IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v465y2010i7294d10.1038_nature09000.html
   My bibliography  Save this article

Deciphering the splicing code

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature09000
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/nature09000?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:465:y:2010:i:7294:d:10.1038_nature09000. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.