Most phenotypic variation relevant to human health and adaptive evolution is genetically complex, with population variation attributable to segregating alleles at many interacting genes with environmentally sensitive effects. The long-term goal of this project is to understand the genetic architecture of such quantitative traits in terms of the molecular basis of allelic variation at individual loci and the distribution of effects of alleles on multiple traits;and the extent to which these effects are context-dependent and vary depending on sex, genetic background, and the physical and social environment. Drosophila melanogaster is an excellent model system for elucidating general principles regarding the genetic architecture of complex traits using genome wide association (GWA) mapping, because high levels of molecular polymorphism and low linkage disequilibrium in Drosophila facilitate the identification of not only genes associated with complex traits, but actual causal polymorphisms. The major impediment to GWA mapping in Drosophila is that complete genome sequence from ~200 fly lines is necessary. The National Human Genome Research Institute recently approved the whole-genome sequencing of 192 inbred D. melanogaster lines, derived from the Raleigh, US population, as a Drosophila Genetic Reference Panel (DGRP). These lines and genome wide polymorphism data will be a community resource for rapid and high resolution mapping of genes affecting complex traits in a range of environments. However, molecular polymorphisms affect quantitative traits by perturbing transcriptional and other biological networks. Understanding the impact of genetic variation on both underlying networks and genetic variation for the traits is necessary if we are to place the statistical associations in biological context.
The specific aims for this project period are to perform GWA analyses of several quantitative traits in two environments, using the 192 DGRP inbred lines;to identify genetic networks associated with quantitative traits in two environments;and to perform functional studies to confirm associations and validate networks. These studies will give unprecedented insight into the interacting loci affecting a range of complex traits, distributions of allelic effects for each trait and pleiotropic effects on multiple traits, and the molecular basis of genotype by environment interaction. These studies will provide a comprehensive understanding of the relative contribution of common vs. rare variants, alleles of large vs. small effects, single nucleotide polymorphisms vs. copy number variants, and non-synonymous polymorphisms in coding regions vs. putative regulatory polymorphisms to the molecular basis of variation for quantitative traits. This systems genetics approach using the Drosophila model will generate a wealth of generally applicable insights in the relationship between genotypic variation and phenotypic variation for the manifestation of complex traits.

Public Health Relevance

Variation in human populations for susceptibility to common diseases and behavioral disorders, as well as responses to pharmacological therapies, is genetically complex. However, the organization of the human genome into haplotype blocks is an impediment to identifying causal polymorphisms associated with complex traits, and variable genetic backgrounds and environmental exposures further limit our ability to determine context-dependent phenotypic effects of molecular polymorphisms in human studies. This study takes advantage of the power of genome wide association analyses in Drosophila and the complete re-sequencing of 192 fly lines to identify molecular polymorphisms and genetic networks associated with several complex traits, and to investigate how the associations and networks are modulated by environmental stress. The insight into general principles of genotype-phenotype relationships will be applicable to human disease.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Eckstrand, Irene A
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North Carolina State University Raleigh
Schools of Earth Sciences/Natur
United States
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Mackay, Trudy F C (2014) Epistasis and quantitative traits: using model organisms to study gene-gene interactions. Nat Rev Genet 15:22-33
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Mackay, Trudy F C; Richards, Stephen; Stone, Eric A et al. (2012) The Drosophila melanogaster Genetic Reference Panel. Nature 482:173-8
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Zhou, Shanshan; Campbell, Terry G; Stone, Eric A et al. (2012) Phenotypic plasticity of the Drosophila transcriptome. PLoS Genet 8:e1002593
Weber, Allison L; Khan, George F; Magwire, Michael M et al. (2012) Genome-wide association analysis of oxidative stress resistance in Drosophila melanogaster. PLoS One 7:e34745

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