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Besides well-known grapevine trunk disease (GTD)-related pathogens, there is an increased interest in wood-colonizing fungi that infect grapevines. During 2017-2018, a survey was conducted in Cyprus and wood samples were collected from vines exhibiting typical GTD symptoms. Based on morphological and multilocus phylogenetic analyses (ITS, LSU

Cercospora beticola is a hemibiotrophic fungus that causes cercospora leaf spot disease of sugar beet (Beta vulgaris). After an initial symptomless biotrophic phase of colonization, necrotic lesions appear on host leaves as the fungus switches to a necrotrophic lifestyle. The phytotoxic secondary metabolite cercosporin has been shown to facilitate fungal virulence for several Cercospora spp. However, because cercosporin production and subsequent cercosporin‐initiated formation of reactive oxygen species is light‐dependent, cell death evocation by this toxin is only fully ensured during a period of light. Here, we report the discovery of the effector protein CbNip1 secreted by C. beticola that causes enhanced necrosis in the absence of light and, therefore, may complement light‐dependent necrosis formation by cercosporin. Infiltration of CbNip1 protein into sugar beet leaves revealed that darkness is essential for full CbNip1‐triggered necrosis, as light exposure delayed CbNip1‐triggered host cell death. Gene expression analysis during host infection shows that CbNip1 expression is correlated with symptom development in planta. Targeted gene replacement of CbNip1 leads to a significant reduction in virulence, indicating the importance of CbNip1 during colonization. Analysis of 89 C. beticola genomes revealed that CbNip1 resides in a region that recently underwent a selective sweep, suggesting selection pressure exists to maintain a beneficial variant of the gene. Taken together, CbNip1 is a crucial effector during the C. beticola–sugar beet disease process., The fungus Cercospora beticola secretes necrosis‐inducing molecules during infection of sugar beet that are optimized to be fully functional during the day or night.

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 nonsynonymous 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.

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 in multiple C. beticola populations. To better understand the genetic and evolutionary basis for resistance in C. beticola, a genome-wide association study (GWAS) and selective sweep analysis were conducted for the first time in this fungal plant pathogen. We performed whole genome resequencing of 190 C. beticola isolates predominantly from North Dakota and Minnesota that were phenotyped for sensitivity to tetraconazole, the most widely used DMI fungicide in this region. GWAS identified mutations in genes associated with DMI fungicide resistance including a Regulator of G-protein Signaling (RGS) protein, an ATP-binding cassette (ABC) pleiotropic drug resistance transporter, a dual-specificity tyrosine phosphorylation-regulated kinase (DYRK), and a gene annotated as a hypothetical protein. A SNP upstream of CbCYP51, the gene encoding the target of DMI fungicides, was also identified via GWAS. Haplotype analysis of CbCYP51 identified a synonymous mutation (E170) in high linkage disequilibrium with the upstream SNP, and multiple non-synonymous mutations (L144F, I387M and Y464S) associated with DMI resistance. Additionally, a putative codon bias effect for the L144F substitution was identified that generated different resistance potentials. We also identified a CbCYP51 paralog in C. beticola, CbCYP51-like, with high protein homology to CYP51C found uniquely in Fusarium species but CbCYP51-like does not appear to influence DMI sensitivity. 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 suggesting that resistance mutations can persist in C. beticola populations. 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.