RT Journal
A1 Tranchevent, Léon-Charles
A1 Aubé, Fabien
A1 Dulaurier, Louis
A1 Benoit-Pilven, Clara
A1 Rey, Amandine
A1 Poret, Arnaud
A1 Chautard, Emilie
A1 Mortada, Hussein
A1 Desmet, François-Olivier
A1 Chakrama, Fatima Zahra
A1 Moreno-Garcia, Maira Alejandra
A1 Goillot, Evelyne
A1 Janczarski, Stéphane
A1 Mortreux, Franck
A1 Bourgeois, Cyril F.
A1 Auboeuf, Didier
T1 Identification of protein features encoded by alternative exons using Exon Ontology
JF Genome Research 
JO Genome Research 
YR 2017 
FD June 01 
VO 27 
IS 6 
SP 1087 
OP 1097 
DO 10.1101/gr.212696.116 
UL http://genome.cshlp.org/content/27/6/1087.abstract 
AB Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named “Exon Ontology,” based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information.