Genome evolution across complex trait hierarchies

Project Summary Most human health traits are highly complex and hierarchical, in which a high-level trait (e.g., energy expenditure) is the product of the combined effects of a suite of sub-phenotypes. These trait hierarchies are typically influenced by many genetic variants of small effect that interact with one another and with environmental factors, making the identification of the causative variants a significant challenge. As a result, past research strategies have largely failed to fully address the complexity of most complex traits, leaving a significant knowledge gap in our understanding of the genetic basis of these traits. This project will use an innovative combination of a large multiparent mapping population and experimental evolution using the powerful fruit fly model system to identify the common mechanistic connections between complex traits and observe how these connections influence multitrait evolution. First, this project will simultaneously evolve flies targeting multiple trait hierarchies and track the genomic and phenotypic changes that occur during adaptation. Second, this project will leverage a large multiparent mapping population that has been used broadly in the genetics community to address fundamental questions about the generality of emergent properties of the genome, such as the extent of pleiotropy, genotype by environment interactions, and genetic background effects. Overall, this research will provide generalizable lessons about how genomes are connected to physiology to produce the interconnected set of traits that affect health across the lifespan.