The capacity of organisms to respond to selective pressures on multiple traits is determined in part by the genetic covariances between those traits. This project will map regions of the genome associated with genetic variation in glucosinolate traits in a population of Boechera stricta, a model plant for evolutionary genetics. B. stricta makes several types of glucosinolates, compounds that defend the plant against insect herbivores. By mapping the regions of the genome that control glucosinolate profile in each type of plant tissue, the investigator will determine whether the same or different loci control glucosinolates throughout the plant. Then, using population data at these genomic regions, the amount of covariation in glucosinolate traits controlled by each locus will be determined.
Knowing the genetic architecture of covarying traits is essential in predicting how those traits are able to respond to selection; if one gene controls multiple traits, evolutionary constraints are likely to be stronger than if trait correlations are caused by correlated selective pressures. Genetic covariances have been important to plant breeders, as well, as they may affect the response to artificial selection. Understanding the genetic basis of glucosinolate allocation, which is agriculturally relevant and affects cancer risk in humans, will lend insight into how breeding programs may affect crop plants. This grant will also support training of a young scientist in important genomic techniques and analyses, as well as outreach efforts in traditionally underperforming schools encouraging students, particularly girls, to pursue college and a career in the STEM fields.
