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A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions

Alternative splicing (AS) of precursor mRNA (pre-mRNA) is a crucial step in the expression of most eukaryotic genes. Splicing factors (SFs) play an important role in AS regulation by binding to the cis-regulatory elements on the pre-mRNA. Although many splicing factors (SFs) and their binding sites...

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Autores principales: Wen, Ji, Chen, Zhibin, Cai, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3559881/
https://www.ncbi.nlm.nih.gov/pubmed/23382993
http://dx.doi.org/10.1371/journal.pone.0054885
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author Wen, Ji
Chen, Zhibin
Cai, Xiaodong
author_facet Wen, Ji
Chen, Zhibin
Cai, Xiaodong
author_sort Wen, Ji
collection PubMed
description Alternative splicing (AS) of precursor mRNA (pre-mRNA) is a crucial step in the expression of most eukaryotic genes. Splicing factors (SFs) play an important role in AS regulation by binding to the cis-regulatory elements on the pre-mRNA. Although many splicing factors (SFs) and their binding sites have been identified, their combinatorial regulatory effects remain to be elucidated. In this paper, we derive a biophysical model for AS regulation that integrates combinatorial signals of cis-acting splicing regulatory elements (SREs) and their interactions. We also develop a systematic framework for model inference. Applying the biophysical model to a human RNA-Seq data set, we demonstrate that our model can explain 49.1%–66.5% variance of the data, which is comparable to the best result achieved by biophysical models for transcription. In total, we identified 119 SRE pairs between different regions of cassette exons that may regulate exon or intron definition in splicing, and 77 SRE pairs from the same region that may arise from a long motif or two different SREs bound by different SFs. Particularly, putative binding sites of polypyrimidine tract-binding protein (PTB), heterogeneous nuclear ribonucleoprotein (hnRNP) F/H and E/K are identified as interacting SRE pairs, and have been shown to be consistent with the interaction models proposed in previous experimental results. These results show that our biophysical model and inference method provide a means of quantitative modeling of splicing regulation and is a useful tool for identifying SREs and their interactions. The software package for model inference is available under an open source license.
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spelling pubmed-35598812013-02-04 A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions Wen, Ji Chen, Zhibin Cai, Xiaodong PLoS One Research Article Alternative splicing (AS) of precursor mRNA (pre-mRNA) is a crucial step in the expression of most eukaryotic genes. Splicing factors (SFs) play an important role in AS regulation by binding to the cis-regulatory elements on the pre-mRNA. Although many splicing factors (SFs) and their binding sites have been identified, their combinatorial regulatory effects remain to be elucidated. In this paper, we derive a biophysical model for AS regulation that integrates combinatorial signals of cis-acting splicing regulatory elements (SREs) and their interactions. We also develop a systematic framework for model inference. Applying the biophysical model to a human RNA-Seq data set, we demonstrate that our model can explain 49.1%–66.5% variance of the data, which is comparable to the best result achieved by biophysical models for transcription. In total, we identified 119 SRE pairs between different regions of cassette exons that may regulate exon or intron definition in splicing, and 77 SRE pairs from the same region that may arise from a long motif or two different SREs bound by different SFs. Particularly, putative binding sites of polypyrimidine tract-binding protein (PTB), heterogeneous nuclear ribonucleoprotein (hnRNP) F/H and E/K are identified as interacting SRE pairs, and have been shown to be consistent with the interaction models proposed in previous experimental results. These results show that our biophysical model and inference method provide a means of quantitative modeling of splicing regulation and is a useful tool for identifying SREs and their interactions. The software package for model inference is available under an open source license. Public Library of Science 2013-01-30 /pmc/articles/PMC3559881/ /pubmed/23382993 http://dx.doi.org/10.1371/journal.pone.0054885 Text en © 2013 Wen 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wen, Ji
Chen, Zhibin
Cai, Xiaodong
A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title_full A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title_fullStr A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title_full_unstemmed A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title_short A Biophysical Model for Identifying Splicing Regulatory Elements and Their Interactions
title_sort biophysical model for identifying splicing regulatory elements and their interactions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3559881/
https://www.ncbi.nlm.nih.gov/pubmed/23382993
http://dx.doi.org/10.1371/journal.pone.0054885
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