Fixed and random effects in the variation of the finger ridge count: a study of fragile-X families.

A maximum-likelihood scoring technique for analysis of pedigree data allows for the concurrent estimation of random and of fixed effects in a quantitative trait. We included both types of effects in genetic models, to study the sources of variation in finger ridge count in 54 large families affected with the fragile-X disorder. The fixed effects were represented by fragile X and sex, and the random effects by environmental and genetic variance. We found a significant effect of fragile X in the mean of the finger ridge count on the thumb (finger 1) and index finger (finger 2), which had the lowest heritability and a negligible nonadditive component of genetic variance. This was in contrast with ridge counts on fingers 3 and 4, which showed little fragile-X effect, but high heritability and a significant nonadditive component. A contrast in genetic properties for ridge counts on fingers 1 and 2, compared with these counts on the remaining three fingers, may be relevant to increased selection pressures on functions of the thumb and of the index finger in evolution of modern man. We have also demonstrated an important effect of fragile X in increasing the additive variance in covariance, especially between male pairs. These findings suggest that the effect of the fragile-X genotype in finger ridge count is additive and superimposed on the normal hereditary variations in this trait.     

Linkage analysis of a model quantitative trait in humans: finger ridge count shows significant multivariate linkage to 5q14.1

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers.     

GENETIC COMPONENTS OF VARIATION IN ENERGY STORAGE IN DROSOPHILA MELANOGASTER

One approach to examining the underlying genetic structure of the variation in a continuous phenotype is to measure a set of possibly mechanistically related traits and determine the quantitative genetic aspects of their transmission. In this study the quantities of stored triacylglycerol and glycogen were measured along with the activities of 10 enzymes in related metabolic pathways in a set of 1,157 half-sib families of Drosophila melanogaster. The families were structured with each male being mated to 10 females and two offspring were scored from each female. Parents and offspring were scored for the phenotypes, and the components of variance (additive, dominance, and environmental) were estimated in three ways, including analysis of variance on offspring alone, parent-offspring regression, and maximum likelihood methods. While there were differences among the estimates made by the three methods, a consistent result was that substantial additive genetic variation was detected for all the traits. Consistent with models for the quantitative genetics of enzyme kinetics, the genetic variances of global properties were largely additive. Previous studies with extracted chromosome lines had indicated several significant genetic correlations among these characters, and much of the correlation was attributable to additive effects. The results imply that there is substantial opportunity for natural or artificial selection to act on quantities of stored lipid and carbohydrate, and that the response to selection is likely to be in part mediated by changes in the kinetics of the enzymes targeted in this study.     

A family study of dermatoglyphic traits in India: resolution of genetic and uterine environmental effects for palmar pattern ridge counts

The inheritance of palmar pattern ridge counts for individual palmar areas, combined distal areas, and all ten areas combined was investigated in families belonging to two strictly endogamous Brahmin castes of peninsular India. Ridge count phenotypes were obtained by the method proposed by Malhotra et al. (1981a), however, zero observations (indicating patterns not circumscribed by triradii) were excluded from analysis. Path analytic methods were applied in order to determine the relative influences of polygenes, intrauterine environment, and residual environment. The proportion of genetic variation was, in general, consistently greater in one population than the other, and significant intrauterine environmental effects were detected for the population with lower heritabilities. The results of this investigation suggest that a simple polygenic model may not be sufficient to explain the inheritance of ridge counts in the interdigital IV configurational area. Distal pattern ridge counts do not appear to be influenced by more or less uterine environmental effects than all areas considered together. The proportion of genetic variation for the total palmar pattern ridge count was 52% in both populations.     

The Design and Use of Variance Component Models in the Analysis of Human Quantitative Pedigree Data

The use of variance components and multivariate linear models in genetics applications has a long history that dates back to (at least) Fisher's seminal 1918 paper “The correlation between relatives on the supposition of Mendelian inheritance” [Phil. Trans. 52: 399–433]. Although extensions and elaborations of Fisher's insights have been offered in recent times, relatively few studies exist which examine the theoretical and operational properties variance component models possess in complicated genetic analysis settings. In this paper variance component models, as well as some of their properties (e.g., power, efficiency, and sample size considerations) are discussed in the context of each of the following genetic analysis settings: 1. the detection of general polygenic additive and dominance effects; 2. the detection of genetic effects in the presence of environmental effects (and vice versa); 3. the detection of pleiotropic gene action; 4. aspects of the detection of genotype by environment interaction; and 5. sequential tests for general hypotheses framed in the context of settings 1 through 4. Exposition of the proposed methods and results are facilitated through a special emphasis placed on pedigree covariance structure modeling.     

Latent structure of dermatoglyphics in gastric cancer patients

Gastric cancer is a very common malignant disease, which etiology is still unknown. It is believed that it is caused by a joint activity of both genetic and environmental factors. Gastric cancer between relatives in some families is almost four times higher and in connection with truncating mutations in the E-cadherin gene. The Helicobacter pylori are also established carcinogen and this infection increases the cancer risk by about 5 times. Digito-palmar dermatoglyphics have already been used for determining hereditary base of some malignant diseases (breast, lung, colorectal cancer etc.), which was the encouragement to investigate the latent structure in patients with gastric cancer (36 males and 32 females) and the control groups (50 males and 50 females). The factor analysis has shown that in both males and females with gastric cancer 5 factors were extracted and in males 77.17% and in females 78.92% of total variance was explained, and this result is different from control group where in males 5 factors and 75.97% of total variance were explained while in control females 6 factors and 82.86% of total variance were explained. The finger ridge counts are extracted on the first factor in all groups. In patients the second factor is formed by the first, fourth and fifth fingers, while in controls mostly by palmar variables. From the obtained findings it can be concluded that the results of latent structure in quantitative analysis of digito-palmar dermatoglyphics are affirming the existence of genetic differences in patients suffered with gastric cancer.     

Path analysis of palmar ridge counts.

The methods for path analysis of family resemblance (Rao et al., '74) are employed to test hypotheses concerning the inheritance of a-b, b-c and c-d palmar ridge counts using the correlation data of Pateria ('74). Homogeneity chi-square tests of the various familial correlations provide no evidence for sex-linkage of either kind, and also suggest that maternal effects are absent. The path coefficient model employed here involves heritability (additive) and common sibling environment. Variance components show that both heritability and common environment are significant, and account for most of the variation at each of the three ridge count area; b-c has the highest heritability, significantly higher than that for a-b or c-d.     

Evolution of Adaptation and Mate Choice: Parental Relatedness Affects Expression of Phenotypic Variance in a Natural Population

Mating between relatives generally results in reduced offspring viability or quality, suggesting that selection should favor behaviors that minimize inbreeding. However, in natural populations where searching is costly or variation among potential mates is limited, inbreeding is often common and may have important consequences for both offspring fitness and phenotypic variation. In particular, offspring morphological variation often increases with greater parental relatedness, yet the source of this variation, and thus its evolutionary significance, are poorly understood. One proposed explanation is that inbreeding influences a developing organism’s sensitivity to its environment and therefore the increased phenotypic variation observed in inbred progeny is due to greater inputs from environmental and maternal sources. Alternatively, changes in phenotypic variation with inbreeding may be due to additive genetic effects alone when heterozygotes are phenotypically intermediate to homozygotes, or effects of inbreeding depression on condition, which can itself affect sensitivity to environmental variation. Here we examine the effect of parental relatedness (as inferred from neutral genetic markers) on heritable and nonheritable components of developmental variation in a wild bird population in which mate choice is often constrained, thereby leading to inbreeding. We found greater morphological variation and distinct contributions of variance components in offspring from highly related parents: inbred offspring tended to have greater environmental and lesser additive genetic variance compared to outbred progeny. The magnitude of this difference was greatest in late-maturing traits, implicating the accumulation of environmental variation as the underlying mechanism. Further, parental relatedness influenced the effect of an important maternal trait (egg size) on offspring development. These results support the hypothesis that inbreeding leads to greater sensitivity of development to environmental variation and maternal effects, suggesting that the evolutionary response to selection will depend strongly on mate choice patterns and population structure.     

Quantitative genetic and translocation experiments reveal genotype‐by‐environment effects on juvenile life‐history traits in two populations of Chinook salmon (Oncorhynchus tshawytscha)

Understanding the genetic architecture of phenotypic plasticity is required to assess how populations might respond to heterogeneous or changing environments. Although several studies have examined population‐level patterns in environmental heterogeneity and plasticity, few studies have examined individual‐level variation in plasticity. Here, we use the North Carolina II breeding design and translocation experiments between two populations of Chinook salmon to detail the genetic architecture and plasticity of offspring survival and growth. We followed the survival of 50 800 offspring through the larval stage and used parentage analysis to examine survival and growth through freshwater rearing. In one population, we found that additive genetic, nonadditive genetic and maternal effects explained 25%, 34% and 55% of the variance in larvae survival, respectively. In the second population, these effects explained 0%, 24% and 61% of the variance in larvae survival. In contrast, fry survival was regulated primarily by additive genetic effects, which indicates a shift from maternal to genetic effects as development proceeds. Fry growth also showed strong additive genetic effects. Translocations between populations revealed that offspring survival and growth varied between environments, the degree of which differed among families. These results indicate genetic differences among individuals in their degree of plasticity and consequently their ability to respond to environmental variation.     

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.     

QUANTITATIVE GENETICS OF GEOMETRIC SHAPE IN THE MOUSE MANDIBLE

Abstract 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 1241 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 breeder's 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.     

Heritability of female extra-pair paternity rate in song sparrows (Melospiza melodia)

The forces driving the evolution of extra-pair reproduction in socially monogamous animals remain widely debated and unresolved. One key hypothesis is that female extra-pair reproduction evolves through indirect genetic benefits, reflecting increased additive genetic value of extra-pair offspring. Such evolution requires that a female's propensity to produce offspring that are sired by an extra-pair male is heritable. However, additive genetic variance and heritability in female extra-pair paternity (EPP) rate have not been quantified, precluding accurate estimation of the force of indirect selection. Sixteen years of comprehensive paternity and pedigree data from socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia) showed significant additive genetic variance and heritability in the proportion of a female's offspring that was sired by an extra-pair male, constituting major components of the genetic architecture required for extra-pair reproduction to evolve through indirect additive genetic benefits. However, estimated heritabilities were moderately small (0.12 and 0.18 on the observed and underlying latent scales, respectively). The force of selection on extra-pair reproduction through indirect additive genetic benefits may consequently be relatively weak. However, the additive genetic variance and non-zero heritability observed in female EPP rate allow for multiple further genetic mechanisms to drive and constrain mating system evolution.     

A family study of dermatoglyphic traits in India. Resolution of genetic and environmental effects for manus,pes and total pattern ridge counts in man

Various constructed ridge count phenotypes were studied in two endogamous populations from peninsular India. Heritabilities were estimated for five summed pattern ridge count traits: fingers and toes together; palms and soles together; fingers and palms together (manus); toes and soles together (pes); and fingers, palms, toes and soles together, defined as the total ridge count in man. In general, these phenotypes were found to he highly heritable, with the summed ridge counts for fingers and toes, and total ridge count showing almost Complete determination by additive polygenes. Total manus and pes pattern counts are less heritable. Little or no uterine environmental effects were detected for any of these phenotypes.     

QUANTITATIVE GENETIC MODELS FOR DEVELOPMENT,EPIGENETIC SELECTION,AND PHENOTYPIC EVOLUTION

Herein we describe a general multivariate quantitative genetic model that incorporates two potentially important developmental phenomena, maternal effects and epigenetic effects. Maternal and epigenetic effects are defined as partial regression coefficients and phenotypic variances are derived in terms of age-specific genetic and environmental variances. As a starting point, the traditional quantitative genetic model of additive gene effects and random environmental effects is cast in a developmental time framework. From this framework, we first extend a maternal effects model to include multiple developmental ages for the occurrence of maternal effects. An example of maternal effects occurring at multiple developmental ages is prenatal and postnatal maternal effects in mammals. Subsequently, a model of intrinsic and epigenetic effects in the absence of maternal effects is described. It is shown that genetic correlations can arise through epigenetic effects, and in the absence of other developmental effects, epigenetic effects are in general confounded with age-specific intrinsic genetic effects. Finally, the two effects are incorporated into the basic quantitative genetic model. For this more biologically realistic model combining maternal and epigenetic effects, it is shown that the phenotypic regressions of offspring on mother and offspring on father can be used in some cases to estimate simultaneously maternal effects and epigenetic effects.     

Inheritance of 18 quantitative dermatoglyphic traits based on factors in MZ and DZ twins

18 quantitative finger and palmar dermatoglyphic traits were analyzed with the aim of determining genetic effects and common familial environmental influences on a large (358 nuclear pedigrees) number of twins (MZ and DZ). Genetic analysis based on principal factors includes variance and bivariate variance decomposition analysis. Especially, Factor 1 (digital pattern size) is remarkable, due to its degree of universality. The results of genetic analysis revealed all three extracted factors have significant proportion of additive genetic variance (93.5% to 72.9%). The main results of bivariate variance decomposition analysis appears significant correlation in residual variance between digital pattern size factor (Factor 1) versus finger pattern intensity factor (Factor 4), and palmar main lines factor (Factor 2) verses a-b ridge count (Factor 3), but there was no significant correlation in the genetic variance of factors.     

Estimates of direct and indirect effects for early juvenile survival in captive populations maintained for conservation purposes: the case of Cuvier's gazelle

Together with the avoidance of any negative impact of inbreeding, preservation of genetic variability for life‐history traits that could undergo future selective pressure is a major issue in endangered species management programmes. However, most of these programmes ignore that, apart from the direct action of genes on such traits, parents, as contributors of offspring environment, can influence offspring performance through indirect parental effects (when parental genotype and phenotype exerts environmental influences on offspring phenotype independently of additive genetic effects). Using quantitative genetic models, we estimated the additive genetic variance for juvenile survival in a population of the endangered Cuvier's gazelle kept in captivity since 1975. The dataset analyzed included performance recording for 700 calves and a total pedigree of 740 individuals. Results indicated that in this population juvenile survival harbors significant additive genetic variance. The estimates of heritability obtained were in general moderate (0.115–0.457) and not affected by the inclusion of inbreeding in the models. Maternal genetic contribution to juvenile survival seems to be of major importance in this gazelle's population as well. Indirect genetic and indirect environmental effects assigned to mothers (i.e., maternal genetic and maternal permanent environmental effects) roughly explain a quarter of the total variance estimated for the trait analyzed. These findings have major evolutionary consequences for the species as show that offspring phenotypes can evolve strictly through changes in the environment provided by mothers. They are also relevant for the captive breeding programme of the species. To take into account, the contribution that mothers have on offspring phenotype through indirect genetic effects when designing pairing strategies might serve to identify those females with better ability to recruit, and, additionally, to predict reliable responses to selection in the captive population.     

Unravelling the effects of differential maternal allocation and male genetic quality on offspring viability in the dung beetle, Onthophagus sagittarius

Good genes models of mate choice assume heritability of fitness-related traits. However, maternal effects can inflate estimates of trait heritability, and genotype-environment interactions can have significant effects on good genes processes of evolution. Thus, partitioning genetic and maternal/environmental sources of variation in studies of good genes mate choice represents an empirical challenge. In this study, we used the dung beetle Onthophagus sagittarius to examine additive genetic and maternal effects on egg-to-adult offspring viability. We used a half-sib full-sib breeding design and manipulated the maternally provided environment by reducing or increasing the mass of the brood ball within which each offspring developed. We found evidence of differential allocation of investment by females in the brood balls they produced. However, experimental manipulations of maternal allocation to brood balls had only a weak and non-significant influence on the sire effects on offspring viability. Significant additive genetic effects on offspring viability were pervasive across our manipulations of the maternally provided larval environment. This finding indicates that although females do show differential allocation to offspring based on sire phenotype, ‘good genes’ benefits of mate choice are not dependent upon differential maternal allocation.     

Heritability of deciduous tooth size in Australian aboriginals

The contributions of genetic and evironmental influences to observed variability of deciduous tooth size were quantified in a group of Australian aboriginals. Phenotypic variability was partitioned into four components; between sides, between fathers, between mothers, and between offspring. Results suggested that about 58% of deciduous tooth-size variability was due to additive genetic variance and 15% to common environmental variance. It appears that additive genetic variance is similar in both deciduous and permanent dentitions, but that common maternal effects are more important in determining deciduous tooth-size variability.     

Factor analytic models of clustered multivariate data with informative censoring

This article describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censoring process, and we account for dependency between these latent variables through a hierarchical model. A linear model is used to relate covariates and latent variables to the primary outcomes for each subunit. A generalized linear model accounts for covariate and latent variable effects on the probability of censoring for subunits within each cluster. The model accounts for correlation within clusters and within subunits through a flexible factor analytic framework that allows multiple latent variables and covariate effects on the latent variables. The structure of the model facilitates implementation of Markov chain Monte Carlo methods for posterior estimation. Data from a spermatotoxicity study are analyzed to illustrate the proposed approach.     

Genetics of testosterone and the aggression-hostility-anger (AHA) syndrome: a study of middle-aged male twins.

The aim of this study was to determine the genetic contribution to the variation in testosterone and the aggression-hostility-anger (AHA) syndrome in middle-aged twins. Moreover, the relation between testosterone and this syndrome, and possible common genetic mechanisms were investigated. Towards this end, blood samples were collected at two time points; the AHA syndrome was measured using three questionnaires: the Buss-Durkee Hostility Inventory with seven subscales, the Jenkins Activity Survey and the Spielberger State-Trait Anger Scale. The results showed substantial heritabilities for testosterone (approximately 60%) and moderate to fair heritabilities for the nine measures of the AHA syndrome (23-53%). The best fitting model for testosterone at two time points included a small age component and additive genetic and unique environmental factors, while a multivariate analysis of the nine AHA subscales resulted in an independent pathway model with two common additive genetic and two common unique environmental factors. No correlation between the common genetic factor influencing testosterone and the AHA subscales was found. We did, however, detect a negative correlation between the common environmental factor underlying testosterone and both common environmental factors influencing the nine AHA subscales, which may reflect a tendency for testosterone levels to rise and hostility to drop (or vice versa) after repeatedly experiencing success (or failure).