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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Sugarbeet and Potato Research » Research » Publications at this Location » Publication #380396

Research Project: Increasing Sugar Beet Productivity and Sustainability through Genetic and Physiological Approaches

Location: Sugarbeet and Potato Research

Title: Genome-wide association and selective sweep studies reveal the complex genetic architecture of DMI fungicide resistance in Cercospora beticola

item SPANNER, REBECCA - North Dakota State University
item TALIADOROS, DEMETRIS - Max Planck Institute For Evolutionary Biology
item RICHARDS, JONATHAN - Louisiana State University
item RIVERA-VARAS, VIVIANA - North Dakota State University
item Neubauer, Jonathan
item Natwick, Mari
item HAMILTON, OLIVIA - North Dakota State University
item VAGHEFI, NILOOFAR - University Of Southern Queensland
item PETHYBRIDGE, SARAH - Cornell University - New York
item SECOR, GARY - North Dakota State University
item Friesen, Timothy
item STUKENBROCK, EVA - Max Planck Institute For Evolutionary Biology
item Bolton, Melvin

Submitted to: Genome Biology and Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/5/2021
Publication Date: 9/9/2021
Citation: Spanner, R., Taliadoros, D., Richards, J., Rivera-Varas, V., Neubauer, J., Natwick, M.B., Hamilton, O., Vaghefi, N., Pethybridge, S., Secor, G.A., Friesen, T.L., Stukenbrock, E.H., Bolton, M.D. 2021. Genome-wide association and selective sweep studies reveal the complex genetic architecture of DMI fungicide resistance in Cercospora beticola. Genome Biology and Evolution. 13(9).

Interpretive Summary: Cercospora leaf spot is the most important disease of sugar beet worldwide. The disease is caused by the fungus Cercospora beticola and is managed principally by timely application of fungicides including those of the sterol demethylation inhibitor (DMI) class. However, reliance on DMIs has caused an increase in resistance to this class of fungicides across the world. In this research, we sequenced the genomes of nearly 200 strains of Cercospora. By comparing the genomes of fungicide-resistant strains against fungicide-sensitive strains, we were able to identify several genes important for fungicide resistance in this pathogen. The identification of genetic mutations linked to fungicide resistance will aid in the development of rapid detection strategies of fungicide-resistant Cercospora strains in the field. This information will help growers decide what fungicides to apply to manage this disease.

Technical Abstract: 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. vulgaris). 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 non-synonymous mutations (L144F, I387M and Y464S) 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.