Although recent advances in genomics have revealed a tremendous amount of nucleotide polymorphism, little is known about why genes segregate for variants that influence quantitative traits. This proposed research seeks to determine which evolutionary processes influence natural genetic variation for complex traits. In order to identify and interpret allelic variants underlying QTLs, this experimental system has four fundamental characteristics: 1) An ecologically important complex trait, 2) a clonable QTL in a known pathway, 3) undisturbed environments where fitness can be measured, and 4) undisturbed populations which retain sequence signatures of temporal and geographic history. These evolutionary analyses use biochemistry to connect genotype with phenotype, and use natural environments to measure fitness. Nevertheless, the fundamental justification for this work is to test hypotheses regarding the evolutionary processes which influence complex trait variation. Towards this goal, a QTL will be cloned which influences ecologically important quantitative variation. Near isogenic lines with better than single gene resolution will be used to measure the fitness and phenotypes of functionally divergent alleles grown in their natural environments. Finally, sequence variation will be used to infer historical and evolutionary influences on allelic variation in undisturbed populations. Public Health Relevance: This proposed research will contribute to our understanding of complex trait variation, which is one of the primary causes of human disease. In addition, these experiments examine the genetics of glucosinolates, which are a focus of biomedical research due to their role in prevention of many forms of cancer, as well as gastritis attributable to Helicobacter pylori.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM086496-03
Application #
7903096
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Eckstrand, Irene A
Project Start
2008-09-30
Project End
2012-08-31
Budget Start
2010-09-01
Budget End
2011-08-31
Support Year
3
Fiscal Year
2010
Total Cost
$293,436
Indirect Cost
Name
Duke University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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Keith, Rose A; Mitchell-Olds, Thomas (2017) Testing the optimal defense hypothesis in nature: Variation for glucosinolate profiles within plants. PLoS One 12:e0180971
Wang, Baosheng; Mitchell-Olds, Thomas (2017) Balancing selection and trans-specific polymorphisms. Genome Biol 18:231
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Olson-Manning, Carrie F; Strock, Christopher F; Mitchell-Olds, Thomas (2015) Flux Control in a Defense Pathway in Arabidopsis thaliana Is Robust to Environmental Perturbations and Controls Variation in Adaptive Traits. G3 (Bethesda) 5:2421-7
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Lee, Cheng-Ruei; Anderson, Jill T; Mitchell-Olds, Thomas (2014) Unifying genetic canalization, genetic constraint, and genotype-by-environment interaction: QTL by genomic background by environment interaction of flowering time in Boechera stricta. PLoS Genet 10:e1004727
Heo, Jae-Yun; Feng, Dongsheng; Niu, Xiaomu et al. (2014) Identification of quantitative trait loci and a candidate locus for freezing tolerance in controlled and outdoor environments in the overwintering crucifer Boechera stricta. Plant Cell Environ 37:2459-69
Anderson, J T; Wagner, M R; Rushworth, C A et al. (2014) The evolution of quantitative traits in complex environments. Heredity (Edinb) 112:4-12

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