University of Oulu

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

Genome-Enhanced Detection and Identification (GEDI) of plant pathogens

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Author: Feau, Nicolas1; Beauseigle, Stéphanie2; Bergeron, Marie-Josée3;
Organizations: 1Department of Forest and Conservation Sciences, Forest Sciences Centre, University of British Columbia
2Biopterre, Sainte-Anne-de-la-Pocatière
3Canadian Forest Service, Natural Resources Canada
4Ottawa Plant Laboratory, Canadian Food Inspection Agency
5BC Cancer agency, Genome Sciences Centre
6Department of Plant Pathology, University of Arkansas at Fayetteville
8Department of Medical Genetics, University of British Columbia
9Department of Molecular Biology and Biochemistry, Simon Fraser University
10Department of Biology Unit of Ecology and Genetics, University of Oulu
11Department of Plant, Soil & Microbial Sciences and Department of Forestry, Michigan State University
12Faculty of Medicine, University of British Columbia
13Foresterie et géomatique, Institut de Biologie Intégrative des Systèmes, Laval University
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.9 MB)
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Language: English
Published: PeerJ, 2018
Publish Date: 2018-08-06


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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Series: PeerJ
ISSN: 2167-8359
ISSN-E: 2167-8359
ISSN-L: 2167-8359
Volume: 6
Article number: e4392
DOI: 10.7717/peerj.4392
Type of Publication: A1 Journal article – refereed
Field of Science: 1181 Ecology, evolutionary biology
Funding: This work was funded by Genome Canada, Genome British Columbia, the Canadian Forest Service (Genomics Research and Development Initiative, GRDI), Canadian Food Inspection Agency, FP Innovations and Boreal Genomics through a Large Scale Applied Research Project (LSARP 2112; Genome Canada) grant.
Copyright information: This is an open access article, free of all copyright, made available under the Creative Commons Public Domain Dedication. This work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.