Dynamics of genomic change during evolutionary rescue in the seed beetle Callosobruchus maculatus

Impacts of limits to adaptation on population and community persistence in a changing environment

A key issue in predicting how ecosystems will respond to environmental change is understanding why populations and communities are able to live and reproduce in some parts of ecological and geographical space, but not in others. The limits to adaptation that cause ecological niches to vary in position and width across taxa and environmental contexts determine how communities and ecosystems emerge from selection on phenotypes and genomes. Ecological trade-offs mean that phenotypes can only be optimal in some environments unless these trade-offs can be reshaped through evolution. However, the amount and rate of evolution are limited by genetic architectures, developmental systems (including phenotypic plasticity) and the legacies of recent evolutionary history. Here, we summarize adaptive limits and their ecological consequences in time (evolutionary rescue) and space (species' range limits), relating theoretical predictions to empirical tests. We then highlight key avenues for future research in this area, from better connections between evolution and demography to analysing the genomic architecture of adaptation, the dynamics of plasticity and interactions between the biotic and abiotic environment. Progress on these questions will help us understand when and where evolution and phenotypic plasticity will allow species and communities to persist in the face of rapid environmental change.This article is part of the discussion meeting issue 'Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future'.

Transcriptional signature of host shift in the seed beetle Zabrotes subfasciatus

In phytophagous insects, adaptation to a new host is a dynamic process, in which early and later steps may be underpinned by different features of the insect genome. Here, we tested the hypothesis that early steps of this process are underpinned by a shift in gene expression patterns. We set up a short-term artificial selection experiment (10 generations) for the use of an alternative host (Cicer arietinum) on populations of the bean beetle Zabrotes subfasciatus. Using Illumina sequencing on young adult females, we show the selected populations differ in the expression of genes associated to stimuli, signalling, and developmental processes. Particularly, the "C. arietinum" population shows upregulation of histone methylation genes, which may constitute a strategy for fine-tuning the insect global gene expression network. Using qPCR on body regions, we demonstrated that the "Phaseolus vulgaris" population upregulates the genes polygalacturonase and egalitarian and that the expression of an odorant receptor transcript variant changes over generations. Moreover, in this population we detected the existence of vitellogenin (Vg) variants in both males and females, possibly harbouring canonical reproductive function in females and extracellular unknown functions in males. This study provides the basis for future genomic investigations seeking to shed light on the nature of the proximate mechanisms involved in promoting differential gene expression associated to insect development and adaptation to new hosts.

How density dependence, genetic erosion and the extinction vortex impact evolutionary rescue

Following severe environmental change that reduces mean population fitness below replacement, populations must adapt to avoid eventual extinction, a process called evolutionary rescue. Models of evolutionary rescue demonstrate that initial size, genetic variation and degree of maladaptation influence population fates. However, many models feature populations that grow without negative density dependence or with constant genetic diversity despite precipitous population decline, assumptions likely to be violated in conservation settings. We examined the simultaneous influences of density-dependent growth and erosion of genetic diversity on populations adapting to novel environmental change using stochastic, individual-based simulations. Density dependence decreased the probability of rescue and increased the probability of extinction, especially in large and initially well-adapted populations that previously have been predicted to be at low risk. Increased extinction occurred shortly following environmental change, as populations under density dependence experienced more rapid decline and reached smaller sizes. Populations that experienced evolutionary rescue lost genetic diversity through drift and adaptation, particularly under density dependence. Populations that declined to extinction entered an extinction vortex, where small size increased drift, loss of genetic diversity and the fixation of maladaptive alleles, hindered adaptation and kept populations at small densities where they were vulnerable to extinction via demographic stochasticity.

Contrasting adaptive genetic consequences of stream insects under changing climate

Freshwater biodiversity undergoes degradation due to climate change. Researchers have inferred the effects of climate change on neutral genetic diversity, assuming the fixed spatial distributions of alleles. However, the adaptive genetic evolution of populations that may change the spatial distribution of allele frequencies along environmental gradients (i.e., evolutionary rescue) have largely been overlooked. We developed a modeling approach that projects the comparatively adaptive and neutral genetic diversities of four stream insects, using empirical neutral/ putative adaptive loci, ecological niche models (ENMs), and a distributed hydrological-thermal simulation at a temperate catchment under climate change. The hydrothermal model was used to generate hydraulic and thermal variables (e.g., annual current velocity and water temperature) at the present and the climatic change conditions, projected based on the eight general circulation models and the three representative concentration pathways scenarios for the two future periods (2031-2050, near future; 2081-2100, far future). The hydraulic and thermal variables were used for predictor variables of the ENMs and adaptive genetic modeling based on machine learning approaches. The increases in annual water temperature in the near- (+0.3-0.7 °C) and far-future (+0.4-3.2 °C) were projected. Of the studied species, with different ecologies and habitat ranges, Ephemera japonica (Ephemeroptera) was projected to lose rear-edge habitats (i.e., downstream) but retain the adaptive genetic diversity owing to evolutionary rescue. In contrast, the habitat range of the upstream-dwelling Hydropsyche albicephala (Trichoptera) was found to remarkably decline, resulting in decreases in the watershed genetic diversity. While the other two Trichoptera species expanded their habitat ranges, the genetic structures were homogenized over the watershed and experienced moderate decreases in gamma diversity. The findings emphasize the evolutionary rescue potential, depending on the extent of species-specific local adaptation.

Laplace's demon in biology: Models of evolutionary prediction

Our ability to predict natural phenomena can be limited by incomplete information. This issue is exemplified by "Laplace's demon," an imaginary creature proposed in the 18th century, who knew everything about everything, and thus could predict the full nature of the universe forward or backward in time. Quantum mechanics, among other things, has cast doubt on the possibility of Laplace's demon in the full sense, but the idea still serves as a useful metaphor for thinking about the extent to which prediction is limited by incomplete information on deterministic processes versus random factors. Here, we use simple analytical models and computer simulations to illustrate how data limits can be captured in a Bayesian framework, and how they influence our ability to predict evolution. We show how uncertainty in measurements of natural selection, or low predictability of external environmental factors affecting selection, can greatly reduce predictive power, often swamping the influence of intrinsic randomness caused by genetic drift. Thus, more accurate knowledge concerning the causes and action of natural selection is key to improving prediction. Fortunately, our analyses and simulations show quantitatively that reasonable improvements in data quantity and quality can meaningfully increase predictability.

Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation

Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Because genetic redundancy often results in nonparallel selection responses among replicates, we propose a modified evolve and resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29 °C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Because two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.

A branching process model of evolutionary rescue

Evolutionary rescue is the process whereby a declining population may start growing again, thus avoiding extinction, via an increase in the frequency of fitter genotypes. These genotypes may either already be present in the population in small numbers, or arise by mutation as the population declines. We present a simple two-type discrete-time branching process model and use it to obtain results such as the probability of rescue, the shape of the population growth curve of a rescued population, and the time until the first rescuing mutation occurs. Comparisons are made to existing results in the literature in cases where both the mutation rate and the selective advantage of the beneficial mutations are small.

Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species

Effective population size affects the efficacy of selection, rate of evolution by drift, and neutral diversity levels. When species are subdivided into multiple populations connected by gene flow, evolutionary processes can depend on global or local effective population sizes. Theory predicts that high levels of diversity might be maintained by gene flow, even very low levels of gene flow, consistent with species long-term effective population size, but tests of this idea are mostly lacking. Here, we show that Lycaeides buttery populations maintain low contemporary (variance) effective population sizes (e.g., ~200 individuals) and thus evolve rapidly by genetic drift. In contrast, populations harbored high levels of genetic diversity consistent with an effective population size several orders of magnitude larger. We hypothesized that the differences in the magnitude and variability of contemporary versus long-term effective population sizes were caused by gene flow of sufficient magnitude to maintain diversity but only subtly affect evolution on generational time scales. Consistent with this hypothesis, we detected low but non-trivial gene flow among populations. Furthermore, using short-term population-genomic time-series data, we documented patterns consistent with predictions from this hypothesis, including a weak but detectable excess of evolutionary change in the direction of the mean (migrant gene pool) allele frequencies across populations, and consistency in the direction of allele frequency change over time. The documented decoupling of diversity levels and short-term change by drift in Lycaeides has implications for our understanding of contemporary evolution and the maintenance of genetic variation in the wild.

Direct and indirect effects of male genital elaboration in female seed beetles

Our understanding of coevolution between male genitalia and female traits remains incomplete. This is perhaps especially true for genital traits that cause internal injuries in females, such as the spiny genitalia of seed beetles where males with relatively long spines enjoy a high relative fertilization success. We report on a new set of experiments, based on extant selection lines, aimed at assessing the effects of long male spines on females in Callosobruchus maculatus. We first draw on an earlier study using microscale laser surgery, and demonstrate that genital spines have a direct negative (sexually antagonistic) effect on female fecundity. We then ask whether artificial selection for long versus short spines resulted in direct or indirect effects on female lifetime offspring production. Reference females mating with males from long-spine lines had higher offspring production, presumably due to an elevated allocation in males to those ejaculate components that are beneficial to females. Remarkably, selection for long male genital spines also resulted in an evolutionary increase in female offspring production as a correlated response. Our findings thus suggest that female traits that affect their response to male spines are both under direct selection to minimize harm but are also under indirect selection (a good genes effect), consistent with the evolution of mating and fertilization biases being affected by several simultaneous processes.

Standing genetic variation in laboratory populations of insecticide-susceptible Phlebotomus papatasi and Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae) for the evolution of resistance

Insecticides can exert strong selection on insect pest species, including those that vector diseases, and have led to rapid evolution of resistance. Despite such rapid evolution, relatively little is known about standing genetic variation for resistance in insecticide-susceptible populations of many species. To help fill this knowledge gap, we generated genotyping-by-sequencing data from insecticide-susceptible Phlebotomus papatasi and Lutzomyia longipalpis sand flies that survived or died from a sub-diagnostic exposure to either permethrin or malathion using a modified version of the Centers for Disease Control and Prevention bottle bioassay. Multi-locus genome-wide association mapping methods were used to quantify standing genetic variation for insecticide resistance in these populations and to identify specific alleles associated with insecticide survival. For each insecticide treatment, we estimated the proportion of the variation in survival explained by the genetic data (i.e., "chip" heritability) and the number and contribution of individual loci with measurable effects. For all treatments, survival to an insecticide exposure was heritable with a polygenic architecture. Both P. papatasi and L. longipalpis had alleles for survival that resided within many genes throughout their genomes. The implications for resistance conferred by many alleles, as well as inferences made about the utility of laboratory insecticide resistance association studies compared to field observations, are discussed.

A population-genomic approach for estimating selection on polygenic traits in heterogeneous environments

Strong selection can cause rapid evolutionary change, but temporal fluctuations in the form, direction and intensity of selection can limit net evolutionary change over longer time periods. Fluctuating selection could affect molecular diversity levels and the evolution of plasticity and ecological specialization. Nonetheless, this phenomenon remains understudied, in part because of analytical limitations and the general difficulty of detecting selection that does not occur in a consistent manner. Herein, I fill this analytical gap by presenting an approximate Bayesian computation (ABC) method to detect and quantify fluctuating selection on polygenic traits from population genomic time-series data. I propose a model for environment-dependent phenotypic selection. The evolutionary genetic consequences of selection are then modelled based on a genotype-phenotype map. Using simulations, I show that the proposed method generates accurate and precise estimates of selection when the generative model for the data is similar to the model assumed by the method. The performance of the method when applied to an evolve-and-resequence study of host adaptation in the cowpea seed beetle (Callosobruchus maculatus) was more idiosyncratic and depended on specific analytical choices. Despite some limitations, these results suggest the proposed method provides a powerful approach to connect the causes of (variable) selection to traits and genome-wide patterns of evolution. Documentation and open-source computer software (fsabc) implementing this method are available from github (https://github.com/zgompert/fsabc.git).

Rapid genomic and phenotypic change in response to climate warming in a widespread plant invader

Predicting plant distributions under climate change is constrained by our limited understanding of potential rapid adaptive evolution. In an experimental evolution study with the invasive common ragweed (Ambrosia artemisiifolia L.) we subjected replicated populations of the same initial genetic composition to simulated climate warming. Pooled DNA sequencing of parental and offspring populations showed that warming populations experienced greater genetic divergence from their parents, than control populations. In a common environment, offspring from warming populations showed more convergent phenotypes in seven out of nine plant traits, with later flowering and larger biomass, than plants from control populations. For both traits, we also found a significantly higher ratio of phenotypic to genetic differentiation across generations for warming than for control populations, indicating stronger response to selection under warming conditions. As a measure for evolutionary rate, the phenotypic and sequence divergence between generations were assessed using the Haldane metric. Our approach combining comparisons between generations (allochronic) and between treatments (synchronic) in an experimental evolutionary field study, and linking population genomic data with phenotyping analyses provided a powerful test to detect rapid responses to selection. Our findings demonstrate that ragweed populations can rapidly evolve in response to climate change within a single generation. Short-term evolutionary responses to climate change may aggravate the impact of some plant invaders in the future and should be considered when making predictions about future distributions and impacts of plant invaders.

Low concordance of short-term and long-term selection responses in experimental Drosophila populations

Experimental evolution is becoming a popular approach to study the genomic selection response of evolving populations. Computer simulation studies suggest that the accuracy of the signature increases with the duration of the experiment. Since some assumptions of the computer simulations may be violated, it is important to scrutinize the influence of the experimental duration with real data. Here, we use a highly replicated Evolve and Resequence study in Drosophila simulans to compare the selection targets inferred at different time points. At each time point, approximately the same number of SNPs deviates from neutral expectations, but only 10% of the selected haplotype blocks identified from the full data set can be detected after 20 generations. Those haplotype blocks that emerge already after 20 generations differ from the others by being strongly selected at the beginning of the experiment and display a more parallel selection response. Consistent with previous computer simulations, our results demonstrate that only Evolve and Resequence experiments with a sufficient number of generations can characterize complex adaptive architectures.

Colonization of Marginal Host Plants by Seed Beetles (Coleoptera: Chrysomelidae): Effects of Geographic Source and Genetic Admixture

The ability to adapt to a novel host plant may vary among insect populations with different genetic histories, and colonization of a marginal host may be facilitated by genetic admixture of disparate populations. We assembled populations of the seed beetle, Callosobruchus maculatus (F.), from four continents, and compared their ability to infest two hosts, lentil and pea. We also formed two cross-continent hybrids (Africa × N.A. and Africa × S.A.). In pre-selection assays, survival was only ~3% in lentil and ~40% in pea. For three replicate populations per line, colonization success on lentil was measured as cumulative exit holes after 75-175 d. On pea, we estimated the change in larval survival after five generations of selection. Females in all lines laid few eggs on lentil, and survival of F1 larvae was uniformly <5%. Subsequently, however, the lines diverged considerably in population growth. Performance on lentil was highest in the Africa × N.A. hybrid, which produced far more adults (mean > 11,000) than either parental line. At the other extreme, Asian populations on lentil appeared to have gone extinct. The Africa × N.A. line also exhibited the highest survival on pea, and again performed better than either parent line. However, no line displayed a rapid increase in survival on pea, as is sometimes observed on lentil. Our results demonstrate that geographic populations can vary substantially in their responses to the same novel resource. In addition, genetic admixtures (potentially caused by long-distance transport of infested seeds) may facilitate colonization of an initially poor host.

Genetic Signatures of Evolutionary Rescue by a Selective Sweep

One of the most useful models in population genetics is that of a selective sweep and the consequent hitch-hiking of linked neutral alleles. While variations on this model typically assume constant population size, many instances of strong selection and rapid adaptation in nature may co-occur with complex demography. Here, we extend the hitch-hiking model to evolutionary rescue, where adaptation and demography not only co-occur but are intimately entwined. Our results show how this feedback between demography and evolution determines-and restricts-the genetic signatures of evolutionary rescue, and how these differ from the signatures of sweeps in populations of constant size. In particular, we find rescue to harden sweeps from standing variance or new mutation (but not from migration), reduce genetic diversity both at the selected site and genome-wide, and increase the range of observed Tajima's D values. For a given initial rate of population decline, the feedback between demography and evolution makes all of these differences more dramatic under weaker selection, where bottlenecks are prolonged. Nevertheless, it is likely difficult to infer the co-incident timing of the sweep and bottleneck from these simple signatures, never mind a feedback between them. Temporal samples spanning contemporary rescue events may offer one way forward.

Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

How to better predict long-term benefits and risks in weed biocontrol: an evolutionary perspective

Classical biological control (also called importation biological control) of weeds has a remarkable track record for efficiency and safety, but further improvement is still needed, particularly to account for potential evolutionary changes after release. Here, we discuss the increasing yet limited evidence of post-introduction evolution and describe approaches to predict evolutionary change. Recent advances include using experimental evolution studies over several generations that combine -omics tools with behavioral bioassays. This novel approach in weed biocontrol is well suited to explore the potential for rapid evolutionary change in real-time and thus can be used to estimate more accurately potential benefits and risks of agents before their importation. We outline this approach with a chrysomelid beetle used to control invasive common ragweed.