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.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM045146-17S1
Application #
7901762
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Eckstrand, Irene A
Project Start
2009-09-01
Project End
2011-08-31
Budget Start
2009-09-01
Budget End
2011-08-31
Support Year
17
Fiscal Year
2009
Total Cost
$438,949
Indirect Cost
Name
North Carolina State University Raleigh
Department
Genetics
Type
Schools of Earth Sciences/Natur
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695
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He, X; Zhou, S; St Armour, G E et al. (2016) Epistatic partners of neurogenic genes modulate Drosophila olfactory behavior. Genes Brain Behav 15:280-90
Huang, Wen; Lyman, Richard F; Lyman, Rachel A et al. (2016) Spontaneous mutations and the origin and maintenance of quantitative genetic variation. Elife 5:
Riedl, Craig A L; Oster, Sara; Busto, Macarena et al. (2016) Natural variability in Drosophila larval and pupal NaCl tolerance. J Insect Physiol 88:15-23
Hunter, Chad M; Huang, Wen; Mackay, Trudy F C et al. (2016) The Genetic Architecture of Natural Variation in Recombination Rate in Drosophila melanogaster. PLoS Genet 12:e1005951
Dembeck, Lauren M; Böröczky, Katalin; Huang, Wen et al. (2015) Genetic architecture of natural variation in cuticular hydrocarbon composition in Drosophila melanogaster. Elife 4:
Anholt, Robert R H; Mackay, Trudy F C (2015) Dissecting the Genetic Architecture of Behavior in Drosophila melanogaster. Curr Opin Behav Sci 2:1-7
Ober, Ulrike; Huang, Wen; Magwire, Michael et al. (2015) Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait. PLoS One 10:e0126880
Huang, Wen; Carbone, Mary Anna; Magwire, Michael M et al. (2015) Genetic basis of transcriptome diversity in Drosophila melanogaster. Proc Natl Acad Sci U S A 112:E6010-9
Garlapow, Megan E; Huang, Wen; Yarboro, Michael T et al. (2015) Quantitative Genetics of Food Intake in Drosophila melanogaster. PLoS One 10:e0138129

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