Evolutionary and population genomics of the wheat pathogen Parastagonospora nodorum

Food production is continuously under threat by plant pathogens. In the agricultural system, pathogen populations are under high selection pressure, and yet demonstrate high adaptive potential to overcome changing conditions. The genetic variation and genomic mechanisms underpinning the fast evolutionary rates in pathogen populations are poorly understood. In this thesis, I studied the genetic basis of adaptation in populations of Parastagonospora nodorum, a major pathogen wheat. We sequenced complete genomes of 172 isolates sampled from important wheat growing regions worldwide, including Oregon, Texas, and New York (United States), Switzerland, Iran, South Africa, and Australia. These populations were sampled between 1991 and 2010 and incorporate a wide range of climatic conditions and agricultural practices. First, I tested the hypothesis of natural selection causing population divergence for local adaptation. I performed a common-garden experiment to collect precise quantitative phenotypic estimates of growth rates and melanization under a range of fungicide concentrations and temperatures. Phenotypic variation was used to estimate population differentiation for quantitative traits among populations (QST). The population genetic differentiation (FST) was calculated based on 50,000 neutral single nucleotide polymorphism (SNPs) markers. Employing a QST – FST comparison, I found that growth rates at 30°C and fungicide resistance estimates were under diversifying selection among populations while balancing selection was predominant for growth rates at 18°C and 24°C, as well for melanization. I found evidence for phenotypic trade-offs between growth rates and melanization at 30°C. Next, I investigated the genetic basis underlying variation for fungicide resistance. I show that non-synonymous mutations in the target gene CYP51 are linked to increased fungicide resistance against demethylation inhibitors. Furthermore, I performed a genome-wide association study to map phenotypic variation to a SNP dataset of 436,365 genome-wide bi-allelic markers, which unveiled novel resistance determinants. I found 34 significantly associated SNPs, including CYP51 and a novel major facilitator superfamily (MFS) linked to fungicide variation. The increase in resistance as determined by the joint effects of the MFS and CYP51 mutations occurred in a non-additive manner. I found no evidence for genetic trade-offs constraining fungicide resistance evolution. Finally, I included additional genome sequences totalling 366 strains to resolve the population structure of P. nodorum and investigate transposable elements (TEs) as drivers of genetic variation. I corroborate that populations are highly admixed, harbor high genetic diversity, and show evidence for frequent sexual recombination. Interestingly, despite robust genomic defenses called repeat induced-point (RIP) mutations, I found evidence for recently inserted TEs across the genome. I found no support that genetic bottlenecks incurred a TE burst among populations in P. nodorum. Moreover, TE copy number expansion was driven by miniature TEs as shown by a high GC content indicating an escape from RIP mutations. Overall, this PhD thesis demonstrates the potential of population genomics in unveiling evolutionary forces driving pathogen adaptation, as well as the genetic basis of adaptation and different sources of genetic novelty among populations