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Plant Pathology (2009) 58, 409–424 Doi: 10.1111/j.1365-3059.2009.02039.x

© 2009 The Authors

Journal compilation © 2009 BSPP 409

BlackwellPublishingLtd

REVIEW

Aggressiveness and its role in the adaptation of plant

pathogens

B. Pariaud

a

*, V. Ravigné

b

, F. Halkett

c

, H. Goyeau

a

, J. Carlier

b

and C. Lannou

a

a

INRA, UMR 1290, 78850 Thiverval Grignon; b

CIRAD, UMR 385, Campus de Baillarguet, 34398 Montpellier; and c

INRA UMR 1136, 54280

Champenoux, France

Aggressiveness, the quantitative component of pathogenicity, and its role in the adaptation of plant pathogens are

still insufficiently investigated. Using mainly examples of biotrophic and necrotrophic fungal pathogens of cereals and

Phytophthora infestans

on potato, the empirical knowledge on the nature of aggressiveness components and their

evolution in response to host and environment is reviewed. Means of measuring aggressiveness components are considered,as well as the sources of environmental variance in these traits. The adaptive potential of aggressiveness components is

evaluated by reviewing evidence for their heritability, as well as for constraints on their evolution, including differential

interactions between host and pathogen genotypes and trade-offs between components of pathogenicity. Adaptations of

pathogen aggressiveness components to host and environment are analysed, showing that: (i) selection for aggressiveness

in pathogen populations can be mediated by climatic parameters; (ii) global population changes or remarkable population

structures may be explained by variation in aggressiveness; and (iii) selection for quantitative traits can influence pathogen

evolution in agricultural pathosystems and can result in differential adaptation to host cultivars, sometimes leading to

erosion of quantitative resistance. Possible links with concepts in evolutionary ecology are suggested.

Keywords

: environmental sources of variation, fitness, heritable reproductive variation, quantitative host resistance,

virulence

Introduction

Understanding why and how pathogens harm their hostsis a central focus in plant pathology and is of particularimportance in the context of cultivated host plants. Uponencountering a potential host, a pathogen may be able tocause infection or not. This compatibility relationshiphas so far largely monopolized the attention of plantpathologists and shaped the discipline (Barrett, 1985;Thrall & Burdon, 2003). One good reason for this maybe that compatibility relationships are relatively easy toinvestigate empirically. In addition, a convincing genetic

mechanism was proposed early on [the ‘gene-for-gene’model (Flor, 1955)] and was rapidly supported by empiricalevidence (Flor, 1971). Finally, plant epidemiology hasrepeatedly proved the dramatic importance of thesecompatibility relationships for disease dynamics in cropsystems (e.g. Hovmøller et al.

, 1993). In contrast, relativelyfew studies have examined the quantitative aspects of

host–pathogen interactions and their consequences forthe dynamics and evolution of pathogen populations.

Most studies on the quantitative aspects of the host–pathogen interaction make reference to pathogen ‘aggres-siveness’. Defining aggressiveness may not be simple,however, as the practical (and often implicit) definition inuse in many papers often differs from both the originaland the ‘official’ definitions.

Originally, Van der Plank (1963) defined aggressivenessas the non-specific component of pathogenicity. Later,Van der Plank (1968) illustrated this definition with datafrom an experiment (Paxman, 1963) in which isolates

of Phytophthora infestans

were grown for successivegenerations on a potato cultivar with no major resistanceR-genes (i.e. all isolates were virulent, according to thegene-for-gene model). Van der Plank (1968) summarized theresults of Paxman’s experiment in an anova table in whichthe isolate effect (main effect) represented aggressiveness.The absence of isolate ×

cultivar interaction supportedVan der Plank’s concept of pathogenicity, according towhich differential interactions always relate to ‘virulence’(which is linked to the presence or absence of R-genes),whereas ‘aggressiveness’ describes a quantitative component

*E-mail: [email protected]

Published online 5 April 2009

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with this difficulty, several criteria are used to estimatelatent periods, such as the time from inoculation to firstsporulation (Jeffrey et al.

, 1962; Jinks & Grindle, 1963;Knott & Mundt, 1991; Miller et al.

, 1998) or the timeneeded for half of the final number of lesions (T

50

) tosporulate (Knott & Mundt, 1991; Flier & Turkensteen,1999) or to show apparent sporulation structures (Johnson,

1980; Tomerlin et al.

, 1983). The most precise method forestimating T

50

was proposed by Shaner (1980) and is basedon an adjustment of the dynamics of lesion emergence toa sigmoid curve. Since latent period is highly dependenton temperature, it is recommended to express the timein degree-days to allow comparisons between differentexperiments (Lovell

et al.

, 2004). It has been observedthat using different methods to measure latent period(e.g. T

50

vs. the time to first sporulation) could lead todifferences in its estimation [see Knott & Mundt (1991)for Puccinia triticina

on wheat and Flier & Turkensteen(1999) for P. infestans

on potato]. Such differences might,of course, result from uncontrolled environmental effects.A more interesting alternative is that variability in latent

period among pathogen genotypes could reveal heter-ogeneity in both the time at which the first sporulationoccurs and the dynamics of lesion maturation, as discussedby Shaw (1990).

Sporulation rate is the amount of spores producedper lesion and per unit of time (Clifford & Clothier, 1974;Sache, 1997). In practice, spores are either weighed(Imhoff et al.

, 1982; Kardin & Groth, 1989) or counted(Leonard, 1969; Rouse et al.

, 1980). Sporulation issometimes expressed in spore production per unit area of diseased leaf (Clifford & Clothier, 1974) or relative tolesion size (Miller et al.

, 1998). It has repeatedly beenshown that spore production per lesion is highly density-

dependent (Kardin & Groth, 1989). It can be useful toconsider the spore production per unit area of sporulatingtissue (Hamid et al.

, 1982a; Subrahmanyam et al.

, 1983;Dowkiw et al.

, 2003), which is considerably less density-dependent (Robert et al.

, 2004).The infectious period is the time from the beginning to

the end of sporulation. This component is difficult toprecisely estimate since sporulation often shows an earlypeak followed by an asymptotic decrease (Leonard, 1969;Robert et al.

, 2004), but more irregular patterns may beobtained (Imhoff et al.

, 1982). For cereal rusts, sporulationcan last for more than 40 days under controlled conditionson adult plants (Leonard, 1969; Mehta & Zadoks, 1970;Imhoff et al.

, 1982; Robert et al.

, 2004).

Since many pathogen species have two or more formsof propagule related to sexual or asexual reproduction(Pringle & Taylor, 2002), infection efficiency, sporulationrate, latent period and infectious period may, in principle,be measured for each type of spore (e.g. Gilles et al

., 2001;Karolewski et al

., 2002). Nevertheless, a given parametermay not have the same meaning when measured on sexualand asexual spores. For example, the latent periodassociated with sexual spores is very different from thatof asexual spores because it depends on the fortuitousencounter and merger of two sexually compatible lesions.

Therefore, while there seems to be room for adaptiveadjustment of asexual latency, sexual latency is expectedto be highly dependent on environmental stochasticity.Moreover, organs resulting from sexual reproductionoften ensure inter-season survival, as in Blumeria graminis

or in Leptosphaeria maculans

, and the latent period, asdefined above, has no meaning in such cases.

Lesion size is another quantitative trait that is measuredas an aggressiveness component (Kolmer & Leonard,1986; Mundt et al.

, 2002b). It is generally defined as thesurface area that produces spores. For some pathogens,such as P. triticina

, lesion size remains limited, but it candramatically increase in some species such as P. infestans

or Puccinia striiformis

, for which lesion growth issemisystemic (Emge et al.

, 1975). In this case, lesion sizeaccounts for a large part of the quantitative developmentof epidemics and lesion growth rate is a key factor inpathogen competition for available host tissue. Lesion sizeis not easy to precisely determine for pathogens such as

Mycosphaerella graminicola

that induce necrosis on thehost leaf (Cowger et al.

, 2000). Moreover, such pathogens

often indirectly cause apical necrosis on the leaves that canbe confused with a diseased area.

Aggressiveness is sometimes estimated through diseaseseverity, measured as the percentage of the infected plantorgan (root, leaf or spike) covered by pathogen lesions(Krupinsky, 1989; Ahmed et al.

, 1995, 1996; Gilbert et al.

,2001; Cowger & Mundt, 2002; Zhan et al.

, 2002;Cumagun & Miedaner, 2003). Disease severity here is acomposite variable resulting from the integrated effect of infection efficiency and lesion size, but also, when assessedat the crop scale, sporulation and dispersal.

The production of mycotoxins (inducing host necrosis)is generally considered an aggressiveness component, but

the relationship between disease severity and mycotoxinproduction is not straightforward. In fusarium headblight of wheat, some studies did not show any relationshipbetween aggressiveness (measured as disease severity) andtoxin production (Gilbert et al.

, 2001), whereas otherauthors found that DON-toxin concentrations in grainswere closely correlated with disease severity (Cumagun &Miedaner, 2004). Deciphering the exact function of toxin production is important to determine its role inaggressiveness. In necrotrophic species, where toxinproduction is only used to kill plant cells and convert theminto resources for growth, toxin production may indeedbe correlated with within-host multiplication. In contrast,in species where toxin production is needed to allow spore

release (e.g. by accelerating host death), it is not expectedto directly correlate with other measurements of within-host multiplication (Day, 2002).

Effects of environment on expression ofaggressiveness components

The effects of climatic parameters (mainly temperatureand relative humidity) on the expression of disease havebeen extensively described in the literature. In addition, itis known that host physiological status (e.g. nitrogen

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B. Pariaud et al.

content, tissue age) affects disease development, particularlyfor biotrophic pathogens (Eversmeyer et al.

, 1980; Tomerlin

et al.

, 1983; Turechek & Stevenson, 1998; Robert et al.

,2004). Finally, some components of the pathogen life cycle(e.g. spore production per lesion) are strongly influenced bylesion density (Katsuya & Green, 1967; Mehta & Zadoks,1970; Rouse et al.

, 1980; Kardin & Groth, 1989; Robert

et al.

, 2004). These sources of variation are generallyconsidered unwanted effects in aggressiveness measure-ments, but may account for a large portion of variability.For instance, in a study of the adaptation of P. triticina

to wheat cultivars (Knott & Mundt, 1991), most of thevariability was accounted for by the growth chamberfor two out of three parameters measured. Similarly,ranking by disease severity of isolates of

M. graminicola

,as well as cultivar-by-isolate interaction, were found tovary between a greenhouse and a growth-chamberexperiment (Krenz et al

., 2008).

Effect of climatic conditions

Variation among years in field experiments can be con-siderable, underlining the strong sensitivity of aggressive-ness measurements to climatic conditions. For instance, ina field study with Fusarium graminearum

, Cumagun &Miedaner (2004) calculated that the isolate-by-environ-ment interaction accounted for 29% of the variance foraggressiveness (measured by disease severity) and 19% of the variance for mycotoxin production.

Most studies linking aggressiveness and climate arelimited to the effect of temperature. It is well known thattemperature influences pathogen development as well asthe expression of host resistance. The effect of temperatureon aggressiveness components has been established for

many pathogen species and presents an optimum forspore germination, lesion development and sporulation.However, the response to temperature may differ amongindividuals (Milus et al.

, 2006). For instance, Milus &Line (1980) showed that the spore production rate of twoleaf rust isolates (

P. triticina

) was identical at 2–18

°

C butdifferent at 10–30

°

C.Interestingly, differences in aggressiveness among

pathogen isolates have sometimes been reported to begreater under non-optimal conditions: differences in thelatent period among isolates were more effectively observedat suboptimal temperatures for pathogen development in

P. triticina

and P. striiformis

f.sp. tritici

(Eversmeyer et al.

,1980; Johnson, 1980; Milus et al.

, 2006). This result sug-

gests that differential responses in terms of aggressivenessmay be less detectable under optimal environmentalconditions (Eversmeyer et al.

, 1980; Johnson, 1980).

Effect of host physiological status

For several biotrophic parasites, high nitrogen content inhost tissues results in increased infection efficiency andspore production (Tiedemann, 1996; Jensen & Munk, 1997;Robert et al.

, 2004). Spore production of biotrophicparasites was also reported to increase when host photo-

synthesis was stimulated (Cohen & Rotem, 1970). More-over, the response to infection may depend on host growthstage (Eversmeyer et al.

, 1980; Johnson, 1980; Milus &Line, 1980; Tomerlin et al.

, 1983) or on the type or age of host tissues (Turechek & Stevenson, 1998). Changes in thequantitative expression of disease with host developmentstage were reviewed by Develey-Rivière & Galiana (2007)

and probably largely relate to differences in the expressionof resistance factors. Host status may affect the quantitativehost–pathogen interaction through the amount of availableresources or through the expression of resistance genes(the latter is not considered further).

Milus & Line (1980) observed that the relative sporeproduction of two P. triticina

cultures changed with hostgrowth stage (seedling or adult plant) on some cultivars.Turechek & Stevenson (1998) showed that the age of hosttissues can have a strong effect on a tree disease such aspecan scab (caused by Cladosporium caryigenum

) foraggressiveness components such as infection efficiency,incubation period, lesion size and sporulation. Knott &Mundt (1991) found a significant difference between upper

and lower leaves for latent period and infection efficiencywhen measuring the aggressiveness of field populationsof P. triticina

on wheat. On average, spore populationsexhibited 25% higher infection efficiency and a 3–4%shorter latent period on the upper leaves than on the lowerleaves. This was attributed either to greater susceptibilityof the upper leaves or to physiological effects. Katsuya &Green (1967) even found significant differences in thelatent period of wheat stem rust, depending on the positionof the lesions along the leaves: latent period was about1 day shorter at the leaf base than toward the tip.

Measurements performed on detached leaves, althoughgenerally considered reliable, may sometimes alter the

differences observed: Miller et al.

(1998) compared theresponses of three to five P. infestans

isolates on two potatocultivars, either on detached leaflets or whole plants. Theyfound that one isolate (537) had a significantly greatersporulation capacity on whole plants than two others(367 and 416), whereas no significant differences werefound among isolates on detached leaflets, regardless of cultivar.

Effect of lesion density

For many biotrophic pathogens, lesion size and sporeproduction are highly density-dependent (e.g. Robert

et al.

,2004), probably because of increased competition among

lesions for host resources and available tissues. This densityeffect may have major consequences for experimentalmeasurements of aggressiveness components such as sporeproduction and lesion size, particularly when differencesin infection efficiency among isolates result in differentlesion densities. In such cases, observed differences inspore production may result from a density effect ratherthan from genetic differences among isolates. For instance,in a study by Clifford & Clothier (1974) on barley leaf rust (

Puccinia hordei

), the greater sporulation capacityobserved on moderately resistant cultivars than on the

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susceptible control could have partly resulted from adensity effect generated by differences in infectionefficiencies.

Pathogen genotypes may respond differently to thiscompetition effect, however, and some individuals seem tobe less affected than others by lesion density (Katsuya &Green, 1967; Kardin & Groth, 1989). Katsuya & Green

(1967) observed the competition between two isolatesbelonging to two different pathotypes of Puccinia graminis

during 14 generations on wheat seedlings in a greenhouse.One isolate was predominant at low densities (less than10 lesions per leaf) on both cultivars, whereas the otherisolate became predominant on one of the cultivars athigh densities (> 100 lesions per leaf). Additional evidenceof genotype-by-density interaction was found by Kardin& Groth (1989) with bean leaf rust (caused by Uromycesappendiculatus

). They observed that the relative lesionsize of several isolates changed when lesion density wasincreased: isolates with the largest lesions at low lesiondensity presented the smallest lesions at high density. Theauthors concluded that a reproductive advantage found

at low densities might be obviated at higher densities.However, the consequences of these differential responsesto competition might be weak on an epidemic scale (seeLannou & Mundt, 1997).

Effect of pathogen physiological status

Variability in aggressiveness measurements may also resultfrom the physiological state of the pathogen. In particular,storage or multiplication conditions may alter pathogenaggressiveness. This was clearly shown for P. infestans

byDay & Shattock (1997) in which isolates collected indifferent years and stored in liquid nitrogen were

compared with ‘standard’ reference isolates. Jeffrey et al.

(1962) and Jinks & Grindle (1963) observed a decrease inaggressiveness of P. infestans

strains after repeated transferson chickpea medium, and reported that different strainsunderwent these changes to varying extents and at differingrates. Nonetheless, Jinks & Grindle (1963) observed thatcycling on potato tubers could enable P. infestans

to recoverits initial aggressiveness level, suggesting that the observedchanges resulted from phenotypic plasticity. Mundt et al.

(2002b), using the bacterial pathosystem Xanthomonasoryzae

pv. oryzae

on rice, tested two cultures resultingfrom separate maintenance of the same initial material.The difference between cultures approached significance(

P = 0.06) in one trial out of two, and variance compo-

nent analysis indicated that the culture environment of thepathogen accounted for 14% of the total variation inlesion length. The authors concluded that culture varia-bility should be considered more often in aggressivenessmeasurements.

The great sensitivity of the quantitative host–pathogeninteraction to environmental variations (including climaticeffects, lesion density, host physiological status, isolatemaintenance and culture conditions) has at least two con-sequences. First, it constitutes a constraint for empiricalstudies of aggressiveness, since it appears to be of primary

importance to perform aggressiveness measurementsunder well-defined and controlled conditions and withstandardized host and pathogen material. Secondly, it isquestionable from an evolutionary perspective whetheraggressiveness components, variable as they are withenvironment, may respond to selection. The genetic basisof aggressiveness traits and their adaptive potential are

discussed below.

Genetic basis of aggressiveness components

Compared with studies on the genetics of quantitativeresistance, investigations of the genetic bases of aggres-siveness components in fungi are scarce. An example of the former is the meta-analysis of the genetic supportof quantitative and qualitative resistance of rice toMagnaporthe grisea by Ballini et al. (2008). Generally,the number of effective genetic factors for quantitativeresistance tends to range from two to 10 or more, but it iscommonly determined by three to five loci (Parlevliet,1993; Young, 1996; Singh et al., 2005). Moreover, it has

been suggested that quantitative loci could be allelicversions of qualitative resistance genes with intermediatephenotypes (Young, 1996, Ballini et al., 2008). It thusappears that the genetic determination of quantitativeresistance is both complex and diversified in terms of thenumber and nature of genes involved. As a consequence,the genetic control of aggressiveness is likely to be complexand variable, and is probably of polygenic determinationin most cases.

Several studies have suggested that aggressivenesscomponents are polygenically determined (Blanch et al.,1981; Caten et al., 1984; Hawthorne et al., 1994; Cumagun& Miedaner, 2004). This was shown, for instance, with

segregation for wheat leaf necrosis and production of pycnidia in Phaeosphaeria nodorum, by tetrad analysis(Halama et al., 1999).

The genetic architecture of quantitative traits can befurther studied through quantitative trait loci (QTL)mapping. Only a few QTL were detected for componentssuch as lesion length or fungal growth in Gibberella zeae(Cumagun et al., 2004) and Heterobasidion annosum (Lindet al., 2007). However, several obstacles make this approachgenerally difficult for plant pathogenic fungi. First, thenumber of loci detected in QTL analysis depends onseveral factors, including the genetic properties of theQTL that control the traits studied, environmental effects,population size and experimental error (Collard et al.,

2005). Secondly, QTL analysis cannot be applied toasexually reproducing species and thus to a large numberof pathogenic fungi. Lastly, QTL analysis requires phe-notypic evaluation and, as mentioned above, quantitativemeasurements in plant pathogens are time-consumingand subject to high variability, which limits the number of progeny and components analysed.

Molecular genetic and genomic approaches have alsobeen used to identify the genes involved in pathogenicity,either qualitatively or quantitatively (aggressiveness-relatedgenes) (Xu et al., 2006). The pathogenicity-related genes

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identified in the rice blast model M. grisea were recentlyreviewed (Ebbole, 2007). The vast majority of these geneswere involved in the ability to infect the host, but somewere found to control quantitative variations of aggres-siveness components.

As a conclusion on this point, empirical evidencefor genetic control has been found for at least some

aggressiveness components. In all cases, this geneticsupport implies that several genes are involved, even if theprecise number of genes and their interactions are still tobe determined. An alternative approach to elucidate thegenetic basis of adaptation involves genome scans of DNApolymorphism (Schlötterer, 2003; Storz, 2005), based onthe identification of neutral markers with deviantbehaviour in natural populations. This population-basedapproach makes it possible to identify loci undergoingselection without having to evaluate the phenotypesthemselves, but is again limited to sexually reproducingfungi. Although promising, it has not yet been applied tofungal pathogens.

Adaptive potential of aggressivenesscomponents

The fact that aggressiveness components have a geneticbasis opens up opportunities for pathogen adaptation.Such adaptation is only possible, however, if heritablegenetic variations exist in pathogen populations for thesetraits. Assuming that heritable genetic variation on aggre-ssiveness components exists in pathogen populations,evolution of aggressiveness will be shaped by geneticconstraints such as (i) differential interactions betweenhosts and pathogen isolates for quantitative traits, (ii) trade-offs between qualitative virulence and aggressiveness (‘cost

of qualitative virulence’) and (iii) trade-offs betweenaggressiveness components or between aggressiveness andsurvival capacity.

Variability for aggressiveness within pathogenpopulations

Within-population variation for quantitative traits is abasic prerequisite for adaptation. However, it is importantto note that potential genetic diversity in aggressivenesshas often been underestimated. In fact, pathotypes havesometimes been considered as homogeneous geneticunits and compared on the basis of a single isolate perpathotype (Katsuya & Green, 1967). Nevertheless, apparent

uniformity within a pathogen population studied on thebasis of qualitative indicators does not exclude the possi-bility of a certain level of variability in aggressiveness:many studies have documented differences in aggressivenessamong isolates belonging to the same pathotype orsharing similar genotypes as defined by neutral markers(Jeffrey et al., 1962; Hamid et al., 1982b; Miller et al.,1998; Carlisle et al., 2002; Mundt et al., 2002b; Miluset al., 2006). Hamid et al. (1982b) found significant intra-pathotype variations for infection efficiency, lesion lengthand sporulation capacity among isolates of the same

pathotype of Cochliobolus carbonum, with differencesbetween the least and the most aggressive isolate of upto 91%. Milus et al. (2006) found that two isolates of P. striiformis f.sp. tritici belonging to the same pathotypenot only had different latent periods at 18°C on wheatseedlings, but also presented different optimal temperaturesfor this trait, one isolate developing faster at 12°C and the

other at 18°C. Significant differences in aggressiveness(lesion expansion rate, latent period, sporulation andinfection efficiency) were found among 17 P. infestansindividuals collected from a Northern Ireland populationand sharing an identical multilocus genotype (allozymeprofiles and mtDNA haplotypes), the same mating type,the same capacity to overcome the specific R1 resistancegene and the same sensitivity to a fungicide (Carlisle et al .,2002). Mundt et al. (2002b) investigated the potentialassociation of aggressiveness variation among isolates andphylogenetic classification in the bacterial pathogenX. oryzae pv. oryzae, and found significant differences inaggressiveness between isolates of the same clonal lineage,and even between isolates of the same RFLP haplotype

within a clonal lineage, suggesting that mutations leadingto increased aggressiveness had rapidly accumulatedwithin the phylogenetic lineages.

Heritability of aggressiveness components

Heritability is defined as the proportion of phenotypicvariance attributable to genetic variance and can beestimated by different methods (Hamid et al., 1982a; Hill& Nelson, 1982; Kolmer & Leonard, 1986; Lehman &Shaner, 1996, 2007). Lehman & Shaner (1996) estimatedthe heritability of the latent period in P. triticina fromvariance analysis involving all possible combinations of

seven single-uredinial isolates on four wheat cultivarsexpressing different levels of quantitative resistance.Except on the most susceptible cultivar, on which allisolates responded equally, heritability values for thelatent period ranged from 0.28 to 0.76, depending on thecultivar tested. The greatest part (42–49%) of the variationamong isolates attributed to genetic factors was found oncultivar CI-13227. This result was later confirmed(Lehman & Shaner, 2007) by a selection experiment:heritability of the latent period was then about 0.70 oncultivar CI-13227 and 0.20 on another partially resistantcultivar. This suggests that heritability of aggressivenessstrongly depends on the genetics of the host–pathogeninteraction. Hill & Nelson (1982) estimated heritability of

several aggressiveness components in progeny populationsobtained from different crosses between five isolates of Cochliobolus heterostrophus race T on one maize line.Their estimates ranged between 0 and 0.6 for lesion length,0.23 and 0.52 for sporulation capacity and 0.21 and 0.58for infection efficiency. According to the authors, thelow heritability value for lesion length confirmed the lowgenetic variation within race T for this aggressivenesscomponent. In C. carbonum race 3, Hamid et al. (1982a)estimated lesion length heritability at 0.87, based on ananalysis of variance of crossed responses of 22 isolates on

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two corn inbred lines. However, Kolmer & Leonard(1986) commented that heritability values determinedfrom genetic responses in multiple environments weremore realistic than values determined by analysis of variance and based on restricted environmental variationand a limited number of phenotypes. They estimatedheritability of lesion length in C. heterostrophus race O in

an artificial selection experiment on a single corn line:starting with a set of bulk isolates, the largest lesionswere selected to constitute the following generation andthe rate of increase of mean lesion length throughoutgenerations was calculated by regression. On the basis of this method, a heritability value of 0.27 was estimatedfor lesion length.

Other authors evaluated the variability explained bygenotype vs. environment without formally calculatingheritability. In a study on P. infestans on artificial medium,Caten (1974) found that 83% of the total variationbetween isolates was of genetic origin. In a greenhousetrial with the bacterial pathogen X. oryzae pv. oryzae onrice, Mundt et al. (2002b) recorded 47–55% of the total

variation in aggressiveness measurements was accountedfor by genetic factors.

Differential interactions between isolates and cultivarsfor aggressiveness components

According to the original definition of aggressiveness(Van der Plank, 1963), variation for quantitative traitswas considered to occur among isolates, but withoutinteractions with the host genotypes (see Introduction).Nevertheless, many studies have shown that these kindsof interactions can be observed. Most of these studieswere undertaken to evaluate quantitative resistance in

host plants, but indirectly revealed differential interactionsbetween host and pathogen genotypes for quantitativetraits.

Using the pathosystem Hordeum vulgare–P. hordei,Parlevliet (1977) compared the latent period and infectionefficiency of five isolates on adult plants of three cultivars,both under controlled conditions and in the field. Thecultivar-by-isolate interaction was significant for thelatent period in both trials. With P. infestans on potato,Carlisle et al. (2002) found cultivar-by-isolate interactionsfor latent period, lesion expansion and sporulation capacity.Cultivar-by-isolate interactions were also found for infectionefficiency, latent period and sporulation capacity withP. triticina (Kuhn et al., 1978; Milus & Line, 1980;

Lehman & Shaner, 1996), for infection efficiency andsporulation capacity with B. graminis f.sp. tritici (Rouseet al., 1980), for infection efficiency with P. nodorum(Scharen & Eyal, 1983), and for lesion expansion withSeptoria musiva on poplar (Krupinsky, 1989). It shouldbe mentioned, however, that such interactions are notalways found: Van Ginkel & Scharen (1988) analysedthe responses of 14 wheat cultivars to 34 Septoria tritici(M. graminicola) isolates for lesion size (necrotic area) onseedlings. Significant differences were found among cultivarsand isolates, but with no significant interactions.

Cost of virulence: a trade-off between qualitativevirulence and aggressiveness

The cost of qualitative virulence is the reduction inpathogen fitness induced by a mutation from avirulenceto qualitative virulence. This concept was originallydeveloped by Van der Plank (1963) and has since been

widely discussed in the literature (see below). With thisconcept, changes in pathogen aggressiveness result directlyfrom the loss of avirulence gene function.

Estimating this fitness cost may be challenging because(i) fitness varies with experimental conditions (Weltz et al.,1990) and (ii) the effect of genetic background has to beeliminated (Østergård, 1987). When comparing aggres-siveness components of B. graminis f.sp. tritici isolatesdiffering in number of qualitative virulence genes,Menzies & MacNeill (1987) did not clearly distinguishwhich part of the reduction in fitness could be attributedto qualitative virulence genes or to isolate genetic back-grounds. Bronson & Ellingboe (1986) even showed bya progeny study that reduced fitness segregated inde-

pendently of the qualitative virulence loci.Some attempts to evaluate the cost of qualitative

virulence have remained inconclusive. In an artificialselection experiment with P. infestans on potato, a single-virulence pathotype was shown to predominate in apathotype mixture after two to nine successive generations(Thurston, 1961). However, in the field, this pathotypewas not always the most aggressive, and more complexpathotypes could be more frequent on a susceptiblecultivar. In a similar experiment with P. triticina on wheat,Kolmer (1993) found that even though pathogen fitnessseemed to sometimes be associated or dissociated withcertain individual qualitative virulences, no general

relationship could be established between the numberof unnecessary qualitative virulence factors and pathogenfitness.

Several authors, however, obtained fitness differencesbetween avirulent races and races carrying unnecessaryvirulence factors that could be clearly attributed to thecost of qualitative virulence. Because the effect of geneticbackground cannot be easily separated from the effectof the avirulence gene itself, these studies were based onindirect measurements. Measured values for virulencecost (reduction in aggressiveness) ranged between 14 and39% for P. graminis f.sp. avenae (Leonard, 1969), 12 and30% for C. heterostrophus, depending on the experimentalprocedure used (Leonard, 1977), 4 and 5.2% for P. graminis

f.sp. tritici (Grant & Archer, 1983), and 5.4 and 6.1% forB. graminis f.sp. hordei (Grant & Archer, 1983). The firstdirect evidence of a cost of virulence was obtained in thecausal agent of bacterial blight on rice (X. oryzae pv.oryzae) by comparing virulent and avirulent isogenic lines(Vera Cruz et al., 2000). Since then, the same result wasobtained with other cloned avirulence genes (Leachet al ., 2001).

Recent progress in plant pathogen genomics has shownthat mutations from avirulence to qualitative virulencemay stem from very different events, ranging from a

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single-base mutation to a large chromosome deletion(e.g. Gout et al., 2007). Depending on the function of thequalitative virulence gene, its redundancy in the genomeand the nature of the mutation, the cost for qualitativevirulence might vary from neutral to nearly lethal, thelatter obviously being not selected in field populations.Moreover, it has been shown with other biological systems

that fitness costs resulting from the acquisition of resistanceto antibiotics or insecticides (Levin et al., 2000; Schoustraet al., 2006; Labbé et al., 2007) can be progressivelycompensated for by subsequent mutations. Similarmechanisms could reduce the cost of virulence in plantpathogen populations, possibly explaining why pathotypescarrying multiple virulence genes can be present at highfrequencies and over long periods of time (e.g. Goyeauet al., 2006).

This link between qualitative virulence and aggre-ssiveness probably has considerable consequences onpathogen evolution, since genotypes which accumulate alarge number of qualitative virulence genes might neverbe the most aggressive on a given host (Thrall & Burdon,

2003).

Genetic correlations between quantitative traits

Genetic correlations between traits, either positive ornegative (trade-offs), should constrain quantitative traitevolution. Trade-offs between aggressiveness componentsor between aggressiveness and other life-history traitsshould therefore be of the utmost importance for pathogenadaptation. Nevertheless, there are surprisingly few datasetsavailable to show the existence of such trade-offs in fungalplant pathogens.

Trade-offs between aggressiveness and survival were

suggested in a study by Leonardet al. (1988) which showedthat C. carbonum presented a low aggressiveness level onmaize but a great survival ability, whereas C. heterostrophusexpressed high aggressiveness levels but a low survivalability. At the intra-species level, Carson (1998) foundevidence of a trade-off between C. heterostrophus lesionlength and survival rate on the soil surface during winter.In a recent study on P. infestans, Montarry et al. (2007)found no trade-off between aggressiveness (measured bycombining lesion size, sporulation and latent period) andoverwinter survival on potato tubers.

Correlations between aggressiveness components haverarely been investigated in fungal plant pathogens. Leonardet al. (1988) found that B. maydis race T, which produces

a host-specific toxin, quickly disappeared from thepathogen population when the host genotypes susceptibleto the toxin were removed from the host population,suggesting the existence of a trade-off between toxinproduction and fitness of the fungus. Authors oftenconsider that components of the pathogen life cycle relatedto aggressiveness are positively correlated, and sometimessuggest that they are under pleiotropic control (Ohm &Shaner, 1975; Milus & Line, 1980). For instance, Milus &Line (1980) found that long latent periods were associatedwith small lesion sizes in wheat leaf rust.

Adaptation for quantitative traits in pathogenpopulations

Most population studies on pathogen adaptation forquantitative traits deal with agricultural systems, butinteresting results have also been obtained with wild path-osystems. Four points are examined here: (i) selection for

aggressiveness mediated by climatic parameters; (ii) globalpopulation changes related to aggressiveness; (iii) adaptationto host cultivars for quantitative traits; and (iv) adaptationto identified quantitative resistances.

Adaptation to environmental conditions

Most studies linking aggressiveness components to theenvironment have aimed to understand quantitativeepidemic development in a range of environmentalsituations, only considering the species level. In somecases, however, it has been demonstrated that the relativefitness of different genotypes within the same pathogenspecies can vary according to environmental effects

(Eversmeyer et al., 1980; Johnson, 1980; Milus & Line,1980; Milus et al., 2006) and a few studies have attemptedto link pathogen population structures and climate.

Milus et al. (2006) demonstrated that better adaptationto warmer temperatures might explain the observedchanges in P. striiformis f.sp. tritici populations in the south-central USA around the year 2000. Under a controlledconditions trial, ‘new’ and ‘old’ isolates had similaraggressiveness levels at 12°C, whereas at 18°C the latentperiod was shortened by about 2 days for isolates fromthe ‘new’ population and germination rates were doubledcompared to the ‘old’ population. The authors concludedthat these differences may have contributed to the recently

expanded geographic range for P. striiformis. Similarly,Katsuya & Green (1967) explained the replacement of wheat stem rust (P. graminis) pathotype 15B by a newpathotype (56) in Canada by a differential effect of temperature. In a competition experiment performedunder controlled conditions, they showed that the relativefitness of these pathotypes was reversed between 15 and20°C, with the ‘new’ pathotype being more frequent athigher temperatures. It should be mentioned, however,that Katsuya & Green (1967) used a single isolate for eachpathotype and thus ignored the potential within-pathotypediversity.

These studies suggest that temperature may sometimeslead to large population shifts within a pathogen species.

However, more subtle effects can also operate in a localadaptation context. There is indeed evidence that theeffect of temperature on pathogen aggressiveness may affectparasite performance through genotype-by-environmentinteractions (Price et al., 2004; Laine, 2008). With a fitnessestimate based on latent period and spore production,Laine (2008) demonstrated that both the strength and thedirection of local adaptation of the powdery mildewfungus, Podosphaera plantaginis in a metapopulation of Plantago lanceolata could change with temperature.In particular, in one of the host subpopulations, the

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sympatric pathogen population was better adapted thanthe allopatric populations at 17°C, whereas it was clearlymaladapted at 23°C.

Changes in population structure related toaggressiveness

Major shifts in pathogen populations have sometimesbeen linked to invasion by a more aggressive population.One of the most well-documented situations is that of therelatively recent replacement of clonal lineage US-1 of P. infestans in the USA by new genotypes. Almost allisolates of this pathogen collected from the ColumbiaBasin, Idaho, in 1992 were of the US-1 genotype, whereas97% were identified as US-8 by 1995 (Miller et al., 1997).Miller et al. (1998) compared the aggressiveness level of 22 isolates from different clonal lineages, including sixUS-1 isolates and three US-8, on four potato cultivarswith different levels of quantitative resistance. They foundthat US-8 isolates had a higher lesion expansion rate, ahigher sporulation capacity and a shorter latent period

than US-1 isolates. Moreover, US-8 isolates rotted tuberslices faster than other isolates, confirming previousstudies (Lambert & Currier, 1997). From these data, theauthors concluded that relative differences in aggressive-ness may partially explain the shift in the P. infestanspopulation in the Columbia Basin from the US-1 to theUS-8 lineage. Even though they relied on a small numberof isolates (one to six per lineage), and despite significantintra-lineage variability, the quantitative differences betweenlineages presented by Miller et al. (1998) were consistentfor several aggressiveness components and were confirmedby other similar studies (e.g. Kato et al., 1997; Lambert &Currier, 1997) and studies investigating defence responses

by potato genotypes to virulent US-1 and US-8 genotypeisolates (e.g. Wang et al ., 2008). A comparable situationoccurred in Europe, where exotic P. infestans genotypesdisplaced the old population (mating type A1) in only afew years in the 1980s. Higher infection efficiency andspore production per lesion produced by new than by oldgenotypes was postulated by Day & Shattock (1997) toexplain the displacement. Interestingly, ‘old’ isolates wereclearly less aggressive on two cultivars with quantitativeresistance, but differences were less distinguishable on aless resistant cultivar. In addition to higher aggressiveness,resistance to the fungicide metalaxyl may have influencedthese population shifts (Day & Shattock, 1997; Miller et al.,1998).

Differential adaptation to host cultivars, related toquantitative traits, may sometimes influence the structureof pathogen populations. Goyeau et al. (2006) surveyedP. triticina populations in France between 1999 and 2002.On wheat cv. Soissons the pathogen was present at arelatively high frequency (9–15%) in the host populationand a single pathotype represented 30–60% of the pathogenpopulation, even though more than 10 other compatiblepathotypes were detected on the same cultivar, but atmuch lower frequencies. Since this pathotype distributionwas found only on cv. Soissons and on a closely related

cultivar, and lasted for several years, the authors hypoth-esized that a greater level of aggressiveness could explainthe dominance of a single pathotype. This hypothesis waslater confirmed in greenhouse experiments: the dominantpathotype had a shorter latent period, greater sporeproduction and larger lesion size on cv. Soissons than didother pathotypes (Pariaud et al ., 2007).

One of the clearest demonstrations of the centralimportance of aggressiveness to pathogen evolutionhas been made with the wild pathosystem Melampsoralini–Linum marginale by Thrall & Burdon (2003). Insouthern Australia, M. lini develops recurrent rustepidemics in an L. marginale metapopulation. In thissystem, the pathogen disperses more broadly than the hostand a pattern of local adaptation to the host populationhas been demonstrated. The authors showed a negativerelationship between aggressiveness (measured as sporeproduction per lesion) and average qualitative virulence(defined here as the average ability of a pathogen populationto overcome the diversity of resistance genes present inthe host population). This trade-off was identified as the

central cause preventing the most virulent pathotypes frominvading all host sub-populations and finally dominating thesystem. It is likely that such trade-offs between qualitativevirulence and aggressiveness play an important role ingenerating local adaptation in gene-for-gene systems byimpeding the emergence and evolution of pathotypes thatare both highly aggressive and capable of multiplying onall host genotypes.

Quantitative adaptation to host cultivars

Most of what we know about pathogen evolution inagricultural systems is based on qualitative gene-for-gene

virulence. However, it is now clear that selection for quan-titative traits influences pathogen evolution in agriculturalpathosystems, and it has been repeatedly demonstratedthat selection for quantitative traits can result in differentialadaptation to host cultivars. This was shown by artificialselection experiments (Leonard, 1969), but a differentialadaptation to the host of origin in field epidemics was alsodemonstrated (Ahmed et al., 1996).

Differential adaptation to host cultivars in artificial selection experimentsOne of the first studies of pathogen quantitative adaptationbased on artificial selection was published by Leonard(1969). He maintained a genetically heterogeneous popu-

lation of P. graminis f.sp. avenae on two different hostgenotypes for seven asexual generations and showed thatthe mean infection efficiency of the population hadincreased by approximately 10–15% at the end of theexperiment on the host on which it had been grown, butnot on the other one. Leonard’s results were later confirmedby two different studies. Chin & Wolfe (1984) sampledpowdery mildew (B. graminis f.sp. hordei) on two differentbarley cultivars grown either in pure stands or in mixture.When collected in pure stands, isolates had a highermultiplication rate (up to 22–24%) on the cultivar from

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which they were isolated than on the other one, but thisdid not occur when the cultivars were grown in mixture.This result was confirmed and extended in a field studywith wheat powdery mildew (B. graminis f.sp. tritici)by Villaréal & Lannou (2000). They demonstrated thatselection for quantitative traits operated in the pathogenpopulation on the scale of a single epidemic and resulted

in a higher aggressiveness level at the end of the cropseason on the host genotype on which the pathogenpopulation multiplied. They compared the averageinfection efficiency of a spontaneous B. graminis populationbefore and after seven successive pathogen generations onpure stands of two different cultivars, a mixture of both,or alternate stands of each cultivar. In this system, theaverage infection efficiency of the pathogen increased onthe pure stands, but did not significantly change in thehost mixture or when the cultivars were changed ateach pathogen generation (alternate stands). Moreover, insome plots, mixtures and alternate sowings tended to selectfor pathogen populations with identical aggressivenesslevels on both cultivars.

Differential adaptation to the host cultivar was tested inselection experiments with different pathosystems. Caten(1974) multiplied six isolates of P. infestans for successivegenerations on tubers from three potato cultivars andthen tested their growth capacity on tubers of the samecultivars. After six generations, and except for a resistantcultivar, pathogen aggressiveness increased by 10% inhomologous combinations (where source and test cultivarswere the same) compared to heterologous combinations.In other studies, however, experimental selection did notdemonstrate quantitative adaptation to the host (Alexanderet al., 1985; Kolmer, 1990).

Adaptation to the cultivar of originSeveral authors have investigated whether populationsisolated from a given cultivar in the field are more aggressiveon this cultivar than on others.

In both field and greenhouse experiments, Bonman et al.(1989) observed that Korean isolates of M. grisea inducedmore disease on japonica rice cultivars than Philippineisolates. Japonica cultivars are predominant in Korea,whereas indica cultivars are more frequent in thePhilippines. Since the isolates tested in this experimentproduced compatible reactions on all the cultivars tested, theauthors concluded that specificity in adaptation to geneticbackground was the primary cause of these differentialinteractions, underlining, however, that japonica and

indica rice cultivars represent different germplasms.Andrivon et al. (2007) obtained similar results in

P. infestans, comparing French and Moroccan populationson the potato cvs Bintje (prevalent in France, but notgrown in Morocco) and Désirée (popular in Morocco, butcultivated to a very small extent in France). French andMoroccan populations globally had greater lesion sizesand sporulation capacities on detached leaflets of cvsBintje and Désirée, respectively.

Similarly, Ahmed et al. (1995) found that M. graminicolaisolates from California induced more disease on Californian

than on Oregonian cultivars, while the reverse result wasobtained for Oregonian isolates. In another study, Ahmedet al. (1996) sampled M. graminicola isolates from winterwheat cultivars in field plots near crop maturity andmeasured their aggressiveness, defined by disease severity,on seedlings of the same wheat cultivars in the green-house. In two separate experiments, the linear contrast

between homologous (where source and test cultivars arethe same) and heterologous combinations was highlysignificant. On two susceptible cultivars, aggressivenesswas 17.2% greater in homologous than heterologouscombinations. The authors concluded that M. graminicolaisolates were better adapted to the host cultivar fromwhich they originated than to other cultivars. However, inanother study with the same pathosystem, Cowger &Mundt (2002) found only weak evidence that the fungalpopulation was subject to selection for greater aggressive-ness on its host of origin.

Some studies gave mixed results or found no evidenceat all for quantitative adaptation to the cultivar of origin.

Jeffrey et al. (1962) compared nine isolates of P. infestans

grown on potato tubers of three cultivars, including theircultivar of origin. They found evidence of adaptation tothe cultivar of origin for lesion growth rate, but not forlatent period. Knott & Mundt (1991) sampled populationsof P. triticina in field plots and tested their aggressivenessin a growth chamber on seedlings of the same cultivars,but found no evidence of increased infection efficiency orshortened latent period on the cultivar of origin. Similarly,Zhan et al. (2002) found no clear evidence of increasedlesion size for M. graminicola isolates on the wheat cultivarfrom which they were isolated.

This lack of clarity could partly result from the limitednumber of isolates tested (three in Bonman et al., 1989;

five in Zhan et al., 2002), which may not represent theoriginal population properly. In addition, since a differentialeffect between seedlings and adult plants was shown(Milus & Line, 1980), it is possible that seedling tests(Knott & Mundt, 1991; Zhan et al., 2002) may not revealquantitative differences in aggressiveness componentsselected on adult plants.

Adaptation to quantitative resistance

Among the studies on pathogen adaptation to hostcultivars, a few specifically refer to identified quantitativeresistances.

Lehman & Shaner (1997) studied adaptation of P. triticina

on a partially resistant cultivar in an artificial-selectionexperiment. They made an isolate population from 200–300 uredinia collected from volunteer seedlings in the field.The population was grown for five asexual generationsunder greenhouse conditions on adult plants of a wheatcultivar with quantitative resistance (determined by fourdifferent genes with unequal effects), then tested on fivedifferent cultivars, including three other partially resistantcultivars and a susceptible check. At each generation, atruncation selection procedure was applied: the sporesproduced by early erupting uredinia (lesions) were collected

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separately from those of later erupting uredinia. Thisresulted in strong selection for a shortened latent period.Before selection, the latent period was 4.3 days longer onthe resistant cultivar than on a susceptible control. Thisdifference was reduced to 2.3 days after selection, whichmeans that the selected population overcame 47% of the resistance. The authors estimated that the selected

population had overcome at least one of the resistancegenes with partial effects. It is interesting to note that thedata (Fig. 2 in their paper) suggested that the latent periodwas reduced on all resistant cultivars but did not changeon the susceptible control (this effect was not statisticallysignificant on the additional cultivars). This selection fora shorter latent period also changed spore productionper lesion, which increased on the resistant cultivar butdecreased on the susceptible check. These results wereglobally confirmed in a later experiment (Lehman &Shaner, 2007).

Kolmer & Leonard (1986) obtained an increased lesionsize in C. heterostrophus by artificial selection on maizecultivars with partial resistance. They studied successive

pathogen generations on five different cultivars and, ateach pathogen generation, they mated the seven (out of 25)most aggressive isolates, i.e. those showing the greatestlesion sizes. This resulted in a significant increase in lesionlength, both across all the cultivars tested (5–10%) andspecifically on the cultivar of selection (14%).

Clifford & Clothier (1974) sampled P. hordei isolateson three different cultivars and multiplied these fieldpopulations in the laboratory for between four and sevengenerations, on seedlings of the host of origin. One of thecultivars (Vada) was known to exhibit quantitativeresistance that reduced infection efficiency. This studyclearly showed a differential adaptation to the cultivar

of origin, with significant interactions between ‘isolatepopulation’ and cultivar. Moreover, populations multipliedon Vada showed increased infection efficiency on thiscultivar, as well as on the other cultivars. In this experiment,the increase in infectivity was associated with a decreasein spore production per lesion. However, given the densitydependence of spore production for such pathogens, it ispossible that the decrease in spore production simplyresulted from a density effect.

In order to evaluate the long-term durability of quan-titative resistance, it is of primary importance to understandhow the deployment of such resistance affects aggressivenessin pathogen populations. Very few reports have comparedthe selective effect of susceptible and quantitatively resistant

cultivars on pathogen populations. A theoretical model(Gandon & Michalakis, 2000) predicts that increasinglevels of quantitative host resistance will select for increasinglevels of damage caused by the parasite to its host(‘virulence’ as defined in ecology). An experimental studyby Cowger & Mundt (2002) was in accordance with thisprediction: changes in average aggressiveness (estimatedby disease severity) of M. graminicola were comparedduring field epidemics on six cultivars differing in theirresistance levels. It appeared that the highest levels of aggressiveness at the end of the epidemics were found on

the more resistant cultivars, and the data presented tendedto support the conclusion that resistant hosts select formore aggressive pathogens than susceptible hosts. In arecent study on the same pathosystem (Krenz et al., 2008),evidence for adaptation to Madsen, a quantitatively resistantwheat cultivar, remained equivocal because of an incon-sistency among results obtained in the different trials.

However, it was previously shown that the quantitativeresistance of this cultivar was gradually eroded (Mundtet al., 2002a), which, together with other studies (Ahmedet al., 1996; Zhan et al., 2002), suggests an adaptation of pathogen populations to Madsen’s quantitative resistance.

Results obtained with M. graminicola on the selectiveeffect exerted by quantitative resistance on a fungalpathogen are consistent with other reports on differentsystems. For example, potato cyst nematodes (Globodera

pallida) reared for 12 generations on four partially resistantpotato genotypes exhibited an increased reproductiverate, whereas those raised on susceptible potato cultivarsdid not (Phillips & Blok, 2008). Moreover, selectionwas specific to the source of resistance used: populations

selected on a particular source of resistance reproducedbetter on hosts with that source of resistance. Pink et al.(1992) suggested that the multiplication of lettuce mosaicvirus in lettuce (Lactuca sativa) cultivars with quantitativeresistance may have contributed to the emergence of moreaggressive viral strains.

It is interesting to note that a similar adaptation effectwas found in M. graminicola toward a multisite fungicide(Cowger & Mundt, 2002): isolates from sprayed plotswere more aggressive than isolates from unsprayed ones.The authors suggested that the multisite fungicide andquantitative host resistance exercised similar selectivepressures on the fungal populations.

Aggressiveness in an evolutionary perspective

Current uses of the term ‘aggressiveness’ in plant pathologyare operational for a discipline that primarily aims atreducing the impact of diseases on crop yield and quality.However, to understand how adaptation of pathogens totheir hosts and environments is translated in terms of aggressiveness, it is essential to be able to link the conceptof aggressiveness to other concepts used in evolutionaryepidemiology, i.e. fitness and virulence (Galvani, 2003).

Fitness is generally defined as the per capita rate of increase of an individual or a gene copy (Futuyma, 1997).It is frequently measured as the average number of

secondary infections produced from a single infected hostin the absence of density-dependent constraints [alsoknown as R0 (May & Anderson, 1983); see Salvaudonet al . (2007) for a plant pathogen application]. Althoughfocussing on among-host transmission seems natural formany animal pathogens, it may be more relevant in someplant pathogens to measure fitness as the average numberof secondary lesions produced from a single initial lesionin the absence of density-dependent constraints, includingalloinfection (among-host transmission) and autoinfection(within-host multiplication).

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In evolutionary epidemiology, as well as in animaland human epidemiology, and unlike in plant pathology,virulence is defined as the quantity of damage induced bya pathogen on its host, and is measured in units of hostfitness and/or mortality (Poulin & Combes, 1999; Readet al., 1999). Virulence is generally assumed to be a directconsequence of within-host pathogen multiplication,

although this direct causative relationship can be questioned(Day, 2002).Aggressiveness, because it describes the ability of a

pathogen to cause severe epidemics at the host populationscale, combines both notions of pathogen fitness andvirulence. Both fitter and more virulent pathogens aregenerally considered as more aggressive since they willcause faster epidemics or more damage to the host popu-lation, respectively. However, aggressiveness cannot beconsidered strictly equivalent to pathogen fitness. Fitness-related traits such as spore viability or inter-seasonalsurvival are not usually considered aggressiveness traits.Similarly, aggressiveness in plant pathology is not asynonym for virulence in evolutionary epidemiology since

many aggressiveness components (e.g. sporulation rate)do not quantify a decrease in host fitness or survival. Inaddition, other parameters that would be relevant tomeasuring pathogen virulence, such as decrease in hostphotosynthetic ability (usually larger than the effectaccounted for by lesion size, see Bastiaans, 1991) andinduced necrosis (pathogen-induced senescence, distinctfrom necrotic infected tissue, e.g. Magboul et al ., 1992)are not usually measured.

As seen above, aggressiveness can be broken down intoseveral components and each of these components islikely to evolve (e.g. Leonard, 1969; Kolmer & Leonard,1986; Lehman & Shaner, 1997, 2007). Recognizing that

aggressiveness results from the expression of elementaryquantitative components should make it possible tobenefit from the predictions of evolutionary epidemiologymodels. For instance, most of these theoretical approachesassume that within-host multiplication harms hosts (i.e.causes virulence), so that fitness results from a trade-off between pathogen transmission and virulence (Day, 2003;Galvani, 2003). As a consequence, aggressiveness com-ponents that are more closely related to transmission arenot expected to evolve under the same evolutionaryforces as aggressiveness components linked to virulence.Establishing the correspondence between aggressivenesscomponents, transmission and virulence is not alwayseasy, however. Lesion size can be related to virulence

(Bastiaans, 1991). The latent period may have a twofoldstatus, since a shorter latent period accelerates transmissionbut a longer latency could allow a greater development of the pathogen’s organs within host tissues and increase itsability to exploit the host. Infection efficiency, spore pro-duction rate and infectious period are transmission traits,but also participate in within-host multiplication throughautoinfection.

Some difficulties met in this analysis obviously come fromevolutionary epidemiology models making a distinctionbetween within- and among host scales, which is not

always relevant in plant pathology. Although manyanimal diseases are caused by parasites with systemiceffects that globally reduce the host viability, many plantparasites have localized effects and do not affect their hostin a systemic manner. This is particularly true for foliarparasites, for which it has been demonstrated that theeffect on the host is largely limited to a local reduction in

photosynthetic capacity (Bastiaans, 1991; Robert et al.,2004). However, the pathogen can increase dramaticallyon an infected host leaf through autoinfection (see Lannouet al., 2008), which is analogous to within-host multipli-cation in animal diseases. The consequence is that thecorrespondence between aggressiveness components,transmission and virulence depends on the scale con-sidered. At the scale of the lesion for instance, lesiongrowth may be considered as causing virulence (i.e. killinglocal host tissues), and other traits (infection efficiency, sporeproduction, etc.) would correspond to transmission.

Theoretical work on pathogen evolution progressesmuch faster than experimental work, and the lack of experimental evidence to evaluate theoretical predictions

and model hypotheses has been emphasized (Ebert &Bull, 2003). The growing body of experimental data onpathogen adaptation for quantitative traits, based on thestudy of crop pathogens, could offer opportunities to fillthis gap, provided that the traits measured are clearlylinked to parameters that underlie evolution.

The extent of phenotypic variability and of heritabilityof these traits is likely to radically condition the durabilityof resistant cultivars. Collecting more information onthe genetic architecture of aggressiveness componentscould bring valuable information for the development of quantitative resistance. Nonetheless, considering the hugeevolutionary potential of plant pathogens, the design

of quantitative resistance should take advantage of thepotential trade-offs between aggressiveness components,in order to enhance the sustainability of crop resistance.Such trade-offs would reflect the constraint for thepathogen to simultaneously invest in different traits,such as sporulation or within-host growth. It is there-fore most important that plant pathologists record, to thegreatest extent possible, all aggressiveness components inpathogen adaptation studies, and check for any negativecorrelations between them. Further study on the survivalof pathogens during intercropping, although difficult inmost pathosystems, would bring additional valuableinformation for both understanding pathogen evolutionand improving disease management.

A major question related to host resistance durabilityis to evaluate to what extent plant pathogens can be con-sidered specialists on a given host cultivar or generalists.It remains difficult at this time to produce an answer from theexperimental data presented above. Clifford & Clothier(1974) observed a non-specific increase of aggressivenessin P. hordei induced by repeated multiplication on a cultivarwith quantitative resistance, but other results obtained inartificial-selection experiments (Leonard, 1969; Chin &Wolfe, 1984; Villaréal & Lannou, 2000), as well as fielddata (Ahmed et al ., 1996), suggested that selection for

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Eversmeyer MG, Kramer CL, Browder LE, 1980. Effect of

temperature and host:parasite combination on the latent

period of Puccinia recondita in seedling wheat plants.

Phytopathology 70, 938–41.

FBPP, 1973. A Guide to the Use of Terms in Plant Pathology .

Kew, UK: Commonwealth Mycological Institute:

Phytopathological Papers No 17.

Flier WG, Turkensteen LJ, 1999. Foliar aggressiveness of

Phytophthora infestans in three potato growing regions in the

Netherlands. European Journal of Plant Pathology 105,

381–8.

Flor HH, 1955. Host-parasite interaction in flax rust. its genetics

and other implications. Phytopathology 45, 680–5.

Flor HH, 1971. Current status of the gene-for-gene concept.

Annual Review of Phytopathology 9, 275–96.

Futuyma DJ, 1997. Evolutionary Biology, 3rd edn. Sunderland,

MA, USA: Sinauer Associates.

Galvani AP, 2003. Epidemiology meets evolutionary ecology.

Trends in Ecology and Evolution 18, 132–9.

Gandon S, Michalakis Y, 2000. Evolution of parasite virulence

against qualitative or quantitative host resistance.

Proceedings of the Royal Society of London, Series B 267,

985–90.Gilbert J, Abramson D, McCallum B, Clear R, 2001.

Comparison of Canadian Fusarium graminearum isolates for

aggressiveness, vegetative compatibility, and production of

ergosterol and mycotoxins. Mycopathologia 153, 209–15.

Gilles T, Fitt BDL, McCartney HA, Papastamati K, Steed JM,

2001. The roles of ascospores and conidia of Pyrenopeziza

brassicae in light leaf spot epidemics on winter oilseed rape

(Brassica napus) in the UK. Annals of Applied Biology 138,

141–52.

Gout L, Kuhn ML, Vincenot L et al ., 2007. Genome structure

impacts molecular evolution at the AvrLm1 avirulence locus

of the plant pathogen Leptosphaeria maculans.

Environmental Microbiology 9, 2978–92.

Goyeau H, Park R, Schaeffer B, Lannou C, 2006. Distributionof pathotypes with regard to host cultivars in French wheat

leaf rust populations. Phytopathology 96, 264–73.

Grant MW, Archer SA, 1983. Calculation of selection

coefficients against unnecessary genes for virulence from field

data. Phytopathology 73, 547–51.

Halama P, Skajennikoff M, Dehorter B, 1999. Tetra analysis of

mating type, mutations, esterase and aggressiveness in

Phaeosphaeria nodorum. Mycological Research 103, 43–9.

Hamid AH, Ayers JE, Schein RD, Hill RR, 1982a. Components

of fitness attributes in Cochliobolus carbonum race 3.


Hamid AH, Ayers JE, Hill RR, 1982b. Host × isolate interaction

in corn inbreds inoculated with Cochliobolus carbonum race

3. Phytopathology 72, 1169–73.Hawthorne BT, Ball RD, Reesgeorge J, 1994. Genetic-analysis

of variation of pathogenicity in Nectria haematococca

(Fusarium solani) onCucurbita sp. Mycological Research 98,

1183–91.

Hill JP, Nelson RR, 1982. The heritability of three parasitic

fitness attributes of Helminthosporium maydis race

T. Phytopathology 72, 525–8.

Holliday P, 1998. A Dictionary of Plant Pathology. Cambridge,

UK: Cambridge University Press.

Hovmøller MS, Munk L, Østergård H, 1993. Observed and

predicted changes in virulence gene frequencies at 11 loci in

a local barley powdery mildew population. Phytopathology

83, 253–60.

Imhoff MW, Leonard KJ, Main CE, 1982. Pattern of bean rust

lesion size increase and spore production. Phytopathology 72,

441–6.

Jeffrey SIB, Jinks JL, Grindle M, 1962. Interracial variation in

Phytophthora infestans and field resistance to potato blight.

Genetica 32, 323–38.

Jensen B, Munk L, 1997. Nitrogen-induced changes in colony

density and spore production of Erysiphe graminis f.sp.

hordei on seedlings of six spring barley cultivars.

Plant Pathology 46, 191–202.

Jinks JL, Grindle M, 1963. Changes induced by training in

Phytophthora infestans. Heredity 18, 245–64.

Johnson DA, 1980. Effect of low temperature on the latent

period of slow and fast rusting winter wheat genotypes.

Plant Disease 64, 1006–8.

Kardin MK, Groth JV, 1989. Density-dependent fitness

interactions in the bean rust fungus. Phytopathology 79,

409–12.

Karolewski Z, Evans N, Fitt BDL, Todd AD, Baierl A, 2002.

Sporulation of Pyrenopeziza brassicae (light leaf spot) on

oilseed rape (Brassica napus) leaves inoculated withascospores or conidia at different temperatures and wetness

durations. Plant Pathology 51, 654–65.

Kato M, Mizubuti ES, Goodwin SB, Fry WE, 1997. Sensitivity

to protectant fungicides and pathogenic fitness of clonal

lineages of Phytophthora infestans in the United States.


Katsuya K, Green GJ, 1967. Reproductive potentials of races

15B and 56 of wheat stem rust. Canadian Journal of Botany

45, 1077–91.

Knott EA, Mundt CC, 1991. Latent period and infection

efficiency of Puccinia recondita f.sp. tritici populations

isolated from different wheat cultivars. Phytopathology 81,

435–9.

Kolmer JA, 1990. Selection of virulence phenotypes in aheterogeneous, asexual population of Puccinia recondita

f.sp. tritici. Phytopathology 80, 1377–81.

Kolmer JA, 1993. Selection in a heterogeneous population of

Puccinia recondita f.sp. tritici. Phytopathology 83, 909–14.

Kolmer JA, Leonard KJ, 1986. Genetic selection and adaptation

of Cochliobolus heterostrophus to corn hosts with partial

resistance. Phytopathology 76, 774–7.

Krenz JE, Sackett KE, Mundt CC, 2008. Specificity of

incomplete resistance to Mycosphaerella graminicola in

wheat. Phytopathology 98, 555–61.

Krupinsky JM, 1989. Variability in Septoria musiva in

aggressiveness. Phytopathology 79, 413–6.

Kuhn RC, Ohm HW, Shaner GE, 1978. Slow leaf-rusting

resistance in wheat against twenty-two isolates of Pucciniarecondita. Phytopathology 68, 651–6.

Labbé P, Berticat C, Berthomieu A et al ., 2007. Forty years

of erratic insecticide resistance evolution in the mosquito

Culex pipiens. PLoS Genetics 3, e205. doi:10.1371/

journal.pgen.0030205.

Laine AL, 2008. Temperature-mediated patterns of local

adaptation in a natural plant–pathogen metapopulation.

Ecology Letters 11, 327–37.

Lambert DH, Currier AI, 1997. Differences in tuber rot

development for North American clones of Phytophthora

infestans. American Potato Journal 74, 39–43.

8/8/2019 39661600




Lannou C, Mundt CC, 1997. Evolution of a pathogen

population in host mixtures: rate of emergence of complex

races. Theoretical and Applied Genetics 94, 991–9.

Lannou C, Soubeyrand S, Frezal L, Chadœuf J, 2008.

Autoinfection in wheat leaf rust epidemics. New Phytologist

177, 1001–11.

Leach JE, Vera Cruz CM, Bai J, Leung H, 2001. Pathogen fitness

penalty as a predictor of durability of disease resistance genes.

Annual Review of Phytopathology 39, 187–224.

Lehman JS, Shaner G, 1996. Genetic variation in latent period

among isolates of Puccinia recondita f.sp. tritici on partially

resistant wheat cultivars. Phytopathology 86, 633–41.

Lehman JS, Shaner G, 1997. Selection of populations of

Puccinia recondita f.sp. tritici for shortened latent period on

a partially resistant wheat cultivar. Phytopathology 87,

170–6.

Lehman JS, Shaner G, 2007. Heritability of latent period

estimated from wild-type and selected populations of Puccinia

triticina. Phytopathology 97, 1022–9.

Leonard KJ, 1969. Selection in heterogeneous populations of

Puccinia graminis f.sp. avenae. Phytopathology 59, 1851–7.

Leonard KJ, 1977. Virulence, temperature optima, and

competitive abilities of isolines of races T and O of Bipolarismaydis. Phytopathology 67, 1273–9.

Leonard KJ, Thakur RP, Leath S, 1988. Incidence of Bipolaris

and Exserohilum species in corn leaves in North Carolina.

Plant Disease 72, 1034–8.

Levin BR, Perrot V, Walker N, 2000. Compensatory mutations,

antibiotic resistance and the population genetics of adaptive

evolution in bacteria. Genetics 154, 985–97.

Lind M, Dalman K, Stenlid J, Karlsson B, Olson A, 2007.

Identification of quantitative trait loci affecting virulence in

the Basidiomycete Heterobasidion annosum s.l . Current

Genetics 52, 35–44.

Lovell DJ, Hunter T, Powers SJ, Parker SR, Van den Bosch F,

2004. Effect of temperature on latent period of septoria leaf

blotch on winter wheat under outdoor conditions.Plant Pathology 53, 170–81.

Magboul AM, Geng S, Gilchrist DG, Jackson LF, 1992.

Environmental influence on the infection of wheat by

Mycosphaerella graminicola. Phytopathology 82, 1407–13.

May RM, Anderson RM, 1983. Epidemiology and genetics in

the coevolution of parasites and hosts. Proceedings of the

Royal Society of London, Series B 219, 281–313.

Mehta YR, Zadoks JC, 1970. Uredospore production and

sporulation period of Puccinia recondita f.sp. triticina on

primary leaves of wheat. Netherlands Journal of Plant

Pathology 76, 267–76.

Menzies JG, MacNeill BH, 1987. Effect of unnecessary genes for

virulence on six components of parasitic fitness in Erysiphe

graminis f.sp. tritici. Canadian Journal of Plant Pathology 9,214–7.

Miller JS, Hamm PB, Johnson DA, 1997. Characterization of

the Phytophthora infestans population in the Columbia Basin

of Oregon and Washington from 1992 to 1995.


Miller JS, Johnson DA, Hamm PB, 1998. Aggressiveness of

isolates of Phytophthora infestans from the Columbia Basin

of Washington and Oregon. Phytopathology 88, 190–7.

Milus EA, Line RF, 1980. Characterization of resistance to leaf

rust in Pacific Northwest wheat lines. Phytopathology 70,

167–72.

Milus EA, Seyran E, McNew R, 2006. Aggressiveness of

Puccinia striiformis f.sp. tritici isolates in the south-central

States. Plant Disease 90, 847–52.

Montarry J, Corbière R, Andrivon D, 2007. Is there a trade-off

between aggressiveness and overwinter survival in

Phytophthora infestans? Functional Ecology 21, 603–10.

Mundt CC, Cowger C, Garrett KA, 2002a. Relevance of

integrated disease management to resistance durability.

Euphytica 124, 245–52.

Mundt CC, Nieva LP, Vera Cruz CM, 2002b. Variation for

aggressiveness within and between lineages of Xanthomonas

oryzae pv. oryzae. Plant Pathology 51, 163–8.

Ohm HW, Shaner GE, 1975. Segregation for slow leaf-rusting

in wheat. Agronomy Abstracts 67, 59.

Østergård H, 1987. Estimating relative fitness in asexually

reproducing plant pathogen populations. Theoretical and

Applied Genetics 74, 87–94.

Pariaud B, Robert C, Goyeau H, Lannou C, 2007. Quantitative

adaptation of wheat leaf rust populations (Puccinia triticina)

to a host cultivar and correlations between components of

aggressiveness. Phytopathology 97, S89.

Parlevliet JE, 1977. Evidence of differential interaction in the

polygenic Hordeum vulgare – Puccinia hordei relation duringepidemic development. Phytopathology 67, 776–8.

Parlevliet JE, 1993. What is durable resistance, a general outline.

In: Jacobs T, Parlevliet JE, eds. Durability of Disease

Resistance. Dordrecht, the Netherlands: Kluwer Academic

Publishers, 23–39.

Paxman GJ, 1963. Variation in Phytophthora infestans.

European Potato Journal 6, 14–23.

Phillips MS, Blok VC, 2008. Selection for reproductive ability in

Globodera pallida populations in relation to quantitative

resistance from Solanum vernei and S. tuberosum ssp.

andigena CPC2802. Plant Pathology 57, 573–80.

Pink DAC, Lot H, Johnson R, 1992. Novel pathotypes of lettuce

mosaic virus – breakdown of a durable resistance? Euphytica

63, 169–74.Poulin R, Combes C, 1999. The concept of virulence:

interpretations and implications. Parasitology Today 15,

474–5.

Price JS, Bever JD, Clay K, 2004. Genotype, environment,

and genotype by environment interactions determine

quantitative resistance to leaf rust (Coleosporium asterum)

in Euthamia graminifolia (Asteraceae). New Phytologist 162,

729–43.

Pringle A, Taylor JW, 2002. The fitness of filamentous fungi.

Trends in Microbiology 10, 474–81.

Read AF, Aaby P, Antia R et al ., 1999. Group report: what can

evolutionary biology contribute to understanding virulence?

In: Stearns SC, ed. Evolution in Health and Disease. Oxford,

UK: Oxford University Press, 205–15.Robert C, Bancal MO, Lannou C, 2004. Wheat leaf rust

uredospore production on adult plants: influence of leaf

nitrogen content and septoria tritici blotch. Phytopathology

94, 712–21.

Rouse DI, Nelson RR, MacKenzie DR, Armitage CR, 1980.

Components of rate-reducing resistance in seedlings of four

wheat cultivars and parasitic fitness in six isolates of Erysiphe

graminis f.sp. tritici. Phytopathology 70, 1097–100.

Sache I, 1997. Effect of density and age of lesions on sporulation

capacity and infection efficiency in wheat leaf rust (Puccinia

recondita f.sp. tritici). Plant Pathology 46, 581–9.

8/8/2019 39661600




Sackett KE, Mundt CC, 2005. The effects of dispersal gradient

and pathogen life cycle components on epidemic velocity in

computer simulations. Phytopathology 95, 992–1000.

Salvaudon L, Héraudet V, Shykoff JA, 2007. Genotype-specific

interactions and the trade-off between host and parasite

fitness. BMC Evolutionary Biology 7, 189.

Scharen AL, Eyal Z, 1983. Analysis of symptoms on spring and

winter wheat cultivars inoculated with different isolates of

Septoria nodorum. Phytopathology 73, 143–7.

Schlötterer C, 2003. Hitchhiking mapping – functional

genomics from the population genetics perspective.

Trends in Genetics 19, 32–8.

Schoustra SE, Slakhorst M, Debets AJM, Hoekstra RF, 2006.

Reducing the cost of resistance; experimental evolution in the

filamentous fungus Aspergillus nidulans. Journal of

Evolutionary Biology 19, 1115–27.

Shaner GE, 1980. Probits for analyzing latent period data in

studies of slow rusting resistance. Phytopathology 70, 1179–

82.

Shaw MW, 1990. Effects of temperature, leaf wetness and

cultivar on the latent period of Mycosphaerella graminicola

on winter wheat. Plant Pathology 39, 255–68.

Shurtleff MC, Averre CW, 1997. Glossary of Plant-Pathological Terms. St Paul, MN, USA: APS Press.

Singh RP, Huerta-Espino J, William HM, 2005. Genetics and

breeding for durable resistance to leaf and stripe rusts in

wheat. Turkish Journal of Agriculture and Forestry 29,

121–7.

Storz JF, 2005. Using genome scans of DNA polymorphism to

infer adaptive population divergence. Molecular Ecology 14,

671–88.

Subrahmanyam P, MacDonald D, Subba Rao PV, 1983.

Influence of host genotype on uredospore production and

germinability in Puccinia arachidis. Phytopathology 73,

726–9.

Thrall PH, Burdon JJ, 2003. Evolution of virulence in a plant

host-pathogen metapopulation. Science 299, 1735–7.Thurston HD, 1961. The relative survival ability of races of

Phytophthora infestans in mixtures. Phytopathology 51,

748–55.

Tiedemann AV, 1996. Single and combined effects of nitrogen

fertilization and ozone on fungal leaf diseases on wheat.

Journal of Plant Diseases and Protection 103, 409–19.

Tomerlin JR, Eversmeyer MG, Kramer CL, Browder LE, 1983.

Temperature and host effects on latent and infectious periods

and on urediniospore production of Puccinia recondita f.sp.

tritici. Phytopathology 73, 414–9.

Turechek WW, Stevenson KL, 1998. Effects of host resistance,

temperature, leaf wetness, and leaf age on infection and lesion

development of pecan scab. Phytopathology 88, 1294–301.

Van der Plank JE, 1963. Plant Diseases: Epidemics and Control .

New York, USA: Academic Press.

Van der Plank JE, 1968. Disease Resistance in Plants. New

York, USA: Academic Press.

Van Ginkel M, Scharen AL, 1988. Host-pathogen relationships

of wheat and Septoria tritici. Phytopathology 78, 762–6.

Vera Cruz CM, Bai J, Oña I et al ., 2000. Predicting durability of

a disease resistance gene based on an assessment of the fitness

loss and epidemiological consequences of avirulence gene

mutation. Proceedings of the National Academy of Sciences,

USA 97, 13500–5.

Villaréal LMM, Lannou C, 2000. Selection for increased spore

efficacy by host genetic background in a wheat powdery

mildew population. Phytopathology 90, 1300–6.Wang X, El Hadrami A, Adam LR, Daayf F, 2008. Differential

activation and suppression of potato defence responses by

Phytophthora infestans isolates representing US-1 and US-8

genotypes. Plant Pathology 57, 1026–37.

Weltz HG, Nagarajan S, Kranz J, 1990. Short-term virulence

dynamics of Erysiphe graminis f.sp. hordei in a single

epidemic on two susceptible barley cultivars. Zeitschrift für

Pflanzenkrankheiten und Pflanzenschutz 97, 250–62.

Xu JR, Peng YL, Dickman MB, Sharon A, 2006. The dawn of

fungal pathogen genomics. Annual Review of


Young ND, 1996. QTL mapping and quantitative disease

resistance in plants. Annual Review of Phytopathology 34,

479–501.Zhan J, Mundt CC, Hoffer ME, McDonald BA, 2002. Local

adaptation and effect of host genotype on the rate of pathogen

evolution: an experimental test in a plant pathosystem.

Journal of Evolutionary Biology 15, 634–47.

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