Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhong, Xiangfu, Heinicke, Fatima, Rayner, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2019
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
Descripción
Sumario: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.