Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing
Ghadie, Mohamed Ali
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CitationGhadie, Mohamed Ali, Luke Lambourne, Marc Vidal, and Yu Xia. 2017. “Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing.” PLoS Computational Biology 13 (8): e1005717. doi:10.1371/journal.pcbi.1005717. http://dx.doi.org/10.1371/journal.pcbi.1005717.
AbstractAlternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:34492024
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