Genetic redundancy fuels polygenic adaptation in Drosophila

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive-not negative-selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.

Threespine Stickleback: A Model System For Evolutionary Genomics

The repeated adaptation of oceanic threespine sticklebacks to fresh water has made it a premier organism to study parallel evolution. These small fish have multiple distinct ecotypes that display a wide range of diverse phenotypic traits. Ecotypes are easily crossed in the laboratory, and families are large and develop quickly enough for quantitative trait locus analyses, positioning the threespine stickleback as a versatile model organism to address a wide range of biological questions. Extensive genomic resources, including linkage maps, a high-quality reference genome, and developmental genetics tools have led to insights into the genomic basis of adaptation and the identification of genomic changes controlling traits in vertebrates. Recently, threespine sticklebacks have been used as a model system to identify the genomic basis of highly complex traits, such as behavior and host-microbiome and host-parasite interactions. We review the latest findings and new avenues of research that have led the threespine stickleback to be considered a supermodel of evolutionary genomics.

How will mosquitoes adapt to climate warming?

The potential for adaptive evolution to enable species persistence under a changing climate is one of the most important questions for understanding impacts of future climate change. Climate adaptation may be particularly likely for short-lived ectotherms, including many pest, pathogen, and vector species. For these taxa, estimating climate adaptive potential is critical for accurate predictive modeling and public health preparedness. Here, we demonstrate how a simple theoretical framework used in conservation biology-evolutionary rescue models-can be used to investigate the potential for climate adaptation in these taxa, using mosquito thermal adaptation as a focal case. Synthesizing current evidence, we find that short mosquito generation times, high population growth rates, and strong temperature-imposed selection favor thermal adaptation. However, knowledge gaps about the extent of phenotypic and genotypic variation in thermal tolerance within mosquito populations, the environmental sensitivity of selection, and the role of phenotypic plasticity constrain our ability to make more precise estimates. We describe how common garden and selection experiments can be used to fill these data gaps. Lastly, we investigate the consequences of mosquito climate adaptation on disease transmission using Aedes aegypti-transmitted dengue virus in Northern Brazil as a case study. The approach outlined here can be applied to any disease vector or pest species and type of environmental change.

Sexual antagonism, temporally fluctuating selection, and variable dominance affect a regulatory polymorphism in Drosophila melanogaster

Understanding how genetic variation is maintained within species is a major goal of evolutionary genetics that can shed light on the preservation of biodiversity. Here, we examined the maintenance of a regulatory single-nucleotide polymorphism (SNP) of the X-linked Drosophila melanogaster gene fezzik. The derived variant at this site is at intermediate frequency in many worldwide populations but absent in populations from the ancestral species range in sub-Saharan Africa. We collected and genotyped wild-caught individuals from a single European population biannually over a period of 5 years, which revealed an overall difference in allele frequency between the sexes and a consistent change in allele frequency across seasons in females but not in males. Modeling based on the observed allele and genotype frequencies suggested that both sexually antagonistic and temporally fluctuating selection may help maintain variation at this site. The derived variant is predicted to be female-beneficial and mostly recessive; however, there was uncertainty surrounding our dominance estimates and long-term modeling projections suggest that it is more likely to be dominant. By examining gene expression phenotypes, we found that phenotypic dominance was variable and dependent upon developmental stage and genetic background, suggesting that dominance may be variable at this locus. We further determined that fezzik expression and genotype are associated with starvation resistance in a sex-dependent manner, suggesting a potential phenotypic target of selection. By characterizing the mechanisms of selection acting on this SNP, our results improve our understanding of how selection maintains genetic and phenotypic variation in natural populations.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

BACKGROUND

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures-either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

RESULTS

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

CONCLUSIONS

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Genomic Responses to Climate Change: Making the Most of the Drosophila Model

It is pressing to understand how animal populations evolve in response to climate change. We argue that new sequencing technologies and the use of historical samples are opening unprecedented opportunities to investigate genome-wide responses to changing environments. However, there are important challenges in interpreting the emerging findings. First, it is essential to differentiate genetic adaptation from phenotypic plasticity. Second, it is extremely difficult to map genotype, phenotype, and fitness. Third, neutral demographic processes and natural selection affect genetic variation in similar ways. We argue that Drosophila melanogaster, a classical model organism with decades of climate adaptation research, is uniquely suited to overcome most of these challenges. In the near future, long-term time series genome-wide datasets of D. melanogaster natural populations will provide exciting opportunities to study adaptation to recent climate change and will lay the groundwork for related research in non-model systems.

Adaptation and correlated fitness responses over two time scales in Drosophila suzukii populations evolving in different environments

The process of local adaptation involves differential changes in fitness over time across different environments. Although experimental evolution studies have extensively tested for patterns of local adaptation at a single time point, there is relatively little research that examines fitness more than once during the time course of adaptation. We allowed replicate populations of the fruit pest Drosophila suzukii to evolve in one of eight different fruit media. After five generations, populations with the highest initial levels of maladaptation had mostly gone extinct, whereas experimental populations evolving on cherry, strawberry and cranberry media had survived. We measured the fitness of each surviving population in each of the three fruit media after five and after 26 generations of evolution. After five generations, adaptation to each medium was associated with increased fitness in the two other media. This was also true after 26 generations, except when populations that evolved on cranberry medium developed on cherry medium. These results suggest that, in the theoretical framework of a fitness landscape, the fitness optima of cherry and cranberry media are the furthest apart. Our results show that studying how fitness changes across several environments and across multiple generations provides insights into the dynamics of local adaptation that would not be evident if fitness were analysed at a single point in time. By allowing a qualitative mapping of an experimental fitness landscape, our approach will improve our understanding of the ecological factors that drive the evolution of local adaptation in D. suzukii.

Fine Mapping without Phenotyping: Identification of Selection Targets in Secondary Evolve and Resequence Experiments

Evolve and Resequence (E&R) studies investigate the genomic selection response of populations in an Experimental Evolution setup. Despite the popularity of E&R, empirical studies in sexually reproducing organisms typically suffer from an excess of candidate loci due to linkage disequilibrium, and single gene or SNP resolution is the exception rather than the rule. Recently, so-called "secondary E&R" has been suggested as promising experimental follow-up procedure to confirm putatively selected regions from a primary E&R study. Secondary E&R provides also the opportunity to increase mapping resolution by allowing for additional recombination events, which separate the selection target from neutral hitchhikers. Here, we use computer simulations to assess the effect of different crossing schemes, population size, experimental duration, and number of replicates on the power and resolution of secondary E&R. We find that the crossing scheme and population size are crucial factors determining power and resolution of secondary E&R: A simple crossing scheme with few founder lines consistently outcompetes crossing schemes where evolved populations from a primary E&R experiment are mixed with a complex ancestral founder population. Regardless of the experimental design tested, a population size of at least 4,800 individuals, which is roughly five times larger than population sizes in typical E&R studies, is required to achieve a power of at least 75%. Our study provides an important step toward improved experimental designs aiming to characterize causative SNPs in Experimental Evolution studies.

The role of climate change in pollinator decline across the Northern Hemisphere is underestimated

Pollinator biodiversity loss occurs at unprecedented rates globally, with particularly sharp declines documented in the North Temperate Zone. There is currently no consensus on the main drivers of the decline. Although climate change is expected to drive biodiversity loss in the future, current warming is often suggested to have positive impacts on pollinator assemblages in higher latitudes. Consequently, pollinator conservation initiatives in Europe and the USA tend to lack climate adaptation initiatives, an omission of which may be risky if climate change has significant negative impacts on pollinators. To gain an understanding of the impacts of climate change on pollinator biodiversity in the Northern Hemisphere, we conducted a literature review on genetic, species and community level diversity. Our findings suggest that global heating most likely causes homogenization of pollinator assemblages at all levels of pollinator biodiversity, making them less resilient to future stochasticity. Aspects of biodiversity that are rarely measured (e.g. genetic diversity, β-diversity, species evenness) tend to be most affected, while some dimensions of climate change, such as fluctuations in winter weather conditions, changes in the length of the vegetational season and increased frequency of extreme weather events, that seldom receive attention in empirical studies, tend to be particularly detrimental to pollinators. Negative effects of global heating on pollinator biodiversity are most likely exacerbated by homogenous and fragmented landscapes, widespread across Europe and the US, which limit opportunities for range-shifts and reduce micro-climatic buffering. This suggests the need for conservation initiatives to focus on increasing landscape connectivity and heterogeneity at multiple spatial scales.

Broad geographic sampling reveals the shared basis and environmental correlates of seasonal adaptation in Drosophila

To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions, and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.

Population structure limits parallel evolution in sticklebacks

Population genetic theory predicts that small effective population sizes (N_e) and restricted gene flow limit the potential for local adaptation. In particular, the probability of evolving similar phenotypes based on shared genetic mechanisms (i.e., parallel evolution), is expected to be reduced. We tested these predictions in a comparative genomic study of two ecologically similar and geographically codistributed stickleback species (viz. Gasterosteus aculeatus and Pungitius pungitius). We found that P. pungitius harbors less genetic diversity and exhibits higher levels of genetic differentiation and isolation-by-distance than G. aculeatus. Conversely, G. aculeatus exhibits a stronger degree of genetic parallelism across freshwater populations than P. pungitius: 2,996 versus 379 single nucleotide polymorphisms located within 26 versus 9 genomic regions show evidence of selection in multiple freshwater populations of G. aculeatus and P. pungitius, respectively. Most regions involved in parallel evolution in G. aculeatus showed increased levels of divergence, suggestive of selection on ancient haplotypes. In contrast, haplotypes involved in freshwater adaptation in P. pungitius were younger. In accordance with theory, the results suggest that connectivity and genetic drift play crucial roles in determining the levels and geographic distribution of standing genetic variation, providing evidence that population subdivision limits local adaptation and therefore also the likelihood of parallel evolution.

Polygenic Adaptation: Integrating Population Genetics and Gene Regulatory Networks

The adaptation of populations to local environments often relies on the selection of optimal values for polygenic traits. Here, we first summarize the results obtained from different quantitative genetics and population genetics models, about the genetic architecture of polygenic traits and their response to directional selection. We then highlight the contribution of systems biology to the understanding of the molecular bases of polygenic traits and the evolution of gene regulatory networks involved in these traits. Finally, we discuss the need for a unifying framework merging the fields of population genetics, quantitative genetics and systems biology to better understand the molecular bases of polygenic traits adaptation.

Multiple haplotype reconstruction from allele frequency data

Because haplotype information is of widespread interest in biomedical applications, effort has been put into their reconstruction. Here, we propose an efficient method, called haploSep, that is able to accurately infer major haplotypes and their frequencies just from multiple samples of allele frequency data. Even the accuracy of experimentally obtained allele frequencies can be improved by re-estimating them from our reconstructed haplotypes. From a methodological point of view, we model our problem as a multivariate regression problem where both the design matrix and the coefficient matrix are unknown. Compared to other methods, haploSep is very fast, with linear computational complexity in the haplotype length. We illustrate our method on simulated and real data focusing on experimental evolution and microbial data.

Secondary Evolve and Resequencing: An Experimental Confirmation of Putative Selection Targets without Phenotyping

Evolve and resequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that either are not replicated or show only a low statistical significance in a primary E&R experiment unless epistatic interactions predominate. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.

Polygenic Selection within a Single Generation Leads to Subtle Divergence among Ecological NichesINc

Selection on standing genetic variation may be effective enough to allow for adaptation to distinct niche environments within a single generation. Minor allele frequency changes at multiple, redundant loci of small effect can produce remarkable phenotypic shifts. Yet, demonstrating rapid adaptation via polygenic selection in the wild remains challenging. Here we harness natural replicate populations that experience similar selection pressures and harbor high within-, yet negligible among-population genetic variation. Such populations can be found among the teleost Fundulus heteroclitus that inhabits marine estuaries characterized by high environmental heterogeneity. We identify 10,861 single nucleotide polymorphisms in F. heteroclitus that belong to a single, panmictic population yet reside in environmentally distinct niches (one coastal basin and three replicate tidal ponds). By sampling at two time points within a single generation, we quantify both allele frequency change within as well as spatial divergence among niche subpopulations. We observe few individually significant allele frequency changes yet find that the "number" of moderate changes exceeds the neutral expectation by 10-100%. We find allele frequency changes to be significantly concordant in both direction and magnitude among all niche subpopulations, suggestive of parallel selection. In addition, within-generation allele frequency changes generate subtle but significant divergence among niches, indicative of local adaptation. Although we cannot distinguish between selection and genotype-dependent migration as drivers of within-generation allele frequency changes, the trait/s determining fitness and/or migration likelihood appear to be polygenic. In heterogeneous environments, polygenic selection and polygenic, genotype-dependent migration offer conceivable mechanisms for within-generation, local adaptation to distinct niches.

Parallel gene expression evolution in natural and laboratory evolved populations

Ecological adaptation is frequently inferred by the comparison of natural populations from different environments. Nevertheless, inference of the selective forces suffers the challenge that many environmental factors covary. With well-controlled environmental conditions, experimental evolution provides a powerful approach to complement the analysis of natural populations. On the other hand, it is apparent that laboratory conditions differ in many ways from natural environments, which raises the question as to what extent selection responses in experimental evolution studies can inform us about adaptation processes in the wild. In this study, we compared the expression profiles of replicated Drosophila melanogaster populations which have been exposed to two distinct temperature regimes (18/28 and 10/20°C) in the laboratory for more than 80 generations. Using gene-wise differential expression analysis and co-expression network analysis, we identified 541 genes and three coregulated gene modules that evolved in the same direction in both temperature regimes, and most of these changes probably reflect an adaptation to the space constraint or diurnal temperature fluctuation that is common in both selection regimes. In total, 203 genes and seven modules evolved temperature-specific expression changes. Remarkably, we detected a significant overlap of these temperature-adaptive genes/modules from experimental evolution with temperature-adaptive genes inferred from natural Drosophila populations covering two different temperature clines. We conclude that well-designed experimental evolution studies are a powerful tool to dissect evolutionary responses.

Few Fixed Variants between Trophic Specialist Pupfish Species Reveal Candidate Cis-Regulatory Alleles Underlying Rapid Craniofacial Divergence

Investigating closely related species that rapidly evolved divergent feeding morphology is a powerful approach to identify genetic variation underlying variation in complex traits. This can also lead to the discovery of novel candidate genes influencing natural and clinical variation in human craniofacial phenotypes. We combined whole-genome resequencing of 258 individuals with 50 transcriptomes to identify candidate cis-acting genetic variation underlying rapidly evolving craniofacial phenotypes within an adaptive radiation of Cyprinodon pupfishes. This radiation consists of a dietary generalist species and two derived trophic niche specialists-a molluscivore and a scale-eating species. Despite extensive morphological divergence, these species only diverged 10 kya and produce fertile hybrids in the laboratory. Out of 9.3 million genome-wide SNPs and 80,012 structural variants, we found very few alleles fixed between species-only 157 SNPs and 87 deletions. Comparing gene expression across 38 purebred F1 offspring sampled at three early developmental stages, we identified 17 fixed variants within 10 kb of 12 genes that were highly differentially expressed between species. By measuring allele-specific expression in F1 hybrids from multiple crosses, we found that the majority of expression divergence between species was explained by trans-regulatory mechanisms. We also found strong evidence for two cis-regulatory alleles affecting expression divergence of two genes with putative effects on skeletal development (dync2li1 and pycr3). These results suggest that SNPs and structural variants contribute to the evolution of novel traits and highlight the utility of the San Salvador Island pupfish system as an evolutionary model for craniofacial development.

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation

Building a genotype-phenotype-fitness map of adaptation is a central goal in evolutionary biology. It is difficult even when adaptive mutations are known because it is hard to enumerate which phenotypes make these mutations adaptive. We address this problem by first quantifying how the fitness of hundreds of adaptive yeast mutants responds to subtle environmental shifts. We then model the number of phenotypes these mutations collectively influence by decomposing these patterns of fitness variation. We find that a small number of inferred phenotypes can predict fitness of the adaptive mutations near their original glucose-limited evolution condition. Importantly, inferred phenotypes that matter little to fitness at or near the evolution condition can matter strongly in distant environments. This suggests that adaptive mutations are locally modular - affecting a small number of phenotypes that matter to fitness in the environment where they evolved - yet globally pleiotropic - affecting additional phenotypes that may reduce or improve fitness in new environments.

Polygenic adaptation: a unifying framework to understand positive selection

Most adaption processes have a polygenic genetic basis, but even with the recent explosive growth of genomic data we are still lacking a unified framework describing the dynamics of selected alleles. Building on recent theoretical and empirical work we introduce the concept of adaptive architecture, which extends the genetic architecture of an adaptive trait by factors influencing its adaptive potential and population genetic principles. Because adaptation can be typically achieved by many different combinations of adaptive alleles (redundancy), we describe how two characteristics - heterogeneity among loci and non-parallelism between replicated populations - are hallmarks for the characterization of polygenic adaptation in evolving populations. We discuss how this unified framework can be applied to natural and experimental populations.

Increased time sampling in an evolve-and-resequence experiment with outcrossing Saccharomyces cerevisiae reveals multiple paths of adaptive change

"Evolve and resequence" (E&R) studies combine experimental evolution and whole-genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling-the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high-resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high-resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context-dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics.

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.

Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster

Organisms living in seasonally variable environments utilize cues such as light and temperature to induce plastic responses, enabling them to exploit favorable seasons and avoid unfavorable ones. Local adapation can result in variation in seasonal responses, but the genetic basis and evolutionary history of this variation remains elusive. Many insects, including Drosophila melanogaster, are able to undergo an arrest of reproductive development (diapause) in response to unfavorable conditions. In D. melanogaster, the ability to diapause is more common in high latitude populations, where flies endure harsher winters, and in the spring, reflecting differential survivorship of overwintering populations. Using a novel hybrid swarm-based genome wide association study, we examined the genetic basis and evolutionary history of ovarian diapause. We exposed outbred females to different temperatures and day lengths, characterized ovarian development for over 2800 flies, and reconstructed their complete, phased genomes. We found that diapause, scored at two different developmental cutoffs, has modest heritability, and we identified hundreds of SNPs associated with each of the two phenotypes. Alleles associated with one of the diapause phenotypes tend to be more common at higher latitudes, but these alleles do not show predictable seasonal variation. The collective signal of many small-effect, clinally varying SNPs can plausibly explain latitudinal variation in diapause seen in North America. Alleles associated with diapause are segregating in Zambia, suggesting that variation in diapause relies on ancestral polymorphisms, and both pro- and anti-diapause alleles have experienced selection in North America. Finally, we utilized outdoor mesocosms to track diapause under natural conditions. We found that hybrid swarms reared outdoors evolved increased propensity for diapause in late fall, whereas indoor control populations experienced no such change. Our results indicate that diapause is a complex, quantitative trait with different evolutionary patterns across time and space.

Fitness effects for Ace insecticide resistance mutations are determined by ambient temperature

BACKGROUND

Insect pest control programs often use periods of insecticide treatment with intermittent breaks, to prevent fixing of mutations conferring insecticide resistance. Such mutations are typically costly in an insecticide-free environment, and their frequency is determined by the balance between insecticide treatment and cost of resistance. Ace, a key gene in neuronal signaling, is a prominent target of many insecticides and across several species, three amino acid replacements (I161V, G265A, and F330Y) provide resistance against several insecticides. Because temperature disturbs neuronal signaling homeostasis, we reasoned that the cost of insecticide resistance could be modulated by ambient temperature.

RESULTS

Experimental evolution of a natural Drosophila simulans population at hot and cold temperature regimes uncovered a surprisingly strong effect of ambient temperature. In the cold temperature regime, the resistance mutations were strongly counter selected (s = - 0.055), but in a hot environment, the fitness costs of resistance mutations were reduced by almost 50% (s = - 0.031). We attribute this unexpected observation to the advantage of the reduced enzymatic activity of resistance mutations in hot environments.

CONCLUSION

We show that fitness costs of insecticide resistance genes are temperature-dependent and suggest that the duration of insecticide-free periods need to be adjusted for different climatic regions to reflect these costs. We suggest that such environment-dependent fitness effects may be more common than previously assumed and pose a major challenge for modeling climate change.

Genotype by environment interaction for gene expression in Drosophila melanogaster

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

Molecular regulatory mechanisms underlying the adaptability of polyploid plants

Polyploidization influences the genetic composition and gene expression of an organism. This multi-level genetic change allows the formation of new regulatory pathways leading to increased adaptability. Although both forms of polyploidization provide advantages, autopolyploids were long thought to have little impact on plant divergence compared to allopolyploids due to their formation through genome duplication only, rather than in combination with hybridization. Recent advances have begun to clarify the molecular regulatory mechanisms such as microRNAs, alternative splicing, RNA-binding proteins, histone modifications, chromatin remodelling, DNA methylation, and N⁶ -methyladenosine (m6A) RNA methylation underlying the evolutionary success of polyploids. Such research is expanding our understanding of the evolutionary adaptability of polyploids and the regulatory pathways that allow adaptive plasticity in a variety of plant species. Herein we review the roles of individual molecular regulatory mechanisms and their potential synergistic pathways underlying plant evolution and adaptation. Notably, increasing interest in m6A methylation has provided a new component in potential mechanistic coordination that is still predominantly unexplored. Future research should attempt to identify and functionally characterize the evolutionary impact of both individual and synergistic pathways in polyploid plant species.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Detecting selected haplotype blocks in evolve and resequence experiments

Shifting from the analysis of single nucleotide polymorphisms to the reconstruction of selected haplotypes greatly facilitates the interpretation of evolve and resequence (E&R) experiments. Merging highly correlated hitchhiker SNPs into haplotype blocks reduces thousands of candidates to few selected regions. Current methods of haplotype reconstruction from Pool‐seq data need a variety of data‐specific parameters that are typically defined ad hoc and require haplotype sequences for validation. Here, we introduce haplovalidate, a tool which detects selected haplotypes in Pool‐seq time series data without the need for sequenced haplotypes. Haplovalidate makes data‐driven choices of two key parameters for the clustering procedure, the minimum correlation between SNPs constituting a cluster and the window size. Applying haplovalidate to simulated E&R data reliably detects selected haplotype blocks with low false discovery rates. Importantly, our analyses identified a restriction of the haplotype block‐based approach to describe the genomic architecture of adaptation. We detected a substantial fraction of haplotypes containing multiple selection targets. These blocks were considered as one region of selection and therefore led to underestimation of the number of selection targets. We demonstrate that the separate analysis of earlier time points can significantly increase the separation of selection targets into individual haplotype blocks. We conclude that the analysis of selected haplotype blocks has great potential for the characterization of the adaptive architecture with E&R experiments.

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.

Restoring ancestral phenotypes is a general pattern in gene expression evolution during adaptation to new environments in Tribolium castaneum

Plasticity and evolution are two processes allowing populations to respond to environmental changes, but how both are related and impact each other remains controversial. We studied plastic and evolutionary responses in gene expression of Tribolium castaneum after exposure of the beetles to new environments that differed from ancestral conditions in temperature, humidity or both. Using experimental evolution with 10 replicated lines per condition, we were able to demonstrate adaptation after 20 generations. We measured whole-transcriptome gene expression with RNA-sequencing to infer evolutionary and plastic changes. We found more evidence for changes in mean expression (shift in the intercept of reaction norms) in adapted lines than for changes in plasticity (shifts in slopes). Plasticity was mainly preserved in selected lines and was responsible for a large part of the phenotypic divergence in expression between ancestral and new conditions. However, we found that genes with the largest evolutionary changes in expression also evolved reduced plasticity and often showed expression levels closer to the ancestral stage. Results obtained in the three different conditions were similar, suggesting that restoration of ancestral expression levels during adaptation is a general evolutionary pattern. With a larger sample in the most stressful condition, we were able to detect a positive correlation between the proportion of genes with reversion of the ancestral plastic response and mean fitness per selection line.

Estimating the genome-wide contribution of selection to temporal allele frequency change

Rapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data (e.g., evolve-and-resequence studies). These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one time point to be predictive of the changes at later time points, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time points and across replicates. We estimate that at least 17 to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances, we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.

Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies

In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.

Long-Term Dynamics Among Wolbachia Strains During Thermal Adaptation of Their Drosophila melanogaster Hosts

Climate change is a major evolutionary force triggering thermal adaptation in a broad range of species. While the consequences of global warming are being studied for an increasing number of species, limited attention has been given to the evolutionary dynamics of endosymbionts in response to climate change. Here, we address this question by studying the dynamics of Wolbachia, a well-studied endosymbiont of Drosophila melanogaster. D. melanogaster populations infected with 13 different Wolbachia strains were exposed to novel hot and cold laboratory environments for up to 180 generations. The short-term dynamics suggested a temperature-related fitness difference resulting in the increase of clade V strains in the cold environment only. Our long-term analysis now uncovers that clade V dominates in all replicates after generation 60 irrespective of temperature treatment. We propose that adaptation of the Drosophila host to either temperature or Drosophila C virus (DCV) infection are the cause of the replicated, temporally non-concordant Wolbachia dynamics. Our study provides an interesting case demonstrating that even simple, well-controlled experiments can result in complex, but repeatable evolutionary dynamics, thus providing a cautionary note on too simple interpretations on the impact of climate change.

Neuronal Function and Dopamine Signaling Evolve at High Temperature in Drosophila

Neuronal activity is temperature sensitive and affects behavioral traits important for individual fitness, such as locomotion and courtship. Yet, we do not know enough about the evolutionary response of neuronal phenotypes in new temperature environments. Here, we use long-term experimental evolution of Drosophila simulans populations exposed to novel temperature regimes. Here, we demonstrate a direct relationship between thermal selective pressure and the evolution of neuronally expressed molecular and behavioral phenotypes. Several essential neuronal genes evolve lower expression at high temperatures and higher expression at low temperatures, with dopaminergic neurons standing out by displaying the most consistent expression change across independent replicates. We functionally validate the link between evolved gene expression and behavioral changes by pharmacological intervention in the experimentally evolved D. simulans populations as well as by genetically triggered expression changes of key genes in D. melanogaster. As natural temperature clines confirm our results for Drosophila and Anopheles populations, we conclude that neuronal dopamine evolution is a key factor for temperature adaptation.

Parallelism in eco-morphology and gene expression despite variable evolutionary and genomic backgrounds in a Holarctic fish

Understanding the extent to which ecological divergence is repeatable is essential for predicting responses of biodiversity to environmental change. Here we test the predictability of evolution, from genotype to phenotype, by studying parallel evolution in a salmonid fish, Arctic charr (Salvelinus alpinus), across eleven replicate sympatric ecotype pairs (benthivorous-planktivorous and planktivorous-piscivorous) and two evolutionary lineages. We found considerable variability in eco-morphological divergence, with several traits related to foraging (eye diameter, pectoral fin length) being highly parallel even across lineages. This suggests repeated and predictable adaptation to environment. Consistent with ancestral genetic variation, hundreds of loci were associated with ecotype divergence within lineages of which eight were shared across lineages. This shared genetic variation was maintained despite variation in evolutionary histories, ranging from postglacial divergence in sympatry (ca. 10-15kya) to pre-glacial divergence (ca. 20-40kya) with postglacial secondary contact. Transcriptome-wide gene expression (44,102 genes) was highly parallel across replicates, involved biological processes characteristic of ecotype morphology and physiology, and revealed parallelism at the level of regulatory networks. This expression divergence was not only plastic but in part genetically controlled by parallel cis-eQTL. Lastly, we found that the magnitude of phenotypic divergence was largely correlated with the genetic differentiation and gene expression divergence. In contrast, the direction of phenotypic change was mostly determined by the interplay of adaptive genetic variation, gene expression, and ecosystem size. Ecosystem size further explained variation in putatively adaptive, ecotype-associated genomic patterns within and across lineages, highlighting the role of environmental variation and stochasticity in parallel evolution. Together, our findings demonstrate the parallel evolution of eco-morphology and gene expression within and across evolutionary lineages, which is controlled by the interplay of environmental stochasticity and evolutionary contingencies, largely overcoming variable evolutionary histories and genomic backgrounds.

Local adaptation across a complex bioclimatic landscape in two montane bumble bee species

Understanding evolutionary responses to variation in temperature and precipitation across species ranges is of fundamental interest given ongoing climate change. The importance of temperature and precipitation for multiple aspects of bumble bee (Bombus) biology, combined with large geographic ranges that expose populations to diverse environmental pressures, make these insects well-suited for studying local adaptation. Here, we analyzed genome-wide sequence data from two widespread bumble bees, Bombus vosnesenskii and Bombus vancouverensis, using multiple environmental association analysis methods to investigate climate adaptation across latitude and altitude. The strongest signatures of selection were observed in B. vancouverensis, but despite unique responses between species for most loci, we detected several shared responses. Genes relating to neural and neuromuscular function and ion transport were especially evident with respect to temperature variables, while genes relating to cuticle formation, tracheal and respiratory system development, and homeostasis were associated with precipitation variables. Our data thus suggest that adaptive responses for tolerating abiotic variation are likely to be complex, but that several parallels among species can emerge even for these complex traits and landscapes. Results provide the framework for future work into mechanisms of thermal and desiccation tolerance in bumble bees and a set of genomic targets that might be monitored for future conservation efforts.

Rapid sex-specific adaptation to high temperature in Drosophila

The pervasive occurrence of sexual dimorphism demonstrates different adaptive strategies of males and females. While different reproductive strategies of the two sexes are well-characterized, very little is known about differential functional requirements of males and females in their natural habitats. Here, we study the impact environmental change on the selection response in both sexes. Exposing replicated Drosophila populations to a novel temperature regime, we demonstrate sex-specific changes in gene expression, metabolic and behavioral phenotypes in less than 100 generations. This indicates not only different functional requirements of both sexes in the new environment but also rapid sex-specific adaptation. Supported by computer simulations we propose that altered sex-biased gene regulation from standing genetic variation, rather than new mutations, is the driver of rapid sex-specific adaptation. Our discovery of environmentally driven divergent functional requirements of males and females has important implications-possibly even for gender aware medical treatments.

Shifting the paradigm in Evolve and Resequence studies: From analysis of single nucleotide polymorphisms to selected haplotype blocks

For almost a decade the combination of whole genome sequencing with experimental evolution (Evolve and Resequence, E&R; Turner, Stewart, Fields, Rice, & Tarone, 2011) has been used to study adaptation in outcrossing organisms. However, complications caused by inversions and hitchhiking variants have prevented this powerful approach from living up to its potential. In this issue of Molecular Ecology, Michalak, Kang, Schou, Garner, and Loeschke (2018), provide an important step ahead by using a population of Drosophila melanogaster devoid of segregating inversions to identify the genetic basis of resistance to five environmental stressors. They further address the challenge of hitchhiking variants by reconstructing selected haplotype blocks. While it is apparent that the haplotype block reconstruction needs further refinements, their work underpins the potential of E&R studies in Drosophila to address fundamental questions in evolutionary biology.

Insect responses to heat: physiological mechanisms, evolution and ecological implications in a warming world

Surviving changing climate conditions is particularly difficult for organisms such as insects that depend on environmental temperature to regulate their physiological functions. Insects are extremely threatened by global warming, since many do not have enough physiological tolerance even to survive continuous exposure to the current maximum temperatures experienced in their habitats. Here, we review literature on the physiological mechanisms that regulate responses to heat and provide heat tolerance in insects: (i) neuronal mechanisms to detect and respond to heat; (ii) metabolic responses to heat; (iii) thermoregulation; (iv) stress responses to tolerate heat; and (v) hormones that coordinate developmental and behavioural responses at warm temperatures. Our review shows that, apart from the stress response mediated by heat shock proteins, the physiological mechanisms of heat tolerance in insects remain poorly studied. Based on life-history theory, we discuss the costs of heat tolerance and the potential evolutionary mechanisms driving insect adaptations to high temperatures. Some insects may deal with ongoing global warming by the joint action of phenotypic plasticity and genetic adaptation. Plastic responses are limited and may not be by themselves enough to withstand ongoing warming trends. Although the evidence is still scarce and deserves further research in different insect taxa, genetic adaptation to high temperatures may result from rapid evolution. Finally, we emphasize the importance of incorporating physiological information for modelling species distributions and ecological interactions under global warming scenarios. This review identifies several open questions to improve our understanding of how insects respond physiologically to heat and the evolutionary and ecological consequences of those responses. Further lines of research are suggested at the species, order and class levels, with experimental and analytical approaches such as artificial selection, quantitative genetics and comparative analyses.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster

Life-history traits or "fitness components"-such as age and size at maturity, fecundity and fertility, age-specific rates of survival, and life span-are the major phenotypic determinants of Darwinian fitness. Analyzing the evolution and genetics of these phenotypic targets of selection is central to our understanding of adaptation. Due to its simple and rapid life cycle, cosmopolitan distribution, ease of maintenance in the laboratory, well-understood evolutionary genetics, and its versatile genetic toolbox, the "vinegar fly" Drosophila melanogaster is one of the most powerful, experimentally tractable model systems for studying "life-history evolution." Here, I review what has been learned about the evolution and genetics of life-history variation in D. melanogaster by drawing on numerous sources spanning population and quantitative genetics, genomics, experimental evolution, evolutionary ecology, and physiology. This body of work has contributed greatly to our knowledge of several fundamental problems in evolutionary biology, including the amount and maintenance of genetic variation, the evolution of body size, clines and climate adaptation, the evolution of senescence, phenotypic plasticity, the nature of life-history trade-offs, and so forth. While major progress has been made, important facets of these and other questions remain open, and the D. melanogaster system will undoubtedly continue to deliver key insights into central issues of life-history evolution and the genetics of adaptation.

275 years of forestry meets genomics in Pinus sylvestris

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA-seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long-term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.

Optimizing the Power to Identify the Genetic Basis of Complex Traits with Evolve and Resequence Studies

Evolve and resequence (E&R) studies are frequently used to dissect the genetic basis of quantitative traits. By subjecting a population to truncating selection for several generations and estimating the allele frequency differences between selected and nonselected populations using next-generation sequencing (NGS), the loci contributing to the selected trait may be identified. The role of different parameters, such as, the population size or the number of replicate populations has been examined in previous works. However, the influence of the selection regime, that is the strength of truncating selection during the experiment, remains little explored. Using whole genome, individual based forward simulations of E&R studies, we found that the power to identify the causative alleles may be maximized by gradually increasing the strength of truncating selection during the experiment. Notably, such an optimal selection regime comes at no or little additional cost in terms of sequencing effort and experimental time. Interestingly, we also found that a selection regime which optimizes the power to identify the causative loci is not necessarily identical to a regime that maximizes the phenotypic response. Finally, our simulations suggest that an E&R study with an optimized selection regime may have a higher power to identify the genetic basis of quantitative traits than a genome-wide association study, highlighting that E&R is a powerful approach for finding the loci underlying complex traits.

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.

Genetic convergence of industrial melanism in three geometrid moths

The rise of dark (melanic) forms of many species of moth in heavily coal-polluted areas of nineteenth- and twentieth-century Britain, and their post-1970s fall, point to a common selective pressure (camouflage against bird predators) acting at the community level. The extent to which this convergent phenotypic response relied on similar genetic and developmental mechanisms is unknown. We examine this problem by testing the hypothesis that the locus controlling melanism in Phigalia pilosaria and Odontopera bidentata, two species of geometrid moth that showed strong associations between melanism and coal pollution, is the same as that controlling melanism in Biston betularia, previously identified as the gene cortex. Comparative linkage mapping using family material supports the hypothesis for both species, indicating a deeply conserved developmental mechanism for melanism involving cortex. However, in contrast to the strong selective sweep signature seen in British B. betularia, no significant association was detected between cortex-region markers and melanic morphs in wild-caught samples of P. pilosaria and O. bidentata, implying much older, or diverse, origins of melanic morph alleles in these latter species.

On the evolution of carry-over effects

The environment experienced early in life often affects the traits that are developed after an individual has transitioned into new life stages and environments. Because the phenotypes induced by earlier environments are then screened by later ones, these 'carry-over effects' influence fitness outcomes across the entire life cycle. While the last two decades have witnessed an explosion of studies documenting the occurrence of carry-over effects, little attention has been given to how they adapt and diversify. To aid future research in this area, we present a framework for the evolution of carry-over effects. Carry-over effects can evolve in two ways. First, the expression of traits later in life may become more or less dependent on the developmental processes of earlier stages (e.g., 'adaptive decoupling'). Genetic correlations between life stages then either strengthen or weaken. Alternatively, those influential developmental processes that begin early in life may become more or less sensitive to that earlier environment. Here, plasticity changes in all the traits that share those developmental pathways across the whole life cycle. Adaptive evolution of a carry-over effect is governed by selection on the induced phenotypes in the later stage, and also by selection on any developmentally linked traits in the earlier life stage. When these selective pressures conflict, the evolution of the carry-over effect will be biased towards maximizing performance in the life stage with stronger selection. Because life stages often contribute unequally to total fitness, the strength of selection in any one stage depends on: (a) the relationship between the traits and the stage-specific fitness components (e.g., juvenile survival, adult mating success), and (b) the reproductive value of the life stage. Considering the evolution of carry-over effects reveals several intriguing features of the evolution of life histories and phenotypic plasticity more generally. For instance, carry-over effects that manifest as maladaptive plasticity in one life stage may represent an adaptive strategy for maximizing fitness in stages with stronger selection. Additionally, adaptation to novel environments encountered early in the life cycle may be faster in the presence of carry-over effects that influence sexually selected traits.