Evolutionary and computational genomics of natural variation in plants
The aim of our group is to decipher how natural selection and other evolutionary forces shape genomic and phenotypic variation in natural plant populations. To this end, we use computational and population genetics approaches applied to large-scale genomics data sets. We integrate these analyses with phenotypic data, growth chamber experiments and molecular validation of candidate functional variants to identify allelic variants that contribute to adaptation in diverse environments.
Current projects in the group focus on natural populations of the perennial, alpine plant Arabis alpina collected in a wide range of environments. First, we characterize variation among European populations in flowering behavior, a crucial component of plant fitness. This comprehensive phenotypic map highlights exceptional cases of divergence suggestive of adaptive evolution. We elucidate adaptive processes in these populations with evolutionary genomics approaches applied to large numbers of re-sequenced individual plants. Understanding natural adaptive dynamics, e.g. in relationship to drought and the developmental response to environmental cues can help us forecast evolutionary responses to climate change, as well as revealing variants of agricultural interest. Comparison of the results with those obtained with annual Arabidopsis thaliana enable us to consider the effects of life history on adaptation.