Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Transcription factors (TFs) regulate gene expression by binding to DNA.
• TF binding is traditionally assessed via DNAse digestion footprints.
• Many TF binding motifs lack detectable footprints due to variable cleavage patterns.

Purpose of the Study:

• To develop a more accurate method for detecting TF activity and its effect on chromatin accessibility.
• To overcome the limitations of traditional footprinting assays.

Main Methods:

• Developed a novel algorithm named bivariate genomic footprinting (BaGFoot).
• BaGFoot analyzes both TF-dependent footprinting and motif-flanking accessibility.
• Algorithm tested for robustness across different accessibility assays (DNase-seq, ATAC-seq) and analysis pipelines.

Main Results:

• 80% of TF binding motifs do not exhibit measurable footprints with traditional methods.
• BaGFoot efficiently detects TF activity and reliably predicts TF binding.
• The algorithm provides insights into TF effects on chromatin accessibility, even when footprints are absent.

Conclusions:

• BaGFoot offers a more comprehensive approach to studying TF-chromatin interactions.
• This method enhances the understanding of gene regulation in diverse biological contexts.
• BaGFoot is a valuable tool for analyzing TF activity and chromatin accessibility.