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Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors

Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting...

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Autores principales: Ye, Zhenqing, Chen, Zhong, Lan, Xun, Hara, Stephen, Sunkel, Benjamin, Huang, Tim H.-M., Elnitski, Laura, Wang, Qianben, Jin, Victor X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950716/
https://www.ncbi.nlm.nih.gov/pubmed/24369421
http://dx.doi.org/10.1093/nar/gkt1338
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author Ye, Zhenqing
Chen, Zhong
Lan, Xun
Hara, Stephen
Sunkel, Benjamin
Huang, Tim H.-M.
Elnitski, Laura
Wang, Qianben
Jin, Victor X.
author_facet Ye, Zhenqing
Chen, Zhong
Lan, Xun
Hara, Stephen
Sunkel, Benjamin
Huang, Tim H.-M.
Elnitski, Laura
Wang, Qianben
Jin, Victor X.
author_sort Ye, Zhenqing
collection PubMed
description Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting mature mRNA. Both transcript isoforms from this skipping event site, i.e. in which the exon is either included (inclusion isoform) or excluded (skipping isoform), are typically present in one cell, and maintain a subtle balance that is vital to cellular function and dynamics. However, how the prevailing conditions dictate which isoform is expressed and what biological factors might influence the regulation of this process remain areas requiring further exploration. In this study, we have developed a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium and experimentally validated several skipping site predictions by RT-PCR. Furthermore, we integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. Our computational analysis found that splice sites within the skipping-isoform-dominated group (SIDG) tended to exhibit weaker MaxEntScan-calculated splice site strength around middle, ‘skipping’, exons compared to those in the inclusion-isoform-dominated group (IIDG). We further showed the positional preference pattern of splicing factors, characterized by enrichment in the intronic splice sites immediately bordering middle exons. Finally, our analysis suggested that different epigenetic factors may introduce a variable obstacle in the process of exon–intron boundary establishment leading to skipping events.
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spelling pubmed-39507162014-03-12 Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors Ye, Zhenqing Chen, Zhong Lan, Xun Hara, Stephen Sunkel, Benjamin Huang, Tim H.-M. Elnitski, Laura Wang, Qianben Jin, Victor X. Nucleic Acids Res Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting mature mRNA. Both transcript isoforms from this skipping event site, i.e. in which the exon is either included (inclusion isoform) or excluded (skipping isoform), are typically present in one cell, and maintain a subtle balance that is vital to cellular function and dynamics. However, how the prevailing conditions dictate which isoform is expressed and what biological factors might influence the regulation of this process remain areas requiring further exploration. In this study, we have developed a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium and experimentally validated several skipping site predictions by RT-PCR. Furthermore, we integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. Our computational analysis found that splice sites within the skipping-isoform-dominated group (SIDG) tended to exhibit weaker MaxEntScan-calculated splice site strength around middle, ‘skipping’, exons compared to those in the inclusion-isoform-dominated group (IIDG). We further showed the positional preference pattern of splicing factors, characterized by enrichment in the intronic splice sites immediately bordering middle exons. Finally, our analysis suggested that different epigenetic factors may introduce a variable obstacle in the process of exon–intron boundary establishment leading to skipping events. Oxford University Press 2014-03 2013-12-24 /pmc/articles/PMC3950716/ /pubmed/24369421 http://dx.doi.org/10.1093/nar/gkt1338 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Ye, Zhenqing
Chen, Zhong
Lan, Xun
Hara, Stephen
Sunkel, Benjamin
Huang, Tim H.-M.
Elnitski, Laura
Wang, Qianben
Jin, Victor X.
Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title_full Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title_fullStr Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title_full_unstemmed Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title_short Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
title_sort computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950716/
https://www.ncbi.nlm.nih.gov/pubmed/24369421
http://dx.doi.org/10.1093/nar/gkt1338
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