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Grulois, D.

Publications and source records attributed to Grulois, D..

2 recordsLinked to original sources

Plasticity across levels: relating epigenomic, transcriptomic, and phenotypic responses to osmotic stress in a halotolerant microalga

Phenotypic plasticity, the ability of a given genotype to produce alternative phenotypes in response to its environment of development, is an important mechanism for coping with variable environments. While the mechanisms underlying phenotypic plasticity are diverse, their relative contributions need to be investigated quantitatively to better understand the evolvability of plasticity across biological levels. This requires relating plastic responses of the epigenome, transcriptome, and organismal phenotype, and how they vary with the genotype. Here we carried out this approach for responses to osmotic stress in Dunaliella salina, a green microalga that is a model organism for salinity tolerance. We compared two strains that show markedly different demographic responses to osmotic stress, and showed that these phenotypic responses involve strain- and environment-specific variation in gene expression levels, but a relative low - but significant - effect of strain x environment interaction. We also found an important genotype effect on the genome-wide methylation pattern, but little contribution from environmental conditions to the latter. However, we did detect a significant marginal effect of epigenetic variation on gene expression, beyond the influence of genetic differences on epigenetic state, and we showed that hypomethylated regions are correlated with higher gene expression. Our results indicate that epigenetic mechanisms are either not involved in the rapid plastic response to environmental change in this species, or involve only few changes in trans that are sufficient to trigger concerted changes in the expression of many genes, and phenotypic responses by multiple traits.

genomics↗

Predicting population genetic change in an experimental stochastic environment

Most natural environments exhibit a substantial component of random variation. Such environmental noise is expected to cause random fluctuations in natural selection, affecting the predictability of evolution. But despite a long-standing theoretical interest for understanding the population genetic consequences of stochastic environments, there has been a dearth of empirical validation and estimation of the underlying parameters of this theory. Indeed, tracking the genetics of a large number of replicate lines under a controlled level of environmental stochasticity is particularly challenging. Here, we tackled this problem by resorting to an automated experimental evolution approach. We used a liquid-handling robot to expose over a hundred lines of the micro-alga Dunaliella salina to randomly fluctuating salinity over a continuous range, with controlled mean, variance, and autocorrelation. We then tracked the frequency of one of two competing strains through amplicon sequencing of a nuclear and choloroplastic barcode sequences. We show that the magnitude of environmental fluctuations (variance), but also their predictability (autocorrelation), have large impacts on the average selection coefficient. Furthermore, the stochastic variance in population genetic change is substantially higher in a fluctuating environment. Reaction norms of selection coefficients and growth rates of single strains against the environment captured the mean response accurately, but failed to explain the high variance induced by environmental stochasticity. Overall, our results provide exceptional insights on the prospects for understanding and predicting genetic evolution in randomly fluctuating environments.

evolutionary biology↗