Genome-Enhanced Detection and Identification (GEDI) of plant pathogens
Feau, Nicolas; Beauseigle, Stéphanie; Bergeron, Marie-Josée; Bilodeau, Guillaume J.; Birol, Inanc; Cervantes-Arango, Sandra; Dhillon, Braham; Dale, Angela L.; Herath, Padmini; Jones, Steven J.M.; Lamarche, Josyanne; Ojeda, Dario I.; Sakalidis, Monique L.; Taylor, Greg; Tsui, Clement K.M.; Uzunovic, Adnan; Yueh, Hesther; Tanguay, Philippe; Hamelin, Richard C. (2018-02-22)
Feau N, Beauseigle S, Bergeron M, Bilodeau GJ, Birol I, Cervantes-Arango S, Dhillon B, Dale AL, Herath P, Jones SJM, Lamarche J, Ojeda DI, Sakalidis ML, Taylor G, Tsui CKM, Uzunovic A, Yueh H, Tanguay P, Hamelin RC. (2018) Genome-Enhanced Detection and Identification (GEDI) of plant pathogens. PeerJ 6:e4392 https://doi.org/10.7717/peerj.4392
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Plant diseases caused by fungi and Oomycetes represent worldwide threats to crops and forest ecosystems. Effective prevention and appropriate management of emerging diseases rely on rapid detection and identification of the causal pathogens. The increase in genomic resources makes it possible to generate novel genome-enhanced DNA detection assays that can exploit whole genomes to discover candidate genes for pathogen detection. A pipeline was developed to identify genome regions that discriminate taxa or groups of taxa and can be converted into PCR assays. The modular pipeline is comprised of four components: (1) selection and genome sequencing of phylogenetically related taxa, (2) identification of clusters of orthologous genes, (3) elimination of false positives by filtering, and (4) assay design. This pipeline was applied to some of the most important plant pathogens across three broad taxonomic groups: Phytophthoras (Stramenopiles, Oomycota), Dothideomycetes (Fungi, Ascomycota) and Pucciniales (Fungi, Basidiomycota). Comparison of 73 fungal and Oomycete genomes led the discovery of 5,939 gene clusters that were unique to the targeted taxa and an additional 535 that were common at higher taxonomic levels. Approximately 28% of the 299 tested were converted into qPCR assays that met our set of specificity criteria. This work demonstrates that a genome-wide approach can efficiently identify multiple taxon-specific genome regions that can be converted into highly specific PCR assays. The possibility to easily obtain multiple alternative regions to design highly specific qPCR assays should be of great help in tackling challenging cases for which higher taxon-resolution is needed.
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