Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations

A universally applicable definition for domestication

The process of domestication is commonly perceived as a human achievement, and domestic species are typically assumed to be those under human control. Domestic species have emerged from a greater diversity of interactions than this perspective allows, and none of the many definitions proposed for domestication can readily, reliably, and consistently distinguish domestic and nondomestic populations. Here, we propose that the process of domestication should instead be defined solely as evolution of a nonhuman population in response to an anthropogenic niche and that a domestic population is one that cannot sustain itself outside of an anthropogenic niche. As a result, this definition does not require comparisons with a presumed and largely unobservable ancestor. Instead, it focuses on the observable relationship between a nonhuman population and humans. It also avoids making assumptions about how domestication happens, thus enabling an exploration of the mechanisms underlying the process of adaptation to an anthropogenic niche. By applying this definition to plants, animals, and microbes, we illustrate its utility for investigating the evolution of the relationship between humans and other species and for anticipating which species are likely to survive in an increasingly human-influenced world. Domestication is simply an evolutionary process resulting from the interaction between two species, one of which is human. As we work to protect Earth's biodiversity, this definition allows us to understand why, in response to the conditions human societies create, some species survive and thrive, while others struggle and go extinct.

Resource presentation dictates genetic and phenotypic adaptation in yeast

BACKGROUND

Environments shape adaptive trajectories of populations, often leading to adaptive parallelism in identical, and divergence in different environments. However, how does the likelihood of these possibilities change with minute changes in the environment remain unclear.

RESULTS

In this study, we evolved Saccharomyces cerevisiae in environments which differed only in the manner in which the sugar source is presented to the population. In one set of populations, carbon was presented as a mixture of glucose-galactose, and in the other, as melibiose, a glucose-galactose disaccharide. Since the two environments differed in how the two monosaccharides are packaged, we call these environments 'synonymous'. Our results show that even subtle environmental differences can lead to differing phenotypic responses between the two sets of evolved populations. However, despite different adaptive responses, pleiotropic effects of adaptation are largely predictable. We also show that distinct genomic targets of adaptation between the two sets of evolved populations are functionally convergent.

CONCLUSION

This study highlights how subtle environmental differences dictate phenotypic and genetic adaptation of populations. Additionally, these results also suggest the predictive potential of ancestor's fitness in understanding pleiotropic responses. Our work underscores the importance of studying more such environments to understand the generality of adaptive responses in populations.

Metabolic remodeling and de novo mutations transcend cryptic variation as drivers of adaptation in yeast

Many organisms live in predictable environments with periodic variations in growth conditions. Adaptation to these conditions can lead to loss of nonessential functions, which could be maladaptive in new environments. Alternatively, living in a predictable environment can allow populations to accumulate cryptic genetic variation that may have no fitness benefit in that condition, but can facilitate adaptation to new environments. However, how these processes together shape the fitness of populations growing in predictable environments remains unclear. Through laboratory evolution experiments in yeast, we show that populations grown in a nutrient-rich environment for 1,000 generations generally have reduced fitness and lower adaptability to novel stressful environments. These populations showed metabolic remodeling and increased lipid accumulation in rich medium which seemed to provide osmotic protection in salt stress. Subsequent adaptation to stressors was primarily driven by de novo mutations, with very little contribution from the mutations accumulated prior to the exposure. Thus, our work suggests that without exposure to new environments, populations might lose their ability to respond effectively to these environments. Furthermore, our findings highlight a major role of exaptation and de novo mutations in adaptation to new environments but do not reveal a significant contribution of cryptic variation in this process.

The dynamics of loss of heterozygosity events in genomes

Genomic instability is a hallmark of tumorigenesis, yet it also plays an essential role in evolution. Large-scale population genomics studies have highlighted the importance of loss of heterozygosity (LOH) events, which have long been overlooked in the context of genetic diversity and instability. Among various types of genomic mutations, LOH events are the most common and affect a larger portion of the genome. They typically arise from recombination-mediated repair of double-strand breaks (DSBs) or from lesions that are processed into DSBs. LOH events are critical drivers of genetic diversity, enabling rapid phenotypic variation and contributing to tumorigenesis. Understanding the accumulation of LOH, along with its underlying mechanisms, distribution, and phenotypic consequences, is therefore crucial. In this review, we explore the spectrum of LOH events, their mechanisms, and their impact on fitness and phenotype, drawing insights from Saccharomyces cerevisiae to cancer. We also emphasize the role of LOH in genomic instability, disease, and genome evolution.

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.

Hybrid adaptation is hampered by Haldane's sieve

Hybrids between species exhibit plastic genomic architectures that could foster or slow down their adaptation. When challenged to evolve in an environment containing a UV mimetic drug, yeast hybrids have reduced adaptation rates compared to parents. We find that hybrids and their parents converge onto similar molecular mechanisms of adaptation by mutations in pleiotropic transcription factors, but at a different pace. After 100 generations, mutations in these genes tend to be homozygous in the parents but heterozygous in the hybrids. We hypothesize that a lower rate of loss of heterozygosity (LOH) in hybrids could limit fitness gain. Using genome editing, we first demonstrate that mutations display incomplete dominance, requiring homozygosity to show full impact and to entirely circumvent Haldane's sieve, which favors the fixation of dominant mutations. Second, tracking mutations in earlier generations confirmed a different rate of LOH in hybrids. Together, these findings show that Haldane's sieve slows down adaptation in hybrids, revealing an intrinsic constraint of hybrid genomic architecture that can limit the role of hybridization in adaptive evolution.

Progressive transcriptomic shifts in evolved yeast strains following gene knockout

Gene knockout disrupts cellular homeostasis, altering gene expression, and phenotypes. We investigated whether cells return to their pre-knockout transcriptomic state through adaptive evolution experiments on hap4Δ and ade1Δ yeast strains. Analysis revealed that genes with higher expression levels and more physical interaction partners in wild-type strains were more likely to be restored, suggesting that genes of significant functional importance have increased resilience to genetic perturbations. However, as the experiment progressed, most initially restored genes became unrestored. Over 60% of differentially expressed genes in knockout strains remained unrestored in evolved strains. Evolved strains exhibited distinct transcriptomic states, diverging from the original strain over time. Ribosome biogenesis components exhibited systematic sequential changes during the evolution. Our findings suggest the knockout strain transcriptomes struggle to return to the original state even after 28 days of culture. Instead, compensatory mechanisms lead to distinct suboptimal states, highlighting the complex transcriptomic dynamics following genetic perturbations.

Evolution of evolvability in rapidly adapting populations

Mutations can alter the short-term fitness of an organism, as well as the rates and benefits of future mutations. While numerous examples of these evolvability modifiers have been observed in rapidly adapting microbial populations, existing theory struggles to predict when they will be favoured by natural selection. Here we develop a mathematical framework for predicting the fates of genetic variants that modify the rates and benefits of future mutations in linked genomic regions. We derive analytical expressions showing how the fixation probabilities of these variants depend on the size of the population and the diversity of competing mutations. We find that competition between linked mutations can dramatically enhance selection for modifiers that increase the benefits of future mutations, even when they impose a strong direct cost on fitness. However, we also find that modest direct benefits can be sufficient to drive evolutionary dead ends to fixation. Our results suggest that subtle differences in evolvability could play an important role in shaping the long-term success of genetic variants in rapidly evolving microbial populations.

Limited population structure but signals of recent selection in introduced African Fig Fly (Zaprionus indianus) in North America

Invasive species have devastating consequences for human health, food security, and the environment. Many invasive species adapt to new ecological niches following invasion, but little is known about the early steps of adaptation. Here we examine population genomics of a recently introduced drosophilid in North America, the African Fig Fly, Zaprionus indianus. This species is likely intolerant of subfreezing temperatures and recolonizes temperate environments yearly. We generated a new chromosome-level genome assembly for Z. indianus. Using resequencing of over 200 North American individuals collected over four years in temperate Virginia, plus a single collection from subtropical Florida, we tested for signatures of recolonization, population structure, and adaptation within invasive populations. We show founding populations are sometimes small and contain close genetic relatives, yet temporal population structure and differentiation of populations is mostly absent across recurrent recolonization events. Although we find limited signals of genome-wide spatial or temporal population structure, we identify haplotypes on the X chromosome that are repeatedly differentiated between Virginia and Florida populations. These haplotypes show signatures of natural selection and are not found in African populations. We also find evidence for several large structural polymorphisms segregating within North America populations and show X chromosome evolution in invasive populations is strikingly different from the autosomes. These results show that despite limited population structure, populations may rapidly evolve genetic differences early in an invasion. Further uncovering how these genomic regions influence invasive potential and success in new environments will advance our understanding of how organisms evolve in changing environments.

Synthetic gene circuit evolution: Insights and opportunities at the mid-scale

Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.

Candida albicans' inorganic phosphate transport and evolutionary adaptation to phosphate scarcity

Phosphorus is essential in all cells' structural, metabolic and regulatory functions. For fungal cells that import inorganic phosphate (Pi) up a steep concentration gradient, surface Pi transporters are critical capacitators of growth. Fungi must deploy Pi transporters that enable optimal Pi uptake in pH and Pi concentration ranges prevalent in their environments. Single, triple and quadruple mutants were used to characterize the four Pi transporters we identified for the human fungal pathogen Candida albicans, which must adapt to alkaline conditions during invasion of the host bloodstream and deep organs. A high-affinity Pi transporter, Pho84, was most efficient across the widest pH range while another, Pho89, showed high-affinity characteristics only within one pH unit of neutral. Two low-affinity Pi transporters, Pho87 and Fgr2, were active only in acidic conditions. Only Pho84 among the Pi transporters was clearly required in previously identified Pi-related functions including Target of Rapamycin Complex 1 signaling, oxidative stress resistance and hyphal growth. We used in vitro evolution and whole genome sequencing as an unbiased forward genetic approach to probe adaptation to prolonged Pi scarcity of two quadruple mutant lineages lacking all 4 Pi transporters. Lineage-specific genomic changes corresponded to divergent success of the two lineages in fitness recovery during Pi limitation. Initial, large-scale genomic alterations like aneuploidies and loss of heterozygosity eventually resolved, as populations gained small-scale mutations. Severity of some phenotypes linked to Pi starvation, like cell wall stress hypersensitivity, decreased in parallel to evolving populations' fitness recovery in Pi scarcity, while severity of others like membrane stress responses diverged from Pi scarcity fitness. Among preliminary candidate genes for contributors to fitness recovery, those with links to TORC1 were overrepresented. Since Pi homeostasis differs substantially between fungi and humans, adaptive processes to Pi deprivation may harbor small-molecule targets that impact fungal growth, stress resistance and virulence.

The loci of environmental adaptation in a model eukaryote

While the underlying genetic changes have been uncovered in some cases of adaptive evolution, the lack of a systematic study prevents a general understanding of the genomic basis of adaptation. For example, it is unclear whether protein-coding or noncoding mutations are more important to adaptive evolution and whether adaptations to different environments are brought by genetic changes distributed in diverse genes and biological processes or concentrated in a core set. We here perform laboratory evolution of 3360 Saccharomyces cerevisiae populations in 252 environments of varying levels of stress. We find the yeast adaptations to be primarily fueled by large-effect coding mutations overrepresented in a relatively small gene set, despite prevalent antagonistic pleiotropy across environments. Populations generally adapt faster in more stressful environments, partly because of greater benefits of the same mutations in more stressful environments. These and other findings from this model eukaryote help unravel the genomic principles of environmental adaptation.

A morphological basis for path-dependent evolution of visual systems

Path dependence influences macroevolutionary predictability by constraining potential outcomes after critical evolutionary junctions. Although it has been demonstrated in laboratory experiments, path dependence is difficult to demonstrate in natural systems because of a lack of independent replicates. Here, we show that two types of distributed visual systems recently evolved twice within chitons, demonstrating rapid and path-dependent evolution of a complex trait. The type of visual system that a chiton lineage can evolve is constrained by the number of openings for sensory nerves in its shell plates. Lineages with more openings evolve visual systems with thousands of eyespots, whereas those with fewer openings evolve visual systems with hundreds of shell eyes. These macroevolutionary outcomes shaped by path dependence are both deterministic and stochastic because possibilities are restricted yet not entirely predictable.

Estimating the Lambda measure in multiple-merger coalescents

Multiple-merger coalescents, also known as Λ-coalescents, have been used to describe the genealogy of populations that have a skewed offspring distribution or that undergo strong selection. Inferring the characteristic measure Λ, which describes the rates of the multiple-merger events, is key to understand these processes. So far, most inference methods only work for some particular families of Λ-coalescents that are described by only one parameter, but not for more general models. This article is devoted to the construction of a non-parametric estimator of the density of Λ that is based on the observation at a single time of the so-called Site Frequency Spectrum (SFS), which describes the allelic frequencies in a present population sample. First, we produce estimates of the multiple-merger rates by solving a linear system, whose coefficients are obtained by appropriately subsampling the SFS. Then, we use a technique that aggregates the information extracted from the previous step through a kernel type of re-construction to give a non-parametric estimation of the measure Λ. We give a consistency result of this estimator under mild conditions on the behavior of Λ around 0. We also show some numerical examples of how our method performs.

Ploidy evolution in a wild yeast is linked to an interaction between cell type and metabolism

Ploidy is an evolutionarily labile trait, and its variation across the tree of life has profound impacts on evolutionary trajectories and life histories. The immediate consequences and molecular causes of ploidy variation on organismal fitness are frequently less clear, although extreme mating type skews in some fungi hint at links between cell type and adaptive traits. Here, we report an unusual recurrent ploidy reduction in replicate populations of the budding yeast Saccharomyces eubayanus experimentally evolved for improvement of a key metabolic trait, the ability to use maltose as a carbon source. We find that haploids have a substantial, but conditional, fitness advantage in the absence of other genetic variation. Using engineered genotypes that decouple the effects of ploidy and cell type, we show that increased fitness is primarily due to the distinct transcriptional program deployed by haploid-like cell types, with a significant but smaller contribution from absolute ploidy. The link between cell-type specification and the carbon metabolism adaptation can be traced to the noncanonical regulation of a maltose transporter by a haploid-specific gene. This study provides novel mechanistic insight into the molecular basis of an environment-cell type fitness interaction and illustrates how selection on traits unexpectedly linked to ploidy states or cell types can drive karyotypic evolution in fungi.

Evolutionary consequences of nascent multicellular life cycles

A key step in the evolutionary transition to multicellularity is the origin of multicellular groups as biological individuals capable of adaptation. Comparative work, supported by theory, suggests clonal development should facilitate this transition, although this hypothesis has never been tested in a single model system. We evolved 20 replicate populations of otherwise isogenic clonally reproducing 'snowflake' yeast (Δace2/∆ace2) and aggregative 'floc' yeast (GAL1p::FLO1 /GAL1p::FLO1) with daily selection for rapid growth in liquid media, which favors faster cell division, followed by selection for rapid sedimentation, which favors larger multicellular groups. While both genotypes adapted to this regime, growing faster and having higher survival during the group-selection phase, there was a stark difference in evolutionary dynamics. Aggregative floc yeast obtained nearly all their increased fitness from faster growth, not improved group survival; indicating that selection acted primarily at the level of cells. In contrast, clonal snowflake yeast mainly benefited from higher group-dependent fitness, indicating a shift in the level of Darwinian individuality from cells to groups. Through genome sequencing and mathematical modeling, we show that the genetic bottlenecks in a clonal life cycle also drive much higher rates of genetic drift-a result with complex implications for this evolutionary transition. Our results highlight the central role that early multicellular life cycles play in the process of multicellular adaptation.

Species and condition shape the mutational spectrum in experimentally evolved biofilms

IMPORTANCE

Biofilm formation is a vital factor for the survival and adaptation of bacteria in diverse environmental niches. Experimental evolution combined with the advancement of whole-population genome sequencing provides us a powerful tool to understand the genomic dynamic of evolutionary adaptation to different environments, such as during biofilm development. Previous studies described the genetic and phenotypic changes of selected clones from experimentally evolved Bacillus thuringiensis and Bacillus subtilis that were adapted under abiotic and biotic biofilm conditions. However, the full understanding of the dynamic evolutionary landscapes was lacking. Furthermore, the differences and similarities of adaptive mechanisms in B. thuringiensis and B. subtilis were not identified. To overcome these limitations, we performed longitudinal whole-population genome sequencing to study the underlying genetic dynamics at high resolution. Our study provides the first comprehensive mutational landscape of two bacterial species' biofilms that is adapted to an abiotic and biotic surface.

Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

Evolution of a minimal cell

Possessing only essential genes, a minimal cell can reveal mechanisms and processes that are critical for the persistence and stability of life1,2. Here we report on how an engineered minimal cell3,4 contends with the forces of evolution compared with the Mycoplasma mycoides non-minimal cell from which it was synthetically derived. Mutation rates were the highest among all reported bacteria, but were not affected by genome minimization. Genome streamlining was costly, leading to a decrease in fitness of greater than 50%, but this deficit was regained during 2,000 generations of evolution. Despite selection acting on distinct genetic targets, increases in the maximum growth rate of the synthetic cells were comparable. Moreover, when performance was assessed by relative fitness, the minimal cell evolved 39% faster than the non-minimal cell. The only apparent constraint involved the evolution of cell size. The size of the non-minimal cell increased by 80%, whereas the minimal cell remained the same. This pattern reflected epistatic effects of mutations in ftsZ, which encodes a tubulin-homologue protein that regulates cell division and morphology5,6. Our findings demonstrate that natural selection can rapidly increase the fitness of one of the simplest autonomously growing organisms. Understanding how species with small genomes overcome evolutionary challenges provides critical insights into the persistence of host-associated endosymbionts, the stability of streamlined chassis for biotechnology and the targeted refinement of synthetically engineered cells2,7-9.

Dynamics of Podospora anserina Genome Evolution in a Long-Term Experiment

The Podospora anserina long-term evolution experiment (PaLTEE) is the only running filamentous fungus study, which is still going on. The aim of our work is to trace the evolutionary dynamics of the accumulation of mutations in the genomes of eight haploid populations of P. anserina. The results of the genome-wide analysis of all of the lineages, performed 8 years after the start of the PaLTEE, are presented. Data analysis detected 312 single nucleotide polymorphisms (SNPs) and 39 short insertion-deletion mutations (indels) in total. There was a clear trend towards a linear increase in the number of SNPs depending on the experiment duration. Among 312 SNPs, 153 were fixed in the coding regions of P. anserina genome. Relatively few synonymous mutations were found, exactly 38; 42 were classified as nonsense mutations; 72 were assigned to missense mutations. In addition, 21 out of 39 indels identified were also localized in coding regions. Here, we also report the detection of parallel evolution at the paralog level in the P. anserina model system. Parallelism in evolution at the level of protein functions also occurs. The latter is especially true for various transcription factors, which may indicate selection leading to optimization of the wide range of cellular processes under experimental conditions.

A Comparison of Methods to Estimate Additive-by-Additive-by-Additive of QTL×QTL×QTL Interaction Effects by Monte Carlo Simulation Studies

The goal of the breeding process is to obtain new genotypes with traits improved over the parental forms. Parameters related to the additive effect of genes as well as their interactions (such as epistasis of gene-by-gene interaction effect and additive-by-additive-by-additive of gene-by-gene-by-gene interaction effect) can influence decisions on the suitability of breeding material for this purpose. Understanding the genetic architecture of complex traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-by-QTL interactions and QTL-by-QTL-by-QTL interactions. With regards to the comparing methods for estimating additive-by-additive-by-additive of QTL×QTL×QTL interaction effects by Monte Carlo simulation studies, there are no publications in the open literature. The parameter combinations assumed in the presented simulation studies represented 84 different experimental situations. The use of weighted regression may be the preferred method for estimating additive-by-additive-by-additive of QTL-QTL-QTL triples interaction effects, as it provides results closer to the true values of total additive-by-additive-by-additive interaction effects than using unweighted regression. This is also indicated by the obtained values of the determination coefficients of the proposed models.

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

Revisiting the Design of the Long-Term Evolution Experiment with Escherichia coli

The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.

Identifying Targets of Selection in Laboratory Evolution Experiments

Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.

Evolutionary repeatability of emergent properties of ecological communities

Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Long-Term Adaptation to Galactose as a Sole Carbon Source Selects for Mutations Outside the Canonical GAL Pathway

Galactose is a secondary fermentable sugar that requires specific regulatory and structural genes for its assimilation, which are under catabolite repression by glucose. When glucose is absent, the catabolic repression is attenuated, and the structural GAL genes are fully activated. In Saccharomyces cerevisiae, the GAL pathway is under selection in environments where galactose is present. However, it is unclear the adaptive strategies in response to long-term propagation in galactose as a sole carbon source in laboratory evolution experiments. Here, we performed a 4,000-generation evolution experiment using 48 diploid Saccharomyces cerevisiae populations to study adaptation in galactose. We show that fitness gains were greater in the galactose-evolved population than in identically evolved populations with glucose as a sole carbon source. Whole-genome sequencing of 96 evolved clones revealed recurrent de novo single nucleotide mutations in candidate targets of selection, copy number variations, and ploidy changes. We find that most mutations that improve fitness in galactose lie outside of the canonical GAL pathway. Reconstruction of specific evolved alleles in candidate target of selection, SEC23 and IRA1, showed a significant increase in fitness in galactose compared to glucose. In addition, most of our evolved populations (28/46; 61%) fixed aneuploidies on Chromosome VIII, suggesting a parallel adaptive amplification. Finally, we show greater loss of extrachromosomal elements in our glucose-evolved lineages compared with previous glucose evolution. Broadly, these data further our understanding of the evolutionary pressures that drive adaptation to less-preferred carbon sources.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

Experimental test of the contributions of initial variation and new mutations to adaptive evolution in a novel environment

Experimental evolution is an approach that allows researchers to study organisms as they evolve in controlled environments. Despite the growing popularity of this approach, there are conceptual gaps among projects that use different experimental designs. One such gap concerns the contributions to adaptation of genetic variation present at the start of an experiment and that of new mutations that arise during an experiment. The primary source of genetic variation has historically depended largely on the study organisms. In the long-term evolution experiment (LTEE) using Escherichia coli, for example, each population started from a single haploid cell, and therefore, adaptation depended entirely on new mutations. Most other microbial evolution experiments have followed the same strategy. By contrast, evolution experiments using multicellular, sexually reproducing organisms typically start with preexisting variation that fuels the response to selection. New mutations may also come into play in later generations of these experiments, but it is generally difficult to quantify their contribution in these studies. Here, we performed an experiment using E. coli to compare the contributions of initial genetic variation and new mutations to adaptation in a new environment. Our experiment had four treatments that varied in their starting diversity, with 18 populations in each treatment. One treatment depended entirely on new mutations, while the other three began with mixtures of clones, whole-population samples, or mixtures of whole-population samples from the LTEE. We tracked a genetic marker associated with different founders in two treatments. These data revealed significant variation in fitness among the founders, and that variation impacted evolution in the early generations of our experiment. However, there were no differences in fitness among the treatments after 500 or 2,000 generations in the new environment, despite the variation in fitness among the founders. These results indicate that new mutations quickly dominated, and eventually they contributed more to adaptation than did the initial variation. Our study thus shows that preexisting genetic variation can have a strong impact on early evolution in a new environment, but new beneficial mutations may contribute more to later evolution and can even drive some initially beneficial variants to extinction.

Loss-of-function mutation survey revealed that genes with background-dependent fitness are rare and functionally related in yeast

In different individuals, the same mutation can lead to different phenotypes due to genetic background effects. This is commonly observed in various systems, including many human diseases. While isolated examples of such background effects have been observed, a systematic view across a large number of individuals is still lacking. Here, we surveyed genetic background effects associated with gene loss-of-function mutations across a population of natural isolates of the yeast Saccharomyces cerevisiae. We found that ∼15% of genes can display a background-dependent fitness change. Genes related to mitochondrial functions are significantly overrepresented, and showed reversed patterns of fitness gain or loss with genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport, suggesting a potential functional rewiring.

In natural populations, the same mutation can lead to different phenotypic outcomes due to the genetic variation that exists among individuals. Such genetic background effects are commonly observed, including in the context of many human diseases. However, systematic characterization of these effects at the species level is still lacking to date. Here, we sought to comprehensively survey background-dependent traits associated with gene loss-of-function (LoF) mutations in 39 natural isolates of Saccharomyces cerevisiae using a transposon saturation strategy. By analyzing the modeled fitness variability of a total of 4,469 genes, we found that 15% of them, when impacted by a LoF mutation, exhibited a significant gain- or loss-of-fitness phenotype in certain natural isolates compared with the reference strain S288C. Out of these 632 genes with predicted background-dependent fitness effects, around 2/3 impact multiple backgrounds with a gradient of predicted fitness change while 1/3 are specific to a single genetic background. Genes related to mitochondrial function are significantly overrepresented in the set of genes showing a continuous variation and display a potential functional rewiring with other genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport. Such rewiring effects are likely modulated by both the genetic background and the environment. While background-specific cases are rare and span diverse cellular processes, they can be functionally related at the individual level. All genes with background-dependent fitness effects tend to have an intermediate connectivity in the global genetic interaction network and have shown relaxed selection pressure at the population level, highlighting their potential evolutionary characteristics.

Adaptation to novel spatially-structured environments is driven by the capsule and alters virulence-associated traits

The extracellular capsule is a major virulence factor, but its ubiquity in free-living bacteria with large environmental breadths suggests that it shapes adaptation to novel niches. Yet, how it does so, remains unexplored. Here, we evolve three Klebsiella strains and their capsule mutants in parallel. Their comparison reveals different phenotypic and genotypic evolutionary changes that alter virulence-associated traits. Non-capsulated populations accumulate mutations that reduce exopolysaccharide production and increase biofilm formation and yield, whereas most capsulated populations become hypermucoviscous, a signature of hypervirulence. Hence, adaptation to novel environments primarily occurs by fine-tuning expression of the capsular locus. The same evolutionary conditions selecting for mutations in the capsular gene wzc leading to hypermucoviscosity also result in increased susceptibility to antibiotics by mutations in the ramA regulon. This implies that general adaptive processes outside the host can affect capsule evolution and its role in virulence and infection outcomes may be a by-product of such adaptation.

Phenotypic and genotypic evolution in worrisome Klebsiella spp. is influenced by the capsule. Here the authors show that adaptation outside the host can impact virulence-associated traits, including de novo emergence of hypermucoviscosity.

Population genetics of clonally transmissible cancers

Populations of cancer cells are subject to the same core evolutionary processes as asexually reproducing, unicellular organisms. Transmissible cancers are particularly striking examples of these processes. These unusual cancers are clonal lineages that can spread through populations via physical transfer of living cancer cells from one host individual to another, and they have achieved long-term success in the colonization of at least eight different host species. Population genetic theory provides a useful framework for understanding the shift from a multicellular sexual animal into a unicellular asexual clone and its long-term effects on the genomes of these cancers. In this Review, we consider recent findings from transmissible cancer research with the goals of developing an evolutionarily informed perspective on transmissible cancers, examining possible implications for their long-term fate and identifying areas for future research on these exceptional lineages.

Mutational robustness changes during long-term adaptation in laboratory budding yeast populations

As an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8000–10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from differences in the relative frequency of certain patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.

Microbial experimental evolution in a massively multiplexed and high-throughput era

Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.

Overdominant and partially dominant mutations drive clonal adaptation in diploid Saccharomyces cerevisiae

Identification of adaptive targets in experimental evolution typically relies on extensive replication and genetic reconstruction. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of evolved mutations. Here, we apply this method to six Saccharomyces cerevisiae clones isolated from four diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains 17-26 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of the evolved clones to a barcoded haploid version of the ancestor. We competed the resulting barcoded diploids en masse and quantified fitness in the experimental and alternative environments by barcode sequencing. We estimated average fitness effects of evolved mutations using barcode-based fitness assays and whole genome sequencing for a subset of segregants. In contrast to our previous work with haploid evolved clones, we find that diploids carry fewer beneficial mutations, with modest fitness effects (up to 5.4%) in the environment in which they arose. In agreement with theoretical expectations, reconstruction experiments show that all mutations with a detectable fitness effect manifest some degree of dominance over the ancestral allele, and most are overdominant. Genotypes with lower fitness effects in alternative environments allowed us to identify conditions that drive adaptation in our system.

How adaptive laboratory evolution can boost yeast tolerance to lignocellulosic hydrolyses

The yeast Saccharomyces cerevisiae is an excellent candidate for establishing cell factories to convert lignocellulosic biomass into chemicals and fuels. To enable this technology, yeast robustness must be improved to withstand the fermentation inhibitors (e.g., weak organic acids, phenols, and furan aldehydes) resulting from biomass pretreatment and hydrolysis. Here, we discuss how evolution experiments performed in the lab, a method commonly known as adaptive laboratory evolution (ALE), may contribute to lifting yeast tolerance against the inhibitors of lignocellulosic hydrolysates (LCHs). The key is that, through the combination of whole-genome sequencing and reverse engineering, ALE provides a robust platform for discovering and testing adaptive alleles, allowing to explore the genetic underpinnings of yeast responses to LCHs. We review the insights gained from past evolution experiments with S. cerevisiae in LCH inhibitors and propose experimental designs to optimise the discovery of genetic variants adaptive to biomass toxicity. The knowledge gathered through ALE projects is envisaged as a roadmap to engineer superior yeast strains for biomass-based bioprocesses.

Increased Pathogenicity of the Nematophagous Fungus Drechmeria coniospora Following Long-Term Laboratory Culture

Domestication provides a window into adaptive change. Over the course of 2 decades of laboratory culture, a strain of the nematode-specific fungus Drechmeria coniospora became more virulent during its infection of Caenorhabditis elegans. Through a close comparative examination of the genome sequences of the original strain and its more pathogenic derivative, we identified a small number of non-synonymous mutations in protein-coding genes. In one case, the mutation was predicted to affect a gene involved in hypoxia resistance and we provide direct corroborative evidence for such an effect. The mutated genes with functional annotation were all predicted to impact the general physiology of the fungus and this was reflected in an increased in vitro growth, even in the absence of C. elegans. While most cases involved single nucleotide substitutions predicted to lead to a loss of function, we also observed a predicted restoration of gene function through deletion of an extraneous tandem repeat. This latter change affected the regulatory subunit of a cAMP-dependent protein kinase. Remarkably, we also found a mutation in a gene for a second protein of the same, protein kinase A, pathway. Together, we predict that they result in a stronger repression of the pathway for given levels of ATP and adenylate cyclase activity. Finally, we also identified mutations in a few lineage-specific genes of unknown function that are candidates for factors that influence virulence in a more direct manner.

Competition dynamics in long-term propagations of Schizosaccharomyces pombe strain communities

Experimental evolution studies with microorganisms such as bacteria and yeast have been an increasingly important and powerful tool to draw long-term inferences of how microbes interact. However, while several strains of the same species often exist in natural environments, many ecology and evolution studies in microbes are typically performed with isogenic populations of bacteria or yeast. In the present study, we firstly perform a genotypic and phenotypic characterization of two laboratory and eight natural strains of the yeast Schizosaccharomyces pombe. We then propagated, in a rich resource environment, yeast communities of 2, 3, 4, and 5 strains for hundreds of generations and asked which fitness-related phenotypes-maximum growth rate or relative competitive fitness-would better predict the outcome of a focal strain during the propagations. While the strain's growth rates would wrongly predict long-term coexistence, pairwise competitive fitness with a focal strain qualitatively predicted the success or extinction of the focal strain by a simple multigenotype population genetics model, given the initial community composition. Interestingly, we have also measured the competitive fitness of the ancestral and evolved communities by the end of the experiment (≈370 generations) and observed frequent maladaptation to the abiotic environment in communities with more than three members. Overall, our results aid establishing pairwise competitive fitness as good qualitative measurement of long-term community composition but also reveal a complex adaptive scenario when trying to predict the evolutionary outcome of those communities.

Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations

Evolutionary adaptation to a constant environment is driven by the accumulation of mutations which can have a range of unrealized pleiotropic effects in other environments. These pleiotropic consequences of adaptation can influence the emergence of specialists or generalists, and are critical for evolution in temporally or spatially fluctuating environments. While many experiments have examined the pleiotropic effects of adaptation at a snapshot in time, very few have observed the dynamics by which these effects emerge and evolve. Here, we propagated hundreds of diploid and haploid laboratory budding yeast populations in each of three environments, and then assayed their fitness in multiple environments over 1000 generations of evolution. We find that replicate populations evolved in the same condition share common patterns of pleiotropic effects across other environments, which emerge within the first several hundred generations of evolution. However, we also find dynamic and environment-specific variability within these trends: variability in pleiotropic effects tends to increase over time, with the extent of variability depending on the evolution environment. These results suggest shifting and overlapping contributions of chance and contingency to the pleiotropic effects of adaptation, which could influence evolutionary trajectories in complex environments that fluctuate across space and time.

DNA damage repair system in C57BL/6 J mice is evolutionarily stable

Background

DNA damage repair (DDR) system is vital in maintaining genome stability and survival. DDR consists of over 160 genes in 7 different pathways to repair specific type of DNA damage caused by external and internal damaging factors. The functional importance of DDR system implies that evolution could play important roles in maintaining its functional intactness to perform its function. Indeed, it has been observed that positive selection is present in BRCA1 and BRCA2 (BRCA), which are key genes in homologous recombination pathway of DDR system, in the humans and its close relatives of chimpanzee and bonobos. Efforts have been made to investigate whether the same selection could exist for BRCA in other mammals but found no evidence so far. However, as most of the studies in non-human mammals analyzed only a single or few individuals in the studied species, the observation may not reflect the true status in the given species. Furthermore, few studies have studied evolution selection in other DDR genes except BRCA. In current study, we used laboratory mouse C57BL/6 J as a model to address evolution selection on DDR genes in non-primate mammals by dynamically monitoring genetic variation across 30 generations in C57BL/6 J.

Results

Using exome sequencing, we collected coding sequences of 169 DDR genes from 44 C57BL/6 J individual genomes in 2018. We compared the coding sequences with the mouse reference genome sequences derived from 1998 C57BL/6 J DNA, and with the mouse Eve6B reference genome sequences derived from 2003 C57BL/6 J DNA, covering 30 generations of C57BL/6 J from 1998 to 2018. We didn’t identify meaningful coding variation in either Brca1 or Brca2, or in 167 other DDR genes across the 30 generations. In the meantime, we did identify 812 coding variants in 116 non-DNA damage repair genes during the same period, which served as a quality control to validate the reliability of our analytic pipeline and the negative results in DDR genes.

Conclusions

DDR genes in laboratory mouse strain C57BL/6 J were not under positive selection across its 30-generation period, highlighting the possibility that DDR system in rodents could be evolutionarily stable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07983-7.

Joint effects of genes underlying a temperature specialization tradeoff in yeast

A central goal of evolutionary genetics is to understand, at the molecular level, how organisms adapt to their environments. For a given trait, the answer often involves the acquisition of variants at unlinked sites across the genome. Genomic methods have achieved landmark successes in pinpointing these adaptive loci. To figure out how a suite of adaptive alleles work together, and to what extent they can reconstitute the phenotype of interest, requires their transfer into an exogenous background. We studied the joint effect of adaptive, gain-of-function thermotolerance alleles at eight unlinked genes from Saccharomyces cerevisiae, when introduced into a thermosensitive sister species, S. paradoxus. Although the loci damped each other’s beneficial impact (that is, they were subject to negative epistasis), most boosted high-temperature growth alone and in combination, and none was deleterious. The complete set of eight genes was sufficient to confer ~15% of the S. cerevisiae thermotolerance phenotype in the S. paradoxus background. The same loci also contributed to a heretofore unknown advantage in cold growth by S. paradoxus. Together, our data establish temperature resistance in yeasts as a model case of a genetically complex evolutionary tradeoff, which can be partly reconstituted from the sequential assembly of unlinked underlying loci.

Organisms adapt to threats in the environment by acquiring DNA sequence variants that tweak traits to improve fitness. Experimental studies of this process have proven to be a particular challenge when they involve manipulation of a suite of genes, all on different chromosomes. We set out to understand how so many loci could work together to confer a trait. We used as a model system eight genes that govern the ability of the unicellular yeast Saccharomyces cerevisiae to grow at high temperature. We introduced these variant loci stepwise into a non-thermotolerant sister species, and found that the more S. cerevisiae alleles we added, the better the phenotype. We saw no evidence for toxic interactions between the genes as they were combined. We also used the eight-fold transgenic to dissect the biological mechanism of thermotolerance. And we discovered a tradeoff: the same alleles that boosted growth at high temperature eroded the organism’s ability to deal with cold conditions. These results serve as a case study of modular construction of a trait from nature, by assembling the genes together in one genome.

Seven Years at High Salinity-Experimental Evolution of the Extremely Halotolerant Black Yeast Hortaea werneckii

The experimental evolution of microorganisms exposed to extreme conditions can provide insight into cellular adaptation to stress. Typically, stress-sensitive species are exposed to stress over many generations and then examined for improvements in their stress tolerance. In contrast, when starting with an already stress-tolerant progenitor there may be less room for further improvement, it may still be able to tweak its cellular machinery to increase extremotolerance, perhaps at the cost of poorer performance under non-extreme conditions. To investigate these possibilities, a strain of extremely halotolerant black yeast Hortaea werneckii was grown for over seven years through at least 800 generations in a medium containing 4.3 M NaCl. Although this salinity is well above the optimum (0.8–1.7 M) for the species, the growth rate of the evolved H. werneckii did not change in the absence of salt or at high concentrations of NaCl, KCl, sorbitol, or glycerol. Other phenotypic traits did change during the course of the experimental evolution, including fewer multicellular chains in the evolved strains, significantly narrower cells, increased resistance to caspofungin, and altered melanisation. Whole-genome sequencing revealed the occurrence of multiple aneuploidies during the experimental evolution of the otherwise diploid H. werneckii. A significant overrepresentation of several gene groups was observed in aneuploid regions. Taken together, these changes suggest that long-term growth at extreme salinity led to alterations in cell wall and morphology, signalling pathways, and the pentose phosphate cycle. Although there is currently limited evidence for the adaptive value of these changes, they offer promising starting points for future studies of fungal halotolerance.

The genetic basis of differential autodiploidization in evolving yeast populations

Spontaneous whole-genome duplication, or autodiploidization, is a common route to adaptation in experimental evolution of haploid budding yeast populations. The rate at which autodiploids fix in these populations appears to vary across strain backgrounds, but the genetic basis of these differences remains poorly characterized. Here, we show that the frequency of autodiploidization differs dramatically between two closely related laboratory strains of Saccharomyces cerevisiae, BY4741 and W303. To investigate the genetic basis of this difference, we crossed these strains to generate hundreds of unique F1 segregants and tested the tendency of each segregant to autodiplodize across hundreds of generations of laboratory evolution. We find that variants in the SSD1 gene are the primary genetic determinant of differences in autodiploidization. We then used multiple laboratory and wild strains of S. cerevisiae to show that clonal populations of strains with a functional copy of SSD1 autodiploidize more frequently in evolution experiments, while knocking out this gene or replacing it with the W303 allele reduces autodiploidization propensity across all genetic backgrounds tested. These results suggest a potential strategy for modifying rates of spontaneous whole-genome duplications in laboratory evolution experiments in haploid budding yeast. They may also have relevance to other settings in which eukaryotic genome stability plays an important role, such as biomanufacturing and the treatment of pathogenic fungal diseases and cancers.