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<p>Plant-pathogenic microorganisms, including the wheat fungal pathogen <i>Zymoseptoria tritici</i>, adapt to their host environment. In plants, genome-wide association studies (GWAS) have been extensively used to uncover the complexity of local adaptation and disease resistance. However, the application of GWAS to decipher the mechanisms underlying fungal pathogenicity and host adaptation trails far behind. Here we established a genome–host association approach to infer statistical associations between pathogen allele frequencies and host of origin for 832 fungal strains isolated from 12 different host cultivars during a natural field epidemic. We identified 2 to 20 genes associated with specialization to the different wheat cultivars, including one known effector gene, <i>Avr3D1</i>, as well as ten pathogenicity-related genes that provided a proof of concept for our genome–host association approach. Our study highlights the polygenic genetic architecture of host adaptation and provides a new application of GWAS in plant pathogens that transcends the limitations imposed by traditional phenotyping methods.</p>

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Genome–host association mapping reveals wheat pathogen genes involved in host specialization

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Cécile Lorrain,
  • Alice Feurtey,
  • Julien Alassimone,
  • Bruce A. McDonald

摘要

Plant-pathogenic microorganisms, including the wheat fungal pathogen Zymoseptoria tritici, adapt to their host environment. In plants, genome-wide association studies (GWAS) have been extensively used to uncover the complexity of local adaptation and disease resistance. However, the application of GWAS to decipher the mechanisms underlying fungal pathogenicity and host adaptation trails far behind. Here we established a genome–host association approach to infer statistical associations between pathogen allele frequencies and host of origin for 832 fungal strains isolated from 12 different host cultivars during a natural field epidemic. We identified 2 to 20 genes associated with specialization to the different wheat cultivars, including one known effector gene, Avr3D1, as well as ten pathogenicity-related genes that provided a proof of concept for our genome–host association approach. Our study highlights the polygenic genetic architecture of host adaptation and provides a new application of GWAS in plant pathogens that transcends the limitations imposed by traditional phenotyping methods.