Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: a case study in Drosophila serrata.

Additive genetic variance, VA, is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g. increased close-relative inbreeding) can alter VA, but how they do so depends on the (typically unknown) gene action and allele frequencies across many loci. For example, VA 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 VA 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 VA, 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 VA, providing insight into historical selection and future evolutionary potential.

Maintenance of quantitative genetic variance in complex, multitrait phenotypes: the contribution of rare, large effect variants in 2 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.

Causes of variability in estimates of mutational variance from mutation accumulation experiments.

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.

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.

Loss of ecologically important genetic variation in late generation hybrids reveals links between adaptation and speciation.

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.

Uneven Distribution of Mutational Variance Across the Transcriptome of Drosophila serrata Revealed by High-Dimensional Analysis of Gene Expression.

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.

Environmentally induced development costs underlie fitness tradeoffs.

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.

Evolution of Genetic Variance during Adaptive Radiation.

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.

Mutational Pleiotropy and the Strength of Stabilizing Selection Within and Between Functional Modules of Gene Expression.

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.

Artificial Selection to Increase the Phenotypic Variance in gmax Fails.

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.

Sexual selection on spontaneous mutations strengthens the between-sex genetic correlation for fitness.

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.

Heritable Micro-environmental Variance Covaries with Fitness in an Outbred Population of Drosophila serrata.

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.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

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.

Genetic Compatibility Underlies Benefits of Mate Choice in an External Fertilizer.

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.

Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata.

How new mutations contribute to genetic variation is a key question in biology. Although the evolutionary fate of an allele is largely determined by its heterozygous effect, most estimates of mutational variance and mutational effects derive from highly inbred lines, where new mutations are present in homozygous form. In an attempt to overcome this limitation, middle-class neighborhood (MCN) experiments have been used to assess the fitness effect of new mutations in heterozygous form. However, because MCN populations harbor substantial standing genetic variance, estimates of mutational variance have not typically been available from such experiments. Here we employ a modification of the animal model to analyze data from 22 generations of Drosophila serrata bred in an MCN design. Mutational heritability, measured for eight cuticular hydrocarbons, 10 wing-shape traits, and wing size in this outbred genetic background, ranged from 0.0006 to 0.006 (with one exception), a similar range to that reported from studies employing inbred lines. Simultaneously partitioning the additive and mutational variance in the same outbred population allowed us to quantitatively test the ability of mutation-selection balance models to explain the observed levels of additive and mutational genetic variance. The Gaussian allelic approximation and house-of-cards models, which assume real stabilizing selection on single traits, both overestimated the genetic variance maintained at equilibrium, but the house-of-cards model was a closer fit to the data. This analytical approach has the potential to be broadly applied, expanding our understanding of the dynamics of genetic variance in natural populations.

Transcriptome-wide effects of sexual selection on the fate of new mutations.

Sexual selection on males is predicted to have widespread effects on genetic variation as a consequence of the pleiotropic allelic effects on sexual and nonsexual traits. We manipulated the opportunity for sexual selection on males during 27 generations of mutation accumulation in inbred lines of Drosophila serrata, and used a microarray platform to investigate the effect of sexual selection on the expression of 2689 genes. While gene expression signal was, on average, higher in the absence of sexual selection, this difference was small (0.1%). In contrast, sexual selection impacted substantially on the mutational variance in gene expression. Over all genes, mutational variance in gene expression was, on average, 42% higher when sexual selection operated than when it was absent. Our results indicate that sexual selection on males can generate widespread effects across the genome. An increase in mutational variance without a corresponding change in mean suggested that most expression traits were unlikely to be under direct sexual selection. Instead, the mutational variance in gene expression traits is consistent with divergence generated by widespread pleiotropic associations with traits affecting male mating success.

The phenome-wide distribution of genetic variance.

A general observation emerging from estimates of additive genetic variance in sets of functionally or developmentally related traits is that much of the genetic variance is restricted to few trait combinations as a consequence of genetic covariance among traits. While this biased distribution of genetic variance among functionally related traits is now well documented, how it translates to the broader phenome and therefore any trait combination under selection in a given environment is unknown. We show that 8,750 gene expression traits measured in adult male Drosophila serrata exhibit widespread genetic covariance among random sets of five traits, implying that pleiotropy is common. Ultimately, to understand the phenome-wide distribution of genetic variance, very large additive genetic variance-covariance matrices (G) are required to be estimated. We draw upon recent advances in matrix theory for completing high-dimensional matrices to estimate the 8,750-trait G and show that large numbers of gene expression traits genetically covary as a consequence of a single genetic factor. Using gene ontology term enrichment analysis, we show that the major axis of genetic variance among expression traits successfully identified genetic covariance among genes involved in multiple modes of transcriptional regulation. Our approach provides a practical empirical framework for the genetic analysis of high-dimensional phenome-wide trait sets and for the investigation of the extent of high-dimensional genetic constraint.

Dominance genetic variance for traits under directional selection in Drosophila serrata.

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected.

The distribution of genetic variance across phenotypic space and the response to selection.

The role of adaptation in biological invasions will depend on the availability of genetic variation for traits under selection in the new environment. Although genetic variation is present for most traits in most populations, selection is expected to act on combinations of traits, not individual traits in isolation. The distribution of genetic variance across trait combinations can be characterized by the empirical spectral distribution of the genetic variance-covariance (G) matrix. Empirical spectral distributions of G from a range of trait types and taxa all exhibit a characteristic shape; some trait combinations have large levels of genetic variance, while others have very little genetic variance. In this study, we review what is known about the empirical spectral distribution of G and show how it predicts the response to selection across phenotypic space. In particular, trait combinations that form a nearly null genetic subspace with little genetic variance respond only inconsistently to selection. We go on to set out a framework for understanding how the empirical spectral distribution of G may differ from the random expectations that have been developed under random matrix theory (RMT). Using a data set containing a large number of gene expression traits, we illustrate how hypotheses concerning the distribution of multivariate genetic variance can be tested using RMT methods. We suggest that the relative alignment between novel selection pressures during invasion and the nearly null genetic subspace is likely to be an important component of the success or failure of invasion, and for the likelihood of rapid adaptation in small populations in general.

The genetic covariance between life cycle stages separated by metamorphosis.

Metamorphosis is common in animals, yet the genetic associations between life cycle stages are poorly understood. Given the radical changes that occur at metamorphosis, selection may differ before and after metamorphosis, and the extent that genetic associations between pre- and post-metamorphic traits constrain evolutionary change is a subject of considerable interest. In some instances, metamorphosis may allow the genetic decoupling of life cycle stages, whereas in others, metamorphosis could allow complementary responses to selection across the life cycle. Using a diallel breeding design, we measured viability at four ontogenetic stages (embryo, larval, juvenile and adult viability), in the ascidian Ciona intestinalis and examined the orientation of additive genetic variation with respect to the metamorphic boundary. We found support for one eigenvector of G: (gobsmax ), which contrasted larval viability against embryo viability and juvenile viability. Target matrix rotation confirmed that while gobsmax shows genetic associations can extend beyond metamorphosis, there is still considerable scope for decoupled phenotypic evolution. Therefore, although genetic associations across metamorphosis could limit that range of phenotypes that are attainable, traits on either side of the metamorphic boundary are capable of some independent evolutionary change in response to the divergent conditions encountered during each life cycle stage.