A high-resolution two-step evolution experiment in yeast reveals a shift from pleiotropic to modular adaptation.

Evolution by natural selection is expected to be a slow and gradual process. In particular, the mutations that drive evolution are predicted to be small and modular, incrementally improving a small number of traits. However, adaptive mutations identified early in microbial evolution experiments, cancer, and other systems often provide substantial fitness gains and pleiotropically improve multiple traits at once. We asked whether such pleiotropically adaptive mutations are common throughout adaptation or are instead a rare feature of early steps in evolution that tend to target key signaling pathways. To do so, we conducted barcoded second-step evolution experiments initiated from 5 first-step mutations identified from a prior yeast evolution experiment. We then isolated hundreds of second-step mutations from these evolution experiments, measured their fitness and performance in several growth phases, and conducted whole genome sequencing of the second-step clones. Here, we found that while the vast majority of mutants isolated from the first-step of evolution in this condition show patterns of pleiotropic adaptation-improving both performance in fermentation and respiration growth phases-second-step mutations show a shift towards modular adaptation, mostly improving respiration performance and only rarely improving fermentation performance. We also identified a shift in the molecular basis of adaptation from genes in cellular signaling pathways towards genes involved in respiration and mitochondrial function. Our results suggest that the genes in cellular signaling pathways may be more likely to provide large, adaptively pleiotropic benefits to the organism due to their ability to coherently affect many phenotypes at once. As such, these genes may serve as the source of pleiotropic adaptation in the early stages of evolution, and once these become exhausted, organisms then adapt more gradually, acquiring smaller, more modular mutations.