Experimental evolution reveals natural selection on standing genetic variation

Genetic basis and repeatability for desiccation resistance in Drosophila melanogaster (Diptera: Drosophilidae)

Dehydration is a stress factor for organisms inhabiting natural habitats where water is scarce. Thus, it may be expected that species facing arid environments will develop mechanisms that maximize resistance to desiccation. Insects are excellent models for studying the effects of dehydration as well as the mechanisms and processes that prevent water loss since the effect of desiccation is greater due to the higher area/volume ratio than larger animals. Even though physiological and behavioral mechanisms to cope with desiccation are being understood, the genetic basis underlying the mechanisms related to variation in desiccation resistance and the context-dependent effect remain unsolved. Here we analyze the genetic bases of desiccation resistance in Drosophila melanogaster and identify candidate genes that underlie trait variation. Our quantitative genetic analysis of desiccation resistance revealed sexual dimorphism and extensive genetic variation. The phenotype-genotype association analyses (GWAS) identified 71 candidate genes responsible for total phenotypic variation in desiccation resistance. Half of these candidate genes were sex-specific suggesting that the genetic architecture underlying this adaptive trait differs between males and females. Moreover, the public availability of desiccation data analyzed on the same lines but in a different lab allows us to investigate the reliability and repeatability of results obtained in independent screens. Our survey indicates a pervasive micro-environment lab-dependent effect since we did not detect overlap in the sets of genes affecting desiccation resistance identified between labs.

How predictable is adaptation from standing genetic variation? Experimental evolution in Drosophila highlights the central role of redundancy and linkage disequilibrium

Experimental evolution is well-suited to test the predictability of evolution without the confounding effects of inaccurate forecasts about future environments. Most of the literature about parallel (and thus predictable) evolution has been carried out in asexual microorganisms, which adapt by de novo mutations. Nevertheless, parallel evolution has also been studied in sexual species at the genomic level. Here, I review the evidence for parallel evolution in Drosophila, the best-studied obligatory outcrossing model for adaptation from standing genetic variation in the laboratory. Similar to asexual microorganisms, evidence for parallel evolution varies between the focal hierarchical levels. Selected phenotypes consistently respond in a very predicable way, but the underlying allele frequency changes are much less predictable. The most important insight is that the predictability of the genomic selection response for polygenic traits depends highly on the founder population and to a much lesser extent on the selection regime. This implies that predicting adaptive genomic response is challenging and requires a good understanding of the adaptive architecture (including linkage disequilibrium) in the ancestral populations. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Evolutionary constraints mediate extinction risk under climate change

Mounting evidence suggests that rapid evolutionary adaptation may rescue some organisms from the impacts of climate change. However, evolutionary constraints might hinder this process, especially when different aspects of environmental change generate antagonistic selection on genetically correlated traits. Here, we use individual-based simulations to explore how genetic correlations underlying the thermal physiology of ectotherms might influence their responses to the two major components of climate change-increases in mean temperature and thermal variability. We found that genetic correlations can influence population dynamics under climate change, with declines in population size varying three-fold depending on the type of correlation present. Surprisingly, populations whose thermal performance curves were constrained by genetic correlations often declined less rapidly than unconstrained populations. Our results suggest that accurate forecasts of the impact of climate change on ectotherms will require an understanding of the genetic architecture of the traits under selection.

Species dynamics in natural bacterial communities over multiple rounds of propagation

Our experimental work illustrates how microbial ecosystems can be shaped by selective pressures over long-term ecological time scales. Natural microbial ecosystems generally consist of various co-existing species, where community composition describes the frequency at which species or types are present. Overall functionality of the system is achieved by interacting species. Upon short-term selection, for instance by transfer to a novel environment, community composition and functionality may change in a process referred to as species sorting. Various factors, such as initial community composition and selective pressures from the environment, may influence this change. Mabisi is a traditional fermented food from Zambia that naturally contains a bacterial community of around twenty unique bacterial types. We used six comparable but different natural bacterial Mabisi communities, each split into five identical replicates, for 16 propagation cycles in a novel, common laboratory environment. Composition of the bacterial communities changed upon propagation. The influence of four main factors on community composition, i.e. initial composition (history), impact of the environment (adaptation), changes due to interaction between species and random processes (chance) in species dynamics, was tested using maximum likelihood ratios. Initial community composition seemed to determine the change in community composition, followed by random processes. Interestingly, we observed convergence at the level of ecosystem functionality, which was measured as profiles of metabolic output. This suggests different combinations of species or types can achieve similar eco-system functionality.

Hybrid evolution repeats itself across environmental contexts in Texas sunflowers (Helianthus)

To what extent is evolution repeatable? Little is known about whether the evolution of hybrids is more (or less) repeatable than that of nonhybrids. We used field experimental evolution in annual sunflowers (Helianthus) in Texas to ask the extent to which hybrid evolution is repeatable across environments compared to nonhybrid controls. We created hybrids between Helianthus annuus (L.) and H. debilis (Nutt.) and grew plots of both hybrids and nonhybrid controls through eight generations at three sites in Texas. We collected seeds from each generation and grew each generation × treatment × home site combination at two final common gardens. We estimated the strength and direction of evolution in terms of fitness and 24 traits, tested for repeated versus nonrepeated evolution, and assessed overall phenotypic evolution across lineages and in relation to a locally adapted phenotype. Hybrids consistently evolved higher fitness over time, while controls did not, although trait evolution varied in strength across home sites. Repeated evolution was more evident in hybrids versus nonhybrid controls, and hybrid evolution was often in the direction of the locally adapted phenotype. Our findings have implications for both the nature of repeatability in evolution and the contribution of hybridization to evolution across environmental contexts.

Return of the Lemnaceae: duckweed as a model plant system in the genomics and postgenomics era

The aquatic Lemnaceae family, commonly called duckweed, comprises some of the smallest and fastest growing angiosperms known on Earth. Their tiny size, rapid growth by clonal propagation, and facile uptake of labeled compounds from the media were attractive features that made them a well-known model for plant biology from 1950 to 1990. Interest in duckweed has steadily regained momentum over the past decade, driven in part by the growing need to identify alternative plants from traditional agricultural crops that can help tackle urgent societal challenges, such as climate change and rapid population expansion. Propelled by rapid advances in genomic technologies, recent studies with duckweed again highlight the potential of these small plants to enable discoveries in diverse fields from ecology to chronobiology. Building on established community resources, duckweed is reemerging as a platform to study plant processes at the systems level and to translate knowledge gained for field deployment to address some of society's pressing needs. This review details the anatomy, development, physiology, and molecular characteristics of the Lemnaceae to introduce them to the broader plant research community. We highlight recent research enabled by Lemnaceae to demonstrate how these plants can be used for quantitative studies of complex processes and for revealing potentially novel strategies in plant defense and genome maintenance.

Eco-Evolutionary Dynamics in Microbial Communities from Spontaneous Fermented Foods

Eco-evolutionary forces are the key drivers of ecosystem biodiversity dynamics. This resulted in a large body of theory, which has partially been experimentally tested by mimicking evolutionary processes in the laboratory. In the first part of this perspective, we outline what model systems are used for experimental testing of eco-evolutionary processes, ranging from simple microbial combinations and, more recently, to complex natural communities. Microbial communities of spontaneous fermented foods are a promising model system to study eco-evolutionary dynamics. They combine the complexity of a natural community with extensive knowledge about community members and the ease of manipulating the system in a laboratory setup. Due to rapidly developing sequencing techniques and meta-omics approaches incorporating data in building ecosystem models, the diversity in these communities can be analysed with relative ease while hypotheses developed in simple systems can be tested. Here, we highlight several eco-evolutionary questions that are addressed using microbial communities from fermented foods. These questions relate to analysing species frequencies in space and time, the diversity-stability relationship, niche space and community coalescence. We provide several hypotheses of the influence of these factors on community evolution specifying the experimental setup of studies where microbial communities of spontaneous fermented food are used.

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.

Resampling the pool of genotypic possibilities: an adaptive function of sexual reproduction

BACKGROUND

Natural populations harbor significant levels of genetic variability. Because of this standing genetic variation, the number of possible genotypic combinations is many orders of magnitude greater than the population size. This means that any given population contains only a tiny fraction of all possible genotypic combinations.

RESULTS

We show that recombination allows a finite population to resample the genotype pool, i.e., the universe of all possible genotypic combinations. Recombination, in combination with natural selection, enables an evolving sexual population to replace existing genotypes with new, higher-fitness genotypic combinations that did not previously exist in the population. This process allows the sexual population to gradually increase its fitness far beyond the range of fitnesses in the initial population. In contrast to this, an asexual population is limited to selection among existing lower fitness genotypes.

CONCLUSIONS

The results provide an explanation for the ubiquity of sexual reproduction in evolving natural populations, especially when natural selection is acting on the standing genetic variation.

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.

Natural selection on sleep duration in Drosophila melanogaster

Sleep is ubiquitous across animal species, but why it persists is not well understood. Here we observe natural selection act on Drosophila sleep by relaxing bi-directional artificial selection for extreme sleep duration for 62 generations. When artificial selection was suspended, sleep increased in populations previously selected for short sleep. Likewise, sleep decreased in populations previously selected for long sleep when artificial selection was relaxed. We measured the corresponding changes in the allele frequencies of genomic variants responding to artificial selection. The allele frequencies of these variants reversed course in response to relaxed selection, and for short sleepers, the changes exceeded allele frequency changes that would be expected under random genetic drift. These observations suggest that the variants are causal polymorphisms for sleep duration responding to natural selection pressure. These polymorphisms may therefore pinpoint the most important regions of the genome maintaining variation in sleep duration.

Creating outbred and inbred populations in haplodiploids to measure adaptive responses in the laboratory

Laboratory studies are often criticized for not being representative of processes occurring in natural populations. One reason for this is the fact that laboratory populations generally do not capture enough of the genetic variation of natural populations. This can be mitigated by mixing the genetic background of several field populations when creating laboratory populations. From these outbred populations, it is possible to generate inbred lines, thereby freezing and partitioning part of their variability, allowing each genotype to be characterized independently. Many studies addressing adaptation of organisms to their environment, such as those involving quantitative genetics or experimental evolution, rely on inbred or outbred populations, but the methodology underlying the generation of such biological resources is usually not explicitly documented. Here, we developed different procedures to circumvent common pitfalls of laboratory studies, and illustrate their application using two haplodiploid species, the spider mites Tetranychus urticae and Tetranychus evansi. First, we present a method that increases the chance of capturing high amounts of variability when creating outbred populations, by performing controlled crosses between individuals from different field-collected populations. Second, we depict the creation of inbred lines derived from such outbred populations, by performing several generations of sib-mating. Third, we outline an experimental evolution protocol that allows the maintenance of a constant population size at the beginning of each generation, thereby preventing bottlenecks and diminishing extinction risks. Finally, we discuss the advantages of these procedures and emphasize that sharing such biological resources and combining them with available genetic tools will allow consistent and comparable studies that greatly contribute to our understanding of ecological and evolutionary processes.

Phenotypic plasticity as a long-term memory easing readaptations to ancestral environments

Phenotypic plasticity refers to environment-induced phenotypic changes without mutation and is present in all organisms. The role of phenotypic plasticity in organismal adaptations to novel environments has attracted much attention, but its role in readaptations to ancestral environments is understudied. To address this question, we use the reciprocal transplant approach to investigate the multitissue transcriptomes of chickens adapted to the Tibetan Plateau and adjacent lowland. While many genetic transcriptomic changes had occurred in the forward adaptation to the highland, plastic changes largely transform the transcriptomes to the preferred state when Tibetan chickens are brought back to the lowland. The same trend holds for egg hatchability, a key component of the chicken fitness. These findings, along with highly similar patterns in comparable experiments of guppies and Escherichia coli, demonstrate that organisms generally "remember" their ancestral environments via phenotypic plasticity and reveal a mechanism by which past experience affects future evolution.

Genome-wide meta-analysis identified novel variant associated with hallux valgus in Caucasians

BACKGROUND

Hallux valgus, one of the most common structural foot deformities, is highly heritable. However, previous efforts to elucidate the genetic underpinnings of hallux valgus through a genome-wide association study (GWAS) conducted in 4409 Caucasians did not identify genome-wide significant associations with hallux valgus in both gender-specific and sex-combined GWAS meta-analyses. In this analysis, we add newly available data and more densely imputed genotypes to identify novel genetic variants associated with hallux valgus.

METHODS

A total of 5925 individuals of European Ancestry were categorized into two groups: 'hallux valgus present' (n = 2314) or 'no deformity' (n = 3611) as determined by trained examiners or using the Manchester grading scale. Genotyping was performed using commercially available arrays followed by imputation to the Haplotype Reference Consortium (HRC) reference panel version 1.1. We conducted both sex-specific and sex-combined association analyses using logistic regression and generalized estimating equations as appropriate in each cohort. Results were then combined in a fixed-effects inverse-variance meta-analyses. Functional Mapping and Annotation web-based platform (FUMA) was used for positional mapping, gene and gene-set analyses.

RESULTS

We identified a novel locus in the intronic region of CLCA2 on chromosome 1, rs55807512 (OR = 0.48, p = 2.96E-09), an expression quantitative trait locus for COL24A1, a member of the collagen gene family.

CONCLUSION

In this report of the largest GWAS of hallux valgus to date, we identified a novel genome-wide significant locus for hallux valgus. Additional replication and functional follow-up will be needed to determine the functional role of this locus in hallux valgus biology.

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.

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.

Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments

Evolve-and-resequence (E+R) experiments leverage next-generation sequencing technology to track the allele frequency dynamics of populations as they evolve. While previous work has shown that adaptive alleles can be detected by comparing frequency trajectories from many replicate populations, this power comes at the expense of high-coverage (>100x) sequencing of many pooled samples, which can be cost-prohibitive. Here, we show that accurate estimates of allele frequencies can be achieved with very shallow sequencing depths (<5x) via inference of known founder haplotypes in small genomic windows. This technique can be used to efficiently estimate frequencies for any number of bi-allelic SNPs in populations of any model organism founded with sequenced homozygous strains. Using both experimentally-pooled and simulated samples of Drosophila melanogaster, we show that haplotype inference can improve allele frequency accuracy by orders of magnitude for up to 50 generations of recombination, and is robust to moderate levels of missing data, as well as different selection regimes. Finally, we show that a simple linear model generated from these simulations can predict the accuracy of haplotype-derived allele frequencies in other model organisms and experimental designs. To make these results broadly accessible for use in E+R experiments, we introduce HAF-pipe, an open-source software tool for calculating haplotype-derived allele frequencies from raw sequencing data. Ultimately, by reducing sequencing costs without sacrificing accuracy, our method facilitates E+R designs with higher replication and resolution, and thereby, increased power to detect adaptive alleles.

Sex solves Haldane's dilemma

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

What are the costs of learning? Modest trade-offs and constitutive costs do not set the price of fast associative learning ability in a parasitoid wasp

Learning ability has been associated with energetic costs that typically become apparent through trade-offs in a wide range of developmental, physiological, and life-history traits. Costs associated with learning ability can be either constitutive or induced, depending on whether they are always incurred or only when information is actively learned and memorized. Using lines of the parasitoid wasp Nasonia vitripennis that were selected for fast associative learning ability, we assessed a range of traits that have previously been identified as potential costs associated with learning. No difference in longevity, lipid reserves, tibia length, egg load, or fecundity was observed between the selected and control lines. All of these traits are considered to potentially lead to constitutive costs in the setup of this study. A gradual reversal to baseline learning after two forms of relaxed selection was indicative of a small constitutive cost of learning ability. We also tested for a trade-off with other memory types formed at later stages, but found no evidence that the mid-term memory that was selected for caused a decrease in performance of other memory types. In conclusion, we observe only one minor effect of a constitutive cost and none of the other costs and trade-offs that are reported in the literature to be of significant value in this case. We, therefore, argue for better inclusion of ecological and economic costs in studies on costs and benefits of learning ability.

Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks

Cryptic genetic variation can facilitate adaptation in evolving populations. To elucidate the underlying genetic mechanisms, we used directed evolution in Escherichia coli to accumulate variation in populations of yellow fluorescent proteins and then evolved these proteins toward the new phenotype of green fluorescence. Populations with cryptic variation evolved adaptive genotypes with greater diversity and higher fitness than populations without cryptic variation, which converged on similar genotypes. Populations with cryptic variation accumulated neutral or deleterious mutations that break the constraints on the order in which adaptive mutations arise. In doing so, cryptic variation opens paths to adaptive genotypes, creates historical contingency, and reduces the predictability of evolution by allowing different replicate populations to climb different adaptive peaks and explore otherwise-inaccessible regions of an adaptive landscape.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

A Polygenic Genetic Architecture of Flowering Time in the Worldwide Arabidopsis thaliana Population

Here, we report an empirical study of the polygenic basis underlying the evolution of complex traits. Flowering time variation measured at 10 and 16°C in the 1,001-genomes Arabidopsis thaliana collection of natural accessions were used as a model. The polygenic architecture of flowering time was defined as the 48 loci that were significantly associated with flowering time-at 10 and/or 16°C and/or their difference-in this population. Contributions from alleles at flowering time associated loci to global and local adaptation were explored by evaluating their distribution across genetically and geographically defined subpopulations across the native range of the species. The dynamics in the genetic architecture of flowering time in response to temperature was evaluated by estimating how the effects of these loci on flowering changed with growth temperature. Overall, the genetic basis of flowering time was stable-about 2/3 of the flowering time loci had similar effects at 10°C and 16°C-but many loci were involved in gene by temperature interactions. Globally present alleles, mostly of moderate effect, contributed to the differences in flowering times between the subpopulations via subtle changes in allele frequencies. More extreme local adaptations were, on several occasions, due to regional alleles with relatively large effects, and their linkage disequilibrium-patterns suggest coevolution of functionally connected alleles within local populations. Overall, these findings provide a significant contribution to our understanding about the possible modes of global and local evolution of a complex adaptive trait in A. thaliana.

Quantitative Operating Principles of Yeast Metabolism during Adaptation to Heat Stress

Microorganisms evolved adaptive responses to survive stressful challenges in ever-changing environments. Understanding the relationships between the physiological/metabolic adjustments allowing cellular stress adaptation and gene expression changes being used by organisms to achieve such adjustments may significantly impact our ability to understand and/or guide evolution. Here, we studied those relationships during adaptation to various stress challenges in Saccharomyces cerevisiae, focusing on heat stress responses. We combined dozens of independent experiments measuring whole-genome gene expression changes during stress responses with a simplified kinetic model of central metabolism. We identified alternative quantitative ranges for a set of physiological variables in the model (production of ATP, trehalose, NADH, etc.) that are specific for adaptation to either heat stress or desiccation/rehydration. Our approach is scalable to other adaptive responses and could assist in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes.

Genome-Wide Mapping of Gene-Phenotype Relationships in Experimentally Evolved Populations

Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM). We focused on the ability of FLAM to distinguish between genes which are differentiated and directly affect a phenotype from differentiated genes which have no effect on the phenotype. FLAM can separate these two classes of genes even with relatively small samples (10 populations, in total). The efficacy of FLAM is improved with increased number of populations, reduced environmental phenotypic variation, and increased within-treatment among-replicate variation. FLAM was applied to SNP variation measured in both twenty-population and thirty-population studies of Drosophila subjected to selection for age-at-reproduction, to illustrate the application of the method.

The advantage of recombination when selection is acting at many genetic Loci

Natural selection can act at many loci across the genome. But as the number of polymorphic loci increases linearly, the number of possible genotypic combinations increases exponentially. Consequently, a finite population - even a very large population - contains only a small sample of all possible multi-locus genotypes. In this paper, we revisit the classic Fisher-Muller models of recombination, taking into account the abundant standing variation that is commonly seen in natural populations. We show that the generation of new genotypic combinations through recombination is an important component of adaptive evolution based on multi-locus selection. Specifically, high-fitness genotypes are expected to be absent from the initial population when the frequencies of favorable alleles at the selected loci are low. But as the allele frequencies rise in response to selection the missing genotypes will be generated by recombination. Given recombination, if the average frequency of the favored alleles at the various selected loci is equal to p, then the expected number of favorable alleles per chromosome will be equal to pL, where L is the number of loci. As the value of p approaches unity at the selected loci, the number of favorable alleles per chromosome will approach a value of L, i.e., at the end of the selection process a favorable allele will be found at all loci. In the absence of recombination, however, selection will be limited to the highest-fitness genotypes that are already present in the initial population. We point out that the fitness of such initial genotypes is far less than the theoretical maximum fitness because they contain a favorable allele at only a fraction of the loci. Consequently, recombination acts to unblock the adaptive response to multi-locus selection in finite populations. Using simulations, we show that the sexual population can withstand invasion by newly-arising asexual clones. These results help explain the maintenance of sexual reproduction in natural populations.

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.

Contingency and determinism in evolution: Replaying life’s tape

Historical processes display some degree of “contingency,” meaning their outcomes are sensitive to seemingly inconsequential events that can fundamentally change the future. Contingency is what makes historical outcomes unpredictable. Unlike many other natural phenomena, evolution is a historical process. Evolutionary change is often driven by the deterministic force of natural selection, but natural selection works upon variation that arises unpredictably through time by random mutation, and even beneficial mutations can be lost by chance through genetic drift. Moreover, evolution has taken place within a planetary environment with a particular history of its own. This tension between determinism and contingency makes evolutionary biology a kind of hybrid between science and history. While philosophers of science examine the nuances of contingency, biologists have performed many empirical studies of evolutionary repeatability and contingency. Here, we review the experimental and comparative evidence from these studies. Replicate populations in evolutionary “replay” experiments often show parallel changes, especially in overall performance, although idiosyncratic outcomes show that the particulars of a lineage’s history can affect which of several evolutionary paths is taken. Comparative biologists have found many notable examples of convergent adaptation to similar conditions, but quantification of how frequently such convergence occurs is difficult. On balance, the evidence indicates that evolution tends to be surprisingly repeatable among closely related lineages, but disparate outcomes become more likely as the footprint of history grows deeper. Ongoing research on the structure of adaptive landscapes is providing additional insight into the interplay of fate and chance in the evolutionary process.

Readapting to DCV Infection without Wolbachia: Frequency Changes of Drosophila Antiviral Alleles Can Replace Endosymbiont Protection

There is now ample evidence that endosymbionts can contribute to host adaptation to environmental challenges. However, how endosymbiont presence affects the adaptive trajectory and outcome of the host is yet largely unexplored. In Drosophila, Wolbachia confers protection to RNA virus infection, an effect that differs between Wolbachia strains and can be targeted by selection. Adaptation to RNA virus infections is mediated by both Wolbachia and the host, raising the question of whether adaptive genetic changes in the host vary with the presence/absence of the endosymbiont. Here, we address this question using a polymorphic D. melanogaster population previously adapted to DCV infection for 35 generations in the presence of Wolbachia, from which we removed the endosymbiont and followed survival over the subsequent 20 generations of infection. After an initial severe drop, survival frequencies upon DCV selection increased significantly, as seen before in the presence of Wolbachia. Whole-genome sequencing, revealed that the major genes involved in the first selection experiment, pastrel and Ubc-E2H, continued to be selected in Wolbachia-free D. melanogaster, with the frequencies of protective alleles being closer to fixation in the absence of Wolbachia. Our results suggest that heterogeneity in Wolbachia infection status may be sufficient to maintain polymorphisms even in the absence of costs.

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.

Forward and reverse mutations in stages of cancer development

Background

Massive occurrences of interstitial loss of heterozygosity (LOH) likely resulting from gene conversions were found by us in different cancers as a type of single-nucleotide variations (SNVs), comparable in abundance to the commonly investigated gain of heterozygosity (GOH) type of SNVs, raising the question of the relationships between these two opposing types of cancer mutations.

Methods

In the present study, SNVs in 12 tetra sample and 17 trio sample sets from four cancer types along with copy number variations (CNVs) were analyzed by AluScan sequencing, comparing tumor with white blood cells as well as tissues vicinal to the tumor. Four published “nontumor”-tumor metastasis trios and 246 pan-cancer pairs analyzed by whole-genome sequencing (WGS) and 67 trios by whole-exome sequencing (WES) were also examined.

Results

Widespread GOHs enriched with CG-to-TG changes and associated with nearby CNVs and LOHs enriched with TG-to-CG changes were observed. Occurrences of GOH were 1.9-fold higher than LOH in “nontumor” tissues more than 2 cm away from the tumors, and a majority of these GOHs and LOHs were reversed in “paratumor” tissues within 2 cm of the tumors, forming forward-reverse mutation cycles where the revertant LOHs displayed strong lineage effects that pointed to a sequential instead of parallel development from “nontumor” to “paratumor” and onto tumor cells, which was also supported by the relative frequencies of 26 distinct classes of CNVs between these three types of cell populations.

Conclusions

These findings suggest that developing cancer cells undergo sequential changes that enable the “nontumor” cells to acquire a wide range of forward mutations including ones that are essential for oncogenicity, followed by revertant mutations in the “paratumor” cells to avoid growth retardation by excessive mutation load. Such utilization of forward-reverse mutation cycles as an adaptive mechanism was also observed in cultured HeLa cells upon successive replatings. An understanding of forward-reverse mutation cycles in cancer development could provide a genomic basis for improved early diagnosis, staging, and treatment of cancers.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0170-6) contains supplementary material, which is available to authorized users.

Decadal stability in genetic variation and structure in the intertidal seaweed Fucus serratus (Heterokontophyta: Fucaceae)

BACKGROUND

The spatial distribution of genetic diversity and structure has important implications for conservation as it reveals a species' strong and weak points with regard to stability and evolutionary capacity. Temporal genetic stability is rarely tested in marine species other than commercially important fishes, but is crucial for the utility of temporal snapshots in conservation management. High and stable diversity can help to mitigate the predicted northward range shift of seaweeds under the impact of climate change. Given the key ecological role of fucoid seaweeds along rocky shores, the positive effect of genetic diversity may reach beyond the species level to stabilize the entire intertidal ecosystem along the temperate North Atlantic. In this study, we estimated the effective population size, as well as temporal changes in genetic structure and diversity of the seaweed F. serratus using 22 microsatellite markers. Samples were taken across latitudes and a range of temperature regimes at seven locations with decadal sampling (2000 and 2010).

RESULTS

Across latitudes, genetic structure and diversity remained stable over 5-10 generations. Stable small-scale structure enhanced regional diversity throughout the species' range. In accordance with its biogeographic history, effective population size and diversity peaked in the species' mid-range in Brittany (France), and declined towards its leading and trailing edge to the north and south. At the species' southern edge, multi-locus-heterozygosity displayed a strong decline from 1999 to 2010.

CONCLUSION

Temporally stable genetic structure over small spatial scales is a potential driver for local adaptation and species radiation in the genus Fucus. Survival and adaptation of the low-diversity leading edge of F. serratus may be enhanced by regional gene flow and 'surfing' of favorable mutations or impaired by the accumulation of deleterious mutations. Our results have clear implications for the conservation of F. serratus at its genetically unique southern edge in Northwest Iberia, where increasing temperatures are likely the major cause for the decline not only of F. serratus, but also other intertidal and subtidal macroalgae. We expect that F. serratus will disappear from Northwest Iberia by 2100 if genetic rescue is not induced by the influx of genetic variation from Brittany.

A multilocus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana

The adaptation to a new habitat often results in a confounding between genomewide genotype and beneficial alleles. When the confounding is strong, or the allelic effects is weak, it is a major statistical challenge to detect the adaptive polymorphisms. We describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci directly associated with the adaptive trait or the expression of genes known to affect it. Then, a multilocus genetic architecture is inferred using a backward elimination association analysis across all candidate loci with an adaptive false discovery rate-based threshold. Effects of population stratification are controlled by accounting for genomic kinship in both steps of the analysis and also by simultaneously testing all candidate loci in the multilocus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. We revealed associations between 33 (29) loci and flowering time at 10 (16)°C in this collection of natural accessions, where standard genomewide association analysis methods detected five (3) loci. The 33 (29) loci explained approximately 55.1 (48.7)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail using new multilocus mapping approaches taking advantage of prior biological information, genome and transcriptome data.

Genome-Wide Analysis of Starvation-Selected Drosophila melanogaster-A Genetic Model of Obesity

Experimental evolution affords the opportunity to investigate adaptation to stressful environments. Studies combining experimental evolution with whole-genome resequencing have provided insight into the dynamics of adaptation and a new tool to uncover genes associated with polygenic traits. Here, we selected for starvation resistance in populations of Drosophila melanogaster for over 80 generations. In response, the starvation-selected lines developed an obese condition, storing nearly twice the level of total lipids than their unselected controls. Although these fats provide a ∼3-fold increase in starvation resistance, the imbalance in lipid homeostasis incurs evolutionary cost. Some of these tradeoffs resemble obesity-associated pathologies in mammals including metabolic depression, low activity levels, dilated cardiomyopathy, and disrupted sleeping patterns. To determine the genetic basis of these traits, we resequenced genomic DNA from the selected lines and their controls. We found 1,046,373 polymorphic sites, many of which diverged between selection treatments. In addition, we found a wide range of genetic heterogeneity between the replicates of the selected lines, suggesting multiple mechanisms of adaptation. Genome-wide heterozygosity was low in the selected populations, with many large blocks of SNPs nearing fixation. We found candidate loci under selection by using an algorithm to control for the effects of genetic drift. These loci were mapped to a set of 382 genes, which associated with many processes including nutrient response, catabolic metabolism, and lipid droplet function. The results of our study speak to the evolutionary origins of obesity and provide new targets to understand the polygenic nature of obesity in a unique model system.

Selection for long and short sleep duration in Drosophila melanogaster reveals the complex genetic network underlying natural variation in sleep

Why do some individuals need more sleep than others? Forward mutagenesis screens in flies using engineered mutations have established a clear genetic component to sleep duration, revealing mutants that convey very long or short sleep. Whether such extreme long or short sleep could exist in natural populations was unknown. We applied artificial selection for high and low night sleep duration to an outbred population of Drosophila melanogaster for 13 generations. At the end of the selection procedure, night sleep duration diverged by 9.97 hours in the long and short sleeper populations, and 24-hour sleep was reduced to 3.3 hours in the short sleepers. Neither long nor short sleeper lifespan differed appreciably from controls, suggesting little physiological consequences to being an extreme long or short sleeper. Whole genome sequence data from seven generations of selection revealed several hundred thousand changes in allele frequencies at polymorphic loci across the genome. Combining the data from long and short sleeper populations across generations in a logistic regression implicated 126 polymorphisms in 80 candidate genes, and we confirmed three of these genes and a larger genomic region with mutant and chromosomal deficiency tests, respectively. Many of these genes could be connected in a single network based on previously known physical and genetic interactions. Candidate genes have known roles in several classic, highly conserved developmental and signaling pathways—EGFR, Wnt, Hippo, and MAPK. The involvement of highly pleiotropic pathway genes suggests that sleep duration in natural populations can be influenced by a wide variety of biological processes, which may be why the purpose of sleep has been so elusive.

One of the biggest mysteries in biology is the need to sleep. Sleep duration has an underlying genetic basis, suggesting that very long and short sleep times could be bred for experimentally. How far can sleep duration be driven up or down? Here we achieved extremely long and short night sleep duration by subjecting a wild-derived population of Drosophila melanogaster to an experimental breeding program. At the end of the breeding program, long sleepers averaged 9.97 hours more nightly sleep than short sleepers. We analyzed whole-genome sequences from seven generations of the experimental breeding to identify allele frequencies that diverged between long and short sleepers, and verified genes and genomic regions with mutation and deficiency testing. These alleles map to classic developmental and signaling pathways, implicating many diverse processes that potentially affect sleep duration.

Different Genomic Changes Underlie Adaptive Evolution in Populations of Contrasting History

Experimental evolution is a powerful tool to understand the adaptive potential of populations under environmental change. Here, we study the importance of the historical genetic background in the outcome of evolution at the genome-wide level. Using the natural clinal variation of Drosophila subobscura, we sampled populations from two contrasting latitudes (Adraga, Portugal and Groningen, Netherlands) and introduced them in a new common environment in the laboratory. We characterized the genome-wide temporal changes underlying the evolutionary dynamics of these populations, which had previously shown fast convergence at the phenotypic level, but not at chromosomal inversion frequencies. We found that initially differentiated populations did not converge either at genome-wide level or at candidate SNPs with signs of selection. In contrast, populations from Portugal showed convergence to the control population that derived from the same geographical origin and had been long-established in the laboratory. Candidate SNPs showed a variety of different allele frequency change patterns across generations, indicative of an underlying polygenic basis. We did not detect strong linkage around candidate SNPs, but rather a small but long-ranging effect. In conclusion, we found that history played a major role in genomic variation and evolution, with initially differentiated populations reaching the same adaptive outcome through different genetic routes.

Genomics of Parallel Experimental Evolution in Drosophila

What are the genomic foundations of adaptation in sexual populations? We address this question using fitness–character and whole-genome sequence data from 30 Drosophila laboratory populations. These 30 populations are part of a nearly 40-year laboratory radiation featuring 3 selection regimes, each shared by 10 populations for up to 837 generations, with moderately large effective population sizes. Each of 3 sets of the 10 populations that shared a selection regime consists of 5 populations that have long been maintained under that selection regime, paired with 5 populations that had only recently been subjected to that selection regime. We find a high degree of evolutionary parallelism in fitness phenotypes when most-recent selection regimes are shared, as in previous studies from our laboratory. We also find genomic parallelism with respect to the frequencies of single-nucleotide polymorphisms, transposable elements, insertions, and structural variants, which was expected. Entirely unexpected was a high degree of parallelism for linkage disequilibrium. The evolutionary genetic changes among these sexual populations are rapid and genomically extensive. This pattern may be due to segregating functional genetic variation that is abundantly maintained genome-wide by selection, variation that responds immediately to changes of selection regime.

Predictable phenotypic, but not karyotypic, evolution of populations with contrasting initial history

The relative impact of selection, chance and history will determine the predictability of evolution. There is a lack of empirical research on this subject, particularly in sexual organisms. Here we use experimental evolution to test the predictability of evolution. We analyse the real-time evolution of Drosophila subobscura populations derived from contrasting European latitudes placed in a novel laboratory environment. Each natural population was sampled twice within a three-year interval. We study evolutionary responses at both phenotypic (life-history, morphological and physiological traits) and karyotypic levels for around 30 generations of laboratory culture. Our results show (1) repeatable historical effects between years in the initial state, at both phenotypic and karyotypic levels; (2) predictable phenotypic evolution with general convergence except for body size; and (3) unpredictable karyotypic evolution. We conclude that the predictability of evolution is contingent on the trait and level of organization, highlighting the importance of studying multiple biological levels with respect to evolutionary patterns.

Experimental Evolution and Heart Function in Drosophila

Drosophila melanogaster is a good model species for the study of heart function. However, most previous work on D. melanogaster heart function has focused on the effects of large-effect genetic variants. We compare heart function among 18 D. melanogaster populations that have been selected for altered development time, aging, or stress resistance. We find that populations with faster development and faster aging have increased heart dysfunction, measured as percentage heart failure after electrical pacing. Experimental evolution of different triglyceride levels, by contrast, has little effect on heart function. Evolved differences in heart function correlate with allele frequency changes at many loci of small effect. Genomic analysis of these populations produces a list of candidate loci that might affect cardiac function at the intersection of development, aging, and metabolic control mechanisms.

The effect of sex on the repeatability of evolution in different environments

The adaptive function of sex has been extensively studied, while less consideration has been given to the potential downstream consequences of sex on evolution. Here, we investigate one such potential consequence, the effect of sex on the repeatability of evolution. By affecting the repeatability of evolution, sex could have important implications for biodiversity, and for our ability to make predictions about the outcome of environmental change. We allowed asexual and sexual populations of Chlamydomonas reinhardtii to evolve in novel environments and monitored both their change in fitness and variance in fitness after evolution. Sex affected the repeatability of evolution by changing the importance of the effect of selection, chance, and ancestral constraints on the outcome of the evolutionary process. In particular, the effects of sex were highly dependent on the initial genetic composition of the population and on the environment. Given the lack of a consistent effect of sex on repeatability across the environments used here, further studies to dissect in more detail the underlying reasons for these differences as well as studies in additional environments are required if we are to have a general understanding of the effects of sex on the repeatability of evolution.

Genomic Trajectories to Desiccation Resistance: Convergence and Divergence Among Replicate Selected Drosophila Lines

Adaptation to environmental stress is critical for long-term species persistence. With climate change and other anthropogenic stressors compounding natural selective pressures, understanding the nature of adaptation is as important as ever in evolutionary biology. In particular, the number of alternative molecular trajectories available for an organism to reach the same adaptive phenotype remains poorly understood. Here, we investigate this issue in a set of replicated Drosophila melanogaster lines selected for increased desiccation resistance-a classical physiological trait that has been closely linked to Drosophila species distributions. We used pooled whole-genome sequencing (Pool-Seq) to compare the genetic basis of their selection responses, using a matching set of replicated control lines for characterizing laboratory (lab-)adaptation, as well as the original base population. The ratio of effective population size to census size was high over the 21 generations of the experiment at 0.52-0.88 for all selected and control lines. While selected SNPs in replicates of the same treatment (desiccation-selection or lab-adaptation) tended to change frequency in the same direction, suggesting some commonality in the selection response, candidate SNP and gene lists often differed among replicates. Three of the five desiccation-selection replicates showed significant overlap at the gene and network level. All five replicates showed enrichment for ovary-expressed genes, suggesting maternal effects on the selected trait. Divergence between pairs of replicate lines for desiccation-candidate SNPs was greater than between pairs of control lines. This difference also far exceeded the divergence between pairs of replicate lines for neutral SNPs. Overall, while there was overlap in the direction of allele frequency changes and the network and functional categories affected by desiccation selection, replicates showed unique responses at all levels, likely reflecting hitchhiking effects, and highlighting the challenges in identifying candidate genes from these types of experiments when traits are likely to be polygenic.

Reconstruction of Haplotype-Blocks Selected during Experimental Evolution

The genetic analysis of experimentally evolving populations typically relies on short reads from pooled individuals (Pool-Seq). While this method provides reliable allele frequency estimates, the underlying haplotype structure remains poorly characterized. With small population sizes and adaptive variants that start from low frequencies, the interpretation of selection signatures in most Evolve and Resequencing studies remains challenging. To facilitate the characterization of selection targets, we propose a new approach that reconstructs selected haplotypes from replicated time series, using Pool-Seq data. We identify selected haplotypes through the correlated frequencies of alleles carried by them. Computer simulations indicate that selected haplotype-blocks of several Mb can be reconstructed with high confidence and low error rates, even when allele frequencies change only by 20% across three replicates. Applying this method to real data from D. melanogaster populations adapting to a hot environment, we identify a selected haplotype-block of 6.93 Mb. We confirm the presence of this haplotype-block in evolved populations by experimental haplotyping, demonstrating the power and accuracy of our haplotype reconstruction from Pool-Seq data. We propose that the combination of allele frequency estimates with haplotype information will provide the key to understanding the dynamics of adaptive alleles.

Ancestral population reconstitution from isofemale lines as a tool for experimental evolution

Experimental evolution is a powerful tool to study adaptation under controlled conditions. Laboratory natural selection experiments mimic adaptation in the wild with better‐adapted genotypes having more offspring. Because the selected traits are frequently not known, adaptation is typically measured as fitness increase by comparing evolved populations against an unselected reference population maintained in a laboratory environment. With adaptation to the laboratory conditions and genetic drift, however, it is not clear to what extent such comparisons provide unbiased estimates of adaptation. Alternatively, ancestral variation could be preserved in isofemale lines that can be combined to reconstitute the ancestral population. Here, we assess the impact of selection on alleles segregating in newly established Drosophila isofemale lines. We reconstituted two populations from isofemale lines and compared them to two original ancestral populations (AP) founded from the same lines shortly after collection. No significant allele frequency changes could be detected between both AP and simulations showed that drift had a low impact compared to Pool‐Seq‐associated sampling effects. We conclude that laboratory selection on segregating variation in isofemale lines is too weak to have detectable effects, which validates ancestral population reconstitution from isofemale lines as an unbiased approach for measuring adaptation in evolved populations.