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Cited by 290RNA Research and SplicingGenomics and Phylogenetic StudiesGenomics and Chromatin Dynamics

Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues

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Reyes, Alejandro, Huber, Wolfgang·2018·Nucleic Acids Research
DOI 10.1093/nar/gkx1165PMC PMC5778607

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Abstract

Most human genes generate multiple transcript isoforms. The differential expression of these isoforms can help specify cell types. Diverse transcript isoforms arise from the use of alternative transcription start sites, polyadenylation sites and splice sites; however, the relative contribution of these processes to isoform diversity in normal human physiology is unclear. To address this question, we investigated cell type-dependent differences in exon usage of over 18 000 protein-coding genes in 23 cell types from 798 samples of the Genotype-Tissue Expression Project. We found that about half of the expressed genes displayed tissue-dependent transcript isoforms. Alternative transcription start and termination sites, rather than alternative splicing, accounted for the majority of tissue-dependent exon usage. We confirmed the widespread tissue-dependent use of alternative transcription start sites in a second, independent dataset, Cap Analysis of Gene Expression data from the FANTOM consortium. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not increase proteome complexity. Thus, alternative transcription start and termination sites are the principal drivers of transcript isoform diversity across tissues, and may underlie the majority of cell type specific proteomes and functions.

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  1. [1]de Klerk E., ’t Hoen P.A. Alternative mRNA transcription, processing, and translation: insights from RNA sequencing. Trends Genet. 2015; 31: 128– 139. 25648499
  2. [2]Breitbart R.E., Andreadis A., Nadal-Ginard B. Alternative splicing: a ubiquitous mechanism for the generation of multiple protein isoforms from single genes. Annu. Rev. Biochem. 1987; 56: 467– 495. 3304142
  3. [3]Keren H., Lev-Maor G., Ast G. Alternative splicing and evolution: diversification, exon definition and function. Nat. Rev. Genet. 2010; 11: 345– 355. 20376054
  4. [5]Tian B., Manley J.L. Alternative polyadenylation of mRNA precursors. Nat. Rev. Mol. Cell Biol. 2016; 18: 18– 30. 27677860 PMC5483950
  5. [6]Wang E.T., Sandberg R., Luo S., Khrebtukova I., Zhang L., Mayr C., Kingsmore S.F., Schroth G.P., Burge C.B. Alternative isoform regulation in human tissue transcriptomes. Nature. 2008; 456: 470– 476. 18978772 PMC2593745
  6. [7]Pan Q., Shai O., Lee L.J., Frey B.J., Blencowe B.J. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat. Genet. 2008; 40: 1413– 1415. 18978789
  7. [8]Forrest A.R.R., Kawaji H., Rehli M., Kenneth Baillie J., de Hoon M. J.L., Haberle V., Lassmann T., Kulakovskiy I.V., Lizio M., Itoh M. A promoter-level mammalian expression atlas. Nature. 2014; 507: 462– 470. 24670764 PMC4529748
  8. [10]Kim E., Magen A., Ast G. Different levels of alternative splicing among eukaryotes. Nucleic Acids Res. 2006; 35: 125– 131. 17158149 PMC1802581
  9. [11]Pozner A., Lotem J., Xiao C., Goldenberg D., Brenner O., Negreanu V., Levanon D., Groner Y. Developmentally regulated promoter-switch transcriptionally controls Runx1 function during embryonic hematopoiesis. BMC Dev. Biol. 2007; 7: 84. 17626615 PMC1941738
  10. [12]Gabut M., Samavarchi-Tehrani P., Wang X., Slobodeniuc V., O’Hanlon D., Sung H.-K., Alvarez M., Talukder S., Pan Q., Mazzoni E. An alternative splicing switch regulates embryonic stem cell pluripotency and reprogramming. Cell. 2011; 147: 132– 146. 21924763
  11. [13]Li Y.I., van de Geijn B., Raj A., Knowles D.A., Petti A.A., Golan D., Gilad Y., Pritchard J.K. RNA splicing is a primary link between genetic variation and disease. Science. 2016; 352: 600– 604. 27126046 PMC5182069
  12. [14]Xiong H.Y., Alipanahi B., Lee L.J., Bretschneider H., Merico D., Yuen R. K.C., Hua Y., Gueroussov S., Najafabadi H.S., Hughes T.R. The human splicing code reveals new insights into the genetic determinants of disease. Science. 2014; 347: 1254806. 25525159 PMC4362528
  13. [16]Sendoel A., Dunn J.G., Rodriguez E.H., Naik S., Gomez N.C., Hurwitz B., Levorse J., Dill B.D., Schramek D., Molina H. Translation from unconventional 5’ start sites drives tumour initiation. Nature. 2017; 541: 494– 499. 28077873 PMC5287289
  14. [18]Yang X., Coulombe-Huntington J., Kang S., Sheynkman G., Hao T., Richardson A., Sun S., Yang F., Shen Y., Murray R. Widespread expansion of protein interaction capabilities by alternative splicing. Cell. 2016; 164: 805– 817. 26871637 PMC4882190
  15. [20]Tress M.L., Abascal F., Valencia A. Alternative splicing may not be the key to proteome complexity. Trends Biochem. Sci. 2017; 42: 98– 110. 27712956 PMC6526280
  16. [21]Rodriguez J.M., Maietta P., Ezkurdia I., Pietrelli A., Wesselink J.-J., Lopez G., Valencia A., Tress M.L. APPRIS: annotation of principal and alternative splice isoforms. Nucleic Acids Res. 2012; 41: D110– D117. 23161672 PMC3531113
  17. [22]Ezkurdia I., Rodriguez J.M., Carrillo-de Santa Pau E., Vázquez J., Valencia A., Tress M.L. Most highly expressed protein-coding genes have a single dominant isoform. J. Proteome Res. 2015; 14: 1880– 1887. 25732134 PMC4768900
  18. [23]Abascal F., Ezkurdia I., Rodriguez-Rivas J., Rodriguez J.M., del Pozo A., Vázquez J., Valencia A., Tress M.L. Alternatively spliced homologous exons have ancient origins and are highly expressed at the protein level. PLoS Comput. Biol. 2015; 11: e1004325. 26061177 PMC4465641
  19. [24]Lianoglou S., Garg V., Yang J.L., Leslie C.S., Mayr C. Ubiquitously transcribed genes use alternative polyadenylation to achieve tissue-specific expression. Genes Dev. 2013; 27: 2380– 2396. 24145798 PMC3828523
  20. [26]Floor S.N., Doudna J.A. Tunable protein synthesis by transcript isoforms in human cells. Elife. 2016; 5: e10921. 26735365 PMC4764583
  21. [27]Wang X., Hou J., Quedenau C., Chen W. Pervasive isoform–specific translational regulation via alternative transcription start sites in mammals. Mol. Syst. Biol. 2016; 12: 875. 27430939 PMC4965872
  22. [28]Shabalina S.A., Ogurtsov A.Y., Spiridonov N.A., Koonin E.V. Evolution at protein ends: major contribution of alternative transcription initiation and termination to the transcriptome and proteome diversity in mammals. Nucleic Acids Res. 2014; 42: 7132– 7144. 24792168 PMC4066770
  23. [29]Pal S., Gupta R., Kim H., Wickramasinghe P., Baubet V., Showe L.C., Dahmane N., Davuluri R.V. Alternative transcription exceeds alternative splicing in generating the transcriptome diversity of cerebellar development. Genome Res. 2011; 21: 1260– 1272. 21712398 PMC3149493
  24. [30]Florea L., Song L., Salzberg S.L. Thousands of exon skipping events differentiate among splicing patterns in sixteen human tissues [version 2; referees: 2 approved]. F1000Res. 2013; 2: 188. 24555089 PMC3892928
  25. [31]Hestand M.S., Zeng Z., Coleman S.J., Liu J., MacLeod J.N. Tissue restricted splice junctions originate not only from tissue-specific gene loci, but gene loci with a broad pattern of expression. PLoS One. 2015; 10: e0144302. 26713731 PMC4695084
  26. [32]Ni T., Yang Y., Hafez D., Yang W., Kiesewetter K., Wakabayashi Y., Ohler U., Peng W., Zhu J. Distinct polyadenylation landscapes of diverse human tissues revealed by a modified PA-seq strategy. BMC Genomics. 2013; 14: 615. 24025092 PMC3848854
  27. [34]Yates A., Akanni W., Amode M.R., Barrell D., Billis K., Carvalho-Silva D., Cummins C., Clapham P., Fitzgerald S., Gil L. Ensembl 2016. Nucleic Acids Res. 2015; 44: D710– D716. 26687719 PMC4702834
  28. [36]Anders S., Reyes A., Huber W. Detecting differential usage of exons from RNA-seq data. Genome Res. 2012; 22: 2008– 2017. 22722343 PMC3460195
  29. [37]Anders S., Pyl P.T., Huber W. HTSeq – a Python framework to work with high-throughput sequencing data. Bioinformatics. 2014; 31: 166– 169. 25260700 PMC4287950
  30. [38]Reyes A., Anders S., Weatheritt R.J., Gibson T.J., Steinmetz L.M., Huber W. Drift and conservation of differential exon usage across tissues in primate species. Proc. Natl. Acad. Sci. U.S.A. 2013; 110: 15377– 15382. 24003148 PMC3780897
  31. [39]Anders S., Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010; 11: R106. 20979621 PMC3218662
  32. [41]Ho D.E., Imai K., King G., Stuart E.A. MatchIt: nonparametric preprocessing for parametric causal inference. J. Stat. Softw. 2011; 42: 1– 28.
  33. [42]Huber W., Carey V.J., Gentleman R., Anders S., Carlson M., Carvalho B.S., Bravo H.C., Davis S., Gatto L., Girke T. Orchestrating high-throughput genomic analysis with Bioconductor. Nat. Methods. 2015; 12: 115– 121. 25633503 PMC4509590
  34. [43]Durinck S., Spellman P.T., Birney E., Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 2009; 4: 1184– 1191. 19617889 PMC3159387
  35. [44]Lawrence M., Huber W., Pagès H., Aboyoun P., Carlson M., Gentleman R., Morgan M.T., Carey V.J. Software for computing and annotating genomic ranges. PLoS Comput. Biol. 2013; 9: e1003118. 23950696 PMC3738458
  36. [46]Hahne F., Ivanek R. Visualizing genomic data using Gviz and Bioconductor. Statistical Genomics. 2016; 1418: 335– 351. 27008022
  37. [47]Mense S.M., Zhang L. Heme: a versatile signaling molecule controlling the activities of diverse regulators ranging from transcription factors to MAP kinases. Cell Res. 2006; 16: 681– 692. 16894358
  38. [48]Balwani M., Desnick R.J. The porphyrias: advances in diagnosis and treatment. Blood. 2012; 120: 4496– 4504. 22791288 PMC3512229
  39. [49]Roberts A.G., Redding S.J., Llewellyn D.H. An alternatively-spliced exon in the 5′-UTR of human ALAS1 mRNA inhibits translation and renders it resistant to haem-mediated decay. FEBS Lett. 2005; 579: 1061– 1066. 15710391
  40. [50]Hakim N.H.A., Kounishi T., Alam A.H.M.K., Tsukahara T., Suzuki H. Alternative splicing of MEF2C promoted by Fox-1 during neural differentiation in P19 cells. Genes Cells. 2010; 15: 255– 267. 20141540
  41. [51]Hopitzan A.A., Baines A.J., Ludosky M.-A., Recouvreur M., Kordeli E. Ankyrin-G in skeletal muscle: tissue-specific alternative splicing contributes to the complexity of the sarcolemmal cytoskeleton. Exp. Cell Res. 2005; 309: 86– 98. 15953600
  42. [52]Ritz K., van Schaik B.D., Jakobs M.E., van Kampen A.H., Aronica E., Tijssen M.A., Baas F. SGCE isoform characterization and expression in human brain: implications for myoclonus–dystonia pathogenesis?. Eur. J. Hum. Genet. 2010; 19: 438– 444. 21157498 PMC3060322
  43. [53]Sielski N.L., Ihnatovych I., Hagen J.J., Hofmann W.A. Tissue specific expression of Myosin IC isoforms. BMC Cell Biol. 2014; 15: 8. 24618359 PMC3984714
  44. [54]Muller J., Cacace A.M., Lyons W.E., McGill C.B., Morrison D.K. Identification of B-KSR1, a novel brain-specific isoform of KSR1 that functions in neuronal signaling. Mol. Cell. Biol. 2000; 20: 5529– 5539. 10891492 PMC86003
  45. [55]Clark T.A., Schweitzer A.C., Chen T.X., Staples M.K., Lu G., Wang H., Williams A., Blume J.E. Discovery of tissue-specific exons using comprehensive human exon microarrays. Genome Biol. 2007; 8: R64. 17456239 PMC1896007
  46. [56]Hayakawa M., Sakashita E., Ueno E., Tominaga S.-i., Hamamoto T., Kagawa Y., Endo H. Muscle-specific exonic splicing silencer for exon exclusion in human ATP Synthase gamma-subunit pre-mRNA. J. Biol. Chem. 2001; 277: 6974– 6984. 11744705
  47. [57]Guerrero-Castillo S., Cabrera-Orefice A., Huynen M.A., Arnold S. Identification and evolutionary analysis of tissue-specific isoforms of mitochondrial complex I subunit NDUFV3. Biochim. Biophys. Acta. 2017; 1858: 208– 217. 27988283
  48. [58]Mele 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. The human transcriptome across tissues and individuals. Science. 2015; 348: 660– 665. 25954002 PMC4547472
  49. [60]Liu S.J., Horlbeck M.A., Cho S.W., Birk H.S., Malatesta M., He D., Attenello F.J., Villalta J.E., Cho M.Y., Chen Y. CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells. Science. 2016; 355: aah7111. 27980086 PMC5394926
  50. [61]Han H., Braunschweig U., Gonatopoulos-Pournatzis T., Weatheritt R.J., Hirsch C.L., Ha K.C., Radovani E., Nabeel-Shah S., Sterne-Weiler T., Wang J. Multilayered control of alternative splicing regulatory networks by transcription factors. Mol. Cell. 2017; 65: 539– 553. 28157508

Cited by

Sorted by citations

Authors
Reyes, A., & Huber, W.
Affiliations
  • Harvard University (US)
  • European Molecular Biology Laboratory (DE)
Corresponding author
  • Reyes, Alejandro
  • Huber, Wolfgang
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2017-11-30
Volume
46
Issue
2
Pages
582-592
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkx1165
PMC
PMC5778607
OpenAlex
W2775755225
Cited by
290
References
11
Citations by year
2026: 30 · 2025: 31 · 2024: 26 · 2023: 28 · 2022: 39 · 2021: 40 · 2020: 48 · 2019: 33 · 2018: 14 · 2017: 1
FWCI
10.84
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders
  • European Commission (H2020, 633974)
  • National Institutes of Health (H2020)
  • Horizon 2020 Framework Programme (633974)
  • National Human Genome Research Institute (R01HG005220)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
alternative transcription start sites, alternative polyadenylation, mRNA isoforms, exon usage, tissue-specific gene expression, alternative splicing, proteome complexity, FANTOM
MeSH terms
Algorithms, Exons, Humans, Models, Genetic, Transcription, Genetic, Alternative Splicing, Gene Expression Profiling, Transcription Initiation Site, Polyadenylation, RNA Isoforms

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