Gregory I. Lang

Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations

The dynamics of adaptation determine which mutations fix in a population, and hence how reproducible evolution will be. This is central to understanding the spectra of mutations recovered in the evolution of antibiotic resistance, the response of pathogens to immune selection, and the dynamics of cancer progression. In laboratory evolution experiments, demonstrably beneficial mutations are found repeatedly, but are often accompanied by other mutations with no obvious benefit. Here we use whole-genome whole-population sequencing to examine the dynamics of genome sequence evolution at high temporal resolution in 40 replicate Saccharomyces cerevisiae populations growing in rich medium for 1,000 generations. We find pervasive genetic hitchhiking: multiple mutations arise and move synchronously through the population as mutational ‘cohorts’. Multiple clonal cohorts are often present simultaneously, competing with each other in the same population. Our results show that patterns of sequence evolution are driven by a balance between these chance effects of hitchhiking and interference, which increase stochastic variation in evolutionary outcomes, and the deterministic action of selection on individual mutations, which favours parallel evolutionary solutions in replicate populations.

Estimating the Per-Base-Pair Mutation Rate in the Yeast Saccharomyces cerevisiae

Although mutation rates are a key determinant of the rate of evolution they are difficult to measure precisely and global mutations rates (mutations per genome per generation) are often extrapolated from the per-base-pair mutation rate assuming that mutation rate is uniform across the genome. Using budding yeast, we describe an improved method for the accurate calculation of mutation rates based on the fluctuation assay. Our analysis suggests that the per-base-pair mutation rates at two genes differ significantly (3.80 × 10−10 at URA3 and 6.44 × 10−10 at CAN1) and we propose a definition for the effective target size of genes (the probability that a mutation inactivates the gene) that acknowledges that the mutation rate is nonuniform across the genome.

The cost of gene expression underlies a fitness trade-off in yeast

Natural selection optimizes an organisms genotype within the context of its environment. Adaptations to one environment can decrease fitness in another, revealing evolutionary trade-offs. Here, we show that the cost of gene expression underlies a trade-off between growth rate and mating efficiency in the yeast Saccharomyces cerevisiae. During asexual growth, mutations that eliminate the ability to mate provide an ≈2% per-generation growth-rate advantage. Some strains, including most laboratory strains, carry an allele of GPA1 (an upstream component of the mating pathway) that increases mating efficiency by ≈30% per round of mating at the cost of an ≈1% per-generation growth-rate disadvantage. In addition to demonstrating a trade-off between growth rate and mating efficiency, our results illustrate differences in the selective pressures defining fitness in the laboratory versus the natural environment and show that selection, acting on the cost of gene expression, can optimize expression levels and promote gene loss.

Genetic Variation and the Fate of Beneficial Mutations in Asexual Populations

The fate of a newly arising beneficial mutation depends on many factors, such as the population size and the availability and fitness effects of other mutations that accumulate in the population. It has proved difficult to understand how these factors influence the trajectories of particular mutations, since experiments have primarily focused on characterizing successful clones emerging from a small number of evolving populations. Here, we present the results of a massively parallel experiment designed to measure the full spectrum of possible fates of new beneficial mutations in hundreds of experimental yeast populations, whether these mutations are ultimately successful or not. Using strains in which a particular class of beneficial mutation is detectable by fluorescence, we followed the trajectories of these beneficial mutations across 592 independent populations for 1000 generations. We find that the fitness advantage provided by individual mutations plays a surprisingly small role. Rather, underlying “background” genetic variation is quickly generated in our initially clonal populations and plays a crucial role in determining the fate of each individual beneficial mutation in the evolving population.

Mutation rates across budding yeast chromosome VI are correlated with replication timing.

Previous experimental studies suggest that the mutation rate is nonuniform across the yeast genome. To characterize this variation across the genome more precisely, we measured the mutation rate of the URA3 gene integrated at 43 different locations tiled across Chromosome VI. We show that mutation rate varies 6-fold across a single chromosome, that this variation is correlated with replication timing, and we propose a model to explain this variation that relies on the temporal separation of two processes for replicating past damaged DNA: error-free DNA damage tolerance and translesion synthesis. This model is supported by the observation that eliminating translesion synthesis decreases this variation.

Mutation Rates, Spectra, and Genome-Wide Distribution of Spontaneous Mutations in Mismatch Repair Deficient Yeast

DNA mismatch repair is a highly conserved DNA repair pathway. In humans, germline mutations in hMSH2 or hMLH1, key components of mismatch repair, have been associated with Lynch syndrome, a leading cause of inherited cancer mortality. Current estimates of the mutation rate and the mutational spectra in mismatch repair defective cells are primarily limited to a small number of individual reporter loci. Here we use the yeast Saccharomyces cerevisiae to generate a genome-wide view of the rates, spectra, and distribution of mutation in the absence of mismatch repair. We performed mutation accumulation assays and next generation sequencing on 19 strains, including 16 msh2 missense variants implicated in Lynch cancer syndrome. The mutation rate for DNA mismatch repair null strains was approximately 1 mutation per genome per generation, 225-fold greater than the wild-type rate. The mutations were distributed randomly throughout the genome, independent of replication timing. The mutation spectra included insertions/deletions at homopolymeric runs (87.7%) and at larger microsatellites (5.9%), as well as transitions (4.5%) and transversions (1.9%). Additionally, repeat regions with proximal repeats are more likely to be mutated. A bias toward deletions at homopolymers and insertions at (AT)n microsatellites suggests a different mechanism for mismatch generation at these sites. Interestingly, 5% of the single base pair substitutions might represent double-slippage events that occurred at the junction of immediately adjacent repeats, resulting in a shift in the repeat boundary. These data suggest a closer scrutiny of tumor suppressors with homopolymeric runs with proximal repeats as the potential drivers of oncogenesis in mismatch repair defective cells.

The spectrum of adaptive mutations in experimental evolution.

A primary goal of recent work in experimental evolution is to probe the molecular basis of adaptation. This requires an understanding of the individual mutations in evolving populations: their identity, their physiological and fitness effects, and the interactions between them. The combination of high-throughput methods for laboratory evolution and next-generation sequencing methods now makes it possible to identify and quantify mutations in hundreds of replicate populations over thousands of generations, and to directly measure fitness effects and epistatic interactions. Many laboratories are now leveraging these tools to study the molecular basis of adaptation and the reproducibility of evolutionary outcomes across a variety of model systems. Genetic analyses on evolved populations are shedding light on the statistics of epistasis between evolved mutations. Here we review the current understanding of the spectrum of mutations observed across these systems, with a focus on epistatic interactions between beneficial mutations and constraints on evolutionary outcomes. We emphasize evolution in asexual microbes, where next generation sequencing methods have been widely applied.

A Test of the Coordinated Expression Hypothesis for the Origin and Maintenance of the GAL Cluster in Yeast

Metabolic gene clusters—functionally related and physically clustered genes—are a common feature of some eukaryotic genomes. Two hypotheses have been advanced to explain the origin and maintenance of metabolic gene clusters: coordinated gene expression and genetic linkage. Here we test the hypothesis that selection for coordinated gene expression underlies the clustering of GAL genes in the yeast genome. We find that, although clustering coordinates the expression of GAL1 and GAL10, disrupting the GAL cluster does not impair fitness, suggesting that other mechanisms, such as genetic linkage, drive the origin and maintenance metabolic gene clusters.

Crowded growth leads to the spontaneous evolution of semistable coexistence in laboratory yeast populations

Significance The spontaneous emergence of stable coexistence between competing lineages in experimental evolution illustrates principles behind the creation and maintenance of biodiversity. Here, we present the first experimental observation of a general mechanism that leads to stable diversification in microbial populations despite competition for shared resources. Coexistence in our system depends on a tradeoff between growth and the ability to avoid cellular crowding. We elucidate the biophysical and genetic basis of this coexistence, and introduce a mathematical model that explains our results. Our analysis demonstrates that this coexistence can be perturbed by evolution on longer time scales, providing a unique quantitative example of how the interactions between ecological and evolutionary processes can create and destroy diversity in microbial populations. Identifying the mechanisms that create and maintain biodiversity is a central challenge in biology. Stable diversification of microbial populations often requires the evolution of differences in resource utilization. Alternatively, coexistence can be maintained by specialization to exploit spatial heterogeneity in the environment. Here, we report spontaneous diversification maintained by a related but distinct mechanism: crowding avoidance. During experimental evolution of laboratory Saccharomyces cerevisiae populations, we observed the repeated appearance of “adherent” (A) lineages able to grow as a dispersed film, in contrast to their crowded “bottom-dweller” (B) ancestors. These two types stably coexist because dispersal reduces interference competition for nutrients among kin, at the cost of a slower maximum growth rate. This tradeoff causes the frequencies of the two types to oscillate around equilibrium over the course of repeated cycles of growth, crowding, and dispersal. However, further coevolution of the A and B types can perturb and eventually destroy their coexistence over longer time scales. We introduce a simple mathematical model of this “semistable” coexistence, which explains the interplay between ecological and evolutionary dynamics. Because crowded growth generally limits nutrient access in biofilms, the mechanism we report here may be broadly important in maintaining diversity in these natural environments.

Hitchhiking and epistasis give rise to cohort dynamics in adapting populations

Significance Mutations are the raw material for evolution. However, complex evolutionary dynamics make it challenging to identify which mutations drive adaptation. During adaptation in asexual populations, multiple mutations move synchronously through the population as mutational cohorts. Here we quantify the fitness effect of 116 mutations from 11 laboratory-evolved yeast populations. We show that only a fraction of genome evolution is strongly adaptive. We map driver and hitchhiker mutations to 31 mutational cohorts, and we identify 1 cohort in which mutations combine to provide a fitness benefit greater than the sum of their individual effects. Our analysis uncovers the roles of genetic hitchhiking and epistasis in determining which mutations ultimately succeed or fail in the context of a rapidly evolving microbial population. 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.