Decoding Gene-Environment Interactions in Complex Traits via Multi-Omics Approaches - PROJECT SUMMARY Complex traits are influenced by the interplay of genetic variations, environmental exposures, and their complex interactions. As environmental conditions shift, genetic variations that were once advantageous may now contribute to diseases. Identifying the genetic basis for phenotypic differences and environmental adaptation is particularly challenging due to the highly polygenic nature of these traits, extensive pleiotropy of the genes involved, and the complexity of gene-environment interactions. The primary research focus of my lab is to unravel the genetic basis of complex trait variation and novel trait evolution through two complementary tactics: (1) We explore cryptic genetic variations that are unmasked by introducing environmental or genetic perturbations in model organisms. (2) We investigate genomic signatures in natural populations that have adapted to extreme environments. To accomplish our research objectives, we employ a combination of experimental and computational methods, including cutting-edge comparative, quantitative, and evolutionary omics studies in both natural and laboratory organisms. Over the next five years, our goal is to dissect a series of complex traits and their interactions with dietary environments by linking the phenome with the genome, and via integrating intermediate molecular phenotypes to construct a gene-transcript-metabolite-phenotype network. We aim to uncover cryptic genetic variations that have been hidden under normal conditions but are revealed through environmental perturbations using both inbred and outbred Drosophila populations, including a novel genetic mapping resource. We will leverage multi-omic analysis to investigate how these variations influence the phenotype of complex traits. Our research strategy includes three key lines: first, we will employ a powerful mapping strategy to uncover cryptic genetic variations under environmental stress and gene-environment interactions across different extreme dietary conditions; next, we will explore the phenotypic changes in Drosophila populations induced by the environmental stress, which allows us to evaluate phenotypic variation and heritability, and identify correlations among metabolic, developmental, and mitochondrial traits, the genetic correlations of these traits and pleiotropy of associated genes; lastly, we will adopt a systems biology approach to integrate genetic variations with transcriptomic and metabolomic data to uncover the relationships between genetic variation, gene expression, metabolite profiles, and complex organismal traits. Overall, the successful execution of this research is expected to uncover novel gene-environment interactions, cryptic genetic variation, unknown pleiotropy, and elusive components of genetic architecture, significantly advancing our understanding of complex traits. By pioneering new multi-omic strategies and providing a comprehensive framework for dissecting the intricate networks linking genetic variation with phenotypic outcomes, this research holds transformative potential for advancing precision medicine and offering new insights into complex diseases.
