Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs
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Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5' start sites, 3' ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.
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LincRNAs were taken from reconstructed transcripts that fell entirely within lincRNA chromatin signatures and excluded known protein-coding genes.
“LincRNAs were collected from reconstructed transcripts (Guttman et al., 2010) that lay entirely within the lincRNA chromatin signatures identified by Guttman et al. (Guttman et al., 2009), which excluded known protein-coding genes.”
From Ribosome Profiling of Mouse Embryonic Stem Cells Reveals the Complexity and Dynamics of Mammalian Proteomes (2011) · cites this paper as Guttman et al., 2010
Transcripts of between 8000 and 16,000 protein-coding genes expressed from a single cell type can be detected depending on data and analysis criteria.
“transcripts of between 8000 and 16 000 protein-coding genes expressed from a single cell type can be detected”
From Deep proteome and transcriptome mapping of a human cancer cell line (2011) · cites this paper as Guttman et al, 2010
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Martin, J., Bruno, V. M., Fang, Z., Meng, X., Blow, M., Zhang, T., Sherlock, G., Snyder, M., & Wang, Z. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-663
- Authors
- Guttman, M., Garber, M., Levin, J. Z., Donaghey, J., Robinson, J., Adiconis, X., Fan, L., Koziol, M. J., Gnirke, A., Nusbaum, C., Rinn, J. L., Lander, E. S., & Regev, A.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Guttman, Mitchell
- Garber, Manuel
- Regev, Aviv
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2010-05
- Volume
- 28
- Issue
- 5
- Pages
- 503-510
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC2868100
- OpenAlex
- W2000875411
- Cited by
- 1,253
- References
- 33
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 18 · 2023: 24 · 2022: 33 · 2021: 50 · 2020: 48 · 2019: 86 · 2018: 90 · 2017: 100 · 2016: 104 · 2015: 139 · 2014: 147 · 2013: 137 · 2012: 138
- FWCI
- 51.24
- Type
- journal article
- Language
- en
- Update notices
- erratum (2010-07-01)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP1OD003958)
- National Human Genome Research Institute (U54HG003067, R01HG005111)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Keywords
- long intergenic non-coding RNA, scripture, mouse embryonic stem cells, neuronal precursors, lung fibroblasts
- MeSH terms
- Animals, Cell Line, Models, Genetic, RNA, Messenger, Transcription, Genetic, Gene Library, Sequence Analysis, RNA, Computational Biology, Gene Expression Profiling, DNA, Intergenic, Mice, Embryonic Stem Cells
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