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Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data

Alternative splicing is a vital process for regulating gene expression and promoting proteomic diversity. It plays a key role in tissue-specific expressed genes. This specificity is mainly regulated by splicing factors that bind to specific sequences called splicing regulatory elements (SREs). Here,...

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Autores principales: Badr, Eman, ElHefnawi, Mahmoud, Heath, Lenwood S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5115852/
https://www.ncbi.nlm.nih.gov/pubmed/27861625
http://dx.doi.org/10.1371/journal.pone.0166978
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author Badr, Eman
ElHefnawi, Mahmoud
Heath, Lenwood S.
author_facet Badr, Eman
ElHefnawi, Mahmoud
Heath, Lenwood S.
author_sort Badr, Eman
collection PubMed
description Alternative splicing is a vital process for regulating gene expression and promoting proteomic diversity. It plays a key role in tissue-specific expressed genes. This specificity is mainly regulated by splicing factors that bind to specific sequences called splicing regulatory elements (SREs). Here, we report a genome-wide analysis to study alternative splicing on multiple tissues, including brain, heart, liver, and muscle. We propose a pipeline to identify differential exons across tissues and hence tissue-specific SREs. In our pipeline, we utilize the DEXSeq package along with our previously reported algorithms. Utilizing the publicly available RNA-Seq data set from the Human BodyMap project, we identified 28,100 differentially used exons across the four tissues. We identified tissue-specific exonic splicing enhancers that overlap with various previously published experimental and computational databases. A complicated exonic enhancer regulatory network was revealed, where multiple exonic enhancers were found across multiple tissues while some were found only in specific tissues. Putative combinatorial exonic enhancers and silencers were discovered as well, which may be responsible for exon inclusion or exclusion across tissues. Some of the exonic enhancers are found to be co-occurring with multiple exonic silencers and vice versa, which demonstrates a complicated relationship between tissue-specific exonic enhancers and silencers.
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spelling pubmed-51158522016-12-08 Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data Badr, Eman ElHefnawi, Mahmoud Heath, Lenwood S. PLoS One Research Article Alternative splicing is a vital process for regulating gene expression and promoting proteomic diversity. It plays a key role in tissue-specific expressed genes. This specificity is mainly regulated by splicing factors that bind to specific sequences called splicing regulatory elements (SREs). Here, we report a genome-wide analysis to study alternative splicing on multiple tissues, including brain, heart, liver, and muscle. We propose a pipeline to identify differential exons across tissues and hence tissue-specific SREs. In our pipeline, we utilize the DEXSeq package along with our previously reported algorithms. Utilizing the publicly available RNA-Seq data set from the Human BodyMap project, we identified 28,100 differentially used exons across the four tissues. We identified tissue-specific exonic splicing enhancers that overlap with various previously published experimental and computational databases. A complicated exonic enhancer regulatory network was revealed, where multiple exonic enhancers were found across multiple tissues while some were found only in specific tissues. Putative combinatorial exonic enhancers and silencers were discovered as well, which may be responsible for exon inclusion or exclusion across tissues. Some of the exonic enhancers are found to be co-occurring with multiple exonic silencers and vice versa, which demonstrates a complicated relationship between tissue-specific exonic enhancers and silencers. Public Library of Science 2016-11-18 /pmc/articles/PMC5115852/ /pubmed/27861625 http://dx.doi.org/10.1371/journal.pone.0166978 Text en © 2016 Badr et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Badr, Eman
ElHefnawi, Mahmoud
Heath, Lenwood S.
Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title_full Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title_fullStr Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title_full_unstemmed Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title_short Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data
title_sort computational identification of tissue-specific splicing regulatory elements in human genes from rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5115852/
https://www.ncbi.nlm.nih.gov/pubmed/27861625
http://dx.doi.org/10.1371/journal.pone.0166978
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