Understanding transcription factor binding through a new model of DamID methylation

The expression of genes in a cell is regulated by proteins termed transcription factors. Different transcription factors can interact cooperatively to fine-tune gene expression. To better understand these interactions and how they influence cellular function, it is essential to know with a high degree of precision where the proteins interact with DNA.
One protocol that profiles genome-wide protein-DNA interactions in vivo is DamID. The protocol works by tethering the protein of interest to an Escherichia coli DNA adenine methyltransferase (DAM). The tethered DAM methylates adenines within GATC sequences in proximity to the protein of interest’s binding site. Although a versatile protocol that requires low amounts of starting material, it has a resolution that is dependent on the frequency of GATC sequences. This resolution is insufficient to effectively distinguish the order of transcription factor binding at regulatory regions. With the goal of improving the resolution of the information that can be extracted from DamID data, this thesis investigated the underlying principles of the technique and describes a new mathematical model for DamID methylation. Methods for scaling the signal produced by the tethered protein to its background signal and the best rate-influence models to model methylation about binding sites in DamID were also investigated. Finally, the methylation function was used to develop a binding site prediction algorithm to identify the binding locations for the protein of interest.
Improving the resolution of the information that can be extracted from DamID data will facilitate research in determining the combinatory mechanics of gene regulation and how transcription factor networks govern cell function