The Genetic basis of local adaptation
The environment is changing at an unprecedented rate and plants are the first to respond to these changes. How plants depend on their local environment and which evolutionary mechanisms lead to local adaptation are critical questions the public is pressing evolutionary ecologists to address.
In the lab, we combine quantitative genetics methods and biogeographic niche modelling to understand the genetic basis of locally adaptive fitness traits. Planting Arabidopsis thaliana across different climates over the native European range and performing genome-wide association mapping, we have identified genomic regions that determine fitness in particular environments, particularly demonstrating the importance of climate variation on adaptation (pdf).
However, selection often targets multiple correlated traits jointly influencing fitness such as life-history traits. We have shown that environmental heterogeneity across four geographically distant field sites across Europe leads to differential selection, either by targeting different loci, trait optimal value or trait correlation direction. This project overall highlighted a functional mechanism of geographic balancing selection potentially explaining the maintenance of differentiation across populations (pdf). If climate variation shapes adaptation, it is critical to understand how climate modification will affect the genetic diversity of a population. Plants have two ways to cope with climate change: they remain in the same location and adapt to new environmental conditions or migrate to track the climate they are adapted to. I am currently assessing the effect of such environmental perturbation using a genetically diverse panel of A. thaliana in controlled chamber conditions. Using the actual climate in Norwich (UK) in real time as reference conditions, I am comparing the fitness of plants in this climate to that of plants exposed to the predicted climate of 2100 and to those having migrated northward by 13° in 2100, where the photoperiodic regime is different. I am using the information from planting genetically diverse plants at various time of the year in these perturbed environmental conditions to predict the expected evolution of intraspecific genetic diversity. We are currently building a single integrated life-cycle model for A. thaliana that would predict the genetic composition of both the plant community and the seed stock. The final objective is to know how genetic diversity will ultimately face climate change when selecting genotypes adapted to increased temperatures or when migrating northward (see video and pdf).