Showing papers by "Arnaud Le Rouzic published in 2023"

Detecting directional epistasis and dominance from cross-line analyses in Alpine populations of Arabidopsis thaliana

Abstract: The contribution of non-additive genetic effects in general, and to the evolutionary potential of populations in particular, is a topic of long-standing theoretical and empirical interest, which nevertheless remains controversial. As a consequence, the empirical study of these effects in natural populations remains scarce, which is problematic because non-additive effects are expected to modify both the adaptive potential of populations and the way we should measure it. In this study, we explored the contribution of dominance and epistasis in natural Alpine populations of Arabidopsis thaliana, for two fitness-related traits, the dry weight and the number of siliques. We first found that, on average, crosses between inbred lines of A. thaliana led to heterosis for the dry weight, but outbreeding depression for the number of siliques. We found that heterosis for the dry weight was due to positive directional dominance. For the number of siliques, however, we found that outbreeding depression was due to the breakdown of positive directional epistasis. The implication of these results for the adaptive potential of the studied populations, as well as the use of line-cross analyses to detect directional non-additive genetic effects, are discussed.

Correlated stabilizing selection shapes the topology of gene regulatory networks

Abstract: The evolution of gene expression is constrained by the topology of gene regulatory networks, as co-expressed genes are likely to have their expressions affected together by mutations. Conversely, co-expression can also be an advantage when genes are under joint selection. Here, we assessed theoretically whether correlated selection (selection for a combination of traits) was able to affect the pattern of correlated gene expressions and the underlying gene regulatory networks. We ran individual-based simulations, applying a stabilizing correlated fitness function to three genetic architectures: a quantitative genetics (multilinear) model featuring epistasis and pleiotropy, a quantitative genetics model where each genes has an independent mutational structure, and a gene regulatory model, mimicking the mechanisms of gene expression regulation. Simulations showed that correlated mutational effects evolved in the three genetic architectures as a response to correlated selection, but the response in gene networks was specific. The intensity of gene co-expression was mostly explained by the regulatory distance between genes (largest correlations being associated to genes directly interacting with each other), and the sign of co-expression was associated with the nature of the regulation (transcription activation or inhibition). These results concur to the idea that gene network topologies could partly reflects past correlated selection patterns on gene expression.