PhyLOTU: A high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data

Thomas J. Sharpton, Samantha J. Riesenfeld, Steven W. Kembel, Joshua Ladau, James P. O'Dwyer, Jessica L. Green, Jonathan A Eisen, Katherine S. Pollard

Research output: Contribution to journalArticle

52 Scopus citations

Abstract

Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonom ic 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 OTUfinding 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?

Original languageEnglish (US)
Article numbere1001061
JournalPLoS Computational Biology
Volume7
Issue number1
DOIs
StatePublished - Jan 2011

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience
  • Ecology
  • Molecular Biology
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'PhyLOTU: A high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data'. Together they form a unique fingerprint.

  • Cite this

    Sharpton, T. J., Riesenfeld, S. J., Kembel, S. W., Ladau, J., O'Dwyer, J. P., Green, J. L., Eisen, J. A., & Pollard, K. S. (2011). PhyLOTU: A high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data. PLoS Computational Biology, 7(1), [e1001061]. https://doi.org/10.1371/journal.pcbi.1001061