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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.
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“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
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“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]
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“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
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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)
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Self-citationA Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains
Irimia, M., Weatheritt, R. J., Ellis, J. D., Parikshak, N. N., Gonatopoulos-Pournatzis, T., Babor, M., Quesnel-Vallières, M., Tapial, J., Raj, B., O’Hanlon, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.035 · Cited by 693
“For example, transcripts from over 95% of human multiexon genes undergo AS, and most of the resulting mRNA splice variants are variably expressed between different cell and tissue types (Pan et al., 2008; Wang et al., 2008).”
BackgroundHallmarks of alternative splicing in cancer
Oltean, S., & Bates, D. O. (2013) · Oncogene · doi:10.1038/onc.2013.533 · Cited by 680
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Derti, A., Garrett-Engele, P. W., MacIsaac, K. D., Stevens, R. C., Sriram, S., Chen, R., Rohl, C. A., Johnson, J. M., & Babak, T. (2012) · Genome Research · doi:10.1101/gr.132563.111 · Cited by 663
Anti-apoptosis and cell survival: A review
Portt, L., Norman, G., Clapp, C., Greenwood, M., & Greenwood, M. T. (2010) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2010.10.010 · Cited by 661
Synthetic spike-in standards for RNA-seq experiments
Jiang, L., Schlesinger, F., Davis, C. A., Zhang, Y., Li, R., Salit, M., Gingeras, T. R., & Oliver, B. (2011) · Genome Research · doi:10.1101/gr.121095.111 · Cited by 653
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Soumillon, M., Necşulea, A., Weier, M., Brawand, D., Zhang, X., Gu, H., Barthès, P., Kokkinaki, M., Nef, S., Gnirke, A., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.05.031 · Cited by 645
Brown, R. L., Reinke, L. M., Damerow, M. S., Perez, D., Chodosh, L. A., Yang, J., & Cheng, C. (2011) · Journal of Clinical Investigation · doi:10.1172/jci44540 · Cited by 645
Genetic variability in the regulation of gene expression in ten regions of the human brain
UK Brain Expression Consortium, Ramasamy, A., North American Brain Expression Consortium, Trabzuni, D., Guelfi, S., Varghese, V., Smith, C., Walker, R., De, T., Coin, L., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3801 · Cited by 644
Barrett, L. W., Fletcher, S., & Wilton, S. D. (2012) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-012-0990-9 · Cited by 641
Rentzsch, P., Schubach, M., Shendure, J., & Kircher, M. (2021) · Genome Medicine · doi:10.1186/s13073-021-00835-9 · Cited by 640
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Proudfoot, N. J. (2011) · Genes & Development · doi:10.1101/gad.17268411 · Cited by 640
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The alternative role of DNA methylation in splicing regulation
Lev-Maor, G., Yearim, A., & Ast, G. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.03.002 · Cited by 604
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Florea, L., Li, S., & Salzberg, S. L. (2013) · F1000Research · doi:10.12688/f1000research.2-188.v2 · Cited by 601
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Lundberg, E., & Borner, G. H. H. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0094-y · Cited by 591
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Yandell, M., & Ence, D. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3174 · Cited by 588
Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing
Yang, X., Coulombe-Huntington, J., Kang, S., Sheynkman, G. M., Hao, T., Richardson, A., Sun, S., Yang, F., Shen, Y. A., Murray, R. R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.01.029 · Cited by 583
RNA splicing dysregulation and the hallmarks of cancer
Bradley, R. K., & Anczuków, O. (2023) · Nature Reviews Cancer · doi:10.1038/s41568-022-00541-7 · Cited by 579
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Lee, S. C.-W., & Abdel-Wahab, O. I. (2016) · Nature Medicine · doi:10.1038/nm.4165 · Cited by 573
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Pepke, S., Wold, B. J., & Mortazavi, A. (2009) · Nature Methods · doi:10.1038/nmeth.1371 · Cited by 568
RNA-seq: from technology to biology
Marguerat, S., & Bähler, J. (2009) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-009-0180-6 · Cited by 566
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Abu Shelbayeh, O., Arroum, T., Morris, S., & Busch, K. B. (2023) · Antioxidants · doi:10.3390/antiox12051075 · Cited by 552
The physiology of alternative splicing
Marasco, L. E., & Kornblihtt, A. R. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-022-00545-z · Cited by 550
Battle, A., Mostafavi, S., Zhu, X., Potash, J. B., Weissman, M. M., McCormick, C., Haudenschild, C. D., Beckman, K. B., Shi, J., Mei, R., et al. (2014) · Genome Research · doi:10.1101/gr.155192.113 · Cited by 547
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Jiang, Y., Xie, M., Chen, W., Talbot, R., Maddox, J. F., Faraut, T., Wu, C., Muzny, D. M., Li, Y., Zhang, W., et al. (2014) · Science · doi:10.1126/science.1252806 · Cited by 514
Roberts, A. M., Ware, J. S., Herman, D. S., Schäfer, S., Baksi, J. A., Bick, A. G., Buchan, R. J., Walsh, R., John, S., Wilkinson, S., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.3010134 · Cited by 502
Regulation of splicing by SR proteins and SR protein-specific kinases
Zhou, Z., & Fu, X. (2013) · Chromosoma · doi:10.1007/s00412-013-0407-z · Cited by 501
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Tang, F., Bárbácioru, C., Nordman, E., Li, B., Xu, N., Bashkirov, V. I., Lao, K., & Surani, M. A. (2010) · Nature Protocols · doi:10.1038/nprot.2009.236 · Cited by 500
Transcript length bias in RNA-seq data confounds systems biology
Oshlack, A., & Wakefield, M. J. (2009) · Biology Direct · doi:10.1186/1745-6150-4-14 · Cited by 497
Fast Computation and Applications of Genome Mappability
Derrien, T., Estellé, J., Marco‐Sola, S., Knowles, D. G., Raineri, E., Guigó, R., & Ribeca, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030377 · Cited by 493
Transcriptome-wide Regulation of Pre-mRNA Splicing and mRNA Localization by Muscleblind Proteins
Wang, E. T., Cody, N. A. L., Jog, S., Biancolella, M., Wang, T. T., Treacy, D. J., Luo, S., Schroth, G. P., Housman, D. E., Reddy, S., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.041 · Cited by 490
Self-citationA new view of transcriptome complexity and regulation through the lens of local splicing variations
Vaquero-Garcia, J., Barrera, A., Gazzara, M. R., González-Vallinas, J., Lahens, N. F., Hogenesch, J. B., Lynch, K. W., & Barash, Y. (2016) · eLife · doi:10.7554/elife.11752 · Cited by 488
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Shumate, A., Wong, B. Y., Pertea, G. M., & Pertea, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009730 · Cited by 488
Desperately seeking microRNA targets
Thomas, M., Lieberman, J., & Lal, A. (2010) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1921 · Cited by 487
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Jan, C. H., Friedman, R. C., Ruby, J. G., & Bartel, D. P. (2010) · Nature · doi:10.1038/nature09616 · Cited by 485
Deep RNA sequencing at single base-pair resolution reveals high complexity of the rice transcriptomePreprint
Zhang, G., Guo, G., Hu, X., Zhang, Y., Li, Q., Li, R., Zhuang, R., Lu, Z., He, Z., Fang, X., et al. (2010) · Genome Research · doi:10.1101/gr.100677.109 · Cited by 484
Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes
Sveen, A., Kilpinen, S. K., Ruusulehto, A., Lothe, R. A., & Skotheim, R. I. (2015) · Oncogene · doi:10.1038/onc.2015.318 · Cited by 482
U1 snRNP Determines mRNA Length and Regulates Isoform Expression
Berg, M. G., Singh, L. N., Younis, I., Liu, Q., Pinto, A. M., Kaida, D., Zhang, Z., Cho, S., Sherrill-Mix, S. A., Wan, L., et al. (2012) · Cell · doi:10.1016/j.cell.2012.05.029 · Cited by 482
Kalyna, M., Simpson, C. G., Syed, N. H., Lewandowska, D., Marquez, Y., Kusenda, B., Marshall, J., Fuller, J., Cardle, L., McNicol, J., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr932 · Cited by 480
Nucleosome positioning as a determinant of exon recognition
Tilgner, H., Nikolaou, C., Althammer, S., Sammeth, M., Beato, M., Valcárcel, J., & Guigó, R. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1658 · Cited by 479
Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis
Baranzini, S. E., Mudge, J., van Velkinburgh, J. C., Khankhanian, P., Khrebtukova, I., Miller, N. A., Zhang, L., Farmer, A. D., Bell, C. J., Kim, R. W., et al. (2010) · Nature · doi:10.1038/nature08990 · Cited by 476
“2), in agreement with a previous study 17 .”
Self-citationShapiro, I. M., Cheng, A. W., Flytzanis, N. C., Balsamo, M., Condeelis, J. S., Oktay, M. H., Burge, C. B., & Gertler, F. B. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002218 · Cited by 476
Self-citationRaj, B., & Blencowe, B. J. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.004 · Cited by 475
Genome-wide analysis of the MYB transcription factor superfamily in soybean
Du, H., Yang, S., Liang, Z., Feng, B.-R., Liu, L., Huang, Y., & Tang, Y. (2012) · BMC Plant Biology · doi:10.1186/1471-2229-12-106 · Cited by 474
Huelga, S. C., Vu, A. Q., Arnold, J. D., Liang, T. Y., Liu, P. P., Yan, B. Y., Donohue, J. P., Shiue, L., Hoon, S., Brenner, S., et al. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.02.001 · Cited by 470
Xue, Y., Zhou, Y., Wu, T., Zhu, T., Ji, X., Kwon, Y.-S., Zhang, C., Yeo, G., Black, D. L., Sun, H., et al. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.12.003 · Cited by 469
From single-cell to cell-pool transcriptomes: Stochasticity in gene expression and RNA splicing
Marinov, G. K., Williams, B. A., McCue, K., Schroth, G. P., Gertz, J., Myers, R. M., & Wold, B. J. (2014) · Genome Research · doi:10.1101/gr.161034.113 · Cited by 468
Self-citationStatistical inferences for isoform expression in RNA-Seq
Jiang, H., & Wong, W. H. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp113 · Cited by 468
Anczuków, O., Rosenberg, A. Z., Akerman, M., Das, S., Zhan, L., Karni, R., Muthuswamy, S. K., & Krainer, A. R. (2012) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2207 · Cited by 464
Long Noncoding RNAs with snoRNA Ends
Yin, Q.-F., Yang, L. C., Zhang, Y., Xiang, J., Wu, Y., Carmichael, G., & Chen, L. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.07.033 · Cited by 464
Regulation of Alternative Splicing Through Coupling with Transcription and Chromatin Structure
Naftelberg, S., Schor, I. E., Ast, G., & Kornblihtt, A. R. (2015) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060614-034242 · Cited by 462
Sharp, P. A. (2009) · Cell · doi:10.1016/j.cell.2009.02.007 · Cited by 462
Uncovering the Complexity of Transcriptomes with RNA-Seq
Costa, V., Angelini, C., Feis, I. D., & Ciccodicola, A. (2010) · BioMed Research International · doi:10.1155/2010/853916 · Cited by 460
Divergent transcription of long noncoding RNA/mRNA gene pairs in embryonic stem cells
Sigova, A. A., Mullen, A. C., Molinié, B., Gupta, S., Orlando, D. A., Guenther, M. G., Almada, A. E., Lin, C. Y., Sharp, P. A., Giallourakis, C. C., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1221904110 · Cited by 459
Analysis of alternative cleavage and polyadenylation by 3′ region extraction and deep sequencing
Hoque, M., Ji, Z., Zheng, D., Luo, W., Li, W., You, B., Park, J. Y., Yehia, G., & Tian, B. (2012) · Nature Methods · doi:10.1038/nmeth.2288 · Cited by 456
Alternative splicing as a source of phenotypic diversity
Wright, C. J., Smith, C. W. J., & Jiggins, C. D. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00514-4 · Cited by 454
A 360° view of circular RNAs: From biogenesis to functions
Wilusz, J. E. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1478 · Cited by 446
Seiler, M., Peng, S., Agrawal, A. A., Palacino, J. J., Teng, T., Zhu, P., Smith, P. G., Johnson, R., Demchok, J. A., Felau, I., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.01.088 · Cited by 445
The emerging roles and functions of circular RNAs and their generation
Yu, C., & Kuo, H. (2019) · Journal of Biomedical Science · doi:10.1186/s12929-019-0523-z · Cited by 443
Complex and dynamic landscape of RNA polyadenylation revealed by PAS-Seq
Shepard, P. J., Choi, E., Lu, J., Flanagan, L. A., Hertel, K. J., & Shi, Y. (2011) · RNA · doi:10.1261/rna.2581711 · Cited by 440
Most “Dark Matter” Transcripts Are Associated With Known Genes
van Bakel, H., Nislow, C., Blencowe, B. J., & Hughes, T. R. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000371 · Cited by 439
Ward, A. J., & Cooper, T. A. (2009) · The Journal of Pathology · doi:10.1002/path.2649 · Cited by 436
Genomewide characterization of non-polyadenylated RNAs
Yang, L. C., Duff, M. O., Graveley, B. R., Carmichael, G., & Chen, L. (2011) · Genome biology · doi:10.1186/gb-2011-12-2-r16 · Cited by 436
Cell-cell communication: New insights and clinical implications
Su, J., Song, Y., Zhu, Z., Huang, X., Fan, J., Qiao, J., & Mao, F. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01888-z · Cited by 433
SMN2 splice modulators enhance U1–pre-mRNA association and rescue SMA mice
Palacino, J., Swalley, S. E., Song, C., Cheung, A. K., Shu, L., Zhang, X., Van Hoosear, M., Shin, Y., Chin, D. N., Keller, C. G., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1837 · Cited by 432
Tissue-specific alternative splicing remodels protein-protein interaction networks
Ellis, J. D., Barrios-Rodiles, M., Çolak, R., Irimia, M., Kim, T., Calarco, J. A., Wang, X., Pan, Q., O'Hanlon, D., Kim, P. M., et al. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.05.037 · Cited by 431
Babu, M. M. (2016) · Biochemical Society Transactions · doi:10.1042/bst20160172 · Cited by 431
Lévesque, C. A., Brouwer, H., Cano, L. M., Hamilton, J. P., Holt, C., Huitema, E., Raffaele, S., Robideau, G. P., Thines, M., Win, J., et al. (2010) · Genome biology · doi:10.1186/gb-2010-11-7-r73 · Cited by 426
Evolution of SR protein and hnRNP splicing regulatory factors
Busch, A., & Hertel, K. J. (2011) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.100 · Cited by 418
Molecular mechanisms of eukaryotic pre-mRNA 3′ end processing regulation
Millevoi, S., & Vagner, S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp1176 · Cited by 416
Mapping in vivo protein-RNA interactions at single-nucleotide resolution from HITS-CLIP data
Zhang, C., & Darnell, R. B. (2011) · Nature Biotechnology · doi:10.1038/nbt.1873 · Cited by 414
Raj, T., Li, Y. I., Wong, G., Humphrey, J., Wang, M., Ramdhani, S., Wang, Y.-C., Ng, B., Gupta, I., Haroutunian, V., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0238-1 · Cited by 410
Widespread Polycistronic Transcripts in Fungi Revealed by Single-Molecule mRNA Sequencing
Gordon, S., Tseng, E., Salamov, A. A., Zhang, J., Meng, X., Zhao, Z., Kang, D., Underwood, J. G., Grigoriev, I. V., Figueroa, M., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0132628 · Cited by 410
Upf1 Senses 3′UTR Length to Potentiate mRNA Decay
Hogg, J. R., & Goff, S. P. (2010) · Cell · doi:10.1016/j.cell.2010.10.005 · Cited by 408
Evolution of human-specific neural SRGAP2 genes by incomplete segmental duplication
Dennis, M. Y., Nuttle, X., Sudmant, P. H., Antonacci, F., Graves, T. A., Nefedov, M., Rosenfeld, J. A., Sajjadian, S., Malig, M., Kotkiewicz, H., et al. (2012) · Cell · doi:10.1016/j.cell.2012.03.033 · Cited by 407
Lambert, N. J., Robertson, A. D., Jangi, M., McGeary, S. E., Sharp, P. A., & Burge, C. B. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.04.016 · Cited by 407
Self-citationDynamic integration of splicing within gene regulatory pathways
Braunschweig, U., Gueroussov, S., Plocik, A. M., Graveley, B. R., & Blencowe, B. J. (2013) · Cell · doi:10.1016/j.cell.2013.02.034 · Cited by 406
De novo transcriptome assembly with ABySS
Birol, İ., Jackman, S. D., Nielsen, C. B., Qian, J. Q., Varhol, R., Stazyk, G., Morin, R. D., Zhao, Y., Hirst, M., Schein, J. E., et al. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp367 · Cited by 403
A guide for the diagnosis of rare and undiagnosed disease: beyond the exome
Marwaha, S., Knowles, J. W., & Ashley, E. A. (2022) · Genome Medicine · doi:10.1186/s13073-022-01026-w · Cited by 401
Reliable Identification of Genomic Variants from RNA-Seq Data
Piskol, R., Ramaswami, G., & Li, J. B. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.08.008 · Cited by 398
Buljan, M., Chalancon, G., Eustermann, S., Wagner, G. P., Fuxreiter, M., Bateman, A., & Babu, M. M. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.05.039 · Cited by 396
“Together with gene duplication and recombination, alternative splicing plays a major role in increasing proteome diversity and organismal complexity (Keren et al., 2010; Nilsen and Graveley, 2010; Romero et al., 2006; Wang et al., 2008).”
A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
Yu, Y., Fuscoe, J. C., Zhao, C., Guo, C., Jia, M., Qing, T., Bannon, D. I., Lancashire, L., Bao, W., Du, T., et al. (2014) · Nature Communications · doi:10.1038/ncomms4230 · Cited by 395
The real cost of sequencing: higher than you think!
Sboner, A., Mu, X. J., Greenbaum, D. S., Auerbach, R. K., & Gerstein, M. (2011) · Genome biology · doi:10.1186/gb-2011-12-8-125 · Cited by 393
Pattern recognition receptors: function, regulation and therapeutic potential
Chen, R., Zou, J., Chen, J., Zhong, X. Y., Kang, R., & Tang, D. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02264-1 · Cited by 392
New insights into the aetiology of colorectal cancer from genome-wide association studies
Tenesa, A., & Dunlop, M. G. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2574 · Cited by 388
The Pivotal Regulatory Landscape of RNA Modifications
Li, S., & Mason, C. E. (2014) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-090413-025405 · Cited by 386
Biased Chromatin Signatures around Polyadenylation Sites and Exons
Spies, N., Nielsen, C. B., Padgett, R. A., & Burge, C. B. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.10.008 · Cited by 385
Self-citationThe Expanding Landscape of Alternative Splicing Variation in Human Populations
Park, E., Pan, Z., Zhang, Z., Lin, L., & Xing, Y. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.11.002 · Cited by 385
An ESRP‐regulated splicing programme is abrogated during the epithelial–mesenchymal transition
Warzecha, C. C., Jiang, P., Amirikian, K., Dittmar, K. A., Lu, H., Shen, S., Guo, W., Xing, Y., & Carstens, R. P. (2010) · The EMBO Journal · doi:10.1038/emboj.2010.195 · Cited by 383
Transcriptomics in the RNA-seq era
McGettigan, P. (2013) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2012.12.008 · Cited by 383
HITS-CLIP: panoramic views of protein-RNA regulation in living cells
Darnell, R. B. (2010) · WIREs RNA · doi:10.1002/wrna.31 · Cited by 382
Byrne, A., Beaudin, A. E., Olsen, H. E., Jain, M., Cole, C., Palmer, T., DuBois, R. M., Forsberg, E. C., Akeson, M., & Vollmers, C. (2017) · Nature Communications · doi:10.1038/ncomms16027 · Cited by 379
Post-transcriptional regulation of gene expression in innate immunity
Carpenter, S. B., Ricci, E. P., Mercier, B. C., Moore, M. J., & Fitzgerald, K. A. (2014) · Nature reviews. Immunology · doi:10.1038/nri3682 · Cited by 374
Defining the transcriptome and proteome in three functionally different human cell lines
Lundberg, E., Fagerberg, L., Klevebring, D., Matic, I., Geiger, T., Cox, J., Älgenäs, C., Lundeberg, J., Mann, M., & Uhlen, M. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.106 · Cited by 373
Shen, S., Park, J. W., Huang, J., Dittmar, K. A., Lu, Z., Zhou, Q., Carstens, R. P., & Xing, Y. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1291 · Cited by 373
A Comparative Study of Techniques for Differential Expression Analysis on RNA-Seq Data
Zhang, Z. H., Jhaveri, D. J., Marshall, V. M., Bauer, D. C., Edson, J., Narayanan, R. K., Robinson, G. J., Lundberg, A. E., Bartlett, P. F., Wray, N. R., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103207 · Cited by 373
Widespread intron retention diversifies most cancer transcriptomes
Dvinge, H., & Bradley, R. K. (2015) · Genome Medicine · doi:10.1186/s13073-015-0168-9 · Cited by 372
Predicting Protein–Protein Interactions from the Molecular to the Proteome Level
Keskin, O., Tuncbag, N., & Gursoy, A. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00683 · Cited by 369
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
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