POPULATION DIFFERENTIATION IN G MATRIX STRUCTURE DUE TO NATURAL SELECTION IN RANA TEMPORARIA

Impacts of oxygen deficiency on embryo life-history traits of migratory locust Locusta migratoria from low and high altitudes

Hypoxia challenges aerobic organisms in numerous environments, and hypoxic conditions may become more severe under future climate-change scenarios. The impact of hypoxia on the development of terrestrial insect embryos is not well understood. Here, to address this gap, embryonic life-history traits of migratory locust Locusta migratoria from low-altitude and high-altitude regions were compared under 2 oxygen levels: normoxia (i.e., 21 kPa oxygen partial pressure and mild hypoxia (i.e., 10 kPa oxygen partial pressure). Our results demonstrated that, whether reared under normoxia or mild hypoxia, L. migratoria from high-altitude populations had longer developmental times, reduced weight, and lower mean relative growth rate as compared with those from low-altitude populations. When transferred from normoxia to mild hypoxia, nearly all the tested life-history traits presented significant negative changes in the low-altitude populations, but not in the high-altitude populations. The factor 'strain' alone explained 18.26%-54.59% of the total variation for traits, suggesting that the phenotypic differences between L. migratoria populations from the 2 altitudes could be driven by genetic variation. Significant genetic correlations were found between life-history traits, and most of these showed differentiation between the 2 altitudinal gradients. G-matrix comparisons showed significant structural differences between L. migratoria from the 2 regions, as well as several negative covariances (i.e., trade-offs) between traits in the low-altitude populations. Overall, our study provides clear evidence that evolutionary divergence of embryonic traits between L. migratoria populations from different altitudes has occurred.

Introduced populations of ragweed show as much evolutionary potential as native populations

Invasive species are a global economic and ecological problem. They also offer an opportunity to understand evolutionary processes in a colonizing context. The impacts of evolutionary factors, such as genetic variation, on the invasion process are increasingly appreciated, but there remain gaps in the empirical literature. The adaptive potential of populations can be quantified using genetic variance-covariance matrices (G), which encapsulate the heritable genetic variance in a population. Here, we use a multivariate Bayesian approach to assess the adaptive potential of invasive populations of ragweed (Ambrosia artemisiifolia), a serious allergen and agricultural weed. We compared several aspects of genetic architecture and the structure of G matrices between three native and three introduced populations, based on phenotypic data collected in a field common garden experiment. We found moderate differences in the quantitative genetic architecture among populations, but we did not find that introduced populations suffer from a limited adaptive potential or increased genetic constraint compared with native populations. Ragweed has an annual life history, is an obligate outcrosser, and produces very large numbers of seeds and pollen grains. These characteristics, combined with the significant additive genetic variance documented here, suggest ragweed will be able to respond quickly to selection pressures in both its native and introduced ranges.

Environmentally triggered variability in the genetic variance-covariance of herbivory resistance of an exotic plant Solidago altissima

The variability in the genetic variance-covariance (G-matrix) in plant resistance and its role in the evolution of invasive plants have been long overlooked. We conducted an additional analysis of the data of a reciprocal transplant experiment with tall goldenrod, Solidago altissima, in multiple garden sites within its native range (USA) and introduced range (Japan). We explored the differences in G-matrix of resistance to two types of foliar herbivores: (a) a lace bug that is native to the USA and recently introduced to Japan, (b) and other herbivorous insects in response to plant origins and environments. A negative genetic covariance was found between plant resistances to lace bugs and other herbivorous insects, in all combinations of garden locations and plant origins except for US plants planted in US gardens. The G-matrix of the resistance indices did not differ between US and Japanese plants either in US or Japanese gardens, while it differed between US and Japanese gardens in both US and Japanese plants. Our results suggested that the G-matrix of the plant resistance may have changed in response to novel environmental differences including herbivore communities and/or other biotic and abiotic factors in the introduced range. This may have revealed a hidden trade-off between resistances, masked by the environmental factors in the origin range. These results suggest that the stability of the genetic covariance during invasion, and the environmentally triggered variability in the G-matrices of plant resistance may help to protect the plant against multiple herbivore species without changing its genetic architecture and that this may lead to a rapid adaptation of resistance in exotic plants. Local environments of the plant also have a critical effect on plant resistance and should be considered in order to understand trait evolution in exotic plants.

Ecomorphological specialization leads to loss of evolvability in primate limbs

Primate limb morphology is often described as either generalized, that is, suited to a range of locomotor and positional behaviors, or specialized for unique locomotor behaviors such as brachiation or bipedalism. The evolution of highly specialized limb morphology may result in loss of evolvability, that is, in a decreased capacity of the locomotor skeleton to evolve in response to selection towards alternative ecomorphological niches. Using evolutionary simulations, I show that the highly specialized limb anatomy of hominoids is associated with a significant loss of evolvability, defined as the number of generations to reach alternative adaptive peaks, and in parallel an increased risk of extinction, particularly in simulated evolution toward generalized quadrupedal limb proportions. Loss of evolvability in apes and humans correlates with three factors: (1) decreased correlation among limb bone lengths (i.e., integration), which slows the rate of change along lines of least evolutionary resistance; (2) limb specialization, which places apes and humans in relatively remote areas of morphospace; and (3) increased skeletal size as a proxy for body size. Thus, locomotor over-specialization can lead to evolutionary dead-ends that significantly increase the probability of hominoid populations going extinct before evolving new adaptive morphologies.

Animal models with group-specific additive genetic variances: extending genetic group models

BACKGROUND

The animal model is a key tool in quantitative genetics and has been used extensively to estimate fundamental parameters, such as additive genetic variance or heritability. An implicit assumption of animal models is that all founder individuals derive from a single population. This assumption is commonly violated, for instance in crossbred livestock or when a meta-population is split into genetically differentiated subpopulations. Ignoring that base populations are genetically heterogeneous and thus split into different 'genetic groups' may lead to biased parameter estimates, especially for additive genetic variance. To avoid such biases, genetic group animal models, which account for the presence of more than one genetic group, have been proposed. Unfortunately, the method to date is only computationally feasible when the breeding values of the groups are allowed to differ in their means, but not in their variances.

RESULTS

We present an extension of the animal model that permits estimation of group-specific additive genetic variances. This is achieved by employing group-specific relatedness matrices for the breeding value components to different genetic groups. We derive these matrices by decomposing the full relatedness matrix via the generalized Cholesky decomposition, and by scaling the respective matrix components for each group. We propose a computationally convenient approximation for the matrix component that encodes for the Mendelian sampling variance, and show that this approximation is not critical. In addition, we explain why segregation variances are often negligible when analyzing the complex polygenic traits that are frequently the focus of evolutionary ecologists and animal breeders. Simulations and an example from an insular meta-population of house sparrows in Norway with three distinct genetic groups illustrate that the method is successful in estimating group-specific additive genetic variances, and that segregation variances are indeed negligible in the empirical example.

CONCLUSIONS

Quantifying differences in additive genetic variance within and among populations is of major biological interest in ecology, evolution, and animal and plant breeding. The proposed method allows to estimate such differences for subpopulations that form a connected set of populations, and may thus also be useful to study temporal or spatial variation of additive genetic variances.

Mapping of quantitative trait loci for life history traits segregating within common frog populations

The evolution of complex traits is often shaped by adaptive divergence. However, very little is known about the number, effect size, and location of the genomic regions influencing the variation of these traits in natural populations. Based on a dense linkage map of the common frog, Rana temporaria, we have localized, for the first time in amphibians, three significant and nine suggestive quantitative trait loci (QTLs) for metabolic rate, growth rate, development time, and weight at metamorphosis, explaining 5.6-18.9% of the overall phenotypic variation in each trait. We also found a potential pleiotropic QTL between development time and size at metamorphosis that, if confirmed, might underlie the previously reported genetic correlation between these traits. Furthermore, we demonstrate that the genetic variation linked to fitness-related larval traits segregates within Rana temporaria populations. This study provides the first insight into the genomic regions that affect larval life history traits in anurans, providing a valuable resource to delve further into the genomic basis of evolutionary change in amphibians.

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments.

It's just sand between the toes: how particle size and shape variation affect running performance and kinematics in a generalist lizard

Animals must cope with and be able to move effectively on a variety of substrates. Substrates composed of granular media, such as sand and gravel, are extremely common in nature, and vary tremendously in particle size and shape. Despite many studies of the properties of granular media and comparisons of locomotion between granular and solid substrates, the effects of systematically manipulating these media on locomotion is poorly understood. We studied granular media ranging over four orders of magnitude in particle size, and differing in the amount of particle shape variation, to determine how these factors affected substrate physical properties and sprinting in the generalist lizard Eremias arguta. We found that media with intermediate particle sizes had high bulk densities, low angles of stability and low load-bearing capacities. Rock substrates with high shape variation had higher values for all three properties than glass bead substrates with low shape variation. We found that E. arguta had the highest maximum velocities and accelerations on intermediate size particles, and higher velocities on rock than glass beads. Lizards had higher stride frequencies and lower duty factors on intermediate particle size substrates, but their stride lengths did not change with substrate. Our findings suggest that sand and gravel may represent different locomotor challenges for animals. Sand substrates provide animals with an even surface for running, but particles shift underfoot. In contrast, gravel particles are heavy, so move far less underfoot, yet provide the animal with an uneven substrate.

Structure and stability of genetic variance-covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three-spined stickleback

The genetic variance-covariance matrix (G) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G-matrices is limited for two reasons. First, phenotypes are high-dimensional, whereas traditional statistical methods are tuned to estimate and analyse low-dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high-dimensional G-matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half-sib breeding design of three-spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low-temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability-as well as the similarity among G-matrices-may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G-matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G, they also illustrate that by enabling the estimation of large G-matrices, the BSFG method can improve predicted evolutionary responses to selection.

Relaxation of herbivore-mediated selection drives the evolution of genetic covariances between plant competitive and defense traits

Insect herbivores are important mediators of selection on traits that impact plant defense against herbivory and competitive ability. Although recent experiments demonstrate a central role for herbivory in driving rapid evolution of defense and competition-mediating traits, whether and how herbivory shapes heritable variation in these traits remains poorly understood. Here, we evaluate the structure and evolutionary stability of the G matrix for plant metabolites that are involved in defense and allelopathy in the tall goldenrod, Solidago altissima. We show that G has evolutionarily diverged between experimentally replicated populations that evolved in the presence versus the absence of ambient herbivory, providing direct evidence for the evolution of G by natural selection. Specifically, evolution in an herbivore-free habitat altered the orientation of G, revealing a negative genetic covariation between defense- and competition-related metabolites that is typically masked in herbivore-exposed populations. Our results may be explained by predictions of classical quantitative genetic theory, as well as the theory of acquisition-allocation trade-offs. The study provides compelling evidence that herbivory drives the evolution of plant genetic architecture.

Conserved G-matrices of morphological and life-history traits among continental and island blue tit populations

The genetic variance-covariance matrix (G-matrix) summarizes the genetic architecture of multiple traits. It has a central role in the understanding of phenotypic divergence and the quantification of the evolutionary potential of populations. Laboratory experiments have shown that G-matrices can vary rapidly under divergent selective pressures. However, because of the demanding nature of G-matrix estimation and comparison in wild populations, the extent of its spatial variability remains largely unknown. In this study, we investigate spatial variation in G-matrices for morphological and life-history traits using long-term data sets from one continental and three island populations of blue tit (Cyanistes caeruleus) that have experienced contrasting population history and selective environment. We found no evidence for differences in G-matrices among populations. Interestingly, the phenotypic variance-covariance matrices (P) were divergent across populations, suggesting that using P as a substitute for G may be inadequate. These analyses also provide the first evidence in wild populations for additive genetic variation in the incubation period (that is, the period between last egg laid and hatching) in all four populations. Altogether, our results suggest that G-matrices may be stable across populations inhabiting contrasted environments, therefore challenging the results of previous simulation studies and laboratory experiments.

Comparative High-Density Linkage Mapping Reveals Conserved Genome Structure but Variation in Levels of Heterochiasmy and Location of Recombination Cold Spots in the Common Frog

By combining 7077 SNPs and 61 microsatellites, we present the first linkage map for some of the early diverged lineages of the common frog, Rana temporaria, and the densest linkage map to date for this species. We found high homology with the published linkage maps of the Eastern and Western lineages but with differences in the order of some markers. Homology was also strong with the genome of the Tibetan frog Nanorana parkeri and we found high synteny with the clawed frog Xenopus tropicalis. We confirmed marked heterochiasmy between sexes and detected nonrecombining regions in several groups of the male linkage map. Contrary to the expectations set by the male heterogamety of the common frog, we did not find male heterozygosity excess in the chromosome previously shown to be linked to sex determination. Finally, we found blocks of loci showing strong transmission ratio distortion. These distorted genomic regions might be related to genetic incompatibilities between the parental populations, and are promising candidates for further investigation into the genetic basis of speciation and adaptation in the common frog.

Similarity in G matrix structure among natural populations of Arabidopsis lyrata

Understanding the stability of the G matrix in natural populations is fundamental for predicting evolutionary trajectories; yet, the extent of its spatial variation and how this impacts responses to selection remain open questions. With a nested paternal half-sib crossing design and plants grown in a field experiment, we examined differences in the genetic architecture of flowering time, floral display, and plant size among four Scandinavian populations of Arabidopsis lyrata. Using a multivariate Bayesian framework, we compared the size, shape, and orientation of G matrices and assessed their potential to facilitate or constrain trait evolution. Flowering time, floral display and rosette size varied among populations and significant additive genetic variation within populations indicated potential to evolve in response to selection. Yet, some characters, including flowering start and number of flowers, may not evolve independently because of genetic correlations. Using a multivariate framework, we found few differences in the genetic architecture of traits among populations. G matrices varied mostly in size rather than shape or orientation. Differences in multivariate responses to selection predicted from differences in G were small, suggesting overall matrix similarity and shared constraints to trait evolution among populations.

The alignment between phenotypic plasticity, the major axis of genetic variation and the response to selection

Phenotypic plasticity is the ability of a genotype to produce more than one phenotype in order to match the environment. Recent theory proposes that the major axis of genetic variation in a phenotypically plastic population can align with the direction of selection. Therefore, theory predicts that plasticity directly aids adaptation by increasing genetic variation in the direction favoured by selection and reflected in plasticity. We evaluated this theory in the freshwater crustacean Daphnia pulex, facing predation risk from two contrasting size-selective predators. We estimated plasticity in several life-history traits, the G matrix of these traits, the selection gradients on reproduction and survival, and the predicted responses to selection. Using these data, we tested whether the genetic lines of least resistance and the predicted response to selection aligned with plasticity. We found predator environment-specific G matrices, but shared genetic architecture across environments resulted in more constraint in the G matrix than in the plasticity of the traits, sometimes preventing alignment of the two. However, as the importance of survival selection increased, the difference between environments in their predicted response to selection increased and resulted in closer alignment between the plasticity and the predicted selection response. Therefore, plasticity may indeed aid adaptation to new environments.

Adaptive divergence in embryonic thermal plasticity among Atlantic salmon populations

In the context of global changes, the long-term viability of populations of endangered ectotherms may depend on their adaptive potential and ability to cope with temperature variations. We measured responses of Atlantic salmon embryos from four populations to temperature variations and used a QST -FST approach to study the adaptive divergence among these populations. Embryos were reared under two experimental conditions: a low temperature regime at 4 °C until eyed-stage and 10 °C until the end of embryonic development and a high temperature regime with a constant temperature of 10 °C throughout embryonic development. Significant variations among populations and population × temperature interactions were observed for embryo survival, incubation time and length. QST was higher than FST in all but one comparison suggesting an important effect of divergent selection. QST was also higher under the high-temperature treatment than at low temperature for length and survival due to a higher variance among populations under the stressful warmer treatment. Interestingly, heritability was lower for survival under high temperature in relation to a lower additive genetic variance under that treatment. Overall, these results reveal an adaptive divergence in thermal plasticity in embryonic life stages of Atlantic salmon suggesting that salmon populations may differentially respond to temperature variations induced by climate change. These results also suggest that changes in temperature may alter not only the adaptive potential of natural populations but also the selection regimes among them.

Effect of diet on the structure of animal personality

There is increasing interest in the proximate factors that underpin individual variation in suites of correlated behaviours. In this paper, we propose that dietary macronutrient composition, an underexplored environmental factor, might play a key role. Variation in macronutrient composition can lead to among-individual differentiation in single behaviours (‘personality’ ) as well as among-individual covariation between behaviours (‘behavioural syndromes’ ). Here, we argue that the nutritional balance during any life stage might affect the development of syndrome structure and the expression of genes with pleiotropic effects that influence development of multiple behaviours, hence genetic syndrome structure. We further suggest that males and females should typically differ in diet-dependent genetic syndrome structure despite a shared genetic basis. We detail how such diet-dependent multivariate gene-environment interactions can have major repercussions for the evolution of behavioural syndromes.

Molecular and quantitative genetic differentiation in Sitobion avenae populations from both sides of the Qinling Mountains

Quantitative trait differences are often assumed to be correlated with molecular variation, but the relationship is not certain, and empirical evidence is still scarce. To address this issue, we sampled six populations of the cereal aphid Sitobion avenae from areas north and south of the Qinling Mountains, and characterized their molecular variation at seven microsatellite loci and quantitative variation at nine life-history traits. Our results demonstrated that southern populations had slightly longer developmental times of nymphs but much higher lifetime fecundity, compared to northern populations. Of the nine tested quantitative characters, eight differed significantly among populations within regions, as well as between northern and southern regions. Genetic differentiation in neutral markers was likely to have been caused by founder events and drift. Increased subdivision for quantitative characters was found in northern populations, but reduced in southern populations. This phenomenon was not found for molecular characters, suggesting the decoupling between molecular and quantitative variation. The pattern of relationships between FST and QST indicated divergent selection and suggested that local adaptation play a role in the differentiation of life-history traits in tested S. avenae populations, particularly in those traits closely related to reproduction. The main role of natural selection over genetic drift was also supported by strong structural differences in G-matrices among S. avenae populations. However, cluster analyses did not result in two groups corresponding to northern and southern regions. Genetic differentiation between northern and southern populations in neutral markers was low, indicating considerable gene flow between them. The relationship between molecular and quantitative variation, as well as its implications for differentiation and evolution of S. avenae populations, was discussed.

Rapid evolutionary responses of life history traits to different experimentally-induced pollutions in Caenorhabditis elegans

BACKGROUND

Anthropogenic disturbances can lead to intense selection pressures on traits and very rapid evolutionary changes. Evolutionary responses to environmental changes, in turn, reflect changes in the genetic structure of the traits, accompanied by a reduction of evolutionary potential of the populations under selection. Assessing the effects of pollutants on the evolutionary responses and on the genetic structure of populations is thus important to understanding the mechanisms that entail specialization to novel environmental conditions or resistance to novel stressors.

RESULTS

Using an experimental evolution approach we exposed Caenorhabditis elegans populations to uranium, salt and alternating uranium-salt environments over 22 generations. We analyzed the changes in the average values of life history traits and the consequences at the demographic level in these populations. We also estimated the phenotypic and genetic (co)variance structure of these traits at different generations. Compared to populations in salt, populations in uranium showed a reduction of the stability of their trait structure and a higher capacity to respond by acclimation. However, the evolutionary responses of traits were generally lower for uranium compared to salt treatment; and the evolutionary responses to the alternating uranium-salt environment were between those of constant environments. Consequently, at the end of the experiment, the population rate of increase was higher in uranium than in salt and intermediate in the alternating environment.

CONCLUSIONS

Our multigenerational experiment confirmed that rapid adaptation to different polluted environments may involve different evolutionary responses resulting in demographic consequences. These changes are partly explained by the effects of the pollutants on the genetic (co)variance structure of traits and the capacity of acclimation to novel conditions. Finally, our results in the alternating environment may confirm the selection of a generalist type in this environment.

Multivariate adaptation but no increase in competitive ability in invasive Geranium carolinianum L. (Geraniaceae)

Adaptive evolution can affect the successful establishment of invasive species, but changes in selective pressures, loss of genetic variation in relevant traits, and/or altered trait correlations can make adaptation difficult to predict. We used a common-garden experiment to assess trait correlations and patterns of adaptation in the invasive plant, Geranium carolinianum, sampled across 20 populations in its native (United States) and invasive (China) ranges. We used multivariate QST - FST tests to determine if phenotypic differences between countries are attributable to adaptation. We also compared population-level variation within each country to assess whether local adaptation resulted in similar multivariate phenotypes in the United States and China. Between countries, most phenotypic differences are indistinguishable from genetic drift, although we detected a signature of adaptation to the colder, drier winters in China. There was no evidence for increases in invasive traits in China. Within countries, strong multivariate adaptation appears to be driven by latitudinal climatic variation in the United States, but not in China. Additionally, adaptive trait combinations as well as their underlying correlations differ between the two countries, indicating that adaptation in invasive populations does not parallel patterns in native populations due to differences in selection pressures, genetic constraints, or both.

Rapid and unpredictable changes of the G-matrix in a natural bird population over 25 years

Knowledge of the genetic variances and covariances of traits (the G-matrix) is fundamental for the understanding of evolutionary dynamics of populations. Despite its essential importance in evolutionary studies, empirical tests of the temporal stability of the G-matrix in natural populations are few. We used a 25-year-long individual-based field study on almost 7000 breeding attempts of the collared flycatcher (Ficedula albicollis) to estimate the stability of the G-matrix over time. Using animal models to estimate G for several time periods, we show that the structure of the time-specific G-matrices changed significantly over time. The temporal changes in the G-matrix were unpredictable, and the structure at one time period was not indicative of the structure at the next time period. Moreover, we show that the changes in the time-specific G-matrices were not related to changes in mean trait values or due to genetic drift. Selection, differences in acquisition/allocation patterns or environment-dependent allelic effects are therefore likely explanations for the patterns observed, probably in combination. Our result cautions against assuming constancy of the G-matrix and indicates that even short-term evolutionary predictions in natural populations can be very challenging.

Trade-offs, geography, and limits to thermal adaptation in a tide pool copepod

Antagonistic correlations among traits may slow the rate of adaptation to a changing environment. The tide pool copepod Tigriopus californicus is locally adapted to temperature, but within populations, the response to selection for increased heat tolerance plateaus rapidly, suggesting either limited variation within populations or costs of increased tolerance. To measure possible costs of thermal tolerance, we selected for increased upper lethal limits for 10 generations in 22 lines of T. californicus from six populations. Then, for each line, we measured six fitness-related traits. Selected lines showed an overall increase in male and female body sizes, fecundity, and starvation resistance, suggesting a small benefit from (rather than costs of) increased tolerance. The effect of selection on correlated traits also varied significantly by population for five traits, indicating that the genetic basis for the selection response differed among populations. Our results suggest that adaptation was limited by the presence of variation within isolated populations rather than by costs of increased tolerance.

Comparing G: multivariate analysis of genetic variation in multiple populations

The additive genetic variance-covariance matrix (G) summarizes the multivariate genetic relationships among a set of traits. The geometry of G describes the distribution of multivariate genetic variance, and generates genetic constraints that bias the direction of evolution. Determining if and how the multivariate genetic variance evolves has been limited by a number of analytical challenges in comparing G-matrices. Current methods for the comparison of G typically share several drawbacks: metrics that lack a direct relationship to evolutionary theory, the inability to be applied in conjunction with complex experimental designs, difficulties with determining statistical confidence in inferred differences and an inherently pair-wise focus. Here, we present a cohesive and general analytical framework for the comparative analysis of G that addresses these issues, and that incorporates and extends current methods with a strong geometrical basis. We describe the application of random skewers, common subspace analysis, the 4th-order genetic covariance tensor and the decomposition of the multivariate breeders equation, all within a Bayesian framework. We illustrate these methods using data from an artificial selection experiment on eight traits in Drosophila serrata, where a multi-generational pedigree was available to estimate G in each of six populations. One method, the tensor, elegantly captures all of the variation in genetic variance among populations, and allows the identification of the trait combinations that differ most in genetic variance. The tensor approach is likely to be the most generally applicable method to the comparison of G-matrices from any sampling or experimental design.

Strain specific genotype-environment interactions and evolutionary potential for body mass in brook charr (Salvelinus fontinalis)

Discriminating between genetic and environmental causes of phenotypic variation is an essential requirement for understanding the evolutionary potential of populations. However, the extent to which genetic variation differs among conspecific groups and environments during ontogeny has rarely been investigated. In this study, the genetic basis of body mass was measured in three divergent strains of brook charr (Salvelinus fontinalis) in different rearing environments and at different time periods. The results indicate that body mass was a heritable trait in all strains but that the level of heritability greatly differed among strains. Moreover, heritability estimates of each strain varied differently according to environmental rearing conditions, and cross-environments correlations were all significantly lower than unity, indicating strain-specific patterns of genotype-environment interactions. Heritability estimates also varied throughout ontogeny and decreased by 50% from 9 to 21 months of age. This study highlights the divergence in genetic architecture and evolutionary potential among these strains and emphasizes the importance of considering the strain-specific potential of the response to selection according to environmental variation.

Quantifying multivariate plasticity: genetic variation in resource acquisition drives plasticity in resource allocation to components of life history

Acquisition and allocation of resources are central to life-history theory. However, empirical work typically focuses only on allocation despite the fact that relationships between fitness components may be governed by differences in the ability of individuals to acquire resources across environments. Here, we outline a statistical framework to partition the genetic basis of multivariate plasticity into independent axes of genetic variation, and quantify for the first time, the extent to which specific traits drive multitrait genotype-environment interactions. Our framework generalises to analyses of plasticity, growth and ageing. We apply this approach to a unique, large-scale, multivariate study of acquisition, allocation and plasticity in the life history of the cricket, Gryllus firmus. We demonstrate that resource acquisition and allocation are genetically correlated, and that plasticity in trade-offs between allocation to components of fitness is 90% dependent on genetic variance for total resource acquisition. These results suggest that genotype-environment effects for resource acquisition can maintain variation in life-history components that are typically observed in the wild.

Q(ST) < F(ST) As a signature of canalization

A key aim of evolutionary biology - inferring the action of natural selection on wild species - can be achieved by comparing neutral genetic differentiation between populations (F(ST)) with quantitative genetic variation (Q(ST)). Each of the three possible outcomes of comparisons of Q(ST) and F(ST) (Q(ST) > F(ST), Q(ST) = F(ST), Q(ST) < F(ST)) is associated with an inference (diversifying selection, genetic drift, uniform selection, respectively). However, published empirical and theoretical studies have focused on the Q(ST) > F(ST) outcome. We believe that this reflects the absence of a straightforward biological interpretation of the Q(ST) < F(ST) pattern. We here report recent evidence of this neglected evolutionary pattern, provide guidelines to its interpretation as either a canalization phenomenon or a consequence of uniform selection and discuss the significant importance this issue will have for the area of evolutionary biology.

Population differences in response to hypoxic stress in Atlantic salmon

Understanding whether populations can adapt to new environmental conditions is a major issue in conservation and evolutionary biology. Aquatic organisms are increasingly exposed to environmental changes linked with human activities in river catchments. For instance, the clogging of bottom substratum by fine sediments is observed in many rivers and usually leads to a decrease in dissolved oxygen concentrations in gravel beds. Such hypoxic stress can alter the development and even be lethal for Atlantic salmon (Salmo salar) embryos that spend their early life into gravel beds. In this study, we used a common garden experiment to compare the responses to hypoxic stress of four genetically differentiated and environmentally contrasted populations. We used factorial crossing designs to measure additive genetic variation of early life-history traits in each population. Embryos were reared under normoxic and hypoxic conditions, and we measured their survival, incubation time and length at the end of embryonic development. Under hypoxic conditions, embryos had a lower survival and hatched later than in normoxic conditions. We found different hypoxia reaction norms among populations, but almost no population effect in both treatments. We also detected significant sire × treatment interactions in most populations and a tendency for heritability values to be lower under stressful conditions. Overall, these results reveal a high degree of phenotypic plasticity in salmon populations that nevertheless differ in their adaptive potential to hypoxia given the distinct reaction norms observed between and within populations.

Adaptive divergence of the moor frog (Rana arvalis) along an acidification gradient

Background

Environmental stress can result in strong ecological and evolutionary effects on natural populations, but to what extent it drives adaptive divergence of natural populations is little explored. We used common garden experiments to study adaptive divergence in embryonic and larval fitness traits (embryonic survival, larval growth, and age and size at metamorphosis) in eight moor frog, Rana arvalis, populations inhabiting an acidification gradient (breeding pond pH 4.0 to 7.5) in southwestern Sweden. Embryos were raised until hatching at three (pH 4.0, 4.3 and 7.5) and larvae until metamorphosis at two (pH 4.3 and 7.5) pH treatments. To get insight into the putative selective agents along this environmental gradient, we measured relevant abiotic and biotic environmental variables from each breeding pond, and used linear models to test for phenotype-environment correlations.

Results

We found that acid origin populations had higher embryonic and larval acid tolerance (survival and larval period were less negatively affected by low pH), higher larval growth but slower larval development rates, and metamorphosed at a larger size. The phenotype-environment correlations revealed that divergence in embryonic acid tolerance and metamorphic size correlated most strongly with breeding pond pH, whereas divergence in larval period and larval growth correlated most strongly with latitude and predator density, respectively.

Conclusion

Our results suggest that R. arvalis has diverged in response to pH mediated selection along this acidification gradient. However, as latitude and pH were closely spatially correlated in this study, further studies are needed to disentangle the specific agents of natural selection along acidification gradients. Our study highlights the need to consider the multiple interacting selective forces that drive adaptive divergence of natural populations along environmental stress gradients.

Quantitative genetics of body size and timing of maturation in two nine-spined stickleback (Pungitius pungitius) populations

Due to its influence on body size, timing of maturation is an important life-history trait in ectotherms with indeterminate growth. Comparison of patterns of growth and maturation within and between two populations (giant vs. normal sized) of nine-spined sticklebacks (Pungitius pungitius) in a breeding experiment revealed that the difference in mean adult body size between the populations is caused by differences in timing of maturation, and not by differential growth rates. The fish in small-sized population matured earlier than those from large-sized population, and maturation was accompanied by a reduction in growth rate in the small-sized population. Males matured earlier and at smaller size than females, and the fish that were immature at the end of the experiment were larger than those that had already matured. Throughout the experimental period, body size in both populations was heritable (h² = 0.10–0.64), as was the timing of maturation in the small-sized population (h² = 0.13–0.16). There was a significant positive genetic correlation between body size and timing of maturation at 140 DAH, but not earlier (at 80 or 110 DAH). Comparison of observed body size divergence between the populations revealed that Q_ST exceeded F_ST at older ages, indicating adaptive basis for the observed divergence. Hence, the results suggest that the body size differences within and between populations reflect heritable genetic differences in the timing of maturation, and that the observed body size divergence is adaptive.

A new method to uncover signatures of divergent and stabilizing selection in quantitative traits

While it is well understood that the pace of evolution depends on the interplay between natural selection, random genetic drift, mutation, and gene flow, it is not always easy to disentangle the relative roles of these factors with data from natural populations. One popular approach to infer whether the observed degree of population differentiation has been influenced by local adaptation is the comparison of neutral marker gene differentiation (as reflected in FST) and quantitative trait divergence (as reflected in QST). However, this method may lead to compromised statistical power, because FST and QST are summary statistics which neglect information on specific pairs of populations, and because current multivariate tests of neutrality involve an averaging procedure over the traits. Further, most FST-QST comparisons actually replace QST by its expectation over the evolutionary process and are thus theoretically flawed. To overcome these caveats, we derived the statistical distribution of population means generated by random genetic drift and used the probability density of this distribution to test whether the observed pattern could be generated by drift alone. We show that our method can differentiate between genetic drift and selection as a cause of population differentiation even in cases with FST=QST and demonstrate with simulated data that it disentangles drift from selection more accurately than conventional FST-QST tests especially when data sets are small.

First-generation linkage map for the common frog Rana temporaria reveals sex-linkage group

The common frog (Rana temporaria) has become a model species in the fields of ecology and evolutionary biology. However, lack of genomic resources has been limiting utility of this species for detailed evolutionary genetic studies. Using a set of 107 informative microsatellite markers genotyped in a large full-sib family (800 F1 offspring), we created the first linkage map for this species. This partial map-distributed over 15 linkage groups-has a total length of 1698.8 cM. In line with the fact that males are the heterogametic sex in this species and a reduction of recombination is expected, we observed a lower recombination rate in the males (map length: 1371.5 cM) as compared with females (2089.8 cM). Furthermore, three loci previously documented to be sex-linked (that is, carrying male-specific alleles) in adults from the wild mapped to the same linkage group. The linkage map described in this study is one of the densest ones available for amphibians. The discovery of a sex linkage group in Rana temporaria, as well as other regions with strongly reduced male recombination rates, should help to uncover the genetic underpinnings of the sex-determination system in this species. As the number of linkage groups found (n=15) is quite close to the actual number of chromosomes (n=13), the map should provide a useful resource for further evolutionary, ecological and conservation genetic work in this and other closely related species.

Adaptive divergence for a fitness-related trait among invasive Ambrosia artemisiifolia populations in France

The impact of natural selection on the adaptive divergence of invasive populations can be assessed by testing the null hypothesis that the extent of quantitative genetic differentiation (Q(ST) ) would be similar to that of neutral molecular differentiation (F(ST) ). Using eight microsatellite loci and a common garden approach, we compared Q(ST) and F(ST) among ten populations of an invasive species Ambrosia artemisiifolia (common ragweed) in France. In a common garden study with varying water and nutrient levels, we measured Q(ST) for five traits (height, total biomass, reproductive allocation, above- to belowground biomass ratio, and days to flowering). Although low F(ST) indicated weak genetic structure and strong gene flow among populations, we found significant diversifying selection (Q(ST) > F(ST) ) for reproductive allocation that may be closely related to fitness. It suggests that abiotic conditions may have exerted selection pressure on A. artemisiifolia populations to differentiate adaptively, such that populations at higher altitude or latitude evolved greater reproductive allocation. As previous studies indicate multiple introductions from various source populations of A. artemisiifolia in North America, our results suggest that the admixture of introduced populations may have increased genetic diversity and additive genetic variance, and in turn, promoted the rapid evolution and adaptation of this invasive species.

Elucidating the role of genetic drift and natural selection in cork oak differentiation regarding drought tolerance

Drought is the main selection agent in Mediterranean ecosystems and it has been suggested as an important evolutionary force responsible for population diversification in these types of environments. However, population divergence in quantitative traits can be driven by either natural selection, genetic drift or both. To investigate the roles of these forces on among-population divergence in ecophysiological traits related to drought tolerance (carbon isotope discrimination, specific leaf area, leaf size and leaf nitrogen content), we compared molecular and quantitative genetic differentiation in a common garden experiment including thirteen cork oak (Quercus suber L.) populations across a gradient of rainfall and temperature. Population differentiation for height, specific leaf area, leaf size and nitrogen leaf content measured during a dry year far exceeded the molecular differentiation measured by six nuclear microsatellites. Populations from dry-cool sites showed the lowest nitrogen leaf content and the smallest and thickest leaves contrasting with those from humid-warm sites. These results suggest (i) these traits are subjected to divergence selection and (ii) the genetic differences among populations are partly due to climate adaptation. By contrast, the low among-population divergence found in basal diameter, annual growth and carbon isotopic discrimination (a surrogate for water use efficiency) suggests low or no divergence selection for these traits. Among-population differentiation for neutral markers was not a good predictor for differentiation regarding the quantitative traits studied here, except for leaf size. The correlation observed between the genetic differentiation for leaf size and that for molecular markers was exclusively due to the association between leaf size and the microsatellite QpZAG46, which suggests a possible linkage between QpZAG46 and genes encoding for leaf size.

Empirical comparison of G matrix test statistics: finding biologically relevant change

A central assumption of quantitative genetic theory is that the breeder's equation (R=GP(-1)S) accurately predicts the evolutionary response to selection. Recent studies highlight the fact that the additive genetic variance-covariance matrix (G) may change over time, rendering the breeder's equation incapable of predicting evolutionary change over more than a few generations. Although some consensus on whether G changes over time has been reached, multiple, often-incompatible methods for comparing G matrices are currently used. A major challenge of G matrix comparison is determining the biological relevance of observed change. Here, we develop a "selection skewers"G matrix comparison statistic that uses the breeder's equation to compare the response to selection given two G matrices while holding selection intensity constant. We present a bootstrap algorithm that determines the significance of G matrix differences using the selection skewers method, random skewers, Mantel's and Bartlett's tests, and eigenanalysis. We then compare these methods by applying the bootstrap to a dataset of laboratory populations of Tribolium castaneum. We find that the results of matrix comparison statistics are inconsistent based on differing a priori goals of each test, and that the selection skewers method is useful for identifying biologically relevant G matrix differences.

The impact of environmental heterogeneity on genetic architecture in a wild population of Soay sheep

This work demonstrates that environmental conditions experienced by individuals can shape their development and affect the stability of genetic associations. The implication of this observation is that the environmental response may influence the evolution of traits in the wild. Here, we examined how the genetic architecture of a suite of sexually dimorphic traits changed as a function of environmental conditions in an unmanaged population of Soay sheep (Ovis aries) on the island of Hirta, St. Kilda, northwest Scotland. We examined the stability of phenotypic, genetic, and environmental (residual) covariance in males during the first year of life between horn length, body weight, and parasite load in environments of different quality. We then examined the same covariance structures across environments within and between the adult sexes. We found significant genotype-by-environment interactions for lamb male body weight and parasite load, leading to a change in the genetic correlation among environments. Horn length was genetically correlated with body weight in males but not females and the genetic correlation among traits within and between the sexes was dependent upon the environmental conditions experienced during adulthood. Genetic correlations were smaller in more favorable environmental conditions, suggesting that in good environments, loci are expressed that have sex-specific effects. The reduction in genetic correlation between the sexes may allow independent evolutionary trajectories for each sex. This study demonstrates that the genetic architecture of traits is not stable under temporally varying environments and highlights the fact that evolutionary processes may depend largely upon ecological conditions.

Understanding the evolution and stability of the G-matrix

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations.

A Bayesian framework for comparative quantitative genetics

Bayesian approaches have been extensively used in animal breeding sciences, but similar approaches in the context of evolutionary quantitative genetics have been rare. We compared the performance of Bayesian and frequentist approaches in estimation of quantitative genetic parameters (viz. matrices of additive and dominance variances) in datasets typical of evolutionary studies and traits differing in their genetic architecture. Our results illustrate that it is difficult to disentangle the relative roles of different genetic components from small datasets, and that ignoring, e.g. dominance is likely to lead to biased estimates of additive variance. We suggest that a natural summary statistic for G-matrix comparisons can be obtained by examining how different the underlying multinormal probability distributions are, and illustrate our approach with data on the common frog (Rana temporaria). Furthermore, we derive a simple Monte Carlo method for computation of fraternity coefficients needed for the estimation of dominance variance, and use the pedigree of a natural Siberian jay (Perisoreus infaustus) population to illustrate that the commonly used approximate values can be substantially biased.

Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.