The probability of parallel genetic evolution from standing genetic variation

Parallel evolution is often assumed to result from repeated adaptation to novel, yet ecologically similar, environments. Here, we develop and analyse a mathematical model that predicts the probability of parallel genetic evolution from standing genetic variation as a function of the strength of phenotypic selection and constraints imposed by genetic architecture. Our results show that the probability of parallel genetic evolution increases with the strength of natural selection and effective population size and is particularly likely to occur for genes with large phenotypic effects. Building on these results, we develop a Bayesian framework for estimating the strength of parallel phenotypic selection from genetic data. Using extensive individual‐based simulations, we show that our estimator is robust across a wide range of genetic and evolutionary scenarios and provides a useful tool for rigorously testing the hypothesis that parallel genetic evolution is the result of adaptive evolution. An important result that emerges from our analyses is that existing studies of parallel genetic evolution frequently rely on data that is insufficient for distinguishing between adaptive evolution and neutral evolution driven by random genetic drift. Overcoming this challenge will require sampling more populations and the inclusion of larger numbers of loci.     

The Population and Evolutionary Dynamics of Homologous Gene Recombination in Bacteria

In bacteria, recombination is a rare event, not a part of the reproductive process. Nevertheless, recombination—broadly defined to include the acquisition of genes from external sources, i.e., horizontal gene transfer (HGT)—plays a central role as a source of variation for adaptive evolution in many species of bacteria. Much of niche expansion, resistance to antibiotics and other environmental stresses, virulence, and other characteristics that make bacteria interesting and problematic, is achieved through the expression of genes and genetic elements obtained from other populations of bacteria of the same and different species, as well as from eukaryotes and archaea. While recombination of homologous genes among members of the same species has played a central role in the development of the genetics and molecular biology of bacteria, the contribution of homologous gene recombination (HGR) to bacterial evolution is not at all clear. Also, not so clear are the selective pressures responsible for the evolution and maintenance of transformation, the only bacteria-encoded form of HGR. Using a semi-stochastic simulation of mutation, recombination, and selection within bacterial populations and competition between populations, we explore (1) the contribution of HGR to the rate of adaptive evolution in these populations and (2) the conditions under which HGR will provide a bacterial population a selective advantage over non-recombining or more slowly recombining populations. The results of our simulation indicate that, under broad conditions: (1) HGR occurring at rates in the range anticipated for bacteria like Streptococcus pneumoniae, Escherichia coli, Haemophilus influenzae, and Bacillus subtilis will accelerate the rate at which a population adapts to environmental conditions; (2) once established in a population, selection for this capacity to increase rates of adaptive evolution can maintain bacteria-encoded mechanisms of recombination and prevent invasion of non-recombining populations, even when recombination engenders a modest fitness cost; and (3) because of the density- and frequency-dependent nature of HGR in bacteria, this capacity to increase rates of adaptive evolution is not sufficient as a selective force to provide a recombining population a selective advantage when it is rare. Under realistic conditions, homologous gene recombination will increase the rate of adaptive evolution in bacterial populations and, once established, selection for higher rates of evolution will promote the maintenance of bacteria-encoded mechanisms for HGR. On the other hand, increasing rates of adaptive evolution by HGR is unlikely to be the sole or even a dominant selective pressure responsible for the original evolution of transformation.     

Trophic convergence drives morphological convergence in marine tetrapods

Marine tetrapod clades (e.g. seals, whales) independently adapted to marine life through the Mesozoic and Caenozoic, and provide iconic examples of convergent evolution. Apparent morphological convergence is often explained as the result of adaptation to similar ecological niches. However, quantitative tests of this hypothesis are uncommon. We use dietary data to classify the feeding ecology of extant marine tetrapods and identify patterns in skull and tooth morphology that discriminate trophic groups across clades. Mapping these patterns onto phylogeny reveals coordinated evolutionary shifts in diet and morphology in different marine tetrapod lineages. Similarities in morphology between species with similar diets—even across large phylogenetic distances—are consistent with previous hypotheses that shared functional constraints drive convergent evolution in marine tetrapods.     

No evidence of immediate fitness benefits of within-season divorce in monogamous birds

Individuals of socially monogamous species can correct for suboptimal partnerships via two secondary mating strategies: divorce and extra-pair mating, with the former potentially providing both genetic and social benefits. Divorcing between breeding seasons has been shown to be generally adaptive behaviour across monogamous birds. Interestingly, some pairs also divorce during the breeding season, when constraints on finding a new partner are stronger. Despite being important for a comprehensive understanding of the evolution of social monogamy, whether within-season divorce is adaptive and how it relates to extra-pair mating remains unknown. Here, we meta-analysed 90 effect sizes on within-season divorce and breeding success, extracted from 31 studies on 24 species. We found no evidence that within-season divorce is adaptive for breeding success. However, the large heterogeneity of effect sizes and strong phylogenetic signal suggest social and environmental factors—which have rarely been considered in empirical studies—may play an important role in explaining variation among populations and species. Furthermore, we found no evidence that within-season divorce and extra-pair mating are complementary strategies. We discuss our findings within the current evidence of the adaptiveness of secondary mating strategies and their interplay that ultimately shapes the evolution of social monogamy.     

Multiple convergent evolution of arboreal life in oribatid mites indicates the primacy of ecology

Frequent convergent evolution in phylogenetically unrelated taxa points to the importance of ecological factors during evolution, whereas convergent evolution in closely related taxa indicates the importance of favourable pre-existing characters (pre-adaptations). We investigated the transitions to arboreal life in oribatid mites (Oribatida, Acari), a group of mostly soil-living arthropods. We evaluated which general force—ecological factors, historical constraints or chance—was dominant in the evolution of arboreal life in oribatid mites. A phylogenetic study of 51 oribatid mite species and four outgroup taxa, using the ribosomal 18S rDNA region, indicates that arboreal life evolved at least 15 times independently. Arboreal oribatid mite species are not randomly distributed in the phylogenetic tree, but are concentrated among strongly sclerotized, sexual and evolutionary younger taxa. They convergently evolved a capitate sensillus, an anemoreceptor that either precludes overstimulation in the exposed bark habitat or functions as a gravity receptor. Sexual reproduction and strong sclerotization were important pre-adaptations for colonizing the bark of trees that facilitated the exploitation of living resources (e.g. lichens) and served as predator defence, respectively. Overall, our results indicate that ecological factors are most important for the observed pattern of convergent evolution of arboreal life in oribatid mites, supporting an adaptationist view of evolution.     

Adaptive and nonadaptive plasticity in changing environments: Implications for sexual species with different life history strategies

Populations adapt to novel environmental conditions by genetic changes or phenotypic plasticity. Plastic responses are generally faster and can buffer fitness losses under variable conditions. Plasticity is typically modeled as random noise and linear reaction norms that assume simple one‐to‐one genotype–phenotype maps and no limits to the phenotypic response. Most studies on plasticity have focused on its effect on population viability. However, it is not clear, whether the advantage of plasticity depends solely on environmental fluctuations or also on the genetic and demographic properties (life histories) of populations. Here we present an individual‐based model and study the relative importance of adaptive and nonadaptive plasticity for populations of sexual species with different life histories experiencing directional stochastic climate change. Environmental fluctuations were simulated using differentially autocorrelated climatic stochasticity or noise color, and scenarios of directional climate change. Nonadaptive plasticity was simulated as a random environmental effect on trait development, while adaptive plasticity as a linear, saturating, or sinusoidal reaction norm. The last two imposed limits to the plastic response and emphasized flexible interactions of the genotype with the environment. Interestingly, this assumption led to (a) smaller phenotypic than genotypic variance in the population (many‐to‐one genotype–phenotype map) and the coexistence of polymorphisms, and (b) the maintenance of higher genetic variation—compared to linear reaction norms and genetic determinism—even when the population was exposed to a constant environment for several generations. Limits to plasticity led to genetic accommodation, when costs were negligible, and to the appearance of cryptic variation when limits were exceeded. We found that adaptive plasticity promoted population persistence under red environmental noise and was particularly important for life histories with low fecundity. Populations producing more offspring could cope with environmental fluctuations solely by genetic changes or random plasticity, unless environmental change was too fast.     

Ethanol resistance in Drosophila melanogaster has increased in parallel cold‐adapted populations and shows a variable genetic architecture within and between populations

Understanding the genetic properties of adaptive trait evolution is a fundamental crux of biological inquiry that links molecular processes to biological diversity. Important uncertainties persist regarding the genetic predictability of adaptive trait change, the role of standing variation, and whether adaptation tends to result in the fixation of favored variants. Here, we use the recurrent evolution of enhanced ethanol resistance in Drosophila melanogaster during this species’ worldwide expansion as a promising system to add to our understanding of the genetics of adaptation. We find that elevated ethanol resistance has evolved at least three times in different cooler regions of the species’ modern range—not only at high latitude but also in two African high‐altitude regions. Applying a bulk segregant mapping framework, we find that the genetic architecture of ethanol resistance evolution differs substantially not only between our three resistant populations, but also between two crosses involving the same European population. We then apply population genetic scans for local adaptation within our quantitative trait locus regions, and we find potential contributions of genes with annotated roles in spindle localization, membrane composition, sterol and alcohol metabolism, and other processes. We also apply simulation‐based analyses that confirm the variable genetic basis of ethanol resistance and hint at a moderately polygenic architecture. However, these simulations indicate that larger‐scale studies will be needed to more clearly quantify the genetic architecture of adaptive evolution and to firmly connect trait evolution to specific causative loci.     

Diversification on an ecologically constrained adaptive landscape

We used phylogenetic analysis of body-size ecomorphs in a crustacean species complex to gain insight into how spatial complexity of ecological processes generates and maintains biological diversity. Studies of geographically widespread species of Hyalella amphipods show that phenotypic evolution is tightly constrained in a manner consistent with adaptive responses to alternative predation regimes. A molecular phylogeny indicates that evolution of Hyalella ecomorphs is characterized by parallel evolution and by phenotypic stasis despite substantial levels of underlying molecular change. The phylogeny suggests that species diversification sometimes occurs by niche shifts, and sometimes occurs without a change in niche. Moreover, diversification in the Hyalella ecomorphs has involved the repeated evolution of similar phenotypic forms that exist in similar ecological settings, a hallmark of adaptive evolution. The evolutionary stasis observed in clades separated by substantial genetic divergence, but existing in similar habitats, is also suggestive of stabilizing natural selection acting to constrain phenotypic evolution within narrow bounds. We interpret the observed decoupling of genetic and phenotypic diversification in terms of adaptive radiation on an ecologically constrained adaptive landscape, and suggest that ecological constraints, perhaps acting together with genetic and functional constraints, may explain the parallel evolution and evolutionary stasis inferred by the phylogeny.     

The repeatability of adaptive radiation during long-term experimental evolution of Escherichia coli in a multiple nutrient environment

Adaptive radiations occur when a species diversifies into different ecological specialists due to competition for resources and trade-offs associated with the specialization. The evolutionary outcome of an instance of adaptive radiation cannot generally be predicted because chance (stochastic events) and necessity (deterministic events) contribute to the evolution of diversity. With increasing contributions of chance, the degree of parallelism among different instances of adaptive radiations and the predictability of an outcome will decrease. To assess the relative contributions of chance and necessity during adaptive radiation, we performed a selection experiment by evolving twelve independent microcosms of Escherichia coli for 1000 generations in an environment that contained two distinct resources. Specialization to either of these resources involves strong trade-offs in the ability to use the other resource. After selection, we measured three phenotypic traits: 1) fitness, 2) mean colony size, and 3) colony size diversity. We used fitness relative to the ancestor as a measure of adaptation to the selective environment; changes in colony size as a measure of the evolution of new resource specialists because colony size has been shown to correlate with resource specialization; and colony size diversity as a measure of the evolved ecological diversity. Resource competition led to the rapid evolution of phenotypic diversity within microcosms. Measurements of fitness, colony size, and colony size diversity within and among microcosms showed that the repeatability of adaptive radiation was high, despite the evolution of genetic variation within microcosms. Consistent with the observation of parallel evolution, we show that the relative contributions of chance are far smaller and less important than effects due to adaptation for the traits investigated. The two-resource environment imposed similar selection pressures in independent populations and promoted parallel phenotypic adaptive radiations in all independently evolved microcosms.     

The probability of genetic parallelism and convergence in natural populations

Genomic and genetic methods allow investigation of how frequently the same genes are used by different populations during adaptive evolution, yielding insights into the predictability of evolution at the genetic level. We estimated the probability of gene reuse in parallel and convergent phenotypic evolution in nature using data from published studies. The estimates are surprisingly high, with mean probabilities of 0.32 for genetic mapping studies and 0.55 for candidate gene studies. The probability declines with increasing age of the common ancestor of compared taxa, from about 0.8 for young nodes to 0.1–0.4 for the oldest nodes in our study. Probability of gene reuse is higher when populations begin from the same ancestor (genetic parallelism) than when they begin from divergent ancestors (genetic convergence). Our estimates are broadly consistent with genomic estimates of gene reuse during repeated adaptation to similar environments, but most genomic studies lack data on phenotypic traits affected. Frequent reuse of the same genes during repeated phenotypic evolution suggests that strong biases and constraints affect adaptive evolution, resulting in changes at a relatively small subset of available genes. Declines in the probability of gene reuse with increasing age suggest that these biases diverge with time.     

Evaluating the within-host fitness effects of mutations fixed during virus adaptation to different ecotypes of a new host

The existence of genetic variation for resistance in host populations is assumed to be essential to the spread of an emerging virus. Models predict that the rate of spread slows down with the increasing frequency and higher diversity of resistance alleles in the host population. We have been using the experimental pathosystem Arabidopsis thaliana—tobacco etch potyvirus (TEV) to explore the interplay between genetic variation in host''s susceptibility and virus diversity. We have recently shown that TEV populations evolving in A. thaliana ecotypes that differ in susceptibility to infection gained within-host fitness, virulence and infectivity in a manner compatible with a gene-for-gene model of host–parasite interactions: hard-to-infect ecotypes were infected by generalist viruses, whereas easy-to-infect ecotypes were infected by every virus. We characterized the genomes of the evolved viruses and found cases of host-driven convergent mutations. To gain further insights in the mechanistic basis of this gene-for-gene model, we have generated all viral mutations individually as well as in specific combinations and tested their within-host fitness effects across ecotypes. Most of these mutations were deleterious or neutral in their local ecotype and only a very reduced number had a host-specific beneficial effect. We conclude that most of the mutations fixed during the evolution experiment were so by drift or by selective sweeps along with the selected driver mutation. In addition, we evaluated the ruggedness of the underlying adaptive fitness landscape and found that mutational effects were mostly multiplicative, with few cases of significant epistasis.     

Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions—drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors—pyrimethamine and cycloguanil—across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary “forks in the road” that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC₅₀ and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance.     

Genetic Variation in Heterogeneous Environments

A model of population structure in heterogeneous environments is described and conditions sufficient for maintaining a polymorphism are derived.

The absolute fitness of any genotype is regarded as a function of location in the niche space and the population density at that location. Two modes of habitat selection are examined: (1) organisms are distributed uniformly over the environment; and (2) each organism selects to occupy that habitat in which it is most fit ("optimal habitant selection").—Sufficient conditions for maintenance of genetic polymorphisms are derived for both models. In populations which do not practice habitat selection heterozygote superiority averaged over the environment is sufficient to guarantee the existence of polymorphisms. Comparable conditions for populations which practice optimal habitat selection are much less restrictive. If the heterozygotes are superior to one homozygote in any one part of the niche and to the other homozygote in any other part of the niche then a polymorphism will be defined.—A positive correlation between genetic and environmental variation follows from the model with habitat selection, but not from the other. The adaptive significance of polymorphisms thus depends on how animals behave.

     

Temporal variation can facilitate niche evolution in harsh sink environments

We examine the impact of temporal variation on adaptive evolution in "sink" environments, where a species encounters conditions outside its niche. Sink populations persist because of recurrent immigration from sources. Prior studies have highlighted the importance of demographic constraints on adaptive evolution in sinks and revealed that adaptation is less likely in harsher sinks. We examine two complementary models of population and evolutionary dynamics in sinks: a continuous-state quantitative-genetics model and an individual-based model. In the former, genetic variance is fixed; in the latter, genetic variance varies because of mutation, drift, and sampling. In both models, a population in a constant harsh sink environment can exist in alternative states: local maladaptation (phenotype comparable to immigrants from the source) or adaptation (phenotype near the local optimum). Temporal variation permits transitions between these states. We show that moderate amounts of temporal variation can facilitate adaptive evolution in sinks, permitting niche evolution, particularly for slow or autocorrelated variation. Such patterns of temporal variation may particularly pertain to sinks caused by biotic interactions (e.g., predation). Our results are relevant to the evolutionary dynamics of species' ranges, the fate of exotic invasive species, and the evolutionary emergence of infectious diseases into novel hosts.     

The importance of evolutionary constraints in ecological time scales

Summary The importance of constraints, defined as factors that retard or prevent a population from reaching its immediate adaptive peak on an ecological time scale is analysed. This is done by means of simple quantitative genetic models, which if anything underestimate the importance of constraints. The results show that even in the simplest case the response to selection will not generally be in the same direction as the selection vector, i.e. the direction to the nearest optimum. Adding complexity identifies cases where selection may lead the population in suboptimal directions. It is concluded that information about univariate genetic variances is not sufficient to predict evolutionary responses and may even be misleading. However, genetic covariances are not always acting as constraints, but can under certain circumstances promote evolution towards the nearest optimum. This can be understood by a spectral decomposition of the genetic variance—covariance matrix, where it is shown that the eigenvector associated with the largest amount of variance will to various degrees determine the outcome of selection. A literature survey of the pattern of character covariation in morphological characters in natural populations shows a wide variety of correlation patterns, but quite often shows a high level of covariance between traits. This suggests that constraints to short-term evolution may be more common than generally appreciated.     

Trait Associations across Evolutionary Time within a Drosophila Phylogeny: Correlated Selection or Genetic Constraint?

Traits do not evolve independently. To understand how trait changes under selection might constrain adaptive changes, phenotypic and genetic correlations are typically considered within species, but these capture constraints across a few generations rather than evolutionary time. For longer-term constraints, comparisons are needed across species but associations may arise because of correlated selection pressures rather than genetic interactions. Implementing a unique approach, we use known patterns of selection to separate likely trait correlations arising due to correlated selection from those reflecting genetic constraints. We examined the evolution of stress resistance in >90 Drosophila species adapted to a range of environments, while controlling for phylogeny. Initially we examined the role of climate and phylogeny in shaping the evolution of starvation and body size, two traits previously not examined in this context. Following correction for phylogeny only a weak relationship between climate and starvation resistance was detected, while all of the variation in the relationship between body size and climate could be attributed to phylogeny. Species were divided into three environmental groups (hot and dry, hot and wet, cold) with the expectation that, if genetic correlations underpin trait correlations, these would persist irrespective of the environment, whereas selection-driven evolution should produce correlations dependent on the environment. We found positive associations between most traits in hot and dry environments coupled with high trait means. In contrast few trait correlations were observed in hot/wet and cold environments. These results suggest trait associations are primarily driven by correlated selection rather than genetic interactions, highlighting that such interactions are unlikely to limit evolution of stress resistance.     

A Mutational Hotspot and Strong Selection Contribute to the Order of Mutations Selected for during Escherichia coli Adaptation to the Gut

The relative role of drift versus selection underlying the evolution of bacterial species within the gut microbiota remains poorly understood. The large sizes of bacterial populations in this environment suggest that even adaptive mutations with weak effects, thought to be the most frequently occurring, could substantially contribute to a rapid pace of evolutionary change in the gut. We followed the emergence of intra-species diversity in a commensal Escherichia coli strain that previously acquired an adaptive mutation with strong effect during one week of colonization of the mouse gut. Following this first step, which consisted of inactivating a metabolic operon, one third of the subsequent adaptive mutations were found to have a selective effect as high as the first. Nevertheless, the order of the adaptive steps was strongly affected by a mutational hotspot with an exceptionally high mutation rate of 10⁻⁵. The pattern of polymorphism emerging in the populations evolving within different hosts was characterized by periodic selection, which reduced diversity, but also frequency-dependent selection, actively maintaining genetic diversity. Furthermore, the continuous emergence of similar phenotypes due to distinct mutations, known as clonal interference, was pervasive. Evolutionary change within the gut is therefore highly repeatable within and across hosts, with adaptive mutations of selection coefficients as strong as 12% accumulating without strong constraints on genetic background. In vivo competitive assays showed that one of the second steps (focA) exhibited positive epistasis with the first, while another (dcuB) exhibited negative epistasis. The data shows that strong effect adaptive mutations continuously recur in gut commensal bacterial species.     

Segregational Drift Constrains the Evolutionary Rate of Prokaryotic Plasmids

Plasmids are extrachromosomal genetic elements in prokaryotes that have been recognized as important drivers of microbial ecology and evolution. Plasmids are found in multiple copies inside their host cell where independent emergence of mutations may lead to intracellular genetic heterogeneity. The intracellular plasmid diversity is thus subject to changes upon cell division. However, the effect of plasmid segregation on plasmid evolution remains understudied. Here, we show that genetic drift during cell division—segregational drift—leads to the rapid extinction of novel plasmid alleles. We established a novel experimental approach to control plasmid allele frequency at the levels of a single cell and the whole population. Following the dynamics of plasmid alleles in an evolution experiment, we find that the mode of plasmid inheritance—random or clustered—is an important determinant of plasmid allele dynamics. Phylogenetic reconstruction of our model plasmid in clinical isolates furthermore reveals a slow evolutionary rate of plasmid-encoded genes in comparison to chromosomal genes. Our study provides empirical evidence that genetic drift in plasmid evolution occurs at multiple levels: the host cell and the population of hosts. Segregational drift has implications for the evolutionary rate heterogeneity of extrachromosomal genetic elements.     

Exploiting Genetic Interference for Antiviral Therapy

Rapidly evolving viruses are a major threat to human health. Such viruses are often highly pathogenic (e.g., influenza virus, HIV, Ebola virus) and routinely circumvent therapeutic intervention through mutational escape. Error-prone genome replication generates heterogeneous viral populations that rapidly adapt to new selection pressures, leading to resistance that emerges with treatment. However, population heterogeneity bears a cost: when multiple viral variants replicate within a cell, they can potentially interfere with each other, lowering viral fitness. This genetic interference can be exploited for antiviral strategies, either by taking advantage of a virus’s inherent genetic diversity or through generating de novo interference by engineering a competing genome. Here, we discuss two such antiviral strategies, dominant drug targeting and therapeutic interfering particles. Both strategies harness the power of genetic interference to surmount two particularly vexing obstacles—the evolution of drug resistance and targeting therapy to high-risk populations—both of which impede treatment in resource-poor settings.