WhichTF is functionally important in your open chromatin data?

Area of Science:

• Genomics
• Computational Biology
• Molecular Biology

Background:

• Identifying functionally important transcription factors (TFs) is crucial for understanding gene regulation.
• Existing methods often rely on TF abundance, which may not reflect functional relevance.
• Chromatin accessibility measurements offer insights into TF activity but require sophisticated analysis.

Purpose of the Study:

• To develop and validate WhichTF, a novel computational method for identifying functionally important TFs from chromatin accessibility data.
• To improve the identification of context-specific TFs compared to abundance-based approaches.
• To provide deeper biological insights into TF-mediated transcriptional regulation.

Main Methods:

• WhichTF integrates chromatin accessibility measurements with conservation-aware TF binding site data and gene-regulatory models.
• An ontology-guided functional approach is used to compute novel enrichment for TF ranking.
• Differential analysis is applied to distinguish regulatory landscapes in closely related samples.

Main Results:

• WhichTF successfully identifies context-specific TFs with functional relevance, such as NF-κB in lymphocytes and GATA factors in cardiac cells.
• Differential analysis highlights the utility of WhichTF in diverse cell types, including lymphocytes, mesoderm development, and disease cells.
• The method reveals under-characterized TFs like RUNX3 and GLI1, and identifies TFs associated with stress response.

Conclusions:

• WhichTF is a powerful computational tool for identifying functionally important transcription factors from chromatin accessibility data.
• The method offers unique advantages over abundance-based approaches, providing context-specific insights.
• WhichTF enhances the understanding of known and novel molecular mechanisms in TF-mediated transcriptional regulation across various biological contexts.