Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

RNA-Seq is an effective method to study the transcriptome, but 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 their relative...

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Main Authors: 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, Gnirke, Andreas, Pochet, Nathalie, Regev, Aviv, Levin, Joshua Z.
Format: Online
Language:English
Published: 2013
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821180/
id pubmed-3821180
recordtype oai_dc
spelling pubmed-38211802014-01-01 Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples 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 Gnirke, Andreas Pochet, Nathalie Regev, Aviv Levin, Joshua Z. Article RNA-Seq is an effective method to study the transcriptome, but 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 their relative merits 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 two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development. 2013-05-19 2013-07 /pmc/articles/PMC3821180/ /pubmed/23685885 http://dx.doi.org/10.1038/nmeth.2483 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author 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
Gnirke, Andreas
Pochet, Nathalie
Regev, Aviv
Levin, Joshua Z.
spellingShingle 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
Gnirke, Andreas
Pochet, Nathalie
Regev, Aviv
Levin, Joshua Z.
Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
author_facet 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
Gnirke, Andreas
Pochet, Nathalie
Regev, Aviv
Levin, Joshua Z.
author_sort Adiconis, Xian
title Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
title_short Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
title_full Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
title_fullStr Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
title_full_unstemmed Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples
title_sort comprehensive comparative analysis of rna sequencing methods for degraded or low input samples
description RNA-Seq is an effective method to study the transcriptome, but 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 their relative merits 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 two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.
publishDate 2013
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821180/
_version_ 1612024597836726272

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