Evolvability in a variable world: genetic architecture in Arabidopsis thaliana and its implications for adaptation

Evolvability, the ability of a population to adapt to its environment, is critically affected by the genetic architecture of key traits which are further affected by the environmental context. Modern approaches to quantifying genetic architecture at several scales of biological organization allow elucidation of constraints and accelerants to evolutionary change. In chapter one, I describe a novel approach to quantifying genetic architecture that combines recombinant inbred lines (RIL) with line cross analysis. By defining genetic effects relative to an F2 population and incorporating RIL (which are available for many model species), the sampling variance of several nonadditive genetic effect estimates is greatly reduced. The RIL population can be simultaneously used for quantitative trait locus (QTL) identification, thus uncovering the effects of specific loci or genomic regions as elements of genetic architecture. In chapter two, I investigate constraints to evolvability in a set of Arabidopsis thaliana RIL populations grown under four levels of nitrogen (N) availability ranging from saturating to stressfully low N-supply rates. I show that changes in N-availability can alter genetic covariances, QTL location and effect magnitude, principle component (PC) structure, and the constraint due to the mismatch between the axes of multivariate genetic variation (particularly PC1 or g-max) and the direction of evolutionary change favored by selection. In chapter three, I show that the G-matrix structures of Arabidopsis RIL populations in different N-environments possess patterns of trait associations different enough to alter simulated evolutionary trajectories. I discuss the role of genetic covariances and main-effect QTL in determining the different adaptive trajectories. In chapter four, I report on an extensive QTL mapping study using A. thaliana RIL to determine the genetic basis of plastic responses to shifts in the N-environments as well as the role of epistasis in quantitative trait architecture. Exhaustive searches for QTL x QTL interactions at 1cM intervals for 78 trait-environment combinations revealed the presence of several epistatic QTL with no main effect and resolved several seemingly pleiotropic QTL in tightly liked interacting loci. The implications of these patterns of genetic architecture are discussed in the concluding chapter