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.

The Contribution of Mutation to Variation in Temperature-Dependent Sprint Speed in Zebrafish, Danio rerio.

AbstractThe contribution of new mutations to phenotypic variation and the consequences of this variation for individual fitness are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males and measured sprint speed in their sons at six temperatures (between 16°C and 34°C). Heterozygous mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). These results suggest pleiotropic effects on speed across different temperatures; however, spurious correlations arise via linkage or heterogeneity in mutation number when mutations have consistent directional effects on each trait. Here, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects that underpin thermal adaptation. We discuss several aspects of experimental design that may affect resolution of mutations with nonsynergistic effects.

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.

Moving beyond heritability in the search for coral adaptive potential.

Global environmental change is happening at unprecedented rates. Coral reefs are among the ecosystems most threatened by global change. For wild populations to persist, they must adapt. Knowledge shortfalls about corals' complex ecological and evolutionary dynamics, however, stymie predictions about potential adaptation to future conditions. Here, we review adaptation through the lens of quantitative genetics. We argue that coral adaptation studies can benefit greatly from "wild" quantitative genetic methods, where traits are studied in wild populations undergoing natural selection, genomic relationship matrices can replace breeding experiments, and analyses can be extended to examine genetic constraints among traits. In addition, individuals with advantageous genotypes for anticipated future conditions can be identified. Finally, genomic genotyping supports simultaneous consideration of how genetic diversity is arrayed across geographic and environmental distances, providing greater context for predictions of phenotypic evolution at a metapopulation scale.

Genetic and phenotypic variation exhibit both predictable and stochastic patterns across an intertidal fish metapopulation.

Interactions among selection, gene flow, and drift affect the trajectory of adaptive evolution. In natural populations, the direction and magnitude of these processes can be variable across different spatial, temporal, or ontogenetic scales. Consequently, variability in evolutionary processes affects the predictability or stochasticity of microevolutionary outcomes. We studied an intertidal fish, Bathygobius cocosensis (Bleeker, 1854), to understand how space, time, and life stage structure genetic and phenotypic variation in a species with potentially extensive dispersal and a complex life cycle (larval dispersal preceding benthic recruitment). We sampled juvenile and adult life stages, at three sites, over three years. Genome-wide SNPs uncovered a pattern of chaotic genetic patchiness, that is, weak-but-significant patchy spatial genetic structure that was variable through time and between life stages. Outlier locus analyses suggested that targets of spatially divergent selection were mostly temporally variable, though a significant number of spatial outlier loci were shared between life stages. Head shape, a putatively ecologically responsive (adaptive) phenotype in B. cocosensis also exhibited high temporal variability within sites. However, consistent spatial relationships between sites indicated that environmental similarities among sites may generate predictable phenotype distributions across space. Our study highlights the complex microevolutionary dynamics of marine systems, where consideration of multiple ecological dimensions can reveal both predictable and stochastic patterns in the distributions of genetic and phenotypic variation. Such considerations probably apply to species that possess short, complex life cycles, have large dispersal potential and fecundities, and that inhabit heterogeneous environments.

Skeletal deformities and meristic trait variations are common in the intertidal fish Bathygobius cocosensis (Perciformes-Gobiidae).

Extreme environmental conditions, such as temperature, can lead to meristic trait variation and skeletal deformities, which may have major impacts on individual fitness. As intertidal ecosystems experience rapid temperature and physicochemical fluctuations, intertidal fish living and reproducing in these environmental conditions may have phenotypes influenced by such variable environments. The impact of intertidal variability on fish development, however, has not been previously investigated. Skeletal deformities and meristic traits were assessed for Bathygobius cocosensis, a common intertidal fish living across the Indo-Pacific region, using a clearing and staining method on 72 individuals. Over 87% of individuals presented meristic variation and over 70% exhibited at least one type of skeletal deformity, mostly recorded in the caudal fin area. The unexpected prevalence of skeletal deformities among this intertidal fish population suggests that such deformities may be suitable markers to evaluate an individual's stress exposure during development and the subsequent fitness effects.

Larval traits show temporally consistent constraints, but are decoupled from postsettlement juvenile growth, in an intertidal fish.

Complex life cycles may evolve to dissociate distinct developmental phases in an organism's lifetime. However, genetic or environmental factors may restrict trait independence across life stages, constraining ontogenetic trajectories. Quantifying covariance across life stages and their temporal variability is fundamental in understanding life-history phenotypes and potential distributions and consequences for selection. We studied developmental constraints in an intertidal fish (Bathygobius cocosensis: Gobiidae) with a discrete pelagic larval phase and benthic juvenile phase. We tested whether traits occurring earlier in life affected those expressed later, and whether larval traits were decoupled from postsettlement juvenile traits. Sampling distinct cohorts from three annual breeding seasons afforded tests of temporally variability in trait covariance. From otoliths (fish ear stones), we measured hatch size, larval duration, pelagic growth (larval traits) and early postsettlement growth (juvenile trait) in 124 juvenile B. cocoensis. We used path analyses to model trait relationships with respect to their chronological expression, comparing models among seasons. We also modelled the effect of season and hatch date on each individual trait to quantify their inherent variability. Our path analyses demonstrated a decoupling of larval traits on juvenile growth. Within the larval phase, longer larval durations resulted in greater pelagic growth, and larger size-at-settlement. There was also evidence that larger hatch size might reduce larval durations, but this effect was only marginally significant. Although pelagic and postsettlement growth were decoupled, pelagic growth had postsettlement consequences: individuals with high pelagic growth were among the largest fish at settlement, and remained among the largest early postsettlement. We observed no evidence that trait relationships varied among breeding seasons, but larval duration differed among breeding seasons, and was shorter for larvae hatching later within each season. Overall, we demonstrate mixed support for the expectation that traits in different life stages are independent. While postsettlement growth was decoupled from larval traits, pelagic development had consequences for the size of newly settled juveniles. Temporal consistency in trait covariances implies that genetic and/or environmental factors influencing them were stable over our three-year study. Our work highlights the importance of individual developmental experiences and temporal variability in understanding population distributions of life-history traits.

Repeatability of locomotor performance and morphology-locomotor performance relationships.

There is good evidence that natural selection drives the evolution of locomotor performance, but the processes that generate the among-individual variation for selection to act on are relatively poorly understood. We measured prolonged swimming performance, Ucrit, and morphology in a large cohort (n=461) of wild-type zebrafish (Danio rerio) at ∼6 months and again at ∼9 months. Using mixed-model analyses to estimate repeatability as the intraclass correlation coefficient, we determined that Ucrit was significantly repeatable (r=0.55; 95% CI: 0.45-0.64). Performance differences between the sexes (males 12% faster than females) and changes with age (decreasing 0.07% per day) both contributed to variation in Ucrit and, therefore, the repeatability estimate. Accounting for mean differences between sexes within the model decreased the estimate of Ucrit repeatability to 21% below the naïve estimate, while fitting age in the models increased the estimate to 14% above the naïve estimate. Greater consideration of factors such as age and sex is therefore necessary for the interpretation of performance repeatability in wild populations. Body shape significantly predicted Ucrit in both sexes in both assays, with the morphology-performance relationship significantly repeatable at the population level. However, morphology was more strongly predicative of performance in older fish, suggesting a change in the contribution of morphology relative to other factors such as physiology and behaviour. The morphology-performance relationship changed with age to a greater extent in males than females.

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.

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.

Evolutionary constraints in high-dimensional trait sets.

Genetic variation for individual traits is typically abundant, but for some multivariate combinations it is very low, suggesting that evolutionary limits might be generated by the geometric distribution of genetic variance. To test this prediction, we artificially selected along all eight genetic eigenvectors of a set of eight quantitative traits in Drosophila serrata. After six generations of 50% truncation selection, at least one replicate population of all treatments responded to selection, allowing us to reject a null genetic subspace as a cause of evolutionary constraint in this system. However, while all three replicate populations of the first five selection treatments displayed a significant response, the remaining three, characterized by low genetic variance in their selection indexes in the base population, displayed inconsistent responses to selection. The observation that only four of the nine replicate populations evolved in response to the direct selection applied to them in these low genetic variance treatments, led us to conclude that a nearly null subspace did limit evolution. Dimensions associated with low genetic variance are often found in multivariate analyses of standing genetic variance in morphological traits, suggesting that the nearly null genetic subspace may be a common mechanism of evolutionary constraint in nature.

Natural selection stops the evolution of male attractiveness.

Sexual selection in natural populations acts on highly heritable traits and tends to be relatively strong, implicating sexual selection as a causal agent in many phenotypic radiations. Sexual selection appears to be ineffectual in promoting phenotypic divergence among contemporary natural populations, however, and there is little evidence from artificial selection experiments that sexual fitness can evolve. Here, we demonstrate that a multivariate male trait preferred by Drosophila serrata females can respond to selection and results in the maintenance of male mating success. The response to selection was associated with a gene of major effect increasing in frequency from 12 to 35% in seven generations. No further response to selection, or increase in frequency of the major gene, was observed between generations 7 and 11, indicating an evolutionary limit had been reached. Genetic analyses excluded both depletion of genetic variation and overdominance as causes of the evolutionary limit. Relaxing artificial selection resulted in the loss of 52% of the selection response after a further five generations, demonstrating that the response under artificial sexual selection was opposed by antagonistic natural selection. We conclude that male D. serrata sexually selected traits, and attractiveness to D. serrata females conferred by these traits, were held at an evolutionary limit by the lack of genetic variation that would allow an increase in sexual fitness while simultaneously maintaining nonsexual fitness. Our results suggest that sexual selection is unlikely to cause divergence among natural populations without a concomitant change in natural selection, a conclusion consistent with observational evidence from natural populations.

Effects of spontaneous mutations on survival and reproduction of Drosophila serrata infected with Drosophila C virus.

The impact of selection on host immune function genes has been widely documented. However, it remains essentially unknown how mutation influences the quantitative immune traits that selection acts on. Applying a classical mutation accumulation (MA) experimental design in Drosophila serrata, we found the mutational variation in susceptibility (median time of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to that reported for intrinsic survival traits. Mean LT50 did not change as mutations accumulated, suggesting no directional bias in mutational effects. Maintenance of genetic variance in immune function is hypothesised to be influenced by pleiotropic effects on immunity and other traits that contribute to fitness. To investigate this, we assayed female reproductive output for a subset of MA lines with relatively long or short survival times under DCV infection. Longer survival time tended to be associated with lower reproductive output, suggesting that mutations affecting susceptibility to DCV had pleiotropic effects on investment in reproductive fitness. Further studies are needed to uncover the general patterns of mutational effect on immune responses and other fitness traits, and to determine how selection might typically act on new mutations via their direct and pleiotropic effects.

Predicting the future.

Experiments on worms suggest that a statistical measure called the G matrix can accurately predict how phenotypes will adapt to a novel environment over multiple generations.

Environmental dependence of mutational (co)variances of adaptive traits.

Standing genetic variation, and capacity to adapt to environment change, will ultimately depend on the fitness effects of mutations across the range of environments experienced by contemporary, panmictic, populations. We investigated how mild perturbations in diet and temperature affect mutational (co)variances of traits that evolve under climatic adaptation, and contribute to individual fitness in Drosophila serrata. We assessed egg-to-adult viability, development time and wing size of 64 lines that had diverged from one another via spontaneous mutation over 30 generations of brother-sister mating. Our results suggested most mutations have directionally concordant (i.e., synergistic) effects in all environments and both sexes. However, elevated mutational variance under reduced macronutrient conditions suggested environment-dependent variation in mutational effect sizes for development time. We also observed evidence for antagonistic effects under standard versus reduced macronutrient conditions, where these effects were further contingent on temperature (for development time) or sex (for size). Diet also influenced the magnitude and sign of mutational correlations between traits, although this result was largely due to a single genotype (line), which may reflect a rare, large effect mutation. Overall, our results suggest environmental heterogeneity and environment-dependency of mutational effects could contribute to the maintenance of genetic variance.

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.

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.

How is epigenetics predicted to contribute to climate change adaptation? What evidence do we need?

Transgenerational effects that are interpreted in terms of epigenetics have become an important research focus at a time when rapid environmental changes are occurring. These effects are usually interpreted as enhancing fitness extremely rapidly, without depending on the slower process of natural selection changing DNA-encoded (fixed) genetic variants in populations. Supporting evidence comes from a variety of sources, including environmental associations with epialleles, cross-generation responses of clonal material exposed to different environmental conditions, and altered patterns of methylation or frequency changes in epialleles across time. Transgenerational environmental effects have been postulated to be larger than those associated with DNA-encoded genetic changes, based on (for instance) stronger associations between epialleles and environmental conditions. Yet environmental associations for fixed genetic differences may always be weak under polygenic models where multiple combinations of alleles can lead to the same evolutionary outcome. The ultimate currency of adaptation is fitness, and few transgenerational studies have robustly determined fitness effects, particularly when compared to fixed genetic variants. Not all transgenerational modifications triggered by climate change will increase fitness: stressful conditions often trigger negative fitness effects across generations that can eliminate benefits. Epigenetic responses and other transgenerational effects will undoubtedly play a role in climate change adaptation, but further, well-designed, studies are required to test their importance relative to DNA-encoded changes. This article is part of the theme issue 'How does epigenetics influence the course of evolution?'

Correlational selection in the age of genomics.

Ecologists and evolutionary biologists are well aware that natural and sexual selection do not operate on traits in isolation, but instead act on combinations of traits. This long-recognized and pervasive phenomenon is known as multivariate selection, or-in the particular case where it favours correlations between interacting traits-correlational selection. Despite broad acknowledgement of correlational selection, the relevant theory has often been overlooked in genomic research. Here, we discuss theory and empirical findings from ecological, quantitative genetic and genomic research, linking key insights from different fields. Correlational selection can operate on both discrete trait combinations and quantitative characters, with profound implications for genomic architecture, linkage, pleiotropy, evolvability, modularity, phenotypic integration and phenotypic plasticity. We synthesize current knowledge and discuss promising research approaches that will enable us to understand how correlational selection shapes genomic architecture, thereby linking quantitative genetic approaches with emerging genomic methods. We suggest that research on correlational selection has great potential to integrate multiple fields in evolutionary biology, including developmental and functional biology, ecology, quantitative genetics, phenotypic polymorphisms, hybrid zones and speciation processes.

The depletion of genetic variance by sexual selection.

Sexually selected traits display substantial genetic variance [1, 2], in conflict with the expectation that sexual selection will deplete it [3-5]. Condition dependence is thought to resolve this paradox [5-7], but experimental tests that relate the direction of sexual selection to the availability of genetic variance are lacking. Here, we show that condition-dependent expression is not sufficient to maintain genetic variance available to sexual selection in multiple male sexually selected traits. We employed an experimental design that simultaneously determined the quantitative genetic basis of nine male cuticular hydrocarbons (CHCs) of Drosophila bunnanda, the extent of condition dependence of these traits, and the strength and direction of sexual selection acting upon them. The CHCs of D. bunnanda are condition dependent, with 18% of the genetic variance in male body size explained by genetic variance in CHCs. Despite the presence of genetic variance in individual male traits, 98% of the genetic variance in CHCs was found to be orientated more than 88 degrees away from the direction of sexual selection and therefore unavailable to selection. A lack of genetic variance in male traits in the direction of sexual selection may represent a general feature of sexually selected systems, even in the presence of condition-dependent trait expression.