Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 9,711

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

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

Open access
Caporaso, J. Gregory, Lauber, Christian L., Walters, William A., Berg-Lyons, Donna, Lozupone, Catherine A., Turnbaugh, Peter J., Fierer, Noah, Knight, Rob·2011·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1000080107
Open this paper in CoChat — free account

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 metaanalysis 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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.1000080107

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 27

  1. EA Grice, et al., Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009). · DOI · Paper page
  2. LFW Roesch, et al., Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J 1, 283–290 (2007). · DOI
  3. ML Sogin, et al., Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc Natl Acad Sci USA 103, 12115–12120 (2006). · DOI
  4. SG Tringe, P Hugenholtz, A renaissance for the pioneering 16S rRNA gene. Curr Opin Microbiol 11, 442–446 (2008). · DOI
  5. NR Pace, A molecular view of microbial diversity and the biosphere. Science 276, 734–740 (1997). · DOI · Paper page
  6. KT Konstantinidis, JM Tiedje, Genomic insights that advance the species definition for prokaryotes. Proc Natl Acad Sci USA 102, 2567–2572 (2005). · DOI
  7. M Hamady, R Knight, Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res 19, 1141–1152 (2009). · DOI
  8. D Pushkarev, NF Neff, SR Quake, Single-molecule sequencing of an individual human genome. Nat Biotechnol 27, 847–852 (2009). · DOI
  9. V Lazarevic, et al., Metagenomic study of the oral microbiota by Illumina high-throughput sequencing. J Microbiol Methods 79, 266–271 (2009). · DOI
  10. J Binladen, et al., The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing. PLoS ONE 2, e197 (2007). · DOI · Paper page
  11. M Hamady, JJ Walker, JK Harris, NJ Gold, R Knight, Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex. Nat Methods 5, 235–237 (2008). · DOI · Paper page
  12. JA Huber, et al., Microbial population structures in the deep marine biosphere. Science 318, 97–100 (2007). · DOI · Paper page
  13. Z Liu, C Lozupone, M Hamady, FD Bushman, R Knight, Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res 35, e120 (2007). · DOI
  14. CA Lozupone, R Knight, Global patterns in bacterial diversity. Proc Natl Acad Sci USA 104, 11436–11440 (2007). · DOI
  15. RE Ley, CA Lozupone, M Hamady, R Knight, JI Gordon, Worlds within worlds: Evolution of the vertebrate gut microbiota. Nat Rev Microbiol 6, 776–788 (2008). · DOI
  16. JC Auguet, A Barberan, EO Casamayor, Global ecological patterns in uncultured Archaea. ISME J 4, 182–190 (2010). · DOI · Paper page
  17. W Li, A Godzik, Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006). · DOI · Paper page
  18. M Hamady, C Lozupone, R Knight, Fast UniFrac: Facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4, 17–27 (2010). · DOI
  19. E Fredkin, Trie memory. Commun ACM 3, 490–499 (1960). · DOI
  20. MN Price, PS Dehal, AP Arkin, FastTree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 26, 1641–1650 (2009). · DOI · Paper page
  21. Q Wang, GM Garrity, JM Tiedje, JR Cole, Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73, 5261–5267 (2007). · DOI · Paper page
  22. PJ Turnbaugh, et al., Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins. Proc Natl Acad Sci USA 107, 7503–7508 (2010). · DOI · Paper page
  23. C Quince, et al., Accurate determination of microbial diversity from 454 pyrosequencing data. Nat Methods 6, 639–641 (2009). · DOI
  24. V Kunin, A Engelbrektson, H Ochman, P Hugenholtz, Wrinkles in the rare biosphere: Pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ Microbiol 12, 118–123 (2010). · DOI · Paper page
  25. CA Lozupone, M Hamady, ST Kelley, R Knight, Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol 73, 1576–1585 (2007). · DOI · Paper page
  26. GE Fox, CR Woese, The architecture of 5S rRNA and its relation to function. J Mol Evol 6, 61–76 (1975). · DOI
  27. PJ Turnbaugh, et al., A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009). · DOI · Paper page

Cited by

See all 9,711

Metadata

Authors
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C. A., Turnbaugh, P. J., Fierer, N., & Knight, R.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2010-06-03
Volume
108
Issue
supplement_1
Pages
4516-4522
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1000080107
OpenAlex
W2080283023
Cited by
9,711
References
7
FWCI
60.47
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.