Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study (vol 32, pg 915, 2014)

• Authors: Sheng Li, Weill Cornell Medical College; Scott W. Tighe, University of Vermont; Charles M. Nicolet, University of Southern California, Los Angeles; Deborah Grove, Pennsylvania State University; Shawn Levy, HudsonAlpha Institute for Biotechnology; William Farmerie, University of Florida; Agnes Viale, Memorial Sloan-Kettering Cancer Institute; Chris Wright, University of Illinois; Peter A. Schweitzer, Cornell University; Yuan Gao, Johns Hopkins University; Dewey Kim, Johns Hopkins University; Joe Boland, NIH/NCI/SAIC-Frederick; Belynda Hicks, NIH/NCI/SAIC-Frederick; Ryan Kim, University of California, Davis, Davis; Sagar Chhangawala, Weill Cornell Medical College; Nadereh Jafari, Northwestern University; Nalini Raghavachari, NIH/NHLBI; Jorge Gandara, Weill Cornell Medical College; Natalia Garcia-Reyero, Mississippi State University; Cynthia Hendrickson, HudsonAlpha Institute for Biotechnology; David Roberson, NIH/NCI/SAIC-Frederick; Jeffrey Rosenfeld, University of Medicine and Dentistry of New Jersey; Todd Smith, PerkinElmer Inc.; Jason G. Underwood, University of Washington; Dongmei Wang, Emory University; Paul Zumbo, Weill Cornell Medical College; Don A. Baldwin, Pathonomics LLC; George S. Grills, Cornell University; Christopher E. Mason, Cornell University
• Journal Title: Nature Biotechnology
• Volume: Volume 32, Number 11
• Publisher: Nature Research (part of Springer Nature) | 2014-11-01, Pages 1166-1166
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1038/nbt1114-1166a
• Subjects: Engineering, Biomedical; Biophysics, General
• Keywords: Science & Technology; Life Sciences & Biomedicine; Biotechnology & Applied Microbiology

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.