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Deciphering the splicing code

Author

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  • Yoseph Barash

    (Biomedical Engineering, University of Toronto, 10 King’s College Road, Toronto M5S 3G4, Canada
    Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada)

  • John A. Calarco

    (Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada)

  • Weijun Gao

    (Biomedical Engineering, University of Toronto, 10 King’s College Road, Toronto M5S 3G4, Canada)

  • Qun Pan

    (Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada)

  • Xinchen Wang

    (Biomedical Engineering, University of Toronto, 10 King’s College Road, Toronto M5S 3G4, Canada
    Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada)

  • Ofer Shai

    (Biomedical Engineering, University of Toronto, 10 King’s College Road, Toronto M5S 3G4, Canada)

  • Benjamin J. Blencowe

    (Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada)

  • Brendan J. Frey

    (Biomedical Engineering, University of Toronto, 10 King’s College Road, Toronto M5S 3G4, Canada
    Donnelly Centre, University of Toronto, 160 College Street, Toronto M5S 3E1, Canada
    Microsoft Research, 7 J. J. Thomson Avenue, Cambridge CB3 0FB, UK)

Abstract

Alternative splicing has a crucial role in the generation of biological complexity, and its misregulation is often involved in human disease. Here we describe the assembly of a ‘splicing code’, which uses combinations of hundreds of RNA features to predict tissue-dependent changes in alternative splicing for thousands of exons. The code determines new classes of splicing patterns, identifies distinct regulatory programs in different tissues, and identifies mutation-verified regulatory sequences. Widespread regulatory strategies are revealed, including the use of unexpectedly large combinations of features, the establishment of low exon inclusion levels that are overcome by features in specific tissues, the appearance of features deeper into introns than previously appreciated, and the modulation of splice variant levels by transcript structure characteristics. The code detected a class of exons whose inclusion silences expression in adult tissues by activating nonsense-mediated messenger RNA decay, but whose exclusion promotes expression during embryogenesis. The code facilitates the discovery and detailed characterization of regulated alternative splicing events on a genome-wide scale.

Suggested Citation

  • Yoseph Barash & John A. Calarco & Weijun Gao & Qun Pan & Xinchen Wang & Ofer Shai & Benjamin J. Blencowe & Brendan J. Frey, 2010. "Deciphering the splicing code," Nature, Nature, vol. 465(7294), pages 53-59, May.
  • Handle: RePEc:nat:nature:v:465:y:2010:i:7294:d:10.1038_nature09000
    DOI: 10.1038/nature09000
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    Citations

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    Cited by:

    1. Ridvan Eksi & Hong-Dong Li & Rajasree Menon & Yuchen Wen & Gilbert S Omenn & Matthias Kretzler & Yuanfang Guan, 2013. "Systematically Differentiating Functions for Alternatively Spliced Isoforms through Integrating RNA-seq Data," PLOS Computational Biology, Public Library of Science, vol. 9(11), pages 1-16, November.
    2. Robert Stojnic & Audrey Qiuyan Fu & Boris Adryan, 2012. "A Graphical Modelling Approach to the Dissection of Highly Correlated Transcription Factor Binding Site Profiles," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-13, November.
    3. Xiangbin Ruan & Kaining Hu & Xiaochang Zhang, 2023. "PIE-seq: identifying RNA-binding protein targets by dual RNA-deaminase editing and sequencing," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    4. Jorge Vaquero-Garcia & Joseph K. Aicher & San Jewell & Matthew R. Gazzara & Caleb M. Radens & Anupama Jha & Scott S. Norton & Nicholas F. Lahens & Gregory R. Grant & Yoseph Barash, 2023. "RNA splicing analysis using heterogeneous and large RNA-seq datasets," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    5. Ilias Georgakopoulos-Soares & Guillermo E. Parada & Hei Yuen Wong & Ragini Medhi & Giulia Furlan & Roberto Munita & Eric A. Miska & Chun Kit Kwok & Martin Hemberg, 2022. "Alternative splicing modulation by G-quadruplexes," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    6. Areum Han & Peter Stoilov & Anthony J Linares & Yu Zhou & Xiang-Dong Fu & Douglas L Black, 2014. "De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-18, January.
    7. Yocelyn Recinos & Dmytro Ustianenko & Yow-Tyng Yeh & Xiaojian Wang & Martin Jacko & Lekha V. Yesantharao & Qiyang Wu & Chaolin Zhang, 2024. "CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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