Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA
- Author:
Zhang TING
1
,
2
;
Zhai JINGJING
;
Zhang XIAORONG
;
Ling LEI
;
Li MENGHAN
;
Xie SHANG
;
Song MINGGUI
;
Ma CHUANG
Author Information
1. State Key Laboratory of Crop Stress Biology for Arid Areas,Center of Bioinformatics,College of Life Sciences,Northwest A&F University,Yangling 712100,China
2. Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region,Ministry of Agriculture and Rural Affairs,Northwest A&F University,Yangling 712100,China
- Keywords:
Galaxy;
Interactive annotation;
Manual inspection;
MicroRNA;
Platform
- From:
Genomics, Proteomics & Bioinformatics
2022;20(3):557-567
- CountryChina
- Language:Chinese
-
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 valu-able 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.
