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Coton, C.

Publications and source records attributed to Coton, C..

3 recordsLinked to original sources

Propagation of genotypic variation across phenotypic levels: a model based on concave relationships unifies disparate observations on phenotypic buffering, dominance, heritability, and inbreeding depression

The way genetic variation propagates across successive phenotypic levels up to the fitness components is central to the issue of the genotype-phenotype relationship. The processes involved are highly non-linear, and exhibit a large diversity of behaviors depending on the genes, organization levels, and traits considered. Nevertheless, the shape of the relationship between traits from adjacent levels is predominantly concave, which is probably due to global constraints on matter and energy in the cell. Based on this observation, we used the properties of concave functions to model how phenotypic differences and inheritance vary across increasingly integrated levels of organization. We show that the more integrated the phenotypic levels, the closer the phenotypic values and the larger the positive deviation from additivity (i.e. dominance or heterosis). These results may explain various observations such as the low heritability and high inbreeding depression of fitness components, and the phenotypic buffering of molecular polymorphisms. Furthermore, the introduction of a cost/crowding factor in the model may explain why overdominance is so rare while heterosis is so common. To our knowledge, this systems biology approach to the genotype-phenotype relationship is the first to be based on a theoretical model of the propagation of genetic variation across phenotypic levels.

genetics↗

Evolution of enzyme levels in metabolic pathways: A theoretical approach. Part 2

Metabolism is essential for cell function and adaptation. Because of their central role in metabolism, kinetic parameters and enzyme concentrations are under constant selective pressure to adapt the fluxes of the metabolic networks to the needs of the organism. In the line of various studies dealing with enzyme evolution, we recently developed a model of evolution of enzyme concentrations under selection for increased flux, considered as a proxy of fitness (Coton et al. 2021). Taking into account two realistic cellular constraints, competition for resources and co-regulations, we determined the evolutionary equilibria and the ranges of neutral variations of enzyme concentrations. In this article, we give more generality to this model, by considering that the enzymes of a pathway can belong to different groups of co-regulation. We determined the equilibria and showed that the constraints modify the adaptive landscape by limiting the number of independent dimensions. We also showed that any trade-off between enzyme concentration is sufficient to limit the flux and to relax selection for increasing other enzyme concentrations. Even though the model is based on simplifying assumptions, the complexity of the relationship between enzyme concentrations prevents the analysis of selective neutrality.

evolutionary biology↗

Evolution of enzyme levels in metabolic pathways: A theoretical approach

The central role of metabolism in cell functioning and adaptation has given rise to count-less studies on the evolution of enzyme-coding genes and network topology. However, very few studies have addressed the question of how enzyme concentrations change in response to positive selective pressure on the flux, considered a proxy of fitness. In particular, the way cellular constraints, such as resource limitations and co-regulation, affect the adaptive landscape of a pathway under selection has never been analyzed theoretically. To fill this gap, we developed a model of the evolution of enzyme concentrations that combines metabolic control theory and an adaptive dynamics approach, and integrates possible dependencies between enzyme concentrations. We determined the evolutionary equilibria of enzyme concentrations and their range of neutral variation, and showed that they differ with the properties of the enzymes, the constraints applied to the system and the initial enzyme concentrations. Simulations of long-term evolution confirmed all analytical and numerical predictions, even though we relaxed the simplifying assumptions used in the analytical treatment.

evolutionary biology↗