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Experimental evolution combined with modern genomic tools provides a great opportunity to examine the dynamics and strength of selection in real time as well as to test the validity of prominent ecological hypotheses. For instance, ecological theory states that plants cannot simultaneously be efficient at certain tasks, such as acquiring and conserving resources, or be both competitive and stress tolerant. Resulting trade-offs between traits are described as major constraints that drive plant diversification across large taxonomic scales. However, the role of these trade-offs on the rapid adaptation and differentiation of populations within species remains to be elucidated. Here we present ARABREED, a project that aims at exploring the evolution of complex trait variation and covariation with the development of new approaches at the interface between ecology, evolutionary biology and genomics. In ARABREED, we monitor the evolution of the model plant Arabidopsis thaliana over several generations in four environments, which differ in resource availability (nutrient and water), and herbivores abundance. Each experimental population consists of 17,500 recombinant lines, previously generated from 350 random crosses between 400 natural and fully sequenced accessions. This has the advantage of breaking up ancestral gene complexes and recreating phenotypes thought to be purged in natural populations. Experimental populations are replicated seven times per environment (28 populations for 500,000 genotypes in total). Each year during the project, multiple samples will be collected to perform population genetic analysis with pool-seq, and plant traits involved in major ecophysiological trade-offs will be phenotyped. Thus, with ARABREED we aim to assess the evolution and the underlying allelic changes of complex traits and trait-trait relationships in response to controlled selection pressures.
In my past research, I sought to examine the importance of genetic and environmental factors on the functioning and evolution of plants. I developed a quantitative genetics approach that integrates concepts and models from ecological theory. A core assumption of my scientific approach is that the covariations between traits determine plant ecological strategies and the performance of individuals in different environments. From a conceptual point of view, I participated in the clarification and development of the ecophysiological models necessary for the analysis of phenotypic diversity and plasticity. I have also set up a set of experiments, often coupled with a modeling approach, in particular to understand the genetic architecture on trait relationships in different environments. More recently, I developed skills in bioinformatics and population genomics to answer ecological questions at different spatial and temporal scales. With the AraBreed project, I aim to investigate the evolution of ecological strategies with the modern tools of population and ecological genomics available in a model species.
Vasseur, F., Exposito-Alonso, M., Ayala-Garay O., Wang, G., Violle C., Vile D., Weigel, D., 2018. Adaptive diversification of plant allometry in Arabidopsis thaliana. [Accepté dans Proceedings of the National Academy of Sciences, sous presse].
Exposito-Alonso, M., Vasseur, F., Ding, W., Wang, G., Burbano, H. A., Weigel, D., 2018. Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nature ecology & evolution 2(2): 352.
Seymour D.K., Chae E., Grimm D.G., Pizarro C.M., HaringMuller A., Vasseur, F., Rakitsch B., Borgwardt K.M., Koenig D., Weigel D., 2016. The genetic architecture of non-additive inheritance in Arabidopsis thaliana hybrids. Proceedings of the National Academy of Sciences, 113(46): E7317-E7326.
Vasseur, F., Bontpart, T., Dauzat, M., Granier, C., & Vile, D., 2014. Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasting adaptive strategies. Journal of Experimental Botany, 65(22): 6457-6469.
Vasseur, F., Violle C., Enquist B.J., Granier C., Vile D., 2012. A common genetic basis to the origin of the leaf economics spectrum and metabolic scaling allometry. Ecology Letters, 15(10): 1149-1157.