Plant resistance (R) genes are a crucial component in plant defence against pathogens. Although R genes often fail to provide durable resistance in an agricultural context, they frequently persist as long-lived balanced polymorphisms in nature. Standard theory explains the maintenance of such polymorphisms through a balance of the costs and benefits of resistance and virulence in a tightly coevolving host-pathogen pair. However, many plant-pathogen interactions lack such specificity. Whether, and how, balanced polymorphisms are maintained in diffusely interacting species is unknown. Here we identify a naturally interacting R gene and effector pair in Arabidopsis thaliana and its facultative plant pathogen, Pseudomonas syringae. The protein encoded by the R gene RPS5 recognizes an AvrPphB homologue (AvrPphB2) and exhibits a balanced polymorphism that has been maintained for over 2 million years (ref. 3). Consistent with the presence of an ancient balanced polymorphism, the R gene confers a benefit when plants are infected with P. syringae carrying avrPphB2 but also incurs a large cost in the absence of infection. RPS5 alleles are maintained at intermediate frequencies in populations globally, suggesting ubiquitous selection for resistance. However, the presence of P. syringae carrying avrPphB is probably insufficient to explain the RPS5 polymorphism. First, avrPphB homologues occur at very low frequencies in P. syringae populations on A. thaliana. Second, AvrPphB only rarely confers a virulence benefit to P. syringae on A. thaliana. Instead, we find evidence that selection for RPS5 involves multiple non-homologous effectors and multiple pathogen species. These results and an associated model suggest that the R gene polymorphism in A. thaliana may not be maintained through a tightly coupled interaction involving a single coevolved R gene and effector pair. More likely, the stable polymorphism is maintained through complex and diffuse community-wide interactions.
Multihost pathogens occur widely on both natural and agriculturally managed hosts. Despite the importance of such generalists, evolutionary studies of host-pathogen interactions have largely focused on tightly coupled interactions between species pairs. We characterized resistance in a collection of Arabidopsis thaliana hosts, including 24 accessions collected from the Midwest USA and 24 from around the world, and patterns of virulence in a collection of Pseudomonas syringae strains, including 24 strains collected from wild Midwest populations of A. thaliana (residents) and 18 from an array of cultivated species (nonresidents). All of the nonresident strains and half of the resident strains elicited a resistance response on one or more A. thaliana accessions. The resident strains that failed to elicit any resistance response possessed an alternative type III secretion system (T3SS) that is unable to deliver effectors into plant host cells; as a result, these seemingly nonpathogenic strains are incapable of engaging in gene for gene interactions with A. thaliana. The remaining resident strains triggered greater resistance compared to nonresident strains, consistent with maladaptation of the resident bacterial population. We weigh the plausibility of two explanations: general maladaptation of pathogen strains and a more novel hypothesis whereby community level epidemiological dynamics result in adaptive dynamics favoring ephemeral hosts like A. thaliana.
Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases, genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits. Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms.
Ecological, evolutionary and molecular models of interactions between plant hosts and microbial pathogens are largely based around a concept of tightly coupled interactions between species pairs. However, highly pathogenic and obligate associations between host and pathogen species represent only a fraction of the diversity encountered in natural and managed systems. Instead, many pathogens can infect a wide range of hosts, and most hosts are exposed to more than one pathogen species, often simultaneously. Furthermore, outcomes of pathogen infection vary widely because host plants vary in resistance and tolerance to infection, while pathogens are also variable in their ability to grow on or within hosts. Environmental heterogeneity further increases the potential for variation in plant host-pathogen interactions by influencing the degree and fitness consequences of infection. Here, we describe these continua of specificity and virulence inherent within plant host-pathogen interactions. Using this framework, we describe and contrast the genetic and environmental mechanisms that underlie this variation, outline consequences for epidemiology and community structure, explore likely ecological and evolutionary drivers, and highlight several key areas for future research.
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