En-Gen: Ecological Genomics of Local Adaptation and Trait Variation in an Arabidopsis Relative
Duke University, Durham NC
Investigators
Abstract
Although recent advances in genomics have revealed a tremendous amount of segregating variation, little is known about why genes segregate for nucleotide polymorphisms that influence ecologically important quantitative traits. For quantitative trait loci controlling complex trait variation, it is still unclear what evolutionary forces explain molecular polymorphism within species. Plausible explanations include deleterious variation, local adaptation, balancing selection, and neutral genetic drift. These hypotheses have fundamentally different implications for evolutionary ecology ? but each is compatible with current understanding of complex trait variation. This project entails ecological and genomics experiments to distinguish among these hypotheses in natural populations of Boechera stricta, an Arabidopsis relative. These analyses will identify quantitative trait loci responsible for local adaptation in flowering time across an elevation gradient. In addition, within population variation at these loci will be compared to predictions of deleterious and balanced polymorphism models in order to infer the evolutionary processes influencing quantitative variation at ecologically important genes. The goal of this project is an understanding of the evolutionary factors responsible for genetic variation within and among plant populations. By examining natural variation for flowering time, the investigator will be able to determine the relative importance of harmful mutations versus advantageous genetic differences, one of the fundamental unresolved questions in studies of complex traits. Other societal benefits will include providing research opportunities for high school students, mentoring undergraduates, and involving underrepresented minorities in the project. This work also will contribute to resources for the scientific community for environmental genomics of plant species.
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