Disease Progress Curve Parameters Helpto Characterise the Types of Resistance to LateBlight Segregating in Cultivated Potato

Sylvie Marhadour & Roland Pellé &

Jean-Marc Abiven & Frédérique Aurousseau &

Hervé Dubreuil & Yves Le Hingrat &Jean-Eric Chauvin

Received: 5 October 2010 /Accepted: 24 February 2013# EAPR 2013

Abstract To decrease the environmental impact of treatments against late blightcaused by Phytophthora infestans on potato, plant genetic resistance is a keystonein developing new culture strategies. Nonspecific resistance to late blight is acomplex trait which is difficult to evaluate, while selection is both difficult and timeconsuming. However, we consider it is important to select for this type of resistanceas it is a promising way to achieve durable resistance. In this study, parametersderived from disease progress curves (DPCs) were used to characterise the types ofresistance among individuals of three tetraploid full-sib families named G1, B2, andK2. These families were composed of 280 (G1), 280 (B2), and 150 (K2) genotypes.Our aim was to avoid visual inspection of 5,710 DPCs and to identify genotypesexhibiting stable resistance. We used three parameters: the slope of the DPC, the dateof appearance of the first symptoms in the tested genotypes compared with a

Potato ResearchDOI 10.1007/s11540-013-9233-1

S. Marhadour (*)FN3PT, 43-45 rue de Naples, 75008 Paris, Francee-mail: sylvie.marhadour@fnpppt.fr

S. Marhadour : R. Pellé : J.-E. ChauvinINRA UMR 1349 IGEPP, Keraiber, 29260 Ploudaniel, France

J.-M. AbivenStation de Création Variétale, Bretagne Plants, Kerloï, 29260 Ploudaniel, France

F. AurousseauStation de recherche du Comité Nord, 76110 Bretteville du Grand Caux, France

H. DubreuilGROCEP, Station de Lavergne, 87370 Laurière, France

Y. Le HingratFN3PT, Roudouhir, 29460 Hanvec, France

susceptible standard, and the relative area under the disease progress curve(rAUDPC). Using an appropriate threshold for each parameter, we demonstrated thatit is possible to classify the response of each genotype in one of the followingcategories: susceptible, non-specific resistance, specific resistance, non-specific re-sistance plus specific resistance (or specific resistance not overcome). Data wereobtained each year from 2005 to 2007 under conditions of natural infection.According to the parameters analysed, non-specific resistance and specific resistancesegregated in the families. The year effect was more than double the family effect forrAUDPC. Empirical adjustment of threshold values in a subsample of the testedgenotypes led to an increase in the effectiveness of our classification method.Calculated classification enabled detection of stable genotypes in each family. Theimpact of the year effect differed with the family. In the G1 family, the distribution ofgenotypes in each category was relatively stable over the 3 years, whereas in K2, theproportion of genotypes demonstrating specific resistance alone increased, particu-larly in 2007. In the B2 family, the proportion of genotypes in the non-specificresistance category decreased from 40% to 15% from 2005 to 2006, and thenremained stable in 2007. The heritabilities of the parameters ranged from 61% to96% depending on the family and on the parameter concerned.

Keywords AUDPC . Field test . Non-specific resistance . Phytophthora infestans .

Population A . Solanum tuberosum . Specific resistance . Tetraploid potato . Year effect

Introduction

Late blight caused by Phytophthora infestans (Mont.) de Bary is the most devastatingdisease in potato, leading to yield losses and problems of tuber quality. Late blight iscurrently controlled by chemicals which are costly for producers and environmentallyunfriendly (reviewed in Haverkort et al. (2008)). Risks of emergence of resistance tofungicides are also increasing.

To manage this disease, genetic resistance can be considered as an additional tool,along with modelling the risks of epidemic outbreak, crop rotations, among others. Inpotato, two main types of resistance to P. infestans have been described based on thebehaviour of Solanum demissum: general or field resistance, further referred to as non-specific resistance (RNS), resulting from the action of many genes, and race-specificresistance (RS) based on the gene for gene relationship (Wastie 1991). The dichotomybetween both types of resistance is, as explained in Umaerus and Umaerus (1994), aworking concept and can be considered an oversimplification. It can also be consideredas partially incorrect, especially in the light of results in molecular genetics (Tan et al.2008). Both types of resistance coexist and RNS is known to be able to lead to a veryhigh level of resistance provided that the combination of QTLs is adequate, whereas RScan result in intermediate levels of resistance (Lindhout 2002). The picture is even morecomplicated when the effect of maturity on late blight resistance is added. It is generallyconsidered difficult to combine a high level of resistance with early maturing type(Umaerus and Umaerus 1994); however, the correlation is not complete (Visker et al.2004). QTLs for late blight resistance that are independent of maturity have beendescribed, as recently reviewed in a meta-QTL analysis (Danan et al. 2011).

Potato Research

Terminology is sometimes confusing and depends on the area of interest of theauthors (genetics, epidemiology, etc.). RNS reduces the progress of the epidemic overtime without isolate specificity (Umaerus and Umaerus 1994). As the phenotypeobserved is mostly quantitative, the term polygenic resistance is used too (Lindhout2002) and because resistance is not complete, the term partial resistance is also used(Van der Plank 1963). When an R gene is efficient, the phenotype observed iscomplete absence of symptoms. In this case, RS is also described as qualitativeresistance. In this article, we use RS and RNS, without a priori judgement of theheredity of the resistances but rather by relying on phenotypes that can be observed ina breeding nursery and scored using a disease severity index.

Because P. infestans is able to relatively rapidly overcome R genes, none of thenumerous R genes identified up to now has been effective for a very long time whenused alone or in combination (reviewed in Fry (2008)). However, even if R geneshave been defeated, some still have an effect by delaying the start of the epidemic,which is of economic importance. It has been suggested that defeated R genes lead toa residual level of RNS (Stewart et al. 2003). RNS is believed to be more durable thanspecific resistance (Van der Plank 1971); however, RNS is not sufficient to solve theproblem of late blight when used alone (Fry 2008). Moreover, the efficiency of Rgenes could be preserved if they were used in combination with RNS factors. Forexample, in the Brassica napus/Laeptosphaeria maculans pathosystem, RNS wasshown to increase the durability of RS when the two were combined (Brun et al.2010). In the Capsicum annuum/Potato virus Y (PVY) pathosystem, the pvr23 genewas defeated when introduced in a susceptible background whereas it remainedefficient in a background with resistance QTLs (Palloix et al. 2009).

Selection for RNS is not easy (Wastie 1991). This may explain why RNS to lateblight is not very common in modern cultivars. One way to increase the efficiency ofthe breeding process for such a complex trait is to use molecular markers linked toresistance factors (Lindhout 2002), especially when RNS needs to be combined withRS to achieve increased durability. In such a case, it is not easy to identify genotypeson the basis of the phenotype alone that have an additional and valuable level of RNSin combination with an effective R gene unless a virulent race is used in controlledconditions. It requires as an important step, the correct characterization of the type ofresistance phenotypes that segregate in the breeding material concerned.

The type of resistance can be characterised using Δa and Δt parameters asdescribed by Andrivon et al. (2006). These parameters, which are calculated fromtraditional disease progress curves (DPCs), can help to handle a lot of data, becausethey avoid the inspection of thousands of DPCs separately. They also provideadditional information to the relative area under the disease progress curve(rAUDPC) concerning resistance which enables the classification of the genotypesinto four categories: susceptible (S), RS, RNS, both RNS and RS (or RS notovercome).

In this paper, we describe how we used Δa and Δt parameters to characterise thetypes of resistance present in individuals belonging to three tetraploid full-sib familiessegregating for late blight resistance. We confirm that threshold values had to beadapted for classification of the experimental material. We show how this methodhelped us to assess the effect of the year on the type of resistance observed in ourexperiments and to detect genotypes with a stable resistant phenotype that remained

Potato Research

stable over the 3 years of the experiment. Heritabilities of these parameters werecalculated.

Material and Methods

Three full-sib families were used: G1, B2, and K2. These families resulted fromcontrolled crosses between three late blight resistant breeding clones from INRAselection and three different susceptible varieties, i.e. INRA89T117.10×Florette,INRA89T123.3×Berber, and INRA92T120.16×Europa, respectively (Fig. 1).According to the Euroblight database, Berber does not carry any R gene controllinglate blight, whereas the status of R genes for Europa and Florette is “unknown”(http://www.euroblight.net/EuroBlight.asp). Resistant genotypes originate from twogenotypes of population A released by CIP in the 1980s and introduced in the INRAin vitro collection in 1985 (Anonymous 1989; Landeo et al. 1995), i.e., CFQ69.1 and65ZA5 (Fig. 1). The original crosses using these genotypes were performed in 1987or 1988 depending on the family. Material was sown and multiplied between 1989and 1992. A very light selection was performed in the multiplication plots at the sametime, mainly for tuber shape, but independently of selection for late blight resistance.Selection for late blight resistance was performed as follows: a progeny test wasperformed in 1991 or 1993 depending on the family. This test included 2×30genotypes. Twenty to 30 genotypes from each selected family were tested in anindividual test under natural infection conditions. The tests took place in Ploudaniel,in the western part of Brittany, France (oceanic conditions) during two successiveyears between 1992 and 1995 depending on the family. Only the most resistantgenotype were experimented the second year. Five plants per genotypes were eval-uated in each individual test.

Fig. 1 Relationships between the resistant parents INRA92T120.16, INRA89T117.10 and INRA89T123.3used in the study and origin of the K2, G1 and B2 families. Boxed genotypes were introduced frompopulation A released by CIP and were the source of the resistance to late blight

Potato Research

The K1, G1, and B2 families were clonally propagated starting from seedlings andthen evaluated in the field each year from 2005 to 2007 under natural infectionconditions. The maximum number of genotypes tested was 280 for G1 and B2families and 150 for the K2 family. The experiments took place in the same locationas describe above. Three replicates of each genotype were included in the trials inaddition to the parents of the families, Black’s differentials (R1 to R11) and standards(Bintje, Robijn, Desirée, Eden). Only two replicates of K2 individuals were tested in2005. Bintje was used as a spreader between the experimental rows. The experimentsagreed with the Euroblight requirements for a field test for foliage blight resistance(http://www.euroblight.net/EuroBlight.asp); however, some of the recommendedstandards were not included (Gloria, Eersteling, Escort and Alpha).

Thematurity of thematerial was judged to be late maturing by breeders who evaluatedeach genotype in multiplication plots. Each genotype included in the experimental plots(each containing 10 plants), was individually evaluated 10 times (13 times in 2007) usinga visual scale of foliage destruction adapted fromDowley et al. (1999). Potato seeds wereplanted in the first or second week of May. The first score was made 30 days afterplanting. Plants were evaluated twice a week during the peak of the epidemic.

Variance analyses were performed on rAUDPC values using the glm procedure inSAS software (SAS Institute Inc., Cary, NC, USA). The first model used was Xijk=μ+Yi+RjYi+Fk+Yi×Fk+GlFk+εijkwhere Yi is the effect of the year i, RjYi is the effect of thej repeat nested in year i, Fk is the effect of the family k, Yi×Fk is the interaction betweenyear i and family k, and GlFk is the effect of genotype l nested in family k. This modelwas used separately on families and parents. A second type of variance analysis wasperformed on each family independently using the following model: Xijk=μ+Yi+RiYi+Gk+Gk×Yi+εijk where Yi is the effect of the year i, RjYi is the effect of the j repeat nestedin year i, Gk is the effect of the genotype k, Gk×Yi is the interaction between year i andgenotype k. Means were calculated using the means option of the general linear modelprocedure.

The Δa and Δt parameters were calculated as explained in Andrivon et al. (2006)and are briefly recalled here. The DPC for each genotype is expressed as yi= f(t)where Yi is disease severity in genotype i and t is time. AUDPCs were calculatedusing the trapezoidal integration method and transformed into relative AUDPCs(rAUDPC (Fry 1978)). DPCs were then linearized by transforming data to Yi=log(yi/1−yi; transformed DPCs Yi=ai.t+bi).

Both parameters were then derived from the following equations:Δt ¼ t0i � t0s where t0i and t0s are the date of appearance of the first visible

symptoms on the tested genotype and on the standard susceptible genotype (Bintje),respectively

Δa ¼ ai � as where ai and as are the slopes of the transformed DPC for the testedgenotype and the standard susceptible genotype (Bintje), respectively.

Based on these two parameters, the resistance type can be postulated as explainedin Table 1.

The number of discrepancies between the type of resistance derived from thevisual inspection of DPCs and the classification were summed for each family andeach year. Visual inspection of the DPCs consisted of a careful observation of thecurves’ shapes. When the curve had a sigmoid shape close to the one of the cultivarBintje, i.e. a rapid increase starting from the very early beginning of the curve, the

Potato Research

genotype represented was considered S. When the curve had a sigmoid shape with adelayed beginning of the rapid increase, the genotype represented was considered RS.When the curve had a linear shape, the genotype was considered RNS. A curve veryclose to the abscise axis corresponded to a RS+RNS genotype (or RS not overcome).The total number of comparisons was 44 for each classification type.

The mean heritability of clones was estimated according to Bradshaw (2007):

H2 ¼ aσ2C

aσ2C þ σ2Cy

b þ σ2

where σ2c ; σ

2cy , σ2 are the variance components of the clones, the clone×year

interaction and residual, a is the number of years×the number of replicates, and bis the number of replicates. Variance components were estimated using theVARCOMP procedure. The year effect was considered as a fixed effect.

Results

1. The year effect was significant for rAUDPC and distribution of the rAUDPC inthe segregating families differed depending on the years.

All the differentials were infected each year, except R5 in 2006 and R9 which wasnever infected. The year effect was the most important effect and was more than twiceas important as the family effect, which came second (Table 2). The general mean ofrAUDPC was 0.24 in 2007, which was significantly higher than the means calculatedin 2005 (0.15) and 2006 (0.11).

Table 1 Resistance types deduced from rules for Δa and Δt parameters as derived from Andrivon et al.(2006)

Δt Δa Type of resistance Class of resistance type

≤3 ≥0.1 S (susceptible) 1

>3 ≥0.1 RS (race-specific resistance) 2

≤3 <0.1 RNS (non-specific resistance) 3

>3 <0.1 RS+RNS (or RS not overcome) 4

Table 2 Results of varianceanalysis on rAUDPC (R2=0.84)

Degrees of freedom Mean Square Pr>F

Model 718 0.14 <0.0001

Error 4,823 0.00

Year 2 6.73 <0.0001

Repeat (year) 6 0.02 0.0005

Family 2 3.17 <0.0001

Year×family 4 0.13 <0.0001

Genotype (family) 704 0.11 <0.0001

Potato Research

Considering rAUDPC means for each family, K2 exhibited the lowest rAUDPCwith a value of 0.11, whereas the means for B2 and G1 were 0.21 and 0.18,respectively. These differences were significant (P<0.05). The mean of this variablefor the susceptible parents was 0.37.

The interactions between year and family and the effect of genotype nested in familywere similar (Table 2). Despite the fact that the interaction was significant, the threefamilies displayed the same behaviour i.e. a general increase in the rAUDPCmeans wasobserved in 2007 (Fig. 2). Variability between individuals was significant. Varianceanalysis performed separately on each family showed that the most important effect wasalways the year effect, followed by the individual effect (data not shown).

In 2005, rAUDPC values were normally distributed in B2 but in 2006 and 2007their distributions were bimodal. In this family, an increase of the number ofgenotypes in the susceptible part of the distribution was observed in 2007 (Fig. 2).Bimodal distributions of rAUDPC were observed in G1 family and each year ofexperimentation (Fig. 2). Distributions of rAUDPC in the K2 family weremonomodal and characterised by a majority of genotypes in the classes correspond-ing to very low values of rAUDPC. This was true in 2005 and especially in 2006when 94 out of 150 genotypes were in the lowest class (Fig. 2). In 2007, intermediateclasses [0.15; 0.21] and [0.21; 0.27] were more represented.

2. Empirical adjustment of the Δt and Δa thresholds on a subset of genotypes.

As explained in Andrivon et al. (2006), threshold values of Δa and Δt parametersneed to be adjusted to the objectives of the study. Four sets of classification values(CL) were tested:

– CL1: threshold equal to 0 for Δa and Δt,– CL2: threshold equal to 3 instead of 0 for Δt (not shown),– CL3: threshold equal to 0.1 instead of 0 for Δa (not shown),– CL4: threshold equal to 3 instead of 0 for Δt and threshold equal to 0.1 instead of

0 for Δa.

A sub-sample of each segregating family was used to check the classification madeusing the different thresholds. The sub-sample was chosen as follows: resistantgenotypes had been previously selected in each family to be used in crosses on thebasis of their phenotypic value. This choice was made by carefully inspecting theDPCs constructed for each replicate and each year of experiment. The number ofgenotypes was five for the G1 and B2 families and six for the K2 family except in2005 (3 genotypes). A value of 3 was chosen for Δt because it corresponded to half ofthe mean interval between successive notations. A value of 0.1 was chosen for Δabecause it corresponded to the standard deviation calculated using three replicates ofeach individual.

The number of discrepancies between resistance types deduced from visual in-spection of the shape of the DPCs and those determined using the Δa and Δtparameters differed between the families and the threshold used for the two param-eters (Table 3). When the average level of resistance of family members was veryhigh, e.g. the K2 family, all the classification methods were in agreement withconclusions from visual inspection. In this family, one genotype (L8) was classifiedas RS+RNS (or RS not overcome) in 2006 (rAUDPC=0.03, Δa=−0.34, and Δt=14)

Potato Research

0

10

20

30

40

50

60

70

[0.02; 0.06]

[0.07; 0.11]

[0.12; 0.16]

[0.17; 0.21]

[0.22; 0.26]

[0.27; 0.31]

[0.32; 0.36]

[0.37; 0.41]

[0.42; 0.46]

[0.47; 0.51]

[0.52; 0.57]

Fre

quen

cies

rAUDPC classes

2005

2006

2007

Resistant parent Susceptible parent

0

10

20

30

40

50

60

70

80

90

[-0.03; 0.02]

[0.03; 0.08]

[0.15; 0.20]

[0.21; 0.26]

[0.27; 0.32]

[0.33; 0.38]

[0.39; 0.44]

[0.45; 0.50]

[0.51; 0.57]

Fre

quen

cies

rAUDPC classes

2005

2006

2007

Resistant parent Susceptible parent

0

10

20

30

40

50

60

70

80

90

100

[-0.03; 0.02]

[0.03; 0.08]

[0.09; 0.14]

[0.15; 0.20]

[0.21; 0.26]

[0.27; 0.32]

[0.33; 0.38]

[0.39; 0.44]

[0.45; 0.51]

Fre

quen

cies

rAUDPC classes

2005

2006

2007

Resistant parent Susceptible parent

a

b

c

Potato Research

and as RS in 2007 (rAUDPC=0.27, Δa=0.16, and Δt=8). In both years, the classi-fication by calculation and visual inspection were identical.

When the results obtained for the G1 and B2 families were taken together, it was notpossible to determine if the discrepancies differed from one year to another. To answerthis question, the number of comparisons would have to be increased. However, whenthe 3 years were grouped, visual inspection and calculated classification using thresh-olds equal to zero did not agree in 10 out of 44 cases. The number of discrepanciesdecreased to 4 out of 44 when threshold values were adjusted to Δt=3 and Δa=0.1(Tables 1 and 3). One of these four still discrepant genotypes observed using adjustedthreshold values was a genotype that was visually deduced to have a RNS phenotype butwas classified as RS in 2005 (genotype O6, family B2). Two other discrepanciesconcerned two genotypes visually deduced to be RNS phenotypes but classified in theS group in 2007 (genotypes G7 and I5, family G1). The last case was a genotypevisually deduced to be an RNS phenotype but classified in the RS+RNS group in 2006(genotype G4, family B2). The difference between RNS and susceptibility is not alwayseasy to score especially when the epidemic is rapid and disease pressure is high(Andrivon et al. 2006). In this case, it was possible to distinguish susceptible from trueRNS using an additional constrain on rAUDPC values. As the identification of geno-types exhibiting RNS is crucial in our research programme, RNS was changed into Swhen the rAUDPC value of the genotype was higher than the mean value of thesusceptible parents minus twice the standard deviation. This led to the followingrAUDPC values: 0.3 in 2005, 0.24 in 2006, and 0.39 in 2007. In the end, only twogenotypes were misclassified, which we consider acceptable.

3. Effect of the year on the classification obtained.

The percentage of genotypes was compiled in each class for each family and eachyear of the experiment using classification 4 and the additional constraint on the valueof rAUDPC.

The impact of the year effect differed among the families analysed (Fig. 3). In theB2 family, the proportion of genotypes in the RNS class decreased from 40% to 15%from 2005 to 2006, then remained stable in 2007. In 2007, this family wascharacterised by a significant proportion of genotypes in the RS class. In G1, thedistribution of genotypes in each class remained relatively stable over the 3 yearswhereas in K2, the proportion of genotypes in class RS increased, especially in 2007.

The year×genotype interaction was significant for rAUPDC in each family (datanot shown). To estimate the impact of this interaction on the classification, theclassification (CL4) of data between 2005 and 2006 and between 2006 and 2007was compared. All genotypes and all three families were compared.

Two main types of deviation between pairs of experimental years were considered:a change in the type of resistance observed (from RS+RNS to RNS or vice versa,

�Fig. 2 Distribution of rAUDPC values in the B2 family (a), G1 family (b) and K2 family (c) in each ofthree consecutive years. Mean values of the parents are indicated by arrows. Mean values of the controlvarieties were: Desirée 0.29, 0.27, and 0.43; Eden 0.15, 0.05, and 0.27; Robijn 0.13, 0.08, and 0.31 for2005, 2006, and 2007, respectively. The standard deviation around the mean was 0.01 or 0.02 forsusceptible parents and ranged between 5×10−5 and 0.01 for resistant parents in the year of testing

Potato Research

Tab

le3

Com

parisonof

theresults

obtained

usingvisual

inspectio

nanddifferentsetof

classificatio

nvalues

(CL1andCL4)

tested

over

3yearsusing16

genotypesfrom

three

segregatingfamilies

(G1,

B2,

andK2)

forallocatin

ggenotypesto

resistantclasses(Table1)

Fam

ilyGenotyp

eYear20

05Year20

06Year20

07

Visual

classificatio

nCL1

CL4

rAudpc

ΔaΔt

Visual

classificatio

nCL1

CL4

rAudpc

ΔaΔt

Visual

classificatio

nCL1

CL4

rAudpc

ΔaΔt

G1

G7

33

30.183

−0.06

03

33

0.18

9−0

.21

01

13

0.413

0.080

−1.9

B10

44

40.032

−0.19

9.8

44

40.01

4−0

.37

7.3

44

40.027

−0.09

3.4

N7

34

30.167

−0.06

1.3

34

30.08

6−0

.32

1.7

32

30.292

0.09

2.4

I53

33

0.050

−0.03

03

33

0.16

2−0

.31

01

13

0.420

0.06

−3.3

C4

44

4−0

.15

12.3

44

40.00

1−0

.39

16.0

44

40.012

−0.14

9.1

B2

G6

44

40.041

−0.18

104

44

0.01

0−0

.34

9.7

44

40.01

−0.06

15.7

O6

32

20.237

0.11

7.7

44

40.10

1−0

.21

9.0

31

30.101

0.08

−6.6

B9

33

30.211

−0.04

−33

43

0.12

2−0

.21

1.7

31

30.122

0.05

−1.9

G4

44

40.107

−0.10

12.3

34

40.03

6−0

.30

4.0

44

40.036

−0.02

3.4

G8

33

31.157

−0.09

03

43

0.26

2−0

.11

1.7

32

30.263

0.08

0.1

K2

A8

44

40.006

−0.10

29.5

44

40.00

1−0

.34

26.3

44

40.020

−0.13

15.7

D10

44

40.001

−0.32

36.5

44

40.007

−0.12

18.7

J44

44

0.026

−0.16

28.5

44

40.00

1−0

.44

26.3

44

40.017

−0.16

17.4

L8

44

40.03

0−0

.34

13.7

22

20.269

0.16

8.4

O2

44

40.00

1−0

.47

19.0

44

40.001

−0.17

12.5

O7

44

40.02

7−0

.49

19.3

44

40.052

−0.14

7.1

Discrepancies

betweenvisualinspectio

nandcalculated

classificatio

nareitalicised

1S(Susceptible),2RS(specificresistance),3RNS(non-specificresistance),4RS+RNSor

RSno

tov

ercome(see

Table1).C

lassificatio

n1(CL1)

thresholdequalto

zero

(the

sameas

used

byAnd

rivo

net

al.(200

6))forΔa

andΔt,Classificatio

n4(CL4)

thresholdequalto

3forΔt

andthresholdequalto

0.1forΔa

Potato Research

from RNS to RS or vice versa, from RS+RNS to RS or vice versa) or a changetowards S. A third type of change was also observed (from S to resistance). However,the proportion of this type of change among experimental years was very low (0–3%)except for genotypes of the G1 family in 2006/2007 that reached 10%.

When comparing 2005 and 2006, the classification of a majority of genotypes ineach family did not change, i.e. 63% of the genotypes in B2, 82% in G1 and 84% inK2 obtained identical classifications. However, the proportion of identical classifica-tions was generally lower between 2006 and 2007: 50% in B2, 65% in G1 and 62% inK2.

Comparing 2005 and 2006, the change in the type of resistance observedconcerned 21% of the genotypes in B2, 8% in G1 and 12% in K2. Between 2006and 2007, the proportions increased: 32% in B2, 18% in G1 and 34% in K2.

Moving into the details in this category, change from RS+RNS to RNS concerned3–9% of the genotypes depending on the year and family. No change from RS+RNSto RS was observed when we compared 2005 and 2006. However, when we com-pared 2006 and 2007, this change concerned 2% of the G1 genotypes, 30% of the K2genotypes and 22% of the B2 genotypes.

A change fromRNS to RS+RNS occurred in around 4% of the genotypes per family.Depending on the family, 1–7% of the genotypes changed from RS to RS+RNSbetween 2005 and 2006. However, this was not the case between 2006 and 2007.

Change towards susceptibility between 2005 and 2006 concerned: 13% of thegenotypes in B2, 8% in G1, and 4% in K2. Comparing 2006 and 2007, the figures didnot differ significantly.

4. Heritabilities calculated on rAUDPC, Δa, and Δt.

Heritability was moderately high to high ranging between 61% and 96% of thevariation in clone means across years and replicates due to genetic differencesbetween the clones (Table 4).

0%

20%

40%

60%

80%

100%

2005 2006 2007 2005 2006 2007 2005 2006 2007

B2 G1 K2

RS+RNS or RS not overcomeRNS

RS

S

Fig. 3 Proportions of resistance types in each of three tetraploid potato families B2, G1, and K2 in each ofthe years 2005–2007. Resistance types represented here were obtained using a Δt threshold of 3, a Δathreshold of 0.1 and an additional criterion for rAUDPC (see text)

Potato Research

In each family, the highest heritabilities were for rAUDPC and the lowest for Δa.The G1 family had the highest heritability values for all traits due to a lower σ2

cy

value than those observed in the other families compared to σ2c values.

All the variables were significantly correlated except Δa and Δt in B2 and K2 in2005 and 2007 (data not shown). Correlations were positive for rAUDPC and Δa butnegative for rAUDPC and Δt. Δa and Δt were significantly and negatively correlated.The level of this correlation was moderate: the mean of correlation coefficient acrossyears and families was equal to −0.34 whereas for rAUDPC and Δa the same meanwas 0.70 and −0.67 for rAUDPC and Δt.

Discussion

Andrivon et al. (2006) demonstrated that parameters derived from DPC curves, i.e.Δa and Δt, can be used to infer the type of resistance of cultivars starting from fielddata. In our study, parameters Δa and Δt were successfully used to characterisegenotypes in segregating families according to their type of resistance. After someadjustments of threshold values to adapt them to our purposes and data, theclassification method was performed with the aim of distinguishing genotypeswhich displayed marked differences between years from more stable genotypes andprovided a global overview of what happened in three segregating families. Using Δaand Δt was easier than inspecting large numbers of DPCs (5,710 including the threefamilies and the 3 years). Moreover, if only rAUDPC values were inspected, wewould not have been able to identify genotypes exhibiting stable non-specific resis-tance over the 3 years of the experiment. However we needed to use an additionalconstraint on rAUDPC values to really distinguish susceptible from RNS genotypes,especially in 2007 when the epidemic was particularly rapid.

We adjusted threshold values to our data and purpose, which was not to selectmaterial but rather to describe it. Avalue of 3 was chosen for Δt because it correspondedto half the mean interval between successive scores. A value of 0.1 was chosen for Δabecause it corresponded to the standard deviation calculated using three replicates of

Table 4 Components of variance σ2c ; σ2cy , σ

2, for clones, clone×year interaction and residual variation,and heritability for each family and each trait

Family Trait σ2c σ2cy σ2 H2

B2 rAUDPC 0.0092 0.0033 0.0023 0.87

Δa 0.0045 0.0069 0.0054 0.61

Δt 15.1 2.8 20.6 0.82

G1 rAUDPC 0.0203 0.0022 0.0013 0.96

Δa 0.0103 0.0052 0.0056 0.81

Δt 30.1 6.7 22.3 0.86

K2 rAUDPC 0.0088 0.0031 0.0013 0.88

Δa 0.008 0.0073 0.0094 0.70

Δt 36.2 7.3 36.2 0.85

Potato Research

each individual. These threshold values could differ depending on the aim of theexperiment and the type of material to be observed. In a breeding programme, onecan choose a threshold value for Δa corresponding to a standard genotype for RNS, forexample half the value of the cultivar Robijn (Andrivon et al. 2006).

The phenotyping we used here was the result of a large number of scores (10–13per experimental unit). In a traditional breeding process, it is not always possible tospend as much time on a single experiment. It has even been proposed to decrease thenumber of dates to two when only dealing with AUDPC values (Jeger and Viljanen-Rollinson 2001), provided that both dates are properly chosen (Haynes andWeintgartner 2004; Kumar et al. 2007). However, when the objective is to improvenon-specific resistance, we need to be as accurate as possible; otherwise it is notpossible to compute realistic parameters. The accuracy of the Δt parameter depends toa great extent on the frequency of disease scoring (Andrivon et al. 2006).

Results showed that the year effect was important. This was expected as theexperiment was performed under conditions of natural infection conditions with nocontrol of the pathogen population. In addition, the last year of the experiment (2007)was very rainy leading to very favourable conditions to P. infestans. Between May 1and August 31 in 2007, total precipitation was 492 mm compared with 205 mm in2005 and 202 mm in 2006. The 2007 epidemic was considered to be the most severefor the last 10 years in all the potato growing regions of France (Duvauchelle et al.2008) and A1 isolates collected on Bintje in 2007 were characterised by increasedaggressiveness compared to isolates collected in previous years (Corbière et al. 2009).

At our experimental location, the natural population of P. infestans is verycomplex and is able to overcome nearly all the R genes of S. demissum as exemplifiedby the results obtained on Black’s differentials. Isolates are collected each year nearthe experiment by phytopathologists. In 2001 and 2002, all the virulences exceptthose corresponding to R5 and R9 were identified in the pathogen population(Montarry et al. 2006). French populations of P. infestans have undergone majorchanges at least since 2003, if not earlier. An A2 mating type was detected for the firsttime in 2003 and has increased continuously since then (Corbière et al. 2009;Duvauchelle et al. 2008). Using isolates sampled between 2006 and 2008 in differentparts of France including in our region, it has been shown that A2 isolates were lessdiverse than A1 isolates but had more complex virulence profiles, half of themcontaining the 11 virulences related to Black’s differentials (Corbière et al. 2010).During the period of our experiments, the pathogen population underwent changes.Although we did not specifically investigate such changes in our own fields, we canhypothesise that these changes also occurred here, at least to some extent. This couldexplain part of the year effect observed in our results, particularly the changes in therAUDPC distribution observed between years given the importance of the R geneeffect on this variable.

The populations of pathogens in our fields are thus probably a mixture of differentraces which, as Stewart and Bradshaw (2001) demonstrated on differentials, couldhave led to overestimation of field resistance especially in genotypes containing the Rgene(s). However, the classification we used did not only rely on rAUDPC. We thinkthat as we used the Δt parameter and considering that the pathogen is “multi-virulent”, we were in a good position to search for RNS. Crosses were obtainedbetween resistant and susceptible genotypes and will be used to check our hypothesis

Potato Research

concerning the type of resistance contained in the genotypes. As demonstrated inSolomon-Blackburn et al. (2007), this is the only way to verify our hypothesis.

Several hypotheses can be proposed to explain the observed changes in theclassification of the genotypes. The change from RS+RNS (or RS not overcome)to RNS may simply be explained by the R gene contained in the genotype beingovercome. The change from RNS to RS+RNS could be explained by the estimationof the Δt value, if the estimated value is close to the threshold value, genotypes canfall into one or the other category. The change from RS+RNS to RS was onlyobserved when we compared 2006 and 2007 and could be explained by our difficultyin detecting true RNS in 2007 due to the rapidity of the epidemic. Another explana-tion could be the reduced efficiency of RNS in a year with a strong epidemic of lateblight. The difference between RS and RS+RNS categories relied on the estimationof Δa; if the estimation was close to the threshold, the genotype could fall into aparticular category although it could in fact be in the other category. The sameexplanation could apply to the low percentage of genotypes that changed from S toRNS between 2006 and 2007.

Changes from S to RS+RNS are more difficult to explain because the estimationsof Δa and Δt are concerned. However, an alternative hypothesis could be theheterogeneity of the isolates in our experiment.

Concerning genotypes exhibiting RS+RNS or RS not overcome, RS may beovercome in a subsequent year of experimentation. Around 15% of the genotypesexhibited RNS (except the K2 family). Resistance factors in these families should notbe strongly influenced by the type of environmental factors that were not controlledin our experiment, i.e. changes in the pathogen population, or meteorological condi-tions. This paper reports results obtained in 3 years of experiments, which is rathershort. However, different studies support the hypothesis of partial resistance to lateblight being stable over very long periods of time (Van der Plank 1971; Colon et al.1995; Inglis et al. 1996; Grünwald et al. 2002).

Categorization also gave us an overview of what happened in the families over theyears. This led us to the conclusion that the G1 family was the most stable, B2 theleast stable and that K2 was generally stable due to a high level of specific resistancetending to be overcome. These findings were confirmed by the calculation of broad-sense heritabilities. The values corresponded to the highest values calculated for othertraits in potato by Bradshaw (2007). Differences between families can be explainedby their different genetic backgrounds.

The next step in our research will be validating our hypothesis concerning the typeof resistance in some progenies using the next generation of material. Genotyping ofthe three families is in progress to detect the QRLs concerned. Recently, the advan-tage of using partial resistance to increase the durability of resistance was demon-strated in the pepper–PVY interaction (Palloix et al. 2009) and in the B. napus/L.maculans interaction (Brun et al. 2010). In the potato–late blight interaction, the useof markers linked to partial resistance will be important in the process of selectingprogenies combining partial resistance and efficient R gene(s). Such markers will giveus a chance to develop resistant clones with increased durability.

Acknowledgments Experiments could not have been done without the help of the technical team of theBretagne Plants breeding station. The authors also thank the students who participated in the experiments.

Potato Research

References

Andrivon D, Pellé R, Ellissèche D (2006) Assessing resistance types and levels to epidemic diseases fromthe analysis of disease progress curves: principles and application to potato late blight. Am J Potato Res83:455–461

Anonymous (1989) Fungal diseases of potato, breeding for late blight resistance. In: International PotatoCenter Annual report 1988. pp 68–71

Bradshaw JE (2007) Potato-breeding strategy. In: Vreugdenhil D (ed) Potato biology and biotechnology.Elsevier, pp 158–177

Brun H, Chèvre AM, Fitt BDL, Powers S, Besnard AL, Ermel M, Huteau V, Marquer B, Eber F, Renard M,Andrivon D (2010) Quantitative resistance increases the durability of qualitative resistance toLeptosphaeria maculans in Brassica napus. New Phytol 185:285–299

Colon LT, Turkensteen LJ, Prummel W, Budding DJ, Hoogendoorn J (1995) Durable resistance to lateblight (Phytophthora infestans) in old potato cultivars. Eur J Plant Pathol 101:387–397

Corbière R, Montarry J, Glais I, Viard A, Andrivon D (2009) Agressiveness differences between A1 andA2 isolates of Phytophthora infestans from France. PPO-Special Report 13:207–213

Corbière R, Magalon H, Boulard F, Andrivon D (2010) Study of invasive French populations (2006–2008)of Phytophthora infestans, to oomycete causing potato late blight. (2010) PPO-Special Report no. 14,289–290

Danan S, Veyrieras JB, Lefebvre V (2011) Construction of a potato consensus map and QTL meta-analysisoffer new insights into the genetic architecture of late blight resistance and plant maturity traits. BMCPlant Biology 11:16

Dowley LJ, Cargenie SF, Balandras-Chatot C, Ellissèche D, Gans P, Schöder-Butin B, Wustman R (1999)Guidelines for evaluating disease resistance in potato cultivars. Foliage blight resistance (field test)Phytophthora infestans (Mont.) de Bary. Potato Res 42:107–111

Duvauchelle S, Détourné D, Dubois L (2008) Evolution of the population of Phytophthora infestans inFrance. Epidemiologic and phenotypic markers. In: Chiru S, Olteanu G, Aldea C, Badarau C (eds) 17thtriennial conference of the European Association for Potato Research, Brasov, Romania. TransilvaniaUniversity of Brasov Publishing House, 157–163

Fry WE (1978) Quantification of general resistance of potato cultivars and fungicide effects for integratedcontrol of potato late blight. Disease Control Pest Manag 68:1650–1655

Fry WE (2008) Plant diseases that changed the world, Phytophthora infestans: the plant (and R gene)destroyer. Mol Plant Pathol 9(3):385–402

Grünwald NJ, Cadena-Hinojosa MA, Rubio-Covarruvias O, Rivera Peña A, Niederhauser JS, Fry WE(2002) Potato cultivars from the Mexican national program: sources and durability of resistance againstlate blight. Phytopathology 92(7):688–693

Haverkort AJ, Boonekamp PM, Hutten R, Jacobsen E, Lotz LAP, Kessel GJT, Visser RGF, van der VossenEAG (2008) Societal costs of late blight in potato and prospects of durable resistance through cisgenicmodification. Potato Research 51:47–57

Haynes KG, Weintgartner DP (2004) The use of area under the disease curve to assess resistance to lateblight in potato germplasm. Am J Potato Res 81:137–141

Inglis DA, Johnson DA, Legard DE, Fry WE, Hamm PB (1996) Relative resistances of potatoclones in response to new and old populations of Phytophthora infestans. Plant Dis 80(5):575–578

Jeger MJ, Viljanen-Rollinson SLH (2001) The use of the area under the disease–progress curve (AUDPC)to assess quantitative disease resistance in crop cultivars. Theor Appl Genet 102:32–40

Kumar R, Kang GS, Pandey SK (2007) Inheritance of resistance to late blight (Phytophthora infestans) inpotato. Euphytica 155:183–191

Landeo JA, Gastelo M, Pinedo H, Flores F (1995) Breeding for horizontal resistance to late blight in potatofree r genes. In: Keane T, O'Sulliva E (eds) Phytophthora infestans. Boole, Dublin, Ireland, pp 268–274

Lindhout P (2002) The perspectives of polygenic resistance in breeding for durable disease resistance.Euphytica 124:217–226

Montarry J, Corbière R, Lesueur S, Glais I, Andrivon D (2006) Does selection by resistant hosts triggerlocal adaptation in plant-pathogen systems? J Evol Biol 19:522–531

Palloix A, Ayme V, Moury B (2009) Durability of plant major resistance genes to pathogens depends on thegenetic background, experimental evidence and consequences for breeding strategies. New Phytol183:190–199

Potato Research

Solomon-Blackburn RM, Stewart HE, Bradshaw JE (2007) Distinguishing major-gene from field resistanceto late blight (Phytophthora infestans) of potato (Solanum tuberosum) and selecting for high levels offield resistance. Theor Appl Genet 115(1):141–149

Stewart HE, Bradshaw JE (2001) Assessment of the field resistance of potato genotypes with major generesistance to late blight (Phytophthora infestans (Mont.) de Bary) using inoculum comprised of twocomplementary races of the fungus. Potato Res 44:41–52

Stewart HE, Bradshaw JE, Pande B (2003) The effect of the presence of R-genes for resistance to late blight(Phytophthora infestans) of potato (Solanum tuberosum) on the underlying level of field resistance.Plant Pathol 52:193–198

Tan MYA, Hutten R, Celis C, Park TH, Niks RE, Visser RGF, van Eck HJ (2008) The rpi-mcd1 locus fromSolanum microdontum involved in resistance to Phytophthora infestans, causing a delay in finection,maps on potato chromosome 4 in a cluster of NBS-LRR genes. Molecular Plant-Microbe Interactions7:909–918

Umaerus V, Umaerus M (1994) Inheritance of resistance to late blight. In: Bradshaw JE, Mackay GR (eds).Potato genetics. pp 365–401

Van der Plank JE (1963) Plant diseases: epidemics and control. Academic, New YorkVan der Plank JE (1971) Stability of resistance to Phytophthora infestans in cultivars without R genes.

Potato Res 14:263–270Visker MHPW, van Raaij HMG, Keizer LCP, Struik PC, Colon LT (2004) Correlation between late blight

resistance and foliage maturity type in potato. Euphytica 137:311–323Wastie RL (1991) Breeding for resistance. In: Ingram DS, Williams PH (eds) Phytophthora infestans, the

cause of late blight of potato, vol 7. Advances in Pathology. Academic, London, UK, pp 193–224

Potato Research