Cooperative transcription factor associations discovered using regulatory variation

Area of Science:

• Genetics
• Molecular Biology
• Bioinformatics

Background:

• Gene expression is tightly regulated by transcription factors binding to DNA.
• Identifying specific combinations of transcription factors at target genes is a major challenge in molecular biology.
• Understanding combinatorial binding is crucial for deciphering gene regulatory networks.

Purpose of the Study:

• To develop and validate a novel computational and experimental pipeline for discovering allele binding interactions of transcription factors.
• To identify combinations of transcription factors that cooperatively bind to target genes.
• To advance the understanding of the genetic basis of variation in transcription factor binding.

Main Methods:

• Development of the ALPHABIT (a large-scale process to hunt for allele binding interacting transcription factors) pipeline.
• Utilizing the Allele Binding Cooperativity test, which leverages inter-individual variation in transcription factor binding.
• Statistical analysis of binding sites integrated with experimental validation.

Main Results:

• The ALPHABIT pipeline successfully predicted transcription factors that associate with NFκB.
• Identified known coassociating factors (E2A, STAT1, IRF2) with NFκB, revealing their global coassociation and cooperative binding sites.
• Discovered a novel coassociation between EBF1 and NFκB, previously unreported.

Conclusions:

• The developed method provides a general approach for discovering combinatorial models of gene regulation.
• This work enhances the understanding of the genetic underpinnings of variation in transcription factor binding.
• The findings offer new insights into the complex interactions governing gene expression and regulatory networks.