Abstract

Resistance 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.

Details

Title
Exploiting long read sequencing to detect azole fungicide resistance mutations in Pyrenophora teres using unique molecular identifiers
Author
Zulak, Katherine G. 1 ; Farfan-Caceres, Lina 1 ; Knight, Noel L. 2 ; Lopez-Ruiz, Francisco J. 1 

 Curtin University, Centre for Crop and Disease Management, School of Molecular and Life Sciences, Bentley, Australia (GRID:grid.1032.0) (ISNI:0000 0004 0375 4078) 
 Curtin University, Centre for Crop and Disease Management, School of Molecular and Life Sciences, Bentley, Australia (GRID:grid.1032.0) (ISNI:0000 0004 0375 4078); University of Southern Queensland, Centre for Crop Health, Toowoomba, Australia (GRID:grid.1048.d) (ISNI:0000 0004 0473 0844) 
Pages
6285
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2957627274
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.