TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Eukaryotic gene expression relies on cis-regulatory elements (CREs) like promoters and enhancers, which bind transcription factors (TFs).
• Tissue- and developmental-specific gene activity is dictated by TF expression and binding affinity at CREs.
• Integrating multimodal genomic data (e.g., ChIP, ATAC, DNase, RNA sequencing) offers insights into CRE accessibility and TF activity but faces significant analytical challenges.

Purpose of the Study:

• To develop an automated pipeline for prioritizing condition-specific TFs from multimodal genomic data.
• To provide a user-friendly tool for analyzing TF activity and gene regulation.
• To facilitate the discovery of novel TFs and their roles in biological processes.

Main Methods:

• Developed TF-Prioritizer, an automated bioinformatics pipeline.
• Input data includes ATAC, DNase, or ChIP sequencing and RNA sequencing data.
• The pipeline prioritizes TFs based on differential activity and generates an interactive web report.

Main Results:

• TF-Prioritizer successfully identified known TFs and their target genes in mouse mammary glands.
• The tool also revealed previously unreported TFs active in lactating mammary glands.
• Analysis of ENCODE datasets (K562, MCF-7) highlighted assay-specific differences in chromatin accessibility and TF binding.

Conclusions:

• TF-Prioritizer enables a comprehensive understanding of genome-wide gene regulation by identifying TFs with differential activity.
• The tool facilitates the identification of potential pathogenic mechanisms and therapeutic targets in biomedical research.
• It offers a valuable resource for researchers studying gene regulation across various biological contexts.