DISSERTATION RESEARCH: Shedding Light on the Complex Relationship Between Circadian Clock Variation and the Trade-off Between Flowering Time and Flower Size

Duke University, Durham NC

Investigators

Abstract

A key question in evolutionary biology is how variation is maintained within populations. One possible mechanism is trade-offs between traits. This research will demonstrate whether such trade-offs occur in natural populations of the monkeyflower, Mimulus guttatus, and if developmental patterns influence such trade-offs. For many plants there is a trade-off between flowering time and number or quality of seeds. For example, plants that flower early typically have smaller flowers that are less attractive to pollinators and produce smaller seeds. However, a single population could maintain genetic variation for both early flowering and large flowers because either strategy might be successful. The project also will provide hands-on experience to undergraduates and outreach to middle and high school students. Mimulus guttatus is a short-lived annual. In both the greenhouse and field there exists a centrally important trade-off between flowering time and flower size. Circadian period length can serve as a highly informative intermediate trait for identifying the genetic underpinnings of flowering time variation. The circadian clock gene network is well characterized, is known to affect flowering time, and varies among populations. The project will identify and characterize loci associated with changes in period length, and determine relationships between period length, differential gene expression, and different flowering parameters. The first aim will be accomplished by determining period length of all members of a pre-existing set of 200 fully sequenced inbred lines generated from a single population. By conducting genome-wide association mapping the researchers will identify loci associated with variation in period length, flowering time, and flower size. The second aim will be accomplished using an RNA sequencing based approach to characterize the contribution of alternate alleles at previously identified loci to differential gene expression.