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Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

Authors :
Ting Zhang
Jingjing Zhai
Xiaorong Zhang
Lei Ling
Menghan Li
Shang Xie
Minggui Song
Chuang Ma
Source :
Genomics, Proteomics & Bioinformatics, Vol 20, Iss 3, Pp 557-567 (2022)
Publication Year :
2022
Publisher :
Oxford University Press, 2022.

Abstract

MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs have been accelerated with the development of high-throughput small RNA sequencing (sRNA-Seq) techniques and bioinformatics tools. However, generating high-quality comprehensive miRNA annotations remains challenging due to the intrinsic complexity of sRNA-Seq data and inherent limitations of existing miRNA prediction tools. Here, we present iwa-miRNA, a Galaxy-based framework that can facilitate miRNA annotation in plant species by combining computational analysis and manual curation. iwa-miRNA is specifically designed to generate a comprehensive list of miRNA candidates, bridging the gap between already annotated miRNAs provided by public miRNA databases and new predictions from sRNA-Seq datasets. It can also assist users in selecting promising miRNA candidates in an interactive mode, contributing to the accessibility and reproducibility of genome-wide miRNA annotation. iwa-miRNA is user-friendly and can be easily deployed as a web application for researchers without programming experience. With flexible, interactive, and easy-to-use features, iwa-miRNA is a valuable tool for the annotation of miRNAs in plant species with reference genomes. We also illustrate the application of iwa-miRNA for miRNA annotation using data from plant species with varying genomic complexity. The source codes and web server of iwa-miRNA are freely accessible at http://iwa-miRNA.omicstudio.cloud/.

Details

Language :
English
ISSN :
16720229
Volume :
20
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Genomics, Proteomics & Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.f8324a9817a4d60a2188ce719c040d1
Document Type :
article
Full Text :
https://doi.org/10.1016/j.gpb.2021.02.010