Beneficial mutations are the driving force of adaptive evolution. In asexual populations, the identification of beneficial alleles is confounded by the presence of genetically linked hitchhiker mutations. Parallel evolution experiments enable the recognition of common targets of selection; yet these targets are inherently enriched for genes of large target size and mutations of large effect. A comprehensive study of individual mutations is necessary to create a realistic picture of the evolutionarily significant spectrum of beneficial mutations. Here we use a bulk-segregant approach to identify the beneficial mutations across 11 lineages of experimentally evolved yeast populations. We report that nearly 80% of detected mutations have no discernible effects on fitness and less than 1% are deleterious. We determine the distribution of driver and hitchhiker mutations in 31 mutational cohorts, groups of mutations that arise synchronously from low frequency and track tightly with one another. Surprisingly, we find that one-third of cohorts lack identifiable driver mutations. In addition, we identify intracohort synergistic epistasis between alleles of hsl7 and kel1, which arose together in a low-frequency lineage.experimental evolution | cohorts | fitness | epistasis A daptation is a fundamental biological process. The identification and characterization of the genetic mechanisms underlying adaptive evolution remains a central challenge in biology. To identify beneficial mutations, recent studies have characterized thousands of first-step mutations and systematic deletion and amplification mutations in the yeast genome (1, 2). These unbiased screens provide a wealth of information regarding the spectrum of beneficial mutations, their fitness effects, and the biological processes under selection. However, this information alone cannot predict which mutations will ultimately succeed in an evolutionary context as genetic interactions and population dynamics also impart substantial influence on the adaptive outcomes.Early theoretical models assume that beneficial mutations are rare, such that once a beneficial mutation escapes drift, it will fix (3-5). For most microbial populations, however, multiple beneficial mutations will arise and spread simultaneously, leading to complex dynamics of clonal interference and genetic hitchhiking (6-9), and in many cases, multiple mutations track tightly with one another through time as mutational cohorts (10-13). The fate of each mutation is therefore dependent not only on its own fitness effect, but on the fitness effects of and interactions between all mutations in the population. Many beneficial mutations will be lost due to drift and clonal interference, whereas many neutral (and even deleterious) mutations will fix by hitchhiking. The influence of clonal interference and genetic hitchhiking on the success of mutations makes it difficult to identify beneficial mutations from sequenced clones or population samples. The extent of genetic hitchhiking and its evolutionary significanc...

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14Beneficial mutations are the driving force of adaptive evolution. In asexual populations, the 15 identification of beneficial alleles is confounded by the presence of genetically-linked hitchhiker 16 mutations. Parallel evolution experiments enable the recognition of common targets of 17 selection, yet these targets are inherently enriched for genes of large target size and mutations 18 of large effect. A comprehensive study of individual mutations is necessary to create a realistic 19 picture of the evolutionarily significant spectrum of beneficial mutations. Here we utilize a bulk-20 segregant approach to identify the beneficial mutations across 11 lineages of experimentally-21 evolved yeast populations. We report that most genome sequence evolution is non-adaptive: 22 nearly 80% of detected mutations have no discernable effects on fitness and less than 1% are 23 deleterious. We determine the distribution of driver and hitchhiker mutations in 31 mutational 24 cohorts, groups of up to ten mutations that arise synchronously from low frequency and track 25 tightly with one another. Surprisingly, we find that one-third of cohorts lack identifiable driver 26 mutations. In addition, we identify intra-cohort synergistic epistasis between mutations in hsl7 27 and kel1, which arose together in a low frequency lineage. 28 29 peer-reviewed)

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