TY - JOUR
T1 - Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study
AU - Li, Sheng
AU - Tighe, Scott W.
AU - Nicolet, Charles M.
AU - Grove, Deborah
AU - Levy, Shawn
AU - Farmerie, William
AU - Viale, Agnes
AU - Wright, Chris
AU - Schweitzer, Peter A.
AU - Gao, Yuan
AU - Kim, Dewey
AU - Boland, Joe
AU - Hicks, Belynda
AU - Kim, Ryan
AU - Chhangawala, Sagar
AU - Jafari, Nadereh
AU - Raghavachari, Nalini
AU - Gandara, Jorge
AU - Garcia-Reyero, Natàlia
AU - Hendrickson, Cynthia
AU - Roberson, David
AU - Rosenfeld, Jeffrey A.
AU - Smith, Todd
AU - Underwood, Jason G.
AU - Wang, May
AU - Zumbo, Paul
AU - Baldwin, Don A.
AU - Grills, George S.
AU - Mason, Christopher E.
N1 - Publisher Copyright:
© 2015 Nature America, Inc.
PY - 2014/8
Y1 - 2014/8
N2 - 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.
AB - 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.
KW - Gene Expression Profiling
KW - High-Throughput Nucleotide Sequencing/methods
KW - Transcriptome
UR - https://www.scopus.com/pages/publications/84922578455
U2 - 10.1038/nbt.2972
DO - 10.1038/nbt.2972
M3 - Article
C2 - 25150835
AN - SCOPUS:84922578455
SN - 1087-0156
VL - 32
SP - 915
EP - 925
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 9
ER -