Factors influencing the effect size distribution of adaptive substitutions

Predicting the direction of phenotypic difference

Predicting phenotypes from genomic data is a key goal in genetics, but for most complex phenotypes, predictions are hampered by incomplete genotype-to-phenotype mapping. Here, we describe a more attainable approach than quantitative predictions, which is aimed at qualitatively predicting phenotypic differences. Despite incomplete genotype-to-phenotype mapping, we show that it is relatively easy to determine which of two individuals has a greater phenotypic value. This question is central in many scenarios, e.g., comparing disease risk between individuals, the yield of crop strains, or the anatomy of extinct vs extant species. To evaluate prediction accuracy, i.e., the probability that the individual with the greater predicted phenotype indeed has a greater phenotypic value, we developed an estimator of the ratio between known and unknown effects on the phenotype. We evaluated prediction accuracy using human data from tens of thousands of individuals from either the same family or the same population, as well as data from different species. We found that, in many cases, even when only a small fraction of the loci affecting a phenotype is known, the individual with the greater phenotypic value can be identified with over 90% accuracy. Our approach also circumvents some of the limitations in transferring genetic association results across populations. Overall, we introduce an approach that enables accurate predictions of key information on phenotypes - the direction of phenotypic difference - and suggest that more phenotypic information can be extracted from genomic data than previously appreciated.

Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara

Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.

A large-effect fitness trade-off across environments is explained by a single mutation affecting cold acclimation

Identifying the genetic basis of local adaptation and fitness trade-offs across environments is a central goal of evolutionary biology. Cold acclimation is an adaptive plastic response for surviving seasonal freezing, and costs of acclimation may be a general mechanism for fitness trade-offs across environments in temperate zone species. Starting with locally adapted ecotypes of Arabidopsis thaliana from Italy and Sweden, we examined the fitness consequences of a naturally occurring functional polymorphism in CBF2. This gene encodes a transcription factor that is a major regulator of cold-acclimated freezing tolerance and resides within a locus responsible for a genetic trade-off for long-term mean fitness. We estimated the consequences of alternate genotypes of CBF2 on 5-y mean fitness and fitness components at the native field sites by comparing near-isogenic lines with alternate genotypes of CBF2 to their genetic background ecotypes. The effects of CBF2 were validated at the nucleotide level using gene-edited lines in the native genetic backgrounds grown in simulated parental environments. The foreign CBF2 genotype in the local genetic background reduced long-term mean fitness in Sweden by more than 10%, primarily via effects on survival. In Italy, fitness was reduced by more than 20%, primarily via effects on fecundity. At both sites, the effects were temporally variable and much stronger in some years. The gene-edited lines confirmed that CBF2 encodes the causal variant underlying this genetic trade-off. Additionally, we demonstrated a substantial fitness cost of cold acclimation, which has broad implications for potential maladaptive responses to climate change.

A life-history allele of large effect shortens developmental time in a wild insect population

Developmental time is a key life-history trait with large effects on Darwinian fitness. In many insects, developmental time is currently under strong selection to minimize ecological mismatches in seasonal timing induced by climate change. The genetic basis of responses to such selection, however, is poorly understood. To address this problem, we set up a long-term evolve-and-resequence experiment in the beetle Tribolium castaneum and selected replicate, outbred populations for fast or slow embryonic development. The response to this selection was substantial and embryonic developmental timing of the selection lines started to diverge during dorsal closure. Pooled whole-genome resequencing, gene expression analysis and an RNAi screen pinpoint a 222 bp deletion containing binding sites for Broad and Tramtrack upstream of the ecdysone degrading enzyme Cyp18a1 as a main target of selection. Using CRISPR/Cas9 to reconstruct this allele in the homogenous genetic background of a laboratory strain, we unravel how this single deletion advances the embryonic ecdysone peak inducing dorsal closure and show that this allele accelerates larval development but causes a trade-off with fecundity. Our study uncovers a life-history allele of large effect and reveals the evolvability of developmental time in a natural insect population.

Temporal Variation in Selection Influences Microgeographic Local Adaptation

AbstractEcological heterogeneity can lead to local adaptation when populations exhibit fitness trade-offs among habitats. However, the degree to which local adaptation is affected by the spatial and temporal scale of environmental variation is poorly understood. A multiyear reciprocal transplant experiment was performed with populations of the annual plant Leptosiphon parviflorus living on adjacent serpentine and nonserpentine soil. Local adaptation over this small geographic scale was observed, but there were differences in the temporal variability of selection across habitats. On serpentine soil, the local population had a consistently large survival advantage, presumably as a result of the temporal stability in selection imposed by soil cation content. In contrast, a fecundity advantage was observed for the sandstone population on its native soil type but only in the two study years with the highest rainfall. A manipulative greenhouse experiment demonstrated that the fitness advantage of the sandstone population in its native soil type depends critically on water availability. The temporal variability in local adaptation driven by variation in precipitation suggests that continued drought conditions have the potential to erode local adaptation in these populations. These results show how different selective factors can influence spatial and temporal patterns of variation in fitness trade-offs.

Recent parallel speciation in Antirrhinum involved complex haplotypes and multiple adaptive characters

A role of ecological adaptation in speciation can be obscured by stochastic processes and differences that species accumulate after genetic isolation. One way to identify adaptive characters and their underlying genes is to study cases of speciation involving parallel adaptations. Recently resolved phylogenies reveal that alpine morphology has evolved in parallel in the genus Antirrhinum (snapdragons): first in an early split of an alpine from a lowland lineage and, more recently, from within the lowland lineage to produce closely related sympatric species with contrasting alpine and lowland forms. Here, we find that two of these later diverged sympatric species are differentiated by only around 2% of nuclear loci. Though showing evidence of recent gene flow, the species remain distinct for a suite of morphological characters typical of earlier-diverged alpine or lowland lineages and their morphologies correlate with features of the local landscape, as expected of ecological adaptations. Morphological differences between the two species involve multiple, unlinked genes so that parental character combinations are readily broken up by recombination in hybrids. We detect little evidence for post-pollination barriers to gene flow or recombination, suggesting that genetic isolation related to ecological adaptation is important in maintaining character combinations and might have contributed to parallel speciation. We also find evidence that genes involved in the earlier alpine-lowland split were reused in parallel evolution of alpine species, consistent with introgressive hybridisation, and speculate that many non-ecological barriers to gene flow might have been purged during the process.

Ecological genetics of local adaptation in Arabidopsis: An 8-year field experiment

There is considerable evidence for local adaptation in nature, yet important questions remain regarding its genetic basis. How many loci are involved? What are their effect sizes? What is the relative importance of conditional neutrality versus genetic trade-offs? Here we address these questions in the self-pollinating, annual plant Arabidopsis thaliana. We used 400 recombinant inbred lines (RILs) derived from two locally adapted populations in Italy and Sweden, grew the RILs and parents at the parental locations, and mapped quantitative trait loci (QTL) for mean fitness (fruits/seedling planted). We previously published results from the first 3 years of the study, and here add five additional years, providing a unique opportunity to assess how temporal variation in selection might affect QTL detection and classification. We found 10 adaptive and one maladaptive QTL in Italy, and six adaptive and four maladaptive QTL in Sweden. The discovery of maladaptive QTL at both sites suggests that even locally adapted populations are not always at their genotypic optimum. Mean effect sizes for adaptive QTL, 0.97 and 0.55 fruits in Italy and Sweden, respectively, were large relative to the mean fitness of the RILs (approximately 8 fruits/seedling planted at both sites). Both genetic trade-offs (four cases) and conditional neutrality (seven cases) contribute to local adaptation in this system. The 8-year dataset provided greater power to detect QTL and to estimate their locations compared to our previous 3-year study, identifying one new genetic trade-off and resolving one genetic trade-off into two conditionally adaptive QTL.

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

Quantitative trait loci mapping reveals an oligogenic architecture of a rapidly adapting trait during the European invasion of common ragweed

Biological invasions offer a unique opportunity to investigate evolution over contemporary timescales. Rapid adaptation to local climates during range expansion can be a major determinant of invasion success, yet fundamental questions remain about its genetic basis. This study sought to investigate the genetic basis of climate adaptation in invasive common ragweed (Ambrosia artemisiifolia). Flowering time adaptation is key to this annual species' invasion success, so much so that it has evolved repeated latitudinal clines in size and phenology across its native and introduced ranges despite high gene flow among populations. Here, we produced a high-density linkage map (4493 SNPs) and paired this with phenotypic data from an F2 mapping population (n = 336) to identify one major and two minor quantitative trait loci (QTL) underlying flowering time and height differentiation in this species. Within each QTL interval, several candidate flowering time genes were also identified. Notably, the major flowering time QTL detected in this study was found to overlap with a previously identified haploblock (putative inversion). Multiple genetic maps of this region identified evidence of suppressed recombination in specific genotypes, consistent with inversions. These discoveries support the expectation that a concentrated genetic architecture with fewer, larger, and more tightly linked alleles should underlie rapid local adaptation during invasion, particularly when divergently adapting populations experience high levels of gene flow.

Genetic basis of speciation and adaptation: from loci to causative mutations

Does evolution proceed in small steps or large leaps? How repeatable is evolution? How constrained is the evolutionary process? Answering these long-standing questions in evolutionary biology is indispensable for both understanding how extant biodiversity has evolved and predicting how organisms and ecosystems will respond to changing environments in the future. Understanding the genetic basis of phenotypic diversification and speciation in natural populations is key to properly answering these questions. The leap forward in genome sequencing technologies has made it increasingly easier to not only investigate the genetic architecture but also identify the variant sites underlying adaptation and speciation in natural populations. Furthermore, recent advances in genome editing technologies are making it possible to investigate the functions of each candidate gene in organisms from natural populations. In this article, we discuss how these recent technological advances enable the analysis of causative genes and mutations and how such analysis can help answer long-standing evolutionary biology questions.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Negotiating mutualism: A locus for exploitation by rhizobia has a broad effect size distribution and context-dependent effects on legume hosts

In mutualisms, variation at genes determining partner fitness provides the raw material upon which coevolutionary selection acts, setting the dynamics and pace of coevolution. However, we know little about variation in the effects of genes that underlie symbiotic fitness in natural mutualist populations. In some species of legumes that form root nodule symbioses with nitrogen‐fixing rhizobial bacteria, hosts secrete nodule‐specific cysteine‐rich (NCR) peptides that cause rhizobia to differentiate in the nodule environment. However, rhizobia can cleave NCR peptides through the expression of genes like the plasmid‐borne Host range restriction peptidase (hrrP), whose product degrades specific NCR peptides. Although hrrP activity can confer host exploitation by depressing host fitness and enhancing symbiont fitness, the effects of hrrP on symbiosis phenotypes depend strongly on the genotypes of the interacting partners. However, the effects of hrrP have yet to be characterised in a natural population context, so its contribution to variation in wild mutualist populations is unknown. To understand the distribution of effects of hrrP in wild rhizobia, we measured mutualism phenotypes conferred by hrrP in 12 wild Ensifer medicae strains. To evaluate context dependency of hrrP effects, we compared hrrP effects across two Medicago polymorpha host genotypes and across two experimental years for five E. medicae strains. We show for the first time in a natural population context that hrrP has a wide distribution of effect sizes for many mutualism traits, ranging from strongly positive to strongly negative. Furthermore, we show that hrrP effect size varies across host genotypes and experiment years, suggesting that researchers should be cautious about extrapolating the role of genes in natural populations from controlled laboratory studies of single genetic variants.

On the genetic architecture of rapidly adapting and convergent life history traits in guppies

The genetic basis of traits shapes and constrains how adaptation proceeds in nature; rapid adaptation can proceed using stores of polygenic standing genetic variation or hard selective sweeps, and increasing polygenicity fuels genetic redundancy, reducing gene re-use (genetic convergence). Guppy life history traits evolve rapidly and convergently among natural high- and low-predation environments in northern Trinidad. This system has been studied extensively at the phenotypic level, but little is known about the underlying genetic architecture. Here, we use four independent F2 QTL crosses to examine the genetic basis of seven (five female, two male) guppy life history phenotypes and discuss how these genetic architectures may facilitate or constrain rapid adaptation and convergence. We use RAD-sequencing data (16,539 SNPs) from 370 male and 267 female F2 individuals. We perform linkage mapping, estimates of genome-wide and per-chromosome heritability (multi-locus associations), and QTL mapping (single-locus associations). Our results are consistent with architectures of many loci of small-effect for male age and size at maturity and female interbrood period. Male trait associations are clustered on specific chromosomes, but female interbrood period exhibits a weak genome-wide signal suggesting a potentially highly polygenic component. Offspring weight and female size at maturity are also associated with a single significant QTL each. These results suggest rapid, repeatable phenotypic evolution of guppies may be facilitated by polygenic trait architectures, but subsequent genetic redundancy may limit gene re-use across populations, in agreement with an absence of strong signatures of genetic convergence from recent analyses of wild guppies.

Evolution of thermal physiology alters the projected range of threespine stickleback under climate change

Species distribution models (SDMs) are widely used to predict range shifts but could be unreliable under climate change scenarios because they do not account for evolution. The thermal physiology of a species is a key determinant of its range and thus incorporating thermal trait evolution into SDMs might be expected to alter projected ranges. We identified a genetic basis for physiological and behavioural traits that evolve in response to temperature change in natural populations of threespine stickleback (Gasterosteus aculeatus). Using these data, we created geographical range projections using a mechanistic niche area approach under two climate change scenarios. Under both scenarios, trait data were either static ("no evolution" models), allowed to evolve at observed evolutionary rates ("evolution" models) or allowed to evolve at a rate of evolution scaled by the trait variance that is explained by quantitative trait loci (QTL; "scaled evolution" models). We show that incorporating these traits and their evolution substantially altered the projected ranges for a widespread panmictic marine population, with over 7-fold increases in area under climate change projections when traits are allowed to evolve. Evolution-informed SDMs should improve the precision of forecasting range dynamics under climate change, and aid in their application to management and the protection of biodiversity.

Evolution in small steps and giant leaps

The first Editor of Evolution was Ernst Mayr. His foreword to the first issue of Evolution published in 1947 framed evolution as a "problem of interaction" that was just beginning to be studied in this broad context. First, I explore progress and prospects on understanding the subsidiary interactions identified by Mayr, including interactions between parts of organisms, between individuals and populations, between species, and between the organism and its abiotic environment. Mayr's overall "problem of interaction" framework is examined in the context of coevolution within and among levels of biological organization. This leads to a comparison in the relative roles of biotic versus abiotic agents of selection and fluctuating versus directional selection, followed by stabilizing selection in shaping the genomic architecture of adaptation. Oligogenic architectures may be typical for traits shaped more by fluctuating selection and biotic selection. Conversely, polygenic architectures may be typical for traits shaped more by directional followed by stabilizing selection and abiotic selection. The distribution of effect sizes and turnover dynamics of adaptive alleles in these scenarios deserves further study. Second, I review two case studies on the evolution of acquired toxicity in animals, one involving cardiac glycosides obtained from plants and one involving bacterial virulence factors horizontally transferred to animals. The approaches used in these studies and the results gained directly flow from Mayr's vision of an evolutionary biology that revolves around the "problem of interaction."

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease

Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.

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.

The genetic basis of floral mechanical isolation between two hummingbird-pollinated Neotropical understorey herbs

Floral divergence can contribute to reproductive isolation among plant lineages, and thus provides an opportunity to study the genetics of speciation, including the number, effect size, mode of action and interactions of quantitative trait loci (QTL). Moreover, flowers represent suites of functionally interrelated traits, but it is unclear to what extent the phenotypic integration of the flower is underlain by a shared genetic architecture, which could facilitate or constrain correlated evolution of floral traits. Here, we examine the genetic architecture of floral morphological traits involved in an evolutionary switch from bill to forehead pollen placement between two species of hummingbird-pollinated Neotropical understorey herbs that are reproductively isolated by these floral differences. For the majority of traits, we find multiple QTL of relatively small effect spread throughout the genome. We also find substantial colocalization and alignment of effects of QTL underlying different floral traits that function together to promote outcrossing and reduce heterospecific pollen transfer. Our results are consistent with adaptive pleiotropy or linkage of many co-adapted genes, either of which could have facilitated a response to correlated selection and helped to stabilize divergent phenotypes in the face of low levels of hybridization. Moreover, our results indicate that floral mechanical isolation can be consistent with an infinitesimal model of adaptation.

Threespine Stickleback: A Model System For Evolutionary Genomics

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

Evolution of resistance under alternative models of selective interference

The use of multiple pesticides or drugs can lead to a simultaneous selection pressure for resistance alleles at different loci. Models of resistance evolution focus on how this can delay the spread of resistance through a population, but often neglect how this can also reduce the probability that a resistance allele spreads. This neglected factor has been studied in a parallel literature as selective interference. Models of interference use alternative constructions of fitness, where selection coefficients from different loci either add or multiply. Although these are equivalent under weak selection, the two constructions make alternative predictions under the strong selection that characterizes resistance evolution. Here, simulations are used to examine the effects of interference on the probability of fixation and time to fixation of a new and strongly beneficial mutation in the presence of another strongly beneficial allele with variable starting frequency. The results from simulations show a complicated pattern of effects. The key result is that, under multiplicativity, the presence of the strongly beneficial allele leads to a small reduction in the probability of fixation for the new beneficial mutation up to ~10%, and a negligible increase in the average time to fixation up to ~2%, whereas under additivity, the effect is more substantial at up to ~50% for the probability of fixation and ~100% for the average time to fixation. Consequently, the effect of interference is only an important feature of resistance evolution under additivity. Current evidence from studies of experimental evolution provides widespread support for the basic features of additivity, which suggests that interference may afford resistance a different pattern of evolution than other adaptations: rather than the gradual and simultaneous selection of many alleles with small effects, the rapid evolution of resistance may involve the sequential selection of alleles with large effects.

Structure and contingency determine mutational hotspots for flower color evolution

Evolutionary genetic studies have uncovered abundant evidence for genomic hotspots of phenotypic evolution, as well as biased patterns of mutations at those loci. However, the theoretical basis for this concentration of particular types of mutations at particular loci remains largely unexplored. In addition, historical contingency is known to play a major role in evolutionary trajectories, but has not been reconciled with the existence of such hotspots. For example, do the appearance of hotspots and the fixation of different types of mutations at those loci depend on the starting state and/or on the nature and direction of selection? Here, we use a computational approach to examine these questions, focusing the anthocyanin pigmentation pathway, which has been extensively studied in the context of flower color transitions. We investigate two transitions that are common in nature, the transition from blue to purple pigmentation and from purple to red pigmentation. Both sets of simulated transitions occur with a small number of mutations at just four loci and show strikingly similar peaked shapes of evolutionary trajectories, with the mutations of the largest effect occurring early but not first. Nevertheless, the types of mutations (biochemical vs. regulatory) as well as their direction and magnitude are contingent on the particular transition. These simulated color transitions largely mirror findings from natural flower color transitions, which are known to occur via repeated changes at a few hotspot loci. Still, some types of mutations observed in our simulated color evolution are rarely observed in nature, suggesting that pleiotropic effects further limit the trajectories between color phenotypes. Overall, our results indicate that the branching structure of the pathway leads to a predictable concentration of evolutionary change at the hotspot loci, but the types of mutations at these loci and their order is contingent on the evolutionary context.

Suppressing evolution in genetically engineered systems through repeated supplementation

Genetically engineered organisms are prone to evolve in response to the engineering. This evolution is often undesirable and can negatively affect the purpose of the engineering. Methods that maintain the stability of engineered genomes are therefore critical to the successful design and use of genetically engineered organisms. One potential method to limit unwanted evolution is by taking advantage of the ability of gene flow to counter local adaption, a process of supplementation. Here, we investigate the feasibility of supplementation as a mechanism to offset the evolutionary degradation of a transgene in three model systems: a bioreactor, a gene drive, and a transmissible vaccine. In each model, continual introduction from a stock is used to balance mutation and selection against the transgene. Each system has its unique features. The bioreactor system is especially tractable and has a simple answer: The level of supplementation required to maintain the transgene at a frequency p ^ is approximatelyp ^ s , where s is the selective disadvantage of the transgene. Supplementation is also feasible in the transmissible vaccine case but is probably not practical to prevent the evolution of resistance against a gene drive. We note, however, that the continual replacement of even a small fraction of a large population can be challenging, limiting the usefulness of supplementation as a means of controlling unwanted evolution.

Fitness maps to a large-effect locus in introduced stickleback populations

Mutations of small effect underlie most adaptation to new environments, but beneficial variants with large fitness effects are expected to contribute under certain conditions. Genes and genomic regions having large effects on phenotypic differences between populations are known from numerous taxa, but fitness effect sizes have rarely been estimated. We mapped fitness over a generation in an F2 intercross between a marine and a lake stickleback population introduced to a freshwater pond. A quantitative trait locus map of the number of surviving offspring per F2 female detected a single, large-effect locus near Ectodysplasin (Eda), a gene having an ancient freshwater allele causing reduced bony armor and other changes. F2 females homozygous for the freshwater allele had twice the number of surviving offspring as homozygotes for the marine allele, producing a large selection coefficient, s = 0.50 ± 0.09 SE. Correspondingly, the frequency of the freshwater allele increased from 0.50 in F2 mothers to 0.58 in surviving offspring. We compare these results to allele frequency changes at the Eda gene in an Alaskan lake population colonized by marine stickleback in the 1980s. The frequency of the freshwater Eda allele rose steadily over multiple generations and reached 95% within 20 y, yielding a similar estimate of selection, s = 0.49 ± 0.05, but a different degree of dominance. These findings are consistent with other studies suggesting strong selection on this gene (and/or linked genes) in fresh water. Selection on ancient genetic variants carried by colonizing ancestors is likely to increase the prevalence of large-effect fitness variants in adaptive evolution.

Firstborn sex defines early childhood growth of subsequent siblings

Animal studies have shown that maternal resource allocation can be sex-biased in order to maximize reproductive success, yet this basic concept has not been investigated in humans. In this study, we explored relationships between maternal factors, offspring sex and prenatal and postnatal weight gain. Sex-specific regression models not only indicated that maternal ethnicity impacted male (n = 2456) and female (n = 1871) childrens postnatal weight gain differently but also that parity and mode of feeding influenced weight velocity of female (β ± s.e. = -0.31 ± 0.11 kg, p = 0.005; β ± s.e. = -0.37 ± 0.11 kg, p < 0.001) but not male offspring. Collectively, our findings imply that maternal resource allocation to consecutive offspring increases after a male firstborn. The absence of this finding in formula fed children suggests that this observation could be mediated by breast milk. Our results warrant further mechanistic and epidemiological studies to elucidate the role of breastfeeding on the programming of infant growth as well as of metabolic and cardiovascular diseases, with potential implications for tailoring infant formulae according to sex and birth order.

The Evolutionary Genomics of Serpentine Adaptation

Serpentine barrens are among the most challenging settings for plant life. Representing a perfect storm of hazards, serpentines consist of broadly skewed elemental profiles, including abundant toxic metals and low nutrient contents on drought-prone, patchily distributed substrates. Accordingly, plants that can tolerate the challenges of serpentine have fascinated biologists for decades, yielding important insights into adaptation to novel ecologies through physiological change. Here we highlight recent progress from studies which demonstrate the power of serpentine as a model for the genomics of adaptation. Given the moderate - but still tractable - complexity presented by the mix of hazards on serpentine, these venues are well-suited for the experimental inquiry of adaptation both in natural and manipulated conditions. Moreover, the island-like distribution of serpentines across landscapes provides abundant natural replicates, offering power to evolutionary genomic inference. Exciting recent insights into the genomic basis of serpentine adaptation point to a partly shared basis that involves sampling from common allele pools available from retained ancestral polymorphism or via gene flow. However, a lack of integrated studies deconstructing complex adaptations and linking candidate alleles with fitness consequences leaves room for much deeper exploration. Thus, we still seek the crucial direct link between the phenotypic effect of candidate alleles and their measured adaptive value - a prize that is exceedingly rare to achieve in any study of adaptation. We expect that closing this gap is not far off using the promising model systems described here.

Genetic and environmental canalization are not associated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves are limited despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia)

Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.

Contingent Convergence: The Ability To Detect Convergent Genomic Evolution Is Dependent on Population Size and Migration

Outlier scans, in which the genome is scanned for signatures of selection, have become a prominent tool in studies of local adaptation, and more recently studies of genetic convergence in natural populations. However, such methods have the potential to be confounded by features of demographic history, such as population size and migration, which are considerably varied across natural populations. In this study, we use forward-simulations to investigate and illustrate how several measures of genetic differentiation commonly used in outlier scans (FST, DXY and Δπ) are influenced by demographic variation across multiple sampling generations. In a factorial design with 16 treatments, we manipulate the presence/absence of founding bottlenecks (N of founding individuals), prolonged bottlenecks (proportional size of diverging population) and migration rate between two populations with ancestral and diverged phenotypic optima. Our results illustrate known constraints of individual measures associated with reduced population size and a lack of migration; but notably we demonstrate how relationships between measures are similarly dependent on these features of demography. We find that false-positive signals of convergent evolution (the same simulated outliers detected in independent treatments) are attainable as a product of similar population size and migration treatments (particularly for DXY), and that outliers across different measures (for e.g., FST and DXY) can occur with little influence of selection. Taken together, we show how underappreciated, yet quantifiable measures of demographic history can influence commonly employed methods for detecting selection.

Genetic and physiological mechanisms of freezing tolerance in locally adapted populations of a winter annual

PREMISE

Despite myriad examples of local adaptation, the phenotypes and genetic variants underlying such adaptive differentiation are seldom known. Recent work on freezing tolerance and local adaptation in ecotypes of Arabidopsis thaliana from Italy and Sweden provides an essential foundation for uncovering the genotype-phenotype-fitness map for an adaptive response to a key environmental stress.

METHODS

We examined the consequences of a naturally occurring loss-of-function (LOF) mutation in an Italian allele of the gene that encodes the transcription factor CBF2, which underlies a major freezing-tolerance locus. We used four lines with a Swedish genetic background, each containing a LOF CBF2 allele. Two lines had introgression segments containing the Italian CBF2 allele, and two contained deletions created using CRISPR-Cas9. We used a growth chamber experiment to quantify freezing tolerance and gene expression before and after cold acclimation.

RESULTS

Freezing tolerance was lower in the Italian (11%) compared to the Swedish (72%) ecotype, and all four experimental CBF2 LOF lines had reduced freezing tolerance compared to the Swedish ecotype. Differential expression analyses identified 10 genes for which all CBF2 LOF lines, and the IT ecotype had similar patterns of reduced cold responsive expression compared to the SW ecotype.

CONCLUSIONS

We identified 10 genes that are at least partially regulated by CBF2 that may contribute to the differences in cold-acclimated freezing tolerance between the Italian and Swedish ecotypes. These results provide novel insight into the molecular and physiological mechanisms connecting a naturally occurring sequence polymorphism to an adaptive response to freezing conditions.

Utilizing the blind cavefish Astyanax mexicanus to understand the genetic basis of behavioral evolution

Colonization of novel habitats often results in the evolution of diverse behaviors. Comparisons between individuals from closely related populations that have evolved divergent behaviors in different environments can be used to investigate behavioral evolution. However, until recently, functionally connecting genotypes to behavioral phenotypes in these evolutionarily relevant organisms has been difficult. The development of gene editing tools will facilitate functional genetic analysis of genotype–phenotype connections in virtually any organism, and has the potential to significantly transform the field of behavioral genetics when applied to ecologically and evolutionarily relevant organisms. The blind cavefish Astyanax mexicanus provides a remarkable example of evolution associated with colonization of a novel habitat. These fish consist of a single species that includes sighted surface fish that inhabit the rivers of Mexico and southern Texas and at least 29 populations of blind cavefish from the Sierra Del Abra and Sierra de Guatemala regions of Northeast Mexico. Although eye loss and albinism have been studied extensively in A. mexicanus, derived behavioral traits including sleep loss, alterations in foraging and reduction in social behaviors are now also being investigated in this species to understand the genetic and neural basis of behavioral evolution. Astyanax mexicanus has emerged as a powerful model system for genotype–phenotype mapping because surface and cavefish are interfertile. Further, the molecular basis of repeated trait evolution can be examined in this species, as multiple cave populations have independently evolved the same traits. A sequenced genome and the implementation of gene editing in A. mexicanus provides a platform for gene discovery and identification of the contributions of naturally occurring variation to behaviors. This review describes the current knowledge of behavioral evolution in A. mexicanus with an emphasis on the molecular and genetic underpinnings of evolved behaviors. Multiple avenues of new research that can be pursued using gene editing tools are identified, and how these will enhance our understanding of behavioral evolution is discussed.

Two reproductive traits show contrasting genetic architectures in Plantago lanceolata

In many species, temperature-sensitive phenotypic plasticity (i.e., an individual's phenotypic response to temperature) displays a positive correlation with latitude, a pattern presumed to reflect local adaptation. This geographical pattern raises two general questions: (a) Do a few large-effect genes contribute to latitudinal variation in a trait? (b) Is the thermal plasticity of different traits regulated pleiotropically? To address the questions, we crossed individuals of Plantago lanceolata derived from northern and southern European populations. Individuals naturally exhibited high and low thermal plasticity in floral reflectance and flowering time. We grew parents and offspring in controlled cool- and warm-temperature environments, mimicking what plants would encounter in nature. We obtained genetic markers via genotype-by-sequencing, produced the first recombination map for this ecologically important nonmodel species, and performed quantitative trait locus (QTL) mapping of thermal plasticity and single-environment values for both traits. We identified a large-effect QTL that largely explained the reflectance plasticity differences between northern and southern populations. We identified multiple smaller-effect QTLs affecting aspects of flowering time, one of which affected flowering time plasticity. The results indicate that the genetic architecture of thermal plasticity in flowering is more complex than for reflectance. One flowering time QTL showed strong cytonuclear interactions under cool temperatures. Reflectance and flowering plasticity QTLs did not colocalize, suggesting little pleiotropic genetic control and freedom for independent trait evolution. Such genetic information about the architecture of plasticity is environmentally important because it informs us about the potential for plasticity to offset negative effects of climate change.

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.

Mating system impacts the genetic architecture of adaptation to heterogeneous environments

Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation. We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an F_ST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability. Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on N_e . Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Sampling strategy optimization to increase statistical power in landscape genomics: A simulation-based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.

Epistasis Detection and Modeling for Genomic Selection in Cowpea (Vigna unguiculata L. Walp.)

Genetic architecture reflects the pattern of effects and interaction of genes underlying phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, consideration for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect-sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 (PCL1 [Vigun11g157600]) and PHYTOCHROME A (PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model, while using known quantitative trait nucleotide(s) (QTNs) as fixed effects improved prediction accuracy when traits were controlled by large effect loci. In general, our study demonstrated that prior understanding of the genetic architecture of a trait can help make informed decisions in GEB.

A homeotic shift late in development drives mimetic color variation in a bumble bee

Natural phenotypic radiations, with their high diversity and convergence, are well-suited for informing how genomic changes translate to natural phenotypic variation. New genomic tools enable discovery in such traditionally nonmodel systems. Here, we characterize the genomic basis of color pattern variation in bumble bees (Hymenoptera, Apidae, Bombus), a group that has undergone extensive convergence of setal color patterns as a result of Müllerian mimicry. In western North America, multiple species converge on local mimicry patterns through parallel shifts of midabdominal segments from red to black. Using genome-wide association, we establish that a cis-regulatory locus between the abdominal fate-determining Hox genes, abd-A and Abd-B, controls the red-black color switch in a western species, Bombus melanopygus Gene expression analysis reveals distinct shifts in Abd-B aligned with the duration of setal pigmentation at the pupal-adult transition. This results in atypical anterior Abd-B expression, a late developmental homeotic shift. Changing expression of Hox genes can have widespread effects, given their important role across segmental phenotypes; however, the late timing reduces this pleiotropy, making Hox genes suitable targets. Analysis of this locus across mimics and relatives reveals that other species follow independent genetic routes to obtain the same phenotypes.

Symbiont evolution during the free-living phase can improve host colonization

For micro-organisms cycling between free-living and host-associated stages, where reproduction occurs in both of these lifestyles, an interesting inquiry is whether evolution during the free-living stage can be positively pleiotropic to microbial fitness in a host environment. To address this topic, the squid host Euprymna tasmanica and the marine bioluminescent bacterium Vibrio fischeri were utilized. Microbial ecological diversification in static liquid microcosms was used to simulate symbiont evolution during the free-living stage. Thirteen genetically distinct V. fischeri strains from a broad diversity of ecological sources (e.g. squid light organs, fish light organs and seawater) were examined to see if the results were reproducible in many different genetic settings. Genetic backgrounds that are closely related can be predisposed to considerable differences in how they respond to similar selection pressures. For all strains examined, new mutations with striking and facilitating effects on host colonization arose quickly during microbial evolution in the free-living stage, regardless of the ecological context under consideration for a strain’s genetic background. Microbial evolution outside a host environment promoted host range expansion, improved host colonization for a micro-organism, and diminished the negative correlation between biofilm formation and motility.

Pseudogenization and Resurrection of a Speciation Gene

A persistent question in evolutionary biology is how complex phenotypes evolve and whether phenotypic transitions are reversible. Multiple losses of floral pigmentation have been documented in the angiosperms, but color re-gain has not yet been described, supporting that re-gain is unlikely. Pollinator-mediated selection in Petunia has resulted in several color shifts comprised of both losses and gains of color. The R2R3-MYB transcription factor AN2 has been identified as a major locus responsible for shifts in pollinator preference. Whereas the loss of visible color has previously been attributed to repeated pseudogenization of AN2, here, we describe the mechanism of an independent re-gain of floral color via AN2 evolution. In P. secreta, purple color is restored through the improbable resurrection of AN2 gene function from a non-functional AN2-ancestor by a single reading-frame-restoring mutation. Thus, floral color evolution in Petunia is mechanistically dependent on AN2 functionality, highlighting its role as a hotspot in color transitions and a speciation gene for the genus.

Antagonistic pleiotropy for carbon use is rare in new mutations

Pleiotropic effects of mutations underlie diverse biological phenomena such as ageing and specialization. In particular, antagonistic pleiotropy ("AP": when a mutation has opposite fitness effects in different environments) generates tradeoffs, which may constrain adaptation. Models of adaptation typically assume that AP is common - especially among large-effect mutations - and that pleiotropic effect sizes are positively correlated. Empirical tests of these assumptions have focused on de novo beneficial mutations arising under strong selection. However, most mutations are actually deleterious or neutral, and may contribute to standing genetic variation that can subsequently drive adaptation. We quantified the incidence, nature, and effect size of pleiotropy for carbon utilization across 80 single mutations in Escherichia coli that arose under mutation accumulation (i.e., weak selection). Although ∼46% of the mutations were pleiotropic, only 11% showed AP; among beneficial mutations, only ∼4% showed AP. In some environments, AP was more common in large-effect mutations; and AP effect sizes across environments were often negatively correlated. Thus, AP for carbon use is generally rare (especially among beneficial mutations); is not consistently enriched in large-effect mutations; and often involves weakly deleterious antagonistic effects. Our unbiased quantification of mutational effects therefore suggests that antagonistic pleiotropy may be unlikely to cause maladaptive tradeoffs.

Gene regulation underlies environmental adaptation in house mice

Changes in cis-regulatory regions are thought to play a major role in the genetic basis of adaptation. However, few studies have linked cis-regulatory variation with adaptation in natural populations. Here, using a combination of exome and RNA-seq data, we performed expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses to study the genetic architecture of regulatory variation in wild house mice (Mus musculus domesticus) using individuals from five populations collected along a latitudinal cline in eastern North America. Mice in this transect showed clinal patterns of variation in several traits, including body mass. Mice were larger in more northern latitudes, in accordance with Bergmann's rule. We identified 17 genes where cis-eQTLs were clinal outliers and for which expression level was correlated with latitude. Among these clinal outliers, we identified two genes (Adam17 and Bcat2) with cis-eQTLs that were associated with adaptive body mass variation and for which expression is correlated with body mass both within and between populations. Finally, we performed a weighted gene co-expression network analysis (WGCNA) to identify expression modules associated with measures of body size variation in these mice. These findings demonstrate the power of combining gene expression data with scans for selection to identify genes involved in adaptive phenotypic evolution, and also provide strong evidence for cis-regulatory elements as essential loci of environmental adaptation in natural populations.

Genetic Basis of Body Color and Spotting Pattern in Redheaded Pine Sawfly Larvae (Neodiprion lecontei)

Pigmentation has emerged as a premier model for understanding the genetic basis of phenotypic evolution, and a growing catalog of color loci is starting to reveal biases in the mutations, genes, and genetic architectures underlying color variation in the wild. However, existing studies have sampled a limited subset of taxa, color traits, and developmental stages. To expand the existing sample of color loci, we performed QTL mapping analyses on two types of larval pigmentation traits that vary among populations of the redheaded pine sawfly (Neodiprion lecontei): carotenoid-based yellow body color and melanin-based spotting pattern. For both traits, our QTL models explained a substantial proportion of phenotypic variation and suggested a genetic architecture that is neither monogenic nor highly polygenic. Additionally, we used our linkage map to anchor the current N. lecontei genome assembly. With these data, we identified promising candidate genes underlying (1) a loss of yellow pigmentation in populations in the mid-Atlantic/northeastern United States [C locus-associated membrane protein homologous to a mammalian HDL receptor-2 gene (Cameo2) and lipid transfer particle apolipoproteins II and I gene (apoLTP-II/I)], and (2) a pronounced reduction in black spotting in Great Lakes populations [members of the yellow gene family, tyrosine hydroxylase gene (pale), and dopamine N-acetyltransferase gene (Dat)]. Several of these genes also contribute to color variation in other wild and domesticated taxa. Overall, our findings are consistent with the hypothesis that predictable genes of large effect contribute to color evolution in nature.

Genetic basis of photosynthetic responses to cold in two locally adapted populations of Arabidopsis thaliana

Local adaptation is common, but the traits and genes involved are often unknown. Physiological responses to cold probably contribute to local adaptation in wide-ranging species, but the genetic basis underlying natural variation in these traits has rarely been studied. Using a recombinant inbred (495 lines) mapping population from locally adapted populations of Arabidopsis thaliana from Sweden and Italy, we grew plants at low temperature and mapped quantitative trait loci (QTLs) for traits related to photosynthesis: maximal quantum efficiency (Fv/Fm), rapidly reversible photoprotection (NPQfast), and photoinhibition of PSII (NPQslow) using high-throughput, whole-plant measures of chlorophyll fluorescence. In response to cold, the Swedish line had greater values for all traits, and for every trait, large effect QTLs contributed to parental differences. We found one major QTL affecting all traits, as well as unique major QTLs for each trait. Six trait QTLs overlapped with previously published locally adaptive QTLs based on fitness measured in the native environments over 3 years. Our results demonstrate that photosynthetic responses to cold can vary dramatically within a species, and may predominantly be caused by a few QTLs of large effect. Some photosynthesis traits and QTLs probably contribute to local adaptation in this system.

The genetic and molecular architecture of phenotypic diversity in sticklebacks

A major goal of evolutionary biology is to identify the genotypes and phenotypes that underlie adaptation to divergent environments. Stickleback fish, including the threespine stickleback (Gasterosteus aculeatus) and the ninespine stickleback (Pungitius pungitius), have been at the forefront of research to uncover the genetic and molecular architecture that underlies phenotypic diversity and adaptation. A wealth of quantitative trait locus (QTL) mapping studies in sticklebacks have provided insight into long-standing questions about the distribution of effect sizes during adaptation as well as the role of genetic linkage in facilitating adaptation. These QTL mapping studies have also provided a basis for the identification of the genes that underlie phenotypic diversity. These data have revealed that mutations in regulatory elements play an important role in the evolution of phenotypic diversity in sticklebacks. Genetic and molecular studies in sticklebacks have also led to new insights on the genetic basis of repeated evolution and suggest that the same loci are involved about half of the time when the same phenotypes evolve independently. When the same locus is involved, selection on standing variation and repeated mutation of the same genes have both contributed to the evolution of similar phenotypes in independent populations.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.

Novel Candidate Genes Underlying Extreme Trophic Specialization in Caribbean Pupfishes

The genetic changes responsible for evolutionary transitions from generalist to specialist phenotypes are poorly understood. Here we examine the genetic basis of craniofacial traits enabling novel trophic specialization in a sympatric radiation of Cyprinodon pupfishes endemic to San Salvador Island, Bahamas. This recent radiation consists of a generalist species and two novel specialists: a small-jawed "snail-eater" and a large-jawed "scale-eater." We genotyped 12 million single nucleotide polymorphisms (SNPs) by whole-genome resequencing of 37 individuals of all three species from nine populations and integrated genome-wide divergence scans with association mapping to identify divergent regions containing putatively causal SNPs affecting jaw size-the most rapidly diversifying trait in this radiation. A mere 22 fixed variants accompanied extreme ecological divergence between generalist and scale-eater species. We identified 31 regions (20 kb) containing variants fixed between specialists that were significantly associated with variation in jaw size which contained 11 genes annotated for skeletal system effects and 18 novel candidate genes never previously associated with craniofacial phenotypes. Six of these 31 regions showed robust signs of hard selective sweeps after accounting for demographic history. Our data are consistent with predictions based on quantitative genetic models of adaptation, suggesting that the effect sizes of regions influencing jaw phenotypes are positively correlated with distance between fitness peaks on a complex adaptive landscape.