The role of recombination in rapid adaptive evolution of fungal plant pathogens: Integrating demographic models, inferences of natural selection and population recombination maps

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Antagonistic co-evolution between pathogens and their hosts can drive rapid adaptive changes in both partners. In this project we aim to understand the underlying mechanisms that drive rapid adaptation in two closely related fungal plant pathogenic species Zymoseptoria tritici (pathogen of cultivated wheat) and Zymoseptoria ardabiliae (pathogen of wild grasses). These two species differ not only in terms of host and environment (agro-ecosystem versus natural grassland) but also in terms of effective population size. We have previously shown that the effective population size is significantly higher in Z. tritici in spite of the strong directional selection pressure imposed to the pathogen in the wheat field. In the first phase of the SPP1819 we compared patterns of polymorphism and divergence to model the distribution of fitness effects across the genome of Z. tritici and to infer the proportion of adaptive mutations fixed by selection, α, as well as the overall rate of adaptation, ωA. In parallel, we used codon models of sequence evolution to detect genes evolving under balancing selection and to infer the strength of purifying selection acting on each gene. We furthermore correlated measures of adaptation with different parameters among others recombination rate, transposable element content, gene density and protein size. Based on α and ωA we find that adaptive evolution overall plays a strong role in protein evolution in Z. tritici and in particular affects genes encoding putative virulence factors. We also report a strong effect of recombination on the rate of adaptation, as well as pervasive background selection. In the second phase of the SPP we will further assess the impact of recombination on rapid adaptive evolution. We will do this by inferring the distribution of selective sweeps throughout the genome of Z. tritici and Z. ardabiliae using composite likelihood ratio (CLR) statistics. In this project we propose to develop new population genetic models that take the demography of the two plant pathogens species into account and include inferred genetic parameters and locus-specific recombination rates to infer maps of selective sweeps across the fungal genomes. This will allow us to compare the distribution of sweeps in the two species and rates of adaptive evolution. Finally, the project will investigate the underlining biological implications of rapid adaptive evolution by conducting functional analyses of selected candidate genes located in swept genome regions. In summary this project will provide novel insight into mechanisms of rapid adaptive evolution of plant pathogens, in particular the role of recombination rate variation. We will finally identify and describe the role of those genes that have experienced recent rapid adaptive evolution in these important plant pathogens.