Beyond single-trait GxE: higher-order environmental interactions and clonal diversity govern trait relationships in yeast
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Predicting organismal responses to complex ecological change requires understanding how multiple environmental stressors (E) and genetic background (G) interact on phenotypic variation (P). Here, we investigate how temperature (E T ) and salinity (E S ) shape growth (P G ) and flocculation (P F ) in multiple strains of the fission yeast, Schizosaccharomyces pombe . We find that environmental interactions are critical, with the effect of temperature on flocculation being inverted by changes in salinity (P∼E×E). Multi-stress reaction norms are genotype-dependent (P∼G×E×E), revealing that evolution can adopt diverse strategies to deal with E×E interactions. We further show that the covariation between traits (P×P) is itself a plastic and evolvable feature. The relationship between growth and flocculation changed from negative to positive or completely uncoupled, depending on the specific G×E×E context. This context-dependent covariation suggests that clonal variability and stochastic processes modulate phenotypic outcomes beyond deterministic genotypic effects. Our findings demonstrate that higher-order interactions govern not only individual traits but also their interrelationships, highlighting the necessity of integrating G×E×E effects and phenotypic covariation into models of adaptation.
Significance Statement
Predicting how organisms respond to environmental change is one of biology’s most urgent challenges. While most studies examine single environmental stressors or traits, natural systems simultaneously expose populations to multiple interacting stressors. Using fission yeast as a model, we demonstrate that higher-order interactions among temperature, salinity, and genetic background influence not only individual traits, such as growth and flocculation, but also their correlations. Remarkably, even genetically near-identical populations displayed divergent trait relationships depending on environmental context, revealing a role for clonal variability and stochasticity in adaptation. These findings demonstrate that evolutionary outcomes cannot be understood by studying traits in isolation, but require integrating multi-stressor interactions and trait covariation into predictive models of adaptation.
