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PhyloSift: phylogenetic analysis of genomes and metagenomes

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analy...

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Detalles Bibliográficos
Autores principales: Darling, Aaron E., Jospin, Guillaume, Lowe, Eric, Matsen, Frederick A., Bik, Holly M., Eisen, Jonathan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897386/
https://www.ncbi.nlm.nih.gov/pubmed/24482762
http://dx.doi.org/10.7717/peerj.243
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author Darling, Aaron E.
Jospin, Guillaume
Lowe, Eric
Matsen, Frederick A.
Bik, Holly M.
Eisen, Jonathan A.
author_facet Darling, Aaron E.
Jospin, Guillaume
Lowe, Eric
Matsen, Frederick A.
Bik, Holly M.
Eisen, Jonathan A.
author_sort Darling, Aaron E.
collection PubMed
description Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).
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spelling pubmed-38973862014-01-30 PhyloSift: phylogenetic analysis of genomes and metagenomes Darling, Aaron E. Jospin, Guillaume Lowe, Eric Matsen, Frederick A. Bik, Holly M. Eisen, Jonathan A. PeerJ Bioinformatics Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454). PeerJ Inc. 2014-01-09 /pmc/articles/PMC3897386/ /pubmed/24482762 http://dx.doi.org/10.7717/peerj.243 Text en © 2014 Darling et al. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Bioinformatics
Darling, Aaron E.
Jospin, Guillaume
Lowe, Eric
Matsen, Frederick A.
Bik, Holly M.
Eisen, Jonathan A.
PhyloSift: phylogenetic analysis of genomes and metagenomes
title PhyloSift: phylogenetic analysis of genomes and metagenomes
title_full PhyloSift: phylogenetic analysis of genomes and metagenomes
title_fullStr PhyloSift: phylogenetic analysis of genomes and metagenomes
title_full_unstemmed PhyloSift: phylogenetic analysis of genomes and metagenomes
title_short PhyloSift: phylogenetic analysis of genomes and metagenomes
title_sort phylosift: phylogenetic analysis of genomes and metagenomes
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897386/
https://www.ncbi.nlm.nih.gov/pubmed/24482762
http://dx.doi.org/10.7717/peerj.243
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