Modeling Cooperative Binding of Transcription Factors to DNA
Transcriptional regulatory networks, composed of regulatory proteins and their target genes, control many aspects of cell development and physiology. One important class of regulatory proteins are transcription factors (TFs), which bind to DNA in a sequence specific manner to regulate gene expression. In the human genome, TFs often bind in clusters, i.e. two or more DNA binding sites in close proximity to each other. However, the binding of TFs to clusters of sites is not well understood. Most studies consider TF binding to clusters of sites to be cooperative simply because of the close proximity between the binding sites. However, by definition, cooperative binding implies that binding of one TF to a site enhances the binding of another TF at another site in the same cluster. When the two binding events are independent of each other, the binding is considered additive, or non-cooperative. In this project, we will develop models of cooperative binding of TFs to neighboring sites. Our models will use features derived from the DNA sequence and structure of the binding sites and their flanking regions, as well as the distance between the binding sites, and will be trained using high-throughput data generated in our lab. We will then use our models to make predictions of cooperative binding across the human genome.