated with these traits could contribute to the

development of breeding strategies for improved chipping varieties.

As indicated in Chapters 2 and 3, the potato cultivars Atlantic and Superior differ significantly

for several tuber quality characteristics. The cross of Atlantic and Superior generated reciprocal

populations that are segregating for total tuber calcium, tuber yield, specific gravity, enzymatic

browning, a visual rate of chip color, chip color as measured in agtrons, chip lightness, chip

redness, chip yellowness, hollow heart and blackspot bruise as well as incidence and severity of

pitted scab. In addition, an important proportion of the observed phenotypic variation is due to

the differences among the genotypes. Therefore, these populations are appropiate to identify the

genetic regions that control tuber calcium, tuber quality and pitted scab tolerance. In this study

115

we used one of the reciprocal populations, the Atlantic x Superior population, to identify QTL

for these traits.

Commercial potato varieties mostly belong to the autotetraploid species Solanum tuberosum.

Polyploids have complex inheritance modes due to preferential and multiple pairing during

cross-over, and the possibility of double reduction (Bradshaw 1994, Wu et al. 2001, Leach et al.

2010). Double reduction is the formation of gametes with segments of two sister chromatids in

the same gamete in polyploids as a result of crossover between a locus and the centromere; and

thus, varies from locus to locus (Mather 1935, 1936, Haynes and Douches 1993). If

quadrivalents are always formed in a tetraploid and an effective cross-over occurs between the

locus and its centromere, the coefficient of double reduction (α) is its maximum of 1/6 (Mather

1936. If there is chromatid segregation, the coefficient of double reduction is equal to 1/7

(Haldane, 1930). The probability of double reduction for each homologous chromosome is 1/4α

(Bradshaw 1994). Theoretically, the frequency of duplex genotypes produced by double

reduction in a simplex genotype is 0 (0%) according to the random chromosome segregation

model (Muller, 1914), 1/28 (3.57%) according to the random chromatid segregation model

(Haldane, 1930), 1/24 (4.17%) according to the maximum equational segregation model

(Mather, 1935, 1936), and 1/10 (10%) according to the general polyploid model (Wu et al.,

2001). The general poplyploid model described by Wu et al. (2001) predicts a 1/10 frequency for

each possible type of gamete including the products of double reduction following the formation

of a quadrivalent assuming that the three types of segregation: no-crossover, cross-over with

equational division, and cross-over with reductional division occur in the same frequency in the

first meiotic division of an autotetraploid. These characteristics of tetraploid potato have made it

116

less preferred for genetic studies.

Potato tetraploid linkage maps have been scarce compared to diploid maps due to its complex

inheritance (Luo et al. 2001). Previous QTL maps in tetraploid populations include those

developed for late blight (Phytophtora infestans (Mont.) de Bary) by Meyer et al. (1998),

Verticillium dahliae by Simko et al. (2004), for Colorado potato beetle (Leptinotarsa

decemlineata [Say]) by Sagredo et al. (2009); for yield, agronomic traits and quality traits by

Bradshaw et al. (2008); and for agronomic traits and internal heat necrosis by McCord et al.

(2011a, 2011b). So far, QTL interval mapping in tetraploid populations has been implemented

only in TetraploidMap (Hackett et al. 2007). This software was developed to deal with simple

sequence repeats (SSR) and amplified fragment length polymorphisms (AFLP). However, the

datasets can be adapted to use single nucleotide polymorphisms (SNP) data. The SolCAP project

developed an Illumina Infinium Bead Chip for potato that evaluates simultaneously 8303 SNP

(Hamilton et al. 2011). The advantages of using SNP markers for tetraploid mapping are that

polymorphisms can be detected ideally in every position of the genome and the dosage can be

determined. To determine the dosage for each SNP locus, a clustering analysis was performed by

the SolCAP using the Illumina GenomeStudio software. A set of 354 diverse lines, two F1

tetraploid mapping populations and one F1 diploid mapping population were included in the

determination of cluster positions for the diploid and tetraploid models (Hirsch et al. 2013). With

the availability of whole-genome genotyping data and the development of software that can deal

with it, linkage mapping of tetraploid populations generated from already accepted commercial

varieties would become an increasingly used tool.

117

The present study aims to identify genomic regions that can explain the phenotypic variation

observed in the Atlantic x Superior tetraploid population (detailed data given in Chapters 2 and

3). This research is the first genetic study of tuber calcium using molecular data and an attempt

to explain some of the observed correlations between tuber quality traits and tuber calcium. In

this study we also attempted to identify regions associated with tolerance to pitted scab at the

tetraploid level.


Population and genotyping

The population generated by the cross of the potato cultivars Atlantic (female) and Superior

(male), and was named the Atlantic x Superior population. This population consists of 184

clones obtained in the Biotron of the University of Wisconsin-Madison, USA. The Atlantic x

Superior population and their parental genotypes were genotyped using the Illumina high-

throughput SNP assay. This assay evaluated 8303 SNP markers identified by Hamilton et al.

(2011) that combine information from cDNA sequencing of popular modern varieties, Atlantic,

Premier Russet and Snowden, and data mining of existing ESTs from a set of old potato

varieties, Bintje, Kennebec and Shepody. For the SNP genotyping, leaf samples were collected

in the maintenance field in 2010 and sent to the Seed Biotechnology Center of the University of

California for DNA isolation and genotyping as part of the SolCAP Project. The advantages of

using SNP markers are their abundance and that they give us information about allele dosage. In

general, it has been observed that SNP are mostly bi-allelic with two alleles segregating in the

populations (Krawczak 1999). Therefore, in a single locus with two alleles of a tetraploid potato,

118

we can get up to 5 different genotypes including: nulliplex (BBBB), simplex (ABBB), duplex

(AABB), triplex (AAAB), and quadriplex (AAAA).

Analysis of genetic structure

The genetic structure was evaluated using the package adegenet (Jombart 2008) in R version

2.13.2 (R Development Core Team 2011). Principal components analysis (PCA) was performed

to confirm that all clones genotyped belong to the Atlantic x Superior population. The two

principal components that explain the most variance were plotted in a two-dimensional graph.

Allele frequencies were estimated and missing data were replaced by the mean allele frequency

for the genetic relatedness analysis. A dendogram was constructed as a graphical representation

of genetic relatedness using the Nei’s distance (Nei 1972) and the complete linkage method of

hierarchical clustering (Sorensen 1948). Duplicated genotypes were identified by a pairwise

comparison of genotypes and estimation of the proportion of matches using the qtl package

(Broman et al. 2003) in R version 2.13.2. Pairs of genotypes with more than 0.99 identities were

identified and only one representative was kept for further analyses.

Sorting SNP markers suitable for tetraploid mapping

Each SNP marker in the potato Infinium SNP chip was assigned a quality indicator by SolCAP.

The markers with quality indicators BAD and QUESTIONABLE, were removed, keeping only

the GOOD and SEGREGATING markers. Further, any marker missing in all clones or in one or

both parents was removed. Then, markers that could not be located (no hits) in the pseudo-

molecule of the Solanum tuberosum Group Phureja double monoploid reference genome

sequence (Potato Genome Sequencing Consortium 2011), and those located in more than two

119

positions (two hits) were also removed. Also, markers that mapped in more than two positions in

the DRH and D84 reference diploid maps (Felcher et al 2012) were removed. Due to lack of

software that allows handling of tetraploid genotypic data with known dosage, only cross types

with expected segregation ratio of 1:1 in tetraploid populations, such as simplex x nulliplex and

nulliplex x simplex (simplex markers) were used for mapping. Simplex markers were more

abundant compared to other types of markers such as duplex (duplex x nulliplex or nulliplex x

duplex) or triplex markers (triplex x nulliplex or nulliplex x triplex) (Data not shown).

Distorted markers, markers missing in most genotypes, genotypes with lots of missing markers,

duplicated markers and duplicated genotypes were analyzed using the tools for data cleaning in

the qtl package (Broman et al. 2003) in R version 2.13.2. Segregation distortion was tested for

each locus using a Chi-square test. A correction for multiple comparisons was performed using a

Bonferroni procedure (Bonferroni 1935) with an experiment wise error rate of 0.05. Therefore,

SNP markers with p-values smaller than 0.05/total number of markers were excluded from the

dataset. Duplicated markers, markers that show identical information, were identified and one

representative marker was kept and the rest were eliminated from the dataset because duplicated

markers will invariably map to the same genomic position (Broman 2010). Duplicated genotypes

are not common but also they are not rare; and may indicate sample duplications (Broman 2010).

Duplicated genotypes may also indicate genotyping errors (Pompanon et al. 2005). Therefore,

duplicated genotypes were also removed from the dataset for mapping analysis.

Evaluation of double reduction

Segregations between a locus with simplex dosage (ABBB) and a locus with nulliplex dosage

(BBBB) are called simplex markers. In a simplex marker, duplex genotypes (AABB) can only be

120

generated by double reduction. The frequency of individuals produced by double reduction in

each SNP marker was estimated as the proportion of duplex genotypes found in simplex

markers. SNP markers with frequency of duplex genotypes 16.67% (1/6) or higher were

removed from the dataset. This threshold was set because 1/6 is the maximum expected value of

double reduction as indicated by Mather (1936). Higher numbers of duplex genotypes are most

likely generated by genotyping errors. Duplex genotypes were relabeled as missing data prior to

linkage analysis in all remaining SNP locus because markers with double reduction cannot be

used in the mapping software TetraploidMap (Hackett et al. 2007).

Construction of a tetraploid linkage map and QTL interval mapping

A tetraploid linkage map was constructed using TetraploidMap (Hackett et al. 2007; available at:

http://www.bioss.ac.uk/knowledge/tetraploidmap/). This software was built to deal with SSR and

AFLP markers but can be accommodated to work with SNP (Christine Hacket from The James

Hutton Institute and Joseph Coombs from Michigan State University, personal communication).

Simplex markers were coded using a binary nomenclature, where simplex genotypes were coded

as 1 and nulliplex genotypes as 0 trying to emulate the coding of a dominant AFLP marker.

Markers with significant segregation distortion, p <0.001 for the Chi-square test, were excluded

from the linkage map analysis. Markers that belong to the same chromosome according to their

physical position in the pseudo-molecule of the potato genome sequence were used for the

clustering analysis, this cluster analysis is the first step to generate a linkage group. The cluster

analysis was performed using a distance coefficient d=1-10-2s, where s is the significance level of

the test for independent segregation (Luo et al. 2001). Recombination frequency and linkage

phase was estimated for each pair of marker loci using maximum likelihood and the Expectation-

121

Maximization (EM) algorithm as described by Luo et al. (2001). The markers were ordered in

each chromosome using a two-point linkage analysis with custom marker ordering and ripple

ordering (Hackett et al. 1998). Linkage phase was assigned manually using the pair-wise

likelihood evaluation of coupling and repulsion described by Luo et al. (2001) to assign markers

to one of the four homologous chromosomes. Markers in coupling with more than one homolog

were removed from the analysis. Overall and per-homolog maps were built for each chromosome

and each parent. Trait data were related to the genotypic data to identify QTL using the interval

mapping approach for full-sib families in autotetraploid species derived from an intercross as

described by Hackett et al. (2001). This method is included in TetraploidMap in the QTL

function (Hackett et al. 2007). The QTL analysis was performed using the full model and

compared to simpler models such as simplex x nulliplex or duplex x nulliplex segregations to

determine the dosage of the QTL and its effect as described by Hackett et al. (2007). If no

simpler model explains the QTL effects, the QTL is considered additive with a complex

inheritance. Using the Permutations function, a total of 100 permutation tests were performed in

order to define 90% and 95% confidence thresholds as described by (Churchill and Doerge

1994). Only peaks with maximum LOD above the 90% threshold of permutation tests were

considered acceptable. The QTL maximum LOD, position and variance explained were

recorded.

Marker regression

The analyses of variance by means comparison (ANOVA) and by ranks comparison (Kruskal-

Wallis test) were performed to detect significant differences between the genotypes carrying

simplex markers versus nulliplex markers. These analyses are available in TetraploidMap

122

(Hackett et al. 2007). The significance threshold was set at p<0.01. Only markers within ± 20 cM

of a detected QTL are reported here.

Phenotypic evaluations

The field performances of the progenies from the Atlantic x Superior population were evaluated

during the 2009-2012 seasons at the Hancock Agricultural Research Station of the University of

Wisconsin-Madison. The traits studied were total tuber yield (ton/ha), tuber calcium (µg/g),

specific gravity (g/g), enzymatic browning (using a visual rating from 1 to 5, light to dark), chip

color (using a visual rating from 1 to 5, light to dark), chip color in agtrons, chip lightness in L

values, chip redness in A values, chip yellowness in B values, incidence of hollow heart,

incidence of black spot bruise, incidence of pitted scab, and severity of pitted scab. All trials

were conducted under standard commercial production practices of Central Wisconsin. A

standard field was used to evaluate tuber calcium, agronomic traits, internal defects, chip quality,

and pitted scab incidence. In addition, a high disease pressure field, a field that has been used

continuously to grow potatoes without rotation and is known to have high amounts of common

scab inoculum, was used to evaluate pitted scab incidence and severity. Two to three

replications/clone and four or eight plants/plot were evaluated using an incomplete block design

for most trials except for the standard field in 2011 where a complete block design was used. In

the incomplete block design, clones were randomized within groups of 28 clones, each group

included a replicate of both parents, groups were randomized within replicates, and replicates

were randomized within years. Best linear unbiased predictions (BLUP) estimated for the

Atlantic x Superior progenies were used as trait data for QTL mapping. Incidence traits were

evaluated as proportions. Clones performances were determined per year and pooling years. The

123

model used to estimate pooled BLUP values was the following: Xijkl = μ + Gi + Yj + Bk(Rl(Yj)) +

(GY)ij + εijkl; where Xijkl are the observed trait measurements, μ is the overall mean, Gi are the

genotypes, Yj are the years, Bk(Rl(Yj)) are the groups nested in replicates and replicates nested in

years, (GY)ij is the interaction between genotypes and years, and εijkl is the residual error. All

variables were considered random. The estimation of per year BLUP used the same model

without the year and genotype x year interaction variables. Linear mixed models and generalized

linear mixed models were used depending on the type of data evaluated, direct observations or

proportions, respectively. A detailed analysis of tuber quality and calcium traits in the Atlantic x

Superior population was presented in Chapter 2 and 3.


Quality assessment of genotypic data

The Atlantic x Superior population studied in this research was created in 2003 followed by

several years of field maintenance. According to the genetic structure analysis, four clones were

identified as clearly genetically distant from the rest of the population (Figure 4.1). We believe

that these clones might belong to the Superior x Snowden population which was also created in

2003 and grown in randomized plots in the same field with the Atlantic x Superior population

throughout the years. The genetic structure analysis also indicates that some clones had been

misidentified (Figure 4.1). A sample of Atlantic was mislabeled as Superior, another Atlantic

sample was mislabeled as a progeny, and a sample of Superior was mislabeled as a progeny. In

addition, clusters of duplicated genotypes were also observed in the hierarchical cluster analysis

124

(data not shown). Two clusters of duplicated genotypes corresponded to genotypes sampled

twice. Other 15 clusters of duplicated genotypes included clones with different codes.

Furthermore, the pair-wise comparison between clones indicates that some clones have high

genotypic identities (identity > 0.99) (Figure 4.2). These highly identical clones were removed

from further analyses in order to avoid redundancy; only one representative from each cluster of

duplicates was used for mapping. After sorting markers and keeping those more suitable for

tetraploid mapping (Table 4.1), the number of SNP markers was reduced from 8303 to 619

simplex markers. These markers were introduced to TetraploidMap where a final sorting

occurred by excluding 5 simplex markers due to high segregation distortion (p-value < 0.001),

and 14 simplex markers due to similarly low values of LOD for coupling with more than one

homolog. A final dataset of 600 simplex markers evaluated in 151 progenies with unique

genotypes passed the quality assessment (Table 4.1) and were used to construct the tetraploid

linkage map for the Atlantic x Superior population.

Evidence of double reduction in the Atlantic x Superior population

Double reduction was evaluated in the Atlantic x Superior population using 968 simplex markers

(Table 4.1). We detected evidence of double reduction in 28.7% out of 968 simplex loci. The

frequency of duplex genotypes produced as a result of double reduction was between 0 and

33.33%. These results contrast with previous studies that reported that double reduction occurs

sporadically in potato (Haynes and Douches, 1993). In a study by Haynes and Douches (1993),

double reduction was estimated using isozymes in 4x-2x crosses and haploid families. Using the

data presented for the Pgm locus in simplex genotypes of Katahdin and Merrimack reported by

Haynes and Douches (1993), the frequency of duplex genotypes was between 5% and 9.18%

125

which is within the range we have observed in the present study. These values exceed the

maximum expected frequency according to the chromosomal and chromatid segregation models

but are within the expected values for the general polyploid model. Nevertheless, 9 SNP markers

in our population had more than 10% duplex genotypes which is the maximum expected

according to the general polyploid model. These loci with higher than expected duplex genotypes

may be caused by genotyping errors, selection acting at the level of the gametes, high

recombination frequency between the locus and the centromere, or a combination of all these

factors. The maximum frequency of double reduction expected is 1/6 or 16.67% of duplex

genotypes. Therefore, the 6 SNP with > 16.67% duplex genotypes were removed from the

dataset for mapping.

Tetraploid linkage map for the Atlantic x Superior population using SNP markers

Tetraploid linkage maps of Atlantic and Superior were constructed using 600 simplex SNP

markers distributed over 12 chromosomes (Table 4.3). The number of SNP mapped per

chromosome ranged from 18 (Chr.12) to 49 (Chr. 2) in Atlantic and from 5 (Chr.11) to 24

(Chr.7) in Superior. Chromosome lengths ranged from 84.8 cM (Chr.12) to 123.7 cM (Chr.1) in

Atlantic and from 34.8 cM (Chr.11) to 116 cM (Chr.4) in Superior. The overall size of the map

was 1238.4 cM for Atlantic and 889 cM for Superior. More than twice (414) markers were

mapped in Atlantic compared to Superior (186). A possible explanation for this difference is that

Atlantic was one of the cultivars used in the development of the SNP markers by SolCAP

whereas Superior was not used. Therefore, one hypothesis coul be that the polymorphisms

detected by the SNP chip might be biased towards Atlantic. Another hypothesis is that Superior

126

is more imbred than Atlantic and thus may have a higher number of homozygous loci compared

to Atlantic. By looking at the pedigrees of both parents it seems that the second hypothesis is the

most plausible (Figure 4.4). On average our map has 1 SNP marker every 2.33 cM for Atlantic

and 1 SNP marker every 3.8 cM for Superior. Areas near the centromeric regions, where

increments in physical position have little effect on map distance, were identified using these

SNP markers as reported previously by Felcher et al. (2012). The physical versus linkage map

correlation plots indicate a misorientation of the cM position with respect to the physical position

suggesting an inversion at the distal end of Chr.10 (Figure not shown). These results indicate that

some chromosomal rearrangements may exist between S. tuberosum and S. phureja because we

have constructed a map using two S. tuberosum cultivars and the physical positions assigned to

the SNP markers in the SolCAP 8300 Infinium Chip were based on the genome sequence of the

double monoploid of S. phureja (DM1-3 516 R44) (Potato Genome Sequencing Consortium

2011). Felcher et al. (2012) also observed regions with chromosomal rearrangements in Chr. 5

and 12 comparing a S. phureja x S. tuberosum-based and S. phureja x S. chacoense-based

diploid maps using the same SNP markers. As a consequence of these chromosomal

rearrangements these authors suggest to exercise caution when extrapolating sequence data

between species. Additional studies and future linkage maps constructed with the SolCAP 8300

Infinium Chip will shed more light on these chromosomal rearrangements.

Phenotypic data

Performance in terms of the best linear unbiased predictions (BLUP) of 151 progenies, selected

for mapping by the criteria described before, was used as trait data to associate with the

genotypic data. BLUP values and broad-sense heritabilities for tuber calcium, tuber yield,

127

specific gravity, chip color, hollow heart, blackspot bruise and pitted scab were estimated

(Chapter 3). Broad-sense heritabilities ranged from 0.19 to 0.85 for all traits evaluated in the

Atlantic x Superior population and the correlation analyses of trait data across years using the

Spearman’s rank correlation indicated a positive correlation between ranks for different years for

most traits; however, all traits were affected by genotype x environment effects (Chapter 3).

Effect of population size and heritability on QTL detection in the Atlantic x Superior

population

Several QTL were identified for all traits evaluated across Atlantic and Superior genomes

(Figure 4.5-4.16 and Table 4.3). The population sizes used for QTL mapping varied from

season to season and ranged from 32 for the 2011 trial in the standard field to 128 in 2010 in the

standard field (Table 4.4). The effects of the QTL were usually around 10% for most years of

evaluation and pooled analysis (Table 4.5). However, higher values of variance explained were

observed in QTL identified only in the 2011 trial in the standard field (Table 4.5). For example

some QTL were identified in the standard field only in 2011, a QTL for specific gravity located

on Chr. 1 of Atlantic at 101.7 cM and explains 39.5% of the variance, another QTL for the visual

rating of chip color located on Chr.11 at 14.2 cM that explains 41.4%, and two other QTL for

hollow heart located on Chr. 1 and Chr. 5 that explain 57 and 49.6% of the variance,

respectively. These high values of variance explained are most likely due to the over-estimation

of the QTL effect when population size is small as explained by Beavis (1994, 1998). In this case

population size was 32 for the 2011 trial in the standard field (Table 4.4). The number of QTL

identified for each trait ranged from 2 to 9 in the Atlantic x Superior populations (Table 4.3).

Fewer and more unstable QTL were found for traits with low heritabilities such as blackspot

128

bruise that had broad-sense heritabilities of 0.3, 0.3 and 0.19 in 2009, 2010 and 2011,

respectively. Two QTL were detected for blackspot bruise; each of them present only in a single

year of evaluation (Table 4.3 and 4.5). This lower power of QTL detection in traits with low

heritability has also been explained by Beavis (1994, 1998).

QTL for tuber calcium

Eight QTL were identified for tuber calcium (TC), seven on Chr. 1, 3, 5, 7, 8, 9, and 11 of

Atlantic and one on Chr. 12 of Superior. The effects of these QTL ranged from 7.7 to 30.3%, two

of these QTL were detected in one year, and the rest were detected in either two years or one

year and the pooled data (Table 4.5). Only one of these QTL increases the concentration of

calcium when it is present but it also has the lowest effect among all the QTL for calcium.

However, the smaller number of markers in Superior may have reduced our power to detect QTL

coming from this parent that has the highest tuber calcium content. Our results confirm that tuber

calcium is controlled by several genes and therefore a trait of a quantitative nature with genes

distributed throughout the potato genome.

QTL for yield and specific gravity

Six QTL were identified for tuber yield (TY), 2 in Atlantic and 4 in Superior. In Atlantic, a QTL

was located on Chr. 1 at 73.7 cM that explained 10.7% of the variance. Another was located on

Chr. 3 of Atlantic at 112 cM that explained 21.8% of the variance. In Superior, two QTL for

tuber yield were located on Chr. 1 at 10 cM and 102 cM with 9.06% and 13.09% variance

explained, respectively. Another QTL detected was found on Chr. 2 of Superior located at 22 cM

and variance explained by this QTL was 11.3%. Another QTL was detected on Chr. 4 of

129

Superior at 20 cM that explained 8.9% of the variance (Table 4.5). Half of the QTL for tuber

yield were additive. The QTL with the largest effect was located in Atlantic and had a duplex

dosage where the dominant allele would increase total yield. In general, three QTL for yield

were located on Chr. 1 suggesting that this chromosome may have several loci that control this

trait. Bradshaw et al. (2008), identified a QTL for yield with dominance for low yield which was

located at 118 cM on Chr. 1 in the 12601ab1x Stirling population. Also, McCord et al. (2011a)

identified QTL on Chr. 2, 3, 5, 10, and 12 of Atlantic as well as on Chr. 5, 6, 7, and 8 of B1829-

5. In our Atlantic x Superior population, we also identified a QTL on Chr.3 of Atlantic but we

did not detect the other reported QTL but we detected another QTL on Chr. 1 of Atlantic that had

not been reported. This difference is expected because QTL detection in bi-parental populations

depends on the segregation in the specific population under study (Würschum 2012).

Ten QTL were identified for specific gravity (SG), 8 in Atlantic and 2 in Superior (Table 4.5).

These QTL explained variances between 7.7% and 39.5% and half of them were detected in a

single year (Table 4.5). For Atlantic, two QTL were found on Chr.1 located at 83.7 and 101.7

cM that explained 12.4% and 39.5% of the variance, respectively. Other QTL were identified on

Chr.2 at 7.3 cM that explained 17.6% of the variance, on Chr. 7 at 22 cM that explained 11.2%

of the variance, on Chr. 8 at 30.9 cM that explains 18.7% of the variance, on Chr. 11 at 70.2 cM

that explains 15.6% of the variance, two on Chr. 12 at 20 and 60 cM that explain 11.8 and 7.7%

of the variance, respectively. In Superior, a QTL on Chr.1 located at 104 cM that explained

11.04 of the variance and another QTL on Chr. 9 at 30.8 cM that explained 9% of the variance.

The QTL for specific gravity with the largest effect was duplex with the dominant allele

increasing the specific gravity and was found in Atlantic (Table 4.5). Our results are in general

130

in agreement with reports by Freyre et al. (1994) that detected 10 QTL in a (S. tuberosum x S.

chacoense) x S. phureja diploid population. Bradshaw et al. (2008) that found two QTL for

specific gravity on Chr.5 at 74 and 76 cM that explained 9.1 and 9.7% of the variance in the

Stirling x 12601 tetraploid population. McCord et al. (2011a) identified QTL in the Atlantic x

B1829-5 on Chr. 2, 3, 5 and 8 together with significant markers in group 7, Chr.9 and 12. We

also found QTL for specific gravity on Chr. 2, 7, 8, 9 and 12 in addition to other QTL on Chr. 1

and 11.

QTL for chip quality

Chip quality was studied using several measurements of chip color and enzymatic browning.

Enzymatic browning (EB) affects chip quality by determining the color of the potato slices

before they enter to the fryer (Krokida et al. 2001). Five QTL were identified for enzymatic

browning. Two of these QTL were located on Chr. 1 and 8 of Atlantic and three on Chr. 5, 6, and

7 of Superior. These QTL explained between 7.4 and 28.5% of the variances and most of them

were detected in two years, or one year and the pooled analysis (Table 4.5). The QTL with the

largest effect was found on Chr. 7 of Superior, followed by the QTL on Chr. 8 of Atlantic.

Enzymatic browning in raw cut potatoes has been related with the polyphenol oxidase (PPO)

enzymatic activity (Jeong et al. 2005). The PPO enzyme, which causes darkening of cut tissues,

has been previously mapped on Chr. 8 of Solanum (Newman et al. 1993). A study by Werij et al.

(2007) identified QTL for enzymatic discoloration (ED) on Chr. 1, 3 and 8 in a diploid

population using interval mapping with AFLP markers and marker regression with CAPS

markers targeting the PPO gene. The QTL on Chr. 8 found by Werij et al. (2007) was located in

a region around 50 cM. In our study, we found a QTL for enzymatic browning located on Chr. 8

131

of Atlantic using interval mapping with SNP markers in our tetraploid population. This QTL was

located at 50.9 cM, almost the same position reported by Werij et al. (2007). This QTL has a

simplex dosage that decreases the enzymatic browning when present. It appears that this QTL is

the PPO gene. These results confirm that our phenotyping method using visual ratings from 1 to

5 was adequate to detect the PPO gene and other QTL regions that might be related to the

substrates of this enzyme and therefore causing enzymatic browning.

For the visual scoring of chip color (CC), we found two QTL on Chr.1 of Superior and six QTL

on Chr. 4, 6, 7, 8, 9, and 11 of Atlantic. In Superior, two QTL on Chr. 1 were located at 68 and

80 cM that explain 10.3 and 8.8% of the total variance, respectively. In Atlantic, the QTL on

Chr. 4 was located at 34 cM that explained 10.1% of the variance. The QTL on Chr. 6 was

located at 36 cM and explained 9.1% of the variance. The QTL on Chr. 7 of Atlantic is located at

70 cM and explained 9.9% of the variance. The QTL on Chr. 8 of Atlantic was located at 84.9

cM and explained 13.8% of the variance. The QTL on Chr. 9 of Atlantic was located at 89.2 cM

and explains 14.9% of the variance. The QTL on Chr. 11 of Atlantic was located at 14.2 cM and

explains 41.4% of the variance but was detected only in 2011. All other QTL were detected at

least in two years. The QTL with largest effect was found in Atlantic on Chr.11 only during the

2011 evaluation and had a complex inheritance. Most previous studies have tried to understand

the genetics of chip color after several months in storage at low temperatures (Douches and

Freyre 1994, Menéndez et al. 2002, Bradshaw et al. 2008). However, in our study we tried to

understand the genetics of chip color shorter after harvest because neither Atlantic nor Superior

are a cold storage chip variety. Nevertheless, we have found eight QTL for chip color which is a

comparable number to what has been reported previously. For example, Douches and Freyre

132

(1994) found 6 QTL in a diploid population on Chr. 2, 4, 5 and 10. Also, Bradshaw et al. (2008)

found 4 QTL for chip color at two storage temperatures 4ºC and 10ºC on Chr. 1, 6 and 11. In this

research, we also found QTL on Chr. 1, 6 and 11 but they were located in different positions as

compared to previous reports. Our results confirm that using a visual rating for chip color is a

good approach to detect gene-based phenotypic variation. And also that chip color is a trait

controlled by several genes distributed throughout the genome.

In our study, six QTL were identified for the three components of chip color, L, A, and B, as

measured by the Hunter colorimeter (Table 4.5). For chip lightness measured as L values (L),

two QTL were detected on Atlantic which explained 11 and 11.8% variance, respectively. One

of these QTL was located on Chr. 7 at 76 cM detected in 2010 and the pooled analysis and the

other on Chr. 9 at 89.2 cM detected in 2010, 2011 and pooled analysis (Table 4.5). For chip

redness measured as A values (A), two QTL were identified in Atlantic. One of these QTL was

on Chr. 8 at 86.9 cM and the other on Chr. 9 at 101.3 cM. These QTL explained 11.5 % of the

variances, respectively; and both QTL were detected in 2010, 2011 and the pooled analysis

(Table 4.5). For chip yellowness measured as B values (B), two QTL were identified in Atlantic.

One of the QTL was located on Chr. 5 at 38 cM and the other one on Chr. 8 at 86.9 cM and

explained 8.4 % and 7.8% of the variances. Both of these QTL were detected in 2010 and the

pooled analysis (Table 4.5). Previous research has used chip lightness measurements to detect

phenotypic variation between varieties and/or under different physiological conditions (Sapers

1989, Rodriguez-Saona and Wrolstad 1997) and differences among transgenic clones (Bhaskar et

al. 2010). However, these measurements have not been previously used for QTL mapping.

133

For chip color measured by the agtron scale (AG), five QTL located on Chr. 1, 2, 4 and 5 of

Superior and one QTL on Chr. 7 of Atlantic were identified (Table 4.5). These QTL explained

between 9.3% and 18.3% of the variances and were detected only in 2009 because data for chip

color as measured in agtrons was collected only one season. The QTL with the largest effect was

found in Atlantic on Chr.7 at 74 cM and with a simplex dosage where the presence of the QTL

increased the agtron values. Previous research has studied chip color using agtron values but

these values have not been used for mapping. It is interesting to note that the QTL found for

agtron readings and L values were located in the same position or close to the QTL identified for

chip color (Table 4.5).

Genetic diversity for chip color has been demonstrated for cultivated and wild potato (Li et al,

2005, 2008; McCann, 2010). Furthermore, QTL for chip color have been identified by previous

studies using diploid populations (Douches and Freyre 1994) and tetraploid populations

(Bradshaw et al. 2008). Douches and Freyre (1994) mapped six QTL for chip color on Chr. 2, 4,

5 and 10 using a marker regression approach. Bradshaw et al. (2008) found QTL for chip color

after storage at 4°C and 10°C on Chr. 1, 6 and 11 in a tetraploid population using interval

mapping. In addition, because chip color is related to sugar content; Menéndez et al. (2002)

reported QTL located on all chromosomes of potatoes for sugar content after cold storage, a trait

that influences chip color. The QTL we found are also distributed in most of the potato

chromosomes in concordance with previous reports and these QTL were confirmed by different

types of measurements used for evaluating chip color and quality.

134

QTL for internal tuber quality

Internal tuber quality was evaluated in terms of the incidence of hollow heart (HH) and the

incidence of blackspot bruise (BB). For hollow heart, two QTL were identified in Superior and

four in Atlantic (Table 4.5). In Atlantic, a QTL detected on Chr. 1 at 45.7 cM explained 57% of

the variance but was detected only in 2011. Two other QTL were found on Chr. 3 at 0 and 40 cM

that explained 17% and 19.7% of the variance, respectively. Another QTL were found on Chr. 6

at 70 cM that explained 19% of the variance and a QTL on Chr. 9 at 101.2 cM that explained

71.7% of the variance. In Superior, a QTL for hollow heart was found on Chr. 3 at 44 cM that

explained 7.5% of the variance; another QTL was found on Chr.5 at 22 cM that explained 49.6%

of the total variance. The latter was detected only in 2011. The QTL on Chr.3 were the most

stable because they were present in two years or three years of evaluations and they were also

present in the pooled data.

For black spot bruise, two QTL were identified on Chr.10 and 11 of Atlantic at 21 and 50.2 cM

with explained variances of 20.9% and 7.1% and detected in 2009 and 2010, respectively. No

QTL for blackspot bruise were found in Superior. The PPO enzyme has been proposed to be

involved in the bruising reaction by previous studies (Matheis 1987, Urbany et al. 2011);

however, we did not detect the QTL on Chr.8 at 50 cM where the PPO enzyme has been located

in our blackspot bruise evaluations. QTL for tuber bruising were detected by Urbany et al.

(2011) using an association mapping approach. They found several markers associated to bruise

susceptibility that were located throughout the genome. In our study, we were not able to detect a

large number of QTL for blackspot bruise due to the low heritability of this trait under the

conditions of our evaluations.

135

Previous genetic studies for internal quality investigated internal heat necrosis (IHN), a defect

that causes necrotic patches in the tuber flesh when plants are subjected to heat stress (Sterret and

Henninger 1997); QTL for IHN have been detected in the Atlantic x B1829-5 tetraploid

population on Chr. 4, 5, 7, 10 of Atlantic, and Chr. 7 of B1829-5 (McCord et al., 2011b). In

addition, Bradshaw et al (2008) evaluated internal quality in terms of an index of internal

condition (IC) that combined all defects in a single score where higher values meant better

internal quality. A QTL for the IC index was found on Chr.5 at 116 cM. In our study, we found a

QTL for incidence of hollow heart on Chr.5 with large effects, 49.6% of variance explained but

it was detected only in the 2011 evaluation.

QTL for pitted scab

Pitted scab was evaluated by recording the incidence of this disease under standard field

conditions, and incidence and severity in a field with high disease pressure. For pitted scab

incidence under standard field conditions, four QTL were identified, two on Chr. 3 and 12 of

Atlantic and two on Chr. 4 and 5 of Superior (Table 4.5). These QTL explained between 7.8%

and 13.7% of the variances. Only the QTL on Chr. 4 of Superior and the QTL on Chr. 12 of

Atlantic were present in two years of evaluation and in the pooled analysis; the other QTL were

present only in one year or only in the pooled analysis. The other QTL with the largest effect was

located on Chr. 4 and explained 13.7% of the variance.

For pitted scab incidence under high disease pressure, seven QTL were identified, three on Chr.

3, 7 and 11 of Atlantic and four on Chr. 2 ,5, 6 and 10 of Superior. These QTL explained

between 7.8% and 23 % of the variances and most were detected in two years of evaluation and

136

the pooled data. The QTL with the largest effect was found in Atlantic and had a simplex dosage

and the incidence of pitted scab increased when the QTL was present (Table 4.5).

For pitted scab severity under high disease pressure, seven QTL were identified, three on Chr. 3,

9 and 11 of Atlantic and four on Chr. 2 ,5, 6 and 10 of Superior. These QTL explained between

9.5% and 49.6 % of the variances and most were detected in one or two years of evaluation and

pooled, and one detected only in the pooled evaluation. The QTL with the largest effect was

found on Chr.9 of Atlantic and had a complex inheritance.

In previous studies, two QTL for scab were found on Chr. 2 and 6 at positions 80 and 86 cM in

the Stirling x 12601ab1 tetraploid population (Bradshaw et al. 2008). We also found QTL in

these chromosomes but located in different positions in the genome. Braun (2013) identified a

QTL located at 10.1 cM on Chr.11 that explained 17 and 24.3% of the variance for lesion type

(LT) and percent surface area (PSA), in a diploid population generated by a cross between the

susceptible S. tuberosum clone US-W4 and the resistant S. chacoense clone 524-8. The

inheritance of pitted scab resistance was earlier studied in diploid potatoes by Alam (1972) who

proposed a simple model of inheritance that involves two loci, one where resistance is conferred

by a dominant allele and another one where resistance is conferred by a recessive allele. Several

studies have concluded that common scab resistance in haploid or diploid potato is controlled by

one or few genes. However, it does not seem to be the case in tetraploid potatoes (Dees and

Wanner 2012). In our study, we have found four QTL for pitted scab incidence under standard

disease conditions and seven QTL each for incidence and severity under high disease pressure

that suggest a quantitative nature for pitted scab tolerance. Our search of QTL for pitted scab

tolerance was successful in part because we focused on the evaluation of pitted lesions which are

137

more prominent and easier to detect and therefore the heritability of this trait is high. Also, the

evaluation in a field with high disease pressure allowed us to have enough inoculum to make

more evident the variation in pitted scab tolerance between genotypes.

Linked QTL and correlations between traits

Tuber calcium (TC) has been found to be negatively correlated to the incidence of hollow heart

(HH), brown center (BC), internal brown spot (IBS) and blackspot bruise (BB) in the Atlantic x

Superior population (see Chapter 3 for details). These correlations might be partially explained

by the linkage of QTL for these traits. In several cases correlated traits had QTL located at close

positions on the same chromosome (Table 4.5). For example on Chr.1, a QTL for TC and a QTL

for HH were located at 101.7 and 45.7 cM of Atlantic. On Chr.3, a QTL for TC was located at 50

cM, another QTL for HH located at 40 cM of Atlantic and another QTL for HH located at 44 cM

of Superior. Also, QTL for TC and HH were located at 87.2 and 101.2 cM of Chr. 9 of Atlantic.

On Chr. 11 of Atlantic, QTL for TC and BB were located in close proximity at 54.2 and 50.2 cM

of Atlantic. This result also indicates that the correlation observed between internal defects and

tuber calcium (Chapter 3) can be explained at least in part by this linkage observed among QTL.

However this hypothesis was not tested in this study.

Tuber calcium (TC) was also found to be positively correlated to chip color (CC), chip redness

(A) and enzymatic browning (EB); and negatively correlated to total yield (TY), chip lightness

(B) and specific gravity(SG) in the Atlantic x Superior population (Chapter 3). These

correlations can be partially explained by the close location of QTL for tuber calcium and yield,

specific gravity, and chip quality traits (Table 4.5). On Chr.1 of Atlantic, there is one QTL for

138

TY at 73.7 cM, two for SG at 83.7 and 101.7 cM, and one at 81.7 cM. These QTL are closely

linked to a QTL for TC located at101.7 cM (Table 4.5). On Chr. 5, there is a QTL for TC at 56

cM of Atlantic which is closely linked to a QTL for chip yellowness at 38 cM and for EB located

at 40 cM. Also on Chr.7, QTL for TC, L, AG and CC were very closely located at 76, 76, 74 and

70 cM, correspondingly. These QTL for the different measurements of chip color might actually

be the same QTL. Similarly on Chr. 8, there were QTL for TC, SG and EB in close positions at

46.9, 30.9 and 50.9 cM, respectively. On Chr. 9 of Atlantic, TC, CC, L, and A have QTL in close

positions located at 87.2, 89.2, 89.2 and 89.2 cM, respectively. On Chr. 11 of Atlantic, TC and

SG were located at 54.2 and 70.2 cM. Taken together these results indicate that the correlation of

tuber calcium with total yield, specific gravity, and the several measurements of chip color can

partly be explained by linkage of QTL for these traits.

In addition, the different types of chip color measurements including visual scores of chip color

(CC), chip lightness (L), chip redness (A), chip yellowness (B), chip color as measured by the

agtron scale (AG) and enzymatic browning (EB) evaluated in this population are highly

correlated among themselves (See Chapter 3). These traits also had some QTL located on the

same chromosomes in close positions indicating that the same genomic regions might be

explaining the phenotypic variation for chip color regardless of the type of measurement. For

instance on Chr.1, we found three QTL for chip quality in Superior. Two of these QTL were for

the visual rating of chip color at 66 cM and 80 cM, and another QTL for chip color as measured

in agtrons at 68 cM. On this Chr. a QTL for EB at 81.7 cM of Atlantic was also detected.

Furthermore on Chr.7, there were three QTL for chip quality in Atlantic when measured as

visual rating of chip color, chip color in agtrons, and chip lightness located at 70, 74 and 76 cM,

139

respectively; the small distance between these QTL suggests that they might be the same QTL.

On Chr. 8 of Atlantic, QTL for CC, A and B were found at 82.9, 86.9 and 86.9 which also could

be considered the same QTL. Furthermore on Chr.9 of Atlantic, QTL for visual rating of chip

color, chip lightness, and chip redness were identified at the same position which is 89.2 cM.

Correlated measurements of chip quality detected QTL in similar positions.

Similarly, measurements of pitted scab incidence under standard field (PS) and high disease field

conditions (PS-E) and severity under high disease field conditions (SPS-E) were highly

correlated (Chapter 3). This correlation was reflected in several QTL located in the same

chromosome and even the same position for these traits (Table 4.5). QTL for pitted scab

incidence and severity in the high disease pressure field were located in the same position or less

than 5 cM apart on Chr. 2, 3, 5, 6, 10 and 11. The QTL for PS were also located on Chr. 3 and 5

but their location was shifted by more than 20 cM. These results suggest that incidence and

severity of pitted scab evaluated in a field with high disease pressure seem to be controlled by

the same genes.

In summary, we have found that some of the QTL for correlated traits are closely linked causing

the simultaneous inheritance of the parental alleles for these traits unless there is recombination.

Therefore, large populations should be evaluated to increase chances of finding recombinants

between correlated traits. Evaluation of large numbers of progenies should help in finding clones

that could be selected as cultivars that combine the various desired traits including high tuber

calcium and good internal quality but also have good chipping quality as well as acceptable

specific gravity and yield.

140

Year to Year variability in QTL detection

Variable detection of QTL among years for all traits studied. Was observed in this study and one

of the reasons could be the significant genotype x environment (GxE) interactions observed in all

the traits evaluated. GxE interactions have a clear influence in the detection and localization of

QTL, as it has previously been observed for several traits in potato (Freyre and Douches 2004),

rice (Zhuang et al. 1997); cotton (Paterson et al. 2003), Arabidopsis and others plants (Ungerer et

al. 2003, Tétard-Jones 2011). Some important sources of variation are the differences in weather

and soil conditions from season to season that can change the relative performance of clones and

therefore the detection and location of QTL. Another important source of error in the QTL

detection and estimation of effects is population size that varied among years and was very small

in the standard field in 2011. In our study, 33 QTL were identified in two or three years of

evaluation plus the pooled QTL analysis. These QTL can be called “stable QTL”. We also

detected 22 QTL in either two years of evaluation or one year plus the pooled analysis. These

QTL can be called “semi-stable QTL”. In addition, 15 QTL were detected in one year of

evaluation or only in the pooled analysis and are called “unstable QTL” (Table 4.5). The last

classification does not include the 5 QTL detected for AG which was evaluated only in 2009. An

example of a stable QTL is the QTL for tuber calcium in Chr1. of Atlantic and this is presented

in Figure 4.17.

The QTL detected in multiple environments are more stable and may be of more importance for

plant breeding (Liu et al. 2006). QTL detected in several environments are most likely QTL with

larger effects (Broman and Sen 2009). Therefore, trait data from several trials, either several

141

years or several locations should be considered when performing QTL analysis in order to have a

stronger support for the detected QTL. This would be an additional confidence criterion to

develop markers for marker assisted selection. Our approach to evaluate traits by year and

pooled years was successful in detecting stable QTL and semi-stable QTL.

Regression analysis of SNP markers and opportunities for marker assisted selection

The best model that explains each QTL effect is indicated in Table 4.5. All QTL were initially

detected using the full or additive model and then compared to simpler models. If no significant

differences were observed with a simpler model, a new QTL analysis and permutations test were

performed with the simpler model. The simpler model was assumed to be the best model if the

peaks were above the LOD threshold; otherwise, the additive model was selected as the best.

Significant differences were identified in several SNP markers for all traits. Only SNP with p-

values < 0.01 for the ANOVA or the Kruskal-Wallis test and located ±20 cM from a detected

QTL are reported. The markers and their type of effect were also given for the SNP with

significant effects (Table 4.5). A positive effect of a marker (+) means that the mean is higher in

the simplex genotypes compared to the nulliplex genotypes; and a negative effect (-) indicates

that means are lower in the simplex genotypes. Combining these results with the availability of

the potato genome sequence; the markers with significant effects located nearby QTL regions

could be good candidates for further analysis towards the development of markers for marker

assisted selection. This is especially true for those with larger effects, present in most years of

evaluation and in simplex dosage where the effect of the marker is the desired effect on the trait.

The presence or absence of a significantly associated marker even if it is closely linked to the

QTL can be used successfully to select for the best phenotypes only if the QTL is in simplex

142

dosage and in coupling with the marker. For example, a marker with potential to be converted in

a presence/absence marker used in marker assisted selection for pitted scab tolerance was found

on Chr. 2 of Superior (Figure 4.18). This c2_ 13213414 marker is nearby a QTL in simplex

dosage that increases the incidence and severity of pitted scab when present. This marker was

located in the same homolog as the QTL and had the same effect. This marker could be used to

select against this QTL.

Because of the complex genetic nature of tetraploid potatoes, the direct application of most of the

associated markers identified in this study is going to be challenging. Several QTL were additive

meaning that their segregation is complex and cannot be explained by a simple inheritance

model. Additional fine mapping analyses within the identified QTL regions need to be performed

in order to identify candidate genes that explain the phenotypic variation. Specific markers for

those regions should be developed using the available potato genome sequence information.

Marker assisted selection (MAS) in potato offers great opportunities to use the currently

available genetic data (Barone 2004) that have not been extensively exploited. MAS in potato

has been applied mostly for pathogen resistance (Pineda et al. 1993, Hämäläinen et al. 1997,

Oberhagemann et al. 1999, Colton et al. 2006, Gebhardt 2006, Śliwka et al. 2010, Lopez-Pardo

et al. 2013) and in a few cases related to tuber quality (Freyre and Douches 1994, Li et al. 2013).

We expect to contribute with new target regions that can be exploited to use MAS for improving

tuber quality traits and scab tolerance. Future analyses of the reciprocal population Superior x

Atlantic would be performed to confirm the QTL regions, and the associations of some SNP

markers with the traits of interest. Lastly, the information provided by our study is a starting

point to locate the actual genes that control tuber calcium, tuber quality and pitted scab tolerance.

143

CONCLUSIONS

The results of this study lead us to conclude the following:

1. A tetraploid map was successfully constructed using 600 simplex SNP markers. The map

for Atlantic had more than twice the number of markers, 414, compared to Superior, 186,

suggesting that the SolCAP 8300 Infinium.

2. A large number of SNP loci with duplex genotypes were identified. Most of these are

probably products of genotyping errors.

3. Using an interval mapping approach, several quantitative trait loci were identified for

tuber calcium, tuber quality traits and pitted scab tolerance in the Atlantic x Superior

population.

4. Few and unstable QTL were detected for blackspot bruise, a trait with low heritability in

this study. Also, the small population size of the 2011 standard field trial caused over-

estimation of QTL effects. Both these results suggest that the Beavis effect can also occur

in tetraploid populations.

5. Tuber quality traits correlated to tuber calcium showed QTL in close positions on the

same chromosome indicating that their correlation can be explained at least partially due

to linkage.

6. The detection and sometimes location of QTL varied between years of evaluation. The

sources of error included environmental variation and population size.

7. Markers with significant effects were identified for several traits in the marker regression

analysis. We are reporting only those close to QTL positions.

8. Approximately half of the QTL were additive. It means that these QTL have a complex

144

inheritance. Nevertheless, some QTL had simpler inheritance such as dominant alleles in

simplex and duplex dosage.

9. Finally, combining the information of this QTL map and the potato genome sequence

offers opportunities to develop markers suitable for MAS and the identification of the

genes that are responsible for controlling tuber quality and tuber calcium in the future.

BIBLIOGRAPHY

Alam, Z. 1972. Inheritance of scab resistance in 24-chromosome potatoes. Ph.D. dissertation University of Wisconsin. Dissertation Abstract. B 32:6764-6765. Bamberg, J.B., J.E Palta, L.A. Peterson, M. Martin, and A.R. Krueger. 1993. Screening tuber-bearing Solanum (potato) germplasm for efficient accumulation of tuber calcium. American Journal of Potato Research 70: 219-226. Barone, A. 2004. Molecular Marker-assisted selection for potato breeding. American Journal of Potato Research 81: 111-117. Beavis, W.D. 1994. The power and deceit of QTL experiments: lessons from comparative QTL studies. In Proceedings of the Forty-Ninth Annual Corn and Sorghum Industry Research Conference, 250-266. Washington, DC: American Seed Trade Assoc. Beavis, W.D. 1998. QTL analyses: power, precision, and accuracy in molecular dissection of complex traits, ed A.H. Paterson, 145-162. Boca Raton, FL: CRC. van Berloo, R., R.C.B. Hutten, H.J. van Eck and R.G.F. Visser. 2007. An online potato pedigree database resource. Potato Research 50: 45-57. Bhaskar, P.B., L. Wu, J.S. Busse, B.R. Whitty, A.J. Hamernik, S.H. Jansky and J. Jiang. 2010. Suppression of the vacuolar invertase gene prevents cold-induced sweetening in potato. Plant Physiology 154: 939-948. Bonferroni, C.E. 1935. Il calcolo delle assicurazioni su gruppi di teste. In Studi in Onore del Professore Salvatore Ortu Carboni, 13-60. Rome, Italy. Bradshaw, J. E. 1994. Quantitative Genetics Theory for Tetrasomic Inheritance. In Potato Genetics, eds. J.E. Bradshaw and G.R. Mackay, 76-77. Wallingford, UK: CAB International. Bradshaw, J.E., C.A. Hackett, B. Pande, R. Waugh, and G.J. Bryan. 2008. QTL mapping of

145

yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Theoretical and Applied Genetics 116: 193-211. Braun, S.R. 2013. Quantitative trait loci analysis and breeding for resistance to common scab in potato. Ph.D. dissertation Plant Breeding and Plant Genetics. University of Wisconsin. Broman, K.W., H. Wu, S. Sen and G.A. Churchill. 2003. R/qtl: QTL mapping in experimental crosses. Bioinformatics 19: 889-890. Broman, K.W., and Sen S. 2009. A guide to QTL mapping with R/qtl. Springer, New York. Broman, K.W. 2010. Technical Report # 214. University of Wisconsin - Madison. Accessed on August 2013. Colton, L. M., H.I. Groza, S.M. Wielgus and J. Jiang. 2006. Marker-assisted selection for the broad-spectrum potato late blight resistance conferred by gene RB derived from a wild potato species. Crop Science 46: 589-594. Churchill, G.A., and R. W. Doerge. 1994. Empirical threshold values for quantitative trait mapping. Genetics 138: 963-971. Dees, M.W., and L.A Wanner. 2012. In search of better management of potato common scab. Potato Research 55: 249-268. Douches, D., and R. Freyre, 1994. Identification of Genetic Factors Influencing Chip Color in Diploid Potato (Solanum spp.). American Journal of Potato Research 71: 581-590. Felcher K.J., J.J. Coombs, A.N. Massa, C.N. Hansey, J.P. Hamilton, R.E. Veilleux, C.R. Buell, and D.S. Douches. 2012. Integration of two diploid potato linkage maps with the potato genome sequence. PLoS ONE 7: e36347. doi:10.1371/journal.pone.0036347 Freyre, R., and D.S Douches.1994. Development of a model for marker-assisted selection of specific gravity in diploid potato across environments. Crop Science 34: 1361-1368. Gebhardt, C., D. Bellin, H. Henselewski, W. Lehmann, J. Schwarzfischer, and J.P.T. Valkonen. 2006. Marker-assisted combination of major genes for pathogen resistance in potato. Theoretical and Applied Genetics 112: 1458-1464. Hackett, C.A, J.E. Bradshaw, R.C. Meyer, J.W. McNicol, D. Milbourne, and R. Waugh. 1998. Linkage analysis in tetraploid species: A simulation study. Genetical Research 71: 143-153. Hackett, C.A., J.E. Bradshaw, and J.W. McNicol, 2001. Interval mapping of QTLs in autotetraploid species. Genetics 159: 1819-1832. Hackett, C.A., I. Milne, J.E. Bradshaw, and Z. Luo. 2007. TetraploidMap for Windows: Linkage

146

map construction and QTL mapping in autotetraploid species. Journal of Heredity 98: 727-729. Haldane, J. B. S. 1930. Theoretical genetics of autopolyploids. Journal of Genetics 22: 349-372. Hamilton, J.P., C. N. Hansey, B. R. Whitty, K. Stoffel, A.N. Massa, A. Van Deynze, W.S. De Jong, D.S. Douches, and C.R. Buell. 2011. Single nucleotide polymorphism discovery in elite North American potato germplasm. BMC Genomics 12: 302-312. Hämäläinen, J. H, K.N. Watanabe, J.P.T. Valkonen, A. Arihara, R.L. Plaisted, E. Pehu, L. Miller, and S.A. Slack. 1997. Mapping and marker-assisted selection for a gene for extreme resistance to potato virus Y. Theoretical and Applied Genetics 94: 192-197. Hirsch, C. N., C. D. Hirsch, K. Felcher, J. Coombs, D. Zarka, A. Van Deynze, W. De Jong, R. E. Veilleux, S. Jansky, P. Bethke, D.S. Douches and C.R. Buell. 2013. Retrospective View of North American Potato (Solanum tuberosum L.) Breeding in the 20th and 21st Centuries. G3: Genes| Genomes| Genetics 3: 1003–1013. Haynes, K.G. and D.S. Douches. 1993. Estimation of the coefficient of double reduction in the cultivated tetraploid potato. Theoretical and Applied Genetics 85: 857-862. Jeong, J.C., H.C. Ok, O.S. Hur, C.G. Kim, C.S. Park, and S.Y. Kim. 2005. Raw material characteristics affect enzymatic browning of pre-peeled potato tubers. Journal of the Korean Society for Horticultural Science 46: 246-249. Jombart, T. 2008. Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics Applications Note 24: 1403-1405. Karlsson, B.H., J.P. Palta and P. M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. Hort Science 41: 1213-1221. Kleinhenz, M.D., J.P. Palta, C.C. Gunter, and K.A. Kelling. 1999. Impact of source and timing of calcium and nitrogen applications on Atlantic potato tuber calcium concentrations and internal quality. Journal of the American Society for Horticultural Science 124: 498-506. Krawczak, M. 1999. Informativity assessment for biallelic single nucleotide polymorphisms. Electrophoresis 20: 1676-1681. Krokida, M.K., V. Oreopoulou, Z.B. Maroulis and D. Marinos-Kouris. 2001. Colour changes during deep fat frying. Journal of Food Engineering 48: 219-225. Leach, L. J., L. Wang, M. J. Kearsey, and Z. Luo. 2010. Multilocus tetrasomic linkage analysis using hidden Markov chain model. PNAS 107: 4270-4274. Li, L., J. Strahwald, H.R. Hofferbert, J. Lübeck, E. Tacke, H. Junghans, and C. Gebhardt. 2005. DNA variation at the invertase locus invGE/GF is associated with tuber quality traits in

147

populations of potato breeding clones. Genetics 170: 813-821. Li, L., M. J. Paulo, J. Strahwald, J. Lübeck, H. R. Hofferbert, E. Tacke, H. Junghans, J. Wunder, A. Draffehn, F. van Eeuwijk, and C. Gebhardt. 2008. Natural DNA variation at candidate loci is associated with potato chip color, tuber starch content, yield and starch yield. Theoretical and Applied Genetics 116: 1167-1181. Li, L.,E. Tacke, H. R. Hofferbert, J. Lübeck, J. Strahwald, A. M. Draffehn, B. Walkemeier, and C. Gebhardt. 2013. Validation of candidate gene markers for marker-assisted selection of potato cultivars with improved tuber quality. Theoretical and Applied Genetics 126: 1039-1052. Liu, P. Y., Z. Jun, and Y. Lu. 2006. Impacts of QTL x environment interactions on genetic response to marker-assisted selection. Acta Genetica Sinica 33: 63-71. Lopez‐Pardo, R., L. Barandalla, E. Ritter and J.I. Ruiz de Galarreta. 2013. Validation of molecular markers for pathogen resistance in potato. Plant Breeding 132: 246-251. Luo, Z. W., C. A. Hackett, J. E. Bradshaw, J. W. McNicol, and D. Milbourne, 2001. Construction of a genetic linkage map in tetraploid species using molecular markers. Genetics 157: 1369-1385. Matheis, G. 1987. Polyphenol oxidase and enzymatic browning of potatoes (Solanum tuberosum). II. Enzymatic browning and potato constituents. Chemie Mikrobiologie Technologie der Lebensmittel 11: 67-70. Mather, K. 1935. Reductional and equational separation of the chromosomes in bivalents and multivalents. Journal of Genetics 30: 53-78. Mather, K. 1936. Segregation and linkage in autotetraploids. Journal of Genetics 32: 287-314. McCann, L. C., P. C. Bethke, and P. W. Simon. 2010. Extensive variation in fried chip color and tuber composition in cold stored tubers of wild potato (Solanum) germplasm. Journal of Agricultural and Food Chemistry 58: 2368-2376. McCord, P. H., B. R. Sosinski, K. G. Haynes, M. E. Clough, and G. C. Yencho. 2011a. Linkage mapping and QTL analysis of agronomic traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Crop Science 51: 771-785. McCord, P.H., B. R. Sosinski, K.G. Haynes, M. E. Clough, and G. C. Yencho. 2011b. QTL mapping of internal heat necrosis in tetraploid potato. Theoretical and Applied Genetics 122: 129-142. McGuire, R. G., and A. Kelman. 1984. Reduced severity of Erwinia soft rot in potato tubers with increased calcium content. Phytopathology 74: 1250-1256.

148

Menéndez, C. M., E. Ritter, R. Schäfer-Pregl, B. Walkemeier, A. Kalde, F. Salamini, and C. Gebhardt. 2002. Cold sweetening in diploid potato: mapping quantitative trait loci and candidate genes. Genetics 162: 1423-1434. Meyer, R. C., D. Milbourne, C. A. Hackett, J. E. Bradshaw, J. W. McNichol, and R. Waugh. 1998. Linkage analysis in tetraploid potato and association of markers with quantitative resistance to late blight (Phytophthora infestans). Molecular and General Genetics 259: 150-160. Muller, H.J. 1914. A new mode of segregation in Gregory’s tetraploid Primulas. The American Naturalist 48: 508-512. Nei, M. 1972. Genetic distance between populations. The American Naturalist 106: 283-292. Newman, S.M., N.T. Eannetta, H.Yu, J.P. Prince, M.C. de Vicente, S.D. Tanksley, and J.C. Steffens. 1993. Organisation of the tomato polyphenol oxidase gene family. Plant Molecular Biology 21: 1035-1051. Oberhagemann, P., C. Chatot-Balandras, R. Schäfer-Pregl, D. Wegener, C. Palomino, F. Salamini, and C. Gebhardt. 1999. A genetic analysis of quantitative resistance to late blight in potato: towards marker-assisted selection. Molecular Breeding 5: 399-415. Olsen, N. L., L. K. Hiller, and L. J. Mikitzel. 1996. The dependence of internal brown spot development upon calcium fertility in potato tubers. Potato Research 39: 165-178. Ozgen, S., B. H. Karlsson, and J. P. Palta. 2006. Response of potatoes (cv. ‘Russet Burbank’) to supplemental calcium applications under field conditions. Tuber calcium, yield, and incidence of brown spot. American Journal of Potato Research 83: 195-204. Palta, J.P. 1996. Role of calcium in plant responses to stresses: Linking basic research to the solution of practical problems. HortScience 31: 51-57. Paterson, A. H, Y. Saranga, M. Menz, C. X. Jiang, and R. J. Wright. 2003. QTL analysis of genotype × environment interactions affecting cotton fiber quality. Theoretical and Applied Genetics 106: 384-396. Pineda, O., M.W. Bonierbale, R.L. Plaisted, B.B. Brodie, and S.D. Tanksley. 1993. Identification of RFLP markers linked to the H1 gene conferring resistance to the potato cyst nematode Globodera rostochiensis. Genome 36: 152-156. Pompanon, F., A. Bonin, E. Bellemain, and P. Taberlet. 2005. Genotyping errors: causes, consequences and solutions. Nature Reviews Genetics 6: 847-846. Potato Genome Sequencing Consortium. 2011. Genome sequence and analysis of the tuber crop potato. Nature 475: 189-195.

149

R Development, Core. Team. 2011: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Rodriguez-Saona, L.E., and R. Wrostald. 1997. Influence of potato composition on chip color quality. American Journal of Potato Research 74: 87-106. Sagredo, B., N. Balbyshev, A. Lafta, H. Casper, and J. Lorenzen. 2009. A QTL that confers resistance to Colorado potato beetle (Leptinotarsa decemlineata [Say]) in tetraploid potato populations segregating for leptine. Theoretical and Applied Genetics 119: 1171-1181. Sapers, G.M., F.W. Douglas, A. Bilyk, A.F. Hsu, H.W. Dower, L. Garzarella, and M. Kozempel. 1989. Enzymatic browning in Atlantic potatoes and related cultivars. Journal of Food Science 54: 362-365. Simko, I, S. Costanzo, K. G. Haynes, B. J. Christ, R. W. Jones. 2004. Linkage disequilibrium mapping of a Verticillium dahliae resistance quantitative trait locus in tetraploid potato (Solanum tuberosum) through a candidate gene approach. Theoretical and Applied Genetics 108: 217-224. Śliwka, J., H. Jakuczun, P. Kamiński, and E. Zimnoch-Guzowska. 2010. Marker-assisted selection of diploid and tetraploid potatoes carrying Rpi-phu1, a major gene for resistance to Phytophthora infestans. Journal of Applied Genetics 51: 133-140. Sorensen, T. 1948. A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analysis of vegetation on Danish commons. Biologiske Skrifter 5: 1-34. Sterret, S.B. and M.R. Henninger 1997. Internal heat necrosis in the midatlantic region-influence of environment and cultural management. American Journal of Potato Research 74: 233-243. Tétard-Jones, C., M.A. Kertesz, and R.F. Preziosi. 2011. Quantitative trait loci mapping of phenotypic plasticity and genotype-environment interactions in plant and insect performance. Philosophical Transactions of the Royal Society B: Biological Sciences 366: 1368-1379. Tzeng, K. C., A. Kelman, K. E. Simmons, and K. A. Kelling. 1986. Relationship of calcium nutrition to internal brown spot of potato tubers and sub-apical necrosis of sprouts. American Journal of Potato Research 63: 87-97. Ungerer, M.C., S.S. Halldorsdottir, M.D. Purugganan, and T.F.C. Mackay. 2003. Genotype-environment interactions at quantitative trait loci affecting inflorescence development in Arabidopsis thaliana. Genetics 165: 353-365. Urbany, C., B. Stich, L. Schmidt, L. Simon, H. Berding, H. Junghans, K.H. Niehoff, A. Braun, E. Tacke, H.R. Hofferbert, J. Lübeck, J. Strahwald, and C. Gebhardt. 2011. Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration. BMC genomics 12: 7.

150

Vega, S.E., Palta, J.P., Bamberg, J.B. 2006. Exploiting cultivated germplasm to breed for enhanced tuber calcium accumulation ability [abstract]. American Journal of Potato Research 83: 136. Werij, J.S., B. Kloosterman, C. Celis-Gamboa, C.R. de Vos, T. America, R.G. Visser, and C.W. Bachem. 2007. Unravelling enzymatic discoloration in potato through a combined approach of candidate genes, QTL, and expression analysis. Theoretical and Applied Genetics 115: 245-252. Wu, R., M. Gallo-Meagher, R. C. Littell, and Z. B. Zeng. 2001. General polyploid model for analyzing gene segregation in outcrossing tetraploid species. Genetics 159: 869-882. Würschum, T. 2012. Mapping QTL for agronomic traits in breeding populations. Theoretical and Applied Genetics 125: 201-210. Zhuang, J. Y., H.X. Lin, J. Lu, H.R. Qian, S. Hittalmani, N. Huang, and K.L. Zheng. 1997. Analysis of QTL× environment interaction for yield components and plant height in rice. Theoretical and Applied Genetics 95: 799-808.

151

TABLES Table 4.1. Selecting SNP markers from the 8303 SNP genotyped in the Atlantic x Superior population to be used in tetraploid linkage mapping. Numbers indicate remaining SNP markers and genotypes.

Criteria to remove from the analysis Remaining

SNP Remaining Genotypes

Initial SNP and genotypes 8303 184 Questionable and bad SNPs 7666 Missing data in all genotypes 5024 No hit or more than two hits 4605† Mixed and twice-sampled genotypes 176 Located in two positions in the genome 4498 Missing in one or both parents 4088 Keep only simplex markers 968‡ SNP with >16.67% double reduction 962 Markers with high segregation distortion (<0.05/#markers)

913

Duplicated markers 628 Markers with <130 individuals typed 619 Individuals with <580 markers typed 166 Duplicated genotypes (>0.99 identity) 151 Markers with high segregation distortion (<0.001) 614 Markers in coupling with more than two homologs 600 Final SNP and genotypes 600 151 † Used in the genetic structure analysis

‡ Data used in the double reduction analysis

152 Table 4.2. The Atlantic x Superior linkage map using SNP markers and QTL identified by parent and chromosome

Chr. SNP markers Map Length (cM)

Total ATL SUP ATL SUP 1 65 42 23 123.7 107.1 2 71 49 22 113.3 88.7 3 62 45 17 115.6 78.3 4 45 32 13 110.2 116 5 56 38 18 97.2 61.5 6 43 36 7 106.1 53.5 7 52 28 24 88.2 85.3 8 53 34 19 86.9 52.9 9 50 37 13 117.2 92.8

10 34 21 13 109.0 44.3 11 39 34 5 86.2 34.8 12 30 18 12 84.8 73.8

Total 600 414 186 1238.4 889

153 Table 4.3. Broad-sense heritabilities per year and pooled data, and QTL present in Atlantic (ATL) and Superior (SUP) for tuber calcium (TC), tuber yield (TY), specific gravity (SG), chip color (CC), browning (EB), agtron (AG), chip lightness (L), chip redness (a), and chip yellowness (b), incidence of hollow heart (HH), black spot bruise (BB), pitted scab (PS), incidence (PS-E) and severity (SPS-E) of pitted scab in a high disease pressure field.

Trait Units Pooled data

Broad-sense heritability† QTL

Pooled 2009 2010 2011 2012 Total ATL SUP

TC µg/g Pool1 2009, 2010 0.61 0.61 0.59 0.44 - 8 7 1

Pool2 2009- 2011 0.55

TY ton/ha Pool1 2009, 2010 0.66 0.85 0.85 0.77 - 6 2 4

Pool2 2009- 2011 0.67

SG g/g Pool1 2009- 2010 0.54 0.68 0.76 0.78 - 10 8 2

Pool2 2009- 2011 0.56

EB 1 to 5‡ Pool 2010, 2011 0.74 - 0.73 0.74 - 5 2 3

AG agtron - - - 0.81 - - - 5 1 4

CC 1 to 5‡ Pool1 2009, 2010 0.42 0.48 0.62 0.83 - 8 6 2

Pool2 2010, 2011 0.64

L lightness Pool 2010, 2011 0.63 - 0.67 0.85 - 2 2 0

A redness Pool 2010, 2011 0.44 - 0.40 0.73 - 2 2 0

B yellowness Pool 2010, 2011 0.29 - 0.67 0.81 - 2 2 0

HH % Pool 2009-2011 0.72 0.59 0.74 0.73 - 7 5 2

BB % - - - 0.30 0.30 0.19 - 2 2 0

PS % Pool 2009- 2011 0.43 0.34 0.49 0.38 - 4 2 2

PS-E % Pool 2011, 2012 0.69 - - 0.57 0.65 7 3 4

SPS-E lesions/tuber Pool 2011, 2012 0.82 - - 0.74 0.80 7 3 4

75 47 28 †Heritabilities presented in Chapter 3 ‡ Visual scale from 1 to 5 used as a numerical variable for genetic analysis, where 1 is very light and 5 is very dark P-value symbols: (**) p <0.01, (*) p < 0.05, (.) p < 0.1, (NS) p ≥0.1

154 Table 4.4. Total and mapped population size from the Atlantic x Superior population Year Field Population

size Mapped population size

Single year evaluations 2009 Standard 121 89 2010 Standard 158 128 2011 Standard 40 32 2011 High disease pressure 128 106 2012 High disease pressure 87 70 Pooled evaluations 2009-2010 Standard 168 128 2010-2011 Standard 160 128 2011-2012 High disease pressure 130 106 2009-2011 Standard 189 128

155 Table 4.5. QTL and SNP markers with significant effects (p<0.01) identified in the Atlantic x Superior population phenotyped during the 2009-2012 seasons for tuber calcium, tuber quality traits and pitted scab

Trait Chr. Pa cM CI LOD %V BM Year detected† Sig. SNP (effect) TC I ATL 101.7 98.7-113.7 2.7 10.7 dup(-) Pool1, 09, 10 TC III ATL 50.0 40-62 3.1 12.2 addit. Pool1, 09, 11 c3_26996294(-) TC V ATL 56.0 42-68 2.5 7.7 simp(+) Pool1, Pool2, 09,

10 c5_6266409(+) c5_6747390(+)

c5_10643561(+) TC VII ATL 76.0 46-88.2 2.4 8.1 simp(-) Pool1, Pool2, 10 TC VIII ATL 46.9 40.9-52.9 3.6 11.7 addit. Pool2, 10, 11 c8_18983006(+)

c8_27972634(+) TC IX ATL 87.2 82.2-100.2 2.4 14.5 dup(-) 09, 11 TC XI ATL 54.2 45.7-72.2 3.4 30.3 addit. 10, 11 c11_16860215(+)

c11_8648059(+) TC XII SUP 28.0 13.5-44 3.9 16.4 addit. Pool1, 09 TY I ATL 73.7 47.7-86.7 3.2 10.7 addit. Pool1, 09 TY I SUP 10.0 5-15 3.4 9.1 addit. Pool1, 09, 10 TY I SUP 102.0 88.5-107.1 3.7 13.1 addit. Pool2, 09, 10 c1_25114767(+)

c1_35975667(+) TY II SUP 22.0 18-50 2.6 11.3 simp(+) Pool1, 09, 10, 11 TY III ATL 112.0 107-112 4.1 21.8 dup(+) Pool1, 09 c3_40272236(-) TY IV SUP 20.0 6-48 2.8 8.9 dup(+) Pool2, 11 c4_38235495(-) SG I ATL 83.7 72.7-94.7 3.4 12.4 addit. 09 SG I ATL 101.7 99.2-106.7 4.3 39.5 addit. 11 c1_72865934(+) SG I SUP 104.0 91-107.1 3.7 11.0 addit. Pool2, 09, 10 SG II ATL 7.3 0-30.3 3.8 17.6 addit. 09 c2_10655356(-)

c2_16641561(-) c2_19385694(-)

SG VII ATL 22.0 14-26 3.4 11.2 dup(-) Pool2, 10, 11 c7_2649481(+) c7_2649508(+) c7_5592920(+) c7_6019278(+) c7_7731500(+) c7_8404685(+) c7_9699749(+)

SG VIII ATL 30.9 3-35 4.1 18.7 dup(+) 09 SG IX SUP 30.8 10.8-34.8 3.2 9.0 dup(-) Pool2, 10 c9_1140252(-)

c9_26345846(-) c9_30026592(-)

SG XI ATL 70.2 68.2-86.2 3.2 15.6 dup(+) 09 SG XII ATL 20.0 3-34 3.6 11.8 addit. Pool2, 09, 10, 11 c12_502211(+) SG XII ATL 60.0 50-84.8 2.0 7.7 simp(-) Pool1, 09, 10 c12_52414999(+)

c12_53697469(-) †Years with peaks, at least one above the permutations threshold. Data on the table corresponds to the year in bold and the best model for the dosage and effects. Chr.=chromosome, Pa=parents, cM=centimorgan, CI=confidence interval, %V=%variance explained, BM=best model, addit.=addititve, complex inheritance, dup(+)=duplex, the dominant allele increases the mean, dup(-)=duplex, the dominant allele decreases the mean, simp(+)=simplex, the mean increases if present, simp(-)=simplex, the mean decreases if present, (+)=mean increase, and (-)=mean decrease, TC = tuber calcium, TY = total yield, SG = specific gravity and EB = enzymatic browning. Population size varied from year to year as indicated in Table 4.4. BLUP values were estimated including the mixed and duplicated genotypes.

Table 4.5 continues on the next page

156 Continue

Trait Chr. Pa cM CI LOD %V BM Year detected† Sig. SNP (effect) EB I ATL 81.7 70.2-92.7 3.0 7.4 addit. Pool, 10, 11 c1_66696384(-)

c1_67731638(-) c1_67731638(-)

EB V SUP 40.0 32-51 3.2 7.9 addit. Pool, 10 EB VI SUP 53.5 12.5-53.5 2.7 8.6 simp(+) Pool, 10 c6_52436008(+) EB VII SUP 6.0 0-9 2.4 28.5 simp(+) Pool, 11 EB VIII ATL 50.9 27-62 3.2 13.0 simp(-) Pool, 10 AG I SUP 68.0 53-101 3.5 20.7 dup(-) 09 c1_68432076(-)

c1_80006794(+) c1_80510838(+)

AG II SUP 86.0 58-88.7 2.0 9.6 simp(-) 09 c2_44147246(-) AG IV SUP 4.0 0-18 3.8 15.8 addit. 09 AG V SUP 6.0 0-17 2.5 11.8 dup,dom+ 09 c5_4797133(-) AG VII ATL 74.0 62.5-77.5 4.1 18.3 simp(+) 09 c7_44184334(+)

c7_44224371(+) c7_45268684(+) c7_45489117(+) c7_45837289(+) c7_46120714(+) c7_46225074(+) c7_46414390(+) c7_48185545(+) c7_49676492(+)

CC I SUP 66.0 57-80 2.8 10.3 simp(+) Pool1, 09 c1_68432076(+) c1_69501311(+)

CC I SUP 80.0 58-84 3.2 8.8 addit. Pool2, 10, 11 c1_68432076(+) c1_69501311(+)

CC IV ATL 34.0 25-47 2.8 10.1 simp(+) Pool1, Pool2, 10 CC VI ATL 36.0 27-66 2.5 9.1 dup(-) Pool1, 09, 11 c6_24006040(+) CC VII ATL 70.0 48-82.5 3.0 9.9 dup(+) Pool1, Pool2, 09,

10 c7_44224371(-) c7_45268684(-) c7_45489117(-) c7_45837289(-)

CC VIII ATL 84.9 78.9-86.9 3.9 13.8 addit. Pool1, Pool2, 09, 10

CC IX ATL 89.2 87.2-94.2 2.7 14.9 dup(+) Pool1, Pool2, 10, 11

CC XI ATL 14.2 10.2-35.2 4.8 41.4 addit. 11 L VII ATL 76.0 68-88.2 3.3 11.0 dup(-) Pool, 10 c7_45450767(-) L IX ATL 89.2 83.2-99.7 2.2 11.8 dup(-) Pool, 10, 11 c9_47031950(-)

† Years with peaks, at least one above the permutations threshold. Data on the table corresponds to the year in bold and the best model for the dosage and effects. Chr.=chromosome, Pa=parents, cM=centimorgan, CI=confidence interval, %V=%variance explained, BM=best model, addit.=addititve, complex inheritance, dup(+)=duplex, the dominant allele increases the mean, dup(-)=duplex, the dominant allele decreases the mean, simp(+)=simplex, the mean increases if present, simp(-)=simplex, the mean decreases if present, (+)=mean increase, and (-)=mean decrease, EB=enzymatic browning, AG=chip color in agtrons, CC=visual rate of chip color, L=chip lightness, A=chip redness, and B=chip yellowness. Population size varied from year to year as indicated in Table 4.4. BLUP values were estimated including the mixed and duplicated genotypes.


157 Continue

Trait Chr. Pa cM CI LOD %V BM Year detected† Sig. SNP (effect) A VIII ATL 86.9 82.9-86.9 3.3 10.5 simp(-) Pool, 10, 11 c8_35411921(-)

c8_39195950(-) c8_40106266(-)

A IX ATL 89.2 76.2-96.2 2.4 13.3 dup(+) Pool, 10, 11 B V ATL 38.0 28-47 3.1 8.4 addit. Pool, 10 c5_4792932(-)

c5_5117198(-) B VIII ATL 86.9 84.9-86.9 2.1 6.6 dup(+) Pool, 10

HH I ATL 45.7 31.7-48.7 5.4 57.0 addit. 11 HH III ATL 0.0 0-16 4.6 17.0 addit. Pool, 09, 10 c3_14240272(+)

c3_15690374(+) c3_18808254(+) c3_21658971(+) c3_26513199(+) c3_26996294(+) c3_27538176 (+) c3_6266729 (+) c3_8946904 (+)

HH III ATL 40.0 38-49 5.0 19.7 simp(-) Pool, 09, 10, 11 c3_14240272(+) c3_15690374(+) c3_18808254(+) c3_21658971(+) c3_26513199(+) c3_26996294(+) c3_27538176 (+) c3_6266729 (+) c3_8946904 (+)

HH III SUP 44.0 32-61 2.8 7.5 addit. Pool, 09, 10 c3_17294767(-) c3_17931555(-)

HH V SUP 22.0 19-24.5 4.2 49.6 dup(-) 11 c5_4797133(-) c5_6224818(-)

c5_14027989(-) HH VI ATL 70.0 67-74 3.4 19.0 dup(-) Pool, 10 c6_47540578(-) HH IX ATL 101.2 99.2-104.2 4.8 71.7 addit. 09, 11 BB X ATL 21.0 8-31 4.3 23.9 dup(+) 09 BB XI ATL 50.2 38.2-64.2 3.0 7.1 dup(-) 10

†Years with peaks, at least one above the permutations threshold. Data on the table corresponds to the year in bold and the best model for the dosage and effects. Chr.=chromosome, Pa=parents, cM=centimorgan, CI=confidence interval, %V=%variance explained, BM=best model, addit.=addititve, complex inheritance, dup(+)=duplex, the dominant allele increases the mean, dup(-)=duplex, the dominant allele decreases the mean, simp(+)=simplex, the mean increases if present, simp(-)=simplex, the mean decreases if present, (+)=mean increase, and (-)=mean decrease, HH=incidence of hollow heart and BB=incidence of blackspot bruise. Population size varied from year to year as indicated in Table 4.4. BLUP values were estimated including the mixed and duplicated genotypes.


158 Continue

Trait Chr. Pa cM CI LOD %V BM Year detected† Sig. SNP (effect) PS III ATL 48.0 39-53 3.2 10.7 dup(-) Pool c3_29440562(-) PS IV SUP 24.0 10-27 4.6 13.7 addit. Pool, 09, 10, 11 c4_6259961(+)

c4_8401238(+) PS V SUP 26.0 17.5-37.5 3.1 7.8 addit. 10 c5_41648687(-) PS XII ATL 6.0 0-18.5 3.8 10.2 addit. Pool, 09, 10 c12_9644160(-)

PS-E II SUP 18.0 14-28 4.2 23.0 simp(+) Pool, 11, 12 c2_1498967(-) c2_13213414(+)

PS-E III ATL 80.0 67-93 3.2 12.8 dup(-) Pool, 12 c3_36273874(-) PS-E V SUP 6.0 0-8 2.6 9.7 addit. Pool, 11, 12 c5_3536366(-)

c5_4796997(-) c5_5845469(-) c5_6413644(-)

PS-E VI SUP 3.5 3.5-16 1.9 7.8 dup(+) Pool, 12 PS-E VII ATL 38.0 20-62 3.2 10.8 addit. Pool, 12 PS-E X SUP 24.0 12.5-28 2.2 9.8 dup(-) Pool, 11, 12 PS-E XI ATL 74.2 80.2-86.2 3.1 12.1 dup(-) Pool, 11, 12

SPS-E II SUP 18.0 0-30 2.6 14.7 simp(+) Pool, 11, 12 c2_13213414(+) SPS-E III ATL 80.0 67-86 4.4 17.6 dup(-) Pool, 11, 12 c3_36273874(-) SPS-E V SUP 0.0 0-10 3.4 9.5 addit. Pool, 11, 12 c5_3536366(-)

c5_4796997(-) c5_5845469(-) c5_6413644(-)

SPS-E VI SUP 3.5 0-14.5 3.1 10.1 addit. Pool, 12 SPS-E IX ATL 101.2 97.2-103.7 4.0 49.6 addit. 12 SPS-E X SUP 24.0 20-27.5 2.5 11.0 dup(-) Pool, 11, 12 c10_39831786(-)

c10_40518785(+) SPS-E XI ATL 80.2 74.2-86.2 4.0 17.6 dup(-) Pool, 11

†Years with peaks, at least one above the permutations threshold. Data on the table corresponds to the year in bold and the best model for the dosage and effects. Chr.=chromosome, Pa=parents, cM=centimorgan, CI=confidence interval, %V=%variance explained, BM=best model, addit.=addititve, complex inheritance, dup(+)=duplex, the dominant allele increases the mean, dup(-)=duplex, the dominant allele decreases the mean, simp(+)=simplex, the mean increases if present, simp(-)=simplex, the mean decreases if present, (+)=mean increase, and (-)=mean decrease, PS= incidence of pitted scab in the standard field, PS-E= incidence of pitted scab in the high disease pressure field, and SPS-E= severity of pitted scab in the high disease pressure field. Population size varied from year to year as indicated in Table 4.4. BLUP values were estimated including the mixed and duplicated genotypes.

159

FIGURES Figure 4.1. Genetic structure based on principal components analysis of Atlantic x Superior progenies and parents explaining 8.53% of the total genotypic variance. ATL3* had been misidentified as Superior, ATL4* had been misidentified as B-028, and SUP2* had been misidentified as B-064.

160 Figure 4.2. Pairwise comparison of genotypic identity. Identities higher than 0.99 indicating duplicated genotypes are shown with an arrow.

Pairwise Comparison of Genotype Identity

Pairwise identity

Nu

mb

er o

f p

air-

wis

e co

mp

aris

on

s

0.0 0.2 0.4 0.6 0.8 1.0

020

060

010

00

Duplicated genotypes(identity>0.99)

161 Figure 4.3. Genetic maps for Atlantic and Superior based on 600 simplex SNP markers.

162 Figure 4.4. Pedigree of the parents

Atlantic Superior

Plots obtained from the Potato pedigree database (van Berloo et al. 2007)

163

Figure 4.5. Genetic maps and QTL located on chromosome 1 of Atlantic and Superior. Error bars indicate the ± 1 LOD confidence interval for the QTL location

164 Figure 4.6. Genetic maps and QTL located on chromosome 2 of Atlantic and Superior. . Error bars indicate the ± 1 LOD confidence interval for the QTL location

165 Figure 4.7. Genetic maps and QTL located on chromosome 3 of Atlantic and Superior. Error bars indicate the ± 1 LOD confidence interval for the QTL location

175 Figure 4.17. LOD profiles in different years of evaluation for the QTL for tuber calcium concentration present on chromosome 1 of Atlantic

176 Figure 4.18. SNP marker with potential to be used in marker assisted selection targeting a QTL located on chromosome 2 of Superior and significantly increases pitted scab incidence and severity when present

Nulliplex(BBBB)

Simplex(ABBB)

1020

3040

5060

Genotype

% I

nci

den

ce (

2011

-20

12)

Pitted Scab IncidenceSNP c2_13213414Chr.2 of Superior

Nulliplex(BBBB)

Simplex(ABBB)

0.0

0.5

1.0

1.5

2.0

2.5

Genotype

Pit

s p

er

tub

er

(20

11-2

012)

Pitted Scab SeveritySNP c2_13213414Chr.2 of Superior

QTL: %V = 23%

SNP: p < 0.01

QTL: %V = 14.7%

SNP: p < 0.01

This QTL explained 23% of the variance for pitted scab incidence and 14.7% of the variance for pitted scab severity in the high disease pressure field. The marker c2_13213414 was associated to this QTL with p <0.01.

177

CHAPTER 5

Over-expressing the Vacuolar Antiporter CAX1 in the Potato Cultivar Atlantic: Phenotype of the Transformed Clones and Implications to Understand the Role of Calcium on Tuber

Quality and Plant Health

ABSTRACT

In vitro-grown plantlets of the potato variety Atlantic were transformed with an Agrobacterium

strain LBA4404 harboring a short version of the Cation Exchanger 1 (CAX1) gene, a tonoplast

calcium-cation transmembrane transporter of Arabidopsis thaliana, driven by the CaMV35S

promoter and the cdc2a promoter. The objective of this study was to evaluate the effect of the

increased calcium transport into the vacuole on the calcium content of in-vitro grown plantlets as

well as calcium distribution in leaves and tubers of greenhouse grown potato plants. Greenhouse

and in-vitro evaluations showed calcium deficiency symptoms in the transgenic clones when

growing under sufficient amounts of media or soil calcium content. Some clones needed up to

ten times the normal media or soil calcium content to grow without calcium deficiency

symptoms. We were able to reach several conclusions from the evaluation of these plants. First,

the increased transport of calcium into the vacuoles of the transgenic lines generates calcium

deficiency symptoms in the plant such as apical shoots damage and leaf margin necrosis. Second,

as most calcium transported to the foliage and tubers moves with water via the apoplast; growing

the transgenic plants with higher amounts of media or soil calcium mitigated calcium deficiency

symptoms in the shoots. Third, the sub-cellular localization analysis of calcium indicates that

calcium is being stored as calcium oxalate in the vacuoles of transgenic plants and therefore

becomes unavailable. Calcium oxalate crystals were not observed in the leaves of the wildtype

178

plants. Fourth, the deficiency symptoms, plant health damage and internal defects appear to be

caused by a reduction of the calcium concentration in the apoplast resulting in compromised

plant health and tuber quality. Our results show that maintaining the homeostasis of the sub-

cellular localization of calcium is very important for tuber quality and plant health.

INTRODUCTION

Calcium is essential for the integrity, maintenance and formation of cell-membrane systems and

cell walls of plants (Kirkby and Pilbeam 1984, Hirschi 2004). Calcium stabilizes cell membranes

by connecting adjacent polar head groups of membrane lipids (Legge et al. 1982, Palta 1996,

Hirschi 2004). It also protects membranes from adverse effects of stress such as salinity (Cramer

et al. 1985), freezing injury (Arora and Palta 1986), and heat stress (Tawfik et al. 1996,

Kleinhenz and Palta 2002, Saidi et al. 2009). Calcium is also a component of cell walls that

forms stiff gels through Ca+2-mediated crosslinking of its carboxyl groups through ionic and

coordinate bonds with a pectin component called homogalacturonan or polygalacturonic acid

(Cosgrove 2005).

Calcium homeostasis maintains the concentration of extracellular calcium in the milimolar range

whereas the cytoplasmic concentration of calcium is in the nanomolar to micromolar range

(Kauss 1987, Gilroy et al. 1993). Calcium antiporters and efflux pumps are important to maintain

the cytoplasmic calcium at low levels and restoring the normal Ca2+ levels after perturbation

(Tuteja and Mahajan 2007). A constant supply of Ca2+ in the range of 1-10 mM is required to

maintain normal growth and development at the whole-plant level (Epstein 1972, Clarkson and

Hanson 1980). Calcium moves with water mainly by the apoplast and its redistribution within

179

the plant is very low (Bangerth 1979, Clarkson 1984, Busse and Palta 2006). In plant tissues that

are deficient in calcium, cell walls disintegrate and tissue collapses resulting in necrosis (Kirby

and Pilbeam 1984, Marschner 1995).

The H+/ Ca2+ antiporter 1, CAX1, is a tonoplast calcium antiporter identified and cloned from

Arabidopsis thaliana by suppressing yeast mutants defective in vacuolar Ca2+ transport (Hirschi

et al. 1996). Several CAX antiporters have been identified in Arabidopsis with different ion

specificities such as CAX2 that transports heavy metals (Hirschi et al. 2000), CAX3 that

transports Ca2+ mainly in roots (Manohar et al. 2011), and CAX4 (Cheng et al. 2002) among

others. The N-terminal regulatory region of CAX1 acts as an autoinhibitory domain for H+/ Ca2+

transport activity when expressed in yeast (Pittman and Hirschi 2001, Pittman et al. 2002). This

region was removed to generate a deregulated short version, denominated sCAX1 (Cheng et al.

2005). The over-expression of sCAX1 in tobacco (Hirschi 1999), carrots (Park et al. 2004),

potato (Park et al. 2005a) and tomato (Park et al. 2005b) has shown to increase calcium content

in leaves, roots, tubers and fruits, respectively.

The Arabidopsis mutants of cax1 showed a reduction of Ca2+/ H+ antiport activity, a reduction in

tonoplast V-type H-translocating ATPase activity, an increase in tonoplast Ca2+-ATPase activity,

and the lack of CAX1 was compensated by increased expression of CAX3 and CAX4 (Cheng et

al. 2003). Also, cax1 mutants have shown characteristics of plants that grow in serpentine soils

which include greater tolerance for low Ca2+, increased tolerance to Mg2+ and higher Mg2+

requirement for maximum growth, and Mg2+ exclusion from leaves (Bradshaw 2005). In

addition, cax1/cax3 double mutants displayed a severe reduction in growth, including leaf tip and

flower necrosis and pronounced sensitivity to exogenous Ca2+ and other ions (Cheng et al. 2005).

CAX1 has been recognized as a key regulator of the apoplastic Ca2+ concentration. CAX1 keeps

180

apoplastic Ca2+ low through compartmentation into mesophyll vacuoles that is essential for

sufficient plant function and productivity (Conn et al. 2011). The unbound extracellular Ca2+

must be maintained in equilibrium across the apoplast/symplast boundary. In leaves, rather than

the cell wall, the vacuole serves as the reservoir for excess accumulation of Ca2+ (Robertson

2013).

Ca2+ deficiency-like symptoms have been reported in transgenic lines of tobacco that are over-

expressing CAX1 (Hirschi 1999). In tomatoes expressing sCAX1, a modest compromise of plant

growth had been reported by Park at al. (2005b); however, another study reported severe

deficiency symptoms and high incidence of blossom end rot in fruits of tomato plants (de Freitas

et al. 2011). A recent study has demonstrated that some of these Ca2+ deficiency symptoms can

be relieved by the expression of another gene encoding for the calcium binding protein

calreticullin (Wu et al. 2012). These deficiency symptoms have not been reported in potato. Park

et al. (2005a) reported that increased levels of sCAX1 do not appear to alter potato growth and

development, nor tuber morphology or yield. They further reported an increased calcium

concentration of various tuber tissues in transgenic plants.

The objectives of our study are to determine if there are calcium deficiency symptoms in potato

caused by the expression of sCAX1; to evaluate the effects on plant health, tuber quality and

calcium content of increased Ca2+ transport into the vacuole by the expression of sCAX1, to test

the hypothesis that because Ca2+ is sequestered in the vacuole there is less Ca2+ available in the

apoplast that weakens the cell walls causing calcium deficiency symptoms and internal defects in

the tubers, and to test if the deficiency symptoms can be relieved by supplemental calcium.

181


Plant material and transformation constructs

In vitro-grown plantlets 5-6 weeks old of the potato variety Atlantic were transformed with the

Agrobacterium strain LBA4404 harboring the small version of the CAX1 gene from Arabidopsis

thaliana. Two gene constructs developed by Park et al (2005a), one carrying the CaMV35S

promoter, CaMV35S::sCAX1; and another with the cdc2a promoter, cdc2a::sCAX1, were used

for transformation. The CaMV and the cdc2a promoters were chosen due to their high and non-

tissue specific transcription (Odell et al. 1985, Doerner et al. 1996). The Atlantic transgenic lines

were named using AT1 for lines carrying the CaMV35S::sCAX1 construct and AT2 for lines

carrying the cdc2a::sCAX1 construct. The numbers following indicate plate number, explants

number, and shoot number separated by an underscore. In addition, four Russet Norkotah

transgenic lines, CAX1 #34, CAX1 #36 K-3-1, CAX1 #36 K-3-2, and CAX1 #49; and a

wildtype line of Russet Norkotah RN#12, generated by Park et al. (2005a) were evaluated as

controls. The Russet Norkotah sCAX1-expressing lines, the Russet Norkotah wildtype and the

gene constructs were kindly provided by Kendall Hirschi from Texas A&M University.

Potato transformation

Stem cuttings of approximately 1cm long were used for transformation. Stem cuttings and the

Agrobacterium strain containing the construct were co-cultured in a media containing Trans-

5mg/L Zeatin Riboside, 0.01mg/L Indol Acetic Acid, and 0.2mg/L Gibberellic Acid (ZIG

media). After 4 to 6 days of co-cultivation under low light, stem cuttings were transferred to ZIG

182

media + Cefotaxime 100 mg/L + Kanamycin 50mg/L (ZIG++); and then, transferred to ZIG ++

media every two weeks until some shoots appeared in the callus formed at both ends of the stem

cuttings. Shoots of at least 2cm long were transferred to Murashige-Skoog media + Kanamycin

50mg/L (MS+), if the explants showed any signs of Agrobacterium growth they were grown in

MS + Cefotaxime 100 mg/L + Kanamycin 50mg/L (MS++). If the explants grew and generated

roots in either MS+ or MS++ media, they were considered positively transformed; otherwise,

they were eliminated. Wildtype explants were also grown in MS+ and MS++ media as negative

controls.

Polymerase chain reaction (PCR)

Genomic DNA was isolated from tissue culture plantlets using an extraction protocol based on a

CTAB 2X buffer (Doyle and Doyle 1990); with a tissue lysis step of 20 seconds using 1/4-inch

ceramic beads performed with a Bead Beater (Biospec) or a Fast Prep-12 instrument (MP

Biomedicals); and treated with RNAse A (Invitrogen) after isolation. The presence of the

transgene was determined by polymerase chain reaction (PCR) of the neomycin

phosphotransferase (NPT II) marker gene. The sequences of the primers used for the NPT II gene

were 5’- AGC CAA CGC TAT GTC CTG AT-3’ and 5’- GAA GGG ACT GGC TGC TAT TG-

3’(GenBank accession: U09365).The presence of a fragment of 370bp indicated that the plant

had been transformed.

PCR efficiency and copy number determination

Transgene copy number determination based on real time PCR offers a fast, inexpensive and

high throughput alternative (Yuan et al. 2007). In real time PCR, the threshold cycle (Ct) is the

183

PCR cycle at which fluorescence exceeds background and a significant increase in fluorescence

is observed (Higuchi et al. 1993). Another important variable to set up a quantitative PCR

(qPCR) assay is the PCR efficiency. Efficiency close to 100% is ideal and an indicator of the

quality of the assay (Saunders 2004). The DNA concentration was determined using a nanodrop

ND-2000 (Thermo Scientific). Template amounts of 50, 100, 200 and 400 ng of the same

transgenic clone in triplicate were used for the calibration curve. The efficiency of the PCR

reactions in this study was estimated by the R2 and the slope of the linear relationship between

the Ct values obtained from a CFX96 real time detection system (BIO-RAD) versus the log2

transformed DNA amounts. The slope should be close to -1 and R2 close to 100%. Primers that

target the CAX1 gene, the NPT II gene and single copy genes including the granule-bound starch

(GBSS, also called waxy) gene and EF1- were tested to determine their PCR efficiency (Figure

5.1). The primer sequences used were 5’-GAAGAAATCGCTCCACTTGC-3’ and 5’-

CTCCCCAGCAAAAACCAAT-3’to amplify a 387bp fragment of the GBSS gene (Genebank

accession: X83220); the 5’-ATTGGAAACGGATATGCTCCA-3’ and 5’-

TCCTTACCTGAACGCCTGTCA-3’ to amplify a 101bp fragment of the EF1- gene (Nicot et

al. 2005); the 5’-AGACAATCGGCTGCTCTGAT-3’ and 5’-AGTGACAACGTCGAGCACAG-

3’ to amplify a 370bp fragments of the NPT II gene (GenBank accession: U09365); and the 5’-

GCAACAGGAGGAGGAGTTTT-3’ and 5’-AACCCACCCACAAGAAGAAT-3’ to amplify a

250bp fragment of the CAX1 gene (TAIR: AT2G38170). The PCR efficiency was high for all

primer pairs evaluated (slope < -0.95, R2 > 0.97). The PCR reaction mix contained 1X Ex-Taq

buffer (Takara), 3mM MgCl2, 300µM DNTPs, 0.8µM of each primer, 0.8X Evagreen (Biotium),

and 0.125 units of Takara Ex-Taq Hot Start version (Takara) in a final volume of 25 µL.

184

The primer pairs used for the copy number determination on most lines were those targeting the

EF1- and CAX1 genes that presented slightly higher PCR efficiency. For each transgenic line,

two replicates of the real time reactions for both genes were performed in different wells of the

same plate. One line was used in all plates as a plate variation control because not all lines could

fit in a single plate. A mixed model that accounts for all the sources of variation was used to

determine the predicted Ct values for each line and gene. The model used was: Ct~ log2dna +

gene + line + plate + line*gene, where log2dna and gene were used as fixed effects variables and

line, plate and line*year were used as random effects variables. The predicted Ct values were

used to estimate copy number using a ΔΔCt method as described by Livak et al.(1995). An

external calibration curve was used to normalize for the variation in DNA concentration. The

formula to estimate copy number is copy = 2^ ΔΔCt, where ΔΔCt = (CtEF1α-CtCAX1)unknown-(CtEF1α-

CtCAX1)reference. The lines with known copy number were CAX1#34 (1 copy), CAX1#36 k-3-1

(1copy), CAX1#36 k-3-2 (1copy), and CAX1#49 (2 copies).

Test for the expression of CAX1 in the transgenic lines by the quantification of transcripts

The tips of two tissue culture plantlets measuring approximately 1.5cm were removed, quick

frozen in liquid nitrogen and stored at -70ºC until RNA extraction. Total RNA was extracted

using the RNAeasy Plant Mini kit (Qiagen) and the contaminating DNA was removed using the

Turbo DNA-freeTM kit (Ambion) according to the manufacturer’s recommendations. The cDNA

was produced using the Superscript III First Strand cDNA Synthesis System (Promega) from

1µg of purified total RNA according to the manufacturer specifications. The RNA and cDNA

concentrations were determined using a nanodrop ND-2000 (Thermo Scientific). The PCR

185

efficiency of the qPCR reaction was tested for the housekeeping gene EF1-α and the CAX1 gene

using different amounts, 25, 50 and 100ng, of cDNA from a single clone as template. The EF1-α

was chosen as the control housekeeping gene because it was one of the most stable under biotic

and abiotic stress in potato (Nicot et al. 2005)

The PCR reaction and primers were the same as the copy number assay. The linear model used

to determine the expected Ct values was Ct ~ line + gene + treatment + log2cdna + line*gene,

where all variables were treated as fixed effects. The relative difference between the amount of

transcripts for the reference gene EF1-α and the transgene CAX1 and the relative difference of

the amount of transcripts among lines were determined by the 2ΔCt and the 2ΔΔCt methods,

respectively. An internal standard curve generated with 25, 50, 100 and 200ng of cDNA from the

same clone was included in this evaluation.

In-vitro culture maintenance

Wild type clones were maintained using a modified Murashige and Skoog (MS) basal media

(Murashige and Skoog 1962) which contains 3mM Calcium in the form of CaCl2. Transgenic

clones were maintained at different levels of calcium in the media depending on which level

reduced significantly apical shoot damage. These levels of calcium were determined by

cultivating the transgenics in a range of calcium concentrations. Calcium levels of 6mM, 10mM,

15mM and 20mM were used for propagation of transgenic plants. The calcium concentration that

gave the healthiest plants was chosen to propagate these transgenics. Plantlets of transgenic

clones grown at their optimal calcium level had adequate development to be used in the tissue

culture and greenhouse experiments.

186

Tissue Culture Experiments

Initial in-vitro experiment: Higher demand of calcium by transgenic clones

Each transgenic clone was grown in tissue culture using standard MS media containing 3mM,

10mM and 30mM Ca+2 levels in the form of CaCl2. The transgenic clones were evaluated using

an augmented design with a single evaluation for most transgenic lines and three evaluations for

the wildtype clone. Each evaluation unit consisted on a set of 4 to 8 plantlets for the transgenic

lines and the wildtype lines. Most clones were included in this experiment. From these

experiments and additional tissue culture maintenance evaluations, the optimum media calcium

concentration for each transgenic line was defined.

In-vitro experiments: sCAX1 effects on plant health and calcium concentration

Each transgenic clone was grown at sufficient calcium concentration, 3mM, and one or more

high calcium concentrations depending on the aim of the experiment. For this purpose MS media

with calcium concentrations of 3mM,10mM, 15mM and 30mM; or 3mM and 15mM have been

used in this study in the form of CaCl2. The transgenic clones were evaluated using a randomized

block design with three replications of each transgenic line and the wildtype. Each replication

contained 6 to 8 plants. A subset of clones with a single copy of sCAX1 was evaluated in these

experiments.

Greenhouse Experiments

These experiments were conducted in order to determine the changes in total leaf calcium, water

soluble calcium, acid soluble calcium, and total tuber calcium, cell wall tuber calcium and

incidence of internal defects in tubers.

187

Plants were grown in the Greenhouses located on the Madison campus of the University of

Wisconsin. Calcium treatments used CaCl2 as the source of calcium. Commercial soil mixes

were not used due to the added gypsum and/or lime they contain. We produced our own growing

mix that contained vermicultite:perlite:peat in a 1:1:1 volume ratio in order to have a better

control of the amount of nutrients applied. The mix was placed in 4L pots up to ¾ of the volume,

and washed several times with tap water, after washing the growing mix pH was 5. Plants were

fertilized once a day with 500mL of a 300 ppm solution of Peat-Lite Special (Peter’s

Professional) made with tap water that contains 70ppm of CaCO3, plus the necessary amount of a

stock solution of 1M or 2.5 M CaCl2 to get the final concentration of the treatment. Treatments

of 1mM and 10mM; or 1mM, 10mM, 15mM and 20mM were used in the experiments. The 1mM

treatment was considered the sufficient calcium treatment and the treatments with 10mM or

more were considered high calcium treatments. The calcium coming from the CaCO3 in the tap

water was not counted as part of the treatment. The transgenic clones were evaluated using a

randomized block design with three replications per clone and different calcium treatments. The

temperature was 20°C/15°C day/night, day length was 16h/8h (light/dark periods), and light

intensity was on average 600μmoles per square meter per second. The light was supplemental

with high intensity discharge lamps when needed.

Total calcium extraction and quantification from leaf tissues of greenhouse grown and in-

vitro plants

A protocol based on the method presented by Kratzke and Palta (1986) was used for extraction

and quantification of tissue calcium. For the tissue culture experiments, whole in-vitro grown

188

plantlets 5-6 week old were either freeze dried or dried in an oven at 60C. For the greenhouse

experiments, the second and third fully extended leaves were sampled and oven-dried

inmediately. Samples were ground to pass a 20-mesh screen and ashed at 550 ºC. The ashes were

dissolved in 5mL of 2N HCl, this solution was filtered using an acid-treated filter paper and

collected in a 50 mL volumetric flask. Ten mL of LaCl3 (2000 mg/L solution) was added to the

flask and the volume raised to 50 mL. The calcium concentration in micrograms per gram of dry

weight (µg/g) was determined using an atomic absorption spectrophotometer Varian SpectrAA

55B (Agilent Technologies, US).

Cell wall and total tuber calcium extraction from tubers

Cell walls were extracted from potato tubers using a protocol adapted from Hoff and Castro

(1969). An average of 20 slices of 1mm-thick was cut from 5 to 16 tubers depending on the size

of the tubers. Slices were rinsed in pre-chilled distilled-deionized water to remove the excess of

starch and dried in a mesh cloth before weighing. The slices were separated in two subsamples,

one for total calcium and the other for cell wall calcium, each with average weights of 10 grams.

The subsample used for total calcium quantification was frozen at -20ºC immediately after

sampling until calcium extraction. The subsample for cell wall calcium extraction was blended

using 100mL of cold distilled-deionized water. The blended tissue was filtered using a propylene

mesh sieve of 100 µm x 100 µm pores and washed with about 900mL of cold distilled-deionized

water to remove starch. The tissue was transferred the to a small beaker with 40mL cold

distilled-deionized water and sonicated for 10 min in sets of 15 seconds followed by 30s of

cooling at amplitude of 20 on an ice bath. The sonicated tissue was filtered again with the

189

propylene mesh sieve, rinsed with 300 mL of water and a final rinse with 30 mL of absolute

ethanol. The cell walls were frozen at -20ºC until calcium extraction.

For calcium extraction, both subsamples, tuber tissue and extracted tuber cell walls were freeze

dried for two weeks. The dried samples were ground manually with a glass rod, ashed and

processed for quantification of calcium using the same procedure as described above for leaf

tissue samples.

Water-extractable and HCl-extractable calcium fractions

The water-extractable and acid-extractable fractions were determined in order to indirectly

measure the amount of apoplastic calcium and calcium oxalate, respectively. For the water-

extractable fraction, 5 mL of distilled-deionized water was added to approximately 0.1 g of dry

tissue in case of leaves and 0.5 g in case of tubers, and let it sit overnight at 4ºC. For the HCl-

extractable fraction, 5 mL of 0.1 N HCl was added to approximately 0.1 g of dry tissue in case of

leaves and 0.5 g in case of tubers, and let it sit overnight at 4ºC. For both fractions, the mix was

filtered using an acid-treated filter paper and collected in a 50 mL volumetric flask. One mL of

H2O2, 5 mL of 2 N HCl and 10 mL of 2000 mg/L LaCl3was added and the final volume of 50

mL was made with distilled-deionized water. These samples were then read in the atomic

absorption spectrophotometer.

Polarized light and environmental scanning electron microscopy

For polarized light microscopy, a thin layer of vascular tissue was peeled off from the abaxial

surface of the leaf using a small forceps and put immediately in a drop of bi-distilled water.

190

Transverse sections of 100-200 microns were obtained from a leaflet of the third fully extended

leaf using a vibratome sectioning system (Oxford). In this procedure, the sample is submerged in

tap water and live sections of the leaf tissue are cut by a vibrating blade. The transversal sections

were immersed in pre-boiled water cooled at room temperature and subjected to vacuum for 5

minutes in order to remove air from the sample. Tap water was used throughout the sectioning to

avoid cell injury.

For the environmental scanning electron microscopy, squares of 5mm x 5mm were sampled from

leaf margins and immediately observed in a FEI Quanta environmental scanning electron

microscope (ESEMTM), the sample temperature was set at 5ºC and vacuum was applied,

accelerated voltage was 20 kV, spot size was 4, and water vapor pressure was 5.08 Torr.

Statistical Analysis

The statistical analysis and plots were obtained using the stats and graphics packages of R

version 3.0.0, respectively (R Development Core Team, 2013).


Calcium deficiency symptoms in the transgenic lines expressing the sCAX1 gene are

alleviated by supplemental calcium

The presence of the transgene was verified by PCR. Most of the lines selected with the MS

media + kanamycin were transgenic; however, a few lines had grown in the media but did not

show a band for the NPT II gene (Figure 5.2). Forty-nine transformed lines were successfully

191

obtained, 48 with the CaMV35S::sCAX1 construct and 1 with the cdc2a::sCAX1 construct. In

addition, the transgene copy number was determined for several lines using qPCR. An initial in-

vitro experiment was performed to test the incidence of calcium deficiency symptoms such as

apical shoot damage, the incidence of stressed leaves and other indicators of plant health such as

plant height and biomass at different calcium treatments compared to the wildtype. There was a

wide range of phenotypic variability among lines that is a consequence of the differences in copy

number, gene expression, somaclonal variation, and the specific genomic position where the

CAX1 gene was inserted by Agrobacterium (Table 5.1). In general, the incidence of apical shoot

damage was reduced at higher media calcium treatments (Table 5.1). Most transgenic lines

showed apical shoot damage in the MS media containing 3mM calcium, the normal

concentration of calcium in the MS media except for few lines presenting multiple copies of the

transgene such as AT1_01_06_02 (6 copies), AT1_02_04_01 (2 or 3 copies), AT1_02_09_01,

AT1_04_03_01 (6 copies), and AT1_06_09_01 (1 copy) that had no apical shoot damage at the

3mM calcium treatment indicating that the multiple copies of sCAX1 may have suffered post-

transcriptional silencing as it was observed in other studies (Tang et al. 2007, Nocarova et al.

2010) (Table 5.1). In addition, at higher calcium treatments, plant height and plant biomass

increased in the transgenics but slightly decreased in the wildtype lines. Also, the total calcium

of the in-vitro cultured plantlets from all transgenic lines and the wildtype increased at higher

calcium treatments. The stress symptoms in the leaves or yellowness were less at higher calcium

treatments except for some of the CAX1 lines of Russet Norkotah. This initial experiment

covered most of our transgenic lines in order to determine general trends. The follow-up

experiments included a reduced set of lines that had a single copy of the sCAX1 gene. Also, the

CAX1 #34 and CAX1 #49 were excluded from further evaluations because of the weakness of

192

the plants and leaf malformations, respectively. Another experiment with a set of clones with a

single copy of the transgene was performed to determine the minimum concentration at which

the transgenic clones alleviate most of their calcium deficiency symptoms without showing salt

stress signs such as yellowish leaves. The single copy transgenics had their sufficient growth at

15mM calcium because at this concentration the apical shoot damage was alleviated in in-vitro

grown plants and was comparable to the wildtype at 3mM (Figure 5.3). These results indicate

that the expression of CAX1 causes the calcium deficiency symptoms observed in in-vitro

cultured plants of potato and that the symptoms are reduced at higher calcium treatments in the

growth media.

A greenhouse experiment was performed in order to study the calcium needs of transgenic plants

to grow normal under greenhouse conditions. In greenhouse grown plants, the calcium

deficiency symptoms observed were apical shoot damage and leaf margin necrosis. In general,

the apical shoot damage was reduced in the high calcium treatment of 10mM, compared to the

1mM calcium treatment. It is important that 1mM was sufficient for normal growth of wildtype

plants (Figure 5.4). The leaf margin necrosis symptom was more evident when the transgenic

lines were grown in the greenhouse because leaves were bigger compared to the in-vitro grown

plants. At higher calcium levels less leaves had this symptom and the symptoms were less severe

in the transgenic lines (Figure 5.5). Nevertheless, the calcium deficiency symptoms caused by

the expression of sCAX1 was not completely or uniformly alleviated under greenhouse

conditions for the whole transgenic plants, especially for leaf margin necrosis. We hypothesized

that the over- expression of the symptoms might be related to the position of the leaf in the plant

and the amount of evapotranspiration in each particular leaf. Comparing the leaf morphology of

normal leaves and leaves showing margin necrosis from the same plant at the 10mM calcium

193

treatment, we observed differences in the morphology of the upper leaf surface (Figure 5.6). The

epidermal cells size was smaller and their shape was more squared. Furthermore, a higher

number of stomata and trichomes were observed on transgenic plants compared to the wildtype

(Figure 5.6). For example, in a given area of upper leaf surface 12 stomata can be observed in

the transgenic leaf with margin necrosis whereas there are no stomata in the similar size area of a

transgenic leaf without deficiency symptoms as well as in the wildtype (Figure 5.6). The higher

stomatal and trichome density are consistent with previous reports of responses under water

stress (Sam et al. 2000). These morphological changes suggest that the sCAX1 lines are under

nutritional stress even though they are growing at sufficient calcium levels.

The transgenic line AT2_01_09_01, the only line that was generated using the cdc2a promoter

had stronger deficiency symptoms than the other transgenic lines at the sufficient and high

calcium treatments. These stronger deficiency symptoms could be caused by a difference in the

levels of expression between the CMV35S promoter and the cdc2a promoter. The comparison of

the relative gene expression between clones revealed that AT2_01_09_01 had almost double the

expression compared to the other lines (Table 5.2).

These results of the in-vitro and greenhouse experiments suggest that the increased transport of

Ca2+ towards the vacuole reduces the availability of calcium in other cell compartments and

therefore calcium deficiency symptoms are observed in the transgenic lines expressing sCAX1

even when they are growing using media or soil calcium concentrations that are sufficient for the

wildtype plants.

194

Calcium content in the sCAX1-expressing lines

As it was indicated before, there was a variable degree of alleviation of calcium deficiency

symptoms in the leaves of plants given the high calcium treatment under greenhouse conditions.

The calcium concentrations in leaf tissue were also variable among the transgenic lines with

some lines showing increased and others showing decreased total calcium concentration. The

results of this evaluation were not presented because of the high variation between samples of

the same clone. The variation observed in calcium from greenhouse leaf samples might be

caused by several sources of variation including leaf age, position in the plant, amount of light

and shade and slight differences in the nutrient solution and soil mix from pot to pot.

Nevertheless, comparing the calcium content of leaves with and without calcium deficiency

symptoms from the same transgenic line at the high calcium treatment, we found that leaves with

margin necrosis had less calcium than leaves without margin necrosis in the greenhouse

evaluation (Table 5.3 and Figure 5.7). These results suggest that when more calcium is

transported to a leaf of the sCAX1 transgenic lines, the calcium deficiency symptoms are

ameliorated.

In order to have a more controlled system and a more homogeneous plant environment, we

performed experiments using in-vitro cultured plants to determine the effect of the expression of

sCAX1on the plantlet calcium concentration. In the in-vitro plantlets, most CAX1 clones showed

similar total leaf calcium content to the wildtype and the amount of total calcium was found to

increase at higher media calcium levels. The concentration of total leaf calcium in dry weight

basis under greenhouse conditions was similar to the wildtype for most transgenic lines in the

3mM calcium treatment. For all transgenic lines, the total concentration of calcium in plants

grown at 15mM calcium was similar or slightly higher as compared to the wildtype. The LSD

195

analysis indicates that the differences are significant between the transgenic lines and the

wildtype at the 15mM calcium treatment (Table 5.4 and Figure 5.8).

In the case of total tuber calcium, there was variability between cultivars and treatments but not

between transgenic lines and the wildtype lines as revealed by the ANOVA analysis (Table 5.5).

The main differences were between the Atlantic and Russet Norkotah lines (Figure 5.9). These

results indicate that if the total amount of calcium in the transgenic lines is similar to the

wildtype but more is being transported into the vacuole in the transgenic plants, we can assume

that there is less in other cellular compartments and especially in the apoplast because the Ca2+

transport into the vacuole modulates apoplastic Ca2+ concentrations (Conn et al. 2011). A close

relationship between apoplastic calcium and cell wall calcium has been documented by previous

research (Demarty et al. 1984, Pechanova et al. 2010, Gilliham et al. 2011a, Wang et al. 2013).

This suggests that in our transgenic lines may be affected by a decrease in apoplastic calcium.

This reduced apoplastic calcium may be compromising the cell walls by decreasing the cell wall-

bound Ca2+ or by a reduction of the cell wall biomass. Further experiments in the following

section will determine which of these mechanisms are affecting the cell walls of the sCAX1-

expressing transgenic lines.

Effects of sCAX1 in the sub-cellular localization of calcium

The expression of sCAX1 in potato causes an increased transport of Ca2+ into the vacuole, but

what happens to that extra calcium? We know from previous reports that calcium cannot be

redistributed to other parts of the cell (Gilliham et al. 2011b). Therefore, calcium might be

forming salts with other compounds stored in the vacuole. One type of calcium salts stored in

vacuoles is calcium oxalate. Calcium oxalate is abundant in certain plants such as Oxalis, beets

196

and spinach. Calcium oxalate forms crystals that vary in bioavailability depending on their

hydration, purity and size (Libert and Franceschi 1987). In our study, we evaluated sCAX1

transgenic lines for the presence of calcium oxalate crystals using polarized light microscopy.

Under polarized light, only tri-dimensional bi-refringent objects such as crystals, that refract light

in two slightly different directions, shine under the microscope. The results of the polarized light

microscopy evaluation indicate that there are calcium oxalate crystals in the leaves of the

transgenic lines at the sufficient and high calcium treatments; meanwhile, the wildtype only

shows few or no crystals at both calcium treatments (Figure 5.10). Calcium oxalate crystals were

observed in the vascular tissue, epidermis and trichomes, and the mesophyll of the leaves of

transgenic plants (Figure 5.10). In the mesophyll, crystals were observed in the spongy cells and

palisade cells (Figure 5.11). Even though we did not test for the presence of calcium oxalates in

tubers, our observations in the leaf cells suggest that the calcium being stored by these transgenic

lines is most likely not going to be bioavailable since it is sequestered in the form of calcium

oxalate. One would expect that the tuber tissue will also contain calcium oxalates. A study of

bioavailability and absorption of sCAX1-expressing carrots showed that there was a reduced

incorporation of calcium into bonds of mice and 10% reduction in fractional (%) absorption from

sCAX1-expressing carrots whereas the total concentration of calcium absorbed in 100g of carrots

was 42% higher compared with an equal quantity of the control indicating that not all of the

calcium sequestered in the vacuole by ectopic expression of sCAX1 is bioavailable (Morris et al.

2008). Therefore, efforts to improve the nutritional quality of potatoes using the expression of

sCAX1 should evaluate calcium bioavailability and absorption to determine to what extent these

calcium oxalates could contribute to human nutrition.

197

Another experiment was performed to test the hypotheses that the increased transport of Ca2+

into the vacuole results in weaker cell walls due to a reduction of the concentration of calcium in

the cell walls or a reduction of the amount of cell walls. Cell walls were extracted from tubers

produced under greenhouse conditions. There was variability in tuber size, with smaller tubers in

the transgenics than the wildtype. A smaller amount of cell walls was observed in the transgenic

lines compared to the wildtype and was confirmed by the ANOVA analysis (Table 5.6 and

Figure 5.12). The ANOVA analysis revealed that the transgenic lines had similar cell wall

calcium concentration as the wildtype (Table 5.7 and Figure 5.13). These results support the

hypothesis that the cell walls biomass decreased as a consequence of the reduced apoplastic Ca2+

concentration in the sCAX1-expressing lines.

The water-extractable fraction of the calcium concentration was also evaluated as an indirect

measurement of apoplastic calcium. The water-extractable fraction in the in-vitro grown plants

was higher in the wildtype than the transgenic lines at the sufficient calcium treatment (3mM)

but at the higher calcium treatment (15mM) the water-extractable fraction becomes more similar

between the wildtype and the transgenic lines (Table 5.8 and Figure 5.14). This result is in

agreement to the predicted changes in apoplastic calcium that is expected to be low in the

transgenic lines at the sufficient calcium treatment (3mM) but increase and become closer to the

wildtype at the high calcium treatment (15mM). Interestingly, significant differences between

the Atlantic and Russet Norkotah lines at =0.1 were observed due to the higher concentrations

for the Russet Norkotah lines, especially at the high calcium treatment. This difference was not

expected because the plants show similar phenotypes.

198

The solubility of calcium oxalate in water is very low which approximately 9 mg/L. is However,

its solubility is much higher in HCl which is around 489.2 mg/L at 25°C (Seidell 1919).

Therefore, the HCl-extractable fraction can be used as an indicator of the amount of calcium

sequestered as calcium oxalate. Some transgenic lines had a higher amount of HCl-extractable

calcium than the wildtype at the sufficient calcium treatment but most of them were higher than

the wildtype at the high calcium treatment (Table 5.9 and Figure 5.15). The lower amount of

water-extractable calcium in the transgenic lines (Figure 5.15) suggests that the apoplastic

calcium is lower in the transgenic lines compared to the wildtype. Furthermore, higher amounts

of HCl-extractable calcium in the transgenic clones (Figure 5.15) indicate an increased

formation of calcium oxalate in the transgenic clones as compared to the wildtype.

Plant heath and tuber quality on the sCAX1 expressing lines

Our observation of the plants show that the over-expression of sCAX1 does not seem to be

beneficial and it is indeed compromising plant health (Figures 5.3 and 5.4). We measured plant

height and biomass as indicators of plant health. The results show that the health of the potato

plant is compromised as shown by lower biomass in transgenic plants (Figures 5.16, 5.17 and

5.18). Under greenhouse conditions, transgenic plants have less biomass as compared to the

wildtype at the sufficient calcium treatment of 1mM. However, their biomass becomes much

similar at higher calcium treatments (Figure 5.16). The ANOVA analysis indicates that the

differences in biomass between the wildtype and the transgenic lines are significant (Table

5.10). Similarly, biomass evaluated under in-vitro conditions was lower in the transgenic lines

compared to the wildtype at the sufficient calcium concentration of 3mM in the media, but their

biomass became more similar at the 15mM calcium treatment (Table 5.11 and 5.17). The data on

199

plant height shows similar trends as biomass. The transgenic lines were shorter than the wildtype

at the sufficient calcium treatment of 3mM, but increased at high calcium treatment and became

more similar to the wildtype (Figure 5.18). The ANOVA analysis indicates that the plant height

differences between the wildtype and the transgenic lines are significant (Table 5.12). These

results show that the over-expression of sCAX1 in potato compromises plant health as shown by

reduced growth compared to the wildtype.

A higher incidence of internal defects, specifically hollow heart, was found in the transgenic

clones as compared to the wildtype in the greenhouse studies (Figure 5.19). The data analysis

indicates that the differences between the incidence of hollow heart in the wildtype and the

transgenic lines are significant (Table 5.13). These results suggest that the increased transport of

calcium into the vacuoles in the sCAX1 transgenic lines has a negative effect on tuber quality.

Even though the total tuber calcium was similar among the transgenic and wildtype lines, the

transgenic lines showed higher tuber defects. These results suggest that an inadequate supply of

Ca2+ to the tuber cell walls compromises tuber cells health resulting in increased internal defects.

Our results also show that the tuber defects were alleviated when soil was given high calcium

treatment (Figure 5.20). These results further confirm the earlier results that tuber internal

defects can be mitigated by a supplemental soil calcium application (Tzeng et al. 1986, Olsen et

al. 1996, Palta 1996, Ozgen et al. 2006, Karlsson et al. 2006).

The relationship between root abundance and calcium uptake under in-vitro culture

conditions

In-vitro plants of Atlantic and its transgenic lines always showed lower calcium than Russet

Norkotah and its transgenic lines at all calcium treatments (Figure 5.8). We hypothesized that

200

this difference might be related to a differential calcium uptake from the media between these

two cultivars. Because calcium is taken up by roots and transported to the plant along with water

mainly in the apoplast, the most logical difference expected between the two potato varieties

would be the amount of roots produced. The roots were collected from 8 in-vitro grown plants in

triplicate, weighed and compared. The results indicate that roots biomass of Atlantic was much

lower than Russet Norkotah (Figure 5.21 and Table 5.14). Data analysis also shows that both

cultivars have significant differences in calcium concentrations (Tables 5.4 and 5.5). These

results indicate a differential response to high calcium levels in the media exists among potato

cultivars and also suggests that an increased amount of roots can contribute to increased uptake

of calcium.

SUMMARY AND CONCLUSIONS

The results presented in this study show that the over-expression of sCAX1 leads to symptoms of

calcium deficiency and compromises tissue health. Our study further illustrates this deficiency

results from transport of calcium to the vacuole where it is sequestered and made unavailable in

the form of calcium oxalate. These results are in agreement with current published reports

(Hirschi 1999, Park et al. 2005b, de Freitas et al. 2011, Wu et al. 2012).

The antiporter H+/Ca2+ CAX1 is known to regulate apoplastic calcium in Arabidopsis as reported

by Conn et al. (2011). In our study, we estimated the apoplastic calcium concentration indirectly

by measuring the water-extractable fraction and assessing the effect of the increased transport of

Ca2+ into the vacuole on cell walls. A reduction in apoplastic calcium would reduce the amount

201

of Ca2+ available to bind to the cell walls. We found that even though the cell wall calcium

concentration did not change significantly, the total amount of cell walls formed was much lower

in the sCAX1 transgenic lines. These results together with the observation that a similar total

tuber calcium concentration was found between the transgenic lines and the wildtype shows that

if the same total amount of total calcium is present in the tissue and more is transported into the

vacuole there is less calcium available in the apoplast and therefore in the cell walls causing

calcium deficiency symptoms and tuber internal defects. Our result also indirectly confirms that

the calcium that goes to the vacuole is trapped in the form of calcium oxalate and cannot be

redistributed to other parts of the cell.

Potato plants grown under very low amounts of calcium such as 30μM are known to show

deficiency symptoms such as apical shoot damage, leaf margin and tip necrosis, and leaf lamina

rolled towards the midrib (Singh and Sharma 1972, Seling et al. 2000, Busse et al. 2004). All

these symptoms were observed in the sCAX1 transgenic lines at sufficient calcium levels (1mM)

and depending on the clone even at higher calcium levels (10mM or more) in the media and/or in

the nutrient solution for plants grown in pots.

Potato tubers are normally low in calcium (Wiersum 1966, Davies and Millard 1985, Kratzke

and Palta 1986) and more than 90% of the calcium in tuber tissue is present in a physiologically

active form (Davies and Millard 1985). This is because calcium moves with water in plants and

very little water moves to the tuber as compared to the leaf tissue (Palta 1996, Busse and Palta

2006). A sub-cellular localization analysis found that the distribution of calcium differs among

tuber cells and most of the calcium is found in the vacuole and very little is present in the cell

walls (Oparka and Davies 1988). When this homeostasis is altered, internal defects appear. In

our study, the transgenic lines showed tuber internal defects in plants grown with sufficient

202

calcium levels (1mM calcium) as a consequence of the increased transport of Ca+2 into the

vacuole in the transgenic lines. Previous studies have shown that increased calcium levels in

potato tubers can improve potato tuber quality by reducing the incidence of internal defects

(Kleinhenz et al. 1999, Karlsson et al. 2006, Ozgen et al. 2006). In our study, we observed that

internal defects of transgenic plants in tubers are mitigated by supplying high calcium (10mM).

In addition, our results suggest that the strategies to respond to supplemental calcium differ

between Atlantic and Russet Norkotah since only Russet Norkotah tends to increase the amount

of roots in presence of additional calcium. The natural variation for total calcium content and

responses to additional calcium levels in the soil and/or media observed among potato clones

may result from the interplay of CAX-like apoplastic calcium regulators and other regulators of

calcium uptake and transport at the root and shoot levels.

Atlantic is a standard chipping cultivar that is susceptible to internal defects such as hollow heart,

internal brown spot, brown center and blackspot bruise. This cultivar also contains less tuber

calcium than other varieties such as Superior (Karlsson et al. 2006). Atlantic is therefore a good

cultivar to test genes that potentially could be used to produce genetically modified potato with

increased tuber calcium concentration without compromising plant health or increasing the

incidence of internal defects. Our results show that even though there was an increased transport

of Ca2+ into the vacuole in the transgenic clones, the total calcium did not increase in the tubers

of Atlantic and Norkotah lines over-expressing sCAX1. This study suggests that CAX1 is a very

important gene that regulates apoplastic calcium and cell wall strength. The natural variation for

this gene should be studied in relation to tuber calcium and tuber quality. Furthermore, the

transgenic lines generated in this study are of great importance for the understanding of calcium

regulation in crops and could be used for example to study genes that restore plant health and

203

tuber quality. This has been done in tobacco and tomato where the co-expression of calreticulin,

a chaperone found in the endoplasmic reticulum, in the sCAX1-expressing lines relieved the

calcium deficiency symptoms caused by sCAX1 (Wu et al. 2012).

BIBLIOGRAPHY

Arora, R. and J.P. Palta. 1988. In Vivo perturbation of membrane-associated calcium by freeze-thaw stress in onion bulb cells simulation of this perturbation in extracellular KCl and alleviation by calcium. Plant Physiology 87: 622-628. Bangerth, F. 1979. Calcium-related physiological disorders of plants. Annual Review of Phytopathology 17: 97-122. Bradshaw, H.D. 2005. Mutations in CAX1 produce phenotypes characteristic of plants tolerant to serpentine soils. New Phytologist 167: 81-88. Busse, J.S. and J.P. Palta. 2006. Investigating the in vivo calcium transport path to developing potato tuber using 45Ca: a new concept in potato tuber calcium nutrition. Physiologia Plantarum 128: 313-323. Cheng, N.H., J.K. Pittman, T. Shigaki, and K.D. Hirschi. 2002. Characterization of CAX4, an Arabidopsis H+/cation antiporter. Plant Physiology 128: 1245-1254. Cheng, N.H., J.K. Pittman, B.J. Barkla, T. Shigaki, and K.D. Hirschi. 2003. The Arabidopsis CAX1 mutant exhibits impaired ion homeostasis, development, and hormonal responses and reveals interplay among vacuolar transporters. The Plant Cell Online 15: 347-364. Cheng N.H., J.K. Pittman, T. Shigaki, J. Lachmansingh, S. LeClere, B. Lahner, D.E. Salt, and K.D. Hirschi. 2005. Functional association of Arabidopsis CAX1 and CAX3 is required for normal growth and ion homeostasis. Plant Physiology 138: 2048-2060. Clarkson, D.T. 1984. Calcium transport between tissues and its distribution in the plant. Plant, Cell & Environment 7: 449-456. Clarkson, D.T., and J.B. Hanson. 1980. The mineral nutrition of higher plants. Annual Review of Plant Physiology 31: 239-298. Cramer, G.R., A. Läuchli, and V.S. Polito. 1985. Displacement of Ca2+ by Na+ from the plasmalemma of root cells. A Primary Response to Salt Stress?. Plant Physiology 79: 207-211.

204

Conn, S.J., M. Gilliham, A. Athman, A.W. Schreiber, U. Baumann, I. Moller, N. Cheng, et al. 2011. Cell-specific vacuolar calcium storage mediated by CAX1 regulates apoplastic calcium concentration, gas exchange, and plant productivity in Arabidopsis. The Plant Cell Online 23: 240-257. Cosgrove, D.J. 2005. Growth of the plant cell wall. Nature Reviews Molecular Cell Biology 6: 850-861. Davies, H.V., and P. Millard. 1985. Fractionation and distribution of calcium in sprouting and non-sprouting potato tubers. Annals of Botany 56: 745-754. Demarty, M., C. Morvan, and M. Thellier. 1984. Calcium and the cell wall. Plant, Cell & Environment 7: 441-448. Doerner, P., J.E. Joergensen, J.E., R. You, J. Steppuhn., and C. Lamb. 1996. Control of root growth and development by cyclin expression. Nature 380: 520-523. Doyle, J.J., and J.L. Doyle. 1990. A rapid total DNA preparation procedure for fresh plant tissue. Focus 12: 13-15. Epstein, E. 1972. Mineral nutrition of plants. Principles and Perspectives. New York: John Wiley and Sons. de Freitas, S.T., M. Padda, Q. Wu, S. Park, and E.J. Mitcham. 2011. Dynamic alternations in cellular and molecular components during blossom-end rot development in tomatoes expressing sCAX1, a constitutively active Ca2+/H+ antiporter from Arabidopsis. Plant Physiology 156: 844-855. Gilliham M., C. Jordans, S. Conn, I. Moller, A. Schreiber, R. Burton, B. Kaiser, S. Tyerman, and R. Leigh. 2011a. Re-examining the role of apoplastic calcium in cell wall modification. 22nd International Conference on Arabidopsis Research. Madison, Wisconsin. Gilliham, M., M. Dayod, B.J. Hocking, B. Xu, S.J. Conn, B.N. Kaiser, S.D. Tyerman. 2011b. Calcium delivery and storage in plant leaves: Exploring the link with water flow. Journal of Experimental Botany 62: 2233-2250. Gilroy, S., P.C. Bethke, and R.L. Jones. 1993. Calcium homeostasis in plants. Journal of Cell Science 106: 453-461. Higuchi, R., C. Fockler, G. Dollinger, and R. Watson. 1993. Kinetic PCR: Real-time monitoring of DNA amplification reactions. Nature Biotechnol 11: 1026-1030. Hirschi, K.D., R.G. Zhen, K.W. Cunningham, P.A. Rea, and G.R. Fink. 1996. CAX1, an H+/Ca2+ antiporter from Arabidopsis. Proceedings of the National Academy of Sciences 93: 8782-8786.

205

Hirschi, K.D. 1999. Expression of Arabidopsis CAX1 in tobacco: altered calcium homeostasis and increased stress sensitivity. The Plant Cell Online 11: 2113-2122. Hirschi, K.D.,V.D. Korenkov, N.L. Wilganowski, and G.J. Wagner. 2000. Expression of Arabidopsis CAX2 in tobacco. Altered metal accumulation and increased manganese tolerance. Plant Physiology 124: 125-134. Hirschi, K.D. 2004. The calcium conundrum. Both versatile nutrient and specific signal. Plant Physiology 136: 2438-2442. Hoff, J.E., and M.D. Castro. 1969. Chemical composition of potato cell wall. Journal of Agricultural and Food Chemistry 17: 1328-1331. Karlsson, B., J.P. Palta, and P.M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. HortScience 41: 1213-1221. Kauss, H. 1987. Some aspects of calcium-dependent regulation in plant metabolism. Annual Review of Plant Physiology 38: 47-72. Kirkby, E.A., and D.J. Pilbeam. 1984. Calcium as a plant nutrient. Plant, Cell & Environment 7: 397-405. Kleinhenz, M.D., J.P. Palta, C.C. Gunter, and K.A. Kelling. 1999. Impact of source and timing of calcium and nitrogen applications on ‘Atlantic’ potato tuber calcium concentrations and internal quality. Journal of the American Society for Horticultural Science 124: 498-506. Kleinhenz, M.D. and J.P. Palta. 2002. Root calcium modulates the response of potato plants to heat stress. Physiologia Plantarum 115: 111-118. Kratzke, M.G. and J.P. Palta. 1986. Calcium accumulation in potato tubers: Role of the basal roots. HortScience 21:1022-1024. Legge, R.L., J.E. Thompson, J.E. Baker, and M. Lieberman. 1982. The effect of calcium on the fluidity and phase properties of microsomal membranes isolated from post-climacteric Golden Delicious apples. Plant and Cell Physiology 23: 161-169. Libert, B. and V.R. Franceschi. 1987. Oxalate in crop plants. Journal of Agricultural and Food Chemistry 35: 926-938. Livak, K.J., S.J. Flood, J. Marmaro, W. Giusti, and K. Deetz. 1995. Oligonucleotides with fluorescent dyes at opposite ends provide a quenched probe system useful for detecting PCR product and nucleic acid hybridization. Genome Research 4: 357-362.

206

Manohar, M.,T. Shigaki, H. Mei, S. Park, J. Marshall, J. Aguilar, and K.D. Hirschi. 2011. Characterization of Arabidopsis Ca2+/H+ exchanger CAX3. Biochemistry 50: 6189-6195. Mann, H.B. and D.R. Whitney. 1947. On a test of whether one of two random variables is stochastically larger than the other. The Annals of Mathematical Statistics 18: 50-60. Marschner, H. 1995. Mineral Nutrition of Plants. Second Edition. Academic Press, Boston. Morris, J., K.M. Hawthorne, T. Hotze, S.A. Abrams, and K.D. Hirschi. 2008. Nutritional impact of elevated calcium transport activity in carrots. Proceedings of the National Academy of Sciences 105: 1431-1435. Murashige, T., and F. Skoog. 1962. A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiologia Plantarum 15: 473-497. Nicot, N., J.F. Hausman, L. Hoffmann, and D. Evers. 2005. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. Journal of Experimental Botany 56: 2907-2914 Nocarova, E., Z. Opatrny, and L. Fischer. 2010. Successive silencing of tandem reporter genes in potato (Solanum tuberosum) over 5 years of vegetative propagation. Annals of Botany 106: 565-572. Odell, J.T., F. Nagy, and N.H. Chua. 1985. Identification of DNA sequences required for activity of the cauliflower mosaic virus 35S promoter. Nature 313: 810-812. Olsen, N.L., L.K. Hiller, and L.J. Mikitzel. 1996. The dependence of internal brown spot development upon calcium fertility in potato tubers. Potato Research 39:165-178. Oparka, K.J., and H.V. Davies. 1988. Subcellular localisation of calcium in potato tubers. Potato Research 31: 297-304. Ozgen, S., B.H. Karlsson, and J.P. Palta. 2006. Response of potatoes (cv Russet Burbank) to supplemental calcium applications under field conditions: Tuber calcium, yield, and incidence of internal brown spot. American Journal of Potato Research 83: 195-204. Palta, J.P. 1996. Role of calcium in plant responses to stresses: Linking basic research to the solution of practical problems. HortScience 31: 51-57. Park, S., C.K. Kim, L.M. Pike, R.H. Smith, and K.D. Hirschi. 2004. Increased calcium in carrots by expression of an Arabidopsis H+/Ca2+ transporter. Molecular Breeding 14: 275-282. Park, S., T.S. Kang, C.K. Kim, J.S. Han, S. Kim, R.H. Smith, and K.D. Hirschi. 2005a. Genetic manipulation for enhancing calcium content in potato tuber. Journal of Agricultural and Food Chemistry 53: 5598-5603.

207

Park, S., N.H. Cheng, J.K Pittman, K.S. Yoo, J. Park, R.H. Smith, and K.D. Hirschi. 2005b. Increased calcium levels and prolonged shelf life in tomatoes expressing Arabidopsis H+/ Ca2+ transporters. Plant Physiology 139: 1194-1206. Pechanova, O., C.Y. Hsu, J. Adams, T. Pechan, L. Vandervelde, J. Drnevich, S. Jawdy et al. 2010. Apoplast proteome reveals that extracellular matrix contributes to multistress response in poplar. BMC Genomics 11(1), 674. doi:10.1186/1471-2164-11-674. Pittman, J. K., and K.D. Hirschi. 2001. Regulation of CAX1, an Arabidopsis Ca2+/H+ antiporter. Identification of an N-terminal autoinhibitory domain. Plant Physiology 127: 1020-1029. Pittman, J.K., T. Shigaki, N.H. Cheng, and K.D. Hirschi. 2002. Mechanism of N-terminal autoinhibition in the Arabidopsis Ca2+/H+ Antiporter CAX1. Journal of Biological Chemistry 277: 26452-26459. R Development Core Team. 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org. Robertson, D.N. 2013. Modulating Plant Calcium for Better Nutrition and Stress Tolerance. ISRN Botany. doi: 10.1155/2013/952043 Saidi, Y., A. Finka, M. Muriset, Z. Bromberg, Y.G. Weiss, F.J. Maathuis, and P. Goloubinoff. 2009. The heat shock response in moss plants is regulated by specific calcium-permeable channels in the plasma membrane. The Plant Cell Online 21: 2829-2843. Sam, O., E. Jerez, J. Dell'Amico, and M.C. Ruiz-Sanchez. 2000. Water stress induced changes in anatomy of tomato leaf epidermes. Biologia Plantarum 43: 275-277. Saunders, N.A. 2004. Quantitative real-time PCR. In Real-time PCR: an essential guide. Norfolk, 103-125, United Kingdom: Horizon Bioscience. Seidell, A. 1919. Solubilities of inorganic and organic compounds: a compilation of quantitative solubility data from the periodical literature. Second Edition. New York: D. Van Nostrand Company. Seling, S., A.H. Wissemeier, P. Cambier, and P. Van Cutsem. 2000. Calcium deficiency in potato (Solanum tuberosum ssp. tuberosum) leaves and its effects on the pectic composition of the apoplastic fluid. Physiologia Plantarum 109: 44-50. Singh, O.S. and V.K. Sharma. 1972. Alterations in growth and metabolism of potato plants by calcium deficiency. Plant and Soil 36: 363-369.

208

Tang, W., R.J. Newton, and D.A. Weidner. 2007. Genetic transformation and gene silencing mediated by multiple copies of a transgene in eastern white pine. Journal of Experimental Botany 58: 545-554. Tawfik, A.A., M.D. Kleinhenz, and J.P. Palta. 1996. Application of calcium and nitrogen for mitigating heat stress effects on potatoes. American Journal of Potato Research 73: 261-273. Tuteja, N., and S. Mahajan. 2007. Calcium signaling network in plants: an overview. Plant Signaling and Behavior 2: 79-85. Tzeng, K.C., A. Kelman, K.E. Simmons, and K.A. Kelling. 1986. Relationship of calcium nutrition to internal brown spot of potato tubers and sub-apical necrosis of sprouts. American Journal of Potato Research 63: 87-97. Wang, L.,X. Lv, H. Li, M. Zhang, H. Wang, B. Jin, and T. Chen. 2013. Inhibition of apoplastic calmodulin impairs calcium homeostasis and cell wall modeling during Cedrus deodara pollen tube growth. PloS One 8: e55411. doi:10.1371/journal.pone.0055411 Wiersum, L.K. 1966. Calcium content of fruits and storage tissues in relation to the mode of water supply. Acta Botanica Neerlandica 15: 406-418. Wu, Q., T. Shigaki, J.S. Han, C.K. Kim, K.D. Hirschi, and S. Park. 2012. Ectopic expression of a maize calreticulin mitigates calcium deficiency-like disorders in sCAX1-expressing tobacco and tomato. Plant Molecular Biology 80: 609-619. Yuan, J.S., J. Burris, N.R. Stewart, A. Mentewab, and C.N. Stewart. 2007. Statistical tools for transgene copy number estimation based on real-time PCR. BMC Bioinformatics 8 (Suppl 7): S6.

209

TABLES Table 5.1. Transgenic and wildtype from Atalantic and Russet Norkotah clones evaluated under in-vitro conditions for various attributes including %multiple shoots, % stressed leaves, height, biomass, calcium and copies of the transgene at three calcium treatments, 3mM, 10mM and 30mM.

line 3mM 10mM 30mM 3mM 10mM 30mM 3mM 10mM 30mM 3mM 10mM 30mM 3mM 10mM 30mM copies MS

ATL-WT 0.0 0.0 0.0 0.0 0.0 1.8 8.5 7.6 5.4 0.4 0.3 0.2 3431 6447 12933 0 3AT1_01_01_01 75.0 0.0 0.0 0.0 0.0 50.0 7.7 8.7 9.4 0.3 0.3 0.4 4071 10159 16186 1 10AT1_01_01_03 50.0 0.0 0.0 0.0 33.3 100.0 1.4 2.6 2.2 0.0 0.1 0.1 17971 ND 20547 ND 15AT1_01_03_01 75.0 25.0 0.0 0.0 0.0 100.0 5.2 8.4 11.1 0.2 0.2 0.6 5068 9317 18569 1 15AT1_01_06_02 0.0 0.0 0.0 0.0 0.0 0.0 7.9 8.8 10.5 0.4 0.4 0.5 4085 6864 15752 2 6AT1_02_01_01 50.0 14.3 0.0 0.0 0.0 14.3 8.8 7.6 8.8 0.4 0.3 0.4 3817 7170 20657 1 15AT1_02_03_01 100.0 50.0 0.0 0.0 25.0 50.0 8.0 8.5 7.0 0.3 0.2 0.3 4281 7990 22909 ND 15AT1_02_03_02 100.0 42.9 42.9 0.0 0.0 42.9 4.6 7.3 7.2 0.1 0.2 0.3 3830 7854 18397 1 20AT1_02_04_01 0.0 0.0 0.0 0.0 0.0 25.0 6.4 5.6 3.0 0.2 0.2 0.1 4942 7316 40000 2 or 3 15AT1_02_04_03 100.0 33.3 33.3 0.0 0.0 0.0 6.7 4.8 8.6 0.3 0.2 0.4 2954 7213 22080 ND 15AT1_02_05_03 100.0 53.3 7.1 0.0 6.7 28.6 4.2 6.5 5.4 0.2 0.2 0.2 3328 6665 16384 ND 15AT1_02_08_01 100.0 90.0 0.0 12.5 10.0 63.6 3.6 7.1 4.6 0.1 0.3 0.3 3492 8037 19380 2 or 3 20AT1_02_09_01 0.0 0.0 0.0 0.0 0.0 0.0 10.7 10.7 7.7 0.4 0.5 0.3 3958 8002 17446 6 6AT1_02_10_01 100.0 25.0 0.0 0.0 0.0 50.0 5.6 7.7 6.9 0.2 0.4 0.3 3844 7709 18104 1 or 2 15AT1_03_01_01 100.0 0.0 0.0 0.0 0.0 0.0 5.1 11.1 9.1 0.2 0.4 0.4 4651 7051 20387 3 20AT1_03_02_01 100.0 33.3 0.0 0.0 33.3 75.0 3.7 4.6 4.8 0.1 0.1 0.2 3821 6448 19033 3 15AT1_03_03_04 100.0 71.4 0.0 0.0 0.0 100.0 5.3 7.9 4.1 0.2 0.3 0.2 2936 7983 20447 ND 15AT1_03_04_02 100.0 33.3 16.7 0.0 66.7 66.7 4.0 6.6 8.0 0.2 0.3 0.3 3186 5785 12878 1 20AT1_03_04_04 100.0 50.0 0.0 0.0 0.0 25.0 4.7 5.4 5.3 0.1 0.2 0.3 3888 3173 23527 1 or 2 10AT1_03_05_02 100.0 75.0 0.0 0.0 25.0 75.0 4.5 5.8 5.0 0.1 0.2 0.2 4491 8937 25497 1 10AT1_03_05_04 100.0 0.0 0.0 0.0 0.0 100.0 9.3 9.2 1.7 0.4 0.3 0.1 3792 2304 22267 1 10AT1_03_05_05 44.4 55.6 11.1 11.1 0.0 33.3 1.3 2.1 3.3 0.1 0.2 0.3 4500 4606 15908 4 20AT1_03_08_01 100.0 100.0 25.0 0.0 0.0 100.0 2.9 5.3 6.6 0.2 0.2 0.3 3485 6066 19770 3 15AT1_03_10_02 50.0 25.0 0.0 0.0 0.0 0.0 4.5 6.7 10.6 0.2 0.2 0.5 3715 7434 15388 ND 6AT1_04_02_02 100.0 50.0 0.0 0.0 0.0 75.0 3.4 3.8 2.5 0.1 0.1 0.1 3702 6863 19033 ND 20AT1_04_02_03 100.0 33.3 0.0 0.0 0.0 50.0 9.1 9.3 3.5 0.2 0.4 0.3 2730 7496 21216 1 or 2 20AT1_04_03_01 0.0 0.0 0.0 0.0 0.0 0.0 11.5 10.1 10.5 0.4 0.3 0.4 4296 10488 20943 3 10AT1_05_02_02 100.0 57.1 0.0 0.0 0.0 66.7 6.2 6.5 5.1 0.2 0.3 0.3 3803 6771 15298 1 15AT1_06_03_01 50.0 0.0 0.0 0.0 0.0 50.0 9.8 5.5 1.9 0.3 0.2 0.1 3788 8305 22075 2 10AT1_06_03_02 0.0 0.0 0.0 0.0 0.0 100.0 3.0 3.6 1.7 0.0 0.1 0.1 4690 7824 19560 ND 10AT1_06_03_04 100.0 0.0 0.0 0.0 0.0 0.0 8.0 7.8 7.0 0.3 0.3 0.3 3002 8734 22955 ND 15AT1_06_08_01 100.0 50.0 0.0 0.0 50.0 0.0 4.3 5.9 6.7 0.1 0.2 0.3 4971 7758 32532 3 15AT1_06_09_01 0.0 0.0 0.0 0.0 0.0 0.0 8.5 4.3 7.1 0.3 0.1 0.3 3542 8257 19170 1 10AT1_06_10_01 25.0 0.0 0.0 0.0 0.0 0.0 10.0 7.9 5.5 0.3 0.3 0.3 3994 10191 19831 ND 6AT1_06_12_02 63.6 60.0 12.5 0.0 0.0 0.0 6.5 8.0 6.4 0.3 0.4 0.3 3696 7252 18179 1 15AT1_06_13_01 100.0 25.0 0.0 0.0 0.0 50.0 4.5 9.7 7.6 0.2 0.3 0.4 4156 7483 17366 ND 20AT1_07_02_03 100.0 62.5 14.3 0.0 0.0 57.1 2.3 5.0 2.6 0.1 0.2 0.1 4191 9739 23984 1 15AT1_07_03_01 50.0 0.0 0.0 0.0 0.0 100.0 7.2 6.7 4.5 0.2 0.2 0.2 3513 8188 18742 2 20AT1_07_04_01 75.0 25.0 0.0 0.0 0.0 25.0 5.1 8.0 6.1 0.2 0.3 0.4 3794 4532 19509 2 10AT1_08_01_01 100.0 25.0 0.0 0.0 50.0 75.0 4.1 7.2 4.4 0.1 0.2 0.2 5876 10896 22194 1 or 2 15AT1_08_02_01 75.0 0.0 0.0 0.0 0.0 0.0 6.7 11.0 11.0 0.2 0.3 0.4 4839 9037 22371 1 15AT2_01_09_01 100.0 50.0 0.0 0.0 0.0 25.0 5.2 4.3 3.8 0.3 0.1 0.3 4018 16706 18853 1 15

RN #12† 0.0 0.0 0.0 0.0 0.0 0.0 13.4 13.9 11.8 0.6 0.7 0.5 4190 7736 11403 0 3CAX1 #34† 100.0 100.0 0.0 0.0 0.0 0.0 5.4 9.8 3.2 0.2 0.3 0.1 5210 11745 19863 1 20

CAX1 #36 K-3-1† 75.0 25.0 0.0 75.0 25.0 25.0 11.3 12.7 5.1 0.5 0.5 0.3 4041 8066 28559 1 15CAX1 #36 K-3-2†100.0 50.0 25.0 50.0 25.0 25.0 17.3 14.2 5.6 0.5 0.5 0.3 4105 7799 27468 1 15

CAX1 #49† 12.5 0.0 0.0 0.0 0.0 0.0 4.0 4.9 3.1 0.2 0.2 0.2 5592 7262 24712 2 10

% multiple shoots % stressed leaves height (cm) biomass (grams) calcium(µg/g)

† Russet Norkotah lines: RN#12 is wildtype and CAX1 #34, CAX1 #36 k-3-1, CAX1 #36 k-3-2 and CAX 1 #49 are transgenic lines expressing sCAX1. High values in red, intermediate in yellow, and low values in green. MS= calcium concentration for best growth, ND= not determined

210 Table 5.2. Analysis of the expression of CAX1 in relation to the house keeping gene EF1-α and a comparison between Atlantic lines.

Atlantic Lines

Threshold cycle difference between CAX1 and EF1-

ΔCt=CtEF1-α-CtCAX1

Difference between clones for threshold cycle variations between CAX1 and EF1-

ΔΔCt

Relative expression

between genes in each line

2ΔCt

Relative expression between

lines 2ΔΔCt

ATL-WT -28.3588 -22.7613 0.000 0.0 AT1_02_01_01 -5.3756 0.2219 0.024 1.2AT1_08_02_01 -5.5975 0 0.021 1.0 AT2_01_09_01 -4.6337 0.9638 0.040 2.0 Table 5.3. Analysis of variance of the calcium concentration in leaves with and without calcium deficiency symptoms evaluated in leaves from the same line. Source DF Mean Sq F-test P (>F) Line 3 4459310 2.0218 0.144967 Symptom 1 21070071 9.5531 0.006017 ** Residual 19 2205568 Lm= Line + Symptom Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) Type indicates a categorical variable with levels transgenic and wildtype Table 5.4. Analysis of variance of the total calcium concentration in plants grown under in-vitro conditions

Source DF Sum Sq Mean Sq F value Pr(>F)

Treatment 1 5.33e+08 5.33e+08 362.602 < 2.2e-16 ***

Cultivar 1 21435992 21435992 14.5929 0.000264 ***

Block 2 731091 365545 0.2489 0.780306

Type‡ 1 24822578 24822578 16.8983 9.58E-05 ***

Treatment x Type 1 3921300 3921300 2.6695 0.106269

Residuals 79 1.16e+08 1468936

Lm = Treatment + Cultivar + Block + Type + Treatment x Type Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.5. Analysis of variance of the total calcium concentration in tubers under greenhouse conditions on a fresh weight basis


Cultivar 2 2984.65 1492.32 28.0758 6.00e-09 ***

Treatment 1 1230.61 1230.61 23.1519 1.37e-05 ***

Block 2 98.51 49.25 0.9266 0.4025

Type‡ 1 0.15 0.15 0.0028 0.9584

Residuals 51 2710.83 53.15

Lm = Treatment + Line + Block + Block x Line Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype

211 Table 5.6. Analysis of variance of the percent cell wall extracted from fresh tuber tissue under greenhouse conditions


Cultivar 2 2.5517 1.2758 2.2329 0.134597

Block 2 1.2796 0.6398 1.1197 0.346969

Type‡ 1 10.6734 10.6734 18.6796 0.000368 ***

Residuals 19 10.8564 0.5714

Lm =Cell wall% ~ Type + Cultivar +Block Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.7. Analysis of variance of the calcium concentration in the tuber cell wall under greenhouse conditions in fresh weight basis


Cultivar 2 10.152 5.076 2.2306 0.1348

Block 2 0.175 0.0873 0.0384 0.9624

Type‡ 1 2.506 2.5062 1.1014 0.3071

Residuals 19 43.236 2.2756

Lm =Cell wall% ~ Type + Cultivar +Block Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.8. Analysis of variance of the percentage of water-extractable fraction of calcium concentration in in-vitro grown plants expressed in dry weight basis as an indirect measurement of apoplastic calcium


Treatment 1 0.35662 0.35662 18.2097 5.39 e-05 ***

Cultivar 1 0.06853 0.06853 3.4994 0.06505 .

Block 2 0.07267 0.03633 1.8552 0.16308

Type‡ 1 0.06705 0.06705 3.4237 0.06796 .

Residuals 80 1.56673 0.01958

Lm = HCl soluble calcium ~ Treatment + Type + Cultivar +Block Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype

212 Table 5.9. Analysis of variance of the HCl-extractable fraction of calcium concentration in in-vitro grown plants in dry weight basis as an indirect measurement of calcium oxalate


Treatment 1 85392778 85392778 197.179 < 2 e-16 ***

Cultivar 1 3163454 3163454 7.305 0.0084 **

Block 2 631065 315533 0.729 0.48576

Type‡ 1 4961500 4961500 11.457 0.00111 **

Residuals 80 34645783 433072

Lm = HCl soluble calcium ~ Treatment + Type + Cultivar +Block Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.10. Analysis of variance of the plant biomass under greenhouse conditions


Treatment 3 531449 177150 4.5923 0.009232 **

Block 3 64491 21497 0.5573 0.647314

Type‡ 1 410243 410243 10.6349 0.002765 **

Treatment x Type 3 378327 126109 3.2692 0.034763 *

Residuals 30 1157253 38575

Lm= Biomass ~ Treatment + Type + Block + Treatment x Type Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.11. Analysis of variance of the plant biomass under in-vitro conditions


Treatment 1 5.0031 5.0031 134.0155 < 2.2 e-16 ***

Block 2 0.3915 0.1958 5.2438 0.005501 **

Type‡ 1 2.7917 2.7917 74.7803 < 2.2 e-16 ***

Treatment x Type 1 1.3845 1.3845 37.086 1.91 e -09 ***

Residuals 665 24.8258 0.0373

Lm= Biomass ~ Treatment + Type + Block + Treatment x Type Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype

213 Table 5.12. Analysis of variance of the plant height under in-vitro conditions


Treatment 1 683.3 683.29 119.9937 < 2.2e-16 ***

Block 2 78.2 39.1 6.8671 0.001117 **

Type‡ 1 576.7 576.68 101.2704 < 2.2e-16 ***

Treatment x Type 1 115.7 115.71 20.3196 7.74e-06 ***

Residuals 665 3786.8 5.69

Lm = Height ~ Treatment + Type + Block + Treatment x Type Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.13. Analysis of deviance of the incidence of hollow heart in tubers under greenhouse conditions

Source DF Deviance Resid. Dev Pr(>Chi)

null 181.345

Treatment 1 2.085 179.26 0.1487

Type‡ 1 105.777 73.482 <2e-16 ***

Cultivar 2 0.432 73.051 0.8059

Block 2 0.553 72.498 0.7586

Glm= Hollow heart ~ Treatment + Type + Cultivar +Block Pr(>Chi) indicates the p values of the Chi-square test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype Table 5.14. Analysis of variance of root weight of in-vitro grown plants


Treatment 1 42.28 42.28 59.3076 3.32e-11 ***

Cultivar 1 58.042 58.042 81.4173 8.77e-14 ***

Block 2 4.276 2.138 2.9993 0.05553 .

Type‡ 1 4.311 4.311 6.0467 0.01612 *

Treatment x Type 1 13.468 13.468 18.892 4.08e-05 ***

Residuals 79 56.319 0.713

Lm= Root weight ~ Treatment + Type + Cultivar + Block + Treatment x Type Pr(>F) indicates the p values of the F test. P-value symbols: p< 0.05 (*), p< 0.01 (**), and p<0.001 (***) ‡Type indicates a categorical variable with levels transgenic and wildtype

214

FIGURES Figure 5.1. PCR efficiencies of the qPCR for all primers used for copy number determination and relative amount of transcripts. The R2 values are indicated in the grey box.

Slope=-1.09 Slope=-1.02

Slope=-1.06 Slope=-0.95

Slope=-0.91 Slope=--0.96

5 6 7 8 9

2425

2627

EF1- for q-PCRUsing gDNA

log2(dna1)

Ct

0.996

5 6 7 8 9

2425

26

CAX1 for qPCRUsing gDNA

log2(dna1)

Ct

0.995

4 5 6 7 8

2021

2223

EF1- for q-PCRUsing cDNA

log2cdna1

Ct

0.976

5 6 7 8 9

2425

2627

CAX1 for q-PCRUsing gDNA

log2(dna1)

Ct

0.996

5 6 7 8 9

2425

26NPT II for qPCR

Using gDNA

log2(dna1)

Ct

0.978

4 5 6 7 8

2526

2728

CAX1 for q-PCRUsing cDNA

log2cdna

Ct

0.991

215 Figure 5.2. Verification of transgenic lines by PCR detection of the nptII gene.

CA

X1

#34

AT

L

SU

P

-+ -

100bp ladder

controls

Putative transgenic lines

++ + ++ +- + ++ ++ +

370 bp

Figure 5.3. Apical shoot damage is alleviated at the 15mM calcium treatment under in-vitro grown conditions

Apical shoot damage

Alleviated shoot

Transgenic3mM

Transgenic15mM

Atlantic ‐WT 3mM

Normal shoot

Figure 5.4. Apical shoot damage is alleviated at the 10mM calcium treatment under greenhouse conditions

Alleviated shoot

Apical shoot damage

Transgenic 1mM

Transgenic 10mM

Atlantic ‐WT1mM

216 Figure 5.5. Leaf margin calcium deficiency symptom alleviated to some degree at 10mM in greenhouse grown transgenic plants.

2 cmAtlantic‐WT Transgenic

1mM 10mM 1mM 10mM

217

Figure 5.6. Morphology of the adaxial epidermal cells in the wildtype, and sCAX1 transgenic lines in leaves with and without margin necrosis

Leaf edge

Leaf edge

Leaf edge

300X Transgenic with margin necrosis

10mM

Transgenic without margin necrosis

10mM

Atlantic‐WT1mM

300X 300X

500X 500X 500X

Pictures taken with a FEI Quanta environmental scanning electron microscope (ESEMTM) under the conditions indicated in the pictures. The green arrows indicate stomata.

218

Figure 5.7. Total calcium concentration (means ± SD) in leaf tissue from symptomatic leaves versus asymptomatic leaves grown in the greenhouse at the high calcium treatment (10mM) under greenhouse conditions. Evaluations performed in single copy lines fom Atlantic and Russet Norkotah lines.

AT1_02_01_01 AT1_08_02_01 CAX1 #36 k-3-1 CAX1 #36 k-3-2

SymptomNo symptom

Cal

ciu

m (

µg

/g d

ry w

eig

ht)

020

0040

0060

0080

00

Symptomatic versus Asymptomatic Leavesat the high calcium treatment

a

ab

a

b

a

b

a

Condition

Atlantic lines Russet Norkotah lines

The differences in calcium concentration between symptomatic versus asymptomatic leaves were significant. A protected LSD test was performed between the means of the symptomatic versus asymptomatic, LSD=1269. ANOVA analysis presented on Table 5.3.

219

Figure 5.8. Calcium concentration of in-vitro grown plants (means ± SD) at the sufficient (3mM) and high (15mM) calcium treatments. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Ca

lciu

m (μ

g/g

)

020

0040

0060

0080

0010

000

1200

0Total calcium concentration in in-vitro grown plants

3mM 15mM 3mM 15mM


ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

b

a

bb

c

b b

a

b

aa

a a

a

Calcium treatments

The differences in total calcium concentration in of vitro grown plants between the transgenic and wildtype lines were significant at 15mM. A protected LSD test was performed between the means for transgenic versus wildtype lines, LSD= 804.8. ANOVA analysis presented on Table 5.4.

220

Figure 5.9. Total calcium concentration (means ± SD) in tubers under greenhouse conditions in the sufficient (1mM) and high calcium treatments (10mM), values expressed on fresh weight basis. The potato cultivar Superior was included for comparison. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Cal

ciu

m (

µg

/g f

resh

we

igh

t)

020

4060

80

Total calcium concentration in tubersat the sufficient and high calcium treatments

1mM 10mM 1mM 10mM 1mM 10mM

Superior

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2


Calcium treatments

Significant differences for total tuber calcium content were detected between cultivars and treatments but not between the transgenic versus wildtype lines by the ANOVA analysis (Table 5.5).

221

Figure 5.10. Detection of calcium oxalates in the sCAX1 transgenic lines

B

C D

A

E F

Transgenic Transgenic

Transgenic Transgenic

WT WT

A. Vascular tissue of a sCAX1 transgenic line showing calcium oxalates. B. Trichomes showing crystals of calcium oxalate. C, D. Close-up to vascular cells with calcium oxalate crystals under polarized light and brightfield in a transgenic line. E, F. Close-up to vascular cells of the Atlantic wildtype under polarized light and brightfield showing no calcium oxalate crystals.

222

Figure 5.11. Calcium oxalates in the mesophyll of the sCAX1 transgenic lines

B

pc

WT

ue

sc

D Transgenic

pc ue

sc

le

vb

C Transgenic

pc ue

sc

le

vb

Aupper epidermis (ue)

palisade cells (pc)

spongy cells (sc)

lower epidermis (le)

Transgenic

vascular bundle (vb)

A. Transversal section of the leaf of a sCAX1 transgenic line showing the differential distribution of crystals among mesophyll cells. B. Epidermis and mesophyll cells showing no crystals of calcium oxalate in the Atlantic wildtype. C, D. Epidermis and mesophyll cells of a transgenic line showing crystals under brightfield and polarized light.

223

Figure 5.12. Percent cell wall biomass extracted from fresh tuber tissue (means ± SD) at the sufficient (1mM) calcium treatment under greenhouse conditions. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines. The potato cultivar Superior was included for comparison.

The differences in the percentage of dry weight cell walls extracted per gram of fresh tuber tissue between the transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD= 0.69%. ANOVA analysis shown in Table 5.6.

Cell wall/tuber fresh weight (% g/g)

0

1

2

3

4

Percent cell wall biomass extracted from tubersat the sufficient calcium treatment

a

b b

b

a

b b

SuperiorAtlantic lines Russet Norkotah lines

224

Figure 5.13. Calcium concentrations (means ± SD) in tuber cell walls under greenhouse conditions in the sufficient (1mM) calcium treatment in fresh weight basis. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines. The potato cultivar Superior was included for comparison.

Calcium concentration in tuber cell wallsat the sufficient calcium treatment


Cal

ciu

m (

µg

/g f

resh

we

igh

t)

24

68

a

ab

a

b

a

b

a

0

The differences in the cell walls calcium concentration in fresh weight basis between the transgenic and wildtype lines were not significant. The LSD test was performed between the means for transgenic versus wildtype lines. LSD= 1.38. ANOVA analysis shown in Table 5.7.

225

Figure 5.14. Water-extractable calcium concentration (means ± SD) in in-vitro grown plants as an indirect measurement of apoplastic calcium. The data on water-extractable fraction is presented as the percentage of total calcium. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Water extractable calcium concentrationunder in-vitro conditions

Per

cen

tag

e

010

2030

4050

15mM 3mM 15mM3mM

a a

b b

a

b

b

aa a

a

a a

a

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines


Calcium treatments

The differences in the percentage of water-extractable calcium concentration between the transgenic and wildtype lines were significant at =0.1. An LSD test was performed between the means for transgenic versus wildtype lines. LSD= 6.6%. ANOVA analysis shown in Table 5.8.

226

Figure 5.15. HCl-extractable calcium concentration in (means ± SD) in-vitro grown plants as an indirect measurement of calcium oxalates. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Cal

ciu

m(µ

g/g

)

010

0020

0030

0040

0050

00

HCl extractable calcium concentrationunder in-vitro conditions

3mM 15mM 3mM 15mM

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

bb b

a

bb

a

c

b

c

a

b

aa


Calcium treatments

The differences in the HCl-extractable calcium concentration between the transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD= 310.4. ANOVA analysis shown in Table 5.9.

227

Figure 5.16. Plant biomass (means ± SD) at different calcium treatments under greenhouse conditions. Evaluations performed in single copy lines and the wildtype fom Atlantic.

1mM 10mM 15mM 20mM

Bio

ma

ss

(g)

050

010

0015

0020

00

Plant biomass at different calcium treatments

under greenhouse conditions

a

b

b

a

b b

ab

a

b

a a

a

ATL-WTAT1_02_01_01AT1_08_02_01

Lines

Calcium treatments

The differences in the plant biomass under greenhouse conditions between the transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD= 251.9. ANOVA analysis shown in Table 5.10.

228

Figure 5.17. Plant biomass (means ± SD) at different calcium treatments under in-vitro conditions. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

3mM 15mM

Bio

ma

ss

(g

)

0.0

0.5

1.0

1.5

Plant biomass at different calcium treatments

under in-vitro conditions

3mM 15mM

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

a

b bb

ab

a a

a

b b

a a a


Calcium treatments

The differences in the plant biomass under in-vitro conditions between the transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD= 0.046. ANOVA analysis shown in Table 5.11.

229

Figure 5.18. Plant height (means ± SD) at different calcium treatments under in-vitro conditions. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Hei

gh

t (c

m)

05

1015

20Plant height at different calcium treatments


3mM 15mM 3mM 15mM

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

a

b

cd

a a ab

a

b b

ab

b


Calcium treatments

The differences in the plant height under in-vitro conditions between the transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD= 0.57. ANOVA analysis shown in Table 5.12.

230

Figure 5.19. Internal defects in transgenic and wildtype lines of Atlantic and Russet Norkotah

Russet Norkotah

transgenic

Russet Norkotah

WT

Atlantic WT

Atlantictransgenic

hollow heart

hollow heart

brown center

231

Figure 5.20. Incidence of hollow heart (means ± SD) at the sufficient (1mM) and high calcium treatment (10mM). The potato cultivar Superior was included for comparison. Evaluations performed in single copy lines and the wildtype fom Atlantic and Russet Norkotah lines.

Pe

rcen

tin

cid

enc

e

020

4060

8010

0

Incidence of internal defects: hollow heartat the sufficient and high calcium treatment

1mM 10mM 1mM 10mM 1mM 10mM

ATL-WT

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

b

aa

a

b

aba

ab

b

aa

b

a

ab


Calcium treatments

The differences in hollow heart incidence at sufficient and high calcium treatments between the transgenic and wildtype lines as demonstrated by the ANODE (Table 5.13). The Kruskal-Wallis test performed to detect differences between the transgenic versus the wildtype lines were significant at =0.05 for the Atlantic lines and at =0.1 for the Russet Norkotah lines. The non-parametric Mann-Whitney test (Mann and Whitney 1947) performed for the incidence of hollow heart at the sufficient and high calcium treatments in a pair-wise manner also demonstrated that defects were significantly reduced only for AT2_01_09_01 with a p-value=0.076.

232

Figure 5.21. Root weight of 8 plants (means ± SD) at the sufficient and high calcium treatments under in-vitro conditions. Evaluations performed in single copy lines fom Atlantic and Russet Norkotah lines, and the wildtype fom Russet Norkotah.

Ro

ot

we

igh

t (g

)

02

46

810

Root weight of 8 plants


3mM 15mM 3mM 15mM

ATL

RN #12-WT

AT1_02_01_01AT1_08_02_01AT2_01_09_01

CAX1 #36 K-3-1CAX1 #36 K-3-2

Lines

a

b bb

a aa a

a

b b

b

a a


Calcium treatments

The differences in the amount of roots between transgenic and wildtype lines were significant. A protected LSD test was performed between the means for transgenic versus wildtype lines. LSD=0.56. ANOVA analysis presented on Table 5.14.

233

CHAPTER 6

General Discussion and Conclusions

DISCUSSION

The present study utilized two populations generated by the reciprocal crosses of Atlantic and

Superior. Our evaluation demonstrated that these populations were well suited for the study of

tuber calcium and its relationship with tuber quality. In addition to tuber calcium the parents used

contrasted for tuber yield; specific gravity; enzymatic browning; visual ratings of chip color, chip

color in agtron units, colorimetric measurements of chip color, incidence of hollow heart and

blackspot bruise; as well as incidence and severity of pitted scab. Our results show that these

reciprocal populations segregated for most of these traits except for blackspot bruise that had low

overall incidences in both reciprocal populations. The evaluation of phenotypic variation for

tuber calcium, tuber quality traits, and pitted scab observed in the reciprocal populations of

Atlantic and Superior had an important genetic component due to significant genotype and

genotype x environment (GxE) effects. These traits also showed in most cases intermediate to

high broad-sense heritabilities.

The populations studied in this research are unique in the sense that these are the first tetraploid

segregating populations that have been studied to understand the genetics of tuber calcium in

relation to several commercially important traits. Previous studies have investigated the

234

phenotypic variation for tuber calcium in commercial cultivars (Karlsson et al. 2006; Brown et

al. 2012), and wild potato germplasm (Bamberg et al. 1993), but not in segregating bi-parental

populations. The progenies of these populations had large enough tubers that permitted precise

estimation of tuber internal quality. This is particularly important because larger tubers are

known to be more susceptible to internal defects such as hollow heart compared to small tubers

(Jansky and Thompson 1990).

Another important aspect of our reciprocal populations of Atlantic x Superior is that the parents

are two important commercially accepted chipping cultivars and this is one of the reasons why

SolCAP selected this population for genotyping. Previous tetraploid populations of potato

evaluating quantitative trait loci for commercial traits have used crosses between a released

cultivar and an advanced breeding line. For instance, the processing advanced line 12601ab1 was

crossed to the fresh market cultivar Stirling to study tuber yield, agronomic quality, and a

common scab index (Bradshaw et al. 2008). A tetraploid population generated by the cross of the

fresh market cultivar Jacqueline Lee (susceptible to scab) and the advanced chip processing line

MSG227-2 (tolerant to scab) was previously used to study pitted scab severity (Driscoll et al.

2009). In addition, a tetraploid population generated by the cross of the chipping cultivar Atlantic

and the advanced chipping line B1829-5 population was used to evaluate internal heat necrosis,

yield, dry matter, specific gravity, maturity, texture and flower color (McCord et al. 2011a,

2011b).

The distribution of the genotypic variation was evaluated to depict segregation. A bell-shaped

distribution was observed for tuber yield, specific gravity, enzymatic browning, visual rating of

235

chip color, chip color in agtron units, chip lightness, chip redness, chip yellowness, and tuber

calcium. However, the distributions were skewed towards resistance for the incidence of hollow

heart, internal brown spot, blackspot bruise, as well as pitted scab incidence and severity.

Phenotypic variation for quantitative traits results from the segregation of alleles at multiple

quantitative trait loci (QTL) with effects that are sensitive to the genetic, sexual, and external

environments (Mackay 2001). Bell-shaped distributions have been related to the segregation of

several loci; however, these can also be obtained if large environmental error is affecting a single

genotype (Falconer and Mackay 1996). Therefore, the phenotypic distributions by itself do not

give information about the quantitative nature of a trait. The phenotypic distributions together

with the heritability estimations, significant genotype effects and QTL analysis performed in this

study suggest that all the traits evaluated, including tuber calcium concentration, are quantitative.

The comparison between the reciprocal populations of Atlantic x Superior revealed that the

progenies had tuber calcium more similar to the maternal parent in all years of evaluation.

Previous studies trying to understand maternal inheritance in potato have been performed in

reciprocal populations using parents from different cultivar groups. These reports studied

cytoplasmic male sterility (De la Puente and Peloquin 1968); tuber initiation, tuber set, vine

senescence, tuber yield, flowering, and male fertility generated by the difference in photoperiod

(Sanford and Hanneman 1979). Further evaluation of yield by Sanford and Hanneman (1982) in

reciprocal populations indicated that the higher-yielding reciprocal always had the higher-

yielding parent as the maternal parent. These authors reported that opposite maturities between

the parents was the proposed explanation for the differences between reciprocal populations for

yield. In our study the two parents were not very different in maturity suggesting that this may

236

not be the cause of the difference between reciprocal populations we studied. Differences in chip

color performance between reciprocal populations were observed in diploid populations (Lauer

and Shaw 1970, Jakuczun and Zimnoch-Guzowska 2004) but not in tetraploid populations

(Coffin et al. 1988, Ehlenfeldt et al. 1990, and Pereira et al. 1993). Nevertheless, we observed

significant differences in performance for enzymatic browning, the visual scale of chip color,

chip color in agtron units and chip lightness but only for one year of evaluation. In our study the

population size was variable between the reciprocal populations and that factor is most likely

influencing the differences between the means and their significance. The differences between

the reciprocal populations of Atlantic x Superior for tuber calcium were significant for the three

years of evaluation suggesting that tuber calcium may be influenced by maternal effects.

A tetraploid map was successfully constructed using 600 simplex SNP markers from the SolCAP

8300 Infinium Chip using the Atlantic x Superior population. Previous mapping studies at the

tetraploid level have been performed using AFLP and SSR markers and therefore were targeting

mostly neutral regions, however the SNP chip from SolCAP was designed to target expressed

regions (Hamilton et al, 2011). In our study QTL were identified for tuber calcium, tuber quality

traits and pitted scab tolerance using an interval mapping approach. The interval mapping

approach in tetraploid populations is described by Luo et al (2001). This interval mapping

approach allowed us to detect 75 QTL in total for all traits studied. However, the ±1 LOD

confidence intervals were large for most QTL. The interval mapping approach is not as powerful

compared to other methodologies such as composite interval mapping that uses covariates to

remove the effects of other QTL allowing a more precise localization of the putative QTL (Zeng

1993, Jansen 1993). Future development of new software tools that can perform composite

237

interval mapping or multiple interval mapping in tetraploid populations and the use of all types

of segregation will allow breeders to take full advantage of the 8300 Infinium SNP Chip and to

map QTL more precisely.

Our study is the first attempt to identify the genomic regions that control tuber calcium. Calcium

is an important trait to study in potato tuber because it has important structural properties that

stabilize cell walls and membranes (Demarty et al. 1984, Hirschi 2004). In our study, eight QTL

were detected for tuber calcium concentrations. This number of QTL is in agreement with

calcium being a quantitative trait. The quantitative nature of calcium concentration in the tuber is

somewhat expected because there is a large number of calcium transporters and calcium binding

regulatory proteins that work in complex networks within cells (Boudsocq and Sheen 2010). Half

of the QTL for tuber calcium were additive. The other half were dominant in a simplex or duplex

dosage. On average, each of these eight QTL explained approximately 10% of the variance.

These results are consistent with a study in soybeans where four QTL explaining around 10% of

the variance each were identified for seed calcium in a F2 population generated by a cross of a

low seed calcium cultivar with a high seed calcium cultivar (Zhang et al. 2009). In another study

in common beans two QTL for calcium content were detected and the sum of the variance

explained by both QTL was 25% (Guzmán-Maldonado et al. 2003), indicating similar QTL

effects compared to the QTL for tuber calcium concentration detected in our study.

Hollow heart studied in the Atlantic x Superior population had an intermediate to moderately

high broad-sense heritability. Seven QTL were found for hollow heart. Four of these QTL were

additive, two were dominant in duplex dosage and one was dominant in simplex dosage. The

238

most stable QTL for hollow heart were located on Chr.3 at 0 and 40 cM respectively, and

explained between 7.5 to 19.7% of the total variance. The several QTL identified for hollow

heart suggests that this trait is controlled by several genes. Bradshaw et al. (2008) evaluated the

internal condition (IC), a simultaneous evaluation of incipient hollow heart, hollow heart,

internal necrosis and flecking in a single visual score in a 1 to 9 scale, in the 12601ab1 x Stirling

population. These authors detected only one QTL for IC in Chr. 5 with a single copy of an allele

for increased defects. It seems that these authors may have had less power to detect QTL because

they combined several defects in a new single score. Interestingly, significantly negative genetic

correlations between hollow heart and tuber calcium were identified in our study. These

correlations are in agreement with previous studies reporting that tuber calcium content can be

increased by seasonal calcium application and this increase was related to reduced internal

defects such as blackspot bruise (Karlsson et al. 2006) and internal brown spot (Ozgen et al.

2006). Calcium has important structural properties that maintain cell strength; thus clones with

an adequate amount of tuber calcium may be able to withstand cell damage by physiological

stress, which is considered a cause of hollow heart (Levitt 1942). Therefore, the negative

correlation observed between tuber calcium and hollow heart can be explained by a direct

protective effect of calcium on the tubers to tolerate physiological stress. This negative

correlation may also be partially explained by linkage between loci for tuber calcium and hollow

heart since QTL for tuber calcium concentration and hollow heart incidence were located less

than 20 cM apart on Chr. 3 and 9.

Another interesting finding in our study is related to the evaluation of pitted scab. When

incidence and severity of pitted scab are studied under high disease pressure conditions, the

239

heritabilities were higher suggesting that the differences between genotypes for tolerance to this

pathogen are better observed in a field that was used to grow potatoes for several years without

rotation and where there is enough inoculum to reveal genotypic differences. This finding is

supported by other published reports indicating that seed-borne inoculum contributes

significantly to the disease level (Cairns et al. 1936, Wilson et al. 1999).

Several studies have concluded that common scab resistance in haploid or diploid potato is

controlled by one or few genes (Alam 1972, Krantz and Eide 1941, Murphy et al. 1995) but it

does not seem to be the case in tetraploid potatoes (Dees and Wanner 2012). A segregating

tetraploid population showed continuous variation in common scab resistance, indicating

complex genetics (Driscoll et al. 2009). Four QTL for pitted scab incidence under standard

disease conditions and seven QTL each for incidence and severity under high disease pressure

were detected in our study in agreement with a quantitative nature for common scab tolerance as

it was suggested by previous research (Dionne and Lawrence 1961, Cipar and Lawrence 1972).

Bradshaw et al. (2008) found two QTL for a scab index from 1 (susceptible) to 9 (resistant) on

Chr. 2 and 6 at positions 80 and 86 cM in the Stirling x 12601ab1 tetraploid population in a

standard field. Recently, Braun (2013) identified a QTL located at 10.1 cM on Chr.11 using two

different types of common scab rating, lesion type (LT) and percent surface area (PSA), in a

diploid population generated by a cross between the susceptible S. tuberosum clone US-W4 and

a scab resistant S. chacoense clone 524-8. Similarly, we found that most QTL identified for the

two measurements of pitted scab resistance in our tetraploid populations, pitted scab incidence

and severity, were located in the same positions suggesting that both traits may be controlled by

the same genes. The number of QTL identified by our study was larger than for previous reports.

240

This may, in part, be due to the evaluation method used in our study. We focused on the

evaluation of pitted lesions which are more prominent and easier to detect and therefore the

heritability of this trait was high. In addition, our evaluations were performed in a high disease

field that had enough inoculum that was effective in revealing genotypic differences.

We also found significantly negative correlations between tuber calcium and pitted scab

incidence and severity under high disease pressure. Previous studies had shown contradictory

data, Horsfall et al. (1954) and Davis et al. (1974) reported a positive correlation between

calcium in the tuber peel and common scab severity. Lambert and Manzer (1991) concluded that

high calcium in the periderm was a consequence rather than a cause of increased scab. Our study

relates incidence and severity of pitted scab lesions with calcium concentration in the tuber

medullary tissue and therefore is not influenced by contact with the pathogen. Several studies

have demonstrated that increased calcium concentrations in the potato tuber and tomato stems

reduced the effects of pathogen infections (McGuire and Kelman 1986, Yamazaki and Hoshina

1995, Jiang et al. 2013). Also Flego et al. (1997) demonstrated that an increase in extracellular

calcium concentration in the plant repressed the expression of a pectic enzyme-encoding gene by

the pathogen. The results of our study are in agreement with these published reports and indicate

a protective action of tuber calcium to prevent pathogen attack.

Nearly half of the QTL identified in this study were additive. For instance, we detected three

additive QTL for tuber yield in Chr. 1 that explained approximately 32.9% of the variance. This

results contrast with previous reports that have found that the non-additive genetic effects are the

main component of variance for yield in diploid potato (Mendiburu and Peloquin 1971, Killick

241

1977). In addition, additive genetic variance was minimal or zero and therefore narrow-sense

heritability was low for average external lesion diameter and internal lesion depth caused by

Fusarium (Burkhart et al. 2007). These studies suggest that non-additive genetic variance is a

main component of the genetic variance for some potato traits at the diploid level. However, Hill

et al. (2008) used evidence from empirical studies of genetic variance components across a range

of traits and species to imply that most genetic variance is additive and typically accounts for

over half, and often close to 100% of the total genetic variance. These authors also presented

theoretical results, based upon the distribution of allele frequencies under neutral and other

population genetic models that show why there is mainly additive genetic variance at the level of

gene action even if there are non-additive effects. For example, at a completely dominant locus

almost all the variance contributed is additive if the recessive gene is at high frequency (Falconer

and Mackay 1996). Hill et al. (2008) postulated two primary explanations to explain that most

genetic variance appears to be additive genetic, first that there is indeed little real dominant or

epistatic gene action, or second that it is mainly because allele frequencies are distributed

towards extreme values, as for example in the neutral mutation model. In addition, bottlenecks

usually change the proportion of variance that is additive due to the dispersal of gene frequencies

and the reduction in mean heterozygosity (Cheverud and Routman 1996). These evidence

support that genetic variance is mainly additive at the level of gene action. In addition, additive

and dominance components evaluated in crosses between clones of group Phureja and haploid

clones of Tuberosum indicates that in some of their trials dominance components were higher

than additive but in other trials the additive and dominance components were similar (Rowe

1969). In support of our findings, previous studies that identified QTL for tuber yield also found

half of the QTL with additive effects. Bradshaw et al. (2008) identified two QTL for tuber yield,

242

one dominant in simplex dosage that explained 13.3% of the variance on Chr. 6 and another one

additive on Chr.1. that explained 5.3% of the variance. Interestingly, the three additive QTL

identified in our study is also located on Chr.1. and explained between 9.1 and 13.1% of the

variance. The QTL effects reported by Bradshaw were based on the analysis of 227 progenies

whereas those in our study were based on 128 progenies. This smaller population size in our

study may be causing an over-estimation of the effects of QTL and the real effects may be lower

than predicted. Another factor to consider is that two of those additive QTL in Chr.1 come from

the same parent Superior thus are linked. The presence of linked QTL can interfere with the

estimation of QTL effects especially when using interval mapping without covariates (Broman

and Sen 2009), as it is the case in TetraploidMap. It appears from the discussion above that the

three QTL identified in Chr. 1 in our study may be additive, however, the estimated effects may

not be the “real” effects.

Different measurements of chip color were found to be highly correlated and most QTL for these

traits were located in close proximity or the same location in the genome. The joint analysis of

multiple phenotypes can increase the power for QTL detection and the precision of QTL

localization and can allow one to test for pleiotropy, a single QTL affecting multiple phenotypes

(Broman and Sen 2009). In our study multiple measurements for the chip color detected QTL for

this trait in the same region indicating that the different methods employed were in agreement.

The results of our study suggest that the over-expression of CAX1 is transporting large amounts

of Ca+2 into the vacuole making it less available in other parts of the cell. This detrimental effect

of an increased transport of Ca+2 into the vacuole has shown to increase the incidence of blossom

243

end defect in tomato fruits (de Freitas et al. 2011) and caused leaves necrosis in tobacco (Hirschi

1999). In our study, the effects of the increased transport of calcium into the vacuole were

associated with apical shoot damage, leaf margin necrosis and internal tuber defects. These

symptoms are a consequence of the induced calcium deficiency in the plant but they can be

alleviated by either increasing the apoplastic calcium or the symplastic movement of calcium.

Apoplastic calcium can be increased by growing the plants under high calcium treatments. The

amelioration of tuber internal defects in the CAX1 transgenic lines resembles that one observed

when supplemental calcium is applied to potatoes in-season (Karlsson et al. 2006, Ozgen et al.

2006). However, the calcium deficiency is very high in the transgenic lines so that the alleviation

is not complete. Symplastic calcium transport has been reported to increase by over-expressing

Calreticullin (CRT) (Wu et al. 2012). CRT is a calcium binding protein that can mobilize Ca+2

through the endoplasmic reticulum and the cytoplasm (Wyatt et al. 2002). The endoplasmic

reticulum is closely associated with plasmodesmata and the desmotubule provides a potential

pathway for movement between cells (Roberts and Oparka 2003). Our results suggest that it

would be interesting to select for potato cultivars that have a high efficiency of apoplastic and

symplatic calcium transport and therefore an adequate supply of calcium where and when it is

needed. These two genes CAX1 and CRT deserve to be studied in more detail in relation to tuber

calcium and tuber quality.

Another question generated by our study is if total tuber calcium is the best predictor of internal

quality. The observed effects of the over-expression of the CAX1 gene in potato demonstrate that

not only the total amount of calcium but its sub-cellular distribution is very important to maintain

cellular health and therefore internal tuber quality. These results suggest that it might be

244

important to determine which fractions of tuber calcium (cell wall calcium, apoplastic calcium or

vacuolar calcium) besides the total tuber calcium is the best predictor of adequate internal

quality. The results of our study suggest that an adequate amount of calcium distributed where it

is needed in the tuber cells is necessary to withstand physiological and biotic stress.

CONCLUSIONS

The goal of this thesis was to generate new knowledge about the genetics of tuber calcium and

its relationship with tuber quality. The results of the research presented in this thesis lead us to

come up with several conclusions listed by chapter in the following lines.

Characteristics of the reciprocal populations of Atlantic x Superior (Chapter 2)

1. Atlantic and Superior have contrasting phenotypes for tuber yield, specific gravity,

enzymatic browning, chip color using visual ratings, chip color in agtron units,

colorimetric measurements of chip color, tuber calcium, incidence of hollow heart and

blackspot bruise, as well as incidence and severity of pitted scab. The reciprocal

populations of Atlantic and Superior are segregating for all traits these cultivars differ.

2. The performance of these populations differed significantly for several traits but only in

one year of evaluation, except for tuber calcium that was significantly different between

the reciprocal populations for the three years of evaluation.

245

3. Tuber yield, specific gravity, chip quality traits and tuber calcium had bell-shaped

distributions that resemble normal distributions. However, the incidences of hollow heart

and blackspot bruise as well as pitted scab incidence and severity had skewed

distributions that suggest the presence of major dominant genes for these traits. Bell-

shaped distributions have been related to the segregation of several loci; however, these

can also be obtained if large environmental error is affecting a single genotype.

Correlations and broad-sense heritabilities between traits in the Atlantic x Superior

reciprocal populations (Chapter 3)

1. The phenotypic variation for tuber calcium, tuber quality traits, and pitted scab observed

in the reciprocal populations of Atlantic and Superior has an important genetic

component due to the significant genotypic effects for all traits. This genotypic variation

can be exploited to select for cultivars with improved yield and specific gravity,

improved chip quality and internal quality, and tolerant to pitted scab.

2. All traits studied including tuber quality traits, pitted scab tolerance and tuber calcium are

influenced by environmental effects, including the year of evaluation as well as

significant genotype x environment (year) in at least one the reciprocal populations.

3. The performances of the reciprocal populations showed significant correlations between

two out of three years of evaluation for most traits. Hollow heart was the only trait that

had significant correlations between all years of evaluation, whereas all years were

uncorrelated for blackspot bruise.

246

4. A significantly negative correlation for hollow heart with tuber calcium was found. This

correlation is in agreement with previous reports that relate high tuber calcium and

decreased incidence of defects.

5. Most measurements of chip color were significantly correlated. We recommend chip

lightness and the visual rating of chip color for selection because they are correlated to all

other measurements of chip color.

6. High correlations were observed between pitted scab incidence and severity under high

disease pressure indicating that pitted scab incidence could be scored for quick

assessments.

7. The results of the relationship analyses indicated that higher tuber calcium decreased the

probability of getting tubers with hollow heart as well as tubers with pitted scab and the

number of pits per tuber under the high disease field conditions.

8. Four promising clones that have good chipping quality, good internal quality, reduced

pitted scab incidence and severity as well as acceptable yield based on three years of

evaluation compared to Atlantic were selected from the reciprocal populations.

Identification of QTL for tuber calcium, tuber quality and pitted scab tolerance in the

Atlantic x Superior tetraploid population (Chapter 4)

10. A tetraploid map was successfully constructed using 600 simplex SNP markers from the

SolCAP 8300 Infinium Chip. The map for Atlantic had more than twice the number of

markers, 414, compared to Superior, 186, probably due to the higher inbred pedigree of

247

Superior.

11. Several SNP loci had more than expected duplex genotypes suggesting that the method

for the estimation of dosage used by SolCAP may not be completely accurate.

12. Several quantitative trait loci were identified for tuber calcium, tuber quality traits and

pitted scab tolerance in the Atlantic x Superior tetraploid population using an interval

mapping approach.

13. The correlation between hollow heart and tuber calcium can be explained at least

partially due to linkage because two QTL for hollow heart were in close proximity to

QTL for tuber calcium concentration indicating that part of the correlation between these

traits may be explained by linkage.

14. For some correlated traits such as several methods of measurement of chip color as well

as measurements of pitted scab incidence and severity, we found several QTL in the same

chromosomes and similar position indicating that these correlated traits might be

detecting the same QTL.

15. The detection and sometimes location of QTL varied from year to year due to the effects

of different population sizes and also probably environmental effects.

16. Markers with significant effects were identified for several traits in the marker regression

analysis and many of them were located ±20 cM of a QTL.

17. Approximately half of the QTL detected were additive with a complex inheritance. The

other half consisted of QTL in a simplex and duplex dosage. These simplex and duplex

QTL have higher potential to become markers for marker assisted selection (MAS).

248

Effect of the over-expression of the CAX1 gene in potato (Chapter 5)

1. A wide range of phenotypic variability was observed among the transgenic lines

probably due to differences in copy number, gene expression and the specific genomic

position where the CAX1 gene was inserted.

2. These results of the in-vitro and greenhouse experiments suggest that the increased

transport of Ca2+ towards the vacuole reduces the availability of calcium in other cell

compartments and therefore calcium deficiency symptoms are observed in the transgenic

lines expressing sCAX1 even when they are growing using media or soil calcium

concentrations that are sufficient for the wildtype plants.

3. The appearance of calcium deficiency symptoms such as apical shoot damage and

marginal necrosis was mitigated at high calcium concentrations in the media or the soil.

4. Squared-shaped and smaller epidermal cells as well as increased number of stomata and

trichomes were observed comparing the leaf morphology leaves showing margin necrosis

and normal leaves from the same transgenic plant at the high (10mM) calcium treatment

in greenhouse grown plants. These characteristics are indicators of nutritional stress even

though they are growing at high calcium levels.

5. The total amount of calcium in in-vitro grown plants and tubers of the transgenic lines is

similar to the wildtype at the sufficient calcium treatment. However, high amount of

calcium are stored in the vacuole. Therefore, we can assume that there is less calcium

available in the apoplast because the Ca2+ transport into the vacuole modulates apoplastic

calcium concentrations.

6. Calcium oxalate crystals were detected in the vascular tissue, epidermis, trichomes as

249

well as the palisade and spongy cells of the mesophyll of leaves from the sCAX1

transgenic plants.

7. The transgenic lines had less cell walls biomass as a consequence of the reduced

apoplastic Ca2+ concentration.

8. The over-expression of sCAX1 in potato compromises plant health as shown by reduced

biomass and height in the transgenic lines compared to the wildtype. Nevertheless, plant

health is ameliorated by high tuber calcium treatments.

9. Higher incidence of internal defects, specifically hollow heart, was found in the

transgenic clones as compared to the wildtype in the greenhouse studies. This internal

defect was mitigated by increased tuber calcium in the soil.

10. Russet Norkotah had significantly higher root biomass than Atlantic at the sufficient and

high calcium treatments. Also, in the presence of high calcium Russet Norkotah increased

whereas Atlantic maintained the root biomass. The transgenic lines of Atlantic increased

their root biomass to similar values compared to the wildtype at the high calcium

treatment. The Russet Norkotah transgenic lines also increased their root biomass but to

significantly higher values compared to the wildtype.

BIBLIOGRAPHY

Alam, Z. (1972). Inheritance of scab resistance in 24-chromosome potatoes. University of Wisconsin--Madison. Bamberg, J.B., J.E Palta, L.A. Peterson, M. Martin, and A.R. Krueger. 1993. Screening tuber-bearing Solanum (potato) germplasm for efficient accumulation of tuber calcium. American Potato Journal 70: 219-226.

250

Boudsocq, M., and J. Sheen. 2010. Stress signaling II: calcium sensing and signaling. In Abiotic Stress Adaptation in Plants, 75-90. Springer Netherlands. Bradshaw, J.E., C.A. Hackett, B. Pande, R. Waugh, and G.J. Bryan. 2008. QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum). Theoretical and Applied Genetics 116: 193–211. Braun, S.R. 2013. Quantitative trait loci analysis and breeding for resistance to common scab in potato. Ph.D. dissertation Plant Breeding and Plant Genetics. University of Wisconsin. Broman K. W., and S. Sen. 2009. A Guide to QTL Mapping with R/qtl. Springer, New York. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller Jr. 2012. Stability and Broad-Sense Heritability of Mineral Content in Potato: Calcium and Magnesium. American Journal of Potato Research 89: 255-261. Burkhart, C.R., B.J, Christ, and K.G. Haynes, 2007. Non-additive genetic variance governs resistance to Fusarium dry rot in a diploid hybrid potato population. American journal of potato research 84: 199-204. Cairns, H., T.N. Greeves, and A.E. Muskett, 1936. The Control of Common Scab (Actinomyces scabies (Thaxt.) Güss.) of the Potato by Tuber Disinfection. Annals of Applied Biology 23(4): 718-74. Cipar, M.S., and C.H. Lawrence. 1972. Scab resistance of haploids from two Solanum tuberosum cultivars. American Journal of Potato Research 49: 117–119. Cheverud, J.M., E.J. Routman. 1996. Epistasis as a source of increased additive genetic variance at population bottlenecks. Evolution 50: 1042–1051. Coffin R, MK Keenan, R Yada, G Tai, M Slavnik, and G Johnston. 1988. Inheritance of genetic factors controlling chip processing quality after tuber storage at low temperatures [Abstract]. American Journal of Potato Research 65:474. Davis, J.R., G.M. McMaster, R.H. Callihan, J.G. Garner, and R.E. McDole. 1974. The relationship of irrigation timing and soil treatments to control potato scab. Phytopathology 64: 1404-1410. Dees, M.W., and L.A. Wanner. 2012. In Search of Better Management of Potato Common Scab. Potato Research 55: 249-268. De la Puente, F., and S. J. Peloquin. 1968. Male fertility of selected 24 chromosome S. tuberosum hybrids. American Potato Journal 45: 436-437. Demarty, M., C. Morvan, and M. Thellier. 1984. Calcium and the cell wall. Plant, Cell & Environment 7: 441-448.

251

Dionne, L.A. and C. H. Lawrence. 1961. Early scab resistant derivatives of Solanum chacoense x Solanum phureja. American Journal of Potato Research 38: 6-8 Driscoll, J., J. Coombs, R. Hammerschmidt, W. Kirk, L. Wanner, and D. Douches. 2009. Greenhouse and Field Nursery Evaluation for Potato Common Scab Tolerance in a Tetraploid Population. American Journal of Potato Research 86: 96–101. Ehlenfeldt M.K., D.F. Lopez-Portilla, A.A. Boe, and R.H. Johansen. 1990. Reducing sugar accumulation in progeny families of cold chipping potato clones. American Journal of Potato Research 67: 83-91. Falconer, D.S., and T.F.C. Mackay. 1996. Introduction to Quantitative Genetics, Fourth Edition. Essex, UK: Longman, Harlow. Flego, D., M. Pirhonen, H. Saarilahti, T.K. Palva, and E.T. Palva. 1997. Control of virulence gene expression by plant calcium in the phytopathogen Erwinia carotovora. Molecular Microbiology 25: 831-838. de Freitas, S.T., M. Padda, Q. Wu, S. Park, and E.J. Mitcham. 2011. Dynamic alternations in cellular and molecular components during blossom-end rot development in tomatoes expressing sCAX1, a constitutively active Ca2

+/H+ antiporter from Arabidopsis. Plant Physiology 156: 844-855. Guzmán-Maldonado, S.H., O. Martínez, J.A. Acosta-Gallegos, F. Guevara-Lara, and O. Paredes- López. 2003. Putative quantitative trait loci for physical and chemical components of common bean. Crop Science 43: 1029-1035. Hamilton, J.P., C. N. Hansey, B. R. Whitty, K. Stoffel, A. N. Massa, A. Van Deynze, W.S. De Jong, D.S. Douches, and C.R. Buell. 2011. Single nucleotide polymorphism discovery in elite North American potato germplasm. BMC Genomics 12: 302-312 Hill, W.G., M.E. Goddard and P.M. Visscher. 2008. Data and Theory Point to Mainly Additive Genetic Variance for Complex Traits. PLoS Genetics 4: e1000008. doi:10.1371/journal.pgen.1000008 Hirschi, K.D. 1999. Expression of Arabidopsis CAX1 in tobacco: altered calcium homeostasis and increased stress sensitivity. The Plant Cell Online 11: 2113-2122. Hirschi, K.D. 2004. The calcium conundrum. Both versatile nutrient and specific signal. Plant Physiology 136: 2438-2442. Horsfall, J.G., J.P. Hollis, and H.G.M. Jacobson. 1954. Calcium and potato scab. Phytopathology 44: 19-24. Jansen, R.C. 1993. Interval mapping of multiple quantitative trait loci. Genetics 135: 205-211.

252

Jansky, S.H. and Thompson D.M. 1990. Expression of Hollow Heart in segregating tetraploid potato families. American Potato Journal 67: 695-793. Jiang, J.F., J.G. Li, and Y.H Dong. 2013. Effect of calcium nutrition on resistance of tomato against bacterial wilt induced by Ralstonia solanacearum. European Journal of Plant Pathology 136: 547-555. Karlsson B.H., J.P. Palta, and P.M. Crump. 2006. Enhancing tuber calcium concentration may reduce incidence of blackspot bruise injury in potatoes. Hort Science 41: 1213-1221. Killick, R.J. 1977. Genetic analysis of several traits in potatoes by means of a diallel cross. Annals of Applied Biology 86: 279-289. Krantz, F.A. and C.J. Eide. 1941. Inheritance of reaction to common scab in the potato. Journal of Agricultural Research 63:219-231. Jakuczun, H. and E. Zimnoch-Guzowska. 2004. Inheritance of glucose content in tubers of diploid potato families. American Journal of Potato Research 81: 359-370. Lambert, D.H., and F.E. Manzer. 1991. Relationship of Calcium to Potato Scab. Phytopathology 81: 632-636. Lauer, F. and R. Shaw. 1970. A possible genetic source for chipping potatoes from 40 F storage. American Journal of Potato Research 47: 275-278. Levitt, J. 1942. A historical study of hollow heart potatoes. American Journal of Potato Research 19: 134-143. Luo, Z. W., C. A. Hackett, J. E. Bradshaw, J. W. McNicol, and D. Milbourne, 2001. Construction of a genetic linkage map in tetraploid species using molecular markers. Genetics 157: 1369-1385. Mackay, T. F. 2001. The genetic architecture of quantitative traits. Annual Review of Genetics 35: 303-339. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011a. Linkage Mapping and QTL Analysis of Agronomic Traits in Tetraploid Potato (Solanum tuberosum subsp. tuberosum). Crop Science 51: 771-785. McCord, P.H., B.R. Sosinski, K.G. Haynes, M.E. Clough, and G.C. Yencho. 2011b. QTL mapping of internal heat necrosis in tetraploid potato. Theoretical and Applied Genetics 122: 129–142. McGuire, R. and A. Kelman. 1986. Calcium in potato tuber cell walls in relation to tissue maceration by Erwinia carotovora pv. atroseptica. Physiology and Biochemistry 7: 401-406.

253

Mendiburu, A.O. and S.J. Peloquin 1971. The significance of 2N gametes in potato breeding. Theoretical and Applied Genetics 49: 53-61. Murphy, A.M., H. Jong, G.C.C. Tai. 1995. Transmission of resistance to common scab from the diploid to the tetraploid level via 4x-2x crosses in potatoes. Euphytica 82:227–233 Ozgen S., B.H. Karlsson, and J.P. Palta. 2006. Response of potatoes (cv. ‘Russet Burbank’) to supplemental calcium applications under field conditions. Tuber calcium yield and incidence of brown spot. Journal American Potato Research 83: 195-204. Pereira, A.D.S., R.H. Coffin, R.Y. Yada and V.S. Machado. 1993. Inheritance patterns of reducing sugars in potato tubers after storage at 12C and 4C followed by reconditioning. American Potato Journal 70: 71-76. Roberts, A. G. and K.J. Oparka. 2003. Plasmodesmata and the control of symplastic transport. Plant, Cell and Environment 26: 103-124. Rowe, P.R. 1969. Quantitative variation in diploid potatoes. American Journal of Potato Research 46: 14-17. Sanford, J.C., and R.E. Hanneman,. 1979. Reciprocal differences in the photoperiod reaction of hybrid populations inSolanum tuberosum. American Potato Journal 56: 531-540. Sanford, J.C. and R.E. Hanneman Jr. 1982. Large yield differences between reciprocal families of Solanum tuberosum. Euphytica 31: 1-12. Wilson, C.R., L.M. Ransom and B. M Pemberton. 1999. The Relative Importance of Seed‐borne Inoculum to Common Scab Disease of Potato and the Efficacy of Seed Tuber and Soil Treatments for Disease Control. Journal of Phytopathology 147: 13-18. Wu, Q., T. Shigaki, J.S. Han, C.K. Kim, K.D. Hirschi, and S. Park. 2012. Ectopic expression of a maize calreticulin mitigates calcium deficiency-like disorders in sCAX1-expressing tobacco and tomato. Plant Molecular Biology 80: 609-619. Wyatt, S.E., P.L. Tsou and D. Robertson. 2002. Expression of the high capacity calcium-binding domain of calreticulin increases bioavailable calcium stores in plants. Transgenic Research 11: 1-10. Yamazaki, H., and T. Hoshina. 1995. Calcium nutrition affects resistance of tomato seedlings to bacterial wilt. HortScience 30: 91-93. Zhang, B., P. Chen, A. Shi, A. Hou, T. Ishibashi, and D. Wang. 2009. Putative quantitative trait loci associated with calcium content in soybean seed. Journal of Heredity 100: 263-269.

254

Zeng, Z-B. 1993. Theoretical basis for separation of multiple linked gene effects in mapping of quantitative trait loci. Proceedings of the National Academy of Sciences 90: 10972–10976.

understanding the genetics of potato tuber calcium and its

Documents