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Genome-Enhanced Detection and Identification (GEDI) of plant pathogens
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 gen...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5825881/ https://www.ncbi.nlm.nih.gov/pubmed/29492338 http://dx.doi.org/10.7717/peerj.4392 |
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author | 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. |
author_facet | 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. |
author_sort | Feau, Nicolas |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5825881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58258812018-02-28 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. PeerJ Genomics 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. PeerJ Inc. 2018-02-22 /pmc/articles/PMC5825881/ /pubmed/29492338 http://dx.doi.org/10.7717/peerj.4392 Text en http://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, made available under the Creative Commons Public Domain Dedication (http://creativecommons.org/publicdomain/zero/1.0/) . This work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Genomics 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. Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title | Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title_full | Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title_fullStr | Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title_full_unstemmed | Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title_short | Genome-Enhanced Detection and Identification (GEDI) of plant pathogens |
title_sort | genome-enhanced detection and identification (gedi) of plant pathogens |
topic | Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5825881/ https://www.ncbi.nlm.nih.gov/pubmed/29492338 http://dx.doi.org/10.7717/peerj.4392 |
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