Abstract
Transcription factor RBPJ is the central component in Notch signal transduction and directly forms a coactivator complex together with the Notch intracellular domain (NICD). While RBPJ protein levels remain constant in most tissues, dynamic expression of Notch target genes varies depending on the given cell-type and the Notch activity state. To elucidate dynamic RBPJ binding genome-wide, we investigated RBPJ occupancy by ChIP-Seq. Surprisingly, only a small set of the total RBPJ sites show a dynamic binding behavior in response to Notch signaling. Compared to static RBPJ sites, dynamic sites differ in regard to their chromatin state, binding strength and enhancer positioning. Dynamic RBPJ sites are predominantly located distal to transcriptional start sites (TSSs), while most static sites are found in promoter-proximal regions. Importantly, gene responsiveness is preferentially associated with dynamic RBPJ binding sites and this static and dynamic binding behavior is repeatedly observed across different cell types and species. Based on the above findings we used a machine-learning algorithm to predict Notch responsiveness with high confidence in different cellular contexts. Our results strongly support the notion that the combination of binding strength and enhancer positioning are indicative of Notch responsiveness.