Protein deprivation decreases male survival and the intensity of sexual antagonism in southern field crickets Gryllus bimaculatus

Recent theory predicts that the magnitude of sexual antagonism should depend on how well populations are adapted to their environment. We tested this idea experimentally by comparing intersexual genetic correlations for adult survival in pedigreed populations of southern field crickets (Gryllus bimaculatus) raised on naturally balanced (free‐choice) vs. imbalanced (protein‐deprived) diets. We tested for (1) sex differences in nutritional intake and preference, (2) sex‐specific effects of protein deprivation on survival and (3) diet dependence of the level of sexual antagonism. Adult males and females consumed a similar amount of protein, but protein deprivation decreased male survival but not female survival. Protein deprivation appeared to decrease the degree of sexual antagonism as intersexual genetic correlations were significantly lower than 1 only for the complementary free‐choice diet group but close to 1 for the protein‐deficient diet group. Our findings thereby implied that variation in nutritional environments can alter the magnitude of sexual antagonism. This research represents an important step towards understanding the relationship between sexual antagonism and adaptation in heterogeneous environments.     

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.     

Genetics of body shape and armour variation in threespine sticklebacks

Patterns of genetic variation and covariation can influence the rate and direction of phenotypic evolution. We explored the possibility that the parallel morphological evolution seen in threespine stickleback (Gasterosteus aculeatus) populations colonizing freshwater environments is facilitated by patterns of genetic variation and covariation in the ancestral (marine) population. We estimated the genetic (G) and phenotypic (P) covariance matrices and directions of maximum additive genetic (g(max) ) and phenotypic (p(max) ) covariances of body shape and armour traits. Our results suggest a role for the ancestral G in explaining parallel morphological evolution in freshwater populations. We also found evidence of genetic constraints owing to the lack of variance in the ancestral G. Furthermore, strong genetic covariances and correlations among traits revealed that selective factors responsible for threespine stickleback body shape and armour divergence may be difficult to disentangle. The directions of g(max) and p(max) were correlated, but the correlations were not high enough to imply that phenotypic patterns of trait variation and covariation within populations are very informative of underlying genetic patterns.     

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.     

Evolutionary quantitative genetics of nonlinear developmental systems

In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium‐term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time‐steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances.     

RESISTANCE OF GENETIC CORRELATION STRUCTURE TO DIRECTIONAL SELECTION IN DROSOPHILA MELANOGASTER

The genetic covariance and correlation matrices for five morphological traits were estimated from four populations of fruit flies, Drosophila melanogaster, to measure the extent of change in genetic covariances as a result of directional selection. Two of the populations were derived from lines that had undergone selection for large or small thorax length over the preceding 23 generations. A third population was constituted using flies from control lines that were maintained with equivalent population sizes as the selected lines. The fourth population contained flies from the original cage population from which the selected and control lines had been started. Tests of the homogeneity of covariance matrices using maximum likelihood techniques revealed significant changes in covariance structure among the selected lines. Prediction of base population trait means from selected line means under the assumption of constant genetic covariances indicated that genetic covariances for the small population differed more from the base population than did the covariances for the large population. The predicted small population means diverged farther from the expected means because the additive genetic variance associated with several traits increased in value and most of the genetic covariances associated with one trait changed in sign. These results illustrate that genetic covariances may remain nearly constant in some situations while changing markedly in others. Possible developmental reasons for the genetic changes are discussed.     

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.     

Cross‐sex genetic covariances limit the evolvability of wing‐shape within and among species of Drosophila

The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross‐sex genetic covariances in their predictions. Drosophila wing‐shape has emerged as a model high‐dimensional phenotype; wing‐shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here, we show that cross‐sex covariances in Drosophila melanogaster, given by the B ‐matrix, may considerably bias wing‐shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, on average, but would double the response to concordant selection. Both cross‐sex within‐trait and cross‐sex cross‐trait covariances determined the predicted response to antagonistic selection, but only cross‐sex within‐trait covariances facilitated the predicted response to concordant selection. Similar patterns were observed in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between‐sex genetic covariances when making predictions about evolution on both macro‐ and microevolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.     

THE EVOLVABILITY OF GROWTH FORM IN A CLONAL SEAWEED

Although modular construction is considered the key to adaptive growth or growth‐form plasticity in sessile taxa (e.g., plants, seaweeds and colonial invertebrates), the serial expression of genes in morphogenesis may compromise its evolutionary potential if growth forms emerge as integrated wholes from module iteration. To explore the evolvability of growth form in the red seaweed, Asparagopsis armata, we estimated genetic variances, covariances, and cross‐environment correlations for principal components of growth‐form variation in contrasting light environments. We compared variance–covariance matrices across environments to test environmental effects on heritable variation and examined the potential for evolutionary change in the direction of plastic responses to light. Our results suggest that growth form in Asparagopsis may constitute only a single genetic entity whose plasticity affords only limited evolutionary potential. We argue that morphological integration arising from modular construction may constrain the evolvability of growth form in Asparagopsis, emphasizing the critical distinction between genetic and morphological modularity in this and other modular taxa.     

Environmental stress correlates with increases in both genetic and residual variances: A meta‐analysis of animal studies

Adaptive evolutionary responses are determined by the strength of selection and amount of genetic variation within traits, however, both are known to vary across environmental conditions. As selection is generally expected to be strongest under stressful conditions, understanding how the expression of genetic variation changes across stressful and benign environmental conditions is crucial for predicting the rate of adaptive change. Although theory generally predicts increased genetic variation under stress, previous syntheses of the field have found limited support for this notion. These studies have focused on heritability, which is dependent on other environmentally sensitive, but nongenetic, sources of variation. Here, we aim to complement these studies with a meta‐analysis in which we examine changes in coefficient of variation (CV) in maternal, genetic, and residual variances across stressful and benign conditions. Confirming previous analyses, we did not find any clear direction in how heritability changes across stressful and benign conditions. However, when analyzing CV, we found higher genetic and residual variance under highly stressful conditions in life‐history traits but not in morphological traits. Our findings are of broad significance to contemporary evolution suggesting that rapid evolutionary adaptive response may be mediated by increased evolutionary potential in stressed populations.     

Concordance between stabilizing sexual selection,intraspecific variation,and interspecific divergence in Phymata

Empirical studies show that lineages typically exhibit long periods of evolutionary stasis and that relative levels of within‐species trait covariance often correlate with the extent of between‐species trait divergence. These observations have been interpreted by some as evidence of genetic constraints persisting for long periods of time. However, an alternative explanation is that both intra‐ and interspecific variation are shaped by the features of the adaptive landscape (e.g., stabilizing selection). Employing a genus of insects that are diverse with respect to a suite of secondary sex traits, we related data describing nonlinear phenotypic (sexual) selection to intraspecific trait covariances and macroevolutionary divergence. We found support for two key predictions (1) that intraspecific trait covariation would be aligned with stabilizing selection and (2) that there would be restricted macroevolutionary divergence in the direction of stabilizing selection. The observed alignment of all three matrices offers a point of caution in interpreting standing variability as metrics of evolutionary constraint. Our results also illustrate the power of sexual selection for determining variation observed at both short and long timescales and account for the apparently slow evolution of some secondary sex characters in this lineage.     

A G matrix analogue to capture the cumulative effects of nongenetic inheritance

The genetic variance‐covariance ( G ) matrix describes the variances and covariances of genetic traits under strict genetic inheritance. Genetically expressed traits often influence trait expression in another via nongenetic forms of transmission and inheritance, however. The importance of non‐genetic influences on phenotypic evolution is increasingly clear, but how genetic and nongenetic inheritance interact to determine the response to selection is not well understood. Here, we use the ‘reachability matrix’ – a key analytical tool of geometric control theory – to integrate both forms of inheritance, capturing how the consequences of generation‐lagged maternal effects accumulate. Building on the classic Lande and Kirkpatrick model that showed how nongenetic (maternal) inheritance fundamentally alters the expected path of phenotypic evolution, we make novel inferences through decomposition of the reachability matrix. In particular, we quantify how nongenetic inheritance affects the distribution (orientation and shape) of ellipses of phenotypic change and how these distributions influence subsequent evolution. This interweaving of phenotypic means and variances accumulates generation by generation and is described analytically by the reachability matrix, which acts as an analogue of G when genetic and nongenetic inheritance both act.     

Runaway sexual selection without genetic correlations: social environments and flexible mate choice initiate and enhance the fisher process

Female mating preferences are often flexible, reflecting the social environment in which they are expressed. Associated indirect genetic effects (IGEs) can affect the rate and direction of evolutionary change, but sexual selection models do not capture these dynamics. We incorporate IGEs into quantitative genetic models to explore how variation in social environments and mate choice flexibility influence Fisherian sexual selection. The importance of IGEs is that runaway sexual selection can occur in the absence of a genetic correlation between male traits and female preferences. Social influences can facilitate the initiation of the runaway process and increase the rate of trait elaboration. Incorporating costs to choice do not alter the main findings. Our model provides testable predictions: (1) genetic covariances between male traits and female preferences may not exist, (2) social flexibility in female choice will be common in populations experiencing strong sexual selection, (3) variation in social environments should be associated with rapid sexual trait divergence, and (4) secondary sexual traits will be more elaborate than previously predicted. Allowing feedback from the social environment resolves discrepancies between theoretical predictions and empirical data, such as why indirect selection on female preferences, theoretically weak, might be sufficient for preferences to become elaborated.     

WATER STRESS ALTERS THE GENETIC ARCHITECTURE OF FUNCTIONAL TRAITS ASSOCIATED WITH DROUGHT ADAPTATION IN AVENA BARBATA

Environmental stress can alter genetic variation and covariation underlying functional traits, and thus affect adaptive evolution in response to natural selection. However, the genetic basis of functional traits is rarely examined in contrasting resource environments, and consequently, there is no consensus regarding whether environmental stress constrains or facilitates adaptive evolution. We tested whether resource availability affects genetic variation for and covariation among seven physiological traits and seven morphological/performance traits by growing the annual grass Avena barbata in dry and well-watered treatments. We found that differences in the overall genetic variance–covariance ( G ) matrix between environments were driven by physiological traits rather than morphology and performance traits. More physiological traits were heritable in the dry treatment than the well-watered treatment and many of the genetic correlations among physiological traits were environment dependent. In contrast, genetic variation and covariation among the morphological and performance traits did not differ across treatments. Furthermore, genetic correlations between physiology and performance were stronger in the dry treatment, which contributed to differences in the overall G -matrix. Our results therefore suggest that physiological adaptation would be constrained by low heritable variation in resource-rich environments, but facilitated by higher heritable variation and stronger genetic correlations with performance traits in resource-poor environments.     

Adaptive and non‐adaptive evolution of trait means and genetic trait correlations for herbivory resistance and performance in an invasive plant

The EICA‐hypothesis predicts that invading plants adapt to their novel environment by evolving increased performance and reduced resistance in response to the release from natural enemies, and assumes a resource allocation tradeoff among both trait groups as mechanistic basis of this evolutionary change. Using the plant Silene latifolia as a study system, we tested these predictions by investigating whether 1) invasive populations evolved lower resistance and higher performance, 2) this evolutionary change is indeed adaptive, and 3) there is a negative genetic correlation between performance and resistance (i.e. a tradeoff) in native and introduced individuals. Moreover, we sampled eight native and eight invasive populations and determined their population co‐ancestry based on neutral SSR‐markers. We performed controlled crossings to produce five sib‐groups per population and exposed them to increased and reduced levels of enemy attack in a full‐factorial experiment to estimate performance and resistance. With these data, we performed trait‐by‐trait comparisons between ranges with ‘animal models’ that account for population co‐ancestry to quantify the amount of variance in traits explained by non‐adaptive versus adaptive evolution. Moreover, we tested for genetic correlations among performance and resistance traits within sib‐groups. We found significant reductions in resistance and increases in performance in invasive versus native populations, which could largely be attributed to adaptive evolution. While we detected a non‐significant trend towards negative genetic performance × resistance correlations in native populations, invasive populations exhibited both significant and non‐significant positive correlations. In summary, these results do not support a shift of performance and resistance trait values along a tradeoff line in response to enemy release, as predicted by EICA. They rather suggest that the independent evolution of both traits is not constrained by a tradeoff, and that various selective agents (including resource availability) interact in shaping both traits and in weakening negative genetic correlations in the invaded habitat.     

Particulate versus integrated evolution of the upper body in late pleistocene humans: A test of two models

Evolutionary biologists are largely polarized in their approaches to integrating microevolutionary and macroevolutionary processes. Neo-Darwinians typically seek to identify population-level selective and genetic processes that culminate in macroevolutionary events. Epigeneticists and structuralists, on the other hand, emphasize developmental constraints on the action of natural selection, and highlight the role of epigenetic shifts in producing evolutionary change in morphology. Accordingly, the ways in which these paradigms view and address morphological contrasts between classes of related organisms differ. These paradigms, although seldomly explicitly stated, emerge in paleoanthropology as well. Considerations of postcranial morphological contrasts between archaic and modern humans typically fall into one of two broad interpretive models. The first derives from the neo-Darwinian perspective and holds that evolution in the postcranial skeleton was largely mosaic (operating in a particulate manner), and that temporal change in specific traits informs us about behavioral shifts or genetic evolution affecting isolated anatomical regions (i.e., adaptive behavioral inferences can be made from comparative studies of individual trait complexes). The alternative model follows from the epigeneticist paradigm and sees change in specific postcranial traits as correlated responses to change in overall body form (involving shifts in regulation of skeletal growth, or selective and developmental responses to broad adaptive shifts). By this view, integration of functional systems both constrains and directs evolution of various traits, and morphological contrasts inform us about overall change in body form related to change in such things as overall growth patterns, climatic adaptation, and technological dependency. These models were tested by confirmatory factor analysis using measures of upper body form and upper limb morphological traits in Eurasian Neandertal and early modern fossils and recent human samples. Results indicate (1) a model of morphological integration fits the data better than a model of no integration, but (2) this integration accounts for less than half of the variance in upper limb traits, suggesting a high degree of tolerance for particulate evolution in the context of an integrated upper body plan. Significant relationships were detected between joint shapes and body size, between humeral shaft shape and body size and chest shape, and between measures of biomechanical efficiency and robusticity. The observed morphological differences between late archaic and early modern humans reflect particulate evolution in the context of constraints imposed by genetic and morphological integration. While particulate approaches to interpreting the fossil record appear to be justified, attention must also be paid to delineating the nature and extent of morphological integration and its role in both constraining and producing observed patterns of variation between groups. Confirmatory factor analysis provides a means of examining trait covariance matrices, and serves as a useful method of identifying patterns of integration in morphology. © 1996 Wiley-Liss, Inc.     

The effects of stress and sex on selection,genetic covariance,and the evolutionary response

The capacity of a population to adapt to selection (evolvability) depends on whether the structure of genetic variation permits the evolution of fitter trait combinations. Selection, genetic variance and genetic covariance can change under environmental stress, and males and females are not genetically independent, yet the combined effects of stress and dioecy on evolvability are not well understood. Here, we estimate selection, genetic (co)variance and evolvability in both sexes of Tribolium castaneum flour beetles under stressful and benign conditions, using a half‐sib breeding design. Although stress uncovered substantial latent heritability, stress also affected genetic covariance, such that evolvability remained low under stress. Sexual selection on males and natural selection on females favoured a similar phenotype, and there was positive intersex genetic covariance. Consequently, sexual selection on males augmented adaptation in females, and intralocus sexual conflict was weak or absent. This study highlights that increased heritability does not necessarily increase evolvability, suggests that selection can deplete genetic variance for multivariate trait combinations with strong effects on fitness, and tests the recent hypothesis that sexual conflict is weaker in stressful or novel environments.     

Evolutionary potential of a widespread clonal grass under changing climate

Adaptive responses are probably the most effective long‐term responses of populations to climate change, but they require sufficient evolutionary potential upon which selection can act. This requires high genetic variance for the traits under selection and low antagonizing genetic covariances between the different traits. Evolutionary potential estimates are still scarce for long‐lived, clonal plants, although these species are predicted to dominate the landscape with climate change. We studied the evolutionary potential of a perennial grass, Festuca rubra, in western Norway, in two controlled environments corresponding to extreme environments in natural populations: cold–dry and warm–wet, the latter being consistent with the climatic predictions for the country. We estimated genetic variances, covariances, selection gradients and response to selection for a wide range of growth, resource acquisition and physiological traits, and compared their estimates between the environments. We showed that the evolutionary potential of F. rubra is high in both environments, and genetic covariances define one main direction along which selection can act with relatively few constraints to selection. The observed response to selection at present is not sufficient to produce genotypes adapted to the predicted climate change under a simple, space for time substitution model. However, the current populations contain genotypes which are pre‐adapted to the new climate, especially for growth and resource acquisition traits. Overall, these results suggest that the present populations of the long‐lived clonal plant may have sufficient evolutionary potential to withstand long‐term climate changes through adaptive responses.     

Are we underestimating the genetic variances of dimorphic traits?

Populations often contain discrete classes or morphs (e.g., sexual dimorphisms, wing dimorphisms, trophic dimorphisms) characterized by distinct patterns of trait expression. In quantitative genetic analyses, the different morphs can be considered as different environments within which traits are expressed. Genetic variances and covariances can then be estimated independently for each morph or in a combined analysis. In the latter case, morphs can be considered as separate environments in a bivariate analysis or entered as fixed effects in a univariate analysis. Although a common approach, we demonstrate that the latter produces downwardly biased estimates of additive genetic variance and heritability unless the quantitative genetic architecture of the traits concerned is perfectly correlated between the morphs. This result is derived for four widely used quantitative genetic variance partitioning methods. Given that theory predicts the evolution of genotype‐by‐environment (morph) interactions as a consequence of selection favoring different trait combinations in each morph, we argue that perfect correlations between the genetic architectures of the different morphs are unlikely. A sampling of the recent literature indicates that the majority of researchers studying traits expressed in different morphs recognize this and do estimate morph‐specific quantitative genetic architecture. However, ca. 16% of the studies in our sample utilized only univariate, fixed‐effects models. We caution against this approach and recommend that it be used only if supported by evidence that the genetic architectures of the different morphs do not differ.     

The causes of repeated genetic evolution

A general understanding of the evolutionary process is limited by the contingency of each evolutionary event, making it difficult, even retrospectively, to explain why things have unfolded the way they have. The repeated evolution of similar traits in organisms facing similar environmental conditions is a pervasive phenomenon, including for animal morphology, and is considered a strong evidence for adaptive evolution. Examples of repeated evolution of particular traits offer a unique opportunity to ask whether evolution has followed similar or different genetic paths. Case studies reveal that although multiple genetic paths were often possible to evolve a morphological trait, similar evolutionary trajectories have been followed repeatedly in independent lineages, suggesting that biases influence the course of genetic evolution. In the light of these examples we examine several factors influencing the genetic paths of adaptive evolution and in particular how the interplay between natural selection and genetic variations carves out predictable genetic trajectories of morphological evolution.