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Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution

Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to stu...

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Detalles Bibliográficos
Autores principales: Shapiro, Jason W., Putonti, Catherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874904/
https://www.ncbi.nlm.nih.gov/pubmed/29559574
http://dx.doi.org/10.1128/mBio.01870-17
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author Shapiro, Jason W.
Putonti, Catherine
author_facet Shapiro, Jason W.
Putonti, Catherine
author_sort Shapiro, Jason W.
collection PubMed
description Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network topology corresponds to host relatedness, how to find groups of genes with the strongest host-specific signatures, and how this perspective can complement phage host prediction tools. We discuss extensions of gene network analysis to predicting the emergence of phages on new hosts, as well as applications to features of phage biology beyond host range.
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spelling pubmed-58749042018-03-29 Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution Shapiro, Jason W. Putonti, Catherine mBio Research Article Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network topology corresponds to host relatedness, how to find groups of genes with the strongest host-specific signatures, and how this perspective can complement phage host prediction tools. We discuss extensions of gene network analysis to predicting the emergence of phages on new hosts, as well as applications to features of phage biology beyond host range. American Society for Microbiology 2018-03-20 /pmc/articles/PMC5874904/ /pubmed/29559574 http://dx.doi.org/10.1128/mBio.01870-17 Text en Copyright © 2018 Shapiro and Putonti. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Shapiro, Jason W.
Putonti, Catherine
Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title_full Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title_fullStr Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title_full_unstemmed Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title_short Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution
title_sort gene co-occurrence networks reflect bacteriophage ecology and evolution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874904/
https://www.ncbi.nlm.nih.gov/pubmed/29559574
http://dx.doi.org/10.1128/mBio.01870-17
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