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Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study

Nature Biotechnology volume 32, pages 915–925 (2014)Cite this article

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An Erratum to this article was published on 07 November 2014

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Abstract

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A–selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

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Figure 1: Experimental design and sequencing platforms.
Figure 2: Transcript coverage across all genes detected.
Figure 3: Intra- and inter-platform variation of RNA-seq transcript metrics.
Figure 4: Inter-platform consistency of splicing and differential expression analysis.
Figure 5: Differentially expressed genes in ribo-depleted and poly-A–enriched libraries.

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Gene Expression Omnibus

Change history

  • 10 October 2014

    In the version of this article initially published, author Jeffrey Rosenfeld's middle initial “A” was omitted. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We greatly appreciate the contribution and distribution of reference sample RNA from L. Shi (FDA) and his valuable interactions to assist in the planning of this study. This work was supported with funding from the National Institutes of Health (NIH), including R01HG006798, R01NS076465, R24RR032341, as well as funds from the Irma T. Hirschl and Monique Weill-Caulier Charitable Trusts and the STARR Consortium (I7-A765).

We thank the following contributors for their technical wisdom, including laboratory expertise, data analysis and bioinformatics contributions, and technical design guidance and consultation. Without their help, this study would not have been possible: D. Stopka (Memorial Sloan-Kettering Cancer Institute), G. Grove (Penn State Univ.), D. Hannon (Penn State Univ.), K. Jones (NIH/NCI/SAIC), C. Raley (NIH/NCI/SAIC), H. O'Geen (UC Davis), D. Zheng (Univ. Illinois-Urbana), O. Nguyen (UC Davis), Z.-W. Lu (UC Davis), J. Spisak (Cornell Univ.), D. Lin (NIH/NIAID), J. Pillardy (Cornell Univ.), P.-Y. Wu (Georgia Institute of Technology), J. Phan (Emory Univ.), D. Oschwald (New York Genome Center), H. Arnold (PerkinElmer), S. Tyndale (Univ. Southern California), H. Truong (Univ. Southern California), Y. Zhang (Univ. Florida), N. Panayotova (Univ. Florida), D. Moraga (Univ. Florida), S. Shanker (Univ. Florida), and N. Barker (US Army Environmental Quality Research Program).

We would also like to thank the platform vendors, Illumina, Life Technologies, Pacific Biosciences and Roche Life Sciences, for their support of this study, and their distinguished scientists for providing technical expertise and assistance in study designs, protocols, new methods development and significant contributions of reagents and sequencing kits. In particular, alphabetically by vendor: G. Schroth (Illumina); M. Gallad, J. Smith, T. Bittick, R. Setterquist and G. Scott (Life Technologies); J. Korlach, S. Turner and E. Tseng (Pacific Biosciences); and K. Fredrickson and C. Teiling (Roche Life Sciences).

We are sincerely appreciative of the Association of Biomolecular Resource Facilities (ABRF) for supporting this study and the contributing ABRF Research Groups. Special thanks to our ABRF executive board liaison A. Perera (Stowers Institute for Medical Research).

Author information

Author notes

  1. Ryan Kim

    Present address: Present address: Korean Bioinformation Center (KOBIC), National Center for Biological Research Resource Information, Daejeon, South Korea.,

  2. Sheng Li and Scott W Tighe: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, USA

    Sheng Li, Sagar Chhangawala, Jorge Gandara, Paul Zumbo & Christopher E Mason

  2. The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, USA

    Sheng Li, Sagar Chhangawala, Jorge Gandara, Paul Zumbo & Christopher E Mason

  3. Vermont Cancer Center, University of Vermont, Burlington, Vermont, USA

    Scott W Tighe

  4. Keck School of Medicine, University of Southern California, Los Angeles, California, USA

    Charles M Nicolet

  5. The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, USA

    Deborah Grove

  6. HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA

    Shawn Levy & Cynthia Hendrickson

  7. Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida, USA

    William Farmerie

  8. Memorial Sloan-Kettering Cancer Institute, New York, New York, USA

    Agnes Viale

  9. Roy J. Carver Biotechnology Center, University of Illinois, Urbana, Illinois, USA

    Chris Wright

  10. Biotechnology Resource Center, Institute of Biotechnology, Cornell University, Ithaca, New York, USA

    Peter A Schweitzer & George S Grills

  11. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA

    Yuan Gao & Dewey Kim

  12. NIH/NCI/SAIC-Frederick, Gaithersburg, Maryland, USA

    Joe Boland, Belynda Hicks & David Roberson

  13. Genome Center, University of California, Davis, Davis, California, USA

    Ryan Kim

  14. Center for Genetic Medicine, Northwestern University, Chicago, Illinois, USA

    Nadereh Jafari

  15. NIH/NHLBI, Bethesda, Maryland, USA

    Nalini Raghavachari

  16. Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, Mississippi, USA

    Natàlia Garcia-Reyero

  17. Division of High Performance and Research Computing, University of Medicine and Dentistry of New Jersey, Newark, New Jersey, USA

    Jeffrey A Rosenfeld

  18. PerkinElmer Inc., Seattle, Washington, USA

    Todd Smith

  19. Department of Genome Sciences, University of Washington, Seattle, Washington, USA

    Jason G Underwood

  20. Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

    May Wang

  21. Pathonomics LLC, Philadelphia, Pennsylvania, USA

    Don A Baldwin

  22. The Feil Family Brain and Mind Research Institute, New York, New York, USA

    Christopher E Mason

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  1. Sheng Li
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Contributions

All authors are members of the Association of Biomolecular Resource Facilities Next-Generation Sequencing (ABRF-NGS) Consortium. S.W.T., C.M.N., D.A.B., G.S.G. and C.E.M. managed the project. S.W.T., C.M.N., D.G., S.L., W.F., A.V., C.W., P.A.S., Y.G., D.K., J.B., B.H., R.K., N.J., N.R., J.G., N.G.-R., C.H., D.R., J.R., T.S., J.G.U., C.E.M. and P.Z. performed sequencing. S.L., S.W.T., C.M.N., D.A.B., G.S.G. and C.E.M. designed the analyses. S.L., P.A.S., J.G.U., P.Z., C.E.M. and D.K. performed the data analyses. S.L., P.Z., M.W., D.K., J.G.U. and C.E.M. made the figures. S.L., S.W.T., C.M.N., D.A.B., G.S.G. and C.E.M. wrote and revised the manuscript. The ABRF-NGS Consortium members contributed to the design and execution of the study.

Corresponding authors

Correspondence to Don A Baldwin, George S Grills or Christopher E Mason.

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The authors declare no competing financial interests.

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Li, S., Tighe, S., Nicolet, C. et al. Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study. Nat Biotechnol 32, 915–925 (2014). https://doi.org/10.1038/nbt.2972

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