Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample

J. Gregory Caporaso, Christian L. Lauber, William A. Walters, Donna Berg-Lyons, Catherine A. Lozupone, Peter J. Turnbaugh, Noah Fierer, Rob Knight

Research output: Contribution to journalArticlepeer-review

6698 Scopus citations

Abstract

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of meta-analysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.

Original languageEnglish (US)
Pages (from-to)4516-4522
Number of pages7
JournalProceedings of the National Academy of Sciences of the United States of America
Volume108
Issue numberSUPPL. 1
DOIs
StatePublished - Mar 15 2011

Keywords

  • Human microbiome
  • Microbial community analysis
  • Microbial ecology
  • Next-generation sequencing

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample'. Together they form a unique fingerprint.

Cite this