Regulation of gene expression plays a key role in the vast majority of developmental cell programs and disease states, and many human therapeutics act through regulation to alter gene expression. Greater than 90% of disease associated variants are in noncoding regions of the genome, which suggests that these variants likely act by altering gene regulation rather than the gene sequences themselves. Further, genetic interactions, for example when two genes physically interact, adds another layer of complexity to the regulation of our genes and can result in unanticipated effects on biological pathways. Despite advances in technologies to study the genome, including the increased accessibility of genome sequencing, we have yet to develop a clear understanding of how a given genotype leads to a given phenotype, or more specifically, how disease risk variants lead to disease and how changes in the expression of one gene can cascade through interconnected gene networks to produce nuanced biological outcomes. To expand our understanding of the functional effects of the genome, we leverage epigenomic and high-throughput technologies to develop new approaches for studying gene regulation and genetic interactions. First, we develop a tool for bidirectional epigenetic editing, termed CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell that can be applied to study the functional effects of noncoding regulatory elements as well as genes. We extend CRISPRai to a single-cell screening platform (CRISPRai Perturb-seq), which enables study of many genetic perturbations in a mixture of cell types in a single experiment. Next, we apply CRISPRai to study the genetic interaction between two hematopoietic transcription factors and elucidate their co-regulation on downstream target genes. Further, we leverage CRISPRai to study the regulatory landscape of the Interleukin-2 gene in T cells and uncover hierarchies among regulatory elements in gene regulation. Finally, we apply single-cell epigenomic analysis to immune cells from patients with the autoimmune disease Systemic Sclerosis to identify key cell types implicated in disease and nominate genomic loci for further study with tools like CRISPRai. Together, these approaches reveal new insight on gene regulation and genetic interactions and broaden the toolkit for studying the functional effects of the genome.

Please contact Madelyn Bernstein for the Zoom link.