Exploiting long read sequencing to detect azole fungicide resistance mutations in Pyrenophora teres using unique molecular identifiers

Article


Zulak, Katherine G., Farfan-Caceres, Lina, Knight, Noel L. and Lopez-Ruiz, Francisco J.. 2024. "Exploiting long read sequencing to detect azole fungicide resistance mutations in Pyrenophora teres using unique molecular identifiers." Scientific Reports. 14 (1). https://doi.org/10.1038/s41598-024-56801-z
Article Title

Exploiting long read sequencing to detect azole fungicide resistance mutations in Pyrenophora teres using unique molecular identifiers

ERA Journal ID201487
Article CategoryArticle
AuthorsZulak, Katherine G., Farfan-Caceres, Lina, Knight, Noel L. and Lopez-Ruiz, Francisco J.
Journal TitleScientific Reports
Journal Citation14 (1)
Article Number6285
Number of Pages13
Year2024
PublisherNature Publishing Group
Place of PublicationUnited Kingdom
ISSN2045-2322
Digital Object Identifier (DOI)https://doi.org/10.1038/s41598-024-56801-z
Web Address (URL)https://www.nature.com/articles/s41598-024-56801-z
AbstractResistance to fungicides is a global challenge as target proteins under selection can evolve rapidly, reducing fungicide efficacy. To manage resistance, detection technologies must be fast and flexible enough to cope with a rapidly increasing number of mutations. The most important agricultural fungicides are azoles that target the ergosterol biosynthetic enzyme sterol 14α-demethylase (CYP51). Mutations associated with azole resistance in the Cyp51 promoter and coding sequence can co-occur in the same allele at different positions and codons, increasing the complexity of resistance detection. Resistance mutations arise rapidly and cannot be detected using traditional amplification-based methods if they are not known. To capture the complexity of azole resistance in two net blotch pathogens of barley we used the Oxford Nanopore MinION to sequence the promoter and coding sequence of Cyp51A. This approach detected all currently known mutations from biologically complex samples increasing the simplicity of resistance detection as multiple alleles can be profiled in a single assay. With the mobility and decreasing cost of long read sequencing, we demonstrate this approach is broadly applicable for characterizing resistance within known agrochemical target sites.
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020300409. Crop and pasture protection (incl. pests, diseases and weeds)
Byline AffiliationsCurtin University
Centre for Crop Health
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