MiRonTop: mining microRNAs targets across large scale gene expression studies

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Identifying in vivo microRNA (miRNA) mRNA targets and understanding their complex interactions within biological networks remain significant challenges in current miRNA research.
• Existing computational tools often lack the integration of diverse data types or comprehensive analysis of miRNA target site characteristics.

Purpose of the Study:

• To introduce MiRonTop, an online Java web tool designed to facilitate the identification of potential miRNA implications in biological systems.
• To enable rapid characterization of pertinent mRNA targets by integrating DNA microarray or high-throughput sequencing data with multiple prediction approaches.

Main Methods:

• MiRonTop integrates DNA microarray and high-throughput sequencing data.
• It employs several existing miRNA target prediction approaches for rapid mRNA target characterization.
• The tool provides representations of enrichment scores based on target site position within the 3'-untranslated region (3"-UTR).

Main Results:

• MiRonTop highlights the contribution of target sites near the stop codon and polyA tail.
• It generates graphs illustrating miRNA enrichment associated with both up- and down-regulated transcripts.
• The tool offers summary tables for selected mRNA targets, including functional annotations via Gene Ontology.

Conclusions:

• MiRonTop addresses key challenges in miRNA research by improving mRNA target identification and clarifying miRNA-biological network interactions.
• The tool provides valuable visualizations and data summaries, aiding researchers in understanding miRNA functions and regulatory roles.
• Its integration of diverse data and analysis of target site positions offers a comprehensive approach to studying miRNA effects in biological systems.