Comparative analysis of RNA sequencing methods for degraded or low-input samples
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Regev_Comparative analysis.pdf
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Author(s)
Adiconis, Xian
Borges-Rivera, Diego
Satija, Rahul
DeLuca, David S.
Busby, Michele A.
Berlin, Aaron M.
Sivachenko, Andrey
Thompson, Dawn Anne
Wysoker, Alec
Fennell, Timothy
Date Issued
May 2013
Journal
Nature Methods
Publisher
Nature Publishing Group
Citation
Adiconis, Xian, Diego Borges-Rivera, Rahul Satija, David S DeLuca, Michele A Busby, Aaron M Berlin, Andrey Sivachenko, et al. “Comparative analysis of RNA sequencing methods for degraded or low-input samples.” Nature Methods 10, no. 7 (May 19, 2013): 623-629.
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Author's final manuscript
Abstract
RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.
Description
available in PMC 2014 January 01.
MIT Department
Massachusetts Institute of Technology. Department of Biology
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1038/nmeth.2483
