Genome-Wide Association and Selective Sweep Studies Reveal the Complex Genetic Architecture of DMI Fungicide Resistance in Cercospora beticola

The rapid and widespread evolution of fungicide resistance remains a challenge for crop disease management. The demethylation inhibitor (DMI) class of fungicides is a widely used chemistry for managing disease, but there has been a gradual decline in efficacy in many crop pathosystems. Reliance on DMI fungicides has increased resistance in populations of the plant pathogenic fungus Cercospora beticola worldwide. To better understand the genetic and evolutionary basis for DMI resistance in C. beticola, a genome-wide association study (GWAS) and selective sweep analysis were conducted for the first time in this species. We performed whole-genome resequencing of 190 C. beticola isolates infecting sugar beet (Beta vulgaris ssp. volgaris). All isolates were phenotyped for sensitivity to the DMI tetraconazole. Intragenic markers on chromosomes 1, 4, and 9 were significantly associated with DMI fungicide resistance, including a polyketide synthase gene and the gene encoding the DMI target CbCYP51. Haplotype analysis of CbCYP51 identified a synonymous mutation (E170) and nonsynonymous mutations (L144F, 1387M, and Y4645) associated with DMI resistance. Genome-wide scans of selection showed that several of the GWAS mutations for fungicide resistance resided in regions that have recently undergone a selective sweep. Using radial plate growth on selected media as a fitness proxy, we did not find a trade-off associated with DMI fungicide resistance. Taken together, we show that population genomic data from a crop pathogen can allow the identification of mutations conferring fungicide resistance and inform about their origins in the pathogen population.

Automated summary

The rapid and widespread evolution of fungicide resistance poses a challenge for crop disease management. Research on genetic mutations conferring fungicide resistance in plant pathogenic fungi can be identified through genome-wide studies and selective sweep analysis.