Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.

Human B cell differentiation into antibody secreting plasma cells is a critical process in the adaptive immune response, whose regulation at the genetic level remains incompletely understood. To reveal the temporal sequence of transcription factor driven cellular changes we generated chromatin accessibility (ATAC-seq) and gene expression (RNA-seq) data from in vitro differentiation of human B cells into plasma cells using a published protocol for differentiation up to the plasma cell stage. Using a new computational method, cisREAD (cis-Regulatory Elements Across Differentiation), we defined a core set of cis-regulatory elements that are confidently linked to dynamic transcription factor binding and changes in gene expression across the mature B lineage. Here we describe how cisREAD identifies regulatory element communities, based on chromatin accessibility and transcription factor co-occupancy, and prioritizes those whose accessibility predicts differential gene expression through regularized regression models. Through downstream analyses of cisREAD-predicted regulation, we show how transcription factors reshape B cell epigenomes and transcriptomes in response to differentiation stimuli. Our results confirm roles for OCT2, IRF4 and PRDM1 in plasma cell differentiation, and reveal that a shift from PU.1/SPIB-driven to AP-1-driven gene regulation is a key determinant of B cell activation.