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ISOGO: Functional annotation of protein-coding splice variants
The advent of RNA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was develop...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6978412/ https://www.ncbi.nlm.nih.gov/pubmed/31974522 http://dx.doi.org/10.1038/s41598-020-57974-z |
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author | Ferrer-Bonsoms, Juan A Cassol, Ignacio Fernández-Acín, Pablo Castilla, Carlos Carazo, Fernando Rubio, Angel |
author_facet | Ferrer-Bonsoms, Juan A Cassol, Ignacio Fernández-Acín, Pablo Castilla, Carlos Carazo, Fernando Rubio, Angel |
author_sort | Ferrer-Bonsoms, Juan A |
collection | PubMed |
description | The advent of RNA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was developed to annotate gene products according to their biological processes, molecular functions and cellular components. Despite a single gene may have several gene products, most annotations are not isoform-specific and do not distinguish the functions of the different proteins originated from a single gene. Several approaches have tried to automatically annotate ontologies at the isoform level, but this has shown to be a daunting task. We have developed ISOGO (ISOform + GO function imputation), a novel algorithm to predict the function of coding isoforms based on their protein domains and their correlation of expression along 11,373 cancer patients. Combining these two sources of information outperforms previous approaches: it provides an area under precision-recall curve (AUPRC) five times larger than previous attempts and the median AUROC of assigned functions to genes is 0.82. We tested ISOGO predictions on some genes with isoform-specific functions (BRCA1, MADD,VAMP7 and ITSN1) and they were coherent with the literature. Besides, we examined whether the main isoform of each gene -as predicted by APPRIS- was the most likely to have the annotated gene functions and it occurs in 99.4% of the genes. We also evaluated the predictions for isoform-specific functions provided by the CAFA3 challenge and results were also convincing. To make these results available to the scientific community, we have deployed a web application to consult ISOGO predictions (https://biotecnun.unav.es/app/isogo). Initial data, website link, isoform-specific GO function predictions and R code is available at https://gitlab.com/icassol/isogo. |
format | Online Article Text |
id | pubmed-6978412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69784122020-01-30 ISOGO: Functional annotation of protein-coding splice variants Ferrer-Bonsoms, Juan A Cassol, Ignacio Fernández-Acín, Pablo Castilla, Carlos Carazo, Fernando Rubio, Angel Sci Rep Article The advent of RNA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was developed to annotate gene products according to their biological processes, molecular functions and cellular components. Despite a single gene may have several gene products, most annotations are not isoform-specific and do not distinguish the functions of the different proteins originated from a single gene. Several approaches have tried to automatically annotate ontologies at the isoform level, but this has shown to be a daunting task. We have developed ISOGO (ISOform + GO function imputation), a novel algorithm to predict the function of coding isoforms based on their protein domains and their correlation of expression along 11,373 cancer patients. Combining these two sources of information outperforms previous approaches: it provides an area under precision-recall curve (AUPRC) five times larger than previous attempts and the median AUROC of assigned functions to genes is 0.82. We tested ISOGO predictions on some genes with isoform-specific functions (BRCA1, MADD,VAMP7 and ITSN1) and they were coherent with the literature. Besides, we examined whether the main isoform of each gene -as predicted by APPRIS- was the most likely to have the annotated gene functions and it occurs in 99.4% of the genes. We also evaluated the predictions for isoform-specific functions provided by the CAFA3 challenge and results were also convincing. To make these results available to the scientific community, we have deployed a web application to consult ISOGO predictions (https://biotecnun.unav.es/app/isogo). Initial data, website link, isoform-specific GO function predictions and R code is available at https://gitlab.com/icassol/isogo. Nature Publishing Group UK 2020-01-23 /pmc/articles/PMC6978412/ /pubmed/31974522 http://dx.doi.org/10.1038/s41598-020-57974-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ferrer-Bonsoms, Juan A Cassol, Ignacio Fernández-Acín, Pablo Castilla, Carlos Carazo, Fernando Rubio, Angel ISOGO: Functional annotation of protein-coding splice variants |
title | ISOGO: Functional annotation of protein-coding splice variants |
title_full | ISOGO: Functional annotation of protein-coding splice variants |
title_fullStr | ISOGO: Functional annotation of protein-coding splice variants |
title_full_unstemmed | ISOGO: Functional annotation of protein-coding splice variants |
title_short | ISOGO: Functional annotation of protein-coding splice variants |
title_sort | isogo: functional annotation of protein-coding splice variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6978412/ https://www.ncbi.nlm.nih.gov/pubmed/31974522 http://dx.doi.org/10.1038/s41598-020-57974-z |
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