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miRBaseMiner, a tool for investigating miRBase content
microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for expe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779376/ https://www.ncbi.nlm.nih.gov/pubmed/31251108 http://dx.doi.org/10.1080/15476286.2019.1637680 |
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author | Zhong, Xiangfu Heinicke, Fatima Rayner, Simon |
author_facet | Zhong, Xiangfu Heinicke, Fatima Rayner, Simon |
author_sort | Zhong, Xiangfu |
collection | PubMed |
description | microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for experienced users, the size of the resource can make it difficult to explore annotation to determine features such as species coverage, the impact of specific characteristics and changes between successive releases. A further consideration is that each new miRBase release contains entries that have had limited review and which may subsequently be removed in a future release to ensure the quality of annotation. To aid the miRBase user, we developed a software tool, miRBaseMiner, for investigating miRBase annotation and generating custom annotation sets. We apply the tool to characterize each release from v9.2 to v22 to examine how annotation has changed across releases and highlight some of the annotation features that users should keep in mind when using for miRBase for data analysis. These include: (1) entries with identical or very similar sequences; (2) entries with multiple annotated genome locations; (3) hairpin precursor entries with extremely low-estimated minimum free energy; (4) entries possessing reverse complementary; (5) entries with 3ʹ poly(A) ends. As each of these factors can impact the identification of dysregulated features and subsequent clinical or biological conclusions, miRBaseMiner is a valuable resource for any user using miRBase as a reference source. |
format | Online Article Text |
id | pubmed-6779376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-67793762019-10-16 miRBaseMiner, a tool for investigating miRBase content Zhong, Xiangfu Heinicke, Fatima Rayner, Simon RNA Biol Research Paper microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for experienced users, the size of the resource can make it difficult to explore annotation to determine features such as species coverage, the impact of specific characteristics and changes between successive releases. A further consideration is that each new miRBase release contains entries that have had limited review and which may subsequently be removed in a future release to ensure the quality of annotation. To aid the miRBase user, we developed a software tool, miRBaseMiner, for investigating miRBase annotation and generating custom annotation sets. We apply the tool to characterize each release from v9.2 to v22 to examine how annotation has changed across releases and highlight some of the annotation features that users should keep in mind when using for miRBase for data analysis. These include: (1) entries with identical or very similar sequences; (2) entries with multiple annotated genome locations; (3) hairpin precursor entries with extremely low-estimated minimum free energy; (4) entries possessing reverse complementary; (5) entries with 3ʹ poly(A) ends. As each of these factors can impact the identification of dysregulated features and subsequent clinical or biological conclusions, miRBaseMiner is a valuable resource for any user using miRBase as a reference source. Taylor & Francis 2019-08-12 /pmc/articles/PMC6779376/ /pubmed/31251108 http://dx.doi.org/10.1080/15476286.2019.1637680 Text en © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
spellingShingle | Research Paper Zhong, Xiangfu Heinicke, Fatima Rayner, Simon miRBaseMiner, a tool for investigating miRBase content |
title | miRBaseMiner, a tool for investigating miRBase content |
title_full | miRBaseMiner, a tool for investigating miRBase content |
title_fullStr | miRBaseMiner, a tool for investigating miRBase content |
title_full_unstemmed | miRBaseMiner, a tool for investigating miRBase content |
title_short | miRBaseMiner, a tool for investigating miRBase content |
title_sort | mirbaseminer, a tool for investigating mirbase content |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779376/ https://www.ncbi.nlm.nih.gov/pubmed/31251108 http://dx.doi.org/10.1080/15476286.2019.1637680 |
work_keys_str_mv | AT zhongxiangfu mirbasemineratoolforinvestigatingmirbasecontent AT heinickefatima mirbasemineratoolforinvestigatingmirbasecontent AT raynersimon mirbasemineratoolforinvestigatingmirbasecontent |