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

'Evolutionary poker': an agent-based model of interactome emergence and epistasis tested against Lenski's long-term E. coli experiments

A simple agent-based model is presented that produces results matching the experimental data found by Lenski's group for ≤50,000 generations of Escherichia coli bacteria under continuous selective pressure. Although various mathematical models have been devised previously to model the Lenski data, the present model has advantages in terms of overall simplicity and conceptual accessibility. The model also clearly illustrates a number of features of the evolutionary process that are otherwise not obvious, such as the roles of epistasis and historical contingency in adaptation and why evolution is time irreversible ('Dollo's law'). The reason for this irreversibility is that genomes become increasingly integrated or organized, and this organization becomes a novel selective factor itself, against which future generations must compete. Selection for integrated or synergistic networks, systems or sets of mutations or traits, not for individual mutations, confers the main adaptive advantage. The result is a punctuated form of evolution that follows a logarithmic occurrence probability, in which evolution proceeds very quickly when interactomes begin to form but which slows as interactomes become more robust and the difficulty of integrating new mutations increases. Sufficient parameters exist in the game to suggest not only how equilibrium or stasis is reached but also the conditions in which it will be punctuated, the factors governing the rate at which genomic organization occurs and novel traits appear, and how population size, genome size and gene variability affect these.

Rapid and Repeated Climate Adaptation Involving Chromosome Inversions following Invasion of an Insect

Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.

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.

Unraveling the Molecular Basis of Stabilizing Selection by Experimental Evolution

Stabilizing selection provides a challenge to molecular population genetics. Although stabilizing selection is ubiquitous, its genomic signature is difficult to distinguish from demographic signals. Experimental evolution provides a promising approach to characterize genomic regions exposed to stabilizing selection. A recent experimental evolution study of Aedes aegypti populations evolving either with or without sexual selection found a pattern of genetic differentiation suggestive of relaxed stabilizing selection. I argue that this study could not have detected the signal of relaxed stabilizing selection. I highlight why incorrect statistical methods resulted in a high number of false positive candidate single nucleotide polymorphism (SNPs) and discuss the fallacy of functional validation of candidate SNPs for polygenic traits by RNA-mediated knockdown.

Haplotype based testing for a better understanding of the selective architecture

BACKGROUND

The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies.

RESULTS

Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits.

CONCLUSIONS

Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios.

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

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'.

Gene expression differences consistent with water loss reduction underlie desiccation tolerance of natural Drosophila populations

BACKGROUND

Climate change is one of the main factors shaping the distribution and biodiversity of organisms, among others by greatly altering water availability, thus exposing species and ecosystems to harsh desiccation conditions. However, most of the studies so far have focused on the effects of increased temperature. Integrating transcriptomics and physiology is key to advancing our knowledge on how species cope with desiccation stress, and these studies are still best accomplished in model organisms.

RESULTS

Here, we characterized the natural variation of European D. melanogaster populations across climate zones and found that strains from arid regions were similar or more tolerant to desiccation compared with strains from temperate regions. Tolerant and sensitive strains differed not only in their transcriptomic response to stress but also in their basal expression levels. We further showed that gene expression changes in tolerant strains correlated with their physiological response to desiccation stress and with their cuticular hydrocarbon composition, and functionally validated three of the candidate genes identified. Transposable elements, which are known to influence stress response across organisms, were not found to be enriched nearby differentially expressed genes. Finally, we identified several tRNA-derived small RNA fragments that differentially targeted genes in response to desiccation stress.

CONCLUSIONS

Overall, our results showed that basal gene expression differences across individuals should be analyzed if we are to understand the genetic basis of differential stress survival. Moreover, tRNA-derived small RNA fragments appear to be relevant across stress responses and allow for the identification of stress-response genes not detected at the transcriptional level.

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.

A possible genomic footprint of polygenic adaptation on population divergence in seed beetles?

Efforts to unravel the genomic basis of incipient speciation are hampered by a mismatch between our toolkit and our understanding of the ecology and genetics of adaptation. While the former is focused on detecting selective sweeps involving few independently acting or linked speciation genes, the latter states that divergence typically occurs in polygenic traits under stabilizing selection. Here, we ask whether a role of stabilizing selection on polygenic traits in population divergence may be unveiled by using a phenotypically informed integrative approach, based on genome‐wide variation segregating in divergent populations. We compare three divergent populations of seed beetles (Callosobruchus maculatus) where previous work has demonstrated a prominent role for stabilizing selection on, and population divergence in, key life history traits that reflect rate‐dependent metabolic processes. We derive and assess predictions regarding the expected pattern of covariation between genetic variation segregating within populations and genetic differentiation between populations. Population differentiation was considerable (mean F_ST = 0.23–0.26) and was primarily built by genes showing high selective constraints and an imbalance in inferred selection in different populations (positive Tajima's D_NS in one and negative in one), and this set of genes was enriched with genes with a metabolic function. Repeatability of relative population differentiation was low at the level of individual genes but higher at the level of broad functional classes, again spotlighting metabolic genes. Absolute differentiation (d_XY) showed a very different general pattern at this scale of divergence, more consistent with an important role for genetic drift. Although our exploration is consistent with stabilizing selection on polygenic metabolic phenotypes as an important engine of genome‐wide relative population divergence and incipient speciation in our study system, we note that it is exceedingly difficult to firmly exclude other scenarios.

Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster

Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.

The evolution of larger size in high-altitude Drosophila melanogaster has a variable genetic architecture

Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus mapping approach to 4 unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of quantitative trait loci for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of quantitative trait locus regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes. Finally, we find that the genetic architectures indicated by our quantitative trait locus mapping results for size traits mirror those from similar experiments on other recently evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.

Pool-GWAS on reproductive dormancy in Drosophila simulans suggests a polygenic architecture

The genetic basis of adaptation to different environments has been of long-standing interest to evolutionary biologists. Dormancy is a well-studied adaptation to facilitate overwintering. In Drosophila melanogaster, a moderate number of genes with large effects have been described, which suggests a simple genetic basis of dormancy. On the other hand, genome-wide scans for dormancy suggest a polygenic architecture in insects. In D. melanogaster, the analysis of the genetic architecture of dormancy is complicated by the presence of cosmopolitan inversions. Here, we performed a genome-wide scan to characterize the genetic basis of this ecologically extremely important trait in the sibling species of D. melanogaster, D. simulans that lacks cosmopolitan inversions. We performed Pool-GWAS in a South African D. simulans population for dormancy incidence at 2 temperature regimes (10 and 12°C, LD 10:14). We identified several genes with SNPs that showed a significant association with dormancy (P-value < 1e-13), but the overall modest response suggests that dormancy is a polygenic trait with many loci of small effect. Our results shed light on controversies on reproductive dormancy in Drosophila and have important implications for the characterization of the genetic basis of this trait.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.

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

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

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

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

No water, no mating: Connecting dots from behaviour to pathways

Insects hold considerable ecological and agricultural importance making it vital to understand the factors impacting their reproductive output. Environmental stressors are examples of such factors which have a substantial and significant influence on insect reproductive fitness. Insects are also ectothermic and small in size which makes them even more susceptible to environmental stresses. The present study assesses the consequence of desiccation on the mating latency and copulations duration in tropical Drosophila melanogaster. We tested flies for these reproductive behavioral parameters at varying body water levels and with whole metabolome analysis in order to gain a further understanding of the physiological response to desiccation. Our results showed that the duration of desiccation is positively correlated with mating latency and mating failure, while having no influence on the copulation duration. The metabolomic analysis revealed three biological pathways highly affected by desiccation: starch and sucrose metabolism, galactose metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis. These results are consistent with carbohydrate metabolism providing an energy source in desiccated flies and also suggests that the phenylalanine biosynthesis pathway plays a role in the reproductive fitness of the flies. Desiccation is a common issue with smaller insects, like Drosophila and other tropical insects, and our findings indicate that this lack of ambient water can immediately and drastically affect the insect reproductive behaviour, which becomes more crucial because of unpredictable and dynamic weather conditions.

How is epigenetics predicted to contribute to climate change adaptation? What evidence do we need?

Transgenerational effects that are interpreted in terms of epigenetics have become an important research focus at a time when rapid environmental changes are occurring. These effects are usually interpreted as enhancing fitness extremely rapidly, without depending on the slower process of natural selection changing DNA-encoded (fixed) genetic variants in populations. Supporting evidence comes from a variety of sources, including environmental associations with epialleles, cross-generation responses of clonal material exposed to different environmental conditions, and altered patterns of methylation or frequency changes in epialleles across time. Transgenerational environmental effects have been postulated to be larger than those associated with DNA-encoded genetic changes, based on (for instance) stronger associations between epialleles and environmental conditions. Yet environmental associations for fixed genetic differences may always be weak under polygenic models where multiple combinations of alleles can lead to the same evolutionary outcome. The ultimate currency of adaptation is fitness, and few transgenerational studies have robustly determined fitness effects, particularly when compared to fixed genetic variants. Not all transgenerational modifications triggered by climate change will increase fitness: stressful conditions often trigger negative fitness effects across generations that can eliminate benefits. Epigenetic responses and other transgenerational effects will undoubtedly play a role in climate change adaptation, but further, well-designed, studies are required to test their importance relative to DNA-encoded changes. This article is part of the theme issue 'How does epigenetics influence the course of evolution?'

Eco-genetics of desiccation resistance in Drosophila

Climate change globally perturbs water circulation thereby influencing ecosystems including cultivated land. Both harmful and beneficial species of insects are likely to be vulnerable to such changes in climate. As small animals with a disadvantageous surface area to body mass ratio, they face a risk of desiccation. A number of behavioural, physiological and genetic strategies are deployed to solve these problems during adaptation in various Drosophila species. Over 100 desiccation-related genes have been identified in laboratory and wild populations of the cosmopolitan fruit fly Drosophila melanogaster and its sister species in large-scale and single-gene approaches. These genes are involved in water sensing and homeostasis, and barrier formation and function via the production and composition of surface lipids and via pigmentation. Interestingly, the genetic strategy implemented in a given population appears to be unpredictable. In part, this may be due to different experimental approaches in different studies. The observed variability may also reflect a rich standing genetic variation in Drosophila allowing a quasi-random choice of response strategies through soft-sweep events, although further studies are needed to unravel any underlying principles. These findings underline that D. melanogaster is a robust species well adapted to resist climate change-related desiccation. The rich data obtained in Drosophila research provide a framework to address and understand desiccation resistance in other insects. Through the application of powerful genetic tools in the model organism D. melanogaster, the functions of desiccation-related genes revealed by correlative studies can be tested and the underlying molecular mechanisms of desiccation tolerance understood. The combination of the wealth of available data and its genetic accessibility makes Drosophila an ideal bioindicator. Accumulation of data on desiccation resistance in Drosophila may allow us to create a world map of genetic evolution in response to climate change in an insect genome. Ultimately these efforts may provide guidelines for dealing with the effects of climate-related perturbations on insect population dynamics in the future.

Genetic mixing for population management: From genetic rescue to provenancing

Animal and plant species around the world are being challenged by the deleterious effects of inbreeding, loss of genetic diversity, and maladaptation due to widespread habitat destruction and rapid climate change. In many cases, interventions will likely be needed to safeguard populations and species and to maintain functioning ecosystems. Strategies aimed at initiating, reinstating, or enhancing patterns of gene flow via the deliberate movement of genotypes around the environment are generating growing interest with broad applications in conservation and environmental management. These diverse strategies go by various names ranging from genetic or evolutionary rescue to provenancing and genetic resurrection. Our aim here is to provide some clarification around terminology and to how these strategies are connected and linked to underlying genetic processes. We draw on case studies from the literature and outline mechanisms that underlie how the various strategies aim to increase species fitness and impact the wider community. We argue that understanding mechanisms leading to species decline and community impact is a key to successful implementation of these strategies. We emphasize the need to consider the nature of source and recipient populations, as well as associated risks and trade-offs for the various strategies. This overview highlights where strategies are likely to have potential at population, species, and ecosystem scales, but also where they should probably not be attempted depending on the overall aims of the intervention. We advocate an approach where short- and long-term strategies are integrated into a decision framework that also considers nongenetic aspects of management.

Convergent Adaptation to Quantitative Host Resistance in a Major Plant Pathogen

Plant pathogens can adapt to quantitative resistance, eroding its effectiveness. The aim of this work was to reveal the genomic basis of adaptation to such a resistance in populations of the fungus Pseudocercospora fijiensis, a major devastating pathogen of banana, by studying convergent adaptation on different cultivars. Samples from P. fijiensis populations showing a local adaptation pattern on new banana hybrids with quantitative resistance were compared, based on a genome scan approach, with samples from traditional and more susceptible cultivars in Cuba and the Dominican Republic. Whole-genome sequencing of pools of P. fijiensis isolates (pool-seq) sampled from three locations per country was conducted according to a paired population design. The findings of different combined analyses highly supported the existence of convergent adaptation on the study cultivars between locations within but not between countries. Five to six genomic regions involved in this adaptation were detected in each country. An annotation analysis and available biological data supported the hypothesis that some genes within the detected genomic regions may play a role in quantitative pathogenicity, including gene regulation. The results suggested that the genetic basis of fungal adaptation to quantitative plant resistance is at least oligogenic, while highlighting the existence of specific host-pathogen interactions for this kind of resistance.IMPORTANCE Understanding the genetic basis of pathogen adaptation to quantitative resistance in plants has a key role to play in establishing durable strategies for resistance deployment. In this context, a population genomic approach was developed for a major plant pathogen (the fungus Pseudocercospora fijiensis causing black leaf streak disease of banana) whereby samples from new resistant banana hybrids were compared with samples from more susceptible conventional cultivars in two countries. A total of 11 genomic regions for which there was strong evidence of selection by quantitative resistance were detected. An annotation analysis and available biological data supported the hypothesis that some of the genes within these regions may play a role in quantitative pathogenicity. These results suggested a polygenic basis of quantitative pathogenicity in this fungal pathogen and complex molecular plant-pathogen interactions in quantitative disease development involving several genes on both sides.

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.

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

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

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

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

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.

Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies

BACKGROUND

The combination of experimental evolution with whole-genome resequencing of pooled individuals, also called evolve and resequence (E&R) is a powerful approach to study the selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients.

RESULTS

In this benchmarking study, we compare 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, CLEAR, and the CMH test perform best despite LRT-1 and the CMH test not requiring time series data. CLEAR provides the most accurate estimates of selection coefficients.

CONCLUSION

This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.

Changes in lipid classes of Drosophila melanogaster in response to selection for three stress traits

Laboratory selection on environmental stress traits is an evolutionary approach that is informative in the context of understanding stress adaptation. Here we characterize changes in a lipidome of Drosophila melanogaster in lines selected for increased heat (elevated heat knockdown refractoriness), cold (decreased time to recover from chill-coma) and desiccation survival. Selection for desiccation resistance resulted in changes in multiple lipid classes used to characterize a lipidome. This included a decrease in triacylglycerols (TAGs) which is relevant to interpretation of storage lipid levels in previous D. melanogaster desiccation survival selection experiments. Chill-coma recovery rate selection was expected to show extensive changes in lipid classes, but only phosphatidic acids exhibited significant change. Selection for increased heat knockdown resistance resulted in a substantial change in the abundance of a class of lipids (diacylglycerols) which could play a role in mediating the heat shock response or result in an increase in neutral lipid mobilization.

Comparative studies of critical physiological limits and vulnerability to environmental extremes in small ectotherms: How much environmental control is needed?

Researchers and practitioners are increasingly using comparative assessments of critical thermal and physiological limits to assess the relative vulnerability of ectothermic species to extreme thermal and aridity conditions occurring under climate change. In most assessments of vulnerability, critical limits are compared across taxa exposed to different environmental and developmental conditions. However, many aspects of vulnerability should ideally be compared when species are exposed to the same environmental conditions, allowing a partitioning of sources of variation such as used in quantitative genetics. This is particularly important when assessing the importance of different types of plasticity to critical limits, using phylogenetic analyses to test for evolutionary constraints, isolating genetic variants that contribute to limits, characterizing evolutionary interactions among traits limiting adaptive responses, and when assessing the role of cross generation effects. However, vulnerability assessments based on critical thermal/physiological limits also need to take place within a context that is relevant to field conditions, which is not easily provided under controlled environmental conditions where behavior, microhabitat, stress exposure rates and other factors will differ from field conditions. There are ways of reconciling these requirements, such as by taking organisms from controlled environments and then testing their performance under field conditions (or vice versa). While comparisons under controlled environments are challenging for many taxa, assessments of critical thermal limits and vulnerability will always be incomplete unless environmental effects within and across generations are considered, and where the ecological relevance of assays measuring critical limits can be established.

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.

Local ancestry analysis reveals genomic convergence in extremophile fishes

The molecular basis of convergent phenotypes is often unknown. However, convergence at a genomic level is predicted when there are large population sizes, gene flow among diverging lineages or strong genetic constraints. We used whole-genome resequencing to investigate genomic convergence in fishes ( Poecilia spp.) that have repeatedly colonized hydrogen sulfide (H₂S)-rich environments in Mexico. We identified genomic similarities in both single nucleotide polymorphisms (SNPs) and structural variants (SVs) among independently derived sulfide spring populations, with approximately 1.2% of the genome being shared among sulfidic ecotypes. We compared these convergent genomic regions to candidate genes for H₂S adaptation identified from transcriptomic analyses and found that a significant proportion of these candidate genes (8%) were also in regions where sulfidic individuals had similar SNPs, while only 1.7% were in regions where sulfidic individuals had similar SVs. Those candidate genes included genes involved in sulfide detoxification, the electron transport chain (the main toxicity target of H₂S) and other processes putatively important for adaptation to sulfidic environments. Regional genomic similarity across independent populations exposed to the same source of selection is consistent with selection on standing variation or introgression of adaptive alleles across divergent lineages. However, combined with previous analyses, our data also support that adaptive changes in mitochondrially encoded subunits arose independently via selection on de novo mutations. Pressing questions remain on what conditions ultimately facilitate the independent rise of adaptive alleles at the same loci in separate populations, and thus, the degree to which evolution is repeatable or predictable. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

Genomic divergence and adaptive convergence in Drosophila simulans from Evolution Canyon, Israel

Biodiversity refugia formed by unique features of the Mediterranean arid landscape, such as the dramatic ecological contrast of "Evolution Canyon," provide a natural laboratory in which local adaptations to divergent microclimate conditions can be investigated. Significant insights have been provided by studies of Drosophila melanogaster diversifying along the thermal gradient in Evolution Canyon, but a comparative framework to survey adaptive convergence across sister species at the site has been lacking. To fill this void, we present an analysis of genomic polymorphism and evolutionary divergence of Drosophila simulans, a close relative of Drosophila melanogaster with which it co-occurs on both slopes of the canyon. Our results show even deeper interslope divergence in D. simulans than in D. melanogaster, with extensive signatures of selective sweeps present in flies from both slopes but enhanced in the population from the hotter and drier south-facing slope. Interslope divergence was enriched for genes related to electrochemical balance and transmembrane transport, likely in response to increased selection for dehydration resistance on the hotter slope. Both species shared genomic regions that underwent major selective sweeps, but the overall level of adaptive convergence was low, demonstrating no shortage of alternative genomic solutions to cope with the challenges of the microclimate contrast. Mobile elements were a major source of genetic polymorphism and divergence, affecting all parts of the genome, including coding sequences of mating behavior-related genes.

Dissection of Complex, Fitness-Related Traits in Multiple Drosophila Mapping Populations Offers Insight into the Genetic Control of Stress Resistance

We leverage two complementary Drosophila melanogaster mapping panels to genetically dissect starvation resistance-an important fitness trait. Using >1600 genotypes from the multiparental Drosophila Synthetic Population Resource (DSPR), we map numerous starvation stress QTL that collectively explain a substantial fraction of trait heritability. Mapped QTL effects allowed us to estimate DSPR founder phenotypes, predictions that were correlated with the actual phenotypes of these lines. We observe a modest phenotypic correlation between starvation resistance and triglyceride level, traits that have been linked in previous studies. However, overlap among QTL identified for each trait is low. Since we also show that DSPR strains with extreme starvation phenotypes differ in desiccation resistance and activity level, our data imply multiple physiological mechanisms contribute to starvation variability. We additionally exploited the Drosophila Genetic Reference Panel (DGRP) to identify sequence variants associated with starvation resistance. Consistent with prior work these sites rarely fall within QTL intervals mapped in the DSPR. We were offered a unique opportunity to directly compare association mapping results across laboratories since two other groups previously measured starvation resistance in the DGRP. We found strong phenotypic correlations among studies, but extremely low overlap in the sets of genomewide significant sites. Despite this, our analyses revealed that the most highly associated variants from each study typically showed the same additive effect sign in independent studies, in contrast to otherwise equivalent sets of random variants. This consistency provides evidence for reproducible trait-associated sites in a widely used mapping panel, and highlights the polygenic nature of starvation resistance.

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.

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.

Spatiotemporal dynamics and genome-wide association genome-wide association analysis of desiccation tolerance in Drosophila melanogaster

Water availability is a major environmental challenge to a variety of terrestrial organisms. In insects, desiccation tolerance varies predictably over spatial and temporal scales and is an important physiological determinant of fitness in natural populations. Here, we examine the dynamics of desiccation tolerance in North American populations of Drosophila melanogaster using: (a) natural populations sampled across latitudes and seasons; (b) experimental evolution in field mesocosms over seasonal time; (c) genome-wide associations to identify SNPs/genes associated with variation for desiccation tolerance; and (d) subsequent analysis of patterns of clinal/seasonal enrichment in existing pooled sequencing data of populations sampled in both North America and Australia. A cline in desiccation tolerance was observed, for which tolerance exhibited a positive association with latitude; tolerance also varied predictably with culture temperature, demonstrating a significant degree of thermal plasticity. Desiccation tolerance evolved rapidly in field mesocosms, although only males showed differences in desiccation tolerance between spring and autumn collections from natural populations. Water loss rates did not vary significantly among latitudinal or seasonal populations; however, changes in metabolic rates during prolonged exposure to dry conditions are consistent with increased tolerance in higher latitude populations. Genome-wide associations in a panel of inbred lines identified twenty-five SNPs in twenty-one loci associated with sex-averaged desiccation tolerance, but there is no robust signal of spatially varying selection on genes associated with desiccation tolerance. Together, our results suggest that desiccation tolerance is a complex and important fitness component that evolves rapidly and predictably in natural populations.

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.

Evolutionary responses of Drosophila melanogaster under chronic malnutrition

Drosophila species have successfully spread and adapted to diverse climates across the globe. For D. melanogaster, rotting vegetative matter provides the primary substrate for mating and oviposition, and also acts as a nutritional resource for developing larvae and adult flies. The transitory nature of decaying vegetation exposes D. melanogaster to rapidly changing nutrient availability. As evidenced by their successful global spread, flies are capable of dealing with fluctuating nutritional reserves within their respective ecological niches. Therefore, D. melanogaster populations might contain standing genetic variation to support survival during periods of nutrient scarcity. The natural history and genetic tractability of D. melanogaster make the fly an ideal model for studies on the genetic basis of resistance to nutritional stress. We review artificial selection studies on nutritionally-deprived D. melanogaster and summarize the phenotypic outcomes of selected animals. Many of the reported evolved traits phenocopy mutants of the nutrient-sensing PI3K/Akt pathway. Given that the PI3K/Akt pathway is also responsive to acute nutritional stress, the PI3K/Akt pathway might underlie traits evolved under chronic nutritional deprivation. Future studies that directly test for the genetic mechanisms driving evolutionary responses to nutritional stress will take advantage of the ease in manipulating fly nutrient availability in the laboratory.

An omnibus test for the global null hypothesis

Global hypothesis tests are a useful tool in the context of clinical trials, genetic studies, or meta-analyses, when researchers are not interested in testing individual hypotheses, but in testing whether none of the hypotheses is false. There are several possibilities how to test the global null hypothesis when the individual null hypotheses are independent. If it is assumed that many of the individual null hypotheses are false, combination tests have been recommended to maximize power. If, however, it is assumed that only one or a few null hypotheses are false, global tests based on individual test statistics are more powerful (e.g. Bonferroni or Simes test). However, usually there is no a priori knowledge on the number of false individual null hypotheses. We therefore propose an omnibus test based on cumulative sums of the transformed p-values. We show that this test yields an impressive overall performance. The proposed method is implemented in an R-package called omnibus.

Quantifying Selection with Pool-Seq Time Series Data

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (N_e) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies.

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.