Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.     

Heterogeneity of genetic architecture of body size traits in a free‐living population

Knowledge of the underlying genetic architecture of quantitative traits could aid in understanding how they evolve. In wild populations, it is still largely unknown whether complex traits are polygenic or influenced by few loci with major effect, due to often small sample sizes and low resolution of marker panels. Here, we examine the genetic architecture of five adult body size traits in a free‐living population of Soay sheep on St Kilda using 37 037 polymorphic SNPs. Two traits (jaw and weight) show classical signs of a polygenic trait: the proportion of variance explained by a chromosome was proportional to its length, multiple chromosomes and genomic regions explained significant amounts of phenotypic variance, but no SNPs were associated with trait variance when using GWAS. In comparison, genetic variance for leg length traits (foreleg, hindleg and metacarpal) was disproportionately explained by two SNPs on chromosomes 16 (s23172.1) and 19 (s74894.1), which each explained >10% of the additive genetic variance. After controlling for environmental differences, females heterozygous for s74894.1 produced more lambs and recruits during their lifetime than females homozygous for the common allele conferring long legs. We also demonstrate that alleles conferring shorter legs have likely entered the population through a historic admixture event with the Dunface sheep. In summary, we show that different proxies for body size can have very different genetic architecture and that dense SNP helps in understanding both the mode of selection and the evolutionary history at loci underlying quantitative traits in natural populations.     

Heritability and evolvability of fitness and nonfitness traits: Lessons from livestock

Data from natural populations have suggested a disconnection between trait heritability (variance standardized additive genetic variance, V_A) and evolvability (mean standardized V_A) and emphasized the importance of environmental variation as a determinant of trait heritability but not evolvability. However, these inferences are based on heterogeneous and often small datasets across species from different environments. We surveyed the relationship between evolvability and heritability in >100 traits in farmed cattle, taking advantage of large sample sizes and consistent genetic approaches. Heritability and evolvability estimates were positively correlated (r = 0.37/0.54 on untransformed/log scales) reflecting a substantial impact of V_A on both measures. Furthermore, heritabilities and residual variances were uncorrelated. The differences between this and previously described patterns may reflect lower environmental variation experienced in farmed systems, but also low and heterogeneous quality of data from natural populations. Similar to studies on wild populations, heritabilities for life‐history and behavioral traits were lower than for other traits. Traits having extremely low heritabilities and evolvabilities (17% of the studied traits) were almost exclusively life‐history or behavioral traits, suggesting that evolutionary constraints stemming from lack of genetic variability are likely to be most common for classical “fitness” (cf. life‐history) rather than for “nonfitness” (cf. morphological) traits.     

Age and sex affect quantitative genetic parameters for dominance rank and aggression in free‐living greylag geese

Knowledge of the genetic and environmental influences on a character is pivotal for understanding evolutionary changes in quantitative traits in natural populations. Dominance and aggression are ubiquitous traits that are selectively advantageous in many animal societies and have the potential to impact the evolutionary trajectory of animal populations. Here we provide age‐ and sex‐specific estimates of additive genetic and environmental components of variance for dominance rank and aggression rate in a free‐living, human‐habituated bird population subject to natural selection. We use a long‐term data set on individually marked greylag geese (Anser anser) and show that phenotypic variation in dominance‐related behaviours contains significant additive genetic variance, parental effects and permanent environment effects. The relative importance of these variance components varied between age and sex classes, whereby the most pronounced differences concerned nongenetic components. In particular, parental effects were larger in juveniles of both sexes than in adults. In paired adults, the partner's identity had a larger influence on male dominance rank and aggression rate than in females. In sex‐ and age‐specific estimates, heritabilities did not differ significantly between age and sex classes. Adult dominance rank was only weakly genetically correlated between the sexes, leading to considerably higher heritabilities in sex‐specific estimates than across sexes. We discuss these patterns in relation to selection acting on dominance rank and aggression in different life history stages and sexes and suggest that different adaptive optima could be a mechanism for maintaining genetic variation in dominance‐related traits in free‐living animal populations.     

Association mapping of morphological traits in wild and captive zebra finches: reliable within,but not between populations

Identifying causal genetic variants underlying heritable phenotypic variation is a long‐standing goal in evolutionary genetics. We previously identified several quantitative trait loci (QTL) for five morphological traits in a captive population of zebra finches (Taeniopygia guttata) by whole‐genome linkage mapping. We here follow up on these studies with the aim to narrow down on the quantitative trait variants (QTN) in one wild and three captive populations. First, we performed an association study using 672 single nucleotide polymorphisms (SNPs) within candidate genes located in the previously identified QTL regions in a sample of 939 wild‐caught zebra finches. Then, we validated the most promising SNP–phenotype associations (n = 25 SNPs) in 5228 birds from four populations. Genotype–phenotype associations were generally weak in the wild population, where linkage disequilibrium (LD) spans only short genomic distances. In contrast, in captive populations, where LD blocks are large, apparent SNP effects on morphological traits (i.e. associations) were highly repeatable with independent data from the same population. Most of those SNPs also showed significant associations with the same trait in other captive populations, but the direction and magnitude of these effects varied among populations. This suggests that the tested SNPs are not the causal QTN but rather physically linked to them, and that LD between SNPs and causal variants differs between populations due to founder effects. While the identification of QTN remains challenging in nonmodel organisms, we illustrate that it is indeed possible to confirm the location and magnitude of QTL in a population with stable linkage between markers and causal variants.     

Novel genetic capacitors and potentiators for the natural genetic variation of sensory bristles and their trait specificity in Drosophila melanogaster

Cryptic genetic variation (CGV) is defined as the genetic variation that has little effect on phenotypic variation under a normal condition, but contributes to heritable variation under environmental or genetic perturbations. Genetic buffering systems that suppress the expression of CGV and store it in a population are called genetic capacitors, and the opposite systems are called genetic potentiators. One of the best‐known candidates for a genetic capacitor and potentiator is the molecular chaperone protein, HSP90, and one of its characteristics is that it affects the genetic variation in various morphological traits. However, it remains unclear whether the wide‐ranging effects of HSP90 on a broad range of traits are a general feature of genetic capacitors and potentiators. In the current study, I searched for novel genetic capacitors and potentiators for quantitative bristle traits of Drosophila melanogaster and then investigated the trait specificity of their genetic buffering effect. Three bristle traits of D. melanogaster were used as the target traits, and the genomic regions with genetic buffering effects were screened using the 61 genomic deficiencies examined previously for genetic buffering effects in wing shape. As a result, four and six deficiencies with significant effects on increasing and decreasing the broad‐sense heritability of the bristle traits were identified, respectively. Of the 18 deficiencies with significant effects detected in the current study and/or by the previous study, 14 showed trait‐specific effects, and four affected the genetic buffering of both bristle traits and wing shape. This suggests that most genetic capacitors and potentiators exert trait‐specific effects, but that general capacitors and potentiators with effects on multiple traits also exist.     

The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses

We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (∼0.03–0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.     

QTL linkage mapping of wing length in zebra finch using genome-wide single nucleotide polymorphisms markers

Avian wing length is an important trait that covaries with the ecology and migratory behaviour of a species and tends to change rapidly when the conditions are altered. Long-distance migrants typically have longer wings than short-distance migrants and sedentary species, and long-winged species also tend to be more dispersive. Although the substantial heritability of avian wing length is well established, the identification of causal genes has remained elusive. Based on large-scale genotyping of 1404 informative single nucleotide polymorphisms (SNP) in a captive population of 1067 zebra finches, we here show that the within-population variation of relative wing length (h(2) = 0.74 ± 0.05) is associated with standing genetic variation in at least six genomic regions (one genome-wide significant and five suggestive). The variance explained by these six quantitative trait loci (QTL) sums to 36.8% of the phenotypic variance (half of the additive genetic variance), although this likely is an overestimate attributable to the Beavis effect. As avian wing length is primarily determined by the length of the primary feathers, we then searched for candidate genes that are related to feather growth. Interestingly, all of the QTL signals co-locate with Wnt growth factors and closely interacting genes (Wnt3a, Wnt5a, Wnt6, Wnt7a, Wnt9a, RhoU and RhoV). Our findings therefore suggest that standing genetic variation in the Wnt genes might be linked to avian wing morphology, although there are many other genes that also fall within the confidence regions.     

NO EFFECT OF ENVIRONMENTAL HETEROGENEITY ON THE MAINTENANCE OF GENETIC VARIATION IN WING SHAPE IN DROSOPHILA MELANOGASTER

Theory suggests that heterogeneous environments should maintain more genetic variation within populations than homogeneous environments, yet experimental evidence for this effect in quantitative traits has been inconsistent. To examine the effect of heterogeneity on quantitative genetic variation, we maintained replicate populations of Drosophila melanogaster under treatments with constant temperatures, temporally variable temperature, or spatially variable temperature with either panmictic or limited migration. Despite observing differences in fitness and divergence in several wing traits between the environments, we did not find any differences in the additive genetic variance for any wing traits among any of the treatments. Although we found an effect of gene flow constraining adaptive divergence between cages in the limited migration treatment, it did not tend to increase within‐population genetic variance relative to any of the other treatments. The lack of any clear and repeatable patterns of response to heterogeneous versus homogeneous environments across several empirical studies suggests that a single general mechanism for the maintenance of standing genetic variation is unlikely; rather, the relative importance of putative mechanisms likely varies considerably from one trait and ecological context to another.     

Quantifying the genetic component of phenotypic variation in unpedigreed wild plants: tailoring genomic scan for within-population use

The study of adaptive genetic variation in natural populations is central to evolutionary biology. Quantitative genetics methods, however, are hardly applicable to long-lived organisms, and current knowledge on adaptive genetic variation in wild plants mostly refers to annuals and short-lived perennials. Studies on long-lived species are essential to explore possible life-history correlates of genetic variation, selection, and trait heritability. In this paper, we propose a method based on molecular markers to quantify the genetic basis of individual phenotypic differences in wild plants under natural conditions. Rather than focusing on inferring individual relatedness to estimate the heritability of phenotypic traits, we directly estimate the proportion of observed phenotypic variance that is statistically accounted for by genotypic differences between individuals. This is achieved by (i) identifying loci that are correlated across individuals with the phenotypic trait of interest by means of an amplified fragment length polymorphism (AFLP)-based explorative genomic scan, and (ii) fitting multiple regression and linear random effect models to estimate the effects of genotype, environment and genotype × environment on phenotypes. We apply this method to estimate genotypic and environmental effects on cumulative maternal fecundity in a wild population of the long-lived Viola cazorlensis monitored for 20 years. Results show that between 56–63% (depending on estimation method) of phenotypic variance in fecundity is accounted for by genotypic differences in 11 AFLP loci that are significantly related to fecundity. Genotype × environment effects accounted for 38% of fecundity variance, which may help to explain the unexpectedly high levels of genetic variance for fecundity found.     

The change in quantitative genetic variation with inbreeding

Inbreeding is known to reduce heterozygosity of neutral genetic markers, but its impact on quantitative genetic variation is debated. Theory predicts a linear decline in additive genetic variance (V(A)) with increasing inbreeding coefficient (F) when loci underlying the trait act additively, but a nonlinear hump-shaped relationship when dominance and epistasis are important. Predictions for heritability (h2) are similar, although the exact shape depends on the value of h2 in the absence of inbreeding. We located 22 published studies in which the level of genetic variation in experimentally inbred populations (measured by V(A) or h2) was compared with that in outbred control populations. For life-history traits, the data strongly supported a nonlinear change in genetic variation with increasing F. V(A) and h2 were, respectively, 244% and 50% higher at F = 0.4 than in outbred populations, and dominance plus epistatic variance together exceeded additive variance by a factor of four. For nonfitness traits the decline was linear and estimates of nonadditive variance were small. These results confirm that population bottlenecks frequently increase V(A) in some traits, and imply that life-history traits are underlain by substantial dominance or epistasis. However, the importance of drift-induced genetic variation in conservation or evolutionary biology is questionable, in part because inbreeding depression usually accompanies inbreeding.     

Genetic constraints on wing pattern variation in Lycaeides butterflies: A case study on mapping complex,multifaceted traits in structured populations

Patterns of phenotypic variation within and among species can be shaped and constrained by trait genetic architecture. This is particularly true for complex traits, such as butterfly wing patterns, that consist of multiple elements. Understanding the genetics of complex trait variation across species boundaries is difficult, as it necessitates mapping in structured populations and can involve many loci with small or variable phenotypic effects. Here, we investigate the genetic architecture of complex wing pattern variation in Lycaeides butterflies as a case study of mapping multivariate traits in wild populations that include multiple nominal species or groups. We identify conserved modules of integrated wing pattern elements within populations and species. We show that trait covariances within modules have a genetic basis and thus represent genetic constraints that can channel evolution. Consistent with this, we find evidence that evolutionary changes in wing patterns among populations and species occur in the directions of genetic covariances within these groups. Thus, we show that genetic constraints affect patterns of biological diversity (wing pattern) in Lycaeides, and we provide an analytical template for similar work in other systems.     

ON THE LOW HERITABILITY OF LIFE-HISTORY TRAITS

Life-history traits such as longevity and fecundity often show low heritability. This is usually interpreted in terms of Fisher's fundamental theorem to mean that populations are near evolutionary equilibrium and genetic variance in total fitness is low. We develop the causal relationship between metric traits and life-history traits to show that a life-history trait is expected to have a low heritability whether or not the population is at equilibrium. This is because it is subject to all the environmental variation in the metric traits that affect it plus additional environmental variation. There is no simple prediction regarding levels of additive genetic variance in life-history traits, which may be high at equilibrium. Several other patterns in the inheritance of life-history traits are readily predicted from the causal model. These include the strength of genetic correlations between life-history traits, levels of nonadditive genetic variance, and the inevitability of genotype-environment interaction.     

EVOLVABILITY OF INDIVIDUAL TRAITS IN A MULTIVARIATE CONTEXT: PARTITIONING THE ADDITIVE GENETIC VARIANCE INTO COMMON AND SPECIFIC COMPONENTS

Genetic covariation among multiple traits will bias the direction of evolution. Although a trait's phenotypic context is crucial for understanding evolutionary constraints, the evolutionary potential of one (focal) trait, rather than the whole phenotype, is often of interest. The extent to which a focal trait can evolve independently depends on how much of the genetic variance in that trait is unique. Here, we present a hypothesis‐testing framework for estimating the genetic variance in a focal trait that is independent of variance in other traits. We illustrate our analytical approach using two Drosophila bunnanda trait sets: a contact pheromone system comprised of cuticular hydrocarbons (CHCs), and wing shape, characterized by relative warps of vein position coordinates. Only 9% of the additive genetic variation in CHCs was trait specific, suggesting individual traits are unlikely to evolve independently. In contrast, most (72%) of the additive genetic variance in wing shape was trait specific, suggesting relative warp representations of wing shape could evolve independently. The identification of genetic variance in focal traits that is independent of other traits provides a way of studying the evolvability of individual traits within the broader context of the multivariate phenotype.     

Sex differences in the genetic architecture of aggressiveness in a sexually dimorphic spider

Sex differences in the genetic architecture of behavioral traits can offer critical insight into the processes of sex‐specific selection and sexual conflict dynamics. Here, we assess genetic variances and cross‐sex genetic correlations of two personality traits, aggression and activity, in a sexually size‐dimorphic spider, Nuctenea umbratica. Using a quantitative genetic approach, we show that both traits are heritable. Males have higher heritability estimates for aggressiveness compared to females, whereas the coefficient of additive genetic variation and evolvability did not differ between the sexes. Furthermore, we found sex differences in the coefficient of residual variance in aggressiveness with females exhibiting higher estimates. In contrast, the quantitative genetic estimates for activity suggest no significant differentiation between males and females. We interpret these results with caution as the estimates of additive genetic variances may be inflated by nonadditive genetic effects. The mean cross‐sex genetic correlations for aggression and activity were 0.5 and 0.6, respectively. Nonetheless, credible intervals of both estimates were broad, implying high uncertainty for these estimates. Future work using larger sample sizes would be needed to draw firmer conclusions on how sexual selection shapes sex differences in the genetic architecture of behavioral traits.     

Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits

The number of variants that have a non-zero effect on a trait (i.e. polygenicity) is a fundamental parameter in the study of the genetic architecture of a complex trait. Although many previous studies have investigated polygenicity at a genome-wide scale, a detailed understanding of how polygenicity varies across genomic regions is currently lacking. In this work, we propose an accurate and scalable statistical framework to estimate regional polygenicity for a complex trait. We show that our approach yields approximately unbiased estimates of regional polygenicity in simulations across a wide-range of various genetic architectures. We then partition the polygenicity of anthropometric and blood pressure traits across 6-Mb genomic regions (N = 290K, UK Biobank) and observe that all analyzed traits are highly polygenic: over one-third of regions harbor at least one causal variant for each of the traits analyzed. Additionally, we observe wide variation in regional polygenicity: on average across all traits, 48.9% of regions contain at least 5 causal SNPs, 5.44% of regions contain at least 50 causal SNPs. Finally, we find that heritability is proportional to polygenicity at the regional level, which is consistent with the hypothesis that heritability enrichments are largely driven by the variation in the number of causal SNPs.     

Multivariate selection and intersexual genetic constraints in a wild bird population

When selection differs between the sexes for traits that are genetically correlated between the sexes, there is potential for the effect of selection in one sex to be altered by indirect selection in the other sex, a situation commonly referred to as intralocus sexual conflict (ISC). While potentially common, ISC has rarely been studied in wild populations. Here, we studied ISC over a set of morphological traits (wing length, tarsus length, bill depth and bill length) in a wild population of great tits (Parus major) from Wytham Woods, UK. Specifically, we quantified the microevolutionary impacts of ISC by combining intra‐ and intersex additive genetic (co)variances and sex‐specific selection estimates in a multivariate framework. Large genetic correlations between homologous male and female traits combined with evidence for sex‐specific multivariate survival selection suggested that ISC could play an appreciable role in the evolution of this population. Together, multivariate sex‐specific selection and additive genetic (co)variance for the traits considered accounted for additive genetic variance in fitness that was uncorrelated between the sexes (cross‐sex genetic correlation = ?0.003, 95% CI = ?0.83, 0.83). Gender load, defined as the reduction in a population's rate of adaptation due to sex‐specific effects, was estimated at 50% (95% CI = 13%, 86%). This study provides novel insights into the evolution of sexual dimorphism in wild populations and illustrates how quantitative genetics and selection analyses can be combined in a multivariate framework to quantify the microevolutionary impacts of ISC.     

Genetic variants and underlying mechanisms influencing variance heterogeneity in maize

Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance‐heterogeneity genome‐wide association study to examine the contribution of variance heterogeneity to oil‐related quantitative traits. We identified 79 unique variance‐controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance‐heterogeneity genes for 21 oil‐related traits using the Levene test (P < 1.0 × 10^?5). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean‐effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two‐hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high‐oil maize (Zea mays L.).     

Lack of nonadditive genetic effects on early fecundity in Drosophila melanogaster

Fecundity is usually considered as a trait closely connected to fitness and is expected to exhibit substantial nonadditive genetic variation and inbreeding depression. However, two independent experiments, using populations of different geographical origin, indicate that early fecundity in Drosophila melanogaster behaves as a typical additive trait of low heritability. The first experiment involved artificial selection in inbred and non-inbred lines, all of them started from a common base population previously maintained in the laboratory for about 35 generations. The realized heritability estimate was 0.151 +/- 0.075 and the inbreeding depression was very small and nonsignificant (0.09 +/- 0.09% of the non-inbred mean per 1% increase in inbreeding coefficient). With inbreeding, the observed decrease in the within-line additive genetic variance and the corresponding increase of the between-line variance were very close to their expected values for pure additive gene action. This result is at odds with previous studies showing inbreeding depression and, therefore, directional dominance for the same trait and species. All experiments, however, used laboratory populations, and it is possible that the original genetic architecture of the trait in nature was subsequently altered by the joint action of random drift and adaptation to captivity. Thus, we carried out a second experiment, involving inbreeding without artificial selection in a population recently collected from the wild. In this case we obtained, again, a maximum-likelihood heritability estimate of 0.210 +/- 0.027 and very little nonsignificant inbreeding depression (0.06 +/- 0.12%). The results suggest that, for fitness-component traits, low levels of additive genetic variance are not necessarily associated with large inbreeding depression or high levels of nonadditive genetic variance.     

Genetic and environmental effects on morphology and fluctuating asymmetry in nestling barn swallows

A barn swallow Hirundo rustica partial cross‐fostering experiment with simultaneous brood size manipulation was conducted in two years with contrasting weather conditions, to estimate heritable variation in tarsus, tail and wing size and fluctuating asymmetry. Environmental stress had contrasting effects depending on trait type. Significant heritabilities for tarsus, tail and wing size were found only in enlarged broods irrespective of year effects, while tarsus asymmetry was significantly heritable in the year with benign weather conditions irrespective of brood size manipulation effects. Tail, wing and composite (multicharacter) asymmetry were never significantly heritable. The environment with the higher heritability generally had higher additive genetic variance and lower environmental variance, irrespective of trait type. Heritability was larger for trait size than for trait asymmetry. Patterns of genetic variation in nestlings do not necessarily translate to the juvenile or adult stage, as indicated by lack of correlation between nestling and fledgling traits.