Inference of cell type specific regulatory networks on mammalian lineages

Transcriptional regulatory networks are at the core of establishing cell type specific gene expression programs. In mammalian systems, such regulatory networks are determined by multiple levels of regulation, including by transcription factors, chromatin environment, and three-dimensional organization of the genome. Recent efforts to measure diverse regulatory genomic datasets across multiple cell types and tissues offer unprecedented opportunities to examine the context-specificity and dynamics of regulatory networks at a greater resolution and scale than before. In parallel, numerous computational approaches to analyze these data have emerged that serve as important tools for understanding mammalian cell type specific regulation. In this article, we review recent computational approaches to predict the expression and sequence-based regulators of a gene's expression level and examine long-range gene regulation. We highlight promising approaches, insights gained, and open challenges that need to be overcome to build a comprehensive picture of cell type specific transcriptional regulatory networks.