Deciphering the splicing code. Nature, 465, 53-59

Biomedical Engineering, Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto M5S 3G4, Canada.
Nature (Impact Factor: 41.46). 05/2010; 465(7294):53-9. DOI: 10.1038/nature09000
Source: PubMed


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.

Download full-text


Available from: Benjamin J Blencowe
  • Source
    • "In recent years a number of technologies have been developed to characterize different features related to the gene translation and multiple roles of the coding sequence have been proposed. Recent studies suggested that the order of codons along the mRNA plays an important role in determining translation efficiency[4,91011. It was suggested that there is weak folding of mRNA molecule in the region surrounding the start codons910111213141516, and endogenous genes tend to perform strong mRNA folding in the region after the start codon[10,17,18], which can improve the fidelity of translation initiation [10,17,19,20]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Incorrect protein translation, caused by codon mismatch, is an important problem of living cells. In this work, a computational model was introduced to quantify the effects of codon mismatch and the model was used to study the protein translation of Saccharomyces cerevisiae. According to simulation results, the probability of codon mismatch will increase when the supply of amino acids is unbalanced, and the longer is the codon sequence, the larger is the probability for incorrect translation to occur, making the synthesis of long peptide chain difficult. By comparing to simulation results without codon mismatch effects taken into account, the fraction of mRNAs with bound ribosome decrease faster along the mRNAs, making the 5' ramp phenomenon more obvious. It was also found in our work that the premature mechanism resulted from codon mismatch can reduce the proportion of incorrect translation when the amino acid supply is extremely unbalanced, which is one possible source of high fidelity protein synthesis after peptidyl transfer.
    Full-text · Article · Feb 2016 · PLoS ONE
  • Source
    • "Studies have shown that FIRs of alternative exons are enriched with splicing regulatory sequences and are evolutionarily conserved to a greater degree than FIRs of constitutive exons (Sorek & Ast, 2003; Barash et al, 2010), implying that they may contribute to the regulation of the precision of inclusion levels. To examine this role of FIR conservation, we focused on the cassette type of alternative exons and compiled a dataset of all human cassette exons (Table EV1). "

    Preview · Article · Dec 2015 · Molecular Systems Biology
  • Source
    • "However, this question still holds since former studies have limited power. Thus in this study, we analyzed the alternative splicing dataset from Barash, Y. et al. (Barash et al., 2010) with mutual information based feature analysis to further address it. We observed that for different tissues, the preferred features vary to some extent. "

    Full-text · Article · Oct 2015 · Protein & Cell
Show more