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Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution
Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlig...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289978/ https://www.ncbi.nlm.nih.gov/pubmed/28217138 http://dx.doi.org/10.3389/fpls.2017.00119 |
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author | Plissonneau, Clémence Benevenuto, Juliana Mohd-Assaad, Norfarhan Fouché, Simone Hartmann, Fanny E. Croll, Daniel |
author_facet | Plissonneau, Clémence Benevenuto, Juliana Mohd-Assaad, Norfarhan Fouché, Simone Hartmann, Fanny E. Croll, Daniel |
author_sort | Plissonneau, Clémence |
collection | PubMed |
description | Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution. |
format | Online Article Text |
id | pubmed-5289978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52899782017-02-17 Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution Plissonneau, Clémence Benevenuto, Juliana Mohd-Assaad, Norfarhan Fouché, Simone Hartmann, Fanny E. Croll, Daniel Front Plant Sci Plant Science Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution. Frontiers Media S.A. 2017-02-03 /pmc/articles/PMC5289978/ /pubmed/28217138 http://dx.doi.org/10.3389/fpls.2017.00119 Text en Copyright © 2017 Plissonneau, Benevenuto, Mohd-Assaad, Fouché, Hartmann and Croll. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Plissonneau, Clémence Benevenuto, Juliana Mohd-Assaad, Norfarhan Fouché, Simone Hartmann, Fanny E. Croll, Daniel Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title | Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title_full | Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title_fullStr | Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title_full_unstemmed | Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title_short | Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution |
title_sort | using population and comparative genomics to understand the genetic basis of effector-driven fungal pathogen evolution |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289978/ https://www.ncbi.nlm.nih.gov/pubmed/28217138 http://dx.doi.org/10.3389/fpls.2017.00119 |
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