Our research focuses on theoretical questions in evolutionary and quantitative genetics. We seek to better understand how the genetic characteristics of living systems affect the process of adaptation and how such characteristics may be moulded by evolutionary forces. For instance, we study the evolution of the genotype-phenotype map and the adaptive consequences of gene pleiotropy (multifunctionality) in the context of adaptation to heterogeneous environments. We use both theoretical and experimental approaches. We use experimental evolution and NGS technology with the red flour beetle Tribolium castaneum as our model species to unravel the role and the genetic basis of variation in gene expression in the course of adaptation to novel habitats.
Ecology also plays a role in our research as we are interested in how species respond to rapid environmental changes from an eco-evolutionary point of view, integrating empirical data with computer modelling. We aim at building integrative approaches to help predict species' range evolution under climate and global changes.
Our modelling work is based on Nemo, an individual-based, genetically and spatially explicit simulation platform. Nemo is distributed under the GNU Public License. It can simulate the simultaneous evolution of several traits such as neutral markers, deleterious mutations, and multivariate quantitative traits in a metapopulation framework.
- Evolutionary quantitative genetics of complex traits
- Epistatic pleiotropy and the evolution of the genotype-phenotype map
- Genetic constraints on adaptation and the evolution of species' ranges
- Role of gene expression in adaptation
- Eco-evolutionary dynamics under environmental changes
- Population and quantitative genetics theory
Our research is in the spotlight!
A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming
Olivier Cotto, Johannes Wessely, Damien Georges, Günther Klonner, Max Schmid, Stefan Dullinger, Wilfried Thuiller & Frédéric Guillaume. Nature Communications, 8, 15399, 05 May 2017