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Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation
Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677323/ https://www.ncbi.nlm.nih.gov/pubmed/31335917 http://dx.doi.org/10.1371/journal.pcbi.1007208 |
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author | Seiler, Enrico Trappe, Kathrin Renard, Bernhard Y. |
author_facet | Seiler, Enrico Trappe, Kathrin Renard, Bernhard Y. |
author_sort | Seiler, Enrico |
collection | PubMed |
description | Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data. |
format | Online Article Text |
id | pubmed-6677323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66773232019-08-05 Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation Seiler, Enrico Trappe, Kathrin Renard, Bernhard Y. PLoS Comput Biol Research Article Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data. Public Library of Science 2019-07-23 /pmc/articles/PMC6677323/ /pubmed/31335917 http://dx.doi.org/10.1371/journal.pcbi.1007208 Text en © 2019 Seiler et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Seiler, Enrico Trappe, Kathrin Renard, Bernhard Y. Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title | Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title_full | Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title_fullStr | Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title_full_unstemmed | Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title_short | Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation |
title_sort | where did you come from, where did you go: refining metagenomic analysis tools for horizontal gene transfer characterisation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677323/ https://www.ncbi.nlm.nih.gov/pubmed/31335917 http://dx.doi.org/10.1371/journal.pcbi.1007208 |
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