Genetic evaluation by BLUP in two-breed terminal crossbreeding systems under dominance

To obtain estimates of breeding values by BLUP using Henderson's mixed-model equations, it is necessary to invert the covariance matrix for each random effect in the model. In a model in which the genotypic value is included as a random effect (genotypic model), it is necessary to invert the genotypic covariance matrix. Under additive inheritance, the inverse of the genotypic covariance matrix can be computed efficiently. Under dominance inheritance, however, an efficient method to invert the genotypic covariance matrix has not yet been developed, especially for crossbred populations. Thus, the use of a genotypic model for BLUP is not suitable for genetic evaluation in large, crossbred populations. We present an equivalent model in which the genotypic effect is partitioned into additive and dominance effects. With this equivalent model, methods used for within-breed genetic evaluation by BLUP can be used for a two-breed terminal cross under dominance.     

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.     

Influence of dominance relationships on the estimation of dominance variance with sire-dam subclass effects

Two data sets from the USDA Livestock and Range Research Laboratory were analyzed to study dominance variance and the influence of dominance relationships. The first consisted of 4,155 birth weight (3,884 weaning weight) records of inbred USDA Line 1 Herefords. The second consisted of 8,065 birth weight (7,380 weaning weight) records from a line-cross experiment with five lines. Two models were used. Both included fixed effects of year-sex of calf and age of dam, and covariates for calving date, inbreeding of animal, and inbreeding of dam. For the second set, additional covariates were line composition and heterozygosity coefficients. Random effects were direct and maternal additive genetic, maternal permanent environment, sire-dam subclass, and residual. Model 1 considered sire-dam subclasses unrelated. Model 2 related sire-dam subclasses with a parental dominance relationship matrix. Variance components were estimated using REML. Differences between estimates with Model 1 and 2 were unimportant except for dominance variance. For the first data set, estimates with Model 2 of relative genetic direct and maternal variances, direct-maternal correlation, permanent environment, and dominance variances for birth weight were .35, .13, -.02, .03, and .25, respectively, and they were .39, .11, .04, .06 and .14 for the second data set. For weaning weight, the first data set estimates were .20, .15, -.37, .19, and .11, respectively, and they were .16, .20, -.07, .18, and .18 for the second data set. Changes, decreases and increases, in estimates of dominance variances may be due to increased information from relationships and family types other than full-sibs. The assumption of unrelated sire-dam subclasses might not be appropriate for estimation of dominance variance in populations with many dominance relationships among sire-dam classes.     

Variances of direct genetic effects, maternal genetic effects, and cytoplasmic inheritance effects for milk yield, fat yield, and fat percentage

Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.     

Epistasis and its contribution to genetic variance components

We present a new parameterization of physiological epistasis that allows the measurement of epistasis separate from its effects on the interaction (epistatic) genetic variance component. Epistasis is the deviation of two-locus genotypic values from the sum of the contributing single-locus genotypic values. This parameterization leads to statistical tests for epistasis given estimates of two-locus genotypic values such as can be obtained from quantitative trait locus studies. The contributions of epistasis to the additive, dominance and interaction genetic variances are specified. Epistasis can make substantial contributions to each of these variance components. This parameterization of epistasis allows general consideration of the role of epistasis in evolution by defining its contribution to the additive genetic variance.     

The fine structural development of preimplantation mouse parthenotes

Crossfostering was performed using lines selected for increased 6-week body weight (H6) and increased 3-to 6-week postweaning gain (M16) and their reciprocal F1 crosses as nurse dams in the selected crossfostering group, and base population controls (C2, ICR) and their reciprocal F1 crosses in the control group. The offspring suckled were H6, M16 and F2 crosses in the selected group, and C2, ICR and their F2 crosses in the control group. Measurements taken on the individual offspring were body weights at birth (WB) and at 12, 21, 31, 42, and 63 days (W12, W21, W31, W42 and W63, respectively) and weight gains between adjacent ages (GB-12, G12-21, G21-31, G31-42 and G42-63, respectively). Least squares constants fitted to populations of genetic and nurse dams were used to calculate specific linear contrasts. Correlated responses to selection in average direct genetic effects were significant and positive for all traits examined in both H6 and M16, while the correlated responses in average maternal genetic effects were negative in M16 and negligible in H6. Selection response was primarily due to average direct genetic effects while the contribution of average maternal genetic effects was of secondary importance. The response in average direct genetic effects was smaller in M16 for postweaning weights (W31, W42 and W63). The correlated responses in average maternal genetic effects were consistently smaller in M16 than in H6. Direct heterosis was significant for all traits except for G12-21 and G42-63 in the control group, whereas maternal heterosis was significant for weight gains at early ages and for body weights. Direct heterosis tended to be larger than maternal heterosis in both selected and control crosses. Percent direct heterosis for body weight was larger in the selected crosses relative to the control crosses through 31 days of age, but the trend was reversed by 63 days. Percent maternal heterosis was consistently larger in the selected crosses.     

Covariance components and prediction for additive and nonadditive preweaning growth genetic effects in an Angus-Brahman multibreed herd

Estimates of covariances and sire expected progeny differences of additive and nonadditive direct and maternal genetic effects for birth and weaning weights were obtained using records from 1,581 straightbred and crossbred calves from the Angus-Brahman multibreed herd at the University of Florida. Covariances were estimated by Restricted Maximum Likelihood, using a Generalized Expectation-Maximization algorithm applied to multibreed populations. Estimates of heritabilities and additive genetic correlations for straightbred and crossbred groups were within the ranges of values found in the literature for these traits. Maximum values of interactibilities (ratios of nonadditive genetic variances to phenotypic variances) and nonadditive correlations were somewhat smaller than heritabilities and additive genetic correlations. Sire additive and total direct and maternal genetic predictions for birth and weaning weight tended to increase with the fraction of Brahman alleles, whereas nonadditive direct and maternal genetic predictions were similar for sires of all Angus and Brahman fractions. These results showed that it is feasible to evaluate sires for additive and nonadditive genetic effects in a structured multibreed population. Data from purebred breeders and commercial producers will be needed to accomplish the same goal at a national level.     

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.     

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.     

Inheritance of learning ability in mice: A diallel-environmental analysis.

Raised 189 male mice from 4 inbred strains and their F1 hybrid crosses under either standard laboratory conditions or mildly stressful conditions. Subsequent performance in appetitive -maze and water-escape learning was analyzed by quantitative genetic methods. The -maze time scores and water-escape times showed large additive genetic and nonadditive genetic components. Environmental stress had a marginally significant effect only on water-escape times, and there was no indication of a Genotype * Environment interaction. Both heterosis and developmental homeostasis were found on water-escape times. Genetic correlations were high between the 2 -maze measures (time and errors), which in turn showed lower correlations with water-escape times. (21 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Biometrical genetics and behavior: Reanalysis of published data.

The techniques which can be used in the analysis of quantitative data by the methods of biometrical genetics are outlined. The need for achieving a suitable scale is noted. Data provided by experiments in psychogentics which are amenable to this type of analysis are reanalized in terms of additive, dominance and interaction components of variance. From Psyc Abstracts 36:01:3DP37B. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A new wave of behavior genetic modeling using covariance structure analysis

A number of useful methods for analyzing covariance structure have been proposed in the studies of human behavior genetics, reflecting the fact that the behavior genetic studies are one of the main origins of covariance structure model. In this paper, I review recent progress on methodology for behavior genetic studies of twins and families from the standpoint of the structural equation modeling. Especially, genetic ACE (additive genetic, common environment and random environment) model, multivariate ACE model, genetic factor analysis model and twin-parent model are focused upon. This review also discusses how to construct applied structural equation models which are useful for psychological research.     

The use of covariance functions and random regressions for genetic evaluation of milk production based on test day records

In the analysis of test day records for dairy cattle, covariance functions allow a continuous change of variances and covariances of test day yields on different lactation days. The equivalence between covariance functions as an infinite dimensional extension of multivariate models and random regression models is shown in this paper. A canonical transformation procedure is proposed for random regression models in large-scale genetic evaluations. Two methods were used to estimate covariance function coefficients for first parity test day yields of Holsteins: 1) a two-step procedure fitting covariance functions to matrices with estimated genetic and residual covariances between predetermined periods of lactation and 2) REML directly from data with a random regression model. The first method gave more reliable estimates, particularly for the periphery of the trajectory. The goodness of fit of a random regression model based on covariables describing the shape of the lactation curve was nearly the same as random regression on Legendre polynomials. In the latter model, two and three regression coefficients were sufficient to fit the covariance structure for additive genetic and permanent environment, respectively. The eigenfunction pattern revealed the possibility of selection for persistency. Covariance functions can be usefully implemented in large-scale test day models by means of random regressions.     

Age-specific inbreeding depression and components of genetic variance in relation to the evolution of senescence

Two major theories of the evolution of senescence (mutation accumulation and antagonistic pleiotropy) make different predictions about the relationships between age, inbreeding effects, and the magnitude of genetic variance components of life-history components. We show that, under mutation accumulation, inbreeding decline and three major components of genetic variance are expected to increase with age in randomly mating populations. Under the simplest version of the antagonistic pleiotropy model, no changes in the severity of inbreeding decline, dominance variance, or the genetic variance of chromosomal homozygotes are expected, but additive genetic variance may increase with age. Age-specific survival rates and mating success were measured on virgin males, using lines extracted from a population of Drosophila melanogaster. For both traits, inbreeding decline and several components of genetic variance increase with age. The results are consistent with the mutation accumulation model, but can only be explained by antagonistic pleiotropy if there is a general tendency for an increase with age in the size of allelic effects on these life-history traits.     

Dominance variance in Fisher's model of assortative mating

It is argued that there is some confusion in the literature concerning the effect of assortative mating on dominance variance. It is shown that in Fisher's model of assortative mating additive deviations of one factor are correlated with additive deviations of another and that this correlation is responsible for the increase in genetic variance. The dominance deviations of one factor are independent of the dominance, as well as of the additive deviations of a second factor. It is shown that in Fisher's model of assortative mating and to the approximation used by him, the dominance variance does not change under assortative mating.     

Effects of maternal employment on lower-class boys.

Repeated direct observations of 149 boys from 140 intact, lower-class families during a period of approximately 5 years were used to check differences in family structure and child rearing techniques of 45 working and 95 nonworking mothers. Comparisons showed no statistically significant differences in social status, father's stability, parental dominance, or emotional tone of parental interaction. The effect of maternal employment on personality development seemed largely dependent on the family milieu: (a) In stable homes, maternal employment appears to decrease the father's status and sibling rivalry and to increase sexual anxiety. (b) In unstable homes, maternal employment tends to decrease the father's status and sibling rivalry while increasing dependency and criminality. The authors conclude that maternal employment has different meanings to the child in stable as compared to unstable homes: in the former, it appears only to equalize status between the sexes and make sex role adjustment more difficult; in the latter, it may be interpreted by the child as rejection. (21 ref.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A model for interpreting genetic correlations with estimates of parameters.

Presents a general additive model for kinship correlational structures which includes genetic, environmental, covariance, and measurement error components. The properties and assumptions of the model and other models which are viewed as special cases are discussed. A procedure is described for estimating the model parameters from sample correlation coefficients. The procedure results in numerical estimates of the ratio of genetic to environmental variance, estimates of the correlation between genetic and environmental factors, and estimates of the correlation between environments. A simple procedure for partitioning a correlation coefficient into its variance components is suggested. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Estimation of dominance variance in purebred Yorkshire swine

We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11.     

Genetic selection strategies: computer modeling

There are four primary factors to consider in genetic selection strategies: 1) accuracy of selection, 2) selection intensity, 3) effective population size, and 4) mating system. Current theory indicates that optimum response to selection is achieved by maximizing the first three factors and using a mating systems that allows optimization of reproductive characteristics in dam lines and production characteristics in sire lines. However, with limited resources, compromises among the first three factors are needed. Simulations are useful for examining those compromises. Unrealistic simplifying assumptions are necessary for analytic theoretical results and thus do not address real world breeding problems. Using simulations, the relationship between selection accuracy, which is increased by use of family selection indices or Best Linear Unbiased Prediction (BLUP), and response to selection was examined. Results show that those procedures place a great restriction on effective population size, which offsets most of their advantage, i.e., there is too little emphasis on effective population size. A revision of the methodology and a reappraisal of the results of selection theory for optimization of genetic response is required. Another relationship that is of fundamental importance in breeding programs is that between selection intensity and effective population size. Analytical results for the additive case have been developed but have never been extended to heterotic traits. A gene level simulation program was developed to examine that relationship. Results show that the optimal selection strategy depends on the trait being selected. For additive traits and in the short term (20 generations), one should maximize selection intensity. For heterotic traits, an intermediate proportion (25% of each sex) gives optimal response. In all breeding strategies, primary attention must be given to the rate of inbreeding, which is increased by increasing either accuracy of selection or selection intensity. Inbreeding reduces response to selection in two ways. First, for both additive and nonadditive traits, inbreeding is a measure of the amount of random genetic drift that has occurred. Genetic drift causes loss of favorable alleles. Once lost, those alleles can never be recovered and thus genetic drift lowers the selection limit. Second, for heterotic traits, inbreeding results in a depression of the mean caused by directional dominance.     

Genetic and environmental components of thyroxine variation in Mennonites from Kansas and Nebraska

Thyroxine is an endocrine hormone that regulates cellular and organismic metabolism. Current research on thyroxine has primarily examined its adaptive potential and genetic inheritance patterns. To date, no studies have attempted to investigate the interaction between the genetic and environmental components of thyroxine variation. This approach is useful because hormones are on feedback regulation; thus interaction occurs between the environment and gene expression. The purposes of this research are to characterize the genetic and environmental components of thyroxine variation using univariate statistics and to estimate the genetic and cultural heritabilities through path analysis. For univariate analyses, analyses of variance are used to determine whether or not age, sex, or community affiliation are covariates of thyroxine level. Significant differences existed in thyroxine level based on sex and community affiliation (p < 0.05). The genetic and environmental components of thyroxine variation were partitioned through path analysis. Heritability was estimated at 0.317 +/- 0.109 for the genetic component and at 0.060 +/- 0.029 for the environmental component. The environmental variables that contributed to the variation in thyroxine level were caffeine consumption, blood calcium level, and biceps skinfold thickness.