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PubMed2000

Quantitative genetics of life-history traits in a long-lived wild mammal.

Quantitative genetic studies of life-history traits in wild populations are very rare, yet variance/covariance estimates of these traits are crucial to understanding the evolution of reproductive strategies. We estimated heritabilities (h2) of several life-history traits (longevity, age and mass at primiparity, and reproductive traits) in two bighorn sheep (Ovis canadensis) populations, and both phenotypic (rP) and genetic (rA) correlations between life-history traits in one population. We included adult mass in our analyses because it is related to several life-history traits. We used the mother-daughter regression method and resampling tests based on data from long-term monitoring of marked females. Contrary to the theoretical prediction of low heritability for fitness-related traits, heritability estimates in the Ram Mountain population ranged from 0.02 to 0.81 (mean of 0.52), and several were different from zero. Coefficients of variation tend to support the hypothesis of a higher environmental influence on life-history traits. In contrast, at Sheep River we found low heritabilities of life-history traits. Phenotypic correlations varied between -0.09 and 0.95. Several genetic correlations were strong, particularly for different reproductive traits that are functionally related, and ranged from -0.34 to 1.71. Overall, genetic and phenotypic correlations between the same variables were similar in magnitude and direction. We found no phenotypic or genetic correlations suggesting trade-offs among life-history traits. Bighorn sheep may not form the large, outbred populations at equilibrium that are assumed by both Fisher's fundamental theorem and by theories predicting antagonistic pleiotropy between life-history traits. Alternatively, the absence of negative genetic correlations may result from genetic variation in ability to acquire resources or from novel environmental conditions existing during the study period.

Animals↗
PubMed2002

The consistency of quantitative genetic estimates in field and laboratory in the yellow dung fly.

How consistent quantitative genetic estimates are across environments is unclear and under discussion. Heritability (h2) estimates of hind tibia length (body size), development time and diapause induction in the yellow dung fly, Scathophaga stercoraria, generated with various methods in various environments are reported and compared. Estimates varied considerably within and among studies, but yielded good overall averages. The genetic correlations between the sexes for body size and development time were expectedly high (r(sex) = 0.57-0.78) but clearly less than unity, implying independent evolution of both traits in males and females of this sexually dimorphic species. Genetic and environmental variance components increased in proportion at variable field relative to constant laboratory conditions, resulting in overall similar h(2). Heritabilities for males and females were also similar, and h(2) of the morphological trait hind tibia length was not necessarily greater than that of the two life history traits. Full-sib (broad-sense) estimates (h(2) = 0.7-1.1) were 2-3 times greater than half-sib and parent/offspring (narrow-sense) estimates (h2 = 0-0.6). Common environment (i.e., among-container) variance averaged 38.3% (body size) and 16.8% (development time) of the broad-sense genetic variance in two laboratory studies. The broad-sense h(2), therefore, may contain substantial amounts (12-50%) of dominance variance and/or variance due to maternal effects. A general conclusion emerging from this and similar studies appears to be that whether field and laboratory genetic estimates differ depends on the environment, trait and species under consideration.

Animals↗
PubMed1985

Quantitative genetic models of female choice based on "arbitrary" male characters.

Multivariate, quantitative genetic models are developed for the evolution of female mating preferences in situations where males contribute only their gametes to their progeny. Although female mating preferences may not be directly subject to selection, they can evolve via genetic correlations with other characters that are undergoing evolutionary change. The first set of models examines the evolutionary origin of mating preferences directed at one or more traits that may or may not be expressed only in males. When several selected characters possess additive genetic variance, an indirect selective force exists for the evolution of multivariate mating preferences. The magnitude of this force is proportional to the covariance between a female's relative preference for a given male's phenotype and the expected viability of his progeny. The contribution of any single character to this covariance determines its potential value as a mate choice criterion. The pattern of genetic and phenotypic covariation may cause selectively unimportant traits to be useful in mate choice. In the extreme, selectively neutral characters may become the objects of mating preferences, if they are relatively immune to random environmental variation and genetically correlated with selectively important characters. The second set of models examines the dynamic evolution of such a selectively neutral ("arbitrary") character that is both the object of a mating preference and genetically correlated with a third trait that affects viability. The outcome of evolution in this three character system is highly indeterminate. As in other sexual selection models, there exists a line of neutral equilibria wherein the mean of the criterion character matches the mean level of mating preference within the population, while the viability trait equilibrates at the phenotypic value conferring maximum viability. This line of equilibria, however, is not likely to be stable unless females choose mates according to absolute mating preferences. Thus, mating preferences that initially may arise as a mean of increasing offspring viability may nevertheless lead to indeterminate and potentially maladaptive evolutionary outcomes.

Animals↗
PubMed2000

Quantitative genetics of allogamous F2: an origin of randomly fertilized populations.

The quantitative genetic properties are derived for the bulk F2 originating from random fertilization (RF) amongst hybrid (F1) individuals. Only its mean appears to have been derived previously, and that definition is confirmed (by another method). New general equations are found also for all genotype frequencies, allele frequencies, inbreeding coefficient, the genotypic, additive-genetic and dominance variances, and broad-sense and narrow-sense heritabilities. The assumption that such an F2 is a classical RF population is shown to be correct. Indeed, the allogamous F2 is a natural origin for the RF population. The relationships are given between precedent RF populations (parents) and subsequent RF populations following hybridization (allogamous F2). The allogamous F2 is generally inbred with respect to its parental F1, the degree depending on the hybrid's parents' allele frequencies. At the same time, it is outbred with respect to those original parents, and not inbred at all with respect to the equivalent RF population. The genotypic variance is generally more than in the F1, and likewise for heritabilities. These findings make it possible to evaluate the genetic advance from selection and hybridization. The results depend on the allele frequencies of the original parents and the degree of overdominance, but generally, selection is more advantageous than hybrid vigour.

Alleles↗
PubMed1994

Alcohol acceptance, preference, and sensitivity in mice. I. Quantitative genetic analysis using BXD recombinant inbred strains.

Although the recombinant inbred strain method was designed for molecular genetic analysis of linkage, it also provides powerful quantitative genetic analyses of heritability and genetic correlations. Measures of alcohol acceptance, alcohol preference, and hypnotic dose sensitivity (HDS) were assessed in 21 strains of mice from the BXD RI series. Sex differences were found to be significant at a phenotypic level. However, heritability estimates for acceptance, preference, and HDS are similar in males and females. Heritability estimates for the three measures are approximately 0.20 for acceptance and preference, and 0.10 for HDS. Analyses of genetic correlations reveal that acceptance and preference share some degree of genetic influence, although they mostly operate under different genetically mediated mechanisms. HDS did not show a significant genetic relationship to either acceptance or preference. Strong correlations were obtained when acceptance, preference, and HDS strain means were correlated across male and female recombinant inbreds, suggesting substantial genetic similarity across sexes.

Alcohol Drinking↗
PubMed2001

Quantitative genetics of seminal receptacle length in Drosophila melanogaster.

The length of the female's primary sperm-storage organ, the seminal receptacle, has undergone rapid divergence within the Drosophila genus. Quantitative genetic analysis of seminal receptacle length was carried out on two laboratory strains of Drosophila melanogaster that had undergone artificial selection for both increased and decreased organ length. Realized heritabilities were 0.176 and 0.270 for the two experiments. Parental strains, F1, F1r (reciprocal), F2, backcross, and backcross reciprocal generations were used in a line-cross (generation means) analysis. This analysis revealed that additive, dominance, and additive-by-dominance epistasis contributed significantly to the means. No significant maternal effects were found. Variance analysis indicated that a completely additive model was adequate to explain the variances observed in these lines. Castle-Wright minimal estimates of 5.25 and 1.91, segregating loci responsible for mean differences, were found for the two respective experiments. There were significant positive correlations between additive effects of seminal receptacle length and thorax length in both experiments. The correlated evolution of sperm and seminal receptacle length is discussed.

Animals↗
PubMed1991

Quantitative genetics of postponed aging in Drosophila melanogaster. II. Analysis of selected lines.

Quantitative genetic analyses of Drosophila melanogaster stocks with postponed aging have suffered from the problem of a lack of certainty concerning patterns of allelic differentiation. The present experiments were designed to alleviate this difficulty by selecting for enhanced levels of characters known to be related to postponed aging. Selection successfully increased the degree of differentiation of postponed aging stocks with respect to starvation resistance and fecundity, but persistent additive genetic variance suggested that selection did not result in fixation of alleles. The artificially selected stocks were subjected to crosses to test for patterns of dominance and maternal effects. There was little evidence for these effects in the inheritance of the characters underlying postponed aging, even with the increased differentiation of the selected stocks.

Aging↗
PubMed2006

A Thurstonian model for quantitative genetic analysis of ranks: a Bayesian approach.

A fully Bayesian method for quantitative genetic analysis of data consisting of ranks of, e.g., genotypes, scored at a series of events or experiments is presented. The model postulates a latent structure, with an underlying variable realized for each genotype or individual involved in the event. The rank observed is assumed to reflect the order of the values of the unobserved variables, i.e., the classical Thurstonian model of psychometrics. Parameters driving the Bayesian hierarchical model include effects of covariates, additive genetic effects, permanent environmental deviations, and components of variance. A Markov chain Monte Carlo implementation based on the Gibbs sampler is described, and procedures for inferring the probability of yet to be observed future rankings are outlined. Part of the model is rendered nonparametric by introducing a Dirichlet process prior for the distribution of permanent environmental effects. This can lead to potential identification of clusters of such effects, which, in some competitions such as horse races, may reflect forms of undeclared preferential treatment.

Bayes Theorem↗
PubMed1998

Quantitative genetics of vector competence for dengue-2 virus in Aedes aegypti.

A quantitative genetic study of the ability of Aedes aegypti to propagate dengue-2 (DEN-2) virus in the midgut and in a disseminated infection in the head was conducted with a standard half-sib breeding design. Aedes aegypti aegypti and A. aegypti formosus differ markedly in oral susceptibility to DEN-2 virus. Mosquitoes were orally infected and, after an extrinsic incubation period of 14 days, virus titer (by tissue culture infectious dose, 50% endpoint) was determined in the midgut (MT) and head (HT). Body size as measured by wing length was not significantly different between infected and uninfected mosquitoes and was not correlated with MT or HT The heritability for MT in both subspecies was 0.41 and was 0.39 for HT in A. aegypti formosus. In A. aegypti aegypti, HT appeared to be controlled by dominant alleles. The MT was not correlated with HT nor did MT determine whether virus disseminated out of the midgut. These results suggest that it is the barriers to infection and dissemination, independent of virus titer, that determine vector competence for DEN-2 virus.

Aedes↗
PubMed2005

A quantitative genetics model for viability selection.

Viability selection will change gene frequencies of loci controlling fitness. Consequently, the frequencies of marker loci linked to the viability loci will also change. In genetic mapping, the change of marker allelic frequencies is reflected by the departure from Mendelian segregation ratio. The non-Mendelian segregation of markers has been used to map viability loci along the genome. However, current methods have not been able to detect the amount of selection (s) and the degree of dominance (h) simultaneously. We developed a method to detect both s and h using an F2 mating design under the classical fitness model. We also developed a quantitative genetics model for viability selection by proposing a continuous liability controlling the viability of individuals. With the liability model, mapping viability loci has been formulated as mapping quantitative trait loci. As a result, nongenetic systematic environmental effects can be easily incorporated into the model and subsequently separated from the genetic effects of the viability loci. The quantitative genetic model has been verified with a series of Monte Carlo simulation experiments.

Algorithms↗
PubMed1993

Multivariate quantitative genetic simulations in anthropology with an example from the South Pacific.

Computer simulation is a commonly used tool both in genetic epidemiology and in anthropological genetics. We describe here various methods for simulating multivariate quantitative genetic evolution and apply these methods in an analysis of craniometrics from two Pacific island samples. The results of this application indicate that the two samples (one from the Tolai and one from the Moriori) are significantly different, even when allowing for founder effect, intense selection on founders, and genetic drift. The simulation methods we describe and use are commonly applied in animal breeding studies and are much more efficient and general than the multilocus gene-dropping technique usually used in anthropological genetics simulations.

Animals↗
PubMed2002

Pleiotropic model of maintenance of quantitative genetic variation at mutation-selection balance.

A pleiotropic model of maintenance of quantitative genetic variation at mutation-selection balance is investigated. Mutations have effects on a metric trait and deleterious effects on fitness, for which a bivariate gamma distribution is assumed. Equations for calculating the strength of apparent stabilizing selection (V(s)) and the genetic variance maintained in segregating populations (V(G)) were derived. A large population can hold a high genetic variance but the apparent stabilizing selection may or may not be relatively strong, depending on other properties such as the distribution of mutation effects. If the distribution of mutation effects on fitness is continuous such that there are few nearly neutral mutants, or a minimum fitness effect is assumed if most mutations are nearly neutral, V(G) increases to an asymptote as the population size increases. Both V(G) and V(s) are strongly affected by the shape of the distribution of mutation effects. Compared with mutants of equal effect, allowing their effects on fitness to vary across loci can produce a much higher V(G) but also a high V(s) (V(s) in phenotypic standard deviation units, which is always larger than the ratio V(P)/V(m)), implying weak apparent stabilizing selection. If the mutational variance V(m) is approximately 10(-3)V(e) (V(e), environmental variance), the model can explain typical values of heritability and also apparent stabilizing selection, provided the latter is quite weak as suggested by a recent review.

Genetic Variation↗
PubMed2001

Models of sexual selection on a quantitative genetic trait when preference is acquired by sexual imprinting.

The evolution of a quantitative genetic trait under stabilizing viability selection and sexual selection is modeled for a polygynous species in which female mating preferences are acquired by sexual imprinting on the parents and by exposure to the surviving population at large. Stabilizing viability selection acts equally on both sexes in the case of a sexually monomorphic trait and on males only in the case of a dimorphic trait. A genetically fixed sensory or perceptual bias defines the origin of the scale on which the trait is measured, and the possibility is incorporated that female preferences may deviate asymmetrically from the familiar-either toward or away from this origin. When viability selection is strong relative to sexual selection, the models predict that the mean trait value will evolve to the viability optimum. With intermediate ratios of the strength of viability to sexual selection, a stable equilibrium can occur on either side of this viability optimum, depending on the direction of asymmetry in female preferences. When viability selection is relatively weak and certain other conditions are also satisfied, runaway selection is predicted.

Animals↗
PubMed1996

Quantitative genetic variation of odor-guided behavior in a natural population of Drosophila melanogaster.

Quantitative genetic variation in behavioral response to the odorant, benzaldehyde, was assessed among a sample of 43 X and 35 third chromosomes extracted from a natural population and substituted into a common inbred background. Significant genetic variation among chromosome lines was detected. Heritability estimates for olfactory response, however, were low, as is typical for traits under natural selection. Furthermore, the loci affecting naturally occurring variation in olfactory response to benzaldehyde were not the same in males and females, since the genetic correlation between the sexes was low and not significantly different from zero for the chromosome 3 lines. Competitive fitness, viability and fertility of the chromosome 3 lines were estimated using the balancer equilibrium technique. Genetic correlations between fitness and odor-guided behavior were not significantly different from zero, suggesting the number of loci causing variation in olfactory response is small relative to the number of loci causing variation in fitness. Since different genes affect variation in olfactory response in males and females, genetic variation for olfactory response could be maintained by genotype x sex environment interaction. This unusual genetic architecture implies that divergent evolutionary trajectories for olfactory behavior may occur in males and females.

Animals↗
PubMed1985

A covariance structure model for quantitative genetic research.

In this paper, we have presented a general covariance structure model for quantitative genetic research that incorporates measurement theory, components of variance, and regression theory for specification of structural relations among variance components. Each portion of the general model addresses specific issues important in delineating the genetic etiology of continuous traits. Through specification of a measurement model, genetic and environmental influences can be estimated independently of measurement error. Genetic and environmental sources of variance are defined from familial sampling designs through the components of variance model. Structural relationships among several traits at the genetic or environmental level can be specified through the regression model. The significance of parameters specified in each part of the model can be tested through model comparisons using a likelihood ratio chi-square test. We utilized the general model to test genetic covariance as a source of observed covariation of obesity and glucose tolerance in the Pima Indians. We initially applied the modeling approach using full-sib, half-sib sampling among the Pima with a second application including offspring as well as parental scores. Our initial applications of the methodology suggest that the covariance structure model can be a useful tool in genetic epidemiological research. Through model comparisons, our findings suggest that the association of glucose tolerance and obesity in the Pima is not due to a common set of genes but rather due to non-familial environmental influences. In conclusion, one task important for future research, as we see it, is the application of covariance structure models to other familial sampling designs and the evaluation of the usefulness of this approach through further applications to data.

Arizona↗
PubMed2001

Direct and indirect sexual selection and quantitative genetics of male traits in guppies (Poecilia reticulata).

The ornamentation and displays on which sexual attractiveness and thus mating success are based may be complex and comprise several traits. Predicting the outcome of sexual selection on such complex phenotypes requires an understanding of both the direct operation of selection on each trait and the indirect consequences of selection operating directly on genetically correlated traits. Here we report the results of a quantitative genetic analysis of the ornamentation, sexual attractiveness, and mating success of male guppies (Poecilia reticulata). We analyze male ornamentation both from the point of view of single ornamental traits (e.g., the area of each color) and of composite measures of the way the entire pattern is likely to be perceived by females (e.g., the mean and contrast in chroma). We demonstrate that there is substantial additive genetic variation in almost all measures of male ornamentation and that much of this variation may be Y linked. Attractiveness and mating success are positively correlated at the phenotypic and genetic level. Orange area and chroma, the area of a male's tail, and the color contrast of his pattern overall are positively correlated with attractiveness and/or mating success at the phenotypic and genetic levels. Using attractiveness and mating success as measures of fitness, we estimate gradients of linear directional sexual selection operating on each male trait and use equations of multivariate evolutionary change to predict the response of male ornamentation to this sexual selection. From these analyses, we predict that indirect selection may have important effects on the evolution of male guppy color patterns.

Animals↗
PubMed2001

Quantitative genetics of geometric shape in the mouse mandible.

We combine the methods of geometric morphometrics and multivariate quantitative genetics to study the patterns of phenotypic and genetic variation of mandible shape in random-bred mice. The data are the positions of 11 landmarks on the mandibles of 1,241 mice from a parent-offspring breeding design. We use Procrustes superimposition to extract shape variation and restricted maximum likelihood to estimate the additive genetic and environmental components of variance and covariance. Matrix permutation tests showed that the genetic and phenotypic as well as the genetic and environmental covariance matrices were similar, but not identical. Likewise, principal component analyses revealed correspondence in the patterns of phenotypic and genetic variation. Patterns revealed in these analyses also showed similarities to features previously found in the effects of quantitative trait loci and in the phenotypes generated in gene knockout experiments. We used the multivariate version of the breeders' equation to explore the potential for short-term response to selection on shape. In general, the correlated response is substantial and regularly exceeds the direct response: Selection applied locally to one landmark usually produces a response in other parts of the mandible as well. Moreover, even selection for shifts of the same landmark in different directions can yield dramatically different responses. These results demonstrate the role of the geometry and anatomical structure of the mandible, which are key determinants of the patterns of the genetic and phenotypic covariance matrices, in molding the potential for adaptive evolution.

Animals↗
PubMed1997

Developmental quantitative genetics, conditional epigenetic variability and growth in mice.

Ontogenetic variation in the causal components of phenotypic variability and covariability is described for body weight and tail length in mice derived from a full 7 x 7 diallel cross. Age-related changes in additive, dominance, sex-linked and maternal variance and covariance between 14 and 70 days of age are described. Age-specific variance components at time t are conditioned on the causal genetic effects at time (t - 1). This procedure demonstrates the generation of significant episodes of new genetic variation arising at specific intervals during ontogeny. These episodes of new genetic variation are placed in the context of epigenetic models in developmental quantitative genetics. These results are also concordant on recent findings on age-specific gene expression in mouse growth as shown by QTL analyses.

Animals↗