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Entropy-Based Model for MiRNA Isoform Analysis
MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs) in high-throughput small RNA sequencing data. However, the biological function involved in these molecules...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4364746/ https://www.ncbi.nlm.nih.gov/pubmed/25785816 http://dx.doi.org/10.1371/journal.pone.0118856 |
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author | Wang, Shengqin Tu, Jing Wang, Lei Lu, Zuhong |
author_facet | Wang, Shengqin Tu, Jing Wang, Lei Lu, Zuhong |
author_sort | Wang, Shengqin |
collection | PubMed |
description | MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs) in high-throughput small RNA sequencing data. However, the biological function involved in these molecules is still not well investigated. Here, we developed a Shannon entropy-based model to estimate isomiR expression profiles of high-throughput small RNA sequencing data extracted from miRBase webserver. By using the Kolmogorov-Smirnov statistical test (KS test), we demonstrated that the 5p and 3p miRNAs present more variants than the single arm miRNAs. We also found that the isomiR variant, except the 3’ isomiR variant, is strongly correlated with Minimum Free Energy (MFE) of pre-miRNA, suggesting the intrinsic feature of pre-miRNA should be one of the important factors for the miRNA regulation. The functional enrichment analysis showed that the miRNAs with high variation, particularly the 5’ end variation, are enriched in a set of critical functions, supporting these molecules should not be randomly produced. Our results provide a probabilistic framework for miRNA isoforms analysis, and give functional insights into pre-miRNA processing. |
format | Online Article Text |
id | pubmed-4364746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43647462015-03-23 Entropy-Based Model for MiRNA Isoform Analysis Wang, Shengqin Tu, Jing Wang, Lei Lu, Zuhong PLoS One Research Article MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs) in high-throughput small RNA sequencing data. However, the biological function involved in these molecules is still not well investigated. Here, we developed a Shannon entropy-based model to estimate isomiR expression profiles of high-throughput small RNA sequencing data extracted from miRBase webserver. By using the Kolmogorov-Smirnov statistical test (KS test), we demonstrated that the 5p and 3p miRNAs present more variants than the single arm miRNAs. We also found that the isomiR variant, except the 3’ isomiR variant, is strongly correlated with Minimum Free Energy (MFE) of pre-miRNA, suggesting the intrinsic feature of pre-miRNA should be one of the important factors for the miRNA regulation. The functional enrichment analysis showed that the miRNAs with high variation, particularly the 5’ end variation, are enriched in a set of critical functions, supporting these molecules should not be randomly produced. Our results provide a probabilistic framework for miRNA isoforms analysis, and give functional insights into pre-miRNA processing. Public Library of Science 2015-03-18 /pmc/articles/PMC4364746/ /pubmed/25785816 http://dx.doi.org/10.1371/journal.pone.0118856 Text en © 2015 Wang 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 Wang, Shengqin Tu, Jing Wang, Lei Lu, Zuhong Entropy-Based Model for MiRNA Isoform Analysis |
title | Entropy-Based Model for MiRNA Isoform Analysis |
title_full | Entropy-Based Model for MiRNA Isoform Analysis |
title_fullStr | Entropy-Based Model for MiRNA Isoform Analysis |
title_full_unstemmed | Entropy-Based Model for MiRNA Isoform Analysis |
title_short | Entropy-Based Model for MiRNA Isoform Analysis |
title_sort | entropy-based model for mirna isoform analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4364746/ https://www.ncbi.nlm.nih.gov/pubmed/25785816 http://dx.doi.org/10.1371/journal.pone.0118856 |
work_keys_str_mv | AT wangshengqin entropybasedmodelformirnaisoformanalysis AT tujing entropybasedmodelformirnaisoformanalysis AT wanglei entropybasedmodelformirnaisoformanalysis AT luzuhong entropybasedmodelformirnaisoformanalysis |