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Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq

Tissue-specific alternative splicing is a key mechanism for generating tissue-specific proteomic diversity in eukaryotes. Splicing regulatory elements (SREs) in pre-mature messenger RNA play a very important role in regulating alternative splicing. In this article, we use mouse RNA-Seq data to deter...

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Detalles Bibliográficos
Autores principales: Wen, Ji, Chiba, Akira, Cai, Xiaodong
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001057/
https://www.ncbi.nlm.nih.gov/pubmed/20685814
http://dx.doi.org/10.1093/nar/gkq679
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author Wen, Ji
Chiba, Akira
Cai, Xiaodong
author_facet Wen, Ji
Chiba, Akira
Cai, Xiaodong
author_sort Wen, Ji
collection PubMed
description Tissue-specific alternative splicing is a key mechanism for generating tissue-specific proteomic diversity in eukaryotes. Splicing regulatory elements (SREs) in pre-mature messenger RNA play a very important role in regulating alternative splicing. In this article, we use mouse RNA-Seq data to determine a positive data set where SREs are over-represented and a reliable negative data set where the same SREs are most likely under-represented for a specific tissue and then employ a powerful discriminative approach to identify SREs. We identified 456 putative splicing enhancers or silencers, of which 221 were predicted to be tissue-specific. Most of our tissue-specific SREs are likely different from constitutive SREs, since only 18% of our exonic splicing enhancers (ESEs) are contained in constitutive RESCUE-ESEs. A relatively small portion (20%) of our SREs is included in tissue-specific SREs in human identified in two recent studies. In the analysis of position distribution of SREs, we found that a dozen of SREs were biased to a specific region. We also identified two very interesting SREs that can function as an enhancer in one tissue but a silencer in another tissue from the same intronic region. These findings provide insight into the mechanism of tissue-specific alternative splicing and give a set of valuable putative SREs for further experimental investigations.
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spelling pubmed-30010572010-12-13 Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq Wen, Ji Chiba, Akira Cai, Xiaodong Nucleic Acids Res Computational Biology Tissue-specific alternative splicing is a key mechanism for generating tissue-specific proteomic diversity in eukaryotes. Splicing regulatory elements (SREs) in pre-mature messenger RNA play a very important role in regulating alternative splicing. In this article, we use mouse RNA-Seq data to determine a positive data set where SREs are over-represented and a reliable negative data set where the same SREs are most likely under-represented for a specific tissue and then employ a powerful discriminative approach to identify SREs. We identified 456 putative splicing enhancers or silencers, of which 221 were predicted to be tissue-specific. Most of our tissue-specific SREs are likely different from constitutive SREs, since only 18% of our exonic splicing enhancers (ESEs) are contained in constitutive RESCUE-ESEs. A relatively small portion (20%) of our SREs is included in tissue-specific SREs in human identified in two recent studies. In the analysis of position distribution of SREs, we found that a dozen of SREs were biased to a specific region. We also identified two very interesting SREs that can function as an enhancer in one tissue but a silencer in another tissue from the same intronic region. These findings provide insight into the mechanism of tissue-specific alternative splicing and give a set of valuable putative SREs for further experimental investigations. Oxford University Press 2010-12 2010-08-04 /pmc/articles/PMC3001057/ /pubmed/20685814 http://dx.doi.org/10.1093/nar/gkq679 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Wen, Ji
Chiba, Akira
Cai, Xiaodong
Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title_full Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title_fullStr Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title_full_unstemmed Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title_short Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq
title_sort computational identification of tissue-specific alternative splicing elements in mouse genes from rna-seq
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001057/
https://www.ncbi.nlm.nih.gov/pubmed/20685814
http://dx.doi.org/10.1093/nar/gkq679
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AT caixiaodong computationalidentificationoftissuespecificalternativesplicingelementsinmousegenesfromrnaseq