Application of an autoregressive process to estimate genetic parameters and breeding values for daily milk yield in a tropical herd of Lucerna cattle and in United States Holstein herds

The objectives of this study were to estimate from test day records the genetic and environmental (co)variance components, correlations, and breeding values to increase genetic gain in milk yield of Lucerna and US Holstein cattle. The effects of repeated observations (within cow) were explained by first-order autoregressive processes within and across lactations using an animal model. Estimates of variance components and correlation coefficients between test days were obtained using derivative-free REML methodology. The autoregressive structure significantly reduced the model error component by disentangling the short-term environmental effects. The additional information and the more heterogeneous environmental variances between lactations in the multiple-lactation test day model than in the first lactation model provided substantially larger estimates of additive genetic variance (0.62 kg2 for Lucerna; 14.73 kg2 for Holstein), heritability (0.13 for Lucerna; 0.42 for Holstein), and individual genetic merit. Rank correlations of breeding values from multiple lactations and from first lactations ranged from 0.18 to 0.37 for females and from 0.73 to 0.89 for males, respectively. Consequently, more selection errors and less genetic gain would be expected from selection decisions based on an analysis of first lactation only, and greater accuracy would be achieved from multiple lactations. Results indicated that substantial genetic gain was possible for milk yield in the Lucerna herd (34 kg/yr). Estimates of genetic variance for Holsteins were larger than previously reported, which portends more rapid genetic progress in US herds also; under our assumptions, increases would be from 173 to 197 kg/yr.     

Genetic models for the analysis of data from the families of identical twins

Genetic models are described which exploit the unique relationships that exist within the families of identical twins to obtain weighted least squares estimates of additive, dominance and epistatic components of genetic variance as well as estimates of the contributions of X-linked genes, maternal effects and three sources of environmental variation. Since all of the relationships required to achieve a resolution of these variance components are contained within each family unit, the model would appear to be superior to previous approaches to the analysis of quantitative traits in man.     

Genes control the cessation of a woman's reproductive life: a twin study of hysterectomy and age at menopause

A classical twin study was performed to assess the extent to which genetic factors explain individual differences in age at menopause and (indications for) hysterectomy. It was further examined whether a genetic effect on the timing of the menopause was mediated through a genetic effect on age at menarche. The subjects were 275 monozygotic and 353 dizygotic female twin pairs. Maximum likelihood model fitting was used to estimate genetic and environmental variance components, Kaplan-Meier survival analysis was used to account for censored data, and the Cox proportional hazards model was used to adjust for potential confounders. A model specifying additive genetic and unique environmental factors showed the best fit to the data, yielding a heritability (h2) for age at menopause of 63%. The significance of the genetic effect was confirmed by the survival analysis and was not affected by adjustment for confounders. Both early and late menopause were found to be significantly influenced by genetic factors. Hysterectomy also showed considerable heritability (h2 = 59%), as did its two main indications: fibroids (h2 = 69%) and menorrhagia (h2 = 55%). The genetic contribution to the variance in age at menarche was estimated to be 45%, with the majority (37%) being due to dominant genetic effects. No correlation was found between age at menopause and age at menarche, suggesting different genetic mechanisms. This study provides convincing evidence for the importance of genetic factors in determining natural and surgical menopause. Understanding how genes control the timing of menopause and exploring whether these genes are indirectly associated with disease are important areas for future study.     

Cyclical etidronate in the prevention of bone loss in corticosteroid-treated primary biliary cirrhosis. A prospective, controlled pilot study

The objectives of this study were to estimate genetic parameters for weaning weight of Simmental cattle from data without selective reporting and to examine heterogeneity of parameters with a multiple trait approach. Heterogeneity of (co)variance components (VC) by sex is accounted for in national genetic evaluations for Simmental cattle. Completely reported data were split into bull, heifer, and steer populations to obtain VC estimates. Estimates of direct-maternal genetic correlation were negative, which suggests that selective reporting was not a cause of a negative correlation in Simmental data. However, analyzing only data for males does not account for selection on females and vice versa. Heterogeneous VC for sex were evaluated by analyzing Simmental data using a multiple trait model where male and female data were treated as two traits. Estimates of heritability of direct (maternal) effects were .19 (.07) and .25 (.12) and estimates of the direct-maternal genetic correlation were -.05 and -.20 for males and females, respectively. The multiple trait model fit the data better (P < .01) than the model under the assumption of homogeneous VC.     

Sulfur distribution in bacteriorhodopsin from multiple wavelength anomalous diffraction near the sulfur K-edge with synchrotron x-ray radiation

Estimates of variance components for test day records in an animal model that considered multiple traits over multiple lactations were calculated using REML methodology. Test day records were classified into 11 periods within first and later lactations. Missing ancestors in the relationship matrix were classified in genetic groups. Data were collected from Costa Rican dairy farms. Estimates of components for total and additive genetic variance were clearly heterogeneous during the lactation. Heritabilities for traits in later parities were slightly higher than those for traits in first parity. Heritabilities were highest for records of midlactation. Phenotypic and genetic correlations for adjacent test days were close to 1. Phenotypic correlations were lower than genetic correlations. Heterogeneity of variances during the lactation suggests the adequacy of the multiple-trait test day model to describe milk yield during the lactation. When missing ancestors were allocated to a single base population instead of genetic groups, the estimates of residual variance were lower, and the estimates of genetic variance and genetic correlations were higher. When standardized records were used instead of actual test day records, the estimates of residual and total variance were lower, and the estimates of genetic variance were higher. Consequently, estimates of heritability and genetic correlations were also higher. Use of standardized data obtained by interpolation procedures is not advised for estimation of genetic variance components in a test day model.     

Genetic and environmental factors in relative body weight and human adiposity

We review the literature on the familial resemblance of body mass index (BMI) and other adiposity measures and find strikingly convergent results for a variety of relationships. Results from twin studies suggest that genetic factors explain 50 to 90% of the variance in BMI. Family studies generally report estimates of parent-offspring and sibling correlations in agreement with heritabilities of 20 to 80%. Data from adoption studies are consistent with genetic factors accounting for 20 to 60% of the variation in BMI. Based on data from more than 25,000 twin pairs and 50,000 biological and adoptive family members, the weighted mean correlations are .74 for MZ twins, .32 for DZ twins, .25 for siblings, .19 for parent-offspring pairs, .06 for adoptive relatives, and .12 for spouses. Advantages and disadvantages of twin, family, and adoption studies are reviewed. Data from the Virginia 30,000, including twins and their parents, siblings, spouses, and children, were analyzed using a structural equation model (Stealth) which estimates additive and dominance genetic variance, cultural transmission, assortative mating, nonparental shared environment, and special twin and MZ twin environmental variance. Genetic factors explained 67% of the variance in males and females, of which half is due to dominance. A small proportion of the genetic variance was attributed to the consequences of assortative mating. The remainder of the variance is accounted for by unique environmental factors, of which 7% is correlated across twins. No evidence was found for a special MZ twin environment, thereby supporting the equal environment assumption. These results are consistent with other studies in suggesting that genetic factors play a significant role in the causes of individual differences in relative body weight and human adiposity.     

Nonshared environment: A theoretical, methodological, and quantitative review.

When genetic similarity is controlled, siblings often appear no more alike than individuals selected at random from the population. Since R. Plomin and D. Daniels' seminal 1987 review, it has become widely accepted that the source of this dissimilarity is a variance component called nonshared environment. The authors review the conceptual foundations of nonshared environment, with emphasis on distinctions between components of environmental variance and causal properties of environmental events and between the effective and objective aspects of the environment. A statistical model of shared and nonshared environmental variables is developed. A quantitative review shows that measured nonshared environmental variables do not account for a substantial portion of the nonshared variability posited by biometric studies of behavior. Other explanations of the preponderance of nonshared environmental variability are suggested. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structure of the Drosophila projectin protein: isoforms and implication for projectin filament assembly

The rare alleles model of mutation-selection balance (MSB) hypothesis for the maintenance of genetic variation was evaluated for two quantitative traits, ovariole number and body size. Mutational variances (VM) for these traits, estimated from mutation accumulation lines, were 4.75 and 1.97 x 10(-4) times the environmental variance (VE), respectively. The mutation accumulation lines were studied in three environments to test for genotype x environment interaction (GEI) of new mutations; significant mutational GEI was found for both traits. Mutations for ovariole number have a quadratic relationship with competitive fitness, suggesting stabilizing selection for the trait; there is no significant correlation between mutations for body size and competitive fitness. Under MSB, the ratio of segregating genetic variance, VG, to mutational variance, VM, estimates the inverse of the selection coefficient against a heterozygote for a new mutation. Estimates of VG/VM for ovariole number and body size were both approximately 1.1 x 10(4). Thus, MSB can explain the level of variation, if mutations affecting these traits are under very weak selection, which is inconsistent with the empirical observation of stabilizing selection, or if the estimate of VM is biased downward by two orders of magnitude. GEI is a possible alternative explanation.     

Subjective well-being is heritable and genetically correlated with dominance in chimpanzees (Pan troglodytes).

The hypothesis that subjective well-being (SWB) is heritable and genetically correlated with Dominance was tested using 128 zoo chimpanzees. Dominance was a chimpanzee-specific personality factor including items reflecting Extraversion and low Neuroticism. SWB was measured with a 4-item scale. The best behavior genetic model included additive genetic and nonshared environmental effects for SWB and Dominance, marginal maternal effects for SWB, a high genetic correlation, and a low nonshared environmental correlation. Results indicated that the shared variance between SWB and Dominance was a consequence of common genes and that the unique variance between SWB and Dominance was a consequence of the nonshared environment. These findings indicate that common genes may underlie the correlation between human personality factors and SWB. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ontogenetic changes in genetic regulation of fetal morphometrics in baboons (Papio hamadryas subspp.)

It is known that different genes are expressed during ontogeny; however, it is unclear how variation in that expression is associated with changes in growth patterns. The objective of this study is to assess how genetic variation in fetal morphology changes with ontogeny in baboons. Longitudinal measures of the head and femur (60 to 180 days gestation) were available for 892 pregnancies. We used a genetic model that allowed both the genetic and environmental variances (sigma 2G and sigma 2E) to change with age and estimated genetic and environmental correlations (rho G and rho E) between measurements at different ages. The results indicate a significant increase in the genetic variance for biparietal diameter and femur length but not for head circumference and fronto-occipital diameter. The rho G estimates for all measures decreased as the age between measures increased from 0 to 120 days, indicating that different groups of genes are expressed early in gestation and late in gestation. The rho E estimates dropped rapidly from 1 to 0 for all measures, indicating temporally localized environmental influences on fetal growth. Thus fetal morphometrics are significantly heritable and those genes that influence them show age-specific expression during ontogeny.     

Analytic methods for seed models with genotype x environment interactions

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.     

Modelling the cause of dependency with application to filaria infection

A preliminary data set is analysed containing filaria specific IgG4 and IgE levels and the presence of microfilariae of 196 people from families of a village in Indonesia. Since filaria infected people may not be microfilaria positive, a filaria infection can easily be missed. First, the probabilities of a filaria infection are estimated from the IgG4 levels and the presence of microfilariae using the EM algorithm. By dichotomizing these probabilities, infection status is estimated for each person. Then for IgG4, IgE and infection status, the correlations between observations are modelled. Three causes for a correlation are considered, namely genetic, intra-uterine or environmental effects. The correlation structure of the genetic and the intra-uterine effects are quite similar and consequently it may be difficult to disentangle them. Empirical variograms are plotted and the various variance components are estimated by maximizing the log-likelihood. For infection status an environmental effect is found and for IgG4 and IgE levels genetic effects are found.     

Genotype-environment interaction and correlation in the analysis of human behavior.

Two issues that complicate behavioral genetic analyses are the interaction and correlation between genetic and environmental influences. In the present report, the effects of genotype-environment interaction and correlation on behavioral genetic studies (twin and adoption studies) are examined. The analysis suggests that genotype-environment interaction may bias twin study estimates of genetic and environmental influence but need not affect adoption studies. On the other hand, genotype-environment correlation may affect both twin and adoption study estimates of genetic and environmental influence, the direction of the effect depending on the sign of the correlation. New tests of genotype-environment interaction and correlation, using adoption data, are proposed. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The heritability of intelligence: Neither known nor unknown.

Comments on "The Genes and Intelligence" section of the U. Neisser et al (see record 83-26553) American Psychological Association (APA) Task Force Report on Intelligence. At issue is the discussion of partitioning phenotypic variance, a discussion which the author claims is not complete. A more detailed review of variance components would have great implications for the interpretation of heritability coefficients applied to intelligence. The vast differences between populations in environmental variability and the resulting extreme relativity of heritability estimates for intelligence would make them of limited use for prediction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bottleneck effect on genetic variance. A theoretical investigation of the role of dominance

The phenomenon that the genetic variance of fitness components increase following a bottleneck or inbreeding is supported by a growing number of experiments and is explained theoretically by either dominance or epistasis. In this article, diffusion approximations under the infinite sites model are used to quantify the effect of dominance, using data on viability in Drosophila melanogaster. The model is based on mutation parameters from mutation accumulation experiments involving balancer chromosomes (set I) or inbred lines (set II). In essence, set I assumes many mutations of small effect, whereas set II assumes fewer mutations of large effect. Compared to empirical estimates from large outbred populations, set I predicts reasonable genetic variances but too low mean viability. In contrast, set II predicts a reasonable mean viability but a low genetic variance. Both sets of parameters predict the changes in mean viability (depression), additive variance, between-line variance and heritability following bottlenecks generally compatible with empirical results, and these changes are mainly caused by lethals and deleterious mutants of large effect. This article suggests that dominance is the main cause for increased genetic variances for fitness components and fitness-related traits after bottlenecks observed in various experiments.     

Genetic and environmental components of "environmental" influences.

Proposes a model of the effects of genotype-environment correlation in nonadoptive families and adoptive families that formalizes the possibility that the correlation between measures of the environment and of child development may be mediated genetically as well as environmentally. The model assumes that adoptive and nonadoptive homes are comparable in terms of means and variances of the environmental measures and that selective placement, the matching of birth parents and adoptive parents on the trait in question, is negligible. Data from classical adoption studies and new data on 185 adoptees (aged 12–24 mo) and 162 nonadoptive families from the Colorado Adoption Project (CAP) are used to illustrate the model and to provide quantitative estimates of the genetic and environmental components of environment-behavior correlations. Instruments used in the CAP study included the Home Observation for Measurement of the Environment, the Family Environment Scale, and the Childhood Temperament Inventory. 113 environment-infant correlations in nonadoptive families and 113 correlations in adoptive families constitute the basic data that were used to assess the extent to which the environment-development correlations in nonadoptive families exceed those in adoptive families. The results from the CAP suggest that correlations between widely used environmental measures and major domains of infant development are mediated genetically to a substantial extent—approximately 50% on the average. (35 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

In vitro study of enzymatic degradation of biological tissues fixed by glutaraldehyde or epoxy compound

RATIONALE AND OBJECTIVES: The authors performed this study to clarify and systematize the large number of variances and correlations observable with variance-component models of receiver operating characteristic (ROC) index estimates. MATERIALS AND METHODS: The authors present a variance-component model for ROC index estimates (and for differences between estimates) and show correspondences between the method of experimental replication and the random components in the model. The authors introduce a notation that identifies both the method of replication and, when examining estimate differences, the estimate pairing scheme. RESULTS: For models with three factors (modality, reader, case sample), the authors delineated four methods of replication and eight pairing schemes for generating estimate differences. For each of the resulting 32 replication-pairing combinations, the authors gave expressions for the variance of the difference and for the correlation between the two ROC index estimates. CONCLUSION: The variance-component approach is a useful statistical tool for modeling different sources of variation that contribute to the overall variance of ROC data and index estimates derived from those data.     

On the sampling variance of intraclass correlations and genetic correlations

Widely used standard expressions for the sampling variance of intraclass correlations and genetic correlation coefficients were reviewed for small and large sample sizes. For the sampling variance of the intraclass correlation, it was shown by simulation that the commonly used expression, derived using a first-order Taylor series performs better than alternative expressions found in the literature, when the between-sire degrees of freedom were small. The expressions for the sampling variance of the genetic correlation are significantly biased for small sample sizes, in particular when the population values, or their estimates, are close to zero. It was shown, both analytically and by simulation, that this is because the estimate of the sampling variance becomes very large in these cases due to very small values of the denominator of the expressions. It was concluded, therefore, that for small samples, estimates of the heritabilities and genetic correlations should not be used in the expressions for the sampling variance of the genetic correlation. It was shown analytically that in cases where the population values of the heritabilities are known, using the estimated heritabilities rather than their true values to estimate the genetic correlation results in a lower sampling variance for the genetic correlation. Therefore, for large samples, estimates of heritabilities, and not their true values, should be used.     

Contribution of age, genes, and environment to the relationship between perceptual speed and cognitive ability.

The aim of this study was to examine genetic influences on cognitive ability in adulthood in the context of the relationship between perceptual speed and cognitive aging. Quantitative genetic analysis of data from the Swedish Adoption Twin Study of Aging allowed for estimation of the contribution of age, genetic, and environmental effects to the variance in a latent cognitive factor and to the covariance between the cognitive factor and perceptual speed. The sample included 292 pairs of monozygotic and dizygotic twins, both reared together and reared apart, ranging in age from 40 to 84 years. Analysis of components of total variance in the cognitive factor indicated that 90% of the age-related variance in the cognitive factor was shared with perceptual speed and 70% of the genetic variance in the cognitive factor was shared with perceptual speed. The correlation between the speed and cognitive factors was primarily genetically mediated. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Recovering components of variance from differential ratings of behavior and environment in pairs of relatives.

Evidence from genetic studies underscores the importance of examining the within-family environment and its association with genetic differences among siblings in influencing children's development. Simulated and published data are analyzed to illustrate the contribution of genetic and environmental factors to differential ratings of behavioral and environmental differences within families. Comparison of the mean differential ratings within various types of pairs is not an adequate index of the underlying genetic and environmental variance components. However, on the assumption that differential ratings are a linear function of underlying trait differences, it is a simple matter to recover within-family statistics that offer a more legitimate basis for estimating genetic and environmental components of variance within families. The assumptions and dangers underlying any analysis of differential ratings are noted. (PsycINFO Database Record (c) 2010 APA, all rights reserved)