The coding capacity of the vertebrate genome is greatly expanded by alternative splicing, which enables a single gene to produce more than one distinct protein. Alternative splicing shapes how genetic information controls cellular processes, and many human disease mutations affect splicing. The ability to predict expression of different alternatively spliced messenger RNAs from genomic sequence data is a long-sought goal in the field of gene expression. The Frey and Blencowe labs at the University of Toronto have combined forces to develop a 'splicing code' that accurately predicts how hundreds of RNA features work together to regulate tissue-dependent alternative splicing for thousands of exons. It has been used to predict how alternative splicing may play important roles in development and neurological processes, and has provided insights into mechanisms of splicing regulation. The code has also been incorporated into a web tool that allows researchers to scan uncharacterized exon and intron sequences to predict tissue-dependent splicing patterns.
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