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
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Full-length transcriptome assembly from RNA-Seq data without a reference genome
Grabherr, M. G., Haas, B. J., Yassour, M., Levin, J. Z., Thompson, D. A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.1883 · Cited by 21,201
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
StringTie enables improved reconstruction of a transcriptome from RNA-seq reads
Pertea, M., Pertea, G. M., Antonescu, C. M., Chang, T.-C., Mendell, J. T., & Salzberg, S. L. (2015) · Nature Biotechnology · doi:10.1038/nbt.3122 · Cited by 14,406
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682
A scaling normalization method for differential expression analysis of RNA-seq data
Robinson, M. D., & Oshlack, A. (2010) · Genome Biology · doi:10.1186/gb-2010-11-3-r25 · Cited by 7,876
Gene ontology analysis for RNA-seq: accounting for selection bias
Young, M. D., Wakefield, M. J., Smyth, G. K., & Oshlack, A. (2010) · Genome Biology · doi:10.1186/gb-2010-11-2-r14 · Cited by 7,107
UniProt: the universal protein knowledgebase in 2021
The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875
“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).”
BackgroundFull-length RNA-seq from single cells using Smart-seq2
Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137
Self-citationmRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969
Differential analysis of gene regulation at transcript resolution with RNA-seq
Trapnell, C., Hendrickson, D. G., Sauvageau, M., Goff, L., Rinn, J. L., & Pachter, L. (2013) · Nature Biotechnology · doi:10.1038/nbt.2450 · Cited by 3,492
Predicting splicing from primary sequence with deep learning
Jaganathan, K., Kyriazopoulou Panagiotopoulou, S., McRae, J. F., Darbandi, S. F., Knowles, D., Li, Y. I., Kosmicki, J. A., Arbelaez, J., Cui, W., Schwartz, G. B., et al. (2019) · Cell · doi:10.1016/j.cell.2018.12.015 · Cited by 2,853
Shen, S., Park, J. W., Lu, Z.-X., Lin, L., Henry, M. D., Wu, Y. N., Zhou, Q., & Xing, Y. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419161111 · Cited by 2,713
Opportunities and challenges in long-read sequencing data analysis
Amarasinghe, S. L., Su, S., Dong, X., Zappia, L., Ritchie, M. E., & Gouil, Q. (2020) · Genome Biology · doi:10.1186/s13059-020-1935-5 · Cited by 2,530
Intrinsically disordered proteins in cellular signalling and regulation
Wright, P. E., & Dyson, H. J. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3920 · Cited by 2,482
Tripathi, V., Ellis, J. D., Shen, Z., Song, D. Y., Pan, Q., Watt, A. T., Freier, S. M., Bennett, C. F., Sharma, A., Bubulya, P. A., et al. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.08.011 · Cited by 2,291
Expansion of the eukaryotic proteome by alternative splicing
Nilsen, T. W., & Graveley, B. R. (2010) · Nature · doi:10.1038/nature08909 · Cited by 2,270
RNA sequencing: advances, challenges and opportunities
Ozsolak, F., & Milos, P. M. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2934 · Cited by 2,135
FMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072
RNA sequencing: the teenage years
Stark, R., Grzelak, M., & Hadfield, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0150-2 · Cited by 2,041
Transcriptome assembly from long-read RNA-seq alignments with StringTie2
Kovaka, S., Zimin, A. V., Pertea, G. M., Razaghi, R., Salzberg, S. L., & Pertea, M. (2019) · Genome biology · doi:10.1186/s13059-019-1910-1 · Cited by 2,041
Fast and SNP-tolerant detection of complex variants and splicing in short reads
Wu, T. D., & Nacu, S. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq057 · Cited by 1,894
Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps
Chi, S. W., Zang, J. B., Mele, A., & Darnell, R. B. (2009) · Nature · doi:10.1038/nature08170 · Cited by 1,791
Improving RNA-Seq expression estimates by correcting for fragment bias
Roberts, A., Trapnell, C., Donaghey, J., Rinn, J. L., & Pachter, L. (2011) · Genome Biology · doi:10.1186/gb-2011-12-3-r22 · Cited by 1,725
Long Noncoding RNAs with Enhancer-like Function in Human Cells
Ørom, U. A., Derrien, T., Beringer, M., Gumireddy, K., Gardini, A., Bussotti, G., Lai, F., Zytnicki, M., Notredame, C., Huang, Q., et al. (2010) · Cell · doi:10.1016/j.cell.2010.09.001 · Cited by 1,721
Bullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-94 · Cited by 1,680
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges
Khatri, P., Sirota, M., & Butte, A. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002375 · Cited by 1,635
Mayr, C., & Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.06.016 · Cited by 1,613
Self-citationFull-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells
Ramsköld, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O. R., Daniels, G. A., Khrebtukova, I., Loring, J. F., Laurent, L. C., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2282 · Cited by 1,609
Self-citationDetecting differential usage of exons from RNA-seq data
Anders, S., Reyes, A., & Huber, W. (2012) · Genome Research · doi:10.1101/gr.133744.111 · Cited by 1,545
The developmental transcriptome of Drosophila melanogaster
Graveley, B. R., Brooks, A. N., Carlson, J. W., Duff, M. O., Landolin, J. M., Yang, L. C., Artieri, C. G., van Baren, M. J., Boley, N. P., Booth, B. W., et al. (2010) · Nature · doi:10.1038/nature09715 · Cited by 1,504
Sequencing depth and coverage: key considerations in genomic analyses
Sims, D., Sudbery, I. M., Ilott, N. E., Heger, A., & Ponting, C. P. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3642 · Cited by 1,488
Oases:robustde novoRNA-seq assembly across the dynamic range of expression levels
Schulz, M. H., Zerbino, D. R., Vingron, M., & Birney, E. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts094 · Cited by 1,470
Bennett, C. F., & Swayze, E. E. (2010) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pharmtox.010909.105654 · Cited by 1,431
Dillies, M., Rau, A., Aubert, J., Hennequet‐Antier, C., Jeanmougin, M., Servant, N., Keime, C., Marot, G., Castel, D., Estellé, J., et al. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs046 · Cited by 1,363
Analysis and design of RNA sequencing experiments for identifying isoform regulation
Katz, Y., Wang, E. T., Airoldi, E. M., & Burge, C. B. (2010) · Nature Methods · doi:10.1038/nmeth.1528 · Cited by 1,353
Self-citationHITS-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
Long pre-mRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43
Polymenidou, M., Lagier-Tourenne, C., Hutt, K. R., Huelga, S. C., Moran, J., Liang, T. Y., Ling, S.-C., Sun, E., Wancewicz, E., Mazur, C., et al. (2011) · Nature Neuroscience · doi:10.1038/nn.2779 · Cited by 1,335
Alternative splicing as a regulator of development and tissue identity
Baralle, F. E., & Giudice, J. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.27 · Cited by 1,333
Araport11: a complete reannotation of the Arabidopsis thaliana reference genome
Cheng, C., Krishnakumar, V., Chan, A. P.-Y., Thibaud‐Nissen, F., Schobel, S., & Town, C. D. (2016) · The Plant Journal · doi:10.1111/tpj.13415 · Cited by 1,329
EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments
Leng, N., Dawson, J. A., Thomson, J. A., Ruotti, V., Rissman, A. I., Smits, B. M. G., Haag, J. D., Gould, M. N., Stewart, R. M., & Kendziorski, C. M. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt087 · Cited by 1,310
The human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304
Personal omics profiling reveals dynamic molecular and medical phenotypes
Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y. K., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.009 · Cited by 1,291
Mechanisms and Regulation of Alternative Pre-mRNA Splicing
Lee, Y., & Rio, D. C. (2015) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060614-034316 · Cited by 1,291
Mechanisms of alternative splicing regulation: insights from molecular and genomics approaches
Chen, M., & Manley, J. L. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2777 · Cited by 1,284
Understanding mechanisms underlying human gene expression variation with RNA sequencing
Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K. (2010) · Nature · doi:10.1038/nature08872 · Cited by 1,256
Guttman, M., Garber, M., Levin, J. Z., Donaghey, J., Robinson, J., Adiconis, X., Fan, L., Koziol, M. J., Gnirke, A., Nusbaum, C., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1633 · Cited by 1,253
The evolution of gene expression levels in mammalian organs
Brawand, D., Soumillon, M., Necsulea, A., Julien, P., Csárdi, G., Harrigan, P., Weier, M., Liechti, A., Aximu-Petri, A., Kircher, M., et al. (2011) · Nature · doi:10.1038/nature10532 · Cited by 1,248
Cooper, T. A., Wan, L., & Dreyfuss, G. (2009) · Cell · doi:10.1016/j.cell.2009.02.011 · Cited by 1,198
Conserved Function of lincRNAs in Vertebrate Embryonic Development despite Rapid Sequence Evolution
Ulitsky, I., Shkumatava, A., Jan, C. H., Sive, H. L., & Bartel, D. P. (2011) · Cell · doi:10.1016/j.cell.2011.11.055 · Cited by 1,197
MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery
Wang, K., Singh, D., Zeng, Z., Coleman, S. J., Huang, Y., Savich, G. L., He, X., Mieczkowski, P., Grimm, S. A., Perou, C. M., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq622 · Cited by 1,193
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177
Scotti, M. M., & Swanson, M. S. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.3 · Cited by 1,163
Integrative omics for health and disease
Karczewski, K. J., & Snyder, M. P. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.4 · Cited by 1,158
A high-resolution map of human evolutionary constraint using 29 mammals
Broad Institute Sequencing Platform and Whole Genome Assembly Team, Lindblad-Toh, K., Baylor College of Medicine Human Genome Sequencing Center Sequencing Team, Genome Institute at Washington University, Garber, M., Zuk, O., Lin, M. F., Parker, B. J., Washietl, S., Kheradpour, P., et al. (2011) · Nature · doi:10.1038/nature10530 · Cited by 1,108
Goodall, G. J., & Wickramasinghe, V. O. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-00306-0 · Cited by 1,090
Alternative splicing and evolution: diversification, exon definition and function
Keren, H., Lev-Maor, G., & Ast, G. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2776 · Cited by 1,082
Computational methods for transcriptome annotation and quantification using RNA-seq
Garber, M., Grabherr, M. G., Guttman, M., & Trapnell, C. (2011) · Nature Methods · doi:10.1038/nmeth.1613 · Cited by 1,042
A Tissue-Mapped Axolotl De Novo Transcriptome Enables Identification of Limb Regeneration Factors
Bryant, D. M., Johnson, K. A., DiTommaso, T., Tickle, T. L., Couger, M. B., Payzin‐Dogru, D., Lee, T. J., Leigh, N. D., Kuo, T., Davis, F. G., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2016.12.063 · Cited by 1,014
SEQC/MAQC-III Consortium (2014) · Nature Biotechnology · doi:10.1038/nbt.2957 · Cited by 983
Self-citationCTCF-promoted RNA polymerase II pausing links DNA methylation to splicing
Shukla, S., Kavak, E., Gregory, M., Imashimizu, M., Shutinoski, B., Kashlev, M., Oberdoerffer, P., Sandberg, R., & Oberdoerffer, S. (2011) · Nature · doi:10.1038/nature10442 · Cited by 973
Self-citationEvolutionary Dynamics of Gene and Isoform Regulation in Mammalian Tissues
Merkin, J., Russell, C., Chen, P., & Burge, C. B. (2012) · Science · doi:10.1126/science.1228186 · Cited by 972
Self-citationSchurch, N. J., Schofield, P., Gierliński, M., Cole, C., Sherstnev, A., Singh, V., Wrobel, N., Gharbi, K., Simpson, G. G., Owen-Hughes, T., et al. (2016) · RNA · doi:10.1261/rna.053959.115 · Cited by 966
Single-Cell RNA-Seq Technologies and Related Computational Data Analysis
Chen, G., Ning, B., & Shi, T. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00317 · Cited by 966
Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq
Islam, S., Kjällquist, U., Moliner, A., Zajac, P., Fan, J.-B., Lönnerberg, P., & Linnarsson, S. (2011) · Genome Research · doi:10.1101/gr.110882.110 · Cited by 949
In situ sequencing for RNA analysis in preserved tissue and cells
Ke, R., Mignardi, M., Pacureanu, A., Svedlund, J., Botling, J., Wählby, C., & Nilsson, M. (2013) · Nature Methods · doi:10.1038/nmeth.2563 · Cited by 934
Barash, Y., Calarco, J. A., Gao, W., Pan, Q., Wang, X., Shai, O., Blencowe, B. J., & Frey, B. J. (2010) · Nature · doi:10.1038/nature09000 · Cited by 925
Genome-wide mapping of alternative splicing in Arabidopsis thalianaPreprint
Filichkin, S. A., Priest, H. D., Givan, S. A., Shen, R., Bryant, D. W., Fox, S. E., Wong, W., & Mockler, T. C. (2009) · Genome Research · doi:10.1101/gr.093302.109 · Cited by 917
Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients
Kahles, A., Lehmann, K.-V., Toussaint, N. C., Hüser, M., Stark, S. G., Sachsenberg, T. T., Stegle, O., Kohlbacher, O., Sander, C., Johnson, R., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.07.001 · Cited by 914
How many human proteoforms are there?
Aebersold, R., Agar, J. N., Amster, I. J., Baker, M. S., Bertozzi, C. R., Boja, E. S., Costello, C. E., Cravatt, B. F., Fenselau, C., Garcia, B. A., et al. (2018) · Nature Chemical Biology · doi:10.1038/nchembio.2576 · Cited by 907
Next-Generation Sequencing: From Basic Research to Diagnostics
Voelkerding, K. V., Dames, S. A., & Durtschi, J. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2008.112789 · Cited by 903
Molecular mechanisms of ROS production and oxidative stress in diabetes
Newsholme, P., Cruzat, V. F., Keane, K. N., Carlessi, R., & de Bittencourt, P. I. H. (2016) · Biochemical Journal · doi:10.1042/bcj20160503c · Cited by 878
Complexity of the Alternative Splicing Landscape in Plants
Reddy, A. S. N., Márquez, Y., Kalyna, M., & Barta, A. (2013) · The Plant Cell · doi:10.1105/tpc.113.117523 · Cited by 867
Alternative pre-mRNA splicing regulation in cancer: pathways and programs unhingedPreprint
David, C. J., & Manley, J. L. (2010) · Genes & Development · doi:10.1101/gad.1973010 · Cited by 848
Improving genetic diagnosis in Mendelian disease with transcriptome sequencing
Cummings, B. B., Marshall, J. L., Tukiainen, T., Lek, M., Donkervoort, S., Foley, A. R., Bolduc, V., Waddell, L. B., Sandaradura, S. A., O’Grady, G. L., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aal5209 · Cited by 831
Epigenetics in Alternative Pre-mRNA Splicing
Luco, R. F., Alló, M., Schor, I. E., Kornblihtt, A. R., & Misteli, T. (2011) · Cell · doi:10.1016/j.cell.2010.11.056 · Cited by 827
An Abundance of Ubiquitously Expressed Genes Revealed by Tissue Transcriptome Sequence Data
Ramsköld, D., Wang, E. T., Burge, C. B., & Sandberg, R. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000598 · Cited by 820
Self-citationAlternative cleavage and polyadenylation: extent, regulation and function
Elkon, R., Ugalde, A. P., & Agami, R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3482 · Cited by 816
Gustavsson, E. K., Zhang, D., Reynolds, R. H., García-Ruiz, S., & Ryten, M. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac409 · Cited by 799
Transcriptome genetics using second generation sequencing in a Caucasian population
Montgomery, S. B., Sammeth, M., Gutierrez-Arcelus, M., Lach, R. P., Ingle, C., Nisbett, J., Guigo, R., & Dermitzakis, E. T. (2010) · Nature · doi:10.1038/nature08903 · Cited by 797
CellRank for directed single-cell fate mapping
Lange, M., Bergen, V., Klein, M., Setty, M. N., Reuter, B., Bakhti, M., Lickert, H., Ansari, M., Gote-Schniering, J., Schiller, H. B., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01346-6 · Cited by 783
Dual RNA-seq of pathogen and host
Westermann, A. J., Gorski, S. A., & Vogel, J. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2852 · Cited by 782
Alternative Splicing Regulatory Networks: Functions, Mechanisms, and Evolution
Ule, J., & Blencowe, B. J. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.09.017 · Cited by 780
RNA processing and its regulation: global insights into biological networks
Licatalosi, D. D., & Darnell, R. B. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2673 · Cited by 777
RNA Splicing by the Spliceosome
Wilkinson, M. E., Charenton, C., & Nagai, K. (2019) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-091719-064225 · Cited by 764
Tripathi, V., Shen, Z., Chakraborty, A., Giri, S., Freier, S. M., Wu, X., Zhang, Y., Gorospe, M., Prasanth, S. G., Lal, A., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003368 · Cited by 763
Roles and mechanisms of alternative splicing in cancer — implications for care
Bonnal, S., López‐Oreja, I., & Valcárcel, J. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-0350-x · Cited by 760
Comprehensive comparative analysis of strand-specific RNA sequencing methods
Levin, J. Z., Yassour, M., Adiconis, X., Nusbaum, C., Thompson, D. A., Friedman, N., Gnirke, A., & Regev, A. (2010) · Nature Methods · doi:10.1038/nmeth.1491 · Cited by 753
RNA ‐Seq methods for transcriptome analysis
Hrdličková, R., Toloue, M., & Tian, B. (2016) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1364 · Cited by 746
Mechanisms and Consequences of Alternative Polyadenylation
Di Giammartino, D. C., Nishida, K., & Manley, J. L. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.08.017 · Cited by 737
Diversity and dynamics of the Drosophila transcriptome
Brown, J., Boley, N. P., Eisman, R. C., May, G. E., Stoiber, M. H., Duff, M. O., Booth, B. W., Wen, J., Park, S. H., Suzuki, A. M., et al. (2014) · Nature · doi:10.1038/nature12962 · Cited by 737
Functional consequences of developmentally regulated alternative splicing
Kalsotra, A., & Cooper, T. A. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3052 · Cited by 729
Spinal muscular atrophy: why do low levels of survival motor neuron protein make motor neurons sick?
Burghes, A. H. M., & Beattie, C. E. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2670 · Cited by 723
Trincado, J. L., Entizne, J. C., Hysenaj, G., Singh, B., Škalič, M., Elliott, D. J., & Eyras, E. (2018) · Genome biology · doi:10.1186/s13059-018-1417-1 · Cited by 720
Biases in Illumina transcriptome sequencing caused by random hexamer priming
Hansen, K. D., Brenner, S. E., & Dudoit, S. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq224 · Cited by 713
Evolution of microRNA diversity and regulation in animals
Berezikov, E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3079 · Cited by 712
RNA splicing factors as oncoproteins and tumour suppressors
Dvinge, H., Kim, E. H., Abdel-Wahab, O. I., & Bradley, R. K. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2016.51 · Cited by 706
A single-molecule long-read survey of the human transcriptome
Sharon, D., Tilgner, H., Grubert, F., & Snyder, M. (2013) · Nature Biotechnology · doi:10.1038/nbt.2705 · Cited by 701
FMRP targets distinct mRNA sequence elements to regulate protein expression
Ascano, M., Mukherjee, N., Bandaru, P., Miller, J. B., Nusbaum, J. D., Corcoran, D. L., Langlois, C., Munschauer, M., Dewell, S., Hafner, M., et al. (2012) · Nature · doi:10.1038/nature11737 · Cited by 701
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
