Reconstruction of Ribosomal RNA Genes from Metagenomic Data
Identifieur interne : 000331 ( Ncbi/Merge ); précédent : 000330; suivant : 000332Reconstruction of Ribosomal RNA Genes from Metagenomic Data
Auteurs : Lu Fan ; Kerensa Mcelroy ; Torsten ThomasSource :
- PLoS ONE [ 1932-6203 ] ; 2012.
Abstract
Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.
Url:
DOI: 10.1371/journal.pone.0039948
PubMed: 22761935
PubMed Central: 3384625
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Reconstruction of Ribosomal RNA Genes from Metagenomic Data</title><author><name sortKey="Fan, Lu" sort="Fan, Lu" uniqKey="Fan L" first="Lu" last="Fan">Lu Fan</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Mcelroy, Kerensa" sort="Mcelroy, Kerensa" uniqKey="Mcelroy K" first="Kerensa" last="Mcelroy">Kerensa Mcelroy</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Thomas, Torsten" sort="Thomas, Torsten" uniqKey="Thomas T" first="Torsten" last="Thomas">Torsten Thomas</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22761935</idno><idno type="pmc">3384625</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384625</idno><idno type="RBID">PMC:3384625</idno><idno type="doi">10.1371/journal.pone.0039948</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">000606</idno><idno type="wicri:Area/Pmc/Curation">000606</idno><idno type="wicri:Area/Pmc/Checkpoint">000383</idno><idno type="wicri:Area/Ncbi/Merge">000331</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Reconstruction of Ribosomal RNA Genes from Metagenomic Data</title><author><name sortKey="Fan, Lu" sort="Fan, Lu" uniqKey="Fan L" first="Lu" last="Fan">Lu Fan</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Mcelroy, Kerensa" sort="Mcelroy, Kerensa" uniqKey="Mcelroy K" first="Kerensa" last="Mcelroy">Kerensa Mcelroy</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Thomas, Torsten" sort="Thomas, Torsten" uniqKey="Thomas T" first="Torsten" last="Thomas">Torsten Thomas</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Pace, Nr" uniqKey="Pace N">NR Pace</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Tringe, Sg" uniqKey="Tringe S">SG Tringe</name></author><author><name sortKey="Hugenholtz, P" uniqKey="Hugenholtz P">P Hugenholtz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hong, S" uniqKey="Hong S">S Hong</name></author><author><name sortKey="Bunge, J" uniqKey="Bunge J">J Bunge</name></author><author><name sortKey="Leslin, C" uniqKey="Leslin C">C Leslin</name></author><author><name sortKey="Jeon, S" uniqKey="Jeon S">S Jeon</name></author><author><name sortKey="Epstein, Ss" uniqKey="Epstein S">SS Epstein</name></author></analytic></biblStruct><biblStruct><analytic><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">22761935</article-id><article-id pub-id-type="pmc">3384625</article-id><article-id pub-id-type="publisher-id">PONE-D-12-14610</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0039948</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biology</subject><subj-group><subject>Computational Biology</subject><subj-group><subject>Sequence Analysis</subject></subj-group></subj-group><subj-group><subject>Ecology</subject><subj-group><subject>Microbial Ecology</subject></subj-group></subj-group><subj-group><subject>Evolutionary Biology</subject><subj-group><subject>Evolutionary Systematics</subject><subj-group><subject>Taxonomy</subject><subj-group><subject>Microbial Taxonomy</subject></subj-group></subj-group></subj-group></subj-group><subj-group><subject>Genomics</subject><subj-group><subject>Metagenomics</subject></subj-group></subj-group><subj-group><subject>Microbiology</subject><subj-group><subject>Microbial Ecology</subject></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Reconstruction of Ribosomal RNA Genes from Metagenomic Data</article-title><alt-title alt-title-type="running-head">16S rRNA Genes in Metagenomes</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Fan</surname><given-names>Lu</given-names></name><xref ref-type="aff" rid="aff1"></xref></contrib><contrib contrib-type="author"><name><surname>McElroy</surname><given-names>Kerensa</given-names></name><xref ref-type="aff" rid="aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Thomas</surname><given-names>Torsten</given-names></name><xref ref-type="aff" rid="aff1"></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>School of Biotechnology and Biomolecular Sciences and Centre for Marine Bio-Innovation, University of New South Wales, Sydney, New South Wales, Australia</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Rodriguez-Valera</surname><given-names>Francisco</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1">Universidad Miguel Hernandez, Spain</aff><author-notes><corresp id="cor1">* E-mail: <email>t.thomas@unsw.edu.au</email></corresp><fn fn-type="con"><p>Conceived and designed the experiments: LF TT. Performed the experiments: LF. Analyzed the data: LF TT. Contributed reagents/materials/analysis tools: LF KM. Wrote the paper: LF KM TT.</p></fn></author-notes><pub-date pub-type="collection"><year>2012</year></pub-date><pub-date pub-type="epub"><day>27</day><month>6</month><year>2012</year></pub-date><volume>7</volume><issue>6</issue><elocation-id>e39948</elocation-id><history><date date-type="received"><day>22</day><month>5</month><year>2012</year></date><date date-type="accepted"><day>29</day><month>5</month><year>2012</year></date></history><permissions><copyright-statement>Fan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</copyright-statement><copyright-year>2012</copyright-year></permissions><abstract><p>Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.</p></abstract><counts><page-count count="9"></page-count></counts></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Fan, Lu" sort="Fan, Lu" uniqKey="Fan L" first="Lu" last="Fan">Lu Fan</name><name sortKey="Mcelroy, Kerensa" sort="Mcelroy, Kerensa" uniqKey="Mcelroy K" first="Kerensa" last="Mcelroy">Kerensa Mcelroy</name><name sortKey="Thomas, Torsten" sort="Thomas, Torsten" uniqKey="Thomas T" first="Torsten" last="Thomas">Torsten Thomas</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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