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dc.contributor.author | Pozo, Fernando | |
dc.contributor.author | Rodriguez, Jose Manuel | |
dc.contributor.author | Martínez Gómez, Laura | |
dc.contributor.author | Vazquez, Jesus | |
dc.contributor.author | Tress, Michael L | |
dc.date.accessioned | 2023-04-12T10:49:25Z | |
dc.date.available | 2023-04-12T10:49:25Z | |
dc.date.issued | 2022-09-16 | |
dc.identifier.citation | Bioinformatics. 2022 Sep 16;38(Suppl_2):ii89-ii94. | es_ES |
dc.identifier.uri | http://hdl.handle.net/20.500.12105/15785 | |
dc.description.abstract | Selecting the splice variant that best represents a coding gene is a crucial first step in many experimental analyses, and vital for mapping clinically relevant variants. This study compares the longest isoforms, MANE Select transcripts, APPRIS principal isoforms, and expression data, and aims to determine which method is best for selecting biological important reference splice variants for large-scale analyses. Proteomics analyses and human genetic variation data suggest that most coding genes have a single main protein isoform. We show that APPRIS principal isoforms and MANE Select transcripts best describe these main cellular isoforms, and find that using the longest splice variant as the representative is a poor strategy. Exons unique to the longest splice isoforms are not under selective pressure, and so are unlikely to be functionally relevant. Expression data are also a poor means of selecting the main splice variant. APPRIS principal and MANE Select exons are under purifying selection, while exons specific to alternative transcripts are not. There are MANE and APPRIS representatives for almost 95% of genes, and where they agree they are particularly effective, coinciding with the main proteomics isoform for over 98.2% of genes. APPRIS principal isoforms for human, mouse and other model species can be downloaded from the APPRIS database (https://appris.bioinfo.cnio.es), GENCODE genes (https://www.gencodegenes.org/) and the Ensembl website (https://www.ensembl.org). MANE Select transcripts for the human reference set are available from the Ensembl, GENCODE and RefSeq databases (https://www.ncbi.nlm.nih.gov/refseq/). Lists of splice variants where MANE and APPRIS coincide are available from the APPRIS database. Supplementary data are available at Bioinformatics online. | es_ES |
dc.description.sponsorship | This paper was published as part of a special issue financially supported by ECCB2022. This work was supported by the National Human Genome Research Institute of the National Institutes of Health under Award Number U24HG007234. This work was also supported by the following grants: PGC2018-097019-B-I00/Ministry of Science, Innovation and Universities; IPT17/0019/Carlos III Institute of Health-Fondo de Investigacio´n Sanitaria and HR17-00247/‘la Caixa’ Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Oxford University Press | es_ES |
dc.type.hasVersion | VoR | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject.mesh | Proteomics | es_ES |
dc.subject.mesh | Animals | es_ES |
dc.subject.mesh | Exons | es_ES |
dc.subject.mesh | Humans | es_ES |
dc.subject.mesh | Mice | es_ES |
dc.subject.mesh | Mutation | es_ES |
dc.subject.mesh | Protein Isoforms | es_ES |
dc.title | APPRIS principal isoforms and MANE Select transcripts define reference splice variants. | es_ES |
dc.type | journal article | es_ES |
dc.rights.license | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.identifier.pubmedID | 36124785 | es_ES |
dc.format.volume | 38 | es_ES |
dc.format.number | Suppl_2 | es_ES |
dc.format.page | ii89 | es_ES |
dc.identifier.doi | 10.1093/bioinformatics/btac473 | es_ES |
dc.contributor.funder | NIH - National Human Genome Research Institute (NHGRI) (Estados Unidos) | es_ES |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades (España) | es_ES |
dc.contributor.funder | Instituto de Salud Carlos III | es_ES |
dc.contributor.funder | Fundación La Caixa | es_ES |
dc.description.peerreviewed | Sí | es_ES |
dc.identifier.e-issn | 1367-4811 | es_ES |
dc.relation.publisherversion | 10.1093/bioinformatics/btac473 | es_ES |
dc.identifier.journal | Bioinformatics (Oxford, England) | es_ES |
dc.repisalud.orgCNIC | CNIC::Grupos de investigación::Proteómica cardiovascular | es_ES |
dc.repisalud.institucion | CNIC | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.relation.projectFECYT | info:eu-repo/grantAgreement/ES/PGC2018-097019-B-I00 | es_ES |
dc.relation.projectFECYT | info:eu-repo/grantAgreement/ES/IPT17/0019 | es_ES |
dc.relation.projectFECYT | info:eu-repo/grantAgreement/ES/HR17-00247 | es_ES |