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Computational annotation of miRNA transcription start sites
MOTIVATION: MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike prot...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820843/ https://www.ncbi.nlm.nih.gov/pubmed/32003428 http://dx.doi.org/10.1093/bib/bbz178 |
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author | Wang, Saidi Talukder, Amlan Cha, Mingyu Li, Xiaoman Hu, Haiyan |
author_facet | Wang, Saidi Talukder, Amlan Cha, Mingyu Li, Xiaoman Hu, Haiyan |
author_sort | Wang, Saidi |
collection | PubMed |
description | MOTIVATION: MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. RESULTS: In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. CONTACT: xiaoman@mail.ucf.edu, haihu@cs.ucf.edu |
format | Online Article Text |
id | pubmed-7820843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-78208432021-01-27 Computational annotation of miRNA transcription start sites Wang, Saidi Talukder, Amlan Cha, Mingyu Li, Xiaoman Hu, Haiyan Brief Bioinform Articles MOTIVATION: MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. RESULTS: In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. CONTACT: xiaoman@mail.ucf.edu, haihu@cs.ucf.edu Oxford University Press 2020-01-31 /pmc/articles/PMC7820843/ /pubmed/32003428 http://dx.doi.org/10.1093/bib/bbz178 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Articles Wang, Saidi Talukder, Amlan Cha, Mingyu Li, Xiaoman Hu, Haiyan Computational annotation of miRNA transcription start sites |
title | Computational annotation of miRNA transcription start sites |
title_full | Computational annotation of miRNA transcription start sites |
title_fullStr | Computational annotation of miRNA transcription start sites |
title_full_unstemmed | Computational annotation of miRNA transcription start sites |
title_short | Computational annotation of miRNA transcription start sites |
title_sort | computational annotation of mirna transcription start sites |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820843/ https://www.ncbi.nlm.nih.gov/pubmed/32003428 http://dx.doi.org/10.1093/bib/bbz178 |
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