Modeling the Complex Impact of Genetic Variation on Gene Expression

Non-coding and regulatory genetic variation plays a significant role in human health, but the impact of regulatory variants has proven difficult to predict from sequence alone. Further, genetic effects can be modulated by context, such as cell type and environmental factors. We have developed machine learning approaches to model the effects of regulatory variation, including predicting the impact of rare regulatory variants on gene expression, modeling the interaction between environmental factors and genetic variation, and detecting regulatory effects that vary over time. I will present recent results evaluating the complex impact of both rare and common genetic variation on gene regulation in diverse contexts including changes in genetic effects evident across cellular differentiation.

Speaker: Alexis Battle, Johns Hopkins