Global environmental change is altering the selection regime for all biota. The key selective factors are altered mean, variance and seasonality of climatic variables and increase in CO(2) concentration itself. We review recent studies that document rapid evolution to global climate change at the phenotypic and genetic level, as a response to shifts in these factors. Among the traits that have changed are photoperiod responses, stress tolerance and traits associated with enhanced dispersal. The genetic basis of two traits with a critical role under climate change, stress tolerance and photoperiod behaviour, is beginning to be understood for model organisms, providing a starting point for candidate gene approaches in targeted nonmodel species. Most studies that have documented evolutionary change are correlative, while selection experiments that manipulate relevant variables are rare. The latter are particularly valuable for prediction because they provide insight into heritable change to simulated future conditions. An important gap is that experimental selection regimes have mostly been testing one variable at a time, while synergistic interactions are likely under global change. The expanding toolbox available to molecular ecologists holds great promise for identifying the genetic basis of many more traits relevant to fitness under global change. Such knowledge, in turn, will significantly advance predictions on global change effects because presence and polymorphism of critical genes can be directly assessed. Moreover, knowledge of the genetic architecture of trait correlations will provide the necessary framework for understanding limits to phenotypic evolution; in particular as lack of critical gene polymorphism or entire pathways, metabolic costs of tolerance and linkage or pleiotropy causing negative trait correlations. Synergism among stressor impacts on organismal function may be causally related to conflict among transcriptomic syndromes specific to stressor types. Because adaptation to changing environment is always contingent upon the spatial distribution of genetic variation, high-resolution estimates of gene flow and hybridization should be used to inform predictions of evolutionary rates.