Can Population Genetics Adapt to Rapid Evolution?

Adapting Biased Gene Conversion theory to account for intensive GC-content deterioration in the human genome by novel mutations

We examined seventy million well-characterized human mutations, and their impact on G+C-compositional dynamics, in order to understand the formation and maintenance of major genomic nucleotide sequence patterns. Among novel mutations, those that change a strong (S) base pair G:C/C:G to a weak (W) pair A:T/T:A occur at nearly twice the frequency of the opposite mutations. Such imbalance puts strong downward pressure on overall GC-content. However, along protracted paths to fixation, S→W mutations are much less likely to propagate than W→S mutations. The magnitude of relative propagation disadvantages for S→W mutations is inexplicable by any currently-accepted model. This fact forced us to re-examine the quantitative features of Biased Gene Conversion (BGC) theory. Revised parameters of BGC that, per average individual, convert 7–14 W base pairs into S pairs, would account for the S-content turnover differences between new and old mutations, and make BGC an instrumental force for nucleotide dynamics and evolution. BGC should thus be considered seriously in both theories and biomedical practice. In particular, BGC should be taken into account during allele imputations, where missing SNP alleles are computationally predicted based on the information about several neighboring alleles. Finally, we analyzed the effect of neighboring nucleotide context on the mutation frequencies, dynamics, and GC-composition turnover. For this purpose, we examined genomic regions having extremely biased nucleotide compositions (enriched for S-, W-, purine/pyrimidine strand asymmetry, or AC/GT-strand asymmetry). It was found that point mutations in these regions preferentially degrade the nucleotide inhomogeneities, decreasing the sequence biases. Degradation of sequence bias is highest for novel mutations, and considerably lower for older mutations (those widespread across populations). Besides BGC, there may be additional, still uncharacterized molecular mechanisms that either preserve genomic regions with biased nucleotide compositions from mutational degradation or fail to degrade such inhomogeneities in specific chromosomal regions.

Standing genetic variation fuels rapid adaptation to ocean acidification

Global climate change has intensified the need to assess the capacity for natural populations to adapt to abrupt shifts in the environment. Reductions in seawater pH constitute a conspicuous global change stressor that is affecting marine ecosystems globally. Here, we quantify the phenotypic and genetic modifications associated with rapid adaptation to reduced seawater pH in the Mediterranean mussel, Mytilus galloprovincialis. We reared a genetically diverse larval population in two pH treatments (pH_T 8.1 and 7.4) and tracked changes in the shell-size distribution and genetic variation through settlement. Additionally, we identified differences in the signatures of selection on shell growth in each pH environment. Both phenotypic and genetic data show that standing variation can facilitate adaptation to declines in seawater pH. This work provides insight into the processes underpinning rapid evolution, and demonstrates the importance of maintaining variation within natural populations to bolster species’ adaptive capacity as global change progresses.

Reductions in seawater pH are affecting marine ecosystems globally. Here, the authors describe phenotypic and genetic modifications associated with rapid adaptation to reduced seawater pH in the mussel Mytilus galloprovincialis, and suggest that standing variation within natural populations plays an important role in bolstering species’ adaptive capacity to global change.

Adaptation to the abiotic environment in insects: the influence of variability on ecophysiology and evolutionary genomics

Advances in tools to gather environmental, phenotypic, and molecular data have accelerated our ability to detect abiotic drivers of variation across the genome-to-phenome spectrum in model and non-model insects. However, differences in the spatial and temporal resolution of these data sets may create gaps in our understanding of linkages between environment, genotype, and phenotype that yield missed or misleading results about adaptive variation. In this review we highlight sources of variability that might impact studies of phenotypic and 'omic environmental adaptation, challenges to collecting data at relevant scales, and possible solutions that link intensive fine-scale reductionist studies of mechanisms to large-scale biogeographic patterns.

Population Genetics in the Human Microbiome

While the human microbiome's structure and function have been extensively studied, its within-species genetic diversity is less well understood. However, genetic mutations in the microbiome can confer biomedically relevant traits, such as the ability to extract nutrients from food, metabolize drugs, evade antibiotics, and communicate with the host immune system. The population genetic processes by which these traits evolve are complex, in part due to interacting ecological and evolutionary forces in the microbiome. Advances in metagenomic sequencing, coupled with bioinformatics tools and population genetic models, facilitate quantification of microbiome genetic variation and inferences about how this diversity arises, evolves, and correlates with traits of both microbes and hosts. In this review, we explore the population genetic forces (mutation, recombination, drift, and selection) that shape microbiome genetic diversity within and between hosts, as well as efforts towards predictive models that leverage microbiome genetics.

The Linked Selection Signature of Rapid Adaptation in Temporal Genomic Data

The majority of empirical population genetic studies have tried to understand the evolutionary processes that have shaped genetic variation in a single sample taken from a present-day population. However, genomic data collected over tens of generations in both natural and laboratory populations are increasingly used to find selected loci underpinning adaptation over these short timescales. Although these studies have been quite successful in detecting selection on large-effect loci, the fitness differences between individuals are often polygenic, such that selection leads to allele frequency changes that are difficult to distinguish from genetic drift. However, one promising signal comes from polygenic selection's effect on neutral sites that become stochastically associated with the genetic backgrounds that lead to fitness differences between individuals. Previous theoretical work has established that the random associations between a neutral allele and heritable fitness backgrounds act to reduce the effective population size experienced by this neutral allele. These associations perturb neutral allele frequency trajectories, creating autocovariance in the allele frequency changes across generations. Here, we show how temporal genomic data allow us to measure the temporal autocovariance in allele frequency changes and characterize the genome-wide impact of polygenic selection. We develop expressions for these temporal autocovariances, showing that their magnitude is determined by the level of additive genetic variation, recombination, and linkage disequilibria in a region. Furthermore, by using analytic expressions for the temporal variances and autocovariances in allele frequency, we demonstrate that one can estimate the additive genetic variation for fitness and the drift-effective population size from temporal genomic data. We also show how the proportion of total variation in allele frequency change due to linked selection can be estimated from temporal data. Overall, we demonstrate that temporal genomic data offer opportunities to identify the role of linked selection on genome-wide diversity over short timescales, and can help bridge population genetic and quantitative genetic studies of adaptation.

A continuum of biological adaptations to environmental fluctuation

Bet-hedging-a strategy that reduces fitness variance at the expense of lower mean fitness among different generations-is thought to evolve as a biological adaptation to environmental unpredictability. Despite widespread use of the bet-hedging concept, most theoretical treatments have largely made unrealistic demographic assumptions, such as non-overlapping generations and fixed or infinite population sizes. Here, we extend the concept to consider overlapping generations by defining bet-hedging as a strategy with lower variance and mean per capita growth rate across different environments. We also define an opposing strategy-the rising-tide-that has higher mean but also higher variance in per capita growth. These alternative strategies lie along a continuum of biological adaptions to environmental fluctuation. Using stochastic Lotka-Volterra models to explore the evolution of the rising-tide versus bet-hedging strategies, we show that both the mean environmental conditions and the temporal scales of their fluctuations, as well as whether population dynamics are discrete or continuous, are crucial in shaping the type of strategy that evolves in fluctuating environments. Our model demonstrates that there are likely to be a wide range of ways that organisms with overlapping generations respond to environmental unpredictability beyond the classic bet-hedging concept.

The feedback between selection and demography shapes genomic diversity during coevolution

Species interactions and coevolution are integral to ecological communities, but we lack empirical information on when and how these interactions generate and purge genetic diversity. Using genomic time series data from host-virus experiments, we found that coevolution occurs through consecutive selective sweeps in both species, with temporal consistency across replicates. Sweeps were accompanied by phenotypic change (resistance or infectivity increases) and expansions in population size. In the host, population expansion enabled rapid generation of genetic diversity in accordance with neutral processes. Viral molecular evolution was, in contrast, confined to few genes, all putative targets of selection. This study demonstrates that molecular evolution during species interactions is shaped by both eco-evolutionary feedback dynamics and interspecific differences in how genetic diversity is generated and maintained.

Microbiome composition shapes rapid genomic adaptation of Drosophila melanogaster

Population genomic data has revealed patterns of genetic variation associated with adaptation in many taxa. Yet understanding the adaptive process that drives such patterns is challenging; it requires disentangling the ecological agents of selection, determining the relevant timescales over which evolution occurs, and elucidating the genetic architecture of adaptation. Doing so for the adaptation of hosts to their microbiome is of particular interest with growing recognition of the importance and complexity of host-microbe interactions. Here, we track the pace and genomic architecture of adaptation to an experimental microbiome manipulation in replicate populations of Drosophila melanogaster in field mesocosms. Shifts in microbiome composition altered population dynamics and led to divergence between treatments in allele frequencies, with regions showing strong divergence found on all chromosomes. Moreover, at divergent loci previously associated with adaptation across natural populations, we found that the more common allele in fly populations experimentally enriched for a certain microbial group was also more common in natural populations with high relative abundance of that microbial group. These results suggest that microbiomes may be an agent of selection that shapes the pattern and process of adaptation and, more broadly, that variation in a single ecological factor within a complex environment can drive rapid, polygenic adaptation over short timescales.

Sex solves Haldane's dilemma

The cumulative reproductive cost of multi-locus selection has been considered to be a potentially limiting factor on the rate of adaptive evolution. In this paper, we show that Haldane's arguments for the accumulation of reproductive costs over multiple loci are valid only for a clonally reproducing population of asexual genotypes. We show that a sexually reproducing population avoids this accumulation of costs. Thus, sex removes a perceived reproductive constraint on the rate of adaptive evolution. The significance of our results is twofold. First, the results demonstrate that adaptation based on multiple genes-such as selection acting on the standing genetic variation-does not entail a huge reproductive cost as suggested by Haldane, provided of course that the population is reproducing sexually. Second, this reduction in the cost of natural selection provides a simple biological explanation for the advantage of sex. Specifically, Haldane's calculations illustrate the evolutionary disadvantage of asexuality; sexual reproduction frees the population from this disadvantage.

The potential of VKORC1 polymorphisms in Mustelidae for evolving anticoagulant resistance through selection along the food chain

In response to strong selection, new mutations can arise quickly and sweep through populations, particularly, if survival and reproduction depend on certain allele copies for adaptation to rapidly changing environments, like resistance against deadly diseases or strong toxins. Since the 1950s, resistance to anticoagulant rodenticides in several rodents has emerged through single nucleotide mutations in the vitamin-K-epoxid-reductase-complex-subunit-1 (VKORC1) gene, often located in its exon 3. Detection of high prevalence and concentrations of anticoagulant rodenticides in non-target vertebrates, including carnivorous Mustelidae, let us assume that secondary exposure by feeding on poisoned prey may also cause selection along the food chain and we hypothesized that VKORC1-based resistance might also have evolved in rodents' predators. Using newly-developed mustelid-specific primers for direct sequencing of genomic DNA, we studied VKORC1-DNA-polymorphisms in 115 mustelids of five species (Martes martes, M. foina, Mustela nivalis, M. erminea, M. putorius), obtained from northern Denmark, yielding six sites with nonsynonymous and several synonymous amino acid polymorphisms in exon 3. Comparison of these VKORC1-genotypes with hepatic rodenticide residues (obtained by HPLC combined with fluorescence or mass spectrometry) in 83 individuals (except M. martes), using generalized linear models, suggested that anticoagulant levels depended on species and specific polymorphisms. Although most VKORC-1 polymorphisms may present standing genetic variation, some are situated in resistance-mediating membrane parts of the VKORC1-encoded protein, and might be a result of selection due to exposure to anticoagulant poisons. Our new molecular markers might allow detecting indirect effects of anticoagulant rodenticides on rodent predator populations in the future.

Additive genetic variance for lifetime fitness and the capacity for adaptation in an annual plant

The immediate capacity for adaptation under current environmental conditions is directly proportional to the additive genetic variance for fitness, V_A (W). Mean absolute fitness, W ¯ , is predicted to change at the rate V A ( W ) W ¯ , according to Fisher's Fundamental Theorem of Natural Selection. Despite ample research evaluating degree of local adaptation, direct assessment of V_A (W) and the capacity for ongoing adaptation is exceedingly rare. We estimated V_A (W) and W ¯ in three pedigreed populations of annual Chamaecrista fasciculata, over three years in the wild. Contrasting with common expectations, we found significant V_A (W) in all populations and years, predicting increased mean fitness in subsequent generations (0.83 to 6.12 seeds per individual). Further, we detected two cases predicting "evolutionary rescue," where selection on standing V_A (W) was expected to increase fitness of declining populations ( W ¯ < 1.0) to levels consistent with population sustainability and growth. Within populations, inter-annual differences in genetic expression of fitness were striking. Significant genotype-by-year interactions reflected modest correlations between breeding values across years, indicating temporally variable selection at the genotypic level that could contribute to maintaining V_A (W). By directly estimating V_A (W) and total lifetime W ¯ , our study presents an experimental approach for studies of adaptive capacity in the wild.

Surfing on the seascape: Adaptation in a changing environment

The environment changes constantly at various time scales and, in order to survive, species need to keep adapting. Whether these species succeed in avoiding extinction is a major evolutionary question. Using a multilocus evolutionary model of a mutation-limited population adapting under strong selection, we investigate the effects of the frequency of environmental fluctuations on adaptation. Our results rely on an "adaptive-walk" approximation and use mathematical methods from evolutionary computation theory to investigate the interplay between fluctuation frequency, the similarity of environments, and the number of loci contributing to adaptation. First, we assume a linear additive fitness function, but later generalize our results to include several types of epistasis. We show that frequent environmental changes prevent populations from reaching a fitness peak, but they may also prevent the large fitness loss that occurs after a single environmental change. Thus, the population can survive, although not thrive, in a wide range of conditions. Furthermore, we show that in a frequently changing environment, the similarity of threats that a population faces affects the level of adaptation that it is able to achieve. We check and supplement our analytical results with simulations.

Why So Variable: Can Genetic Variance in Flowering Thresholds Be Maintained by Fluctuating Selection?

We use integral projection models (IPMs) and individual-based simulations to study the evolution of genetic variance in two monocarpic plant systems. Previous approaches combining IPMs with an adaptive dynamics-style invasion analysis predicted that genetic variability in the size threshold for flowering will not be maintained, which conflicts with empirical evidence. We ask whether this discrepancy can be resolved by making more realistic assumptions about the underlying genetic architecture, assuming a multilocus quantitative trait in an outcrossing diploid species. To do this, we embed the infinitesimal model of quantitative genetics into an IPM for a size-structured cosexual plant species. The resulting IPM describes the joint dynamics of individual size and breeding value of the evolving trait. We apply this general framework to the monocarpic perennials Oenothera glazioviana and Carlina vulgaris. The evolution of heritable variation in threshold size is explored in both individual-based models (IBMs) and IPMs, using a mutation rate modifier approach. In the Oenothera model, where the environment is constant, there is selection against producing genetically variable offspring. In the Carlina model, where the environment varies between years, genetically variable offspring provide a selective advantage, allowing the maintenance of genetic variability. The contrasting predictions of adaptive dynamics and quantitative genetics models for the same system suggest that fluctuating selection may be more effective at maintaining genetic variation than previously thought.

Adaptive introgression enables evolutionary rescue from extreme environmental pollution

Radical environmental change that provokes population decline can impose constraints on the sources of genetic variation that may enable evolutionary rescue. Adaptive toxicant resistance has rapidly evolved in Gulf killifish (Fundulus grandis) that occupy polluted habitats. We show that resistance scales with pollution level and negatively correlates with inducibility of aryl hydrocarbon receptor (AHR) signaling. Loci with the strongest signatures of recent selection harbor genes regulating AHR signaling. Two of these loci introgressed recently (18 to 34 generations ago) from Atlantic killifish (F. heteroclitus). One introgressed locus contains a deletion in AHR that confers a large adaptive advantage [selection coefficient (s) = 0.8]. Given the limited migration of killifish, recent adaptive introgression was likely mediated by human-assisted transport. We suggest that interspecies connectivity may be an important source of adaptive variation during extreme environmental change.

Polygenic adaptation: From sweeps to subtle frequency shifts

Evolutionary theory has produced two conflicting paradigms for the adaptation of a polygenic trait. While population genetics views adaptation as a sequence of selective sweeps at single loci underlying the trait, quantitative genetics posits a collective response, where phenotypic adaptation results from subtle allele frequency shifts at many loci. Yet, a synthesis of these views is largely missing and the population genetic factors that favor each scenario are not well understood. Here, we study the architecture of adaptation of a binary polygenic trait (such as resistance) with negative epistasis among the loci of its basis. The genetic structure of this trait allows for a full range of potential architectures of adaptation, ranging from sweeps to small frequency shifts. By combining computer simulations and a newly devised analytical framework based on Yule branching processes, we gain a detailed understanding of the adaptation dynamics for this trait. Our key analytical result is an expression for the joint distribution of mutant alleles at the end of the adaptive phase. This distribution characterizes the polygenic pattern of adaptation at the underlying genotype when phenotypic adaptation has been accomplished. We find that a single compound parameter, the population-scaled background mutation rate Θ_bg, explains the main differences among these patterns. For a focal locus, Θ_bg measures the mutation rate at all redundant loci in its genetic background that offer alternative ways for adaptation. For adaptation starting from mutation-selection-drift balance, we observe different patterns in three parameter regions. Adaptation proceeds by sweeps for small Θ_bg ≲ 0.1, while small polygenic allele frequency shifts require large Θ_bg ≳ 100. In the large intermediate regime, we observe a heterogeneous pattern of partial sweeps at several interacting loci.

It is still an open question how complex traits adapt to new selection pressures. While population genetics champions the search for selective sweeps, quantitative genetics proclaims adaptation via small concerted frequency shifts. To date the empirical evidence of clear sweep signals is more scarce than expected, while subtle shifts remain notoriously hard to detect. In the current study we develop a theoretical framework to predict the expected adaptive architecture of a simple polygenic trait, depending on parameters such as mutation rate, effective population size, size of the trait basis, and the available genetic variability at the onset of selection. For a population in mutation-selection-drift balance we find that adaptation proceeds via complete or partial sweeps for a large set of parameter values. We predict adaptation by small frequency shifts for two main cases. First, for traits with a large mutational target size and high levels of genetic redundancy among loci, and second if the starting frequencies of mutant alleles are more homogeneous than expected in mutation-selection-drift equilibrium, e.g. due to population structure or balancing selection.

Pervasive function and evidence for selection across standing genetic variation in S. cerevisiae

Quantitative genetics aims to map genotype to phenotype, often with the goal of understanding how organisms evolved. However, it remains unclear whether the genetic variants identified are exemplary of evolution. Here we analyzed progeny of two wild Saccharomyces cerevisiae isolates to identify 195 loci underlying complex metabolic traits, resolving 107 to single polymorphisms with diverse molecular mechanisms. More than 20% of causal variants exhibited patterns of emergence inconsistent with neutrality. Moreover, contrary to drift-centric expectation, variation in diverse wild yeast isolates broadly exhibited this property: over 30% of shared natural variants exhibited phylogenetic signatures suggesting that they are not neutral. This pattern is likely attributable to both homoplasy and balancing selection on ancestral polymorphism. Variants that emerged repeatedly were more likely to have done so in isolates from the same ecological niche. Our results underscore the power of super-resolution mapping of ecologically relevant traits in understanding adaptation and evolution.

Ecological and Evolutionary Processes Shaping Viral Genetic Diversity

The contemporary genomic diversity of viruses is a result of the continuous and dynamic interaction of past ecological and evolutionary processes. Thus, genome sequences of viruses can be a valuable source of information about these processes. In this review, we first describe the relevant processes shaping viral genomic variation, with a focus on the role of host–virus coevolution and its potential to give rise to eco-evolutionary feedback loops. We further give a brief overview of available methodology designed to extract information about these processes from genomic data. Short generation times and small genomes make viruses ideal model systems to study the joint effect of complex coevolutionary and eco-evolutionary interactions on genetic evolution. This complexity, together with the diverse array of lifetime and reproductive strategies in viruses ask for extensions of existing inference methods, for example by integrating multiple information sources. Such integration can broaden the applicability of genetic inference methods and thus further improve our understanding of the role viruses play in biological communities.

Pervasive Linked Selection and Intermediate-Frequency Alleles Are Implicated in an Evolve-and-Resequencing Experiment of Drosophila simulans

We develop analytical and simulation tools for evolve-and-resequencing experiments and apply them to a new study of rapid evolution in Drosophila simulans Likelihood test statistics applied to pooled population sequencing data suggest parallel evolution of 138 SNPs across the genome. This number is reduced by orders of magnitude from previous studies (thousands or tens of thousands), owing to differences in both experimental design and statistical analysis. Whole genome simulations calibrated from Drosophila genetic data sets indicate that major features of the genome-wide response could be explained by as few as 30 loci under strong directional selection with a corresponding hitchhiking effect. Smaller effect loci are likely also responding, but are below the detection limit of the experiment. Finally, SNPs showing strong parallel evolution in the experiment are intermediate in frequency in the natural population (usually 30-70%) indicative of balancing selection in nature. These loci also exhibit elevated differentiation among natural populations of D. simulans, suggesting environmental heterogeneity as a potential balancing mechanism.

Rapid seasonal evolution in innate immunity of wild Drosophila melanogaster

Understanding the rate of evolutionary change and the genetic architecture that facilitates rapid adaptation is a current challenge in evolutionary biology. Comparative studies show that genes with immune function are among the most rapidly evolving genes across a range of taxa. Here, we use immune defence in natural populations of Drosophila melanogaster to understand the rate of evolution in natural populations and the genetics underlying rapid change. We probed the immune system using the natural pathogens Enterococcus faecalis and Providencia rettgeri to measure post-infection survival and bacterial load of wild D. melanogaster populations collected across seasonal time along a latitudinal transect along eastern North America (Massachusetts, Pennsylvania and Virginia). There are pronounced and repeatable changes in the immune response over the approximately 10 generations between spring and autumn collections, with a significant but less distinct difference observed among geographical locations. Genes with known immune function are not enriched among alleles that cycle with seasonal time, but the immune function of a subset of seasonally cycling alleles in immune genes was tested using reconstructed outbred populations. We find that flies containing seasonal alleles in Thioester-containing protein 3 (Tep3) have different functional responses to infection and that epistatic interactions among seasonal Tep3 and Drosomycin-like 6 (Dro6) alleles underlie the immune phenotypes observed in natural populations. This rapid, cyclic response to seasonal environmental pressure broadens our understanding of the complex ecological and genetic interactions determining the evolution of immune defence in natural populations.

From low to high gear: there has been a paradigm shift in our understanding of evolution

Experimental studies of evolution performed in nature and the associated demonstration of rapid evolution, observable on a time scale of months to years, were an acclaimed novelty in the 1980-1990s. Contemporary evolution is now considered ordinary and is an integrated feature of many areas of research. This shift from extraordinary to ordinary reflects a change in the perception of evolution. It was formerly thought of as a historical process, perceived through the footprints left in the fossil record or living organisms. It is now seen as a contemporary process that acts in real time. Here we review how this shift occurred and its consequences for fields as diverse as wildlife management, conservation biology, and ecosystems ecology. Incorporating contemporary evolution in these fields has caused old questions to be recast, changed the answers, caused new and previously inconceivable questions to be addressed, and inspired the development of new subdisciplines. We argue further that the potential of contemporary evolution has yet to be fulfilled. Incorporating evolutionary dynamics in any research program can provide a better assessment of how and why organisms and communities came to be as they are than is attainable without an explicit treatment of these dynamics.

A reference genome of the European beech (Fagus sylvatica L.)

Background

The European beech is arguably the most important climax broad-leaved tree species in Central Europe, widely planted for its valuable wood. Here, we report the 542 Mb draft genome sequence of an up to 300-year-old individual (Bhaga) from an undisturbed stand in the Kellerwald-Edersee National Park in central Germany.

Findings

Using a hybrid assembly approach, Illumina reads with short- and long-insert libraries, coupled with long Pacific Biosciences reads, we obtained an assembled genome size of 542 Mb, in line with flow cytometric genome size estimation. The largest scaffold was of 1.15 Mb, the N50 length was 145 kb, and the L50 count was 983. The assembly contained 0.12% of Ns. A Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis retrieved 94% complete BUSCO genes, well in the range of other high-quality draft genomes of trees. A total of 62,012 protein-coding genes were predicted, assisted by transcriptome sequencing. In addition, we are reporting an efficient method for extracting high-molecular-weight DNA from dormant buds, by which contamination by environmental bacteria and fungi was kept at a minimum.

Conclusions

The assembled genome will be a valuable resource and reference for future population genomics studies on the evolution and past climate change adaptation of beech and will be helpful for identifying genes, e.g., involved in drought tolerance, in order to select and breed individuals to adapt forestry to climate change in Europe. A continuously updated genome browser and download page can be accessed from beechgenome.net, which will include future genome versions of the reference individual Bhaga, as new sequencing approaches develop.

Quantifying temporal change in plant population attributes: insights from a resurrection approach

Rapid evolution in annual plants can be quantified by comparing phenotypic and genetic changes between past and contemporary individuals from the same populations over several generations. Such knowledge will help understand the response of plants to rapid environmental shifts, such as the ones imposed by global climate change. To that end, we undertook a resurrection approach in Spanish populations of the annual plant Arabidopsis thaliana that were sampled twice over a decade. Annual weather records were compared to their historical records to extract patterns of climatic shifts over time. We evaluated the differences between samplings in flowering time, a key life-history trait with adaptive significance, with a field experiment. We also estimated genetic diversity and differentiation based on neutral nuclear markers and nucleotide diversity in candidate flowering time (FRI and FLC) and seed dormancy (DOG1) genes. The role of genetic drift was estimated by computing effective population sizes with the temporal method. Overall, two climatic scenarios were detected: intense warming with increased precipitation and moderate warming with decreased precipitation. The average flowering time varied little between samplings. Instead, within-population variation in flowering time exhibited a decreasing trend over time. Substantial temporal changes in genetic diversity and differentiation were observed with both nuclear microsatellites and candidate genes in all populations, which were interpreted as the result of natural demographic fluctuations. We conclude that drought stress caused by moderate warming with decreased precipitation may have the potential to reduce within-population variation in key life-cycle traits, perhaps as a result of stabilizing selection on them, and to constrain the genetic differentiation over time. Besides, the demographic behaviour of populations probably accounts for the substantial temporal patterns of genetic variation, while keeping rather constant those of phenotypic variation.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

BACKGROUND

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.

RESULTS

To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation.

CONCLUSIONS

Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

Population Genomics of Herbicide Resistance: Adaptation via Evolutionary Rescue

The evolution of herbicide resistance in weed populations is a highly replicated example of adaptation surmounting the race against extinction, but the factors determining its rate and nature remain poorly understood. Here, we explore theory and empirical evidence for the importance of population genetic parameters-including effective population size, dominance, mutational target size, and gene flow-in influencing the probability and mode of herbicide resistance adaptation and its variation across species. We compiled data on the number of resistance mutations across populations for 79 herbicide-resistant species. Our findings are consistent with theoretical predictions that self-fertilization reduces resistance adaptation from standing variation within populations, but increases independent adaptation across populations. Furthermore, we provide evidence for a ploidy-mating system interaction that may reflect trade-offs in polyploids between increased effective population size and greater masking of beneficial mutations. We highlight the power of population genomic approaches to provide insights into the evolutionary dynamics of herbicide resistance with important implications for understanding the limits of adaptation.

Rapid evolution of aphid pests in agricultural environments

Aphids constitute a major group of crop pests that inflict serious damages to plants, both directly by ingesting phloem and indirectly as vectors of numerous diseases. In response to intense and repeated human-induced pressures, such as insecticide treatments, the use of resistant plants and biological agents, aphids have developed a series of evolutionary responses relying on adaptation and phenotypic plasticity. In this review, we highlight some remarkable evolutionary responses to anthropogenic pressures in agroecosystems and discuss the mechanisms underlying the ecological and evolutionary success of aphids. We outline the peculiar mode of reproduction, the polyphenism for biologically important traits and the diverse and flexible associations with microbial symbionts as key determinants of adaptive potential and pest status of aphids.

Multiple Modes of Positive Selection Shaping the Patterns of Incomplete Selective Sweeps over African Populations of Drosophila melanogaster

It remains a challenge in evolutionary genetics to elucidate how beneficial mutations arise and propagate in a population and how selective pressures on mutant alleles are structured over space and time. By identifying "sweeping haplotypes (SHs)" that putatively carry beneficial alleles and are increasing (or have increased) rapidly in frequency, and surveying the geographic distribution of SH frequencies, we can indirectly infer how selective sweeps unfold in time and thus which modes of positive selection underlie those sweeps. Using population genomic data from African Drosophila melanogaster, we identified SHs from 37 candidate loci under selection. At more than half of loci, we identify single SHs. However, many other loci harbor multiple independent SHs, namely soft selective sweeps, either due to parallel evolution across space or a high beneficial mutation rate. At about a quarter of the loci, intermediate SH frequencies are found across multiple populations, which cannot be explained unless a certain form of frequency-dependent positive selection, such as heterozygote advantage, is invoked given the reasonable range of migration rates between African populations. At one locus, many independent SHs are observed over multiple populations but always together with ancestral haplotypes. This complex pattern is compatible with a large number of mutational targets in a gene and frequency-dependent selection on new variants. We conclude that very diverse modes of positive selection are operating at different sets of loci in D. melanogaster populations.

Seven Billion Microcosms: Evolution within Human Microbiomes

Rational microbiome-based therapies may one day treat a wide range of diseases and promote wellness. Yet, we are still limited in our abilities to employ such therapies and to predict which bacterial strains have the potential to stably colonize a person. The Lieberman laboratory is working to close this knowledge gap and to develop an understanding of how individual species and strains behave in the human microbiome, including with regard to their niche ranges, survival strategies, and the degree to which they adapt to individual people. We employ system-level approaches, with a particular emphasis on using de novo mutations and evolutionary inference to reconstruct the history of bacterial lineages within individuals.

Modularity Facilitates Flexible Tuning of Plastic and Evolutionary Gene Expression Responses during Early Divergence

Gene expression changes have been recognized as important drivers of adaptation to changing environmental conditions. Little is known about the relative roles of plastic and evolutionary responses in complex gene expression networks during the early stages of divergence. Large gene expression data sets coupled with in silico methods for identifying coexpressed modules now enable systems genetics approaches also in nonmodel species for better understanding of gene expression responses during early divergence. Here, we combined gene coexpression analyses with population genetics to separate plastic and population (evolutionary) effects in expression networks using small salmonid populations as a model system. We show that plastic and population effects were highly variable among the six identified modules and that the plastic effects explained larger proportion of the total eigengene expression than population effects. A more detailed analysis of the population effects using a QST - FST comparison across 16,622 annotated transcripts revealed that gene expression followed neutral expectations within modules and at the global level. Furthermore, two modules showed enrichment for genes coding for early developmental traits that have been previously identified as important phenotypic traits in thermal responses in the same model system indicating that coexpression analysis can capture expression patterns underlying ecologically important traits. We suggest that module-specific responses may facilitate the flexible tuning of expression levels to local thermal conditions. Overall, our study indicates that plasticity and neutral evolution are the main drivers of gene expression variance in the early stages of thermal adaptation in this system.

The genetic architecture of ecological adaptation: intraspecific variation in host plant use by the lepidopteran crop pest Chloridea virescens

Intraspecific variation in ecologically important traits is a cornerstone of Darwin's theory of evolution by natural selection. The evolution and maintenance of this variation depends on genetic architecture, which in turn determines responses to natural selection. Some models suggest that traits with complex architectures are less likely to respond to selection than those with simple architectures, yet rapid divergence has been observed in such traits. The simultaneous evolutionary lability and genetic complexity of host plant use in the Lepidopteran subfamily Heliothinae suggest that architecture may not constrain ecological adaptation in this group. Here we investigate the response of Chloridea virescens, a generalist that feeds on diverse plant species, to selection for performance on a novel host, Physalis angulata (Solanaceae). P. angulata is the preferred host of Chloridea subflexa, a narrow specialist on the genus Physalis. In previous experiments, we found that the performance of C. subflexa on P. angulata depends on many loci of small effect distributed throughout the genome, but whether the same architecture would be involved in the generalist's adoption of P. angulata was unknown. Here we report a rapid response to selection in C. virescens for performance on P. angulata, and establish that the genetic architecture of intraspecific variation is quite similar to that of the interspecific differences in terms of the number, distribution, and effect sizes of the QTL involved. We discuss the impact of genetic architecture on the ability of Heliothine moths to respond to varying ecological selection pressures.

A soft selective sweep during rapid evolution of gentle behaviour in an Africanized honeybee

Highly aggressive Africanized honeybees (AHB) invaded Puerto Rico (PR) in 1994, displacing gentle European honeybees (EHB) in many locations. Gentle AHB (gAHB), unknown anywhere else in the world, subsequently evolved on the island within a few generations. Here we sequence whole genomes from gAHB and EHB populations, as well as a North American AHB population, a likely source of the founder AHB on PR. We show that gAHB retains high levels of genetic diversity after evolution of gentle behaviour, despite selection on standing variation. We observe multiple genomic loci with significant signatures of selection. Rapid evolution during colonization of novel habitats can generate major changes to characteristics such as morphological or colouration traits, usually controlled by one or more major genetic loci. Here we describe a soft selective sweep, acting at multiple loci across the genome, that occurred during, and may have mediated, the rapid evolution of a behavioural trait.

Africanized honey bees (AHB) are notoriously aggressive, but in Puerto Rico they have a ‘gentle’ phenotype. Here, Avalos et al. show that there has been a soft selective sweep at several loci in the Puerto Rican AHB population and suggest a role in the rapid evolution of gentle behaviour.

Duplications and Positive Selection Drive the Evolution of Parasitism-Associated Gene Families in the Nematode Strongyloides papillosus

Gene duplication is a major mechanism playing a role in the evolution of phenotypic complexity and in the generation of novel traits. By comparing parasitic and nonparasitic nematodes, a recent study found that the evolution of parasitism in Strongyloididae is associated with a large expansion in the Astacin and CAP gene families.To gain novel insights into the developmental processes in the sheep parasite Strongyloides papillosus, we sequenced transcriptomes of different developmental stages and sexes. Overall, we found that the majority of genes are developmentally regulated and have one-to-one orthologs in the diverged S. ratti genome. Together with the finding of similar expression profiles between S. papillosus and S. ratti, these results indicate a strong evolutionary constraint acting against change at sequence and expression levels. However, the comparison between parasitic and free-living females demonstrates a quite divergent pattern that is mostly due to the previously mentioned expansion in the Astacin and CAP gene families. More detailed phylogenetic analysis of both gene families shows that most members date back to single expansion events early in the Strongyloides lineage and have undergone subfunctionalization resulting in clusters that are highly expressed either in infective larvae or in parasitic females. Finally, we found increased evidence for positive selection in both gene families relative to the genome-wide expectation.In summary, our study reveals first insights into the developmental transcriptomes of S. papillosus and provides a detailed analysis of sequence and expression evolution in parasitism-associated gene families.

Directing evolution: the next revolution in drug discovery?

The strong biological rationale to pursue challenging drug targets such as protein-protein interactions has stimulated the development of novel screening strategies, such as DNA-encoded libraries, to allow broader areas of chemical space to be searched. There has also been renewed interest in screening natural products, which are the result of evolutionary selection for a function, such as interference with a key signalling pathway of a competing organism. However, recent advances in several areas, such as understanding of the biosynthetic pathways for natural products, synthetic biology and the development of biosensors to detect target molecules, are now providing new opportunities to directly harness evolutionary pressure to identify and optimize compounds with desired bioactivities. Here, we describe innovations in the key components of such strategies and highlight pioneering examples that indicate the potential of the directed-evolution concept. We also discuss the scientific gaps and challenges that remain to be addressed to realize this potential more broadly in drug discovery.

Biological function in the twilight zone of sequence conservation

Strong DNA conservation among divergent species is an indicator of enduring functionality. With weaker sequence conservation we enter a vast ‘twilight zone’ in which sequence subject to transient or lower constraint cannot be distinguished easily from neutrally evolving, non-functional sequence. Twilight zone functional sequence is illuminated instead by principles of selective constraint and positive selection using genomic data acquired from within a species’ population. Application of these principles reveals that despite being biochemically active, most twilight zone sequence is not functional.

Evidence and Consequence of a Highly Adapted Clonal Haplotype within the Australian Ascochyta rabiei Population

The Australian Ascochyta rabiei (Pass.) Labr. (syn. Phoma rabiei) population has low genotypic diversity with only one mating type detected to date, potentially precluding substantial evolution through recombination. However, a large diversity in aggressiveness exists. In an effort to better understand the risk from selective adaptation to currently used resistance sources and chemical control strategies, the population was examined in detail. For this, a total of 598 isolates were quasi-hierarchically sampled between 2013 and 2015 across all major Australian chickpea growing regions and commonly grown host genotypes. Although a large number of haplotypes were identified (66) through short sequence repeat (SSR) genotyping, overall low gene diversity (Hexp = 0.066) and genotypic diversity (D = 0.57) was detected. Almost 70% of the isolates assessed were of a single dominant haplotype (ARH01). Disease screening on a differential host set, including three commonly deployed resistance sources, revealed distinct aggressiveness among the isolates, with 17% of all isolates identified as highly aggressive. Almost 75% of these were of the ARH01 haplotype. A similar pattern was observed at the host level, with 46% of all isolates collected from the commonly grown host genotype Genesis090 (classified as "resistant" during the term of collection) identified as highly aggressive. Of these, 63% belonged to the ARH01 haplotype. In conclusion, the ARH01 haplotype represents a significant risk to the Australian chickpea industry, being not only widely adapted to the diverse agro-geographical environments of the Australian chickpea growing regions, but also containing a disproportionately large number of aggressive isolates, indicating fitness to survive and replicate on the best resistance sources in the Australian germplasm.

Adaptive Roles of SSY1 and SIR3 During Cycles of Growth and Starvation in Saccharomyces cerevisiae Populations Enriched for Quiescent or Nonquiescent Cells

Over its evolutionary history, Saccharomyces cerevisiae has evolved to be well-adapted to fluctuating nutrient availability. In the presence of sufficient nutrients, yeast cells continue to proliferate, but upon starvation haploid yeast cells enter stationary phase and differentiate into nonquiescent (NQ) and quiescent (Q) cells. Q cells survive stress better than NQ cells and show greater viability when nutrient-rich conditions are restored. To investigate the genes that may be involved in the differentiation of Q and NQ cells, we serially propagated yeast populations that were enriched for either only Q or only NQ cell types over many repeated growth–starvation cycles. After 30 cycles (equivalent to 300 generations), each enriched population produced a higher proportion of the enriched cell type compared to the starting population, suggestive of adaptive change. We also observed differences in each population’s fitness suggesting possible tradeoffs: clones from NQ lines were better adapted to logarithmic growth, while clones from Q lines were better adapted to starvation. Whole-genome sequencing of clones from Q- and NQ-enriched lines revealed mutations in genes involved in the stress response and survival in limiting nutrients (ECM21, RSP5, MSN1, SIR4, and IRA2) in both Q and NQ lines, but also differences between the two lines: NQ line clones had recurrent independent mutations affecting the Ssy1p-Ptr3p-Ssy5p (SPS) amino acid sensing pathway, while Q line clones had recurrent, independent mutations in SIR3 and FAS1. Our results suggest that both sets of enriched-cell type lines responded to common, as well as distinct, selective pressures.

When evolution is the solution to pollution: Key principles, and lessons from rapid repeated adaptation of killifish (Fundulus heteroclitus) populations

For most species, evolutionary adaptation is not expected to be sufficiently rapid to buffer the effects of human‐mediated environmental changes, including environmental pollution. Here we review how key features of populations, the characteristics of environmental pollution, and the genetic architecture underlying adaptive traits, may interact to shape the likelihood of evolutionary rescue from pollution. Large populations of Atlantic killifish (Fundulus heteroclitus) persist in some of the most contaminated estuaries of the United States, and killifish studies have provided some of the first insights into the types of genomic changes that enable rapid evolutionary rescue from complexly degraded environments. We describe how selection by industrial pollutants and other stressors has acted on multiple populations of killifish and posit that extreme nucleotide diversity uniquely positions this species for successful evolutionary adaptation. Mechanistic studies have identified some of the genetic underpinnings of adaptation to a well‐studied class of toxic pollutants; however, multiple genetic regions under selection in wild populations seem to reflect more complex responses to diverse native stressors and/or compensatory responses to primary adaptation. The discovery of these pollution‐adapted killifish populations suggests that the evolutionary influence of anthropogenic stressors as selective agents occurs widely. Yet adaptation to chemical pollution in terrestrial and aquatic vertebrate wildlife may rarely be a successful “solution to pollution” because potentially adaptive phenotypes may be complex and incur fitness costs, and therefore be unlikely to evolve quickly enough, especially in species with small population sizes.

Naturally acidified habitat selects for ocean acidification-tolerant mussels

Ocean acidification severely affects bivalves, especially their larval stages. Consequently, the fate of this ecologically and economically important group depends on the capacity and rate of evolutionary adaptation to altered ocean carbonate chemistry. We document successful settlement of wild mussel larvae (Mytilus edulis) in a periodically CO₂-enriched habitat. The larval fitness of the population originating from the CO₂-enriched habitat was compared to the response of a population from a nonenriched habitat in a common garden experiment. The high CO₂-adapted population showed higher fitness under elevated Pco₂ (partial pressure of CO₂) than the non-adapted cohort, demonstrating, for the first time, an evolutionary response of a natural mussel population to ocean acidification. To assess the rate of adaptation, we performed a selection experiment over three generations. CO₂ tolerance differed substantially between the families within the F₁ generation, and survival was drastically decreased in the highest, yet realistic, Pco₂ treatment. Selection of CO₂-tolerant F₁ animals resulted in higher calcification performance of F₂ larvae during early shell formation but did not improve overall survival. Our results thus reveal significant short-term selective responses of traits directly affected by ocean acidification and long-term adaptation potential in a key bivalve species. Because immediate response to selection did not directly translate into increased fitness, multigenerational studies need to take into consideration the multivariate nature of selection acting in natural habitats. Combinations of short-term selection with long-term adaptation in populations from CO₂-enriched versus nonenriched natural habitats represent promising approaches for estimating adaptive potential of organisms facing global change.