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

Genomics Proteomics Bioinformatics. 2022 Jun;20(3):557-567. doi: 10.1016/j.gpb.2021.02.010. Epub 2021 Jul 28.

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/.

Keywords: Galaxy; Interactive annotation; Manual inspection; MicroRNA; Platform.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Genomics
  • Internet
  • MicroRNAs* / genetics
  • MicroRNAs* / metabolism
  • Molecular Sequence Annotation
  • Plants / genetics
  • RNA, Plant / genetics
  • Reproducibility of Results
  • Sequence Analysis, RNA
  • Software

Substances

  • MicroRNAs
  • RNA, Plant