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Since Dr Roy Johnson defined durable resistance 30 years ago (1981), breeding for durable plant resistance has remained a long-sought goal despite some progress in the understanding of factors that influence resistance durability in terms of both the pathogen and the host. McDonald & Linde (2002) suggested that the evolutionary potential of the pathogen is the main factor that determines resistance durability. Pathogen species with a mixed reproduction system, a high potential for gene flow, large effective population sizes and high mutation rates pose the greatest risk to overcome genetic resistance (McDonald & Linde, 2002). Other authors have investigated the potential for host resistance variation to determine evolutionary trajectories of pathogen populations. In natural systems, Thrall & Burdon (2003) demonstrated that the mean virulence, that is the average number of resistance genes overcome, of a pathogen population increases directly with the mean resistance of plant populations. Life history traits of the host, including host resistance, are essential factors for the determination of the evolution of the pathogen population, especially for obligate pathogens (Barrett et al., 2008). Two extreme categories of resistance are generally recognized: qualitative resistance conditioned by a single gene and quantitative resistance conditioned by multiple genes of partial effect. However, the distinction between these two categories is not straightforward and there is a ‘great deal of gray area’ between these extremes (Poland et al., 2009). In agroecosystems, genetically homogeneous crops with qualitative resistance facilitate strong directional selection on pathogen populations when they are planted over a large area, and can lead to resistance breakdown. The breakdown of major genes has been demonstrated in many pathosystems (Parisi et al., 1993; Bayles et al., 2000; Rouxel et al., 2003; Caffier & Laurens, 2005; Stokstad, 2007; Peressotti et al., 2010; Gladieux et al., 2011). Polygenic quantitative resistances based on several genes of partial effect (i.e. quantitative trait loci, QTLs) have been frequently considered to be broad-spectrum and have been empirically shown to be more durable (Parlevliet, 2002). Two hypotheses have been proposed to explain this extended durability. First, a pathogen would require the combination of a larger number of mutations in its genome to overcome polygenic resistance than to overcome monogenic resistance. Second, selection pressures exerted on the pathogen by quantitative resistance would be lower and distributed among several genes, which would reduce the risk of emergence of virulent variants from the pathogen population (Lindhout, 2002; Poland et al., 2009). The pyramiding of quantitative resistance factors with major resistance genes has also been shown recently to increase the durability of the latter resistance factors (Palloix et al., 2009; Brun et al., 2010).
Nevertheless, erosion of quantitative resistance over time following pathogen adaptation has been observed in some pathosystems (Abang et al., 2006; Montarry et al., 2006; Andrivon et al., 2007; Le Guen et al., 2007; Lehman & Shaner, 2007; Antonovics et al., 2011). Other authors have also shown that partially resistant cultivars exert directional selection on pathogen populations, but at a slower rate than the susceptible cultivar (Zhan et al., 2002; Sommerhalder et al., 2011). Such a weak selection could be the result of ‘minor-gene-for-minor-gene interaction’ proposed by Parlevliet & Zadoks (1977) to explain specific, despite partial, interactions observed between quantitative resistance and different pathogen isolates. Partially resistant hosts could therefore exert differential selection pressures on pathogens. Following a more theoretical approach, Gandon & Michalakis (2002) used a simulation model to demonstrate that quantitative resistance selects for more aggressive pathogens, leading to erosion of the resistance. It was assumed that all partially resistant host genotypes were infected by all pathogens, allowing within-host competition that selects for higher aggressiveness.
Many genetic mapping studies of disease resistance QTLs have been performed by independent inoculation of several pathogen isolates on a given mapping population. Such experiments have frequently shown strong isolate × QTL interactions, indicating isolate-specific (i.e. narrow-spectrum) resistance QTLs, as well as QTLs detected with all or most of the isolates, suggesting broad-spectrum resistance QTLs (Talukder et al., 2004; Jorge et al., 2005; Marcel et al., 2008). The spectrum of action of the resistance factors in the partially resistant cultivars is thought to be an important determinant of resistance durability (Kou & Wang, 2010). One of the putative mechanisms underlying quantitative resistance is the mutation of genes involved in basal resistance. Basal resistance is a broad-spectrum resistance and would be more difficult for a pathogen to evade and thus more durable (Poland et al., 2009). In the rice blast pathosystem, constitutive expression of defence is a ‘hallmark’ of partial resistance (Vergne et al., 2010). On the contrary, a narrow spectrum of action would imply a specific recognition system that could be more easily overcome by a pathogen following differential selection. It has not yet been demonstrated whether the pressures exerted by quantitative resistance are different according to the spectrum of action. More precisely, the identification of selection pressures exerted by individual resistance factors could make it possible to control virulence evolution by the management of host resistance through space and time (Palumbi, 2001; Sapoukhina et al., 2009).
There is a real lack of data at this time on the impact of quantitative resistance genes on the adaptation of pathogen populations, preventing plant breeders and landscape managers from proposing strategies for the choice of quantitative resistance combinations and to optimize their deployment. In this article, we have investigated the impact of apple quantitative resistances on the genetic composition of a mixed inoculum of Venturia inaequalis isolates. This pathosystem is particularly suited to the investigation of such questions. First, many quantitative resistance factors have been identified, including both specific and broad-spectrum QTLs of resistance (Calenge et al., 2004; Soufflet-Freslon et al., 2008). Second, this fungus has a great evolutionary potential, especially because of its mixed reproduction system (McDonald & Linde, 2002). Indeed, phylogeographic studies on V. inaequalis have demonstrated its great capacity to adapt to new environments (Gladieux et al., 2008, 2010; Lê Van et al., 2012). Another convincing example of adaptation was given by the breakdown in multiple orchards of the major resistance gene Rvi6 (Vf), widely used in apple breeding programmes (Gladieux et al., 2011).
Advances in molecular technology, such as the development of pyrosequencing, have permitted new insights into microorganism community composition (Benson et al., 2010). Quantitative measurement of the allele proportions of pathogen populations should make it possible to evaluate whether different plant genotypes exert differential selection pressures on a diverse pathogen population according to their resistance QTLs. Several isolates are generally inoculated independently to define the spectrum of action of the QTL. However, such practices are not adapted to the field situation, where isolates are in competition. The use of co-inoculated isolates is an alternative, but could lead to the identification of false broad-spectrum factors that are, in fact, resistance factors specific to the most competitive isolate in the mixture. Thus, we first investigated whether the definition of specific or broad-spectrum resistance QTLs is congruent when isolates are co-inoculated or inoculated independently. Second, using quantitative pyrosequencing technology, we evaluated whether host genotypes exert differential selection pressures on co-inoculated V. inaequalis isolates according to the spectrum of action of the resistance QTLs they carry. We hypothesized that broad-spectrum resistance does not exert differential selection, whereas narrow-spectrum resistance does. Evidence for this would be that broad-spectrum resistance factors do not select for particular isolates, whereas narrow-spectrum resistances decrease the frequencies of some isolates in the mixture relative to the susceptible host genotypes.