miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered...

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Transcriptome profiling yields numerous gene co-expression signatures.
• MicroRNA (miRNA)-mediated targeted transcript degradation explains a fraction of these signatures.
• Identifying regulatory miRNAs is crucial for understanding gene expression.

Purpose of the Study:

• To develop a computational tool, miRvestigator, for identifying miRNAs involved in gene co-regulation.
• To systematically compute similarity P-values for miRNA seed sequences against motifs in 3 UTRs.
• To provide a user-friendly interface for miRNA discovery and facilitate experimental validation.

Main Methods:

• Utilized a novel hidden Markov model (HMM) algorithm within miRvestigator.
• Computed similarity P-values for miRNA seed sequences from miRBase.
• Integrated HMM with a de novo miRNA seed sequence discovery algorithm.
• Developed a web server with a user-friendly interface.

Main Results:

• miRvestigator identifies specific miRNAs likely to bind to 3 UTRs and mediate co-regulation.
• The tool systematically computes P-values for miRNA seed sequence similarity.
• Identified putative miRNA binding sites within 3 UTRs of query transcripts.

Conclusions:

• miRvestigator is a valuable tool for discovering miRNAs involved in gene co-expression.
• The integrated HMM algorithm provides a robust method for miRNA seed sequence analysis.
• The web server facilitates research by providing predicted miRNA binding sites for experimental validation.