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GeneticaAn International Journal of Genetics andEvolution ISSN 0016-6707 GeneticaDOI 10.1007/s10709-016-9898-x

Comparative assessment of genetic diversityin cytoplasmic and nuclear genome ofupland cotton

Sharof S. Egamberdiev, SukumarSaha, Ilkhom Salakhutdinov, JohnieN. Jenkins, Dewayne Deng & IbrokhimY. Abdurakhmonov

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Comparative assessment of genetic diversity in cytoplasmicand nuclear genome of upland cotton

Sharof S. Egamberdiev1 • Sukumar Saha2 • Ilkhom Salakhutdinov1 •

Johnie N. Jenkins2 • Dewayne Deng2 • Ibrokhim Y. Abdurakhmonov1

Received: 8 October 2015 / Accepted: 7 April 2016! Springer International Publishing Switzerland (outside the USA) 2016

Abstract The importance of the cytoplasmic genome formany economically important traits is well documented in

several crop species, including cotton. There is no report on

application of cotton chloroplast specific SSR markers as adiagnostic tool to study genetic diversity among improved

Upland cotton lines. The complete plastome sequence

information inGenBank provided us an opportunity to reporton 17 chloroplast specific SSRmarkers using a cost-effective

data mining strategy. Here we report the comparative anal-

ysis of genetic diversity among a set of 42 improved Uplandcotton lines using SSR markers specific to chloroplast and

nuclear genome, respectively. Our results revealed that low

to moderate level of genetic diversity existed in both nuclearand cytoplasm genome among this set of cotton lines.

However, the specific estimation suggested that genetic

diversity is lower in cytoplasmic genome compared to thenuclear genome among this set of Upland cotton lines. In

summary, this research is important from several perspec-tives. We detected a set of cytoplasm genome specific SSR

primer pairs by using a cost-effective data mining strategy.

We reported for the first time the genetic diversity in thecytoplasmic genome within a set of improved Upland cotton

accessions. Results revealed that the genetic diversity in

cytoplasmic genome is narrow, compared to the nucleargenome within this set of Upland cotton accessions. Our

results suggested that most of these polymorphic chloroplast

SSRs would be a valuable complementary tool in addition tothe nuclear SSR in the study of evolution, gene flow and

genetic diversity in Upland cotton.

Keywords Cytoplasmic genome ! Chloroplast specificSSR markers ! Nuclear SSR markers ! Genetic diversity !Upland cotton

Introduction

Breeders normally select genotypes based on morphologi-

cal characters, primarily regulated by nuclear genome

because gene flow took place predominantly throughnuclear genome via pollination and subsequently via fer-

tilization of male and female gametes. However, cyto-plasmic genome including mitochondria and chloroplast

genomes play a critical role to perform many important

biological functions (Han et al. 2007; Allen et al. 2005;Karaca et al. 2004); therefore, it is important to know the

genetic diversity associated with cytoplasmic genome in a

plant species.Cytoplasmic genome is distinguished from nuclear

genome by the characteristics of non-recombinant, mater-

nally uniparental inheritance, haploid and highly conser-vative nature due to low mutation rate (Wendel 1989; Cato

Sharof S. Egamberdiev and Sukumar Saha equally credited as the firstauthor for their contribution in this research.

Disclaimer Mention of trademark or proprietary product does notconstitute a guarantee or warranty of the product by the United StatesDepartment of Agriculture and does not imply its approval to theexclusion of other products that may also be suitable.

Electronic supplementary material The online version of thisarticle (doi:10.1007/s10709-016-9898-x) contains supplementarymaterial, which is available to authorized users.

& Sukumar SahaSukumar.saha@ars.usda.gov

1 Center of Genomics and Bioinformatics, Academy ofSciences of Uzbekistan, Tashkent, Uzbekistan 111215

2 Crop Science Research Laboratory, Genetics and SustainableAgriculture Research Unit, USDA-ARS, Mississippi State,MS 39762, USA

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DOI 10.1007/s10709-016-9898-x

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and Richardson 1996; Ferris et al. 1998; Marchelli et al.

1998; Fineschi et al. 2002; Arroyo-Garcia et al. 2002). Thenuclear genes are normally inherited in a Mendelian and

quantitative inheritance pattern following the recombina-

tion events between the male and female gametes. Thedifferent characteristics and mode of genetic inheritance of

cytoplasmic genome from nuclear genome provides com-

plementary useful information to study gene flow, evolu-tion and population history in a plant species.

The economical importance of cytoplasmic genome iswell documented by the severity and wide range of

Southern corn leaf blight epidemic (SCLB) caused by

Helminthosporium maydis, race T, infecting corn plantswith Texas male sterile cytoplasm from inbred Tcms in

1970 (Ullstrup 1972; Shurtleff 1980). This inbred cyto-

plasm was used in about 85 % of the hybrid seed cornproduced in the United States, and the impact of this epi-

demic was well-reflected by rapid increase of corn price

from about $1.35 per bushel to $1.68 within 3 months inChicago grain market, the largest market dealing in this

commodity in the United States (Ullstrup 1972).

Normally, it is very difficult to detect the genetic effectof cytoplasmic genome because of its uniparental inheri-

tance pattern and it is only possible to discern the differ-

ence in the event of reciprocal crosses. Sometimes, thepresence of multiple copies of the organelle genome in an

organism makes it difficult to identify new cytoplasmic

mutants because its effect can be masked by other non-mutant organelles in the plant cells (Allen et al. 2005).

Sometimes, the presence of similar sequence in both

nuclear and cytoplasmic genome makes genetic studies ofcytoplasmic genome very challenging.

There are very few reports on the genetic diversity in the

cytoplasmic genome in Upland cotton (Li et al. 2014). Thisprompted us to mitigate the problem of detecting diversity

in the cytoplasmic genome of cotton by developing

chloroplast specific SSR markers using data mining strat-egy from public sequence databases of GenBank (https://

www.ncbi.nlm.nih.gov/genbank/). This cytoplasmic geno-

type-based profiling is faster and more economical thanphenotypic based profiling of the genotypes using recip-

rocal crosses of the parents for detecting the effect of

cytoplasmic genome.In many crops including cotton, simple sequence repeats

(SSRs) or microsatellites are considered to be one of the

markers of choice because they are (1) PCR-based, (2)usually co-dominant, (3) usually multiallelic and hyper-

variable, and (4) randomly dispersed throughout the gen-

ome normally the chloroplast genome contains a singlecircular chromosome with two single copy regions (Lar-

ge:LSC and Small:SSC), separated by two inverted repeat

regions of about 10–76 kbp with an average 20–30 kbp inmost species (Hamza 2010). Recently, the advanced

sequencing technologies provided a scope to sequence

chloroplast genome from several tetraploid and diploidGossypium species (Lee et al. 2006; Ibrahim et al. 2006;

Xu et al. 2012). The complete plastome sequence infor-

mation in GenBank provided us an opportunity to developcytoplasm specific SSR marker in cotton. We followed the

overall strategy of our previous study detecting for the first

time EST-SSR markers in cotton (Qureshi et al. 2004).There are several studies on the genetic diversity in the

nuclear genome of cotton using SSR markers (Abdu-rakhmonov et al. 2008, 2009; Khan et al. 2009; Lacape

et al. 2007; Bertini et al. 2006; Tyagi et al. 2014). How-

ever, here we present for the first time the report on the useof cytoplasmic SSR markers in a comparative analysis of

genetic diversity of the cytoplasmic genome with the

nuclear genome in a set of improved Upland cotton lines.

Materials and methods

Materials

We have selected a set of 42 diverse Upland cotton lines

including improved populations from wild race stocks,

obsolete non-transgenic cultivars, and germplasm linesreleased by public breeders.

Chloroplast specific SSR primer pairs

The overall strategy of developing cpSSR markers were

based on our previous study on EST-SSR (Qureshi et al.2004). We downloaded published chloroplast genome

sequences for G. hirsutum and G. barbadense (Lee et al.

2006; Ibrahim et al. 2006; Xu et al. 2012) and performedsearching for simple sequence repeat regions following the

overall method of Qureshi et al. (2004).

We searched G. hirsutum chloroplast for the presence ofmicrosatellite motifs from about 160, 301 bp sequence

length from public sequence databases of GenBank

(https://www.ncbi.nlm.nih.gov/genbank/). Sequences con-taining at least four di-, tri, tetra-, penta- or hexanucleotide

repeats were detected using Perl script (Buyyarapu et al.

2011). Primers were designed for the flanking regions ofthe SSR using the web-based software, ‘‘Primer3’’ program

(Rozen and Skaletsky 2000) which was based on the cri-

teria of 50 % GC content, a minimum melting temperatureof 50 "C, and absence of secondary structure. Primers were

designed ranging from 18 to 27 nucleotides in length and

amplified products of 100–400 bp following the overallmethod of Qureshi et al. (2004). The primers were syn-

thesized by Life Technologies Corp., Carlsbad, CA, USA.

We used only polymorphic cpSSR primer pairs in our finalresult analysis.

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DNA extraction

We used about two mg of fresh leaf samples of individualline for DNA extraction using a QIAGEN DNeasy Plant

Maxi kit (QIAGEN Inc., CA) and/or with a QIAGEN

DNeasy Plant Mini kit following the manufacturer’s pro-tocol. DNA solutions were diluted to a working concen-

tration of 10 ng ll-1 and stored at 4 "C until PCR

amplification.

PCR method with universal labeled primerfor cpSSR

PCR reactions were performed in 10 ll volumes containing

10 ng of cotton template DNA, 19 GeneAmp PCR Goldbuffer from Applied Biosystems, (109, 150 mM Tris–HCl,

PH 8.0, 500 mM KCl), 1 mM MgCl2, 0.2 mM dNTPs,

0.5 lM of forward and reverse primer mixtures, 0.35 ll ofAmpliTaq Gold, (Applied Biosystems). Dye-labeled chro-

mosome specific forward and unlabeled reverse primers

were used in all PCR reactions. We used a modified PCRprotocol to be cost effective by using a universal Fluores-

cent labeled HPLC Purified T13 primer. To use universal

primer, we added a 19 bp long sequence of CAGTTTTCCCAGTCACGAC to the 50 left end of each forward

primer, and a 4 bp short sequence of GTTT to the 50 left

end of the respective reverse primer (CAGTTTTCCCAGTCACGAC). The modified forward and reverse SSR

primers were dissolved in water respectively to make a

100 lM stock solution. Then forward and reverse SSRprimers are combined to make a diluted 5 lM working

solution. PCR reaction was carried out in 10-ll reactionscontaining 2.5 ll of DNA, 10x Gold Taq Buffer, 20 mMMgCI2, 10 mM dNTPS, 0.3 of each 3 primers, 1 unit of

Taq polymerase and 4.4 milliQ water. The PCR amplifi-

cation profile consisted of an initial denaturation of DNA at95 "C for 3 min, followed by 95 "C for 1 m, 60 "C for

1 m; GOTO 2:1 time, 95 "C for 30 s, 60 "C for 30 s, 68 "Cfor 30 s; GOTO 5; 26 times and a final extension of 4 m at68 "C.

PCR method with nuclear SSR primer pairs

We selected 56 nuclear SSR primer pairs covering com-

plete nuclear genome covering all of the chromosomes toscreen the same set of 42 diverse Upland cotton lines from

CMD web page (Blenda et al. 2006). The nuclear SSR

primer pairs were selected based on the previous studiesconsidering their presence across the whole genome and

association with important fiber traits (Abdurakhmonovet al. 2008, 2009; Guo et al. 1997; Qin et al. 2008; Wu et al.

2009; Yu et al. 2012; Zhang et al. 2013; Fang et al. 2013).

PCR-amplifications were performed in a 8 ll reaction mix

containing 0.8 ll 109 PCR buffer, 0.2 ll dNTPs (10 mM

each), 0.72 ll 25 mM MgCl2, 0.2 ll 5 pM labeled primers(FAM, HEX, VIC, PET), 0.07 ll AmpliTaq Gold DNA

polymerase (Applied Biosystems, USA), and 15 ng geno-

mic DNA. PCR amplification was carried out using a PTC-225 DNA Engine Tetrad thermocycler (MJ Research,

USA) with first denaturation at 95 "C for 10 m, followed

by 10 cycles of 94 "C for 1 m, 60 "C for 1 m (decreases of0.5 "C in each cycle) and 72 "C for 2 m; 33 cycles of

94 "C for 15 s, 55 "C for 30 s, and 72 "C for 1 m. A final6 m extension at 72 "C was performed. Our final result

analysis was based on the screening of 42 Upland cotton

lines with 17 cpSSR and 65 nuclear SSR primer pairs inthis study of genetic diversity (Tables 1, 2, 3).

Gel electrophoresis

The PCR products were diluted 1:20 before loading into

capillaries and run in a denaturing capillary electrophoresisin an ABI 37309l with a 96-capillary system using POP-7

polymer (Applied Biosystems, USA) following the overall

methods of Abdurakhmonov et al. (2008, 2009). The sizeof amplified products was detected using GeneMapper 3.7

(Applied Biosystems, USA) as well as confirmed by visual

corrected for appropriate sizes. The nuclear SSR productsizes were also confirmed based on the available SSR

amplicon product sizes where available in the panel of

CMD web page (Blenda et al. 2006).

Data scoring

We followed the overall method of Bertini et al. (2006) for

dendogram construction and power maker software for data

analysis including PIC value estimation (Liu and Muse2005). Nei’s (1978) genetic distance and phylogenetic

analyses of cotton accessions was calculated using

PAUP*4.0 b. We used Cluster analysis using unweightedpair group method of UPGMA and the dendrogram

resulting from these estimations was drawn using STA-

TISTICA program (StatSoft Inc., http://www.statsoft.com/).Since G. hirsutum is an allopolyploid with reticulated

germplasm resources, nuclear SSR primer pairs often

yielded multiple PCR-products in our cotton accessions.There is a great risk of false allele calling for multiple-band

SSR markers when wide germplasm resources with

unknown pedigree information are genotyped, unless onlysingle-band loci are selected for genotyping. We scored

both the cpSSR and nuclear SSR data as a dominant marker

to avoid ambiguous scoring for allelic relationship withoutpedigree data and considering our primary goal to compare

the genetic diversity of the haplotype markers specific to

the cytoplasmic genome with nuclear genome in a set ofUpland cotton lines. We scored the SSR data like a

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dominant marker type with ‘‘1’’ for absent, ‘‘2’’ for present

state, or ‘‘0’’ for the occasional non-amplification ormissing data state, taking each band as an independent

marker locus with a clear size band separation (Abdu-

rakhmonov et al. 2008, 2009) to avoid assignment ofincorrect allelic relationships.

Since G. hirsutum is an allopolyploid with reticulated

germplasm resources, nuclear SSR primer pairs oftenyielded multiple PCR-products in our cotton accessions.

We scored both the cpSSR and nuclear SSR data as adominant marker to avoid ambiguous scoring for allelic

relationship without pedigree data and considering our

primary goal to compare the genetic diversity of the

haplotype markers specific to the cytoplasmic genome with

nuclear genome in a set of Upland cotton lines. The markerdata were analyzed to estimate genetic similarity between

cultivars based on the simple matching coefficient (SI)

using the overall method of Bertini et al. (2006). The SIestimated the similarity between genotypes for each culti-

var by awarding a score to each microsatellite and created

the dissimilarity coefficient index data for individual line.The genetic diversity of each microsatellite locus and

polymorphism information content (PIC) was calculatedusing PowerMarker software (Liu and Muse 2005). The

gene frequency of the microsatellite marker was estimated

based on PIC value.

Table 1 List of the SSR primer pairs specific to the cotton plastid

# Primer name Forward primer (50-30) Reverse primer (50-30) GenBank no

1 cpSSR04 CAGTTTTCCCAGTCACGACggggtcagtcaaacttct GTTTttcagggcgattttatca DQ345959.1

2 cpSSR 15 CAGTTTTCCCAGTCACGACgcaacgatttctatcagtca GTTTcttgttctagcaagagtgtt HQ901196.1

3 cpSSR 19 CAGTTTTCCCAGTCACGACcacatggatacaatctaaatggacg GTTTgaatgattcccatttcagtcg HQ901196.1

4 cpSSR 20 CAGTTTTCCCAGTCACGACgcgccattctaggattcc GTTTtaatggcttggctcgtgga HQ901196.1

5 cpSSR 21 CAGTTTTCCCAGTCACGACtcaaaatcggcagggtat GTTTattgaaaggcaagtcttacg DQ345959.1

6 cpSSR 22 CAGTTTTCCCAGTCACGACatctcacactaagccggt GTTTtgcaatgaattgtttcaaggcc HQ901196.1

7 cpSSR 23 CAGTTTTCCCAGTCACGACggggtcagtcaaacttct GTTTttcttcagttcagggcga HQ901200.1

8 cpSSR 26 CAGTTTTCCCAGTCACGACtcaccttcaacaagcgtaga GTTTacagagatggtgcgatttg HQ901196.1

9 cpSSR 27 CAGTTTTCCCAGTCACGACagcgaaatcgactgaagga GTTTctcgtcgaaacttccaattaggg HQ901196.1

10 cpSSR 29 CAGTTTTCCCAGTCACGACtatgggtctccgatagagacga GTTTaccaatttcgccatatcccc HQ901196.1

11 cpSSR 30 CAGTTTTCCCAGTCACGACcatttcagggccgaattacgc GTTTtgtatggcgcaacctgat DQ345959.1

12 cpSSR 33 CAGTTTTCCCAGTCACGACcgagttattgtcgcggga GTTTaattggagcttgaacccg HQ901196.1

13 cpSSR 36 CAGTTTTCCCAGTCACGACttggaaatgccctttctctc GTTTaagactatgccttcgcca HQ901196.1

14 cpSSR 37 CAGTTTTCCCAGTCACGACaggtctgaattctccaatgga GTTTgactgagaaggttgactcaag HQ901196.1

15 cpSSR 40 CAGTTTTCCCAGTCACGACtagcaacggaaccggggaaagta GTTTcgccaacagttaatcacggaaga HQ901196.1

16 cpSSR 41 CAGTTTTCCCAGTCACGACgcagcaccttaggatggc GTTTggaatctccggatctacgc HQ901196.1

17 cpSSR 45 CAGTTTTCCCAGTCACGACaaaggactcactgagccg GTTTccgagatcctttcgacga HQ901196.1

Table 2 Comparative analysis of nuclear and chloroplast specific SSR markers

SSRmarkerstype

Total numberof primerpairs used

Number ofmarkers/primer pair

Range ofmajor allelefrequency

Average of themajor allelefrequency

Range ofgenediversity

Averageof genediversity

Rangeof PICvalue

Averageof PICvalue

Marker withhighest PICvalue

NuclearspecificSSR

56 4 0.50–1.00 0.88 0–0.50 0.16 0–0.38 0.14 BNL0569_143

ChloroplastspecificSSR

14 5 0.65–1.00 0.94 0–0.46 0.10 0–0.35 0.09 CRSSR40_214

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Table 3 Coefficient of dissimilarity index among the lines using SSR markers (N nuclear SSR markers, CP Chloroplast specific SSR markers)

AcalaUltima Arkot9304b Arkot9308 Arkot9314 Arkot9506 Arkot9513 Coker315 DP90

N CP N CP N CP N CP N CP N CP N CP N CP

AcalaUltima 0 0 0.28 0.2 0.21 0.18 0.2 0.11 0.22 0.14 0.37 0.18 0.22 0.09 0.23 0.23

Arkot9304b 0.28 0.2 0 0 0.28 0.23 0.26 0.09 0.26 0.07 0.37 0.18 0.23 0.18 0.26 0.09

Arkot9308 0.21 0.18 0.28 0.23 0 0 0.22 0.2 0.21 0.23 0.36 0.27 0.25 0.27 0.22 0.25

Arkot9314 0.2 0.11 0.26 0.09 0.22 0.2 0 0 0.22 0.02 0.37 0.09 0.21 0.09 0.22 0.14

Arkot9506 0.22 0.14 0.26 0.07 0.21 0.23 0.22 0.02 0 0 0.28 0.11 0.19 0.11 0.26 0.16

Arkot9513 0.37 0.18 0.37 0.18 0.36 0.27 0.37 0.09 0.28 0.11 0 0 0.37 0.09 0.37 0.18

Coker315 0.22 0.09 0.23 0.18 0.25 0.27 0.21 0.09 0.19 0.11 0.37 0.09 0 0 0.26 0.18

DP90 0.23 0.23 0.26 0.09 0.22 0.25 0.22 0.14 0.26 0.16 0.37 0.18 0.26 0.18 0 0

DE119xT1388F6F11 0.25 0.11 0.3 0.11 0.25 0.2 0.26 0.02 0.27 0.05 0.34 0.07 0.28 0.07 0.29 0.11

DPL90xT1388F6 0.2 0.25 0.25 0.07 0.2 0.27 0.19 0.16 0.23 0.14 0.37 0.2 0.23 0.2 0.19 0.02

DPL90xT239BC3F8 0.17 0.43 0.24 0.41 0.2 0.3 0.17 0.39 0.22 0.41 0.38 0.41 0.2 0.39 0.18 0.36

FM966 0.22 0.16 0.3 0.16 0.24 0.25 0.24 0.07 0.24 0.09 0.36 0.07 0.25 0.07 0.23 0.16

LA1110004okra su 0.23 0.2 0.23 0 0.23 0.23 0.22 0.09 0.23 0.07 0.36 0.18 0.21 0.18 0.18 0.09

LA1110017 0.16 0.55 0.24 0.48 0.17 0.41 0.19 0.5 0.19 0.48 0.35 0.52 0.21 0.5 0.2 0.48

M1388 2 0.24 0.11 0.29 0.11 0.26 0.2 0.25 0.02 0.26 0.05 0.4 0.07 0.26 0.07 0.22 0.11

M237 3 0.24 0.16 0.28 0.25 0.26 0.34 0.26 0.16 0.27 0.18 0.39 0.16 0.3 0.11 0.25 0.25

M239 7 0.25 0.14 0.3 0.14 0.22 0.23 0.24 0.05 0.26 0.07 0.37 0.05 0.28 0.09 0.23 0.14

M240 0.21 0.18 0.28 0.27 0.23 0.36 0.22 0.18 0.24 0.2 0.37 0.18 0.24 0.14 0.22 0.27

MD52ne 0.29 0.11 0.36 0.11 0.31 0.2 0.29 0.02 0.32 0.05 0.39 0.07 0.31 0.07 0.29 0.11

MD65 11 0.35 0.2 0.37 0.02 0.36 0.23 0.34 0.11 0.34 0.09 0.47 0.16 0.35 0.16 0.32 0.07

MD90ne 0.32 0.18 0.36 0.05 0.33 0.2 0.3 0.09 0.36 0.11 0.47 0.14 0.35 0.14 0.23 0.05

MD9ne 0.26 0.14 0.31 0.11 0.24 0.16 0.25 0.16 0.3 0.18 0.38 0.23 0.28 0.23 0.19 0.14

Miscot7803 52 0.19 0.11 0.28 0.11 0.22 0.2 0.2 0.02 0.23 0.05 0.38 0.07 0.25 0.07 0.24 0.11

Miscot7918 0.27 0.14 0.32 0.07 0.23 0.23 0.28 0.02 0.25 0 0.32 0.11 0.27 0.11 0.31 0.16

MiscotT8 27 0.2 0.14 0.25 0.14 0.2 0.23 0.2 0.05 0.23 0.07 0.39 0.05 0.25 0.05 0.25 0.14

PMHS26 0.24 0.11 0.29 0.11 0.25 0.2 0.25 0.02 0.26 0.05 0.36 0.07 0.22 0.07 0.26 0.11

Prymaid 0.19 0.11 0.27 0.11 0.21 0.2 0.2 0.02 0.23 0.05 0.39 0.07 0.21 0.07 0.22 0.11

PSC355 0.21 0.25 0.27 0.18 0.22 0.07 0.18 0.16 0.24 0.18 0.4 0.2 0.22 0.2 0.18 0.18

SG747 0.16 0.45 0.26 0.43 0.21 0.32 0.19 0.41 0.23 0.43 0.37 0.41 0.21 0.41 0.21 0.39

ST474 0.17 0.09 0.22 0.18 0.18 0.27 0.16 0.09 0.22 0.11 0.36 0.14 0.19 0.05 0.16 0.18

ST825 0.34 0.18 0.35 0.27 0.33 0.36 0.34 0.18 0.24 0.2 0.18 0.14 0.33 0.09 0.35 0.27

T 2318USSR 0.31 0.45 0.37 0.52 0.27 0.57 0.3 0.48 0.3 0.5 0.39 0.52 0.29 0.48 0.29 0.52

T 2319USSR 0.45 0.5 0.48 0.57 0.46 0.64 0.44 0.52 0.4 0.55 0.41 0.52 0.4 0.48 0.45 0.57

T 2320USSR 0.21 0.57 0.28 0.52 0.26 0.59 0.22 0.48 0.25 0.5 0.42 0.48 0.24 0.52 0.26 0.52

TAM182 33ELS 0.21 0.18 0.23 0.05 0.22 0.2 0.2 0.09 0.22 0.11 0.37 0.14 0.22 0.14 0.18 0.05

TAM88G 104 0.24 0.14 0.25 0.11 0.24 0.23 0.24 0.02 0.24 0.05 0.38 0.07 0.22 0.11 0.17 0.16

TAM96WD 18 0.27 0.18 0.34 0.16 0.27 0.27 0.28 0.07 0.3 0.09 0.36 0.16 0.27 0.16 0.25 0.16

TAM98D 99ne 0.28 0.25 0.3 0.16 0.3 0.07 0.27 0.14 0.32 0.16 0.36 0.23 0.29 0.23 0.29 0.2

TAMWD69 s 0.18 0.2 0.25 0.18 0.19 0.3 0.18 0.09 0.23 0.11 0.36 0.14 0.23 0.18 0.22 0.23

TM 1 0.25 0.27 0.34 0.23 0.29 0.34 0.28 0.27 0.28 0.3 0.42 0.27 0.3 0.23 0.27 0.23

TTU077433 0.16 0.14 0.29 0.07 0.21 0.23 0.2 0.02 0.23 0 0.39 0.11 0.22 0.11 0.22 0.16

TTU0808161 0.17 0.18 0.28 0.16 0.21 0.27 0.2 0.07 0.25 0.09 0.38 0.16 0.19 0.16 0.23 0.2

Average 0.23 0.21 0.29 0.18 0.24 0.26 0.24 0.14 0.25 0.16 0.36 0.18 0.25 0.18 0.24 0.2

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Table 3 continued

DE119xT1388F6F11 DPL90xT1388F6 DPL90xT239BC3F8 FM966 LA1110004okra su LA1110017

N CP N CP N CP N CP N CP N CP

AcalaUltima 0.25 0.11 0.2 0.25 0.17 0.43 0.22 0.16 0.23 0.2 0.16 0.55

Arkot9304b 0.3 0.11 0.25 0.07 0.24 0.41 0.3 0.16 0.23 0 0.24 0.48

Arkot9308 0.25 0.2 0.2 0.27 0.2 0.3 0.24 0.25 0.23 0.23 0.17 0.41

Arkot9314 0.26 0.02 0.19 0.16 0.17 0.39 0.24 0.07 0.22 0.09 0.19 0.5

Arkot9506 0.27 0.05 0.23 0.14 0.22 0.41 0.24 0.09 0.23 0.07 0.19 0.48

Arkot9513 0.34 0.07 0.37 0.2 0.38 0.41 0.36 0.07 0.36 0.18 0.35 0.52

Coker315 0.28 0.07 0.23 0.2 0.2 0.39 0.25 0.07 0.21 0.18 0.21 0.5

DP90 0.29 0.11 0.19 0.02 0.18 0.36 0.23 0.16 0.18 0.09 0.2 0.48

DE119xT1388F6F11 0 0 0.23 0.14 0.23 0.36 0.29 0.05 0.27 0.11 0.26 0.48

DPL90xT1388F6 0.23 0.14 0 0 0.16 0.39 0.25 0.18 0.21 0.07 0.19 0.45

DPL90xT239BC3F8 0.23 0.36 0.16 0.39 0 0 0.21 0.41 0.21 0.41 0.16 0.18

FM966 0.29 0.05 0.25 0.18 0.21 0.41 0 0 0.26 0.16 0.19 0.52

LA1110004okra su 0.27 0.11 0.21 0.07 0.21 0.41 0.26 0.16 0 0 0.21 0.48

LA1110017 0.26 0.48 0.19 0.45 0.16 0.18 0.19 0.52 0.21 0.48 0 0

M1388 2 0.31 0 0.23 0.14 0.21 0.36 0.27 0.05 0.22 0.11 0.23 0.48

M237 3 0.28 0.14 0.24 0.27 0.22 0.39 0.27 0.18 0.26 0.25 0.22 0.5

M239 7 0.27 0.02 0.25 0.16 0.2 0.36 0.23 0.07 0.27 0.14 0.21 0.48

M240 0.26 0.16 0.23 0.3 0.2 0.39 0.21 0.2 0.25 0.27 0.19 0.55

MD52ne 0.33 0 0.3 0.14 0.27 0.36 0.26 0.05 0.32 0.11 0.28 0.48

MD65 11 0.43 0.09 0.34 0.05 0.33 0.39 0.39 0.14 0.34 0.02 0.34 0.45

MD90ne 0.38 0.07 0.3 0.07 0.3 0.36 0.32 0.11 0.32 0.05 0.32 0.48

MD9ne 0.28 0.16 0.23 0.16 0.21 0.45 0.27 0.2 0.27 0.11 0.24 0.55

Miscot7803 52 0.26 0 0.23 0.14 0.21 0.36 0.25 0.05 0.26 0.11 0.18 0.48

Miscot7918 0.27 0.05 0.28 0.14 0.27 0.41 0.3 0.09 0.3 0.07 0.26 0.48

MiscotT8 27 0.26 0.02 0.19 0.16 0.19 0.39 0.2 0.02 0.24 0.14 0.18 0.5

PMHS26 0.23 0 0.25 0.14 0.2 0.36 0.27 0.05 0.25 0.11 0.21 0.48

Prymaid 0.25 0 0.2 0.14 0.2 0.36 0.19 0.05 0.24 0.11 0.17 0.48

PSC355 0.27 0.14 0.2 0.2 0.17 0.23 0.25 0.18 0.21 0.18 0.21 0.34

SG747 0.26 0.39 0.2 0.41 0.14 0.25 0.21 0.43 0.2 0.43 0.18 0.16

ST474 0.25 0.07 0.15 0.2 0.14 0.36 0.2 0.11 0.19 0.18 0.18 0.48

ST825 0.35 0.16 0.34 0.3 0.35 0.45 0.34 0.11 0.33 0.27 0.32 0.52

T 2318USSR 0.28 0.5 0.28 0.55 0.29 0.66 0.28 0.55 0.33 0.52 0.3 0.73

T 2319USSR 0.46 0.55 0.45 0.59 0.47 0.68 0.47 0.55 0.45 0.57 0.47 0.75

T 2320USSR 0.25 0.5 0.2 0.55 0.19 0.7 0.24 0.5 0.25 0.52 0.21 0.77

TAM182 33ELS 0.28 0.07 0.17 0.07 0.18 0.36 0.23 0.11 0.22 0.05 0.19 0.48

TAM88G 104 0.29 0.05 0.23 0.18 0.18 0.39 0.23 0.09 0.2 0.11 0.22 0.5

TAM96WD 18 0.32 0.09 0.29 0.18 0.26 0.36 0.3 0.14 0.28 0.16 0.27 0.5

TAM98D 99ne 0.33 0.16 0.32 0.23 0.26 0.25 0.26 0.2 0.3 0.16 0.28 0.36

TAMWD69s 0.23 0.11 0.18 0.25 0.16 0.41 0.23 0.16 0.23 0.18 0.18 0.52

TM 1 0.32 0.25 0.28 0.25 0.22 0.39 0.27 0.3 0.3 0.23 0.27 0.5

TTU077433 0.26 0.05 0.21 0.14 0.19 0.41 0.22 0.09 0.23 0.07 0.2 0.48

TTU0808161 0.27 0.09 0.2 0.23 0.19 0.43 0.22 0.14 0.22 0.16 0.19 0.55

Average 0.28 0.14 0.24 0.21 0.22 0.38 0.25 0.17 0.25 0.18 0.22 0.48

Genetica

123

Author's personal copy

Table 3 continued

M1388 2 M237 3 M239 7 M240 MD52ne MD65 11 MD90ne MD9ne

N CP N CP N CP N CP N CP N CP N CP N CP

AcalaUltima 0.24 0.11 0.24 0.16 0.25 0.14 0.21 0.18 0.29 0.11 0.35 0.2 0.32 0.18 0.26 0.14

Arkot9304b 0.29 0.11 0.28 0.25 0.3 0.14 0.28 0.27 0.36 0.11 0.37 0.02 0.36 0.05 0.31 0.11

Arkot9308 0.26 0.2 0.26 0.34 0.22 0.23 0.23 0.36 0.31 0.2 0.36 0.23 0.33 0.2 0.24 0.16

Arkot9314 0.25 0.02 0.26 0.16 0.24 0.05 0.22 0.18 0.29 0.02 0.34 0.11 0.3 0.09 0.25 0.16

Arkot9506 0.26 0.05 0.27 0.18 0.26 0.07 0.24 0.2 0.32 0.05 0.34 0.09 0.36 0.11 0.3 0.18

Arkot9513 0.4 0.07 0.39 0.16 0.37 0.05 0.37 0.18 0.39 0.07 0.47 0.16 0.47 0.14 0.38 0.23

Coker315 0.26 0.07 0.3 0.11 0.28 0.09 0.24 0.14 0.31 0.07 0.35 0.16 0.35 0.14 0.28 0.23

DP90 0.22 0.11 0.25 0.25 0.23 0.14 0.22 0.27 0.29 0.11 0.32 0.07 0.23 0.05 0.19 0.14

DE119xT1388F6F11 0.31 0 0.28 0.14 0.27 0.02 0.26 0.16 0.33 0 0.43 0.09 0.38 0.07 0.28 0.16

DPL90xT1388F6 0.23 0.14 0.24 0.27 0.25 0.16 0.23 0.3 0.3 0.14 0.34 0.05 0.3 0.07 0.23 0.16

DPL90xT239BC3F8 0.21 0.36 0.22 0.39 0.2 0.36 0.2 0.39 0.27 0.36 0.33 0.39 0.3 0.36 0.21 0.45

FM966 0.27 0.05 0.27 0.18 0.23 0.07 0.21 0.2 0.26 0.05 0.39 0.14 0.32 0.11 0.27 0.2

LA1110004okra su 0.22 0.11 0.26 0.25 0.27 0.14 0.25 0.27 0.32 0.11 0.34 0.02 0.32 0.05 0.27 0.11

LA1110017 0.23 0.48 0.22 0.5 0.21 0.48 0.19 0.55 0.28 0.48 0.34 0.45 0.32 0.48 0.24 0.55

M1388 2 0 0 0.26 0.14 0.22 0.02 0.23 0.16 0.31 0 0.35 0.09 0.31 0.07 0.26 0.16

M237 3 0.26 0.14 0 0 0.25 0.11 0.25 0.07 0.3 0.14 0.42 0.23 0.35 0.2 0.28 0.3

M239 7 0.22 0.02 0.25 0.11 0 0 0.21 0.14 0.28 0.02 0.41 0.11 0.34 0.09 0.25 0.18

M240 0.23 0.16 0.25 0.07 0.21 0.14 0 0 0.23 0.16 0.37 0.25 0.32 0.23 0.24 0.32

MD52ne 0.31 0 0.3 0.14 0.28 0.02 0.23 0.16 0 0 0.45 0.09 0.38 0.07 0.32 0.16

MD65 11 0.35 0.09 0.42 0.23 0.41 0.11 0.37 0.25 0.45 0.09 0 0 0.31 0.02 0.36 0.11

MD90ne 0.31 0.07 0.35 0.2 0.34 0.09 0.32 0.23 0.38 0.07 0.31 0.02 0 0 0.26 0.09

MD9ne 0.26 0.16 0.28 0.3 0.25 0.18 0.24 0.32 0.32 0.16 0.36 0.11 0.26 0.09 0 0

Miscot7803 52 0.27 0 0.23 0.14 0.22 0.02 0.17 0.16 0.27 0 0.4 0.09 0.34 0.07 0.28 0.16

Miscot7918 0.33 0.05 0.32 0.18 0.27 0.07 0.26 0.2 0.33 0.05 0.46 0.09 0.4 0.11 0.29 0.18

MiscotT8 27 0.23 0.02 0.27 0.16 0.24 0.05 0.22 0.18 0.29 0.02 0.36 0.11 0.35 0.09 0.28 0.18

PMHS26 0.27 0 0.26 0.14 0.24 0.02 0.23 0.16 0.29 0 0.4 0.09 0.38 0.07 0.3 0.16

Prymaid 0.24 0 0.26 0.14 0.22 0.02 0.19 0.16 0.32 0 0.37 0.09 0.34 0.07 0.26 0.16

PSC355 0.21 0.14 0.25 0.27 0.26 0.16 0.2 0.3 0.29 0.14 0.31 0.16 0.28 0.14 0.22 0.23

SG747 0.25 0.39 0.25 0.34 0.22 0.36 0.19 0.41 0.28 0.39 0.35 0.41 0.3 0.39 0.24 0.48

ST474 0.21 0.07 0.24 0.11 0.21 0.09 0.18 0.14 0.27 0.07 0.34 0.16 0.27 0.14 0.22 0.23

ST825 0.36 0.16 0.38 0.16 0.35 0.14 0.33 0.18 0.34 0.16 0.43 0.25 0.43 0.23 0.36 0.3

T 2318USSR 0.34 0.5 0.36 0.5 0.3 0.48 0.32 0.52 0.36 0.5 0.41 0.55 0.33 0.52 0.28 0.55

T 2319USSR 0.46 0.55 0.45 0.55 0.47 0.52 0.48 0.57 0.5 0.55 0.47 0.59 0.5 0.57 0.46 0.59

T 2320USSR 0.27 0.5 0.25 0.59 0.25 0.48 0.23 0.61 0.27 0.5 0.38 0.55 0.34 0.52 0.25 0.57

TAM182 33ELS 0.25 0.07 0.25 0.2 0.25 0.09 0.23 0.23 0.29 0.07 0.33 0.02 0.3 0 0.25 0.09

TAM88G 104 0.24 0.05 0.25 0.14 0.2 0.02 0.22 0.16 0.26 0.05 0.32 0.14 0.29 0.11 0.22 0.18

TAM96WD 18 0.28 0.09 0.3 0.23 0.28 0.11 0.27 0.2 0.35 0.09 0.39 0.18 0.35 0.16 0.27 0.23

TAM98D 99ne 0.35 0.16 0.3 0.3 0.31 0.18 0.27 0.32 0.29 0.16 0.44 0.18 0.39 0.16 0.34 0.23

TAMWD69 s 0.24 0.11 0.24 0.16 0.21 0.09 0.21 0.18 0.3 0.11 0.36 0.2 0.34 0.18 0.25 0.25

TM 1 0.28 0.25 0.27 0.11 0.29 0.23 0.26 0.18 0.32 0.25 0.38 0.2 0.37 0.18 0.27 0.27

TTU077433 0.22 0.05 0.23 0.18 0.24 0.07 0.21 0.2 0.3 0.05 0.36 0.09 0.33 0.11 0.26 0.18

TTU0808161 0.23 0.09 0.24 0.23 0.22 0.11 0.22 0.25 0.26 0.09 0.37 0.18 0.33 0.16 0.27 0.23

Average 0.26 0.14 0.27 0.22 0.26 0.15 0.24 0.25 0.3 0.14 0.37 0.18 0.33 0.16 0.27 0.23

Genetica

123

Author's personal copy

Table 3 continued

Miscot7803 52 Miscot7918 MiscotT8 27 PMHS26 Prymaid PSC355 SG747 ST474

N CP N CP N CP N CP N CP N CP N CP N CP

AcalaUltima 0.19 0.11 0.27 0.14 0.2 0.14 0.24 0.11 0.19 0.11 0.21 0.25 0.16 0.02 0.17 0.16

Arkot9304b 0.28 0.11 0.32 0.07 0.25 0.14 0.29 0.11 0.27 0.11 0.27 0.18 0.26 0 0.22 0.14

Arkot9308 0.22 0.2 0.23 0.23 0.2 0.23 0.25 0.2 0.21 0.2 0.22 0.07 0.21 0 0.18 0.14

Arkot9314 0.2 0.02 0.28 0.02 0.2 0.05 0.25 0.02 0.2 0.02 0.18 0.16 0.19 0.14 0.16 0.27

Arkot9506 0.23 0.05 0.25 0 0.23 0.07 0.26 0.05 0.23 0.05 0.24 0.18 0.23 0.39 0.22 0.34

Arkot9513 0.38 0.07 0.32 0.11 0.39 0.05 0.36 0.07 0.39 0.07 0.4 0.2 0.37 0.07 0.36 0.11

Coker315 0.25 0.07 0.27 0.11 0.25 0.05 0.22 0.07 0.21 0.07 0.22 0.2 0.21 0.16 0.19 0.16

DP90 0.24 0.11 0.31 0.16 0.25 0.14 0.26 0.11 0.22 0.11 0.18 0.18 0.21 0.55 0.16 0.55

DE119xT1388F6F11 0.26 0 0.27 0.05 0.26 0.02 0.23 0 0.25 0 0.27 0.14 0.26 0.5 0.25 0.5

DPL90xT1388F6 0.23 0.14 0.28 0.14 0.19 0.16 0.25 0.14 0.2 0.14 0.2 0.2 0.2 0.5 0.15 0.59

DPL90xT239BC3F8 0.21 0.36 0.27 0.41 0.19 0.39 0.2 0.36 0.2 0.36 0.17 0.23 0.14 0.07 0.14 0.2

FM966 0.25 0.05 0.3 0.09 0.2 0.02 0.27 0.05 0.19 0.05 0.25 0.18 0.21 0.05 0.2 0.14

LA1110004okra su 0.26 0.11 0.3 0.07 0.24 0.14 0.25 0.11 0.24 0.11 0.21 0.18 0.2 0.43 0.19 0.18

LA1110017 0.18 0.48 0.26 0.48 0.18 0.5 0.21 0.48 0.17 0.48 0.21 0.34 0.18 0.16 0.18 0.48

M1388 2 0.27 0 0.33 0.05 0.23 0.02 0.27 0 0.24 0 0.21 0.14 0.25 0.39 0.21 0.07

M237 3 0.23 0.14 0.32 0.18 0.27 0.16 0.26 0.14 0.26 0.14 0.25 0.27 0.25 0.34 0.24 0.11

M239 7 0.22 0.02 0.27 0.07 0.24 0.05 0.24 0.02 0.22 0.02 0.26 0.16 0.22 0.36 0.21 0.09

M240 0.17 0.16 0.26 0.2 0.22 0.18 0.23 0.16 0.19 0.16 0.2 0.3 0.19 0.41 0.18 0.14

MD52ne 0.27 0 0.33 0.05 0.29 0.02 0.29 0 0.32 0 0.29 0.14 0.28 0.39 0.27 0.07

MD65 11 0.4 0.09 0.46 0.09 0.36 0.11 0.4 0.09 0.37 0.09 0.31 0.16 0.35 0.41 0.34 0.16

MD90ne 0.34 0.07 0.4 0.11 0.35 0.09 0.38 0.07 0.34 0.07 0.28 0.14 0.3 0.39 0.27 0.14

MD9ne 0.28 0.16 0.29 0.18 0.28 0.18 0.3 0.16 0.26 0.16 0.22 0.23 0.24 0.48 0.22 0.23

Miscot7803 52 0 0 0.26 0.05 0.22 0.02 0.23 0 0.19 0 0.24 0.14 0.22 0.39 0.19 0.07

Miscot7918 0.26 0.05 0 0 0.28 0.07 0.23 0.05 0.27 0.05 0.31 0.18 0.3 0.43 0.26 0.11

MiscotT8 27 0.22 0.02 0.28 0.07 0 0 0.26 0.02 0.19 0.02 0.21 0.16 0.18 0.41 0.18 0.09

PMHS26 0.23 0 0.23 0.05 0.26 0.02 0 0 0.23 0 0.25 0.14 0.23 0.39 0.22 0.07

Prymaid 0.19 0 0.27 0.05 0.19 0.02 0.23 0 0 0 0.19 0.14 0.18 0.39 0.16 0.07

PSC355 0.24 0.14 0.31 0.18 0.21 0.16 0.25 0.14 0.19 0.14 0 0 0.18 0.25 0.13 0.2

SG747 0.22 0.39 0.3 0.43 0.18 0.41 0.23 0.39 0.18 0.39 0.18 0.25 0 0 0.13 0.39

ST474 0.19 0.07 0.26 0.11 0.18 0.09 0.22 0.07 0.16 0.07 0.13 0.2 0.13 0.39 0 0

ST825 0.34 0.16 0.29 0.2 0.36 0.14 0.35 0.16 0.37 0.16 0.35 0.3 0.36 0.45 0.31 0.14

T 2318USSR 0.32 0.5 0.35 0.5 0.27 0.52 0.33 0.5 0.29 0.5 0.3 0.57 0.3 0.64 0.25 0.48

T 2319USSR 0.49 0.55 0.39 0.55 0.45 0.52 0.42 0.55 0.48 0.55 0.45 0.64 0.48 0.68 0.45 0.48

T 2320USSR 0.22 0.5 0.29 0.5 0.2 0.48 0.25 0.5 0.22 0.5 0.25 0.57 0.22 0.68 0.2 0.57

TAM182 33ELS 0.2 0.07 0.3 0.11 0.21 0.09 0.26 0.07 0.2 0.07 0.19 0.14 0.18 0.39 0.14 0.14

TAM88G 104 0.22 0.05 0.29 0.05 0.26 0.07 0.25 0.05 0.24 0.05 0.2 0.18 0.21 0.39 0.19 0.11

TAM96WD 18 0.28 0.09 0.3 0.09 0.29 0.11 0.32 0.09 0.29 0.09 0.24 0.23 0.27 0.45 0.24 0.16

TAM98D 99ne 0.28 0.16 0.33 0.16 0.3 0.18 0.26 0.16 0.3 0.16 0.3 0.02 0.26 0.27 0.23 0.23

TAMWD69s 0.21 0.11 0.25 0.11 0.17 0.14 0.24 0.11 0.2 0.11 0.21 0.25 0.19 0.45 0.18 0.18

TM 1 0.28 0.25 0.35 0.3 0.28 0.27 0.3 0.25 0.29 0.25 0.27 0.27 0.26 0.34 0.24 0.23

TTU077433 0.24 0.05 0.29 0 0.22 0.07 0.24 0.05 0.18 0.05 0.19 0.18 0.2 0.43 0.18 0.11

TTU0808161 0.2 0.09 0.26 0.09 0.22 0.11 0.24 0.09 0.17 0.09 0.21 0.23 0.2 0.48 0.16 0.16

Average 0.25 0.14 0.29 0.16 0.24 0.15 0.26 0.14 0.24 0.14 0.24 0.21 0.23 0.35 0.21 0.21

Genetica

123

Author's personal copy

Table 3 continued

ST825 T 2318USSR T 2319USSR T 2320USSR TAM182 33ELS TAM88G 104

N CP N CP N CP N CP N CP N CP

AcalaUltima 0.34 0.05 0.31 0.18 0.45 0.02 0.21 0.11 0.21 0.09 0.24 0.18

Arkot9304b 0.35 0.02 0.37 0.16 0.48 0 0.28 0.09 0.23 0.07 0.25 0.16

Arkot9308 0.33 0.02 0.27 0.16 0.46 0 0.26 0.09 0.22 0.07 0.24 0.16

Arkot9314 0.34 0.16 0.3 0.3 0.44 0.14 0.22 0.16 0.2 0.14 0.24 0.23

Arkot9506 0.24 0.36 0.3 0.41 0.4 0.39 0.25 0.41 0.22 0.39 0.24 0.48

Arkot9513 0.18 0.09 0.39 0.14 0.41 0.07 0.42 0.16 0.37 0.14 0.38 0.23

Coker315 0.33 0.14 0.29 0.18 0.4 0.16 0.24 0.25 0.22 0.23 0.22 0.3

DP90 0.35 0.52 0.29 0.57 0.45 0.55 0.26 0.59 0.18 0.57 0.17 0.59

DE119xT1388F6F11 0.35 0.48 0.28 0.52 0.46 0.5 0.25 0.55 0.28 0.52 0.29 0.55

DPL90xT1388F6 0.34 0.48 0.28 0.61 0.45 0.5 0.2 0.55 0.17 0.52 0.23 0.57

DPL90xT239BC3F8 0.35 0.09 0.29 0.23 0.47 0.07 0.19 0.02 0.18 0 0.18 0.09

FM966 0.34 0.02 0.28 0.16 0.47 0.05 0.24 0.14 0.23 0.11 0.23 0.18

LA1110004okra su 0.33 0.27 0.33 0.52 0.45 0.57 0.25 0.52 0.22 0.05 0.2 0.11

LA1110017 0.32 0.52 0.3 0.73 0.47 0.75 0.21 0.77 0.19 0.48 0.22 0.5

M1388 2 0.36 0.16 0.34 0.5 0.46 0.55 0.27 0.5 0.25 0.07 0.24 0.05

M237 3 0.38 0.16 0.36 0.5 0.45 0.55 0.25 0.59 0.25 0.2 0.25 0.14

M239 7 0.35 0.14 0.3 0.48 0.47 0.52 0.25 0.48 0.25 0.09 0.2 0.02

M240 0.33 0.18 0.32 0.52 0.48 0.57 0.23 0.61 0.23 0.23 0.22 0.16

MD52ne 0.34 0.16 0.36 0.5 0.5 0.55 0.27 0.5 0.29 0.07 0.26 0.05

MD65 11 0.43 0.25 0.41 0.55 0.47 0.59 0.38 0.55 0.33 0.02 0.32 0.14

MD90ne 0.43 0.23 0.33 0.52 0.5 0.57 0.34 0.52 0.3 0 0.29 0.11

MD9ne 0.36 0.3 0.28 0.55 0.46 0.59 0.25 0.57 0.25 0.09 0.22 0.18

Miscot7803 52 0.34 0.16 0.32 0.5 0.49 0.55 0.22 0.5 0.2 0.07 0.22 0.05

Miscot7918 0.29 0.2 0.35 0.5 0.39 0.55 0.29 0.5 0.3 0.11 0.29 0.05

MiscotT8 27 0.36 0.14 0.27 0.52 0.45 0.52 0.2 0.48 0.21 0.09 0.26 0.07

PMHS26 0.35 0.16 0.33 0.5 0.42 0.55 0.25 0.5 0.26 0.07 0.25 0.05

Prymaid 0.37 0.16 0.29 0.5 0.48 0.55 0.22 0.5 0.2 0.07 0.24 0.05

PSC355 0.35 0.3 0.3 0.57 0.45 0.64 0.25 0.57 0.19 0.14 0.2 0.18

SG747 0.36 0.45 0.3 0.64 0.48 0.68 0.22 0.68 0.18 0.39 0.21 0.39

ST474 0.31 0.14 0.25 0.48 0.45 0.48 0.2 0.57 0.14 0.14 0.19 0.11

ST825 0 0 0.38 0.52 0.42 0.52 0.39 0.57 0.31 0.23 0.33 0.16

T 2318USSR 0.38 0.52 0 0 0.43 0.14 0.26 0.14 0.3 0.52 0.32 0.45

T 2319USSR 0.42 0.52 0.43 0.14 0 0 0.45 0.23 0.47 0.57 0.46 0.5

T 2320USSR 0.39 0.57 0.26 0.14 0.45 0.23 0 0 0.23 0.52 0.23 0.45

TAM182 33ELS 0.31 0.23 0.3 0.52 0.47 0.57 0.23 0.52 0 0 0.19 0.11

TAM88G 104 0.33 0.16 0.32 0.45 0.46 0.5 0.23 0.45 0.19 0.11 0 0

TAM96WD 18 0.31 0.25 0.31 0.5 0.42 0.52 0.33 0.5 0.25 0.16 0.25 0.09

TAM98D 99ne 0.37 0.32 0.36 0.55 0.53 0.61 0.3 0.55 0.28 0.16 0.29 0.16

TAMWD69s 0.33 0.23 0.26 0.52 0.46 0.55 0.22 0.52 0.2 0.18 0.23 0.07

TM 1 0.38 0.27 0.33 0.52 0.46 0.57 0.25 0.61 0.28 0.18 0.27 0.25

TTU077433 0.38 0.2 0.31 0.5 0.46 0.55 0.23 0.5 0.23 0.11 0.22 0.05

TTU0808161 0.34 0.25 0.3 0.5 0.45 0.45 0.21 0.5 0.2 0.16 0.21 0.09

Average 0.34 0.24 0.31 0.43 0.44 0.43 0.25 0.43 0.24 0.19 0.24 0.2

Genetica

123

Author's personal copy

Table 3 continued

TAM96WD 18 TAM98D 99ne TAMWD69s TM 1 TTU077433 TTU0808161

N CP N CP N CP N CP N CP N CP

AcalaUltima 0.27 0.02 0.28 0.07 0.18 0 0.25 0.02 0.16 0.02 0.17 0.16

Arkot9304b 0.34 0 0.3 0.05 0.25 0.02 0.34 0 0.29 0 0.28 0.14

Arkot9308 0.27 0 0.3 0.05 0.19 0.02 0.29 0 0.21 0 0.21 0.14

Arkot9314 0.28 0.14 0.27 0.18 0.18 0.16 0.28 0.14 0.2 0.14 0.2 0

Arkot9506 0.3 0.39 0.32 0.43 0.23 0.41 0.28 0.39 0.23 0.39 0.25 0.25

Arkot9513 0.36 0.07 0.36 0.11 0.36 0.09 0.42 0.07 0.39 0.07 0.38 0.2

Coker315 0.27 0.16 0.29 0.2 0.23 0.14 0.3 0.16 0.22 0.16 0.19 0.3

DP90 0.25 0.55 0.29 0.55 0.22 0.52 0.27 0.55 0.22 0.55 0.23 0.64

DE119xT1388F6F11 0.32 0.5 0.33 0.5 0.23 0.52 0.32 0.5 0.26 0.5 0.27 0.57

DPL90xT1388F6 0.29 0.5 0.32 0.5 0.18 0.48 0.28 0.5 0.21 0.5 0.2 0.57

DPL90xT239BC3F8 0.26 0.07 0.26 0.11 0.16 0.09 0.22 0.07 0.19 0.07 0.19 0.14

FM966 0.3 0.05 0.26 0.05 0.23 0.07 0.27 0.05 0.22 0.05 0.22 0.18

LA1110004okra su 0.28 0.16 0.3 0.16 0.23 0.18 0.3 0.23 0.23 0.07 0.22 0.16

LA1110017 0.27 0.5 0.28 0.36 0.18 0.52 0.27 0.5 0.2 0.48 0.19 0.55

M1388 2 0.28 0.09 0.35 0.16 0.24 0.11 0.28 0.25 0.22 0.05 0.23 0.09

M237 3 0.3 0.23 0.3 0.3 0.24 0.16 0.27 0.11 0.23 0.18 0.24 0.23

M239 7 0.28 0.11 0.31 0.18 0.21 0.09 0.29 0.23 0.24 0.07 0.22 0.11

M240 0.27 0.2 0.27 0.32 0.21 0.18 0.26 0.18 0.21 0.2 0.22 0.25

MD52ne 0.35 0.09 0.29 0.16 0.3 0.11 0.32 0.25 0.3 0.05 0.26 0.09

MD65 11 0.39 0.18 0.44 0.18 0.36 0.2 0.38 0.2 0.36 0.09 0.37 0.18

MD90ne 0.35 0.16 0.39 0.16 0.34 0.18 0.37 0.18 0.33 0.11 0.33 0.16

MD9ne 0.27 0.23 0.34 0.23 0.25 0.25 0.27 0.27 0.26 0.18 0.27 0.23

Miscot7803 52 0.28 0.09 0.28 0.16 0.21 0.11 0.28 0.25 0.24 0.05 0.2 0.09

Miscot7918 0.3 0.09 0.33 0.16 0.25 0.11 0.35 0.3 0.29 0 0.26 0.09

MiscotT8 27 0.29 0.11 0.3 0.18 0.17 0.14 0.28 0.27 0.22 0.07 0.22 0.11

PMHS26 0.32 0.09 0.26 0.16 0.24 0.11 0.3 0.25 0.24 0.05 0.24 0.09

Prymaid 0.29 0.09 0.3 0.16 0.2 0.11 0.29 0.25 0.18 0.05 0.17 0.09

PSC355 0.24 0.23 0.3 0.02 0.21 0.25 0.27 0.27 0.19 0.18 0.21 0.23

SG747 0.27 0.45 0.26 0.27 0.19 0.45 0.26 0.34 0.2 0.43 0.2 0.48

ST474 0.24 0.16 0.23 0.23 0.18 0.18 0.24 0.23 0.18 0.11 0.16 0.16

ST825 0.31 0.25 0.37 0.32 0.33 0.23 0.38 0.27 0.38 0.2 0.34 0.25

T 2318USSR 0.31 0.5 0.36 0.55 0.26 0.52 0.33 0.52 0.31 0.5 0.3 0.5

T 2319USSR 0.42 0.52 0.53 0.61 0.46 0.55 0.46 0.57 0.46 0.55 0.45 0.45

T 2320USSR 0.33 0.5 0.3 0.55 0.22 0.52 0.25 0.61 0.23 0.5 0.21 0.5

TAM182 33ELS 0.25 0.16 0.28 0.16 0.2 0.18 0.28 0.18 0.23 0.11 0.2 0.16

TAM88G 104 0.25 0.09 0.29 0.16 0.23 0.07 0.27 0.25 0.22 0.05 0.21 0.09

TAM96WD 18 0 0 0.34 0.2 0.24 0.11 0.32 0.34 0.28 0.09 0.26 0.11

TAM98D 99ne 0.34 0.2 0 0 0.28 0.23 0.34 0.3 0.3 0.16 0.28 0.2

TAMWD69s 0.24 0.11 0.28 0.23 0 0 0.27 0.27 0.19 0.11 0.18 0.14

TM 1 0.32 0.34 0.34 0.3 0.27 0.27 0 0 0.27 0.3 0.27 0.34

TTU077433 0.28 0.09 0.3 0.16 0.19 0.11 0.27 0.3 0 0 0.16 0.09

TTU0808161 0.26 0.11 0.28 0.2 0.18 0.14 0.27 0.34 0.16 0.09 0 0

Average 0.29 0.2 0.3 0.23 0.23 0.21 0.29 0.26 0.24 0.18 0.23 0.23

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Results

Chloroplast genome

We detected the presence of many simple sequence repeat

(SSR) motifs including many single nucleotide repeatmotif in chloroplast genome. The sequences were assem-

bled into large contigs for quality and length improvements

based on sequence homology using NCBI BLAST tool in alocal database for cpSSR analysis to minimize the redun-

dancy. Our sequence analysis revealed that the simple

repeats constituted the highest number of repeats within thechloroplast genome confirming the results of Xu et al.

(2012). We also found several indels and multiple SNPs in

the chloroplast genome which might be useful in devel-oping additional cytoplasmic markers.

We developed 17 cpSSR primer pairs from chloroplast

genome to detect the genetic variation in cytoplasmicgenome within a set of 42 improved Upland cotton

accessions based on the following criteria: (1) distributed

across whole chloroplast genome, (2) did not produce anyunambiguous PCR products, (3) had little risk of marker

size overlapping in PCR products and (4) markers hadabout 10 bp length of repeat motifs with potential to find

some polymorphism (Table 1). However, we discarded

results of three primer pairs (cpSSR 23, cpSSR 26 andcpSSR 30) from our result analysis because they did not

fulfill some of the above criteria.

Fourteen cpSSR primer pairs generated more than onefragments ranging from 2 to 8 amplicons/primer pair. The

primer pairs generated a total of 55 polymorphic SSR

markers ranging in amplicon sizes of 112–370 bp with anaverage of about five amplicons per primer pair (Table 2;

Supplementary Table 1). The PIC value for cpSSR markers

varied from 0 to 0.35 with an average of 0.09 and 58 %SSR markers were polymorphic (Table 2; Supplementary

Table 1). The most informative cpSSR marker was

SSRCP40_214 contributing the highest PIC value of 0.35(Supplementary Table 1). The frequency of the major

allele/cpSSR marker varied from 0.65 to 1. Some of the

cpSSR primer pairs amplified rare bands in some specificlines. For example, cpSSR20_257 had a unique band of

257 fragment size in the lines of T-2318 (USSR), T-2319

(USSR) and T-2320 (USSR), lines from USSR originsuggesting a similar source of maternal parent. However,

cpSSR04 had a fragment of 230 bp present only in

T2320USSR suggesting introgression of a different sourceof maternal cytoplasm in its origin than other USSR cotton

lines. Also cpSSR21_308 had a unique band of 308 frag-

ment size in T-2318 (USSR) and T-2320 (USSR) lines.Preliminary results revealed that cpSSR 27 primer pair

produced a unique band of 367 fragment size in Pima 3-79,

T-2318 (USSR), T-2319 (USSR) and T-2320 (USSR)

suggesting the possibilities of some introgression of G.barbadense cytoplasm as maternal source during the

development of these lines (unpublished information).

The average coefficient of dissimilarity, estimating thegenetic distance among the 42 accessions based on the

cpSSR markers, varied from 0.14 to 0.53 with an overall

average of 0.22 (Table 3). However, the dissimilaritycoefficients of few lines such as T2318USSR,

T2319USSR, T2320USSR, LA1110017 and SG 747 werevery high ranging from 0.40 to 0.53 compared to the other

cotton lines (Table 3). We also observed that Arcot 9308

had a very high dissimilarity coefficient compared to otherArcot lines suggesting possibly a different source of

maternal parent in its origin, although these lines were

originated from the same breeders.The genetic distance in the phylogenetic estimation was

based on the dissimilarity coefficient of SSR makers

among the lines. The results from the phylogenetic analysisusing cpSSR markers grouped the relationship among the

42 cultivars into three broad groups (A, B, C) and seven

minor groups (G1 to G7) at a threshold level of aboutgenetic distance coefficient 0.55 in UPGMA clustering

(Fig. 1). Results revealed further that the cultivars more or

less tended to cluster within their breeding or geographicsources of origin suggesting possibly similar maternal

parental germplasms were used in developing these lines.

For example, G1 minor group at a threshold level of 19 %of genetic distance coefficient for UPGMA clustering had

three lines originated from Former Soviet Russia suggest-

ing similar source of maternal cytoplasm. The broad threegroups could further be subdivided into seven sub groups

(G1–G7) as per the phylogram. Thirty six of the total 42

lines (86 %) were grouped into C group at about 0.21 as thethreshold level for UPGMA clustering and these group

could be further classified under five minor clusters G3 to

G7 suggesting the presence of more genetic variation incytoplasm genome within these lines. About 52 % of the

cultivars were clustered in the minor group G6 at a dis-

imilarity coefficient of about 0.15. It is important to notethat Acala Ultima and T2320USSR lines were located at

the two extreme end of the UPGMA clustering suggesting

the maximum diversity existed in the maternal genomebetween these two lines.

Nuclear genome

We selected 56 nuclear SSR primer pair based on the

following specific criteria: (1) they are associated withsome important fiber QTLs as per previous published

information (Abdurakhmonov et al. 2008, 2009; Guo et al.

1997; Qin et al. 2008; Wu et al. 2009; Zhang et al. 2013;

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Fang et al. 2013), (2) they are located to different chro-

mosomes covering most part of the genome, (3) they pro-duced very clear reproducible PCR band for scoring and

the marker represented at least at the 5 % allele frequency

threshold for the total data set without any rare or uniqueband in the lines (Abdurakhmonov et al. 2008, 2009; Khan

et al. 2009; Lacape et al. 2007; Tyagi et al. 2014). Our

results showed 75 % of these primer pairs were polymor-phic. The PIC values of the primer pairs ranged from 0 to

0.38 with an average PIC value of 0.14 (Table 2; Supple-

mentary Table 2). BNL 0569_143 had the highest PICvalue of 0.38. Fifty-six nuclear SSR primer pairs produced

1–10 fragments with an average of about four amplicons/

primer pair ranging in fragment sizes of 100–371 bp. Themajor allele frequency ranged from 0.50 to 1.00 with an

average of 0.88 (Table 3). Sixty-six percent of the nuclear

SSR markers had a frequency of higher than 0.90 for themajor allele. Results from coefficient of dissimilarity based

on nuclear SSR profile index estimating the genetic dis-

tance of 42 accessions varied 0.22–0.44 with an overallaverage of 0.27 (Table 3). T 2319 USSR line had the

highest genetic dissimilarity coefficient of 0.44. Arcot 513,

MD 6511 and ST 825 had genetic dissimilarity coefficientsof 0.37, 0.36 and 0.34, respectively, from other lines.

The dendrogram based on genetic distance coefficient

classified 42 cotton lines into four major groups (A, B, Cand D) and six minor groups (G1–G6) considering a

threshold level at 35 % level based on nuclear SSR profile

(Fig. 2). The results revealed that the G6 minor group

contains 34 out of 42 lines (81 %) at a threshold level ofgenetic distance coefficient 0.27. T2319USSR and Acala

Ultima were located at the two extreme end of the den-

drogram suggesting the presence of maximum geneticdistance between these two lines in the nuclear genome. It

is interesting to note that some of the individual line

showed distinct differences in the genetic profile betweenmaternal and paternal genome based on the dendrogram

position. For example, T2320USSR, a line at the extreme

end of the cpSSR dendrogram, clustered with majorityother lines in G6 minor groups of nuclear SSR dendrogram

suggesting the presence distinct difference between the

paternal and maternal genome in the origin of this line.However, the reader must be aware that most the nuclear

SSR markers were pre-selected which might not be dis-

tributed at random across the genome and might have someeffects on the outcome of the results.

Discussion

Genetic variation for desirable alleles and the accuratecharacterization of the variability among breeding lines are

the foundation for any successful breeding program.

Complete cotton chloroplast genome sequences provided avaluable source to identify and use chloroplast specific

SSR markers in this study (Lee et al. 2006; Ibrahim et al.

Fig. 1 Genetic relationshipamong the Upland cotton linesbased on cpSSR markers

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2006; Xu et al. 2012). Recently, the only other study

reported on the use of chloroplast specific 75 SSR markersusing a similar strategy to study genetic diversity within

different species of Gossypium accessions to understand

cotton phylogeny and its evolution. (Li et al. 2014). Nor-mally, it is difficult to find variation in chloroplast genome

due to the low mutation rate. However, chloroplast

microsatellites, or simple sequence repeats, detect higherlevels of polymorphism and conserved primers for the

amplification of chloroplast microsatellites have been used

for genetic studies in conifers (Vendramin et al. 1996),gramineae (Provan et al. 2004) and dicotyledons (Weising

and Gardner 1999).In principle, mutation rates for length variation in

microsatellites have been found to be higher than point

mutations rates (Li et al. 2002). This could result in thesame genetic state of individuals in two different

microsatellite lineages evolving through two different

independent mutational events, an incident commonlyknown as homoplasy. Homoplasy within CPSSRs has been

considered in some cases as a potential problem for its use

as a genetic marker in population studies (Provan et al.2001). However, such effect of homoplasy in another

similar study was considered as moderate and disregarded

its potential to confound the results in genetic study(Cuenca et al. 2003). Therefore, we should be aware of

some limitations in the studies of genetic variation using

cpSSR markers such as: (1) the presence of sequences

differences in the similar size of amplicons (i.e., anamplicon size homoplasy) between the genotypes (Navas-

cues and Emerson 2005; Wheeler et al. 2014), (2) some-

times occurrence of bi-parental inheritance leading toheteroplasmy in some species (Hansen et al. 2007), and (3)

cytoplasmic introgression from another species due to

interspecific hybridization of the studied taxa (Lee et al.1998; Provan et al. 2001; Currat et al. 2008; Ebert and

Peakall 2009, Wheeler et al. 2014). With the continuous

declining costs and rapid development of the sequencingtechnologies some of these limitations could be overcome

by more detail analysis of genetic results using sequencingmethods.

Our primary objective in this paper was to study the

genetic diversity in cytoplasmic genome within 42improved Upland improved cotton lines (G. hirsutum) from

diverse genetic backgrounds. Several studies suggested that

recent cotton yield stagnation, declining fiber quality, aswell as increasing genetic vulnerability to biotic and abiotic

stresses are primarily due to narrow genetic base in the

nuclear genome of Upland cotton. This could be attributedto over reliance on crosses among closely-related elite

domesticated genotypes or reselection within existing cul-

tivars for high yield and superior fiber quality in cottonbreeding program (Van Esbroeck et al. 1999). However,

there is a critical need to study the genetic diversity within

Fig. 2 Genetic relationshipamong the Upland cotton linesbased on nuclear SSR markers

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the cytoplasmic genome of Upland cotton because almost

95 % of all cotton produced around the world is accountedfor by Upland cotton (G. hirsutum) because of its improved

agronomic characteristics including high yield.

Chloroplasts replicate independently of nuclear divisionwithout any genomic recombination, contrary to nuclear

genomes where normally recombination provided the

opportunity to create new variation. Normally, chloroplastsare inherited uniparentally from maternal parent in most of

the angiosperm (Sears 1980; Whatley 1982; Muir andFilatov 2007). Wendel (1989) documented the maternal

inheritance of chloroplast genome in cotton suggesting that

an A genome diploid with a chloroplast genome similar toG. arboreum and G. harbaceum was the possible donor of

the cytoplasm for all of the tetraploid cotton species in

evolution. These reports justify the use of cpSSR markersas the diagnostic tool representing the cytoplasmic genome

in cotton in the study of genetic variation.

It has been reported that the genetic variation in cyto-plasmic genome caused significant differences in several

phenotypes of maize, wheat, rice, potato and barley (Scotti

et al. 2004; Tao et al. 2004; Goloenko et al. 2002; Rao andFleming 1978; Allen et al. 2005; Leigh et al. 2013). Pre-

vious studies documented that the cytoplasm had a sig-

nificant effect on important QTLs and phenotypes in cotton(Han et al. 2007; Karaca et al. 2004). Cytoplasm has been

reported to have significant genetic effects on boll number,

lint percentage and fiber length in tetraploid cotton (Hanet al. 2007). Our previous study recorded that a plastid

mutant caused in the production of yellow virescent leaf in

young cotton seedlings (Karaca et al. 2004). A recentreview on 99 whole chloroplast genome from different

plant species using GenBank data confirmed the abundant

presence of hypervariable cpSSRs in the noncodingcpDNAs of plants with a variation frequency of 86 (median

value) in 81 vascular plants justifying the merit of cpSSR

as a tool in genetic studies (Ebert and Peakall 2009).Development of microsatellite or SSR (simple sequence

repeats) markers specific to chloroplast genome provides a

tool for analysis of phylogenetic relationships, cytoplasmicdiversity, inheritance of plastids, determination of precise

direction of cross between different genotype and moni-

toring gene flow and to study the history of domestication(Arroyo-Garcia et al. 2002; Bowers et al. 1999; Provan

2000; Provan et al. 2001).

Previous reports on 13 Gossypium species cotton plas-tome sequences including tetraploid cotton species docu-

mented the presence of large number of SSR loci including

the number of mononucleotide C 8 bp, dinucleotide C8 bp, trinucleotide C 9 bp, tetranucleotide C 12 bp, and

pentanucleotide C 15 bp (Lee et al. 2006; Xu et al. 2012).

They reported that different SSRs motifs were present indifferent frequencies with mononucleotide repeat motif as

the most abundant type ranging from 50 to 58 %. Among

the mononucleotides A or T was present as the predomi-nant type covering 95–97 % of the mononucleotide repeat

motifs. Li et al. (2014) obtained 100 mononucleotide and

16 dinucleotide cpSSRs, with lengths of 8–16 and 10–14nt, respectively, from 12.6 kb chloroplast region.

Comparing pair wise sequences of polymorphic SSR

loci among 13 chloroplast genomes revealed great varia-tion in sequences ranging from a minimum 2 loci (G.

barbadense race yuanmou and G. barbadense racekniyuam) to more than 115 loci (between tetraploid spe-

cies and D-genome species). The previous study showed

the presence of the most of the direct repeats in plastidsequences within intergenic spacer regions, intron

sequences and ycf2, an essential hypothetical chloroplast

gene and a 72 bp-long direct repeat was present in thepsaA and psaB genes, whereas a 34-bp forward repeat

was present within the rrn23 gene and a 32 bp-long direct

repeat in two serine transfer-RNA (trnS) genes that rec-ognize different codons; trnS-GCU and trnS-UGA (Xu

et al. 2012). Our analysis on cotton plastid sequences

further confirmed this report and provided us a scope todevelop chloroplast specific SSR markers in cotton using

following the overall method of our previous study in the

discovery of cotton EST-SSR using a cost-effective datamining strategy from public databases (Qureshi et al.

2004).

We developed 17 cpSSR primer pairs producing on anaverage four amplicons ranging in size 112–383 bp with

average major allele frequency 0.93, and PIC value 0.09

ranging from 0 to 0.35 with 58 % polymorphic in G. hir-sutum (Table 2). Li et al. (2014) reported the 66 % of

cpSSR were polymorphic and PIC value ranged from 0.11

to 0.88 with an average of 0.60 in Gossypium species.The multiple amplicons from most of the individual

cpSSR primer pairs suggested the presence of duplicated

events in the chloroplast genome. However, it was not clearjust from the amplicon sizes whether the size variation by

the cpSSR markers were due to only SSR length variation

or some other changes in sequences in our study. However,the signature stutter bands associated with the most of the

SSR markers in ABI gel system suggested the potential of

these markers as SSR type. We observed the presence ofdeletion/insertion and SNPs in chloroplast genome of the

tetraplod cotton during our comparative sequence analysis.

Xu et al. (2012) reported that 1–3 bp and 5 bp indels werethe primary source of SSR polymorphism in Gossypium

species. BLAST results of our sequence analysis further

confirmed the presence of such indels in the tetraploidcotton plastome sequences. In a preliminary study, we also

observed that primers specific to these indels can also be

used as a useful tool to detect genetic diversity in thecytoplasm of the tetraploid cotton.

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The original collection of the sequences from cotton

chloroplast sequences using NCBI GenBank and ourBLAST search results showed that these primers pairs were

specific to the chloroplast sequences. Fifty-eight percent of

cpSSR markers were polymorphic among these set of 42Upland cotton lines. It is noteworthy to mention that pre-

vious study based on RFLP markers indicated extremely

low level of variation in plastid genome of tetraploid cottonsuggesting the merit of the cpSSR markers (Wendel 1989).

Normally SSR markers are highly polymorphic and thehigh level of polymorphism arises from the number of

repeat units probably due to slipped-strand mis-pairing

during replication of the SSRs by the DNA polymarase(Erisen 1999; Levinson and Gutman 1987). Therefore, SSR

loci often evolved by insertions or deletions of one or more

repeat elements thereby increasing or decreasing in thelength of the repeat units. Previous studies in wheat, pine,

and other species documented that in spite of the low

mutation rate in chloroplast DNA relative to nuclear DNA,the hyper-variable nature of cpSSR make them an ideal

tool for genetic analysis of cytoplasmic genome (Leigh

et al. 2013; Cato and Richardson 1996; Xu et al. 2012;Ebert and Peakall 2009).

The PIC value provides the estimation on the informa-

tiveness of individual marker. A comparative analysis ofPIC values, an estimation of the probability of a poly-

morphism between two random samples of the germplasm

(Chao et al. 2009), based on cpSSR marker versus nuclearSSR marker (average cpSSR PIC value 0.08 versus nuclear

SSR PIC value 0.13) revealed that cpSSR markers were

more conserved compared to the nuclear SSR markers. Arecent study with 120 genome wide nuclear SSR markers

among a set of 381 accessions comprising 378 Upland

(Gossypium hirsutum L.) and 3 G. barbadense L. acces-sions of the United States estimated the average PIC value

was 0.17 (Tyagi et al. 2014), whereas some other studies on

similar investigations using nuclear SSR markers estimatedaverage PIC value for cotton SSRs could range from 0.122

(Abdurakhmonov et al. 2008, 2011) to 0.80 (Zhang et al.

2011). Our results revealed that the major allele frequencywas higher in chloroplast genome compared to the nuclear

genome among these lines suggesting the narrow genetic

diversity among maternal parents compared to the nucleargenome originating from the fertilization and recombina-

tion of both maternal and paternal parents. However, our

pre-selection of the nuclear SSR markers might haveeliminated some informative markers that could have some

influence on the nuclear SSR results.

With a reasonable level of confidence results revealedthat low to moderate level of genetic diversity existed in

both nuclear and cytoplasm genome among these cotton

lines. The overall results of the genetic diversity based onnuclear SSR markers are concordant with previous studies

(Hinze et al. 2012; Zhang et al. 2005; Sapkal et al. 2011).

Since chloroplast SSR markers are haploid in nature andtransmitted maternally in cotton (Cronn et al. 2002), as

expected the results from cpSSR showed a different pattern

of variation in cytoplasmic compared to the variation innuclear genome produced by recombination of both

maternal and paternal parents (Provan and Campanella

2003). Previous study also documented that phylogenies ofchloroplast and nuclear markers differ significantly within

Gossypium sp. (Cronn et al. 2002). Genetic variation incotton cytoplasm is maintained normally by gene flow

through egg cells, where as diversity in the nuclear genome

is determined by the gene flow through pollen and eggcells. Our results on genetic diversity in nuclear and

cytoplasmic genome can perhaps be used to determine the

pedigree history and selection of appropriate parents tomaximize the benefits at both nuclear and cytoplasmic

genomes.

The dissimilarity coefficient represents how diversegenetic resources were used in creating these lines. Results

based on cpSSR dissimilarity coefficient average ranged

from 0.14 to 0.53 with an overall average of 0.22, whereasthe dissimilarity coefficient of nuclear SSR markers varied

from 0.22 to 0.44 with an overall average of 0.27 sup-

porting the idea that chloroplast genome are more con-served compared to the nuclear genome in cotton among

this set of accessions. Bertini et al. (2006) estimated

genetic distance ranging from 0.00 to 0.71 with average of0.40 based on the coefficient of dissimilarity among 53

Upland cultivars using nuclear SSR markers. However,

Tyagi et al. (2014) estimated that the average genetic dis-tance among a set of 378 G. hirsutum accessions was lower

(0.195) comparative to our results using nuclear SSR

markers. Our result also showed all of the accessionsgrouped under the threshold value of 0.25 dissimilarity

coefficient of cpSSR, whereas around 73 % of these

accessions were clustered under the same threshold valueof dissimilarity coefficient in nuclear SSR dendrogram,

suggesting a more conserved and narrow base in cotton

cytoplasmic genome compared to the nuclear genomeamong these sets of accessions.

Results from the cpSSR dendrogram showed that the

accessions in some cases from the similar breeding sourcesor geographic locations clustered together, suggesting the

use of a similar in-house gene pool as the maternal parents

in the breeding program. For example, G1 minor group at athreshold level of 0.19 dissimilarity coefficient in UPGMA

clustering grouped three lines (T2319 USSR, T2318 USSR

and T2320 USSR) originated from Former Soviet Russia,suggesting the potential of similar sources of maternal

cytoplasm from the same geographic location. This type of

information will be more valuable when specific pedigreeinformation is available; however, we should take into

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account under the consideration of evolutionary inferences

(Wheeler et al. 2014). It is important to note that T2319USSR, T2318 USSR and T2320 USSR were separated in

different clade based on 0.45, 0.3 and 0.23 dissimilarity

coefficient, respectively, in the nuclear SSR dendrogram. Itis thus tempting to speculate about the pedigree of these

materials that these lines originated in USSR using a

similar source of maternal parents at USSR. However,since their introduction in USA, breeders used these

materials as maternal parents in crosses with other Uplandcotton lines as paternal parents creating genetic variation

among these lines.

We also observed that some accessions from differentsources had similar genetic background in the cytoplasmic

genome. For example, it is interesting to note that Acalla

Ultima and LA110017 clustered together in a group verydistant from other cultivars, suggesting genetically these

two lines are similar in cytoplasmic genome, but very

diverse from other accessions as per the result of cpSSRdendrogram. Acala cotton was developed for high fiber

qualities by interspecific introgression from crosses of G

arboreum, G. thurberi and G. hirsutum using triple hybridbreeding method (Smith and Cothren 1999; Zhang et al.

2005). Our result is congruent with a previous study on

genetic diversity using AFLP markers (Badigannavar et al.2012). They reported that most of the Louisiana genotypes

are congruent with the appearance of Acala-type genotypes

in their pedigree. Results also showed that the AcalaUltima and LA110017 lines were distantly separated based

on genetic distance in nuclear SSR dendrogram. Acala

lines were used in the USA cotton breeding program pri-marily for the improvement fiber qualities. On the other

hand, breeders used other Upland cotton lines to improve

yield and wide adaptation in their programs. These twodivergent selection pressures might have caused by the use

of diverse genetic sources as paternal parents in the

breeding program, thus separated these two lines distantlyin nuclear SSR dendrogram.

It is interesting to note that our results on genetic rela-

tionships are more or less congruent with some of thepedigree histories of the accessions. For example, TTU

0774-3-3 ranked genetically very close to Acala Ultima as

per both cpSSR and nuclear SSR dendrogram results. TTU0774-3-3 was developed from a cross of TTU 202-1107B

with Acala 1517-95 for improved fiber quality and well

adaptability in Texas High Plains (Bechere et al. 2007).DPL90XT1338F6n and DPL90 were grouped in the same

clade on CRSSR dendogram, but differ distinctly in nuclear

SSR dendrogram suggesting DPL90 was used as maternalparent in the cross of DPL90XT1338F6 genetic similarity

among the accessions originating from different breeding

programs shows that different breeding programs in theUSA are targeted to meet some specific regional needs;

however, germplasm exchange and use of some common

elite cultivars especially in the selection of some commontraits as parents was not uncommon among different

breeding programs (Tyagi et al. 2014).

It is tempting to speculate that perhaps the differentmolecular identity of the conserved chloroplast genome

complements the dynamic changes in nuclear genome

through the union of maternal and paternal gametes andoffers a scope of phenotypic plasticity in evolution main-

taining its own genetic niche. It will be interesting toinvestigate if any of these cpSSR markers are associated

with important fiber and agronomic traits. This may shed

some new light on the importance of the cytoplasmicgenome associated with those traits and the use of these

markers for marker assisted selection program in

improvement of the traits. We are currently investigatingthis aspect.

In summary, this research is important from several

perspectives. We detected a set of cytoplasm genomespecific SSR primer pairs by using a cost-effective data

mining strategy. We reported for the first time the genetic

diversity in the cytoplasmic genome within a set ofimproved Upland cotton accessions. Results revealed that

the genetic diversity in the cytoplasmic genome is narrow

compared to the nuclear genome within this set of Uplandcotton accessions. We also observed that genetic relation-

ship among the lines showed a different pattern of variation

in cytoplasmic compared to the nuclear genome. Thecomparative results of this research on the variation of

cytoplasmic and nuclear genome of a set of Upland cotton

accessions will complement to understand the geneticdiversity and gene flow within this set of improved Upland

cotton accessions. This will help breeders develop a

breeding strategy to maximize the effects of geneticdiversity in the genetic improvement of Upland cotton.

Acknowledgments The authors thank the Office of InternationalResearch Programs, U. S. Department of Agriculture (USDA) forproviding funds for this study under research grant UZB2-31016-TA-09 and U.S. Civilian Research & Development Foundation (CRDF)and Cotton Incorporated, USA. We thank the Academy of Sciences ofUzbekistan for supporting this joint study within USDA-Uzbekistancooperative programs. Mention of trade names or commercial prod-ucts in this article is solely for the purpose of providing specificinformation and does not imply recommendation or endorsement bythe U. S. Department of Agriculture. The U. S. Department ofAgriculture is equal opportunity provider and employer. Weacknowledge joint publication of USDA/ARS, and MississippiAgricultural and Forestry Experiment Station, approved for publica-tion as Journal Article of the Mississippi Agricultural and ForestryExperiment Station. We thank all of the public and private cottonbreeders who provided seeds for this study. We would specificallylike to acknowledge the help of Dr. Jack C. McCarty, Dr. WayneSmith, Dr. Bill Meredith, Dr. Gerald O. Myers, Dr. Ted Wallace, Dr.Fred Bourland, Dr. Jack Jones, and Dr. Dick L. Auld for their help inthis study by providing seeds of their released germplasm. Withouttheir help and support we could not accomplished the goals of this

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research project. We also thank Dr. B. Todd Campbell and Dr.Mauricio Ulloa for their help in reviewing the manuscript.

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