Comprehensive comparative analysis of strand-specific RNA sequencing methods
Open accessAbstract
Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-construction protocols, including both published and our own methods. We found marked differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling. Weighing each method's performance and ease, we identified the dUTP second-strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the current availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in other organisms.
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Removing the main axes of technical variation entirely may eliminate important aspects of the biological signal.
“While several studies have opted to remove these axes of variation entirely27,65, this may result in eliminating important aspects of the biological signal.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [65]
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- Authors
- Levin, J. Z., Yassour, M., Adiconis, X., Nusbaum, C., Thompson, D. A., Friedman, N., Gnirke, A., & Regev, A.
- Affiliations
- Broad Institute (US)
- Hebrew University of Jerusalem (IL)
- Corresponding author
- Levin, Joshua Z
- Regev, Aviv
- ORCID
- Venue
- Nature Methods
- Published
- 2010-08-15
- Volume
- 7
- Issue
- 9
- Pages
- 709-715
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC3005310
- OpenAlex
- W2152045787
- Cited by
- 753
- References
- 33
- Citations by year
- 2026: 15 · 2025: 29 · 2024: 17 · 2023: 41 · 2022: 48 · 2021: 29 · 2020: 29 · 2019: 42 · 2018: 48 · 2017: 65 · 2016: 58 · 2015: 69 · 2014: 79 · 2013: 79 · 2012: 64
- FWCI
- 23.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (5r01ca119176-10, DP1OD003958)
- National Human Genome Research Institute (U54HG003067)
- National Cancer Institute (R01-CA119176)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- strand-specific RNA-seq, strand specificity, library complexity, benchmarking, computational pipeline
- MeSH terms
- Substrate Specificity, Gene Library, Sequence Analysis, RNA, DNA, Complementary, Computational Biology, Gene Expression Profiling
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