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Abstract:
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By analyzing the correlation between phenotypic and genotypic variation in human populations, Genome-Wide Association Studies have been successful in identifying numerous genetic loci relevant to human traits such as disease susceptibilities and anthropometric features. However, such direct statistical associations provide limited information on the underlying biological processes relevant to the trait. I believe that the integration of gene regulatory information will be a key step in achieving better understanding of these genotype-phenotype relations. In this lecture I will review research by my lab and others on the inference of context-specific gene regulatory relations based on bulk or single cell data from diverse cell type, tissue type and developmental contexts. I will also describe our effort to exploit this information to build multi-layer statistical models capable of providing a more mechanistic understanding of human trait variation.
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