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Quantitative pathogenicity and host adaptation in a fungal plant pathogen revealed by whole-genome sequencing | Nature Communications
www.nature.comKnowledge of genetic determinism and evolutionary dynamics mediating host-pathogen interactions is essential to manage fungal plant diseases. Studies on the genetic architecture of fungal pathogenicity often focus on large-effect effector genes triggering strong, qualitative resistance. It is not clear how this translates to predominately quantitative interactions. Here, we use the Zymoseptoria tritici-wheat model to elucidate the genetic architecture of quantitative pathogenicity and mechanisms mediating host adaptation. With a multi-host genome-wide association study, we identify 19 high-confidence candidate genes associated with quantitative pathogenicity. Analysis of genetic diversity reveals that sequence polymorphism is the main evolutionary process mediating differences in quantitative pathogenicity, a process that is likely facilitated by genetic recombination and transposable element dynamics. Finally, we use functional approaches to confirm the role of an effector-like gene and a methyltransferase in phenotypic variation. This study highlights the complex genetic architecture of quantitative pathogenicity, extensive diversifying selection and plausible mechanisms facilitating pathogen adaptation. The understanding of pathogenicity in quantitative plant pathosystems remains limited. This study reveals the genetic architecture of quantitative pathogenicity traits in a significant fungal plant pathogen, shedding light on potential evolutionary mechanisms involved in host adaptation.
ELI5.
In plant/pathogen interactions there are two main groups of resistance.
Qualitative- A few genes that inhibit the pathogen almost completely. The pathogen is classified by these resistant genes into races. This is the type of genetics most of you learned with Punnet Squares in school.
Quantitative- what this paper is about. Many genes act in an complex interlinked fashion to control a disease. These genes can be located in groups or scattered around the genome. This has made creating usable molecular markers extremely difficult for breedings efforts. Traditionally you figure out molecular markers by running a few thousand of them and then using statistical models to correlate where the observed phenotype is linked to in the genome. It works really well for 1-2 gene traits. Not very well for 10+ gene traits.
This is basically the researchers saying “fuck it” we’ll just sequence the entire genomes to figure this one out.