Population-level transposable element expression dynamics influence trait evolution in a fungal crop pathogen.

The rapid adaptive evolution of microbes is driven by strong selection pressure acting on genetic variation. How adaptive genetic variation is generated within species and how such variation influences phenotypic trait expression is often not well understood though. We focused on the recent activity of transposable elements (TEs) using deep population genomics and transcriptomics analyses of a fungal plant pathogen with a highly active content of TEs in the genome. Zymoseptoria tritici causes one of the most damaging diseases on wheat, with recent adaptation to the host and environment being facilitated by TE-associated mutations. We obtained genomic and RNA-sequencing data from 146 isolates collected from a single wheat field. We established a genome-wide map of TE insertion polymorphisms in the population by analyzing recent TE insertions among individuals. We quantified the locus-specific transcription of individual TE copies and found considerable population variation at individual TE loci in the population. About 20% of all TE copies show transcription in the genome suggesting that genomic defenses such as repressive epigenetic marks and repeat-induced polymorphisms are at least partially ineffective at preventing the proliferation of TEs in the genome. A quarter of recent TE insertions are associated with expression variation of neighboring genes providing broad potential to influence trait expression. We indeed found that TE insertions are likely responsible for variation in virulence on the host and potentially diverse components of secondary metabolite production. Our large-scale transcriptomics study emphasizes how TE-derived polymorphisms segregate even in individual microbial populations and can broadly underpin trait variation in pathogens.IMPORTANCEPathogens can rapidly adapt to new hosts, antimicrobials, or changes in the environment. Adaptation arises often from mutations in the genome; however, how such variation is generated remains poorly understood. We investigated the most dynamic regions of the genome of Zymoseptoria tritici, a major fungal pathogen of wheat. We focused on the transcription of transposable elements. A large proportion of the transposable elements not only show signatures of potential activity but are also variable within a single population of the pathogen. We find that this variation in activity is likely influencing many important traits of the pathogen. Hence, our work provides insights into how a microbial species can adapt over the shortest time periods based on the activity of transposable elements.

Genome-wide expression QTL mapping reveals the highly dynamic regulatory landscape of a major wheat pathogen.

BACKGROUND: In agricultural ecosystems, outbreaks of diseases are frequent and pose a significant threat to food security. A successful pathogen undergoes a complex and well-timed sequence of regulatory changes to avoid detection by the host immune system; hence, well-tuned gene regulation is essential for survival. However, the extent to which the regulatory polymorphisms in a pathogen population provide an adaptive advantage is poorly understood. RESULTS: We used Zymoseptoria tritici, one of the most important pathogens of wheat, to generate a genome-wide map of regulatory polymorphism governing gene expression. We investigated genome-wide transcription levels of 146 strains grown under nutrient starvation and performed expression quantitative trait loci (eQTL) mapping. We identified cis-eQTLs for 65.3% of all genes and the majority of all eQTL loci are within 2kb upstream and downstream of the transcription start site (TSS). We also show that polymorphism in different gene elements contributes disproportionally to gene expression variation. Investigating regulatory polymorphism in gene categories, we found an enrichment of regulatory variants for genes predicted to be important for fungal pathogenesis but with comparatively low effect size, suggesting a separate layer of gene regulation involving epigenetics. We also show that previously reported trait-associated SNPs in pathogen populations are frequently cis-regulatory variants of neighboring genes with implications for the trait architecture. CONCLUSIONS: Overall, our study provides extensive evidence that single populations segregate large-scale regulatory variation and are likely to fuel rapid adaptation to resistant hosts and environmental change.

Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen.

BACKGROUND: Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers between species and rapid evolutionary change within species. The acquisition, rearrangement, and deletion of gene clusters can generate significant metabolome diversity. However, the genetic basis underlying variation in SM production remains poorly understood. RESULTS: Here, we analyzed the metabolite production of a large population of the fungal pathogen of wheat, Zymoseptoria tritici. The pathogen causes major yield losses and shows variation in gene clusters. We performed untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry to profile the metabolite diversity among 102 isolates of the same species. We found substantial variation in the abundance of the detected metabolites among isolates. Integrating whole-genome sequencing data, we performed metabolite genome-wide association mapping to identify loci underlying variation in metabolite production (i.e., metabolite-GWAS). We found that significantly associated SNPs reside mostly in coding and gene regulatory regions. Associated genes encode mainly transport and catalytic activities. The metabolite-GWAS identified also a polymorphism in the 3'UTR region of a virulence gene related to metabolite production and showing expression variation. CONCLUSIONS: Taken together, our study provides a significant resource to unravel polymorphism underlying metabolome diversity within a species. Integrating metabolome screens should be feasible for a range of different plant pathogens and help prioritize molecular studies.