It has become clear that genetic background, including both common and rare variants, significantly influences disease susceptibility, severity, prognosis and even treatment effectiveness. Most genetic variants assert subtle effects in isolation, but certain combinations can disrupt normal homeostasis and sensitize an individual to disorder. Thus, many complex diseases have resisted classification by single-gene experimental and/or statistical modeling approaches. A comprehensive characterization of the genetic etiology of complex disorders and disease must account for the effects of all inputs (e.g. genetic variation) on all outputs (e.g. transcription, measures of structure/function) in the context of the affected system.
My overarching research goals are to 1) characterize the transcriptional network architecture underlying normal organ development and homeostasis, 2) predict the genes, gene-gene interactions, and coregulated gene cohorts with major roles in this process, and 3) identify and validate genetic mutations with individual small effects that together disrupt the buffering capacity of the transcriptional network and cause a disordered/disease state. To that end, I take a systems genetics approach that integrates advanced computational methods and experimental validation techniques to next-generation genetic mapping populations, including the mouse Collaborative Cross and Diversity Outcross, to elucidate and compare the transcriptional network structure and dynamics driving organogenesis (the embryonic gonad at the critical time point of primary sex determination) and adult tissue homeostasis (liver).