The Precision Medicine Initiative aims to leverage population-scale genome sequencing data to tailor treatment strategies to each individual's specific disease etiology and genetic background. However, common disease is increasingly understood to be both highly polygenic and pleiotropic, and many adult onset diseases likely stem at least in part from insults to cell differentiation during early embryogenesis. This complexity presents a steep challenge for achieving the goal of precision medicine, and points to the need for animal and cell models to fully dissect the molecular hierarchy and temporal dynamics linking genetic lesions to proximal effects on gene regulation and cell decisions, and to distal effects on disease. My research program takes advantage of powerful mouse mapping populations ? the Diversity Outbred (DO) and Collaborative Cross (CC) ? and embryonic stem cell lines derived from these populations, and integrates multi-scale genomics and advanced statistical approaches to decode how segregating genetic variation perturbs gene regulatory networks and influences ground state pluripotency, cell differentiation trajectories, and adult organ function. My published studies have yielded important insights into post-transcriptional regulation of the liver proteome. In Project 1 of this proposal, I will build on these previous and ongoing efforts to define the consequences of genetic variation on quantitative measures of protein translation and phosphorylation in the liver. This multidimensional genomic analysis will provide an unprecedented view of how genetic variation affects the molecular hierarchy of transcriptional and post-transcriptional mechanisms that regulate protein abundance and function. In Project 2, I will apply a similar systems genetic approach to characterize the genetic determinants and transcriptional dynamics underlying ground state pluripotency and differentiation potential in genetically diverse mouse embryonic stem cell (mESC) lines. This new research focus for my laboratory stems from an internal multi- investigator collaboration and successful pilot project, and has already revealed how segregating genetic variation influences chromatin accessibility, transcript abundance, and maintenance of the ground state. Project 2 will extend this molecular characterization to include quantitative proteomics and temporal single-cell transcriptomics, and will integrate statistical modeling tools to infer the molecular causal chain that links genetic variation to the fate decisions of individual cells. Together, the proposed projects will yield important insights into post-transcriptional regulation of the proteome, tissue homeostasis, and maintenance of ground state pluripotency and differentiation potential, and the influence of segregating natural genetic variation on the complex molecular hierarchy governing these processes. Future research will seek to further link this detailed molecular characterization with downstream assays of organ function and cell differentiation to construct and test predictive models of these processes, and ultimately to translate these insights from the mouse to inform cell differentiation, organ homeostasis, and disease processes in the human population.
The Precision Medicine Initiative aims to leverage patient genome sequences to tailor treatment strategies to each individual's specific disease etiology and genetic background. Achieving this worthwhile goal depends on our ability to dissect the complex causal chain linking genetic lesion to disease. My research program integrates emerging mouse genetic mapping populations and embryonic stem cell lines, state-of-the-art genomic profiling technologies, and advanced statistical modeling approaches to elucidate how genetic variation segregating in a population influences gene regulation at multiple levels and causes downstream effects on cell differentiation, organ function, and disease.