Additive genetic variance, V A , is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g. increased close-relative inbreeding) can alter V A , but how they do so depends on the (typically unknown) gene action and allele frequencies across many loci. For example, V A increases proportionally with the inbreeding coefficient when allelic effects are additive, but smaller (or larger) increases can occur when allele frequencies are unequal at causal loci with dominance effects. Here, we describe an experimental approach to assess the potential for dominance effects to deflate V A under inbreeding. Applying a powerful paired pedigree design in Drosophila serrata , we measured 11 wing traits on half-sibling families bred via either random or sibling mating, differing only in homozygosity (not allele frequency). Despite close inbreeding and substantial power to detect small V A , we detected no deviation from the expected additive effect of inbreeding on genetic (co)variances. Our results suggest the average dominance coefficient is very small relative to the additive effect, or that allele frequencies are relatively equal at loci affecting wing traits. We outline the further opportunities for this paired pedigree approach to reveal the characteristics of V A , providing insight into historical selection and future evolutionary potential.

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.

Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardized estimates of this mutational variance, VM, span 2 orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using 2 approaches. First, meta-analyses of ∼150 estimates of standardized VM from 37 mutation accumulation studies did not support a difference among taxa (which differ in mutation rate) but provided equivocal support for differences among trait types (life history vs morphology, predicted to differ in mutation rate). Notably, several experimental factors were confounded with taxon and trait, and further empirical data are required to resolve their influences. Second, we analyzed morphological data from an experiment in Drosophila serrata to determine the potential for unintentional heterogeneity among environments in which phenotypes were measured (i.e. among laboratories or time points) or transient segregation of mutations within mutation accumulation lines to affect standardized VM. Approximating the size of an average mutation accumulation experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardized VM. This heterogeneity was (partially) attributable to unintended environmental variation or within line segregation of mutations only for wing size, not wing shape traits. We conclude that sampling error contributed substantial variation within this experiment, and infer that it will also contribute substantially to differences among published estimates. We suggest a logistically permissive approach to improve the precision of estimates, and consequently our understanding of the dynamics of mutational variance of quantitative traits.

This R code specifies parameters for input into model but requires an R package to be installed (code included for this).

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.

The files contained herein include BSFG output containing posterior samples for parameters of interest, and R code and other input files used to generate the main manipulations of the data and output presented in the corresponding manuscript.

Each file contains a 60x3385 data matrix of log10 expression measurements, scaled to unit variance within traits.NOTE: This dataset has been superseded by a more up to date version. View the current version here: https://doi.org/10.48610/a3c5652

Adaptation to contrasting environments occurs when advantageous alleles accumulate in each population, but it remains largely unknown whether these same advantageous alleles create genetic incompatibilities that can cause intrinsic reproductive isolation leading to speciation. Identifying alleles that underlie both adaptation and reproductive isolation is further complicated by factors such as dominance and genetic interactions among loci, which can affect both processes differently and obscure potential links between adaptation and speciation. Here, we use a combination of field and glasshouse experiments to explore the connection between adaptation and speciation while accounting for dominance and genetic interactions. We created a hybrid population with equal contributions from four contrasting ecotypes of Senecio lautus (Asteraceae), which produced hybrid genomes both before (F1 hybrid generation) and after (F4 hybrid generation) recombination among the parental ecotypes. In the glasshouse, plants in the second generation (F2 hybrid generation) showed reduced fitness as a loss of fertility. However, fertility was recovered in subsequent generations, suggesting that genetic variation underlying the fitness reduction was lost in subsequent generations. To quantify the effects of losing genetic variation at the F2 generation on the fitness of later generation hybrids, we used a reciprocal transplant to test for fitness differences between parental ecotypes, and F1 and F4 hybrids in all four parental habitats. Compared to the parental ecotypes and F1 hybrids, variance in F4 hybrid fitness was lower, and lowest in habitats that showed stronger native-ecotype advantage, suggesting that stronger natural selection for the native ecotype reduced fitness variation in the F4 hybrids. Fitness trade-offs that were present in the parental ecotypes and F1 hybrids were absent in the F4 hybrid. Together, these results suggest that the genetic variation lost after the F2 generation was likely associated with both adaptation and intrinsic reproductive isolation among ecotypes from contrasting habitats.

Testing whether local adaptation and intrinsic reproductive isolation share a genetic basis can reveal important connections between adaptation and speciation. Local adaptation arises as advantageous alleles spread through a population, but whether these same advantageous alleles fail on the genetic backgrounds of other populations remains largely unknown. We used a quantitative genetic breeding design to produce a late generation (F4) recombinant hybrid population by equally mating amongst four contrasting ecotypes of a native Australian daisy for four generations. We tracked fitness across generations and measured morphological traits in the glasshouse, and used a reciprocal transplant to quantify fitness in all four parental habitats. In the glasshouse, plants in the second generation showed a reduction in fitness as a loss of fertility, but this was fully recovered in the following generation. The F4 hybrid lacked extreme phenotypes present in the parental ecotypes, suggesting that genes reducing hybrid fitness were linked to traits specific to each ecotype. In the natural habitats, additive genetic variance for fitness was greatest for habitats that showed stronger native-ecotype advantage, suggesting that a loss of genetic variation present in the parental ecotypes were adaptive in the natural habitats. Reductions in genetic variance for fitness were associated with a loss of ecological trade-offs previously described in the parental ecotypes. Furthermore, natural selection on morphological traits differed amongst the parental habitats, but was not predicted to occur towards the morphology of the parental ecotypes. Together, these results suggest that intrinsic reproductive isolation removed adaptive genetic variation present in the parental ecotypes. The evolution of these distinct ecotypes was likely governed by genetic variation that resulted in both ecological trade-offs and intrinsic reproductive isolation among populations adapted to contrasting environments.

Genetic variation in resident species can influence the assembly and dynamics of communities, but the potential for these genetic effects to persist across generations is largely unresolved. In principle, persistent, directional changes in communities are only predicted when community properties covary genetically with the fitness of resident species. Estimates of genetic covariance between the fitness of a resident species and its community are therefore necessary to "close the eco-evolutionary loop" in studies of community genetics, but such estimates are rare. Emulating community genetics experiments in plants, we used clonal replicates of 21 genotypes of a resident species (the encrusting bryozoan, Hippopodina) to investigate the magnitude of genotypic variance contributing to assembly of a marine benthic community. Genotypes explained up to 35% of variation in community assembly. Critically, the performance of Hippopodina genotypes covaried both with the evenness of communities and with the abundances of some individual species, representing an indirect genetic effect that creates the potential for multigenerational interactions between Hippopodina and co-existing species. Our results suggest that different genotypes will associate with different community members consistently across generations, and such non-random associations can give rise to specialization. Further interactions between species other than Hippopodina itself may also be altered by effects of genetic variation in the focal species. Furthermore, species in the community other than Hippopodina itself will interact more commonly in the presence of some genotypes over others. Our results support the potential for genetic variation in one species to have deterministic effects on the dynamics of ecological communities.

There are essentially an infinite number of traits that could be measured on any organism, and almost all individual traits display genetic variation, yet substantial genetic variance in a large number of independent traits is not plausible under basic models of selection and mutation. One mechanism that may be invoked to explain the observed levels of genetic variance in individual traits is that pleiotropy results in fewer dimensions of phenotypic space with substantial genetic variance. Multivariate genetic analyses of small sets of functionally related traits have shown that standing genetic variance is often concentrated in relatively few dimensions. It is unknown if a similar concentration of genetic variance occurs at a phenome-wide scale when many traits of disparate function are considered, or if the genetic variance generated by new mutations is also unevenly distributed across phenotypic space. Here, we used a Bayesian sparse factor model to characterize the distribution of mutational variance of 3385 gene expression traits of Drosophila serrata after 27 generations of mutation accumulation, and found that 46% of the estimated mutational variance was concentrated in just 21 dimensions with significant mutational heritability. We show that the extent of concentration of mutational variance into such a small subspace has the potential to substantially bias the response to selection of these traits.

Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.

Variational modules, sets of pleiotropically covarying traits, affect phenotypic evolution, and therefore are predicted to reflect functional modules, such that traits within a variational module also share a common function. Such an alignment of function and pleiotropy is expected to facilitate adaptation by reducing the deleterious effects of mutations, and by allowing coordinated evolution of functionally related sets of traits. Here, we adopt a high-dimensional quantitative genetic approach using a large number of gene expression traits in Drosophila serrata to test whether functional grouping, defined by gene ontology (GO terms), predicts variational modules. Mutational or standing genetic covariance was significantly greater than among randomly grouped sets of genes for 38% of our functional groups, indicating that GO terms can predict variational modularity to some extent. We estimated stabilizing selection acting on mutational covariance to test the prediction that functional pleiotropy would result in reduced deleterious effects of mutations within functional modules. Stabilizing selection within functional modules was weaker than that acting on randomly grouped sets of genes in only 23% of functional groups, indicating that functional alignment can reduce deleterious effects of pleiotropic mutation but typically does not. Our analyses also revealed the presence of variational modules that spanned multiple functions.

Local adaptation can lead to genotype-by-environment interactions, which can create fitness tradeoffs in alternative environments, and govern the distribution of biodiversity across geographic landscapes. Exploring the ecological circumstances that promote the evolution of fitness tradeoffs requires identifying how natural selection operates and during which ontogenetic stages natural selection is strongest. When organisms disperse to areas outside their natural range, tradeoffs might emerge when organisms struggle to reach key life history stages, or alternatively, die shortly after reaching life history stages if there are greater risks of mortality associated with costs to developing in novel environments. We used multiple populations from four ecotypes of an Australian native wildflower (Senecio pinnatifolius) in reciprocal transplants to explore how fitness tradeoffs arise across ontogeny. We then assessed whether the survival probability for plants from native and foreign populations was contingent on reaching key developmental stages. We found that fitness tradeoffs emerged as ontogeny progressed when native plants were more successful than foreign plants at reaching seedling establishment and maturity. Native and foreign plants that failed to reach seedling establishment died at the same rate, but plants from foreign populations died quicker than native plants after reaching seedling establishment, and died quicker regardless of whether they reached sexual maturity or not. Development rates were similar for native and foreign populations, but changed depending on the environment. Together, our results suggest that natural selection for environment-specific traits early in life history created tradeoffs between contrasting environments. Plants from foreign populations were either unable to develop to seedling establishment, or they suffered increased mortality as a consequence of reaching seedling establishment. The observation of tradeoffs together with environmentally dependent changes in development rate suggest that foreign environments induce organisms to develop at a rate different from their native habitat, incurring consequences for lifetime fitness and population divergence.

The genetic basis of stochastic variation within a defined environment, and the consequences of such micro-environmental variance for fitness are poorly understood. Using a multigenerational breeding design in Drosophila serrata, we demonstrated that the micro-environmental variance in a set of morphological wing traits in a randomly mating population had significant additive genetic variance in most single wing traits. Although heritability was generally low (<1%), coefficients of additive genetic variance were of a magnitude typical of other morphological traits, indicating that the micro-environmental variance is an evolvable trait. Multivariate analyses demonstrated that the micro-environmental variance in wings was genetically correlated among single traits, indicating that common mechanisms of environmental buffering exist for this functionally related set of traits. In addition, through the dominance genetic covariance between the major axes of micro-environmental variance and fitness, we demonstrated that micro-environmental variance shares a genetic basis with fitness, and that the pattern of selection is suggestive of variance-reducing selection acting on micro-environmental variance.

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy–Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix.

A proposed benefit to sexual selection is that it promotes purging of deleterious mutations from populations. For this benefit to be realized, sexual selection, which is usually stronger on males, must purge mutations deleterious to both sexes. Here, we experimentally test the hypothesis that sexual selection on males purges deleterious mutations that affect both male and female fitness. We measured male and female fitness in two panels of spontaneous mutation-accumulation lines of the fly, Drosophila serrata, each established from a common ancestor. One panel of mutation accumulation lines limited both natural and sexual selection (LS lines), whereas the other panel limited natural selection, but allowed sexual selection to operate (SS lines). Although mutation accumulation caused a significant reduction in male and female fitness in both the LS and SS lines, sexual selection had no detectable effect on the extent of the fitness reduction. Similarly, despite evidence of mutational variance for fitness in males and females of both treatments, sexual selection had no significant impact on the amount of mutational genetic variance for fitness. However, sexual selection did reshape the between-sex correlation for fitness: significantly strengthening it in the SS lines. After 25 generations, the between-sex correlation for fitness was positive but considerably less than one in the LS lines, suggesting that, although most mutations had sexually concordant fitness effects, sex-limited, and/or sex-biased mutations contributed substantially to the mutational variance. In the SS lines this correlation was strong and could not be distinguished from unity. Individual-based simulations that mimick the experimental setup reveal two conditions that may drive our results: (1) a modest-to-large fraction of mutations have sex-limited (or highly sex-biased) fitness effects, and (2) the average fitness effect of sex-limited mutations is larger than the average fitness effect of mutations that affect both sexes similarly.

Stabilizing selection is important in evolutionary theories of the maintenance of genetic variance and has been invoked as the key process determining macroevolutionary patterns of trait evolution. However, manipulative evidence for the extent of stabilizing selection, particularly on multivariate traits, is lacking. We used artificial disruptive selection in Drosophila serrata as a tool to determine the relative strength of stabilizing selection experienced by multivariate trait combinations with contrasting levels of genetic and mutational variance. Contrary to expectation, when disruptive selection was applied to the major axis of standing genetic variance, gmax, we observed a significant and repeatable decrease in its phenotypic variance. In contrast, the multivariate trait combination predicted to be under strong stabilizing selection showed a significant and repeatable increase in its phenotypic variance. Correlated responses were observed in all selection treatments, and viability selection operating on extreme phenotypes of traits genetically correlated with those directly selected on limited our ability to increase their phenotypic range. Our manipulation revealed that multivariate trait combinations were subject to stabilizing selection; however, we did not observe a direct relationship between the strength of stabilizing selection and the levels of standing genetic variance in multivariate trait combinations. Contrasting patterns of allele frequencies underlying traits with high versus low levels of standing genetic variance may be implicated in determining the response to artificial selection in multivariate trait combinations.

In accordance with the consensus that sexual selection is responsible for the rapid evolution of display traits on macroevolutionary scales, microevolutionary studies suggest sexual selection is a widespread and often strong form of directional selection in nature. However, empirical evidence for the contemporary evolution of sexually selected traits via sexual rather than natural selection remains weak. In this study, we used a novel application of quantitative genetic breeding designs to test for a genetic response to sexual selection on eight chemical display traits from a field population of the fly, Drosophila serrata. Using our quantitative genetic approach, we were able to detect a genetically based difference in means between groups of males descended from fathers who had either successfully sired offspring or were randomly collected from the same wild population for one of these display traits, the diene (Z,Z)-5,9-C-27 : 2. Our experimental results, in combination with previous laboratory studies on this system, suggest that both natural and sexual selection may be influencing the evolutionary trajectories of these traits in nature, limiting the capacity for a contemporary evolutionary response.

Mate choice is a common feature of sexually reproducing species. In sessile or sedentary external fertilizers, however, direct interactions between reproductive partners are minimal, and instead mate recognition and choice must occur at the level of gametes. It is common for some sperm and egg combinations to have higher fertilization success than others, but it remains unclear whether differences in fertilization reflect gamete-level mate choice (GMC) for paternal quality or parental compatibility. Here, we examine the mechanisms underlying GMC in an externally fertilizing ascidian. A manipulative mate-choice assay confirmed that offspring viability was greater in clutches where we allowed GMC than in clutches where we precluded GMC. A complementary quantitative genetic experiment then revealed that paternal quality effects were generally weaker than parental compatibility effects, particularly for the trait combination underlying the benefits of GMC. Overall, our data suggest that gametes that are more compatible at fertilization produce more viable offspring than gametes that are less compatible at fertilization. Therefore, although the regalia we typically associate with sexual selection are absent in external fertilizers, mechanisms that allow females to bias fertilization in favor of some males over others produce significant fitness benefits in organisms reproducing via the ancestral strategy.