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Practical innovations for high-throughput amplicon sequencing

Nature Methods volume 10, pages 999–1002 (2013)Cite this article

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Abstract

We describe improvements for sequencing 16S ribosomal RNA (rRNA) amplicons, a cornerstone technique in metagenomics. Through unique tagging of template molecules before PCR, amplicon sequences can be mapped to their original templates to correct amplification bias and sequencing error with software we provide. PCR clamps block amplification of contaminating sequences from a eukaryotic host, thereby substantially enriching microbial sequences without introducing bias.

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Figure 1: Molecular tagging reduces sequence error for a clonal template.
Figure 2: Molecular tagging lowers estimates of alpha diversity and improves technical reproducibility.
Figure 3: PNA specifically blocks amplification of contaminant sequences.

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Acknowledgements

We thank J. Tremblay and S.G. Tringe of the Department of Energy Joint Genome Institute for early discussions regarding their independent invention and adoption of frameshifting primers. We thank S.H. Paredes, C. Jabara, S. Biswas and H. Kelkar for essential discussions and S.L. Lebeis, N.W. Breakfield, B.J. Campbell and C.W. Schadt for comments on the manuscript. This work was supported by US National Science Foundation Microbial Systems Biology grant IOS-0958245 to J.L.D. D.S.L. was supported by US National Institutes of Health (NIH) Training Grant T32 GM07092-34. S.Y. was supported by NIH Training Grant T32 GM067553-06. J.L.D. acknowledges the Howard Hughes Medical Institute and the Gordon and Betty Moore Foundation for funding (in part via grant GBMF3030 to J.L.D.).

Author information

Author notes

  1. Derek S Lundberg and Scott Yourstone: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biology, University of North Carolina, Chapel Hill, North Carolina, USA

    Derek S Lundberg, Scott Yourstone, Corbin D Jones & Jeffery L Dangl

  2. Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina, USA

    Derek S Lundberg, Corbin D Jones & Jeffery L Dangl

  3. Program in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina, USA

    Scott Yourstone & Corbin D Jones

  4. Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA

    Piotr Mieczkowski

  5. Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA

    Piotr Mieczkowski & Corbin D Jones

  6. Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, North Carolina, USA

    Piotr Mieczkowski, Corbin D Jones & Jeffery L Dangl

  7. Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina, USA

    Jeffery L Dangl

  8. Howard Hughes Medical Institute, University of North Carolina, Chapel Hill, North Carolina, USA

    Jeffery L Dangl

Authors
  1. Derek S Lundberg
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  2. Scott Yourstone
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  3. Piotr Mieczkowski
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  4. Corbin D Jones
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  5. Jeffery L Dangl
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Contributions

D.S.L., P.M., C.D.J. and J.L.D. conceived wet-bench methods. S.Y. designed and wrote the informatics pipeline. D.S.L. and P.M. designed and performed experiments. D.S.L. and S.Y. analyzed data. D.S.L. wrote the manuscript with help from all authors.

Corresponding author

Correspondence to Jeffery L Dangl.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–17 and Supplementary Note (PDF 2371 kb)

Supplementary Table 1

Primers, PNA, Regular expressions (XLS 98 kb)

Supplementary Table 2

Sample metadata (XLS 107 kb)

Supplementary Table 3

Primers for Earth Microbiome Project comparison (XLS 32 kb)

Supplementary Table 4

MiSeq sample sheets (XLS 49 kb)

Supplementary Table 5

Contaminant 16S sequences (TXT 61 kb)

Supplementary Table 6

Plant organelle 16S sequences (XLS 102 kb)

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Lundberg, D., Yourstone, S., Mieczkowski, P. et al. Practical innovations for high-throughput amplicon sequencing. Nat Methods 10, 999–1002 (2013). https://doi.org/10.1038/nmeth.2634

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