The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Alternative isoform regulation in human tissue transcriptomes
Open accessAbstract
Through alternative processing of pre-messenger RNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes on the basis of deep sequencing of complementary DNA fragments, yielding a digital inventory of gene and mRNA isoform expression. Analyses in which sequence reads are mapped to exon-exon junctions indicated that 92-94% of human genes undergo alternative splicing, 86% with a minor isoform frequency of 15% or more. Differences in isoform-specific read densities indicated that most alternative splicing and alternative cleavage and polyadenylation events vary between tissues, whereas variation between individuals was approximately twofold to threefold less common. Extreme or 'switch-like' regulation of splicing between tissues was associated with increased sequence conservation in regulatory regions and with generation of full-length open reading frames. Patterns of alternative splicing and alternative cleavage and polyadenylation were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3' untranslated regions suggested common involvement of specific factors in tissue-level regulation of both splicing and polyadenylation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Direct sequencing of RNA libraries also provides the opportunity to explore alternative splicing, a key mechanism that contributes to transcriptome diversity (Pan et al., 2008;Wang et al., 2008).”
From An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex (2014) · cites this paper as Wang et al., 2008
The cited source says what the claim attributes to it.
In the citing paper
“RNA sequencing (RNA-seq) studies indicate that ~93% of human genes undergo alternative splicing and about 86% have a minor isoform frequency above 15% (ref. 11).”
From How many human proteoforms are there? (2018) · cites this paper as [11]
The cited source says what the claim attributes to it.
In the citing paper
“RNA sequencing (RNA-seq) studies indicate that ~93% of human genes undergo alternative splicing and about 86% have a minor isoform frequency above 15% (ref. 11).”
From How many human proteoforms are there? (2018) · cites this paper as [11]
In the citing paper
“RNA-seq experiments have discovered over 100,000 AS transcripts in the human genome (Pan et al., 2008; Wang et al., 2008)”
From Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome (2019) · cites this paper as Wang et al., 2008
In the citing paper
“Transcripts from ∼95% of multi-exon human genes are alternatively spliced (Pan et al., 2008, Wang et al., 2008).”
From Impact of Alternative Splicing on the Human Proteome (2017) · cites this paper as Wang et al., 2008
In the citing paper
“Several recent findingspropose that Rbfox can also regulate alternative polyadenylation (Wang et al., 2008) and mRNA stability (Ray et al., 2013), based on analysis of Rbfox motif sites in 3′ UTRs that are correlated with transcript abundance in different tissues.”
From HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism (2014) · cites this paper as Wang et al., 2008
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Initial sequencing and analysis of the human genome
International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855
Self-citationMechanisms of Alternative Pre-Messenger RNA Splicing
Black, D. L. (2003) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.72.121801.161720 · Cited by 2,704
MAQC Consortium, Shi, L., Shi, L., Reid, L. H., Jones, W. D., Shippy, R., Warrington, J. A., Baker, S. C., Collins, P. J., de Longueville, F., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1239 · Cited by 2,126
Self-citationXie, X., Lu, J., Kulbokas, E. J., Golub, T. R., Mootha, V., Lindblad-Toh, K., Lander, E. S., & Kellis, M. (2005) · Nature · doi:10.1038/nature03441 · Cited by 1,872
Genome-Wide Survey of Human Alternative Pre-mRNA Splicing with Exon Junction Microarrays
Johnson, J. M., Castle, J. C., Garrett-Engele, P. W., Kan, Z., Loerch, P., Armour, C. D., Santos, R., Schadt, E. E., Stoughton, R. B., & Shoemaker, D. D. (2003) · Science · doi:10.1126/science.1090100 · Cited by 1,418
HITS-CLIP yields genome-wide insights into brain alternative RNA processing
Licatalosi, D. D., Mele, A., Fak, J. J., Ule, J., Kayikci, M., Chi, S. W., Clark, T. A., Schweitzer, A. C., Blume, J. E., Wang, X., et al. (2008) · Nature · doi:10.1038/nature07488 · Cited by 1,352
Understanding alternative splicing: towards a cellular code
Matlin, A. J., Clark, F., & Smith, C. W. J. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1645 · Cited by 1,299
Sultan, M., Schulz, M. H., Richard, H., Magen, A., Klingenhoff, A., Scherf, M., Seifert, M., Borodina, T., Soldatov, A., Parkhomchuk, D., et al. (2008) · Science · doi:10.1126/science.1160342 · Cited by 1,293
Research works printed but not linked: 2
- Schroth, G. P., Luo, S. & Khrebtukova, I. Transcriptome analysis using high-throughput DNA sequencing. Methods Mol. Biol. (in the press)
- Pan, Q., Shai, O., Lee, L. J., Frey, B. J. & Blencowe, B. J. Deep surveying of alternative splicing complexity in the human genome by next generation sequencing. Nature Genet. (in the press)
Cited by
Sorted by citations
Items 1,001–1,022 of 1,022
Attig, L., Vigé, A., Gabory, A., Karimi, M., Beauger, A. A., Gross, M., Athias, A., Gallou‐Kabani, C., Gambert, P., Ekström, T. J., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066816 · Cited by 73
Chiang, Y.-A., Hung, H., Lee, C.-W., Huang, Y.-T., & Wang, H. (2012) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2012.10.021 · Cited by 73
Calarco, J. A., Zhen, M., & Blencowe, B. J. (2011) · RNA · doi:10.1261/rna.2603911 · Cited by 72
Statistical Modeling of RNA-Seq Data
Salzman, J., Jiang, H., & Wong, W. H. (2011) · Statistical Science · doi:10.1214/10-sts343 · Cited by 68
Liu, X., Freitas, J., Zheng, D., Oliveira, M. S., Hoque, M., Martins, T., Henriques, T., Tian, B., & Moreira, A. (2017) · RNA · doi:10.1261/rna.062661.117 · Cited by 67
An Emerging Role for Long Non-Coding RNA Dysregulation in Neurological Disorders
Fenoglio, C., Ridolfi, E., Galimberti, D., & Scarpini, E. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms141020427 · Cited by 68
Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations
Iancu, O. D., Colville, A., Oberbeck, D., Darakjian, P., McWeeney, S. K., & Hitzemann, R. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00174 · Cited by 57
Triple-Stage Mass Spectrometry Unravels the Heterogeneity of an Endogenous Protein Complex
Ben-Nissan, G., Belov, M. E., Morgenstern, D., Levin, Y., Dym, O., Arkind, G., Lipson, C., Makarov, A. A., & Sharon, M. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.7b00518 · Cited by 54
Aberrant expression of splicing factors in newly diagnosed acute myeloid leukemia
Liu, J., Huang, B., Xiao, Y., Xiong, H.-M., Li, J., Feng, D.-Q., Chen, X.-M., Zhang, H.-B., & Wang, X.-Z. (2012) · Onkologie · doi:10.1159/000338941 · Cited by 53
RNA-Seq Reveals Novel Transcriptional Reorganization in Human Alcoholic Brain
Farris, S. P., & Dayne Mayfield, R. (2014) · International Review of Neurobiology · doi:10.1016/b978-0-12-801105-8.00011-4 · Cited by 49
Promotion of exon 6 inclusion in HuD pre-mRNA by Hu protein family members
Wang, H., Molfenter, J., Zhu, H., & Lou, H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq028 · Cited by 49
Mojica, W., & Hawthorn, L. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-5 · Cited by 43
Highly accurate isoform identification for the human transcriptome
Sommer, M. J., Cha, S., Varabyou, A., Rincon, N., Park, S., Minkin, I., Pertea, M., Steinegger, M., & Salzberg, S. L. (2022) · doi:10.1101/2022.06.08.495354 · Cited by 40
Gordon, J. M. B., Shikov, S., Kuehner, J. N., Liriano, M., Lee, E., Stafford, W., Poulsen, M. B., Harrison, C., Moore, C., & Bohm, A. (2011) · Biochemistry · doi:10.1021/bi200964p · Cited by 33
Xu, T., Verhagen, M., Joosten, R., Sun, W., Sacchetti, A., Munoz Sagredo, L., Orian-Rousseau, V., & Fodde, R. (2022) · eLife · doi:10.7554/elife.82006 · Cited by 25
Hao, Y., Colak, R., Teyra, J., Corbi-Verge, C., Ignatchenko, A., Hahne, H., Wilhelm, M., Kuster, B., Braun, P., Kaida, D., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.06.031 · Cited by 23
Integrating many co-splicing networks to reconstruct splicing regulatory modules
Dai, C., Li, W., Liu, J., & Zhou, X. J. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-s1-s17 · Cited by 20
Sharina, I. G., & Martin, E. (2017) · Antioxidants & Redox Signaling · doi:10.1089/ars.2016.6687 · Cited by 19
Eckenfelder, A., Tordo, J., Babbs, A., Davies, K. E., Goyenvalle, A., & Danos, O. (2012) · Molecular Therapy - Nucleic Acids · doi:10.1038/mtna.2012.24 · Cited by 17
Arendt-Tranholm, A., Mwirigi, J. M., & Price, T. J. (2024) · Pain · doi:10.1097/j.pain.0000000000003255 · Cited by 10
Crowl, S., Coleman, M. B., Chaphiv, A., Jordan, B. T., & Naegle, K. M. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101318 · Cited by 10
LRP2: A proteogenomics pipeline for long-read informed protein isoform analysis and discovery
Schertzer, M. D., Lewandowski, J. T., Watts, E. F., Rosenow, W., Mehlferber, M. M., Jeffery, E. D., Adamson, S. I., Bruand, J., Tseng, E., Neelamraju, Y., et al. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag790
Metadata
- Authors
- Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B.
- Affiliations
- Massachusetts Institute of Technology (US)
- Karolinska Institutet (SE)
- Illumina (United States) (US)
- Whitehead Institute for Biomedical Research (US)
- National Center for Genome Resources (US)
- Corresponding author
- Burge, Christopher B.
- ORCID
- Venue
- Nature
- Published
- 2008-11
- Volume
- 456
- Issue
- 7221
- Pages
- 470-476
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC2593745
- OpenAlex
- W2155804510
- Cited by
- 5,181
- References
- 41
- Citations by year
- 2026: 172 · 2025: 222 · 2024: 253 · 2023: 254 · 2022: 317 · 2021: 364 · 2020: 294 · 2019: 304 · 2018: 266 · 2017: 262 · 2016: 294 · 2015: 316 · 2014: 345 · 2013: 347 · 2012: 376
- FWCI
- 108.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Human Genome Research Institute (R01HG002439)
- National Cancer Institute (P30CA008748)
- National Institute of General Medical Sciences (R01GM085319)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- alternative splicing, mRNA isoforms, tissue-specific gene expression, exon-exon junctions, sequence conservation, 3' untranslated region, human transcriptome, human cell lines, splicing regulation
- MeSH terms
- RNA Splicing Factors, Base Sequence, Cell Line, Exons, Humans, Organ Specificity, Repressor Proteins, RNA, Messenger, Open Reading Frames, RNA-Binding Proteins, Alternative Splicing, Protein Isoforms, Gene Expression Profiling, Polyadenylation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review