Massive habitat-specific genomic response in D. melanogaster populations during experimental evolution in hot and cold environments

Repeatability of evolution and genomic predictions of temperature adaptation in seed beetles

Climate warming is threatening biodiversity by increasing temperatures beyond the optima of many ectotherms. Owing to the inherent non-linear relationship between temperature and the rate of cellular processes, such shifts towards hot temperature are predicted to impose stronger selection compared with corresponding shifts towards cold temperature. This suggests that when adaptation to warming occurs, it should be relatively rapid and predictable. Here we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits in the beetle Callosobruchus maculatus. We conducted an evolve-and-resequence experiment on three genetic backgrounds of the beetle reared at hot or cold temperature. Indeed, we find that phenotypic evolution was faster and more repeatable at hot temperature. However, at the genomic level, adaptation to heat was less repeatable when compared across genetic backgrounds. As a result, genomic predictions of phenotypic adaptation in populations exposed to hot temperature were accurate within, but not between, backgrounds. These results seem best explained by genetic redundancy and an increased importance of epistasis during adaptation to heat, and imply that the same mechanisms that exert strong selection and increase repeatability of phenotypic evolution at hot temperature reduce repeatability at the genomic level. Thus, predictions of adaptation in key phenotypes from genomic data may become increasingly difficult as climates warm.

Experimental evolution in maize with replicated divergent selection identifies two plant-height-associated regions

Experimental evolution studies are common in agricultural research, where they are often deemed "long-term selection." These are often used to perform selection mapping, which involves identifying markers that were putatively under selection based on finding signals of selection left in the genome. A challenge of previous selection mapping studies, especially in agricultural research, has been the specification of robust significance thresholds. This is in large part because long-term selection studies in crops have rarely included replication. Usually, significance thresholds in long-term selection experiments are based on outliers from an empirical distribution. This approach is prone to missing true positives or including false positives. Under laboratory conditions with model species, replicated selection has been shown to be a powerful tool, especially for the specification of significance thresholds. Another challenge is that commonly used single-marker-based statistics may identify neutral linked loci which have hitchhiked along with regions that are actually under selection. In this study, we conducted divergent, replicated selection for short and tall plant height in a random-mating maize population under real field conditions. Selection of the 5% tallest and shortest plants was conducted for 3 generations. Significance thresholds were specified using the false discovery rate for selection (FDRfS) based on a window-based statistic applied to a statistic leveraging replicated selection (FSTSum). Overall, we found 2 significant regions putatively under selection. One region was located on chromosome 3 close to the plant-height genes Dwarf1 and iAA8. We applied a haplotype block analysis to further dissect the pattern of selection in significant regions of the genome. We observed patterns of strong selection in the subpopulations selected for short plant height on chromosome 3.

(Limited) Predictability of thermal adaptation in invertebrates

Evolutionary genomic approaches provide powerful tools to understand variation in and evolution of physiological processes. Untargeted genomic or transcriptomic screens can identify functionally annotated candidate genes linked to specific physiological processes, in turn suggesting evolutionary roles for these processes. Such studies often aim to inform modeling of the potential of natural populations to adapt to climate change, but these models are most accurate when evolutionary responses are repeatable, and thus predictable. Here, we synthesize the evolutionary genetic and comparative transcriptomic literature on terrestrial and marine invertebrates to assess whether evolutionary responses to temperature are repeatable within populations, across populations and across species. There is compelling evidence for repeatability, sometimes even across species. However, responses to laboratory selection and geographic variation across thermal gradients appear to be highly idiosyncratic. We also survey whether genetic/transcriptomic studies repeatedly identify candidate genes in three functional groups previously associated with the response to thermal stress: heat shock protein (Hsp) genes, proteolysis genes and immunity genes. Multiple studies across terrestrial and marine species identify candidates included in these gene sets. Yet, each of the gene sets are identified in only a minority of studies. Together, these patterns suggest that there is limited predictability of evolutionary responses to natural selection, including across studies within species. We discuss specific patterns for the candidate gene sets, implications for predictive modeling, and other potential applications of evolutionary genetics in elucidating physiology and gene function. Finally, we discuss limitations of inferences from available evolutionary genetic studies and directions for future research.

A path integral approach for allele frequency dynamics under polygenic selection

Many phenotypic traits have a polygenic genetic basis, making it challenging to learn their genetic architectures and predict individual phenotypes. One promising avenue to resolve the genetic basis of complex traits is through evolve-and-resequence (E&R) experiments, in which laboratory populations are exposed to some selective pressure and trait-contributing loci are identified by extreme frequency changes over the course of the experiment. However, small laboratory populations will experience substantial random genetic drift, and it is difficult to determine whether selection played a role in a given allele frequency change (AFC). Predicting AFCs under drift and selection, even for alleles contributing to simple, monogenic traits, has remained a challenging problem. Recently, there have been efforts to apply the path integral, a method borrowed from physics, to solve this problem. So far, this approach has been limited to genic selection, and is therefore inadequate to capture the complexity of quantitative, highly polygenic traits that are commonly studied. Here, we extend one of these path integral methods, the perturbation approximation, to selection scenarios that are of interest to quantitative genetics. We derive analytic expressions for the transition probability (i.e. the probability that an allele will change in frequency from x to y in time t) of an allele contributing to a trait subject to stabilizing selection, as well as that of an allele contributing to a trait rapidly adapting to a new phenotypic optimum. We use these expressions to characterize the use of AFC to test for selection, as well as explore optimal design choices for E&R experiments to uncover the genetic architecture of polygenic traits under selection.

Insect Models to Study Human Lipid Metabolism Disorders

Disorders of lipid metabolism such as obesity have become some of the most significant diseases of the twenty-first century. Despite these metabolic diseases affecting more than a third of the population in highly industrialized nations, the mechanisms underlying disease development remain poorly understood. Insect models, such as Drosophila melanogaster, offer a means of systematically examining conserved lipid metabolism and its pathology. Over the past several decades, Drosophila melanogaster has been used to greatly expand on our knowledge of metabolic disease, often taking advantage of the extensive genetic tools available to researchers. Additionally, Drosophila melanogaster has served and will continue to serve as a powerful tool for validating the results of genome-wide approaches to the study of diseases. This chapter explores the advancements of insect models in the study of lipid metabolism disorders as well as highlight opportunities for future areas of research.

Experimental Evolution in a Warming World: The Omics Era

A comprehensive understanding of the genetic mechanisms that shape species responses to thermal variation is essential for more accurate predictions of the impacts of climate change on biodiversity. Experimental evolution with high-throughput resequencing approaches (evolve and resequence) is a highly effective tool that has been increasingly employed to elucidate the genetic basis of adaptation. The number of thermal evolve and resequence studies is rising, yet there is a dearth of efforts to integrate this new wealth of knowledge. Here, we review this literature showing how these studies have contributed to increase our understanding on the genetic basis of thermal adaptation. We identify two major trends: highly polygenic basis of thermal adaptation and general lack of consistency in candidate targets of selection between studies. These findings indicate that the adaptive responses to specific environments are rather independent. A review of the literature reveals several gaps in the existing research. Firstly, there is a paucity of studies done with organisms of diverse taxa. Secondly, there is a need to apply more dynamic and ecologically relevant thermal environments. Thirdly, there is a lack of studies that integrate genomic changes with changes in life history and behavioral traits. Addressing these issues would allow a more in-depth understanding of the relationship between genotype and phenotype. We highlight key methodological aspects that can address some of the limitations and omissions identified. These include the need for greater standardization of methodologies and the utilization of new technologies focusing on the integration of genomic and phenotypic variation in the context of thermal adaptation.

A Path Integral Approach for Allele Frequency Dynamics Under Polygenic Selection

Many phenotypic traits have a polygenic genetic basis, making it challenging to learn their genetic architectures and predict individual phenotypes. One promising avenue to resolve the genetic basis of complex traits is through evolve-and-resequence experiments, in which laboratory populations are exposed to some selective pressure and trait-contributing loci are identified by extreme frequency changes over the course of the experiment. However, small laboratory populations will experience substantial random genetic drift, and it is difficult to determine whether selection played a roll in a given allele frequency change. Predicting how much allele frequencies change under drift and selection had remained an open problem well into the 21st century, even those contributing to simple, monogenic traits. Recently, there have been efforts to apply the path integral, a method borrowed from physics, to solve this problem. So far, this approach has been limited to genic selection, and is therefore inadequate to capture the complexity of quantitative, highly polygenic traits that are commonly studied. Here we extend one of these path integral methods, the perturbation approximation, to selection scenarios that are of interest to quantitative genetics. In particular, we derive analytic expressions for the transition probability (i.e., the probability that an allele will change in frequency from x , to y in time t ) of an allele contributing to a trait subject to stabilizing selection, as well as that of an allele contributing to a trait rapidly adapting to a new phenotypic optimum. We use these expressions to characterize the use of allele frequency change to test for selection, as well as explore optimal design choices for evolve-and-resequence experiments to uncover the genetic architecture of polygenic traits under selection.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

Natural alleles at the Doa locus underpin evolutionary changes in Drosophila lifespan and fecundity

'Evolve and resequence' (E&R) studies in Drosophila melanogaster have identified many candidate loci underlying the evolution of ageing and life history, but experiments that validate the effects of such candidates remain rare. In a recent E&R study we have identified several alleles of the LAMMER kinase Darkener of apricot (Doa) as candidates for evolutionary changes in lifespan and fecundity. Here, we use two complementary approaches to confirm a functional role of Doa in life-history evolution. First, we used transgenic RNAi to study the effects of Doa at the whole-gene level. Ubiquitous silencing of expression in adult flies reduced both lifespan and fecundity, indicating pleiotropic effects. Second, to characterize segregating variation at Doa, we examined four candidate single nucleotide polymorphisms (SNPs; Doa-1, -2, -3, -4) using a genetic association approach. Three candidate SNPs had effects that were qualitatively consistent with expectations based on our E&R study: Doa-2 pleiotropically affected both lifespan and late-life fecundity; Doa-1 affected lifespan (but not fecundity); and Doa-4 affected late-life fecundity (but not lifespan). Finally, the last candidate allele (Doa-3) also affected lifespan, but in the opposite direction from predicted.

Experimental evolution reveals the synergistic genomic mechanisms of adaptation to ocean warming and acidification in a marine copepod

Metazoan adaptation to global change relies on selection of standing genetic variation. Determining the extent to which this variation exists in natural populations, particularly for responses to simultaneous stressors, is essential to make accurate predictions for persistence in future conditions. Here, we identified the genetic variation enabling the copepod Acartia tonsa to adapt to experimental ocean warming, acidification, and combined ocean warming and acidification (OWA) over 25 generations of continual selection. Replicate populations showed a consistent polygenic response to each condition, targeting an array of adaptive mechanisms including cellular homeostasis, development, and stress response. We used a genome-wide covariance approach to partition the allelic changes into three categories: selection, drift and replicate-specific selection, and laboratory adaptation responses. The majority of allele frequency change in warming (57%) and OWA (63%) was driven by shared selection pressures across replicates, but this effect was weaker under acidification alone (20%). OWA and warming shared 37% of their response to selection but OWA and acidification shared just 1%, indicating that warming is the dominant driver of selection in OWA. Despite the dominance of warming, the interaction with acidification was still critical as the OWA selection response was highly synergistic with 47% of the allelic selection response unique from either individual treatment. These results disentangle how genomic targets of selection differ between single and multiple stressors and demonstrate the complexity that nonadditive multiple stressors will contribute to predictions of adaptation to complex environmental shifts caused by global change.

Understanding the biology of species' ranges: when and how does evolution change the rules of ecological engagement?

Understanding processes that limit species' ranges has been a core issue in ecology and evolutionary biology for many decades, and has become increasingly important given the need to predict the responses of biological communities to rapid environmental change. However, we still have a poor understanding of evolution at range limits and its capacity to change the ecological 'rules of engagement' that define these communities, as well as the time frame over which this occurs. Here we link papers in the current volume to some key concepts involved in the interactions between evolutionary and ecological processes at species' margins. In particular, we separate hypotheses about species' margins that focus on hard evolutionary limits, which determine how genotypes interact with their environment, from those concerned with soft evolutionary limits, which determine where and when local adaptation can persist in space and time. We show how theoretical models and empirical studies highlight conditions under which gene flow can expand local limits as well as contain them. In doing so, we emphasize the complex interplay between selection, demography and population structure throughout a species' geographical and ecological range that determines its persistence in biological communities. However, despite some impressively detailed studies on range limits, particularly in invertebrates and plants, few generalizations have emerged that can predict evolutionary responses at ecological margins. We outline some directions for future work such as considering the impact of structural genetic variants and metapopulation structure on limits, and the interaction between range limits and the evolution of mating systems and non-random dispersal. This article is part of the theme issue 'Species' ranges in the face of changing environments (Part II)'.

Loss of transcriptional plasticity but sustained adaptive capacity after adaptation to global change conditions in a marine copepod

Adaptive evolution and phenotypic plasticity will fuel resilience in the geologically unprecedented warming and acidification of the earth’s oceans, however, we have much to learn about the interactions and costs of these mechanisms of resilience. Here, using 20 generations of experimental evolution followed by three generations of reciprocal transplants, we investigated the relationship between adaptation and plasticity in the marine copepod, Acartia tonsa, in future global change conditions (high temperature and high CO₂). We found parallel adaptation to global change conditions in genes related to stress response, gene expression regulation, actin regulation, developmental processes, and energy production. However, reciprocal transplantation showed that adaptation resulted in a loss of transcriptional plasticity, reduced fecundity, and reduced population growth when global change-adapted animals were returned to ambient conditions or reared in low food conditions. However, after three successive transplant generations, global change-adapted animals were able to match the ambient-adaptive transcriptional profile. Concurrent changes in allele frequencies and erosion of nucleotide diversity suggest that this recovery occurred via adaptation back to ancestral conditions. These results demonstrate that while plasticity facilitated initial survival in global change conditions, it eroded after 20 generations as populations adapted, limiting resilience to new stressors and previously benign environments.

Rapid adaptation will facilitate species resilience under global climate change, but its effects on plasticity are less commonly investigated. This study shows that 20 generations of experimental adaptation in a marine copepod drives a rapid loss of plasticity that carries costs and might have impacts on future resilience to environmental change.

Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae

"Synthetic recombinant" populations have emerged as a useful tool for dissecting the genetics of complex traits. They can be used to derive inbred lines for fine QTL mapping, or the populations themselves can be sampled for experimental evolution. In the latter application, investigators generally value maximizing genetic variation in constructed populations. This is because in evolution experiments initiated from such populations, adaptation is primarily fueled by standing genetic variation. Despite this reality, little has been done to systematically evaluate how different methods of constructing synthetic populations shape initial patterns of variation. Here we seek to address this issue by comparing outcomes in synthetic recombinant Saccharomyces cerevisiae populations created using one of two strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains. We find that more genetic variation is initially present and maintained when population construction includes a round of pairwise crossing. As perhaps expected, we also observe that increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when constructing populations for use in evolution experiments, simply mixing founder strains in equal proportion may limit the adaptive potential.

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.

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.

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.

Experimental evolution supports signatures of sexual selection in genomic divergence

Comparative genomics has contributed to the growing evidence that sexual selection is an important component of evolutionary divergence and speciation. Divergence by sexual selection is implicated in faster rates of divergence of the X chromosome and of genes thought to underlie sexually selected traits, including genes that are sex biased in expression. However, accurately inferring the relative importance of complex and interacting forms of natural selection, demography, and neutral processes that occurred in the evolutionary past is challenging. Experimental evolution provides an opportunity to apply controlled treatments for multiple generations and examine the consequent genomic divergence. Here, we altered sexual selection intensity, elevating sexual selection in polyandrous lines and eliminating it in monogamous lines, and examined patterns of allele frequency divergence in the genome of Drosophila pseudoobscura after more than 160 generations of experimental evolution. Divergence is not uniform across the genome but concentrated in "islands," many of which contain candidate genes implicated in mating behaviors and other sexually selected phenotypes. These are more often seen on the X chromosome, which also shows greater divergence in F ST than neutral expectations. There are characteristic signatures of selection seen in these regions, with lower diversity on the X chromosome than the autosomes, and differences in diversity on the autosomes between selection regimes. Reduced Tajima's D within some of the divergent regions may imply that selective sweeps have occurred, despite considerable recombination. These changes are associated with both differential gene expression between the lines and sex-biased gene expression within the lines. Our results are very similar to those thought to implicate sexual selection in divergence between species and natural populations, and hence provide experimental support for the likely role of sexual selection in driving such types of genetic divergence, but also illustrate how variable outcomes can be for different genomic regions.

An Experimental Test of Adaptive Introgression in Locally Adapted Populations of Splash Pool Copepods

As species struggle to keep pace with the rapidly warming climate, adaptive introgression of beneficial alleles from closely related species or populations provides a possible avenue for rapid adaptation. We investigate the potential for adaptive introgression in the copepod, Tigriopus californicus, by hybridizing two populations with divergent heat tolerance limits. We subjected hybrids to strong heat selection for 15 generations followed by whole-genome resequencing. Utilizing a hybridize evolve and resequence (HER) technique, we can identify loci responding to heat selection via a change in allele frequency. We successfully increased the heat tolerance (measured as LT50) in selected lines, which was coupled with higher frequencies of alleles from the southern (heat tolerant) population. These repeatable changes in allele frequencies occurred on all 12 chromosomes across all independent selected lines, providing evidence that heat tolerance is polygenic. These loci contained genes with lower protein-coding sequence divergence than the genome-wide average, indicating that these loci are highly conserved between the two populations. In addition, these loci were enriched in genes that changed expression patterns between selected and control lines in response to a nonlethal heat shock. Therefore, we hypothesize that the mechanism of heat tolerance divergence is explained by differential gene expression of highly conserved genes. The HER approach offers a unique solution to identifying genetic variants contributing to polygenic traits, especially variants that might be missed through other population genomic approaches.

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.

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.

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.

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.

Genome scan detection of selective sweeps among biotypes of the soybean aphid, Aphis glycines, with differing virulence to resistance to A. glycines (Rag) traits in soybean, Glycine max

Multiple biotypes of soybean aphid, Aphis glycines, occur in North America adapted for survival (virulence) on soybean, Glycine max, with one or more different resistance to A. glycines (Rag) traits. The degree of genome-wide variance between biotypes and the basis of virulence remains unknown, but the latter is hypothesized to involve secreted effector proteins. Between 167,249 and 217,750 single nucleotide polymorphisms (SNPs) were predicted from whole genome re-sequencing of A. glycines avirulent biotype 1 (B1) and virulent B2, B3 and B4 colony-derived iso-female lines when compared to the draft B1 genome assembly, Ag_bt1_v6.0. Differences in nucleotide diversity indices (π) estimated within 1000 bp sliding windows demonstrated that 226 of 353 (64.0%) regions most differentiated between B1 and ≥ 2 virulent biotypes, representing < 0.1% of the 308 Mb assembled genome size, are located on 15 unordered scaffolds. Furthermore, these 226 intervals were coincident and show a significant association with 326 of 508 SNPs with significant locus-by-locus FST estimates between biotype populations (r = 0.6271; F1,70 = 45.36, P < 0.001) and genes showing evidence of directions selection (πN/πS > 2.0; r = 0.6233; F1,70 = 50.20, P < 0.001). A putative secreted effector glycoprotein is encoded in proximity to genome intervals of low estimated π (putative selective sweep) within avirulent B1 compared to all three virulent biotypes. Additionally, SNPs are clustered in or in proximity to genes putatively involved in intracellular protein cargo transport and the regulation of secretion. Results of this study indicate that factors on a small number of scaffolds of the A. glycines genome may contribute to variance in virulence towards Rag traits in G. max.

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.

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.

Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations

MOTIVATION

Evolve and resequence (E&R) experiments show promise in capturing real-time evolution at genome-wide scales, enabling the assessment of allele frequency changes SNPs in evolving populations and thus the estimation of population genetic parameters in the Wright-Fisher model (WF) that quantify the selection on SNPs. Currently, these analyses face two key difficulties: the numerous SNPs in E&R data and the frequent unreliability of estimates. Hence, a methodology for efficiently estimating WF parameters is needed to understand the evolutionary processes that shape genomes.

RESULTS

We developed a novel method for estimating WF parameters (EMWER), by applying an expectation maximization algorithm to the Kolmogorov forward equation associated with the WF model diffusion approximation. EMWER was used to infer the effective population size, selection coefficients and dominance parameters from E&R data. Of the methods examined, EMWER was the most efficient method for selection strength estimation in multi-core computing environments, estimating both selection and dominance with accurate confidence intervals. We applied EMWER to E&R data from experimental Drosophila populations adapting to thermally fluctuating environments and found a common selection affecting allele frequency of many SNPs within the cosmopolitan In(3R)P inversion. Furthermore, this application indicated that many of beneficial alleles in this experiment are dominant.

AVAILABILITY AND IMPLEMENTATION

Our C++ implementation of 'EMWER' is available at https://github.com/kojikoji/EMWER.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Little evidence of adaptation potential to ocean acidification in sea urchins living in "Future Ocean" conditions at a CO2 vent

Ocean acidification (OA) can be detrimental to calcifying marine organisms, with stunting of invertebrate larval development one of the most consistent responses. Effects are usually measured by short-term, within-generation exposure, an approach that does not consider the potential for adaptation. We examined the genetic response to OA of larvae of the tropical sea urchin Echinometra sp. C. raised on coral reefs that were either influenced by CO2 vents (pH ~ 7.9, future OA condition) or nonvent control reefs (pH 8.2). We assembled a high quality de novo transcriptome of Echinometra embryos (8 hr) and pluteus larvae (48 hr) and identified 68,056 SNPs. We tested for outlier SNPs and functional enrichment in embryos and larvae raised from adults from the control or vent sites. Generally, highest F ST values in embryos were observed between sites (intrinsic adaptation, most representative of the gene pool in the spawned populations). This comparison also had the highest number of outlier loci (40). In the other comparisons, classical adaptation (comparing larvae with adults from the control transplanted to either the control or vent conditions) and reverse adaptation (larvae from the vent site returned to the vent or explanted at the control), we only observed modest numbers of outlier SNPs (6-19) and only enrichment in two functional pathways. Most of the outliers detected were silent substitutions without adaptive potential. We conclude that there is little evidence of realized adaptation potential during early development, while some potential (albeit relatively low) exists in the intrinsic gene pool after more than one generation of exposure.

Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies

Many traits of interest are highly heritable and genetically complex, meaning that much of the variation they exhibit arises from differences at numerous loci in the genome. Complex traits and their evolution have been studied for more than a century, but only in the last decade have genome-wide association studies (GWASs) in humans begun to reveal their genetic basis. Here, we bring these threads of research together to ask how findings from GWASs can further our understanding of the processes that give rise to heritable variation in complex traits and of the genetic basis of complex trait evolution in response to changing selection pressures (i.e., of polygenic adaptation). Conversely, we ask how evolutionary thinking helps us to interpret findings from GWASs and informs related efforts of practical importance.

DNA Motifs Are Not General Predictors of Recombination in Two Drosophila Sister Species

Meiotic recombination is crucial for chromosomal segregation and facilitates the spread of beneficial and removal of deleterious mutations. Recombination rates frequently vary along chromosomes and Drosophila melanogaster exhibits a remarkable pattern. Recombination rates gradually decrease toward centromeres and telomeres, with a dramatic impact on levels of variation in natural populations. Two close sister species, Drosophila simulans and Drosophila mauritiana do not only have higher recombination rates but also exhibit a much more homogeneous recombination rate that only drops sharply very close to centromeres and telomeres. Because certain sequence motifs are associated with recombination rate variation in D. melanogaster, we tested whether the difference in recombination landscape between D. melanogaster and D. simulans can be explained by the genomic distribution of recombination rate–associated sequence motifs. We constructed the first high-resolution recombination map for D. simulans based on 189 haplotypes from a natural D. simulans population and searched for short sequence motifs linked with higher than average recombination in both sister species. We identified five consensus motifs significantly associated with higher than average chromosome-wide recombination rates in at least one species and present in both. Testing fine resolution associations between motif density and recombination, we found strong and positive associations genome-wide over a range of scales in D. melanogaster, while the results were equivocal in D. simulans. Despite the strong association in D. melanogaster, we did not find a decreasing density of these short-repeat motifs toward centromeres and telomeres. We conclude that the density of recombination-associated repeat motifs cannot explain the large-scale recombination landscape in D. melanogaster, nor the differences to D. simulans. The strong association seen for the sequence motifs in D. melanogaster likely reflects their impact influencing local differences in recombination rates along the genome.

Rare genetic variation and balanced polymorphisms are important for survival in global change conditions

Standing genetic variation is important for population persistence in extreme environmental conditions. While some species may have the capacity to adapt to predicted average future global change conditions, the ability to survive extreme events is largely unknown. We used single-generation selection experiments on hundreds of thousands of Strongylocentrotus purpuratus sea urchin larvae generated from wild-caught adults to identify adaptive genetic variation responsive to moderate (pH 8.0) and extreme (pH 7.5) low-pH conditions. Sequencing genomic DNA from pools of larvae, we identified consistent changes in allele frequencies across replicate cultures for each pH condition and observed increased linkage disequilibrium around selected loci, revealing selection on recombined standing genetic variation. We found that loci responding uniquely to either selection regime were at low starting allele frequencies while variants that responded to both pH conditions (11.6% of selected variants) started at high frequencies. Loci under selection performed functions related to energetics, pH tolerance, cell growth and actin/cytoskeleton dynamics. These results highlight that persistence in future conditions will require two classes of genetic variation: common, pH-responsive variants maintained by balancing selection in a heterogeneous environment, and rare variants, particularly for extreme conditions, that must be maintained by large population sizes.

Molecular evidence supports a genic capture resolution of the lek paradox

The genic capture hypothesis, where sexually selected traits capture genetic variation in condition and the condition reflects genome-wide mutation load, stands to explain the presence of abundant genetic variation underlying sexually selected traits. Here we test this hypothesis by applying bidirectional selection to male mating success for 14 generations in replicate populations of Drosophila melanogaster. We then resequenced the genomes of flies from each population. Consistent with the central predictions of the genic capture hypothesis, we show that genetic variance decreased with success selection and increased with failure selection, providing evidence for purifying sexual selection. This pattern was distributed across the genome and no consistent molecular pathways were associated with divergence, consistent with condition being the target of selection. Together, our results provide molecular evidence suggesting that strong sexual selection erodes genetic variation, and that genome-wide mutation-selection balance contributes to its maintenance.

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

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

Genetic redundancy fuels polygenic adaptation in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e., result from selection on a large number of genetic loci-but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes-e.g., fitness, metabolic rate, and fat content-and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

Selection for reproduction under short photoperiods changes diapause-associated traits and induces widespread genomic divergence

The incidence of reproductive diapause is a critical aspect of life history in overwintering insects from temperate regions. Much has been learned about the timing, physiology and genetics of diapause in a range of insects, but how the multiple changes involved in this and other photoperiodically regulated traits are interrelated is not well understood. We performed quasinatural selection on reproduction under short photoperiods in a northern fly species, Drosophila montana, to trace the effects of photoperiodic selection on traits regulated by the photoperiodic timer and / or by a circadian clock system. Selection changed several traits associated with reproductive diapause, including the critical day length for diapause (CDL), the frequency of diapausing females under photoperiods that deviate from daily 24 h cycles and cold tolerance, towards the phenotypes typical of lower latitudes. However, selection had no effect on the period of free-running locomotor activity rhythm regulated by the circadian clock in fly brain. At a genomic level, selection induced extensive divergence between the selection and control line replicates in 16 gene clusters involved in signal transduction, membrane properties, immunologlobulins and development. These changes resembled ones detected between latitudinally divergent D. montana populations in the wild and involved SNP divergence associated with several genes linked with diapause induction. Overall, our study shows that photoperiodic selection for reproduction under short photoperiods affects diapause-associated traits without disrupting the central clock network generating circadian rhythms in fly locomor activity.

Genomic signatures of experimental adaptive radiation in Drosophila

Abiotic environmental factors play a fundamental role in determining the distribution, abundance and adaptive diversification of species. Empowered by new technologies enabling rapid and increasingly accurate examination of genomic variation in populations, researchers may gain new insights into the genomic background of adaptive radiation and stress resistance. We investigated genomic variation across generations of large-scale experimental selection regimes originating from a single founder population of Drosophila melanogaster, diverging in response to ecologically relevant environmental stressors: heat shock, heat knock down, cold shock, desiccation and starvation. When compared to the founder population, and to parallel unselected controls, there were more than 100,000 single nucleotide polymorphisms (SNPs) displaying consistent allelic changes in response to selective pressures across generations. These SNPs were found in both coding and noncoding sequences, with the highest density in promoter regions, and involved a broad range of functionalities, including molecular chaperoning by heat-shock proteins. The SNP patterns were highly stressor-specific despite considerable variation among line replicates within each selection regime, as reflected by a principal component analysis, and co-occurred with selective sweep regions. Only ~15% of SNPs with putatively adaptive changes were shared by at least two selective regimes, while less than 1% of SNPs diverged in opposite directions. Divergent stressors driving evolution in the experimental system of adaptive radiation left distinct genomic signatures, most pronounced in starvation and heat-shock selection regimes.

Effects of evolutionary history on genome wide and phenotypic convergence in Drosophila populations

BACKGROUND

Studies combining experimental evolution and next-generation sequencing have found that adaptation in sexually reproducing populations is primarily fueled by standing genetic variation. Consequently, the response to selection is rapid and highly repeatable across replicate populations. Some studies suggest that the response to selection is highly repeatable at both the phenotypic and genomic levels, and that evolutionary history has little impact. Other studies suggest that even when the response to selection is repeatable phenotypically, evolutionary history can have significant impacts at the genomic level. Here we test two hypotheses that may explain this discrepancy. Hypothesis 1: Past intense selection reduces evolutionary repeatability at the genomic and phenotypic levels when conditions change. Hypothesis 2: Previous intense selection does not reduce evolutionary repeatability, but other evolutionary mechanisms may. We test these hypotheses using D. melanogaster populations that were subjected to 260 generations of intense selection for desiccation resistance and have since been under relaxed selection for the past 230 generations.

RESULTS

We find that, with the exception of longevity and to a lesser extent fecundity, 230 generations of relaxed selection has erased the extreme phenotypic differentiation previously found. We also find no signs of genetic fixation, and only limited evidence of genetic differentiation between previously desiccation resistance selected populations and their controls.

CONCLUSION

Our findings suggest that evolution in our system is highly repeatable even when populations have been previously subjected to bouts of extreme selection. We therefore conclude that evolutionary repeatability can overcome past bouts of extreme selection in Drosophila experimental evolution, provided experiments are sufficiently long and populations are not inbred.

Genetic basis of thermal plasticity variation in Drosophila melanogaster body size

Body size is a quantitative trait that is closely associated to fitness and under the control of both genetic and environmental factors. While developmental plasticity for this and other traits is heritable and under selection, little is known about the genetic basis for variation in plasticity that can provide the raw material for its evolution. We quantified genetic variation for body size plasticity in Drosophila melanogaster by measuring thorax and abdomen length of females reared at two temperatures from a panel representing naturally segregating alleles, the Drosophila Genetic Reference Panel (DGRP). We found variation between genotypes for the levels and direction of thermal plasticity in size of both body parts. We then used a Genome-Wide Association Study (GWAS) approach to unravel the genetic basis of inter-genotype variation in body size plasticity, and used different approaches to validate selected QTLs and to explore potential pleiotropic effects. We found mostly “private QTLs”, with little overlap between the candidate loci underlying variation in plasticity for thorax versus abdomen size, for different properties of the plastic response, and for size versus size plasticity. We also found that the putative functions of plasticity QTLs were diverse and that alleles for higher plasticity were found at lower frequencies in the target population. Importantly, a number of our plasticity QTLs have been targets of selection in other populations. Our data sheds light onto the genetic basis of inter-genotype variation in size plasticity that is necessary for its evolution.

Environmental conditions can influence development and lead to the production of phenotypes adjusted to the conditions adults will live in. This developmental plasticity, which can help organisms cope with environmental heterogeneity, is heritable and under selection. Its evolution will depend on available genetic variation. Using a panel of D. melanogaster flies representing naturally segregating alleles, we identified DNA sequence variants associated to variation in thermal plasticity for body size. We found that these variants correspond to a diverse set of functions and that their effects differ between body parts and properties of the thermal response. Our results shed new light onto the long discussed genes for plasticity.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Experimental evidence for rapid genomic adaptation to a new niche in an adaptive radiation

A substantial part of biodiversity is thought to have arisen from adaptive radiations in which one lineage rapidly diversified into multiple lineages adapted to many different niches. However, selection and drift reduce genetic variation during adaptation to new niches and may thus prevent or slow down further niche shifts. We tested whether rapid adaptation is still possible from a highly derived ecotype in the adaptive radiation of threespine stickleback on the Haida Gwaii archipelago, Western Canada. In a 19-years selection experiment, we let giant stickleback from a large blackwater lake evolve in a small clearwater pond without vertebrate predators. 56 whole genomes from the experiment and 26 natural populations revealed that adaptive genomic change was rapid in many small genomic regions and encompassed 75% of the adaptive genomic change between 12,000 years old ecotypes. Adaptive genomic change was as fast as phenotypic change in defence and trophic morphology and both were largely parallel between the short-term selection experiment and long-term natural adaptive radiation. Our results show that functionally relevant standing genetic variation can persist in derived adaptive radiation members, allowing adaptive radiations to unfold very rapidly.

Rapid evolution of aphid pests in agricultural environments

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