Dissecting cryptic genetic variation underlying complex traits in Drosophila

项目总结

PROJECT SUMMARY Determining the genetic basis of complex traits is a significant challenge, largely due to several factors. Firstly, complex traits involve multiple genetic variants, environmental factors, and intricate interactions among them. Secondly, there is cryptic genetic variation that remains "hidden" within genetic backgrounds and only expresses under atypical conditions. Thirdly, there are missing connections between genotypes and phenotypes, such as molecular phenotypes like transcriptomics and metabolomics, which represent a critical gap in our understanding. To address these challenges, we use Drosophila as a model organism, taking advantage of the abundant natural variation, the powerful genetic tools, and the ability to better control environmental factors. Our goal is to reveal the system cryptic genetic variation by sensitizing the system using two complementary approaches – high sugar diet as environmental stressor and an inducible genetic defect as genetic perturbation. We will use a system approach by integrating genomics, transcriptomics, and metabolomics to dissect the gene-gene and gene-environment interactions responsible for metabolism and development. First, we will identify cryptic genetic variation in high sugar diet-induced metabolic and developmental traits and gene by diet interactions using a new mapping resource we have created with advanced intercross populations to enhance mapping power and resolution. Secondly, we will use the metabolome as an intermediate molecular phenotype to bridge the gap between identified genetic variants and organismal phenotypes. By analyzing a wider range of traits under different dietary conditions, we will identify the genetic variants and metabolites associated with these traits, and use these findings to build complex genome- metabolome-phenome interaction networks. Lastly, we have developed an inducible model that introduces a genetic defect genotype into various genomic backgrounds of the Drosophila Genetic Reference Panel. This will allow us to identify cryptic genetic modifiers and gene-gene interaction underlying affected metabolic and physiological phenotypes, and we will also profile the transcriptome to further understand the molecular functions of associated variants. Overall, the proposed study is expected to expose cryptic genetic variation, uncover novel gene-gene and gene-environment interactions, reveal missing pathway members underlying metabolism and development, and provide new models and strategies to investigate complex traits.