Patterns of quantitative genetic variation in multiple dimensions

On the resolution of sexual conflict over shared traits

Anisogamy, different-sized male and female gametes, sits at the heart of sexual selection and conflict between the sexes. Sperm producers (males) and egg producers (females) of the same species generally share most, if not all, of the same genome, but selection frequently favours different trait values in each sex for traits common to both. The extent to which this conflict might be resolved, and the potential mechanisms by which this can occur, have been widely debated. Here, we summarize recent findings and emphasize that once the sexes evolve, sexual selection is ongoing, and therefore new conflict is always possible. In addition, sexual conflict is largely a multivariate problem, involving trait combinations underpinned by networks of interconnected genes. Although these complexities can hinder conflict resolution, they also provide multiple possible routes to decouple male and female phenotypes and permit sex-specific evolution. Finally, we highlight difficulty in the study of sexual conflict over shared traits and promising directions for future research.

Drift on holey landscapes as a dominant evolutionary process

An organism's phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits-like most behaviors, physiological processes, and life-history traits-should be distributed under different evolutionary processes are not clear. Here, we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across six phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high-dimensional "holey landscapes." This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.

Two common, often coexisting grassland plant species differ in their evolutionary potential in response to experimental drought

For terrestrial plant communities, the increase in frequency and intensity of drought events is considered as one of the most severe consequences of climate change. While single-species studies demonstrate that drought can lead to relatively rapid adaptive genetic changes, the evolutionary potential and constraints to selection need to be assessed in comparative approaches to draw more general conclusions. In a greenhouse experiment, we compare the phenotypic response and evolutionary potential of two co-occurring grassland plant species, Bromus erectus and Trifolium pratense, in two environments differing in water availability. We quantified variation in functional traits and reproductive fitness in response to drought and compared multivariate genetic variance-covariance matrices and predicted evolutionary responses between species. Species showed different drought adaptation strategies, reflected in both their species-specific phenotypic plasticity and predicted responses to selection indicating contrasting evolutionary potential under drought. In T. pratense we found evidence for stronger genetic constraints under drought compared to more favourable conditions, and for some traits plastic and predicted evolutionary responses to drought had opposing directions, likely limiting the potential for adaptive change. Our study contributes to a more detailed understanding of the evolutionary potential of species with different adaptive strategies in response to climate change and may help to inform future scenarios for semi-natural grassland ecosystems.

Selection and the direction of phenotypic evolution

Predicting adaptive phenotypic evolution depends on invariable selection gradients and on the stability of the genetic covariances between the component traits of the multivariate phenotype. We describe the evolution of six traits of locomotion behavior and body size in the nematode Caenorhabditis elegans for 50 generations of adaptation to a novel environment. We show that the direction of adaptive multivariate phenotypic evolution can be predicted from the ancestral selection differentials, particularly when the traits were measured in the new environment. Interestingly, the evolution of individual traits does not always occur in the direction of selection, nor are trait responses to selection always homogeneous among replicate populations. These observations are explained because the phenotypic dimension with most of the ancestral standing genetic variation only partially aligns with the phenotypic dimension under directional selection. These findings validate selection theory and suggest that the direction of multivariate adaptive phenotypic evolution is predictable for tens of generations.

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Exact expressions and numerical evaluation of average evolvability measures for characterizing and comparing [Formula: see text] matrices

Theory predicts that the additive genetic covariance ([Formula: see text]) matrix determines a population's short-term (in)ability to respond to directional selection-evolvability in the Hansen-Houle sense-which is typically quantified and compared via certain scalar indices called evolvability measures. Often, interest is in obtaining the averages of these measures across all possible selection gradients, but explicit formulae for most of these average measures have not been known. Previous authors relied either on approximations by the delta method, whose accuracy is generally unknown, or Monte Carlo evaluations (including the random skewers analysis), which necessarily involve random fluctuations. This study presents new, exact expressions for the average conditional evolvability, average autonomy, average respondability, average flexibility, average response difference, and average response correlation, utilizing their mathematical structures as ratios of quadratic forms. The new expressions are infinite series involving top-order zonal and invariant polynomials of matrix arguments, and can be numerically evaluated as their partial sums with, for some measures, known error bounds. Whenever these partial sums numerically converge within reasonable computational time and memory, they will replace the previous approximate methods. In addition, new expressions are derived for the average measures under a general normal distribution for the selection gradient, extending the applicability of these measures into a substantially broader class of selection regimes.

How development affects evolution

Natural selection acts on developmentally constructed phenotypes, but how does development affect evolution? This question prompts a simultaneous consideration of development and evolution. However, there has been a lack of general mathematical frameworks mechanistically integrating the two, which may have inhibited progress on the question. Here, we use a new mathematical framework that mechanistically integrates development into evolution to analyse how development affects evolution. We show that, while selection pushes genotypic and phenotypic evolution up the fitness landscape, development determines the admissible evolutionary pathway, such that evolutionary outcomes occur at path peaks rather than landscape peaks. Changes in development can generate path peaks, triggering genotypic or phenotypic diversification, even on constant, single-peak landscapes. Phenotypic plasticity, niche construction, extra-genetic inheritance, and developmental bias alter the evolutionary path and hence the outcome. Thus, extra-genetic inheritance can have permanent evolutionary effects by changing the developmental constraints, even if extra-genetically acquired elements are not transmitted to future generations. Selective development, whereby phenotype construction points in the adaptive direction, may induce adaptive or maladaptive evolution depending on the developmental constraints. Moreover, developmental propagation of phenotypic effects over age enables the evolution of negative senescence. Overall, we find that development plays a major evolutionary role.

Dimensionality and Modularity of Adaptive Variation: Divergence in Threespine Stickleback from Diverse Environments

AbstractPopulations are subjected to diverse environmental conditions that affect fitness and induce evolutionary or plastic responses, resulting in phenotypic divergence. Some authors contend that such divergence is concentrated along a single major axis of trait covariance even if that axis does not lead populations directly toward a fitness optimum. Other authors argue that divergence can occur readily along many phenotype axes at the same time. We use populations of threespine stickleback (Gasterosteus aculeatus) from 14 lakes with contrasting ecological conditions to find some resolution along the continuum between these two extremes. Unlike many previous studies, we included several functional suites of traits (defensive, swimming, trophic) potentially subject to different sources of selection. We find that populations exhibit dimensionality of divergence that is high enough to preclude a history of constraint along a single axis-both for divergence in multivariate mean trait values and for the structure of trait covariances. Dimensionality varied among trait suites and were strongly influenced by the inclusion of specific traits, and integration of trait suites varied between populations. We leverage this variation into new insights about the process of divergence and suggest that similar analyses could increase understanding of other adaptive radiations.

Maintenance of quantitative genetic variance in complex, multi-trait phenotypes: The contribution of rare, large effect variants in two Drosophila species

The interaction of evolutionary processes to determine quantitative genetic variation has implications for contemporary and future phenotypic evolution, as well as for our ability to detect causal genetic variants. While theoretical studies have provided robust predictions to discriminate among competing models, empirical assessment of these has been limited. In particular, theory highlights the importance of pleiotropy in resolving observations of selection and mutation, but empirical investigations have typically been limited to few traits. Here, we applied high-dimensional Bayesian Sparse Factor Genetic modeling to gene expression datasets in 2 species, Drosophila melanogaster and Drosophila serrata, to explore the distributions of genetic variance across high-dimensional phenotypic space. Surprisingly, most of the heritable trait covariation was due to few lines (genotypes) with extreme [>3 interquartile ranges (IQR) from the median] values. Intriguingly, while genotypes extreme for a multivariate factor also tended to have a higher proportion of individual traits that were extreme, we also observed genotypes that were extreme for multivariate factors but not for any individual trait. We observed other consistent differences between heritable multivariate factors with outlier lines vs those factors without extreme values, including differences in gene functions. We use these observations to identify further data required to advance our understanding of the evolutionary dynamics and nature of standing genetic variation for quantitative traits.

Evolution: How important is the dimensionality of natural selection in local adaptation?

Organisms adapt to their local environments, which may vary in one aspect, or many. A new study shows that such dimensionality matters, as it impacts the magnitude and dynamics of local adaptation, with broader ecological consequences, such as the evolution of generalists.

Diversity in nonlinear responses to soil moisture shapes evolutionary constraints in Brachypodium

Water availability is perhaps the greatest environmental determinant of plant yield and fitness. However, our understanding of plant-water relations is limited because-like many studies of organism-environment interaction-it is primarily informed by experiments considering performance at two discrete levels-wet and dry-rather than as a continuously varying environmental gradient. Here, we used experimental and statistical methods based on function-valued traits to explore genetic variation in responses to a continuous soil moisture gradient in physiological and morphological traits among 10 genotypes across two species of the model grass genus Brachypodium. We find that most traits exhibit significant genetic variation and nonlinear responses to soil moisture variability. We also observe differences in the shape of these nonlinear responses between traits and genotypes. Emergent phenomena arise from this variation including changes in trait correlations and evolutionary constraints as a function of soil moisture. Our results point to the importance of considering diversity in nonlinear organism-environment relationships to understand plastic and evolutionary responses to changing climates.

Mapping pleiotropic loci using a fast-sequential testing algorithm

Pleiotropy (i.e., genes with effects on multiple traits) leads to genetic correlations between traits and contributes to the development of many syndromes. Identifying variants with pleiotropic effects on multiple health-related traits can improve the biological understanding of gene action and disease etiology, and can help to advance disease-risk prediction. Sequential testing is a powerful approach for mapping genes with pleiotropic effects. However, the existing methods and the available software do not scale to analyses involving millions of SNPs and large datasets. This has limited the adoption of sequential testing for pleiotropy mapping at large scale. In this study, we present a sequential test and software that can be used to test pleiotropy in large systems of traits with biobank-sized data. Using simulations, we show that the methods implemented in the software are powerful and have adequate type-I error rate control. To demonstrate the use of the methods and software, we present a whole-genome scan in search of loci with pleiotropic effects on seven traits related to metabolic syndrome (MetS) using UK-Biobank data (n~300 K distantly related white European participants). We found abundant pleiotropy and report 170, 44, and 18 genomic regions harboring SNPs with pleiotropic effects in at least two, three, and four of the seven traits, respectively. We validate our results using previous studies documented in the GWAS-catalog and using data from GTEx. Our results confirm previously reported loci and lead to several novel discoveries that link MetS-related traits through plausible biological pathways.

Statistics of eigenvalue dispersion indices: Quantifying the magnitude of phenotypic integration

Analysis of trait covariation plays a pivotal role in the study of phenotypic evolution. The magnitude of covariation is often quantified with statistics based on dispersion of eigenvalues of a covariance or correlation matrix-eigenvalue dispersion indices. This study clarifies the statistical justifications of these statistics and elaborates on their sampling properties. The relative eigenvalue variance of a covariance matrix is known in the statistical literature a test statistic for sphericity, and thus is an appropriate measure of eccentricity of variation. The same of a correlation matrix is equal to the average squared correlation, which has a straightforward interpretation as a measure of integration. Here, expressions for the mean and variance of these statistics are analytically derived under multivariate normality, clarifying the effects of sample size N, number of variables p, and parameters on sampling bias and error. Simulations confirm that approximations involved are reasonably accurate with a moderate sample size (N ≥ 16-64). Importantly, sampling properties of these indices are not adversely affected by a high p:N ratio, promising their utility in high-dimensional phenotypic analyses. They can furthermore be applied to shape variables and phylogenetically structured data with appropriate modifications.

Environmental effects on the genetic architecture of fitness components in a simultaneous hermaphrodite

Understanding how environmental change affects genetic variances and covariances of reproductive traits is key to formulate firm predictions on evolutionary responses. This is particularly true for sex-specific variance in reproductive success, which has been argued to affect how populations can adapt to environmental change. Our current knowledge on the impact of environmental stress on sex-specific genetic architecture of fitness components is still limited and restricted to separate-sexed organisms. However, hermaphroditism is widespread across animals and may entail interesting peculiarities with respect to genetic constraints imposed on the evolution of male and female reproduction. We explored how food restriction affects the genetic variance-covariance (G) matrix of body size and reproductive success of the simultaneously hermaphroditic freshwater snail Physa acuta. Our results provide strong evidence that the imposed environmental stress elevated the opportunity for selection in both sex functions. However, the G-matrix remained largely stable across the tested food treatments. Importantly, our results provide no support for cross-sex genetic correlations suggesting no strong evolutionary coupling of male and female reproductive traits. We discuss potential implications for the adaptation to changing environments and highlight the need for more quantitative genetic studies on male and female fitness components in simultaneous hermaphrodites.

Integrating genomics and multivariate evolutionary quantitative genetics: a case study of constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance-covariance matrix, G, and the vector of directional selection gradients, β, are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate genome-wide association study (GWAS) with G and β estimation in a well-studied system of multivariate constraint: sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata. In a panel of wild-derived re-sequenced lines, we augment genome-based restricted maximum likelihood to estimate G alongside multivariate single nucleotide polymorphism (SNP) effects, detecting 532 significant associations from 1 652 276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β. SNP effects were significantly misaligned with the major eigenvector of G, gmax, but well aligned to the second and third eigenvectors g2 and g3. We discuss potential factors leading to these varied results including multivariate stabilizing selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

The contribution of mutation and selection to multivariate quantitative genetic variance in an outbred population of Drosophila serrata

Genetic variance is not equal for all multivariate combinations of traits. This inequality, in which some combinations of traits have abundant genetic variation while others have very little, biases the rate and direction of multivariate phenotypic evolution. However, we still understand little about what causes genetic variance to differ among trait combinations. Here, we investigate the relative roles of mutation and selection in determining the genetic variance of multivariate phenotypes. We accumulated mutations in an outbred population of Drosophila serrata and analyzed wing shape and size traits for over 35,000 flies to simultaneously estimate the additive genetic and additive mutational (co)variances. This experimental design allowed us to gain insight into the phenotypic effects of mutation as they arise and come under selection in naturally outbred populations. Multivariate phenotypes associated with more (less) genetic variance were also associated with more (less) mutational variance, suggesting that differences in mutational input contribute to differences in genetic variance. However, mutational correlations between traits were stronger than genetic correlations, and most mutational variance was associated with only one multivariate trait combination, while genetic variance was relatively more equal across multivariate traits. Therefore, selection is implicated in breaking down trait covariance and resulting in a different pattern of genetic variance among multivariate combinations of traits than that predicted by mutation and drift. Overall, while low mutational input might slow evolution of some multivariate phenotypes, stabilizing selection appears to reduce the strength of evolutionary bias introduced by pleiotropic mutation.

Effective Dimensionality: A Tutorial

The topic of this tutorial is the effective dimensionality (ED) of a dataset, that is, the equivalent number of orthogonal dimensions that would produce the same overall pattern of covariation. The ED quantifies the total dimensionality of a set of variables, with no assumptions about their underlying structure. The ED of a dataset has important implications for the "curse of dimensionality"; it can be used to inform decisions about data analysis and answer meaningful empirical questions. The tutorial offers an accessible introduction to ED, distinguishes it from the related but distinct concept of intrinsic dimensionality, critically reviews various ED estimators, and gives indications for practical use with examples from personality research. An R function is provided to implement the techniques described in the tutorial.

Immigration counter-acts local micro-evolution of a major fitness component: Migration-selection balance in free-living song sparrows

Ongoing adaptive evolution, and resulting “evolutionary rescue” of declining populations, requires additive genetic variation in fitness. Such variation can be increased by gene flow resulting from immigration, potentially facilitating evolution. But, gene flow could in fact constrain rather than facilitate local adaptive evolution if immigrants have low additive genetic values for local fitness. Local migration‐selection balance and micro‐evolutionary stasis could then result. However, key quantitative genetic effects of natural immigration, comprising the degrees to which gene flow increases the total local additive genetic variance yet counteracts local adaptive evolutionary change, have not been explicitly quantified in wild populations. Key implications of gene flow for population and evolutionary dynamics consequently remain unclear. Our quantitative genetic analyses of long‐term data from free‐living song sparrows (Melospiza melodia) show that mean breeding value for local juvenile survival to adulthood, a major component of fitness, increased across cohorts more than expected solely due to drift. Such micro‐evolutionary change should be expected given nonzero additive genetic variance and consistent directional selection. However, this evolutionary increase was counteracted by negative additive genetic effects of recent immigrants, which increased total additive genetic variance but prevented a net directional evolutionary increase in total additive genetic value. These analyses imply an approximate quantitative genetic migration‐selection balance in a major fitness component, and hence demonstrate a key mechanism by which substantial additive genetic variation can be maintained yet decoupled from local adaptive evolutionary change.

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

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

Genetic basis for divergence in developmental gene expression in two closely related sea urchins

The genetic basis for divergence in developmental gene expression among species is poorly understood, despite growing evidence that such changes underlie many interesting traits. Here we quantify transcription in hybrids of Heliocidaris tuberculata and Heliocidaris erythrogramma, two closely related sea urchins with highly divergent developmental gene expression and life histories. We find that most expression differences between species result from genetic influences that affect one stage of development, indicating limited pleiotropic consequences for most mutations that contribute to divergence in gene expression. Activation of zygotic transcription is broadly delayed in H. erythrogramma, the species with the derived life history, despite its overall faster premetamorphic development. Altered expression of several terminal differentiation genes associated with the derived larval morphology of H. erythrogramma is based largely on differences in the expression or function of their upstream regulators, providing insights into the genetic basis for the evolution of key life history traits.

Why does allometry evolve so slowly?

Morphological allometry is striking due to its evolutionary conservatism, making it an example of a certain sort of evolutionary stasis. Organisms that vary in size, whether for developmental, environmental, or evolutionary reasons, adopt shapes that are predictable from that size alone. There are two major hypotheses to explain this. It may be that natural selection strongly favors each allometric pattern, or that organisms lack the development and genetic capacity to produce variant shapes for selection to act on. Using a high-throughput system for measuring the size and shape of Drosophila wings, we documented an allometric pattern that has been virtually unchanged for 40 million years. We performed an artificial selection experiment on the static allometric slope within one species. In just 26 generations, we were able to increase the slope from 1.1 to 1.4, and decrease it to 0.8. Once artificial selection was suspended, the slope rapidly evolved back to a value near the initial static slope. This result decisively rules out the hypothesis that allometry is preserved due to a lack of genetic variation, and provides evidence that natural selection acts to maintain allometric relationships. On the other hand, it seems implausible that selection on allometry in the wing alone could be sufficiently strong to maintain static allometries over millions of years. This suggests that a potential explanation for stasis is selection on a potentially large number of pleiotropic effects. This seems likely in the case of allometry, as the sizes of all parts of the body may be altered when the allometric slope of one body part is changed. Unfortunately, hypotheses about pleiotropy have been very difficult to test. We lay out an approach to begin the systematic study of pleiotropic effects using genetic manipulations and high-throughput phenotyping.

Do traits separated by metamorphosis evolve independently? Concepts and methods

Despite the ubiquity of complex life cycles, we know little of the evolutionary constraints exerted by metamorphosis. Here, we present pitfalls and methods to answer whether animals with a complex life cycle can independently adapt to the environments encountered at each life stage, with a specific focus on the microevolution of quantitative characters. We first discuss challenges associated with study traits and populations. We further emphasize the benefits of using a combination of approaches. We then develop how multivariate methods can limit several issues by revealing genetic patterns that are invisible when only considering trait-by-trait genetic correlations. Finally, we detail how Lande's work on sexual dimorphism can be applied in measuring G matrices across life stages. The methods and tools described here will contribute towards building a predictive framework for trait evolution across life stages.

Sublethal larval exposure to imidacloprid impacts adult behaviour in Drosophila melanogaster

Pesticides are now chronically found in numerous ecosystems incurring widespread toxic effects on multiple organisms. For insects, the larvae are very exposed to pesticide pollution and the acute effect of insecticides on larvae has been characterized in a range of species. However, the carry-on effects in adults of sublethal exposure occurring in larvae are not well characterized. Here, we use a collection of strains of Drosophila melanogaster differing in their larval resistance to a commonly used insecticide, imidacloprid, and we test the effect of larval exposure on behavioural traits at the adult stage. Focusing on locomotor activity and on courtship and mating behaviour, we observed a significant carry-on effect of imidacloprid exposure. The heritability of activity traits measured in flies exposed to imidacloprid was higher than measured in controls and in these, courtship traits were genetically less correlated from mating success. Altogether, we did not observe a significant effect of the larval insecticide resistance status on adult behavioural traits, suggesting that selection for resistance in larvae does not involve repeatable behavioural changes in adults. This lack of correlation between larval resistance and adult behaviour also suggests that resistance at the larval stage does not necessarily result in increased behavioural resilience at a later life stage. These findings imply that selection for resistance in larvae as well as for behavioural resilience to sublethal exposure in adult will combine and impose a greater evolutionary constraint. Our conclusions further substantiate the need to encompass multiple trait measures and life stages in toxicological assays to properly assess the environmental impact of pesticides.

Reproductive transitions in plants and animals: selfing syndrome, sexual selection and speciation

The evolution of predominant self-fertilisation frequently coincides with the evolution of a collection of phenotypes that comprise the 'selfing syndrome', in both plants and animals. Genomic features also display a selfing syndrome. Selfing syndrome traits often involve changes to male and female reproductive characters that were subject to sexual selection and sexual conflict in the obligatorily outcrossing ancestor, including the gametic phase for both plants and animals. Rapid evolution of reproductive traits, due to both relaxed selection and directional selection under the new status of predominant selfing, lays the genetic groundwork for reproductive isolation. Consequently, shifts in sexual selection pressures coupled to transitions to selfing provide a powerful paradigm for investigating the speciation process. Plant and animal studies, however, emphasise distinct selective forces influencing reproductive-mode transitions: genetic transmission advantage to selfing or reproductive assurance outweighing the costs of inbreeding depression vs the costs of males and meiosis. Here, I synthesise links between sexual selection, evolution of selfing and speciation, with particular focus on identifying commonalities and differences between plant and animal systems and pointing to areas warranting further synergy.

EIGENVALUE DISTRIBUTIONS OF VARIANCE COMPONENTS ESTIMATORS IN HIGH-DIMENSIONAL RANDOM EFFECTS MODELS

We study the spectra of MANOVA estimators for variance component covariance matrices in multivariate random effects models. When the dimensionality of the observations is large and comparable to the number of realizations of each random effect, we show that the empirical spectra of such estimators are well-approximated by deterministic laws. The Stieltjes transforms of these laws are characterized by systems of fixed-point equations, which are numerically solvable by a simple iterative procedure. Our proof uses operator-valued free probability theory, and we establish a general asymptotic freeness result for families of rectangular orthogonally-invariant random matrices, which is of independent interest. Our work is motivated in part by the estimation of components of covariance between multiple phenotypic traits in quantitative genetics, and we specialize our results to common experimental designs that arise in this application.

Causes of maladaptation

Evolutionary biologists tend to approach the study of the natural world within a framework of adaptation, inspired perhaps by the power of natural selection to produce fitness advantages that drive population persistence and biological diversity. In contrast, evolution has rarely been studied through the lens of adaptation's complement, maladaptation. This contrast is surprising because maladaptation is a prevalent feature of evolution: population trait values are rarely distributed optimally; local populations often have lower fitness than imported ones; populations decline; and local and global extinctions are common. Yet we lack a general framework for understanding maladaptation; for instance in terms of distribution, severity, and dynamics. Similar uncertainties apply to the causes of maladaptation. We suggest that incorporating maladaptation-based perspectives into evolutionary biology would facilitate better understanding of the natural world. Approaches within a maladaptation framework might be especially profitable in applied evolution contexts - where reductions in fitness are common. Toward advancing a more balanced study of evolution, here we present a conceptual framework describing causes of maladaptation. As the introductory article for a Special Feature on maladaptation, we also summarize the studies in this Issue, highlighting the causes of maladaptation in each study. We hope that our framework and the papers in this Special Issue will help catalyze the study of maladaptation in applied evolution, supporting greater understanding of evolutionary dynamics in our rapidly changing world.

Sexual antagonism drives the displacement of polymorphism across gene regulatory cascades

Males and females have different reproductive roles and are often subject to contrasting selection pressures. This sexual antagonism can lead, at a given locus, to different alleles being favoured in each sex and, consequently, to genetic variation being maintained in a population. Although the presence of sexually antagonistic (SA) polymorphisms has been documented across a range of species, their evolutionary dynamics remain poorly understood. Here, we study SA selection on gene expression, which is fundamental to sexual dimorphism, via the evolution of regulatory binding sites. We show that for sites longer than 1 nucleotide, expression polymorphism is maintained only when intermediate expression levels are deleterious to both sexes. We then show that, in a regulatory cascade, expression polymorphism tends to become displaced over evolutionary time from the target of SA selection to upstream regulators. Our results have consequences for understanding the evolution of sexual dimorphism, and provide specific empirical predictions for the regulatory architecture of genes under SA selection.

A function-valued trait approach to estimating the genetic basis of size at age and its potential role in fisheries-induced evolution

Natural selection is inherently a multivariate phenomenon. The selection pressure on size (natural and artificial) and the age at which selection occurs is likely to induce evolutionary changes in growth rates across the entire life history. However, the covariance structure that will determine the path of evolution for size at age has been studied in only a few fish species. We therefore estimated the genetic covariance function for size throughout ontogeny using Atlantic silversides (Menidia menidia) as the model system. Over a 3-year period, a total of 542 families were used to estimate the genetic covariance in length at age from hatch through maturity. The function-valued trait approach was employed to estimate the genetic covariance functions. A Bayesian hierarchical model was used to account for the unbalanced design, unequal measurement intervals, unequal sample sizes, and family-aggregated data. To improve mixing, we developed a two-stage sampler using a Gibbs sampler to generate the posterior of a well-mixing approximate model followed by an importance sampler to draw samples from posterior of the completely specified model. We found that heritability of length is age-specific and there are strong genetic correlations in length across ages that last 30 days or more. We used these estimates in a hypothetical model predicting the evolutionary response to harvesting following a single generation of selection under both sigmoidal and unimodal patterns of gear selectivity to illustrate the potential outcomes of ignoring the genetic correlations. In these scenarios, genetic correlations were found to have a strong effect on both the direction and magnitude of the response to harvest selection.

Genetic and environmental variation in transcriptional expression of seminal fluid proteins

Seminal fluid proteins (SFPs) are crucial mediators of sexual selection and sexual conflict. Recent studies have chiefly focused on environmentally induced plasticity as one source of variation in SFP expression, particularly in response to differing sperm competition levels. However, understanding the evolution of a trait in heterogenous environments requires estimates of both environmental and genetic sources of variation, as well as their interaction. Therefore, we investigated how environment (specifically mating group size, a good predictor of sperm competition intensity), genotype and genotype-by-environment interactions affect seminal fluid expression. To do so, we reared 12 inbred lines of a simultaneously hermaphroditic flatworm Macrostomum lignano in groups of either two or eight worms and measured the expression levels of 58 putative SFP transcripts. We then examined the source of variation in the expression of each transcript individually and for multivariate axes extracted from a principal component analysis. We found that mating group size did not affect expression levels according to the single transcript analyses, nor did it affect the first principal component (presumably representing overall investment in seminal fluid production). However, mating group size did affect the relative expression of different transcripts captured by the second principal component (presumably reflecting variation in seminal fluid composition). Most transcripts were genetically variable in their expression level and several exhibited genotype-by-environment interactions; relative composition also showed high genetic variation. Collectively, our results reveal the tightly integrated nature of the seminal fluid transcriptome and provide new insights into the quantitative genetic basis of seminal fluid investment and composition.

Dynamics fingerprints of active conformers of epidermal growth factor receptor kinase

Epidermal growth factor receptor (EGFR) is a prototypical cell-surface receptor that plays a key role in the regulation of cellular signaling, proliferation and differentiation. Mutations of its kinase domain have been associated with the development of a variety of cancers and, therefore, it has been the target of drug design. Single amino acid substitutions (SASs) in this domain have been proven to alter the equilibrium of pre-existing conformer populations. Despite the advances in structural descriptions of its so-called active and inactive conformations, the associated dynamics aspects that characterize them have not been thoroughly studied yet. As the dynamic behaviors and molecular motions of proteins are important for a complete understanding of their structure-function relationships we present a novel procedure, using (or based on) normal mode analysis, to identify the collective dynamics shared among different conformers in EGFR kinase. The method allows the comparison of patterns of low-frequency vibrational modes defining representative directions of motions. Our procedure is able to emphasize the main similarities and differences between the collective dynamics of different conformers. In the case of EGFR kinase, two representative directions of motions have been found as dynamics fingerprints of the active conformers. Protein motion along both directions reveals to have a significant impact on the cavity volume of the main pocket of the active site. Otherwise, the inactive conformers exhibit a more heterogeneous distribution of collective motions. © 2018 Wiley Periodicals, Inc.

The Contemporary Evolution of Fitness

The rate of evolution of population mean fitness informs how selection acting in contemporary populations can counteract environmental change and genetic degradation (mutation, gene flow, drift, recombination). This rate influences population increases (e.g., range expansion), population stability (e.g., cryptic eco-evolutionary dynamics), and population recovery (i.e., evolutionary rescue). We review approaches for estimating such rates, especially in wild populations. We then review empirical estimates derived from two approaches: mutation accumulation (MA) and additive genetic variance in fitness (IAw). MA studies inform how selection counters genetic degradation arising from deleterious mutations, typically generating estimates of <1% per generation. IAw studies provide an integrated prediction of proportional change per generation, nearly always generating estimates of <20% and, more typically, <10%. Overall, considerable, but not unlimited, evolutionary potential exists in populations facing detrimental environmental or genetic change. However, further studies with diverse methods and species are required for more robust and general insights.

Variation and Evolution of Function-Valued Traits

Function-valued traits—phenotypes whose expression depends on a continuous index (such as age, temperature, or space)—occur throughout biology and, like any trait, it is important to understand how they vary and evolve. Although methods for analyzing variation and evolution of function-valued traits are well developed, they have been underutilized by evolutionists, especially those who study natural populations. We seek to summarize advances in the study of function-valued traits and to make their analyses more approachable and accessible to biologists who could benefit greatly from their use. To that end, we explain how curve thinking benefits conceptual understanding and statistical analysis of functional data. We provide a detailed guide to the most flexible and statistically powerful methods and include worked examples (with R code) as supplemental material. We review ways to characterize variation in function-valued traits and analyze consequences for evolution, including constraint. We also discuss how selection on function-valued traits can be estimated and combined with estimates of heritable variation to project evolutionary dynamics.

Herbicide resistance costs: what are we actually measuring and why?

Despite the considerable research efforts invested over the years to measure the fitness costs of herbicide resistance, these have rarely been used to inform a predictive theory about the fate of resistance once the herbicide is discontinued. One reason for this may be the reductive focus on relative fitness of two genotypes as a single measure of differential performance. Although the extent of variation in relative fitness between resistant and susceptible plants has not been assessed consistently, we know enough about plant physiology and ecology not to reduce it to a single fixed value. Research must therefore consider carefully the relevance of the experimental environment, the life stage and the choice of metric when measuring fitness-related traits. The reason most often given for measuring the cost of resistance, prediction of the impacts of management options on population dynamics, cannot be addressed using arbitrary components of fitness or a fixed value of relative fitness. To inform management options, the measurement of traits that capture the relevant processes and the main causes of their variation are required. With an emphasis on the benefit of field experiments measured over multiple time points and seasons, we highlight examples of studies that have made significant advances in this direction. © 2017 Society of Chemical Industry.

Environmental Plasticity in the Intersexual Correlation and Sex Bias of Gene Expression

Intersexual genetic correlations are expected to constrain the evolution of sexual dimorphic traits, including the degree of sex-biased gene expression. Consistent with that expectation, studies in fruit flies and birds have reported that genes whose expression has a strong intersexual genetic correlation (rMF) show a lower level of sex-biased expression (SBE). However, it is known that both rMF and SBE can be affected by the environment. It is therefore unclear whether there is a consistent relationship between these 2 quantities across multiple environments. In this paper, we study this relationship in the African malaria mosquito Anopheles gambiae. We show that both rMF and SBE change between environments. The change in SBE across environments is significantly correlated with dN/dS: greater changes in SBE are associated with higher values of dN/dS. Furthermore, the relationship between rMF and SBE is sensitive to the environment. We conclude that this relationship is sufficiently plastic that environmental effects should be considered in future studies.

Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor, Hyla cinerea, and Dendropsophus ebraccatus. We recorded male calls and calculated standardized phenotypic variance-covariance (P) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition levels in H. versicolor. Our findings suggest new directions in animal communication research in which the complex relationships among the traits of multiple signals are a key consideration for understanding signal evolution.

Genetic constraints on adaptation: a theoretical primer for the genomics era

Genetic constraints are features of inheritance systems that slow or prohibit adaptation. Several population genetic mechanisms of constraint have received sustained attention within the field since they were first articulated in the early 20th century. This attention is now reflected in a rich, and still growing, theoretical literature on the genetic limits to adaptive change. In turn, empirical research on constraints has seen a rapid expansion over the last two decades in response to changing interests of evolutionary biologists, along with new technologies, expanding data sets, and creative analytical approaches that blend mathematical modeling with genomics. Indeed, one of the most notable and exciting features of recent progress in genetic constraints is the close connection between theoretical and empirical research. In this review, we discuss five major population genetic contexts of genetic constraint: genetic dominance, pleiotropy, fitness trade-offs between types of individuals of a population, sign epistasis, and genetic linkage between loci. For each, we outline historical antecedents of the theory, specific contexts where constraints manifest, and their quantitative consequences for adaptation. From each of these theoretical foundations, we discuss recent empirical approaches for identifying and characterizing genetic constraints, each grounded and motivated by this theory, and outline promising areas for future work.

How does mutation affect the distribution of phenotypes?

The potential for mutational processes to influence patterns of neutral or adaptive phenotypic evolution is not well understood. If mutations are directionally biased, shifting trait means in a particular direction, or if mutation generates more variance in some directions of multivariate trait space than others, mutation itself might be a source of bias in phenotypic evolution. Here, we use mutagenesis to investigate the affect of mutation on trait mean and (co)variances in zebrafish, Danio rerio. Mutation altered the relationship between age and both prolonged swimming speed and body shape. These observations suggest that mutational effects on ontogeny or aging have the potential to generate variance across the phenome. Mutations had a far greater effect in males than females, although whether this is a reflection of sex-specific ontogeny or aging remains to be determined. In males, mutations generated positive covariance between swimming speed, size, and body shape suggesting the potential for mutation to affect the evolutionary covariation of these traits. Overall, our observations suggest that mutation does not generate equal variance in all directions of phenotypic space or in each sex, and that pervasive variation in ontogeny or aging within a cohort could affect the variation available to evolution.