Integrating genomics, development and evolution to elucidate the genotype-phenotype map of Drosophila wing morphology

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My long term research goal is to understand the genetic, genomic and developmental basis of natural phenotypic variation. Specifically, the goal of providing a broader quantitative genetics framework for precise and long-term predictions of phenotypic change critically requires a more integrative and detailed understanding of how genetic and environmental variation modulates development. Research in my lab works to address critical issues regarding the function of natural genetic variants across wild type genetic backgrounds, and how this ultimately shapes phenotypic effects. Our work is at the interface of developmental and quantitative genomics using a genetic model organism (Drosophila). Our approach allows us to address questions about the influence of allelic effects on complex phenotypes, and how these are modified by both genetic background and the environment. Aim 1: Recently we have developed a hypothesis to explain when (in terms of magnitude of the genetic perturbations) such genetic background effects are likely to be prevalent in natural populations. From our hypothesis, we predict that alleles of intermediate severity are most likely to be sensitive to the influence of wild type genetic background. The first aim for my research program is to test this prediction utilizing a broad distributions of mutations. This work will combine both standard genetic tools with a phenomic approach to developmental analysis of these allelic effects across a large panel of wild type genetic backgrounds. Aim 2: Why does a mutation have different effects in different individuals? One possibility is that wild type strains vary with respect to the timing or function of critical developmental events. Thus mutations may only perturb development events that are critical in some wild type strains, but not in others . I propose to test this using wing development. Aim 3: The Drosophila wing is a well established model for modifier screens to identify novel components in signaling pathways. Yet, it is unclear whether these same genes contribute phenotypically in natural populations. Our second program aim addresses this question, identifying natural genetic variants that contribute as modifiers of mutations of large effect. Using a combination of artificial selection, genetic mapping and genomic approaches, we will determine whether segregating genetic variants modifing mutations of large effect are concordant with genes contributing in traditional mutational studies. Our work will provide significant progress relating the findings of lab based developmental studies with segregating genetic variation. Furthermore, testing our hypothesis on the nature of genetic background effects may substantially alter our understanding of the nature of heterogeneity in allelic effects and the influence on complex traits including disease, which will be of benefit to all Canadians.