Genomics of Adaptation Depends on the Rate of Environmental Change in Experimental Yeast Populations

Allelic variation of PmCBF03 contributes to the altitude and temperature adaptability in Japanese apricot (Prunus mume Sieb. et Zucc.)

Japanese apricot is an important subtropical deciduous fruit tree in China, widely distributed in different altitude areas. How does it adapt to the different temperature environments in these areas? In this study, we identified a low-temperature transcription factor PmCBF03 on chromosome 7 through adaptive analysis of populations at different altitudes, which has an early termination single nucleotide polymorphism mutation. There were two different types of variation, PmCBF03A type in high-altitude areas and PmCBF03T type in low-altitude areas. PmCBF03A gene increased the survival rate, Fv/Fm values, antioxidant enzyme activity, and expression levels of antioxidant enzyme genes, and reducing electrolyte leakage and accumulation of reactive oxygen species in transgenic Arabidopsis under low temperature and freezing stress. Simultaneously, PmCBF03A gene promoted the dormancy of transgenic Arabidopsis seeds than wild-type. Biochemical analysis demonstrated that PmCBF03A directly bound to the DRE/CRT element in the promoters of the PmCOR413, PmDAM6 and PmABI5 genes, promoting their transcription and enhanced the cold resistance and dormancy of the overexpressing PmCBF03A lines. While PmCBF03T gene is unable to bind to the promoters of PmDAM6 and PmABI5 genes, leading to early release of dormancy to adapt to the problem of insufficient chilling requirement in low-altitude areas.

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.

Quantitative systems-based prediction of antimicrobial resistance evolution

Predicting evolution is a fundamental problem in biology with practical implications for treating antimicrobial resistance, which is a complex system-level phenomenon. In this perspective article, we explore the limits of predicting antimicrobial resistance evolution, quantitatively define the predictability and repeatability of microevolutionary processes, and speculate on how these quantities vary across temporal, biological, and complexity scales. The opportunities and challenges for predicting antimicrobial resistance in the context of systems biology are also discussed. Based on recent research, we conclude that the evolution of antimicrobial resistance can be predicted using a systems biology approach integrating quantitative models with multiscale data from microbial evolution experiments.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Mutagenic Characteristics of Six Heavy Metals in Escherichia coli: The Commonality and Specificity

The history of long-term environmental exposure to heavy metals can be recorded in the genome as sporadic and specific mutations. Variable environments introduce diverse and adaptive mutations to organisms. To reveal the information hidden in genomes about environmental exposure to heavy metals, we performed long-term mutation accumulation (MA) experiments with Escherichia coli, analyzed genomes from 36 populations across 1650 generations with 6 heavy metal exposure regimes (arsenic, cadmium, chromium, copper, nickel, and lead), and inferred metal-specific evolution modes at the genomic level. All heavy metals induced genetic mutations with a mean rate of 3.459 × 10-9 per nucleotide per generation. The mutational spectrum exhibited distinct signatures; however, heavy metals also shared common mutation signatures prominently associated with all cancer types. The mutated genes showed an average similarity of 54.4% within the same exposure regime, whereas only 38.8% between exposure regimes. In terms of biological insights, mutated genes were enriched to fundamental cellular processes such as metabolism, motility, and transport. Our study elucidates the mutagenic commonality and specificity of environmental heavy metals, which are highly specific at mutational features and locus, but conserved at gene and functional levels, and may play crucial roles in the convergence of adaptation to heavy metals.

Whole genome sequencing and RNA-seq evaluation allowed to detect Cd adaptation footprint in Chironomus riparius

Evolutionary adaptation and phenotypic plasticity are important processes on how organisms respond to pollutant exposure. We dissected here the contribution of both processes to increased tolerance in Chironomus riparius to cadmium (Cd) exposure in a multi-generation experiment and inferred the underlying genomic basis. We simulated environmentally realistic conditions by continuously increasing contaminant concentration in six replicates initiated with 1000 larvae each, three pre-exposed to Cd and three not exposed to Cd (no-Cd) over eight generations. We measured life-cycle traits, transcriptomic responses and genome-wide allele frequency changes from this evolve and resequencing (E&R) experiment. Overall, life cycle tests revealed little phenotypic adaptation to Cd exposure, but a slightly increase in survival in the first larval stage was observed. Population genomic analyses showed a strong genome-wide selective response in all replicates, highlighting two main biological functions involved in development and growth of the chironomids. Emphasizing that laboratory conditions continually exert selective pressure. However, the integration of the transcriptomic to the genomic data allowed to distinguish pathways specifically selected by the Cd exposure related to microtubules and organelles and cellular movement. Those pathways could be functionally related to an excretion of metals. Thus, our results indicate that genetic adaptation to Cd in C. riparius can happen within few generations under an environmentally relevant exposure scenario, but substantial phenotypic tolerance might take more time to arise. With our approach, we introduce an experimental setup to fill the existing gap in evolutionary ecotoxicology to investigate these early signs of genetic adaptation.

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.

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an alignment-based score for any protein variant, with scores categorized as neutral or deleterious based on a pre-set threshold. PROVEAN has been used widely in evolutionary studies, for example, to estimate mutation load in natural populations, but has not been formally tested as a predictor of aggregate mutational effects on fitness. Using three large published data sets on the genome sequences of laboratory mutation accumulation lines, we assessed how well PROVEAN predicted the actual fitness patterns observed, relative to other metrics. In most cases, we find that a simple count of the total number of mutant proteins is a better predictor of fitness than the number of proteins with variants scored as deleterious by PROVEAN. We also find that the sum of all mutant protein scores explains variation in fitness better than the number of mutant proteins in one of the data sets. We discuss the implications of these results for studies of populations in the wild.

Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation

Historical contingency and diminishing returns epistasis have been typically studied for relatively divergent genotypes and/or over long evolutionary timescales. Here, we use Saccharomyces cerevisiae to study the extent of diminishing returns and the changes in the adaptive mutational spectra following a single first adaptive mutational step. We further evolve three clones that arose under identical conditions from a common ancestor. We follow their evolutionary dynamics by lineage tracking and determine adaptive outcomes using fitness assays and whole genome sequencing. We find that diminishing returns manifests as smaller fitness gains during the 2^nd step of adaptation compared to the 1^st step, mainly due to a compressed distribution of fitness effects. We also find that the beneficial mutational spectra for the 2^nd adaptive step are contingent on the 1^st step, as we see both shared and diverging adaptive strategies. Finally, we find that adaptive loss-of-function mutations, such as nonsense and frameshift mutations, are less common in the second step of adaptation than in the first step.

Analyses of both natural and experimental evolution suggest that adaptation depends on the evolutionary past and adaptive potential decreases over time. Here, by tracking yeast adaptation with DNA barcoding, the authors show that such evolutionary phenomena can be observed even after a single adaptive step.

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.

Genome-wide DNA mutations in Arabidopsis plants after multigenerational exposure to high temperatures

BACKGROUND

Elevated temperatures can cause physiological, biochemical, and molecular responses in plants that can greatly affect their growth and development. Mutations are the most fundamental force driving biological evolution. However, how long-term elevations in temperature influence the accumulation of mutations in plants remains unknown.

RESULTS

Multigenerational exposure of Arabidopsis MA (mutation accumulation) lines and MA populations to extreme heat and moderate warming results in significantly increased mutation rates in single-nucleotide variants (SNVs) and small indels. We observe distinctive mutational spectra under extreme and moderately elevated temperatures, with significant increases in transition and transversion frequencies. Mutation occurs more frequently in intergenic regions, coding regions, and transposable elements in plants grown under elevated temperatures. At elevated temperatures, more mutations accumulate in genes associated with defense responses, DNA repair, and signaling. Notably, the distribution patterns of mutations among all progeny differ between MA populations and MA lines, suggesting that stronger selection effects occurred in populations. Methylation is observed more frequently at mutation sites, indicating its contribution to the mutation process at elevated temperatures. Mutations occurring within the same genome under elevated temperatures are significantly biased toward low gene density regions, special trinucleotides, tandem repeats, and adjacent simple repeats. Additionally, mutations found in all progeny overlap significantly with genetic variations reported in 1001 Genomes, suggesting non-uniform distribution of de novo mutations through the genome.

CONCLUSION

Collectively, our results suggest that elevated temperatures can accelerate the accumulation, and alter the molecular profiles, of DNA mutations in plants, thus providing significant insight into how environmental temperatures fuel plant evolution.

The Role of Structural Variation in Adaptation and Evolution of Yeast and Other Fungi

Mutations in DNA can be limited to one or a few nucleotides, or encompass larger deletions, insertions, duplications, inversions and translocations that span long stretches of DNA or even full chromosomes. These so-called structural variations (SVs) can alter the gene copy number, modify open reading frames, change regulatory sequences or chromatin structure and thus result in major phenotypic changes. As some of the best-known examples of SV are linked to severe genetic disorders, this type of mutation has traditionally been regarded as negative and of little importance for adaptive evolution. However, the advent of genomic technologies uncovered the ubiquity of SVs even in healthy organisms. Moreover, experimental evolution studies suggest that SV is an important driver of evolution and adaptation to new environments. Here, we provide an overview of the causes and consequences of SV and their role in adaptation, with specific emphasis on fungi since these have proven to be excellent models to study SV.

The population genetics of ploidy change in unicellular fungi

Changes in ploidy are a significant type of genetic variation, describing the number of chromosome sets per cell. Ploidy evolves in natural populations, clinical populations, and lab experiments, particularly in fungi. Despite a long history of theoretical work on this topic, predicting how ploidy will evolve has proven difficult, as it is often unclear why one ploidy state outperforms another. Here, we review what is known about contemporary ploidy evolution in diverse fungal species through the lens of population genetics. As with typical genetic variants, ploidy evolution depends on the rate that new ploidy states arise by mutation, natural selection on alternative ploidy states, and random genetic drift. However, ploidy variation also has unique impacts on evolution, with the potential to alter chromosomal stability, the rate and patterns of point mutation, and the nature of selection on all loci in the genome. We discuss how ploidy evolution depends on these general and unique factors and highlight areas where additional experimental evidence is required to comprehensively explain the ploidy transitions observed in the field and the lab.

Rate of environmental change across scales in ecology

The rate of change (RoC) of environmental drivers matters: biotic and abiotic components respond differently when faced with a fast or slow change in their environment. This phenomenon occurs across spatial scales and thus levels of ecological organization. We investigated the RoC of environmental drivers in the ecological literature and examined publication trends across ecological levels, including prevalent types of evidence and drivers. Research interest in environmental driver RoC has increased over time (particularly in the last decade), however, the amount of research and type of studies were not equally distributed across levels of organization and different subfields of ecology use temporal terminology (e.g. 'abrupt' and 'gradual') differently, making it difficult to compare studies. At the level of individual organisms, evidence indicates that responses and underlying mechanisms are different when environmental driver treatments are applied at different rates, thus we propose including a time dimension into reaction norms. There is much less experimental evidence at higher levels of ecological organization (i.e. population, community, ecosystem), although theoretical work at the population level indicates the importance of RoC for evolutionary responses. We identified very few studies at the community and ecosystem levels, although existing evidence indicates that driver RoC is important at these scales and potentially could be particularly important for some processes, such as community stability and cascade effects. We recommend shifting from a categorical (e.g. abrupt versus gradual) to a quantitative and continuous (e.g. °C/h) RoC framework and explicit reporting of RoC parameters, including magnitude, duration and start and end points to ease cross-scale synthesis and alleviate ambiguity. Understanding how driver RoC affects individuals, populations, communities and ecosystems, and furthermore how these effects can feed back between levels is critical to making improved predictions about ecological responses to global change drivers. The application of a unified quantitative RoC framework for ecological studies investigating environmental driver RoC will both allow cross-scale synthesis to be accomplished more easily and has the potential for the generation of novel hypotheses.

Evolution, Microbes, and Changing Ocean Conditions

Experimental evolution and the associated theory are underutilized in marine microbial studies; the two fields have developed largely in isolation. Here, we review evolutionary tools for addressing four key areas of ocean global change biology: linking plastic and evolutionary trait changes, the contribution of environmental variability to determining trait values, the role of multiple environmental drivers in trait change, and the fate of populations near their tolerance limits. Wherever possible, we highlight which data from marine studies could use evolutionary approaches and where marine model systems can advance our understanding of evolution. Finally, we discuss the emerging field of marine microbial experimental evolution. We propose a framework linking changes in environmental quality (defined as the cumulative effect on population growth rate) with population traits affecting evolutionary potential, in order to understand which evolutionary processes are likely to be most important across a range of locations for different types of marine microbes.

Aneuploidy in yeast: Segregation error or adaptation mechanism?

Aneuploidy is the loss or gain of chromosomes within a genome. It is often detrimental and has been associated with cell death and genetic disorders. However, aneuploidy can also be beneficial and provide a quick solution through changes in gene dosage when cells face environmental stress. Here, we review the prevalence of aneuploidy in Saccharomyces, Candida, and Cryptococcus yeasts (and their hybrid offspring) and analyse associations with chromosome size and specific stressors. We discuss how aneuploidy, a segregation error, may in fact provide a natural route for the diversification of microbes and enable important evolutionary innovations given the right ecological circumstances, such as the colonisation of new environments or the transition from commensal to pathogenic lifestyle. We also draw attention to a largely unstudied cross link between hybridisation and aneuploidy. Hybrid meiosis, involving two divergent genomes, can lead to drastically increased rates of aneuploidy in the offspring due to antirecombination and chromosomal missegregation. Because hybridisation and aneuploidy have both been shown to increase with environmental stress, we believe it important and timely to start exploring the evolutionary significance of their co-occurrence.

Evolutionary Dynamics in the RNA Bacteriophage Qβ Depends on the Pattern of Change in Selective Pressures

The rate of change in selective pressures is one of the main factors that determines the likelihood that populations can adapt to stress conditions. Generally, the reduction in the population size that accompanies abrupt environmental changes makes it difficult to generate and select adaptive mutations. However, in systems with high genetic diversity, as happens in RNA viruses, mutations with beneficial effects under new conditions can already be present in the population, facilitating adaptation. In this work, we have propagated an RNA bacteriophage (Qβ) at temperatures higher than the optimum, following different patterns of change. We have determined the fitness values and the consensus sequences of all lineages throughout the evolutionary process in order to establish correspondences between fitness variations and adaptive pathways. Our results show that populations subjected to a sudden temperature change gain fitness and fix mutations faster than those subjected to gradual changes, differing also in the particular selected mutations. The life-history of populations prior to the environmental change has great importance in the dynamics of adaptation. The conclusion is that in the bacteriophage Qβ, the standing genetic diversity together with the rate of temperature change determine both the rapidity of adaptation and the followed evolutionary pathways.

Adaptive genome duplication affects patterns of molecular evolution in Saccharomyces cerevisiae

Genome duplications are important evolutionary events that impact the rate and spectrum of beneficial mutations and thus the rate of adaptation. Laboratory evolution experiments initiated with haploid Saccharomyces cerevisiae cultures repeatedly experience whole-genome duplication (WGD). We report recurrent genome duplication in 46 haploid yeast populations evolved for 4,000 generations. We find that WGD confers a fitness advantage, and this immediate fitness gain is accompanied by a shift in genomic and phenotypic evolution. The presence of ploidy-enriched targets of selection and structural variants reveals that autodiploids utilize adaptive paths inaccessible to haploids. We find that autodiploids accumulate recessive deleterious mutations, indicating an increased susceptibility for nonadaptive evolution. Finally, we report that WGD results in a reduced adaptation rate, indicating a trade-off between immediate fitness gains and long-term adaptability.

Whole genome duplications—the simultaneous doubling of each chromosome—can have a profound influence on evolution. Evidence of ancient whole genome duplications can be seen in most modern genomes. Experimental evolution, the long-term propagation of organisms under well-controlled laboratory conditions, yields valuable insight into the processes of adaptation and genome evolution. One interesting, and common, outcome of laboratory evolution experiments that start with haploid yeast populations is the emergence of diploid lineages via whole genome duplication. We show that, under our laboratory conditions, whole genome duplication provides a direct fitness benefit, and we identify several consequences of whole genome duplication on adaptation. Following whole-genome duplication, the rate of adaptation slows, the biological targets of selection change, and aneuploidies, copy-number variants and recessive lethal mutations accumulate. By studying the effect of whole genome duplication on adaptation, we can better understand how selection acts on ploidy, a fundamental biological parameter that varies considerably across life.

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change.