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Mini-Review Article

Comparative Analysis of Published Database Predicting MicroRNA Binding in 3’UTR of mRNA in Diverse Species

Author(s): Sonu Singh Ahirwar, Rehma Rizwan, Samdish Sethi, Zainab Shahid, Shivani Malviya, Rekha Khandia, Amit Agarwal and Ashwin Kotnis*

Volume 13, Issue 1, 2024

Published on: 27 October, 2023

Page: [2 - 13] Pages: 12

DOI: 10.2174/0122115366261005231018070640

Price: $65

Abstract

Background: Micro-RNAs are endogenous non-coding RNA moieties of 22-27 nucleotides that play a crucial role in the regulation of various biological processes and make them useful prognostic and diagnostic biomarkers. Discovery and experimental validation of miRNA is a laborious and time-consuming process. For early prediction, multiple bioinformatics databases are available for miRNA target prediction; however, their utility can confuse amateur researchers in selecting the most appropriate tools for their study.

Objective: This descriptive review aimed to analyse the usability of the existing database based on the following criteria: accessibility, efficiency, interpretability, updatability, and flexibility for miRNA target prediction of 3’UTR of mRNA in diverse species so that the researchers can utilize the database most appropriate to their research.

Methods: A systematic literature search was performed in PubMed, Google Scholar and Scopus databases up to November 2022. ≥10,000 articles found online, including ⁓130 miRNA tools, which contain various information on miRNA. Out of them, 31 databases that provide information on validated 3’UTR miRNAs target databases were included and analysed in this review.

Results: These miRNA database tools are being used in varied areas of biological research to select the most suitable miRNA for their experimental validation. These databases, updated until the year 2021, consist of miRNA-related data from humans, animals, mice, plants, viruses etc. They contain 525-29806351 data entries, and information from most databases is freely available on the online platform.

Conclusion: Reviewed databases provide significant information, but not all information is accurate or up-to-date. Therefore, Diana-TarBase and miRWalk are the most comprehensive and up-to-date databases.

Keywords: miRNA, RNA, 3’UTR, databases, disease, genes, SNPs, cancer.

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