Orateur
Summary
Through the non-genetic heterogeneity it confers, stochasticity (or ‘noise’) in gene expression has been implicated in a wide range of biological phenomena, playing an active role in differentiation, appearance of cellular resistance to toxic molecules or stress, adaptability in fluctuating environments. The hypothesis of stochastic gene expression as a major source of phenotypic diversification important for population dynamics and evolution is now widely accepted. Moreover, recent works have shown how selection influences phenotypic fluctuations in evolutionary experiments. In these experiments, increase in phenotypic fluctuation through noise in gene expression is clearly a relevant evolutionary strategy. Using yeast as an experimental model, several hypotheses concerning the adaptation of industrial strains (versus laboratory strains) to stressful environments will be presented. Moreover, innovative theoretical works on the links between variability in gene expression and genetic variability will be discussed. In particular, the hypothesis of noise-driven heterogeneity in the rate of genetic-variant generation (RGVG) as a basis for evolvability provides opportunities to apply in silico experiments using multi-agent simulation to improve the model. By modulating environmental constraints on the agents, such simulations might provide indications on variations of the RGVG strictly driven by heterogeneity in the expression of DNA repair and maintenance genes and selection.