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PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data.
Sharpton, Thomas J; Riesenfeld, Samantha J; Kembel, Steven W; Ladau, Joshua; O'Dwyer, James P; Green, Jessica L; Eisen, Jonathan A; Pollard, Katherine S.
Afiliação
  • Sharpton TJ; The J. David Gladstone Institutes, University of California San Francisco, San Francisco, California, United States of America. thomas.sharpton@gladstone.ucsf.edu
PLoS Comput Biol ; 7(1): e1001061, 2011 Jan 20.
Article em En | MEDLINE | ID: mdl-21283775
ABSTRACT
Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity?
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genômica Tipo de estudo: Incidence_studies / Prognostic_studies Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2011 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genômica Tipo de estudo: Incidence_studies / Prognostic_studies Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2011 Tipo de documento: Article País de afiliação: Estados Unidos