Comparative analysis of RNA sequencing methods for degraded or low-input samples
available in PMC 2014 January 01
| Main Authors: | , , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Nature Publishing Group
2014
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| Online Access: | http://hdl.handle.net/1721.1/84966 https://orcid.org/0000-0001-8567-2049 |
| _version_ | 1811088432896671744 |
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| 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. |
| author2 | Massachusetts Institute of Technology. Department of Biology |
| author_facet | Massachusetts Institute of Technology. Department of Biology 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 |
| collection | MIT |
| description | available in PMC 2014 January 01 |
| first_indexed | 2024-09-23T14:02:06Z |
| format | Article |
| id | mit-1721.1/84966 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:02:06Z |
| publishDate | 2014 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/849662022-10-01T18:42:27Z 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. Massachusetts Institute of Technology. Department of Biology Regev, Aviv available in PMC 2014 January 01 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. National Institutes of Health (U.S.) (Pioneer Award DP1-OD003958-01) National Human Genome Research Institute (U.S.) (NHGRI) 1P01HG005062-01) National Human Genome Research Institute (U.S.) (NHGRI Center of Excellence in Genome Science Award 1P50HG006193-01) Howard Hughes Medical Institute (Investigator) Merkin Family Foundation for Stem Cell Research Broad Institute of MIT and Harvard (Klarman Cell Observatory) National Human Genome Research Institute (U.S.) (NHGRI grant HG03067) Fonds voor Wetenschappelijk Onderzoek--Vlaanderen 2014-02-14T19:57:31Z 2014-02-14T19:57:31Z 2013-05 2013-02 Article http://purl.org/eprint/type/JournalArticle 1548-7091 1548-7105 http://hdl.handle.net/1721.1/84966 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. https://orcid.org/0000-0001-8567-2049 en_US http://dx.doi.org/10.1038/nmeth.2483 Nature Methods 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. application/pdf Nature Publishing Group PMC |
| 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. Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title | Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title_full | Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title_fullStr | Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title_full_unstemmed | Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title_short | Comparative analysis of RNA sequencing methods for degraded or low-input samples |
| title_sort | comparative analysis of rna sequencing methods for degraded or low input samples |
| url | http://hdl.handle.net/1721.1/84966 https://orcid.org/0000-0001-8567-2049 |
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