We are a creative and energetic team at UT Southwestern Medical Center's Green Center for Reproductive Biology, and we are intensely focused on unraveling the functions of the non-coding genome. While this “dark matter” comprises the vast majority of mammalian genomes, our understanding of its function is only in its infancy. We know that it holds a wealth of regulatory information to precisely coordinate gene expression across all of an organism’s cell types. Underscoring their functional significance, most disease-associated loci are non-coding.
Still, our understanding of regulatory element function is largely anecdotal, and it is surprising how little we know given how proficient we have become at finding them. How do the millions of non-coding regulatory elements, including enhancers, promoters, insulators, and repressors, synergize to precisely control gene expression? How do genetic and epigenetic perturbations affect regulatory element function and contribute to disease? Can we build a predictive understanding of non-coding element function to learn rules of gene regulation? We explore these questions using a systems biology approach: developing and employing integrative techniques at the interface of gene regulation, epigenetics, functional genomics, and bioinformatics.
Specifically, to provide a descriptive global view of gene regulation, we employ high throughput sequencing assays to interrogate the epigenome, identify regulatory elements, and probe the three-dimensional interactions of these elements with target genes. In parallel, to derive predictive models, we are developing high throughput approaches using epigenome engineering to endogenously assay regulatory function. Through integrative bioinformatic analysis, we apply these predictive models to descriptive global data to address key questions of regulatory function in developmental and disease contexts.
Our eventual goal is to understand gene regulation in humans so well that we can 1) predict it and 2) engineer it for potential therapeutic benefit.