mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data

Area of Science:

• Bioinformatics
• Computational Biology
• Molecular Biology

Background:

• Identifying microRNA (miRNA) targets is crucial for understanding post-transcriptional gene regulation.
• Over-representation analysis of predicted miRNA targets in transcription factor-regulated gene sets aids in identifying biologically relevant targets.

Purpose of the Study:

• To develop a user-friendly web application, mBISON, for calculating the significance of miRNA target over-representation in gene sets.
• To facilitate the analysis of miRNA-mediated gene regulation, particularly in conjunction with ChIP-sequencing data.

Main Methods:

• mBISON calculates miRNA target enrichment significance in user-defined gene sets.
• Gene sets can be input as gene lists or derived from ChIP-seq datasets using a specified peak-gene association method.
• The application utilizes TargetScan predictions and incorporates randomization for False Discovery Rate calculation, including 3'UTR length correction.

Main Results:

• The mBISON web application is now available for public use.
• It enables the direct analysis of ChIP-seq data for miRNA target identification.
• The tool provides a straightforward method for extracting functional miRNA insights from gene lists.

Conclusions:

• mBISON offers an accessible and efficient web-based tool for miRNA target enrichment analysis.
• It simplifies the interpretation of functional roles of miRNAs in gene regulatory networks.
• The application is particularly useful for researchers working with ChIP-seq data and gene lists.