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Identification of protein features encoded by alternative exons using Exon Ontology
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 phe...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453322/ https://www.ncbi.nlm.nih.gov/pubmed/28420690 http://dx.doi.org/10.1101/gr.212696.116 |
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author | Tranchevent, Léon-Charles Aubé, Fabien Dulaurier, Louis Benoit-Pilven, Clara Rey, Amandine Poret, Arnaud Chautard, Emilie Mortada, Hussein Desmet, François-Olivier Chakrama, Fatima Zahra Moreno-Garcia, Maira Alejandra Goillot, Evelyne Janczarski, Stéphane Mortreux, Franck Bourgeois, Cyril F. Auboeuf, Didier |
author_facet | Tranchevent, Léon-Charles Aubé, Fabien Dulaurier, Louis Benoit-Pilven, Clara Rey, Amandine Poret, Arnaud Chautard, Emilie Mortada, Hussein Desmet, François-Olivier Chakrama, Fatima Zahra Moreno-Garcia, Maira Alejandra Goillot, Evelyne Janczarski, Stéphane Mortreux, Franck Bourgeois, Cyril F. Auboeuf, Didier |
author_sort | Tranchevent, Léon-Charles |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5453322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54533222017-06-15 Identification of protein features encoded by alternative exons using Exon Ontology Tranchevent, Léon-Charles Aubé, Fabien Dulaurier, Louis Benoit-Pilven, Clara Rey, Amandine Poret, Arnaud Chautard, Emilie Mortada, Hussein Desmet, François-Olivier Chakrama, Fatima Zahra Moreno-Garcia, Maira Alejandra Goillot, Evelyne Janczarski, Stéphane Mortreux, Franck Bourgeois, Cyril F. Auboeuf, Didier Genome Res Resource 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. Cold Spring Harbor Laboratory Press 2017-06 /pmc/articles/PMC5453322/ /pubmed/28420690 http://dx.doi.org/10.1101/gr.212696.116 Text en © 2017 Tranchevent et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Resource Tranchevent, Léon-Charles Aubé, Fabien Dulaurier, Louis Benoit-Pilven, Clara Rey, Amandine Poret, Arnaud Chautard, Emilie Mortada, Hussein Desmet, François-Olivier Chakrama, Fatima Zahra Moreno-Garcia, Maira Alejandra Goillot, Evelyne Janczarski, Stéphane Mortreux, Franck Bourgeois, Cyril F. Auboeuf, Didier Identification of protein features encoded by alternative exons using Exon Ontology |
title | Identification of protein features encoded by alternative exons using Exon Ontology |
title_full | Identification of protein features encoded by alternative exons using Exon Ontology |
title_fullStr | Identification of protein features encoded by alternative exons using Exon Ontology |
title_full_unstemmed | Identification of protein features encoded by alternative exons using Exon Ontology |
title_short | Identification of protein features encoded by alternative exons using Exon Ontology |
title_sort | identification of protein features encoded by alternative exons using exon ontology |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453322/ https://www.ncbi.nlm.nih.gov/pubmed/28420690 http://dx.doi.org/10.1101/gr.212696.116 |
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