Experimental organisms, such as Drosophila, can be genetically manipulated to recapitulate human diseases. We have constructed a complex disease model of misfolded proteins by expressing a mutant diabetes-causing human proinsulin protein (INSC96Y) in the Drosophila eye and other tissues. The severity of proteostatic disease phenotypes in this model varies when the mutant transgene is placed in different wild-derived genetic backgrounds and this genetic variation can be mapped with high resolution by genome-wide association studies (GWAS), bulk segregant analysis of extreme phenotypes, and gene expression studies. Here we propose innovative experimental approaches to enhance the value of Drosophila as a model for investigating naturally occurring genetic variation influencing the severity of proteostatic disease or other complex traits. This application has three specific aims: (1) Map genetic variation and expression QTL's that modify cellular response to proteostatic challenge in two developing tissues, the eye and notum. A novel application of bulk segregant analysis of extreme phenotypes in an array of synthetic fly populations will be used to enhance the signals from both common SNPs and rare variants with effect sizes not detectable by conventional GWAS; (2) Screen the synthetic populations to identify alleles that are suppressed by the inhibition of apoptosis. The approach is a novel population genomic analog of a classical genetic suppressor screen; and (3) Investigate the interaction between environmental and genetic inputs to the breakdown of proteostasis.
Human genetic variation influences many aspects of health and disease, but the vast majority of this genetic variation is proving difficult to pinpoint to single genes or mutations. We propose novel approaches using a fruit fly model of protein misfolding disease to investigate the genetic complexity of this disease. Although specific mutations may differ between fruit fly and human, many important characteristics of this variation are expected to be the same between the two species. The results should be valuable in designing better cost-effective strategies for identifying health-related genetic variation in humans.
