Genetic analysis of life-history constraint and evolution in a wild ungulate population

Trade-offs among life-history traits are central to evolutionary theory. In quantitative genetic terms, trade-offs may be manifested as negative genetic covariances relative to the direction of selection on phenotypic traits. Although the expression and selection of ecologically important phenotypic variation are fundamentally multivariate phenomena, the in situ quantification of genetic covariances is challenging. Even for life-history traits, where well-developed theory exists with which to relate phenotypic variation to fitness variation, little evidence exists from in situ studies that negative genetic covariances are an important aspect of the genetic architecture of life-history traits. In fact, the majority of reported estimates of genetic covariances among life-history traits are positive. Here we apply theory of the genetics and selection of life histories in organisms with complex life cycles to provide a framework for quantifying the contribution of multivariate genetically based relationships among traits to evolutionary constraint. We use a Bayesian framework to link pedigree-based inference of the genetic basis of variation in life-history traits to evolutionary demography theory regarding how life histories are selected. Our results suggest that genetic covariances may be acting to constrain the evolution of female life-history traits in a wild population of red deer Cervus elaphus: genetic covariances are estimated to reduce the rate of adaptation by about 40%, relative to predicted evolutionary change in the absence of genetic covariances. Furthermore, multivariate phenotypic (rather than genetic) relationships among female life-history traits do not reveal this constraint.     

Natural selection, evolvability and bias due to environmental covariance in the field in an annual plant

Estimates of the form and magnitude of natural selection based on phenotypic relationships between traits and fitness measures can be biased when environmental factors influence both relative fitness and phenotypic trait values. I quantified genetic variances and covariances, and estimated linear and quadratic selection coefficients, for seven traits of an annual plant grown in the field. For replicates of 50 paternal half-sib families, coefficients of selection were calculated both for individual phenotypic values of the traits and for half-sib family mean values. The potential for evolutionary response was supported by significant heritability and phenotypic directional selection for several traits but contradicted by the absence of significant genetic variation for fitness estimates and evidence of bias in phenotypic selection coefficients due to environmental covariance for at least two of the traits analysed. Only studies of a much wider range of organisms and traits will reveal the frequency and extent of such bias.     

Partitioning of resources: the evolutionary genetics of sexual conflict over resource acquisition and allocation

Fitness depends on both the resources that individuals acquire and the allocation of those resources to traits that influence survival and reproduction. Optimal resource allocation differs between females and males as a consequence of their fundamentally different reproductive strategies. However, because most traits have a common genetic basis between the sexes, conflicting selection between the sexes over resource allocation can constrain the evolution of optimal allocation within each sex, and generate trade‐offs for fitness between them (i.e. ‘sexual antagonism’ or ‘intralocus sexual conflict’). The theory of resource acquisition and allocation provides an influential framework for linking genetic variation in acquisition and allocation to empirical evidence of trade‐offs between distinct life‐history traits. However, these models have not considered the emergence of trade‐offs within the context of sexual dimorphism, where they are expected to be particularly common. Here, we extend acquisition–allocation theory and develop a quantitative genetic framework for predicting genetically based trade‐offs between life‐history traits within sexes and between female and male fitness. Our models demonstrate that empirically measurable evidence of sexually antagonistic fitness variation should depend upon three interacting factors that may vary between populations: (1) the genetic variances and between‐sex covariances for resource acquisition and allocation traits, (2) condition‐dependent expression of resource allocation traits and (3) sex differences in selection on the allocation of resource to different fitness components.     

An evolutionary quantitative genetics model for phenotypic (co)variances under limited dispersal,with an application to socially synergistic traits

Darwinian evolution consists of the gradual transformation of heritable traits due to natural selection and the input of random variation by mutation. Here, we use a quantitative genetics approach to investigate the coevolution of multiple quantitative traits under selection, mutation, and limited dispersal. We track the dynamics of trait means and of variance–covariances between traits that experience frequency‐dependent selection. Assuming a multivariate‐normal trait distribution, we recover classical dynamics of quantitative genetics, as well as stability and evolutionary branching conditions of invasion analyses, except that due to limited dispersal, selection depends on indirect fitness effects and relatedness. In particular, correlational selection that associates different traits within‐individuals depends on the fitness effects of such associations between‐individuals. We find that these kin selection effects can be as relevant as pleiotropy for the evolution of correlation between traits. We illustrate this with an example of the coevolution of two social traits whose association within‐individuals is costly but synergistically beneficial between‐individuals. As dispersal becomes limited and relatedness increases, associations between‐traits between‐individuals become increasingly targeted by correlational selection. Consequently, the trait distribution goes from being bimodal with a negative correlation under panmixia to unimodal with a positive correlation under limited dispersal.     

Predicting evolutionary responses to selection on polyandry in the wild: additive genetic covariances with female extra-pair reproduction

The evolutionary forces that underlie polyandry, including extra-pair reproduction (EPR) by socially monogamous females, remain unclear. Selection on EPR and resulting evolution have rarely been explicitly estimated or predicted in wild populations, and evolutionary predictions are vulnerable to bias due to environmental covariances and correlated selection through unmeasured traits. However, evolutionary responses to (correlated) selection on any trait can be directly predicted as additive genetic covariances (cov_A) with appropriate components of relative fitness. I used comprehensive life-history, paternity and pedigree data from song sparrows (Melospiza melodia) to estimate cov_A between a female''s liability to produce extra-pair offspring and two specific fitness components: relative annual reproductive success (ARS) and survival to recruitment. All three traits showed non-zero additive genetic variance. Estimates of cov_A were positive, predicting evolution towards increased EPR, but 95% credible intervals overlapped zero. There was therefore no conclusive prediction of evolutionary change in EPR due to (correlated) selection through female ARS or recruitment. Negative environmental covariance between EPR and ARS would have impeded evolutionary prediction from phenotypic selection differentials. These analyses demonstrate an explicit quantitative genetic approach to predicting evolutionary responses to components of (correlated) selection on EPR that should be unbiased by environmental covariances and unmeasured traits.     

THE MEASUREMENT OF SELECTION ON QUANTITATIVE TRAITS: BIASES DUE TO ENVIRONMENTAL COVARIANCES BETWEEN TRAITS AND FITNESS

The use of regression techniques for estimating the direction and magnitude of selection from measurements on phenotypes has become widespread in field studies. A potential problem with these techniques is that environmental correlations between fitness and the traits examined may produce biased estimates of selection gradients. This report demonstrates that the phenotypic covariance between fitness and a trait, used as an estimate of the selection differential in estimating selection gradients, has two components: a component induced by selection itself and a component due to the effect of environmental factors on fitness. The second component is shown to be responsible for biases in estimates of selection gradients. The use of regressions involving genotypic and breeding values instead of phenotypic values can yield estimates of selection gradients that are not biased by environmental covariances. Statistical methods for estimating the coefficients of such regressions, and for testing for biases in regressions involving phenotypic values, are described.     

THE COADAPTATION OF PARENTAL AND OFFSPRING CHARACTERS

Parents often have important influences on their offspring's traits and/or fitness (i.e., maternal or paternal effects). When offspring fitness is determined by the joint influences of offspring and parental traits, selection may favor particular combinations that generate high offspring fitness. We show that this epistasis for fitness between the parental and offspring genotypes can result in the evolution of their joint distribution, generating genetic correlations between the parental and offspring characters. This phenomenon can be viewed as a coadaptive process in which offspring genotypes evolve to function with the parentally provided environment and, in turn, the genes for this environment become associated with specific offspring genes adapted to it. To illustrate this point, we present two scenarios in which selection on offspring alone alters the correlation between a maternal and an offspring character. We use a quantitative genetic maternal effect model combined with a simple quadratic model of fitness to examine changes in the linkage disequilibrium between the maternal and offspring genotypes. In the first scenario, stabilizing selection on a maternally affected offspring character results in a genetic correlation that is opposite in sign to the maternal effect. In the second scenario, directional selection on an offspring trait that shows a nonadditive maternal effect can result in selection for positive covariances between the traits. This form of selection also results in increased genetic variation in maternal and offspring characters, and may, in the extreme case, promote host-race formation or speciation. This model provides a possible evolutionary explanation for the ubiquity of large genetic correlations between maternal and offspring traits, and suggests that this pattern of coinheritance may reflect functional relationships between these characters (i.e., functional integration).     

THE DETERMINATION OF GENETIC COVARIANCES AND PREDICTION OF EVOLUTIONARY TRAJECTORIES BASED ON A GENETIC CORRELATION MATRIX

There is much interest in measuring selection, quantifying evolutionary constraints, and predicting evolutionary trajectories in natural populations. For these studies, genetic (co)variances among fitness traits play a central role. We explore the conditions that determine the sign of genetic covariances and demonstrate a critical role of selection in shaping genetic covariances. In addition, we show that genetic covariance matrices rather than genetic correlation matrices should be characterized and studied in order to infer genetic basis of population differentiation and/or to predict evolutionary trajectories.     

Contribution of photosynthetic rate to growth and reproduction in Amaranthus hybridus

While it is known that genetic variation for photosynthetic and growth traits exists in natural populations, the functional significance of this variation remains unclear, particularly for photosynthetic traits. To test the hypothesis that photosynthetic rate has direct effects on reproduction as well as contributing indirectly to reproduction through effects on growth, we compared wild-type Amaranthus hybridus families to those with a single gene mutation that confers a lower photosynthetic rate. Wild-type and photosynthetic-mutant families were grown in competitive and non-competitive environments and we compared size, biomass allocation, architecture, and reproduction at three developmental stages. To assess the contributions of individual growth traits to reproduction, we calculated covariances between standardized traits and relative fitness (selection differentials), and compared selection between the two biotypes. Finally, we used path analysis to calculate the indirect effects of photosynthetic rate on fitness through growth. The size, allocation, and architecture of photosynthetic mutants did not differ from those of the wild type in either the competitive or non-competitive environment, with the exception that they were taller by the last developmental stage. However, the reproductive biomass of the photosynthetic mutants was significantly reduced compared to the wild type. In the competitive environment, the wild type achieved greater fitness because, while similar in size to the mutants, at any given size it produced more reproductive biomass. This suggests that photosynthetic rate affected the linkage between plant size and reproduction and is evidence of an indirect contribution to fitness. In the non-competitive environment, there were fewer differences in selection differentials between the two plant genotypes, suggesting fewer indirect effects. Path analysis showed that variation in photosynthetic biotype had indirect effects on reproductive biomass, via growth traits, and that there were no direct effects. Photosynthetic rate appears to have fitness consequences primarily through multiple contributions to growth throughout development. Received: 27 March 1998 / Accepted: 28 August 1998     

Testing for environmentally induced bias in phenotypic estimates of natural selection: theory and practice

Measuring natural selection has been a fundamental goal of evolutionary biology for more than a century, and techniques developed in the last 20 yr have provided relatively simple means for biologists to do so. Many of these techniques, however, share a common limitation: when applied to phenotypic data, environmentally induced covariances between traits and fitness can lead to biased estimates of selection and misleading predictions about evolutionary change. Utilizing estimates of breeding values instead of phenotypic data with these methods can eliminate environmentally induced bias, although this approach is more difficult to implement. Despite this potential limitation to phenotypic methods and the availability of a potential solution, little empirical evidence exists on the extent of environmentally induced bias in phenotypic estimates of selection. In this article, we present a method for detecting bias in phenotypic estimates of selection and demonstrate its use with three independent data sets. Nearly 25% of the phenotypic selection gradients estimated from our data are biased by environmental covariances. We find that bias caused by environmental covariances appears mainly to affect quantitative estimates of the strength of selection based on phenotypic data and that the magnitude of these biases is large. As our estimates of selection are based on data from spatially replicated field experiments, we suggest that our findings on the prevalence of bias caused by environmental covariances are likely to be conservative.     

Mutation accumulation, performance, fitness

The morphology-performance-fitness paradigm is usually exploredby determining whether natural or "phenotypically engineered"variation among individuals in morphology (physiology) or performancecovaries with an index of fitness such as survival. Here westudy between-line covariation between performance and fitnessfor 44 lines of flies that had undergone mutation accumulation(in the absence of natural selection) on the second chromosomefor 62 generations, plus 13 control lines. These mutation accumulation(MA) lines were known to have reduced competitive fitness andlife history scores, and to have positive between-line covariancesamong life history traits. We measured several performance traitsof larvae and adults (and a life history trait), examined covariancesamong those trait means, and also examined covariances of traitswith competitive fitness. MA lines had significantly lower performancesthan did control lines in most traits. However, because controllines had been unknowingly contaminated, a conclusion that MAreduces performance must be tentative. Correlations among performancetraits were highly variable in sign, suggesting that MA doesnot negatively affect all traits equivalently. Even so, correlationmatrices for MA and for control lines were very similar. Inbivariate comparisons, only one performance trait (a "get-a-gripindex," which measures the ability of a falling fly to catchitself on baffles) was positively correlated with competitivefitness. Multivariate analyses again suggested the importanceprimarily of get-a-grip. Two main patterns emerge from thisstudy. First, MA negatively affects diverse aspects of physiologicalperformance, but does so differentially across traits. Second,except for GAG, MA-induced variation in performance is at bestweakly correlated with competitive fitness.     

Interpreting Geographic Variation in Life-History Traits

The geographic variation in the length of the larval periodand the size at metamorphosis of the wood frog,Rana sylvatica,is examined for populations in the tundra of Canada, the mountainsof Virginia, and the lowlands of Maryland. We argue that theobserved differences in developmental plasticity, heriisbilitiesand genetic covariances of traits among localities result fromdifferential selection pressures in each environment, and arerelated to the physiological constraints inherent in developmentand to the degree of compromise between the timing and sizeat metamorphosis allowed in each environment. In Maryland populationsfitness has been maximized by evolutionary changes in size alone;body size in this population is canalized, has low heritabilityand is highly correlated with juvenile survival relative todevelopmental time. In Canada, minimum developmental time yieldsmaximum fitness; the length of the larval period in this populationis canalized and genetically monomorphic relative to body size.In contrast, fitness in the Virginia populations has been determinedby correlated and pleiotropic effects of genes on both developmentaltime and larval body size, and both traits are equally canalized,affect juvenile survivorship equally and display moderate heritabilities.These results stress the importance of interpreting variationin life-history traits relative to constraints inherent in developmentand those imposed by the environment. Heritability and survivorshipdata support the general notion that fitness traits should havelow levels of additive genetic variation, but also suggest thatantagonistic pleiotropy may act to preserve genetic variationin fitness traits under simultaneous selection, and cautionagainst inferring evolutionary importance of individual traitswithout considering the possible presence of pleiotropy.     

Genetic variation and the potential response to selection on leaf traits after habitat degradation in a long-lived cycad

Rapid evolution may be common in human-dominated landscapes where environmental changes are severe. We used phenotypic selection analyses and a marker-based method to estimate genetic variances and covariances to predict the potential response to selection in populations of a long-lived cycad recently exposed to drastic environmental changes. Patterns of selection in adult fecundity showed that different traits were under directional selection in subpopulations from native-undisturbed habitats and the novel degraded-forest habitat. Plants from a native-habitat subpopulation tend to maximize fitness through larger leaf area or smaller specific leaf area (SLA). In contrast, larger leaf production increased fitness in a degraded-habitat subpopulation, and canopy openness appears to be a major agent of selection for this trait. Leaf production and SLA showed significant additive genetic variance and no genetic trade-offs with examined traits, suggesting that these traits can respond to selection. Directional selection coefficients and heritability values were large, therefore significant phenotypic changes between subpopulations in few generations are possible. These results suggest that recent environmental change can result in strong directional selection in subpopulations of this cycad, and that these subpopulations have the potential to diverge at the genetic level in leaf traits after anthropogenic habitat degradation.     

Protein deprivation facilitates the independent evolution of behavior and morphology

Ecological conditions such as nutrition can change genetic covariances between traits and accelerate or slow down trait evolution. As adaptive trait correlations can become maladaptive following rapid environmental change, poor or stressful environments are expected to weaken genetic covariances, thereby increasing the opportunity for independent evolution of traits. Here, we demonstrate the differences in genetic covariance among multiple behavioral and morphological traits (exploration, aggression, and body weight) between southern field crickets (Gryllus bimaculatus) raised in favorable (free‐choice) versus stressful (protein‐deprived) nutritional environments. We also quantify the extent to which differences in genetic covariance structures contribute to the potential for the independent evolution of these traits. We demonstrate that protein‐deprived environments tend to increase the potential for traits to evolve independently, which is caused by genetic covariances that are significantly weaker for crickets raised on protein‐deprived versus free‐choice diets. The weakening effects of stressful environments on genetic covariances tended to be stronger in males than in females. The weakening of the genetic covariance between traits under stressful nutritional environments was expected to facilitate the opportunity for adaptive evolution across generations. Therefore, the multivariate gene‐by‐environment interactions revealed here may facilitate behavioral and morphological adaptations to rapid environmental change.     

Variances and covariances of phenological traits in a wild mammal population

In a seasonal environment, there are multiple aspects of timing, or phenology, that contribute to an individual's fitness. Several studies have shown a genetic basis to variation between individuals in breeding time, but we know little about the heritability of other phenological traits in wild populations. Furthermore, the presence of genetic correlations between phenological variables could act to constrain or promote any response to selection, but less is known of the multivariate genetic relationships underlying phenological traits in the wild. Here, we use data from a wild population of red deer on the Isle of Rum, Scotland, to investigate covariances between eight phenological traits. Variation was characterized at the level of the phenotype, genotype, and year, and traits measured in different sexes enabled us to test for cross-sex genetic correlations. Phenotypic correlations were broadly strong and positive, as were correlations between traits expressed in the same year. We found evidence of significant additive genetic variation in five of the eight phenological traits studied. However there was little evidence of genetic correlations between traits, implying that much of the observed phenotypic correlation was environmentally induced. Our results suggest that different phenological traits may be free to move along independent evolutionary trajectories.     

A general model of the relation between phenotypic selection and genetic response

The phenotypic view of selection assumes that genetic responses can be predicted from selective forces and heritability — or in the classical quantitative genetic equation: R = h²S. However, data on selection in bird populations show that often no selection responses is found, despite consistent selective forces on phenotypes and significant heritable variation. Such discrepancies may arise due to the assumption that selection only acts on observed phenotypes. We derive a general selection equation that takes into account the possibility that some relevant (internal or external) traits are not measured. This equation shows that the classic equation applies if selection directly acts on the measured, phenotypic traits. This is not the case when, for instance, there are unknown internal genetic trade-offs, or unknown common environmental factors affecting both trait and fitness. In such cases, any relationship between phenotypic selection and genetic response is possible. Fortunately, the classical model can be tested by comparing phenotypic and genetic covariances between traits and fitness; an indication that important internal or external traits are missing can thus be obtained. Such an analysis was indeed found in the literature; for selection on fledging weight in Great Tits it yielded valuable extra information.     

A general model of functional constraints on phenotypic evolution

A general model of the functional constraints on the rate and direction of phenotypic evolution is developed using a decomposition of the Lande-Arnold model of multivariate phenotypic evolution. The important feature of the model is the F matrix of performance coefficients reflecting the causal relationship between morphophysiological (m-p) and functional performance traits. The structure of F, which reflects the functional architecture of the organism, constrains the shape of the adaptive landscape and thus the rate and direction of m-p trait evolution. The rate of m-p trait evolution is a function of the pattern of coefficients in a row of F. The sums and variances of these rows are related to current concepts of evolvability. The direction of m-p trait evolution through m-p trait space is a function of the functional covariances among m-p traits. The functional covariance between a pair of m-p traits is a measure of how much the traits function together and is computed as the covariance between rows of F. Finally, it is shown that genetic covariances between m-p traits and performance traits are a function of the F matrix, but a G matrix that includes these covariances cannot be used to model functional constraints effectively.     

Epistatic pleiotropy and the genetic architecture of covariation within early and late-developing skull trait complexes in mice

The role of epistasis as a source of trait variation is well established, but its role as a source of covariation among traits (i.e., as a source of "epistatic pleiotropy") is rarely considered. In this study we examine the relative importance of epistatic pleiotropy in producing covariation within early and late-developing skull trait complexes in a population of mice derived from an intercross of the Large and Small inbred strains. Significant epistasis was found for several pairwise combinations of the 21 quantitative trait loci (QTL) affecting early developing traits and among the 20 QTL affecting late-developing traits. The majority of the epistatic effects were restricted to single traits but epistatic pleiotropy still contributed significantly to covariances. Because of their proportionally larger effects on variances than on covariances, epistatic effects tended to reduce within-group correlations of traits and reduce their overall degree of integration. The expected contributions of single-locus and two-locus epistatic pleiotropic QTL effects to the genetic covariance between traits were analyzed using a two-locus population genetic model. The model demonstrates that, for single-locus or epistatic pleiotropy to contribute to trait covariances in the study population, both traits must show the same pattern of single-locus or epistatic effects. As a result, a large number of the cases where loci show pleiotropic effects do not contribute to the covariance between traits in this population because the loci show a different pattern of effect on the different traits. In general, covariance patterns produced by single-locus and epistatic pleiotropy predicted by the model agreed well with actual values calculated from the QTL analysis. Nearly all single-locus and epistatic pleiotropic effects contributed positive components to covariances between traits, suggesting that genetic integration in the skull is achieved by a complex combination of pleiotropic effects.     

The genetic structure of female life history in D. melanogaster: comparisons among populations

Two questions were addressed: (1) What is the genetic variance-covariance structure of a suite of four female life history traits in D. melanogaster? and (2) Does the genetic architecture of these traits differ among populations? Three populations of D. melanogaster were studied. Genetic variances and covariances were estimated by sib analysis three times for each population: immediately upon establishment of populations in the laboratory, and subsequently after approximately 6 months and 2 years of laboratory culture. Entire genetic variance-covariance matrices, as well as their individual components, were compared between populations by means of likelihood ratio tests. All traits studied were significantly heritable in at least one-half of estimates. Despite large sample sizes, additive genetic covariances were for the most part not statistically significant, and only two significant negative covariance estimates were obtained throughout the experiments. Therefore, these experiments provide little support for evolutionary life history theories that are based on negative genetic correlations among life history components. Neither do they support the idea that genetic variance for fitness components is maintained by trade-offs. Evidence suggests that the G matrix of one population was initially different from those of the other two populations. Those differences disappeared after 2 years of laboratory culture. At the level of individual (co)variance components, there were relatively few differences among populations, and the overall impression was that the three populations had generally similar genetic architectures for the traits studied.     

Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies

Genetic and environmental covariances between pairs of complex traits are important quantitative measurements that characterize their shared genetic and environmental architectures. Accurate estimation of genetic and environmental covariances in genome-wide association studies (GWASs) can help us identify common genetic and environmental factors associated with both traits and facilitate the investigation of their causal relationship. Genetic and environmental covariances are often modeled through multivariate linear mixed models. Existing algorithms for covariance estimation include the traditional restricted maximum likelihood (REML) method and the recent method of moments (MoM). Compared to REML, MoM approaches are computationally efficient and require only GWAS summary statistics. However, MoM approaches can be statistically inefficient, often yielding inaccurate covariance estimates. In addition, existing MoM approaches have so far focused on estimating genetic covariance and have largely ignored environmental covariance estimation. Here we introduce a new computational method, GECKO, for estimating both genetic and environmental covariances, that improves the estimation accuracy of MoM while keeping computation in check. GECKO is based on composite likelihood, relies on only summary statistics for scalable computation, provides accurate genetic and environmental covariance estimates across a range of scenarios, and can accommodate SNP annotation stratified covariance estimation. We illustrate the benefits of GECKO through simulations and applications on analyzing 22 traits from five large-scale GWASs. In the real data applications, GECKO identified 50 significant genetic covariances among analyzed trait pairs, resulting in a twofold power gain compared to the previous MoM method LDSC. In addition, GECKO identified 20 significant environmental covariances. The ability of GECKO to estimate environmental covariance in addition to genetic covariance helps us reveal strong positive correlation between the genetic and environmental covariance estimates across trait pairs, suggesting that common pathways may underlie the shared genetic and environmental architectures between traits.