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Splicing predictions reliably classify different types of alternative splicing
Alternative splicing is a key player in the creation of complex mammalian transcriptomes and its misregulation is associated with many human diseases. Multiple mRNA isoforms are generated from most human genes, a process mediated by the interplay of various RNA signature elements and trans-acting fa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408789/ https://www.ncbi.nlm.nih.gov/pubmed/25805853 http://dx.doi.org/10.1261/rna.048769.114 |
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author | Busch, Anke Hertel, Klemens J. |
author_facet | Busch, Anke Hertel, Klemens J. |
author_sort | Busch, Anke |
collection | PubMed |
description | Alternative splicing is a key player in the creation of complex mammalian transcriptomes and its misregulation is associated with many human diseases. Multiple mRNA isoforms are generated from most human genes, a process mediated by the interplay of various RNA signature elements and trans-acting factors that guide spliceosomal assembly and intron removal. Here, we introduce a splicing predictor that evaluates hundreds of RNA features simultaneously to successfully differentiate between exons that are constitutively spliced, exons that undergo alternative 5′ or 3′ splice-site selection, and alternative cassette-type exons. Surprisingly, the splicing predictor did not feature strong discriminatory contributions from binding sites for known splicing regulators. Rather, the ability of an exon to be involved in one or multiple types of alternative splicing is dictated by its immediate sequence context, mainly driven by the identity of the exon's splice sites, the conservation around them, and its exon/intron architecture. Thus, the splicing behavior of human exons can be reliably predicted based on basic RNA sequence elements. |
format | Online Article Text |
id | pubmed-4408789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44087892016-05-01 Splicing predictions reliably classify different types of alternative splicing Busch, Anke Hertel, Klemens J. RNA Bioinformatics Alternative splicing is a key player in the creation of complex mammalian transcriptomes and its misregulation is associated with many human diseases. Multiple mRNA isoforms are generated from most human genes, a process mediated by the interplay of various RNA signature elements and trans-acting factors that guide spliceosomal assembly and intron removal. Here, we introduce a splicing predictor that evaluates hundreds of RNA features simultaneously to successfully differentiate between exons that are constitutively spliced, exons that undergo alternative 5′ or 3′ splice-site selection, and alternative cassette-type exons. Surprisingly, the splicing predictor did not feature strong discriminatory contributions from binding sites for known splicing regulators. Rather, the ability of an exon to be involved in one or multiple types of alternative splicing is dictated by its immediate sequence context, mainly driven by the identity of the exon's splice sites, the conservation around them, and its exon/intron architecture. Thus, the splicing behavior of human exons can be reliably predicted based on basic RNA sequence elements. Cold Spring Harbor Laboratory Press 2015-05 /pmc/articles/PMC4408789/ /pubmed/25805853 http://dx.doi.org/10.1261/rna.048769.114 Text en © 2015 Busch and Hertel; Published by Cold Spring Harbor Laboratory Press for the RNA Society http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Bioinformatics Busch, Anke Hertel, Klemens J. Splicing predictions reliably classify different types of alternative splicing |
title | Splicing predictions reliably classify different types of alternative splicing |
title_full | Splicing predictions reliably classify different types of alternative splicing |
title_fullStr | Splicing predictions reliably classify different types of alternative splicing |
title_full_unstemmed | Splicing predictions reliably classify different types of alternative splicing |
title_short | Splicing predictions reliably classify different types of alternative splicing |
title_sort | splicing predictions reliably classify different types of alternative splicing |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408789/ https://www.ncbi.nlm.nih.gov/pubmed/25805853 http://dx.doi.org/10.1261/rna.048769.114 |
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