Direct-maternal Covariance Research Articles

Maternal effects and its importance in the genetic evaluations of preweaning live weight traits of beef cattle. A review.

Maternal effects in cattle genetics are defined as the causal influence of the phenotype or maternal genotype on the offspring's phenotype by effects occurring when the genetic and environmental characteristics of the mother influence the phenotype of the offspring beyond the direct inheritance of genes. Its relevance has been strongly described in genetic models focused on the genetic improvement of preweaning traits in cow-calf beef cattle production systems. Here, basic concepts and the importance of maternal effects when using linear and animal model procedures for genetic evaluations of growth and live-weight traits in beef cattle are reviewed and discussed. A brief history of estimation methods from classical studies to recent studies used for the development of animal models for studying maternal effects is also provided. Some important biometric concepts for maternal effect estimation are described, and the antagonism between direct genetic effects and maternal effects, its biological basis, and sources of error in the estimation of direct genetic and maternal covariance are discussed. Finally, some genomic perspectives are presented.

Estimation and consequences of direct-maternal genetic and environmental covariances in models for genetic evaluation in broilers

BackgroundMaternal effects influence juvenile traits such as body weight and early growth in broilers. Ignoring significant maternal effects leads to reduced accuracy and inflated predicted breeding values. Including genetic and environmental direct-maternal covariances into prediction models in broilers can increase the accuracy and limit inflation of predicted breeding values better than simply adding maternal effects to the model. To test this hypothesis, we applied a model accounting for direct-maternal genetic covariance and direct-maternal environmental covariance to estimate breeding values.ResultsThis model, and simplified versions of it, were tested using simulated broiler populations and then was applied to a large broiler population for validation. The real population analyzed consisted of a commercial line of broilers, for which body weight at a common slaughter age was recorded for 41 selection rounds. The direct-maternal genetic covariance was negative whereas the direct-maternal environmental covariance was positive. Simulated populations were created to mimic the real population. The predictive ability of the models was assessed by cross-validation, where the validation birds were all from the last five selection rounds. Accuracy of prediction was defined as the correlation between the predicted breeding values estimated without the phenotypic records of the validation population and a predictor. The predictors were the breeding values estimated using all the phenotypic information and the phenotypes corrected for the fixed effects, and for the simulated data, the true breeding values. In the real data, adding the environmental covariance, with or without also adding the genetic covariance, increased the accuracy, or reduced deflation of breeding values compared with a model not including dam–offspring covariance. Nevertheless, in the simulated data, reduction in the inflation of breeding values was possible and was associated with a gain in accuracy of up to 6% compared with a model not including both forms of direct-maternal covariance.ConclusionsIn this paper, we propose a simple approach to estimate the environmental direct-maternal covariance using standard software for REML analysis. The genetic covariance between dam and offspring was negative whereas the corresponding environmental covariance was positive. Considering both covariances in models for genetic evaluation increased the accuracy of predicted breeding values.

Estimation of nonadditive and additive genetic effects on growth traits of Horro cattle.

The estimation of nonadditive genetic effects plays a significant role in the accuracy of estimated breeding values for growth traits. Data for estimation of individual and maternal heterosis of crossbreed cattle in Ethiopia are limited to research institutions and universities. This paper aimed to estimate the crossbreeding effects for growth traits of Holstein Friesian × Horro and Jersey × Horro crossbreds in Ethiopia. The data included pedigree and weight data of animals born between 1980 and 2008. Heritability of growth traits was estimated using restricted maximum likelihood (ASREML). However, the additive genetic, maternal, and heterosis effects for growth traits of crossbred animals were estimated using the crossbreeding effects (CBE3) package by fitting Kinghorn's Model one. The direct and maternal heritability estimates for 1-year weight with the model that included the direct maternal covariance were 0.77 ± 0.12 and 0.26 ± 0.09, respectively. Individual heteroses estimated for Holstein Friesian × Horro and Jersey × Horro were significantly high and positive for 1-year weight (21.6 ± 6.7 and 26.0 ± 3.9kg), preweaning average daily gain (27.4 ± 26 and 28.9 ± 15g), and postweaning average daily gain (68.8 ± 16.6 and 61.8 ± 9.9g), respectively. The maternal additive genetic effect for growth traits was mostly positive; therefore, it may be preferable to use crossbred cows from purebred dams instead of crossbred cows from crossbred dams. The significantly higher heterosis and additive genetic parameters in Holstein Friesian × Horro crossbreds indicated that these crossbreds may be preferable to Jersey × Horro crossbreds in areas occupied by Horro cattle.

Single-step genomic evaluation of lambing ease in Australian terminal sire breed sheep

Context Australian sheep breeding values (ASBVs) for the categorical trait of lambing ease are routinely estimated by Sheep Genetics via a threshold model. This has been pedigree-only, and has not utilised genomic information. Aim The present study aimed to update the genetic evaluation model and parameters for lambing ease for terminal sire sheep (dominated by White Suffolk and Poll Dorset breeds). The model includes correlations with birthweight and gestation length. Cross-validation was used to determine the value of the improved models and the inclusion of genomic information. Methods New data-preparation pipelines were developed to accommodate improved data-filtering methods and contemporary group construction. Genetic parameters, including correlations among traits, were estimated using continuous and threshold models, with various combinations of effects in mixed animal models. Cross-validation of breeding values was performed against progeny performance, by using forward prediction. Key results The increased volume of data, improved data preparation steps and enhanced evaluation software now allow a more complex model to be fitted, including maternal, sire by flock-year and genetic group effects, which were significant for all traits, along with the inclusion of multiple sire groups in the pedigree. However, the inclusion of the direct-maternal covariance and sire by flock-year terms resulted in unrealistically inflated estimates of some components, and thus the final covariance matrices required some adjustments. Cross-validation of breeding values was performed against progeny performance using forward prediction. For all traits, the phenotype accuracies and estimated breeding value correlations were higher from the new model without genomics than were those from the current routine evaluation. The benefit from including genomic information based on cross-validation is minimal currently but is expected to improve as the size of the reference population grows. Further work is required to define acceptable data-quality thresholds for the construction of datasets for routine breeding value estimation. Conclusions The new model and parameters resulted in ASBVs with an improved predictive ability, with increased accuracy and reduced bias compared with the current analysis. Furthermore, a small increase in accuracy was observed for all traits from utilising genomic information in the model. Implications The new genetic evaluation procedures and models will be used to update those being applied in the routine Sheep Genetics evaluation system and also support further index development for the terminal sire breeds in Australia.

Estimates of variance components and heritability using different animal models for growth, backfat, litter size, and healthy birth ratio in Large White pigs

This study compared the estimates of variance components using various animal models for Large White pigs. The traits included three production traits, birth weight (BW), age at 100 kg (Age_100), and backfat thickness at 100 kg (BF_100), and two reproduction traits, number of total born (NTB) and the ratio of healthy births (RHB). Five models including or ignoring common litter environmental effects, maternal effects, and the direct-maternal covariance (σam) were used for this study. The results showed that the model including all terms, or including all terms except σam, yielded the best-fitting result. The direct variance and heritability were overestimated when the model ignored all previously listed effects, especially for production traits. When all terms were modeled, the direct heritability estimates ([Formula: see text] ± standard error) were 0.038 ± 0.008, 0.216 ± 0.022, 0.416 ± 0.023, 0.066 ± 0.013, and 0.049 ± 0.007 for BW, Age_100, BF_100, NTB, and RHB, respectively. The common litter effects reached statistical significance for all traits, and maternal heritability reached statistical significance for three production traits. The direct-maternal correlations were negative for all traits but only reached statistical significance for BW. These results indicate that using a more complex model may result in more accurate estimation of variance components in Large White pigs.

Estimates of genetic parameters for worm resistance, wool and growth traits in Merino sheep of Uruguay

The genotype of an individual and the environment as the maternal ability of its dam have substantial effects on the phenotype expression of many production traits. The aim of the present study was to estimate the (co)variance components for worm resistance, wool and growth traits in Merino sheep, testing the importance of maternal effects and to determine the most appropriate model for each trait. The traits analyzed were Greasy Fleece Weight (GFW), Clean Fleece Weight (CFW), average Fibre Diameter (FD), Coefficient of Variation of FD (CVFD), Staple Length (SL), Comfort Factor (CF30), Weaning Weight (WWT), Yearling Body Weight (YWT) and Faecal worm Egg Count (FEC). The data were recorded during a 15-year period from 1995 to 2010, from Uruguayan Merino stud flocks. A Bayesian analysis was performed to estimate (co)variance components and genetic parameters. By ignoring or including maternal genetic or environmental effects, five different univariate models were fitted in order to determine the most effective for each trait. For CVFD and YWT, the model fitting the data best included direct additive effects as the only significant random source of variation. For GFW, CFW, FD, SL and CF30 the most appropriate model included direct-maternal covariance; while for FEC included maternal genetics effects with a zero direct-maternal covariance. The most suitable model for WWT included correlated maternal genetic plus maternal permanent environmental effects. The estimates of direct heritability were moderate to high and ranged from 0.15 for log transformed FEC to 0.74 for FD. Most of the direct additive genetic correlation (rg) estimations were in the expected range for Merino breed. However, the estimate of rg between FEC and FD was unfavourable (−0.18±0.03). In conclusion, there is considerable genetic variation in the traits analyzed, indicating the potential to make genetic progress on these traits. This study showed that maternal effects are influencing most of traits analyzed, thus these effects should be considered in Uruguayan Merino breeding programs; since the implementation of an appropriate model of analysis is critical to obtain accurate estimates.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

BackgroundThe focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.MethodsData from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.Results and discussionOn average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.ConclusionsFor the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.

Contribution of direct and maternal genetic effects to life‐history evolution

Maternal effects are ubiquitous in nature. In plants, most work has focused on the effects of maternal environments on offspring trait expression. Less is known about the prevalence of genetic maternal effects and how they influence adaptive evolution. Here, we used multivariate genetic models to estimate the contributions of maternal and direct genetic (co)variance, the cross-generation direct-maternal covariance, and M, the matrix of maternal effect coefficients, for life-history traits in Campanulastrum americanum, a monocarpic herb. Following a three-generation breeding design, we grew paternal half-sib families with full-sib relatives of each parent and measured juvenile and adult traits. Seed size was influenced exclusively by maternal environmental effects, whereas maternal genetic effects influenced traits throughout the life cycle, including strong direct and maternal additive genetic correlations within and between generations for phenological and size traits. Examination of M suggested that both juvenile and adult traits in maternal plants influenced the expression of offspring traits. This study reveals substantial potential for genetic maternal effects to contribute to adaptive evolution including cross-generation direct-maternal correlations that may slow selection response, maternal effects on phenology that reinforce genetic correlations, and within- and between-generation genetic correlations that may influence life-history polymorphism.

Efeito da covariância genética aditivo-materna sobre estimativas de parâmetros genéticos e em avaliações genéticas de características de crescimento de animais Tabapuã

Avaliou-se o efeito da covariância genética aditiva direto-materna sobre estimativas de parâmetros genéticos e sobre a predição e a ordenação de valores genéticos de animais da raça Tabapuã. Os parâmetros genéticos foram estimados com base em 19646, 14276, 10663 e 6172 registros de pesos ao nascimento e ajustados para 205, 365 e 550 dias de idade em análises unicaracterística, utilizando o programa computacional MTDREML, pelo método da máxima verossimilhança restrita livre de derivadas por modelos animal com ou sem a inclusão da covariância. As estimativas da covariância genética aditiva direto-materna foram, respectivamente, -0,08; -0,22; -0,10 e 0,34, para os pesos ao nascer e ajustados para 205, 365 e 550 dias de idade. As herdabilidades diretas e maternas obtidas sob modelo com a inclusão da covariância genética direto-materna foram, respectivamente, 0,31 e 0,10; 0,20 e 0,17; 0,20 e 0,06 e 0,17 e 0,01, para os mesmos pesos, enquanto sem a inclusão foram, respectivamente, 0,31 e 0,09; 0,18 e 0,14; 0,20 e 0,05 e 0,18 e 0,02. Os valores de correlação de posto entre os valores genéticos preditos pelos modelos com e sem a inclusão foram 0,999; 0,992; 0,999 e 0,998. As correlações de posto entre os valores genéticos maternos foram 0,999; 0,985; 0,992 e 0,771. A inclusão da covariância genética aditiva direto-materna não influenciou as estimativas dos parâmetros genéticos e teve efeito inexpressivo na ordenação dos valores genéticos dos pesos de animais da raça Tabapuã.

Influence of population structure on estimates of direct and maternal parameters

The estimation of (co)variance components for multiple traits with maternal genetic effects was found to be influenced by population structure. Two traits in a closed breeding herd with random mating were simulated over nine generations. Population structures were simulated on the basis of different proportions of dams not having performance records (0, 0.1, 0.5, 0.8 and 0.9): three genetic correlations (-0.5, 0.0 and +0.5) between direct and maternal effects and three genetic correlations (0, 0.3 and 0.8) between two traits. Three ratios of direct to maternal genetic variances, (1:3, 1:1, 3:1), were also considered. Variance components were estimated by restricted maximum likelihood. The proportion of dams without records had an effect on the SE of direct-maternal covariance estimates when the proportion was 0.8 or 0.9 and the true correlation between direct and maternal effects was negative. The ratio of direct to maternal genetic variances influenced the SE of the (co)variance estimates more than the proportion of dams with missing records. The correlation between two traits did not have an effect on the SE of the estimates. The proportion of dams without records and the correlation between direct and maternal effects had the strongest effects on bias of estimates. The largest biases were obtained when the proportion of dams without records was high, the correlation between direct and maternal effects was positive, and the direct variance was greater than the maternal variance, as would be the situation for most growth traits in livestock. Total bias in all parameter estimates for two traits was large in the same situations. Poor population structure can affect both bias and SE of estimates of the direct-maternal genetic correlation, and can explain some of the large negative estimates often obtained.

Inclusão da covariância genética direta-materna no modelo para estimar parâmetros e predizer valores genéticos para ganho de peso em bovinos da raça Angus

Com o objetivo de estimar o efeito da inclusão da covariância genética direta-materna no modelo de análise sobre as estimativas de parâmetros genéticos e predição de valores genéticos (VG) para ganho médio diário do nascimento à desmama (GMDND) e da desmama ao sobreano (GMDDS), foram utilizados registros de 11.202 e de 4.665 animais da raça Angus, respectivamente, para GMDND e GMDDS. As (co)variâncias foram obtidas adotando-se um modelo animal que, para GMDND, incluiu os efeitos aleatórios genéticos aditivos diretos e maternos e residual, os efeitos fixos de grupo de contemporâneos à desmama, além das covariáveis idade da vaca ao parto (IV) e idade do animal à desmama e, para GMDDS, considerou os efeitos aleatórios descritos e os fixos de grupo de contemporâneos ao sobreano, além das covariáveis IV e idade do animal ao sobreano. Para ambos os modelos, foi considerado aleatório o efeito de ambiente permanente da vaca. As herdabilidades diretas estimadas para GMDND foram 0,25 não considerando e 0,55 considerando a covariância genética direta-materna; comportamento similar foi observado para a herdabilidade materna (0,07 e 0,22). Para GMDDS, as herdabilidades diretas estimadas foram similares: 0,21 não considerando a covariância e 0,22 quando a covariância foi considerada. O teste da razão de verossimilhança mostrou não haver diferença significativa, a 5% de probabilidade, entre os modelos adotados para ambas as características. As correlações entre os efeitos genéticos aditivos diretos e maternos foram negativas, tanto para GMDND quanto para GMDDS. As correlações de Spearman entre os ordenamentos dos reprodutores, de acordo com seus valores genéticos (rank correlation), obtidos incluindo e não incluindo a covariância entre os efeitos diretos e maternos no modelo de análise (0,88 para GMDND e 0,99 para GMDDS) sugerem que a inclusão da covariância genética direta-materna no modelo é relevante somente para GMDND.

Componentes de (co)variância e parâmetros genéticos de características de crescimento da raça Simental no Brasil

Informações de genealogia e produção, cedidas pela Associação Brasileira de Criadores da Raça Simental (ABCRS), relativas aos pesos desde o nascimento até um ano de idade, foram utilizadas para estimar, sob modelos alternativos, os componentes de variância e os parâmetros genéticos em animais da raça Simental no Brasil. A matriz de parentesco incluiu 25.812 animais dos quais 7587 com dados de produção. O modelo 1 contém, além do erro, o efeito genético direto. Os modelos seguintes contêm os componentes do modelo 1, mais o efeito permanente de ambiente materno (modelo 2), ou o componente genético materno (modelo 3), ambos os componentes (modelo 5), os componentes do modelo 3 mais a covariância entre os efeitos genéticos direto e materno (modelo 4) e todos os componentes citados (modelo 6). Os modelos foram comparados pelo teste de razão de verossimilhança pelo chi² (P<0,01). Os componentes de variância e os valores de herdabilidades, estimados para os efeitos direto e materno, foram decrescentes, desde o modelo 1 até o modelo 6, na razão direta em que o modelo incorpora mais efeitos aleatórios. Para a fase de aleitamento foi encontrada variância genética nula, entretanto, alto valor para a variância de ambiente permanente. Os efeitos maternos, genético e de ambiente permanente são importantes para a raça Simental no Brasil e devem ser considerados em programas de seleção. Entretanto, os valores mais elevados de herdabilidade materna, encontrados com modelos sem efeito de ambiente permanente, sugerem que o método utilizado não discrimina apropriadamente esses efeitos, oriundos de mesma fonte de variação.

Comparison of models to estimate maternal effects for weaning weight of Swiss Angus cattle fitting a sire×herd interaction as an additional random effect

Field data of Swiss Angus cattle were used to explore the consequences of including in the model additional random effects, such as maternal effects and a sire×herd interaction (SH), on the estimates of genetic parameters for weaning weight. Data were analysed using Restricted Maximum Likelihood (REML), applied to animal models comprising fixed effects of herd, year of birth, month of birth, sex, birth type, age of dam and age of calf at weaning. All investigated models included a random direct genetic effect, but differed for combinations of random maternal genetic and permanent environmental effects as well as for direct-maternal genetic covariance and for sire×herd interaction. The models including SH effect fitted the data significantly better (P<0.01) than those ignoring the interaction. Ignoring SH effect resulted in a strong negative correlation between additive direct and maternal effects. The models including SH resulted in reduced estimates of direct and maternal genetic variance and of direct-maternal genetic covariance and, consequently, in a less negative correlation between direct and maternal genetic effects. With the inclusion of SH effect in the model, the direct-maternal covariance was no longer statistically significant. The SH variance represented only 7% of the phenotypic variance but accounted for a great amount of the covariance between direct and maternal genetic effects estimated ignoring SH.

Litter, permanent environmental, ram-flock, and genetic effects on early weight gain of lambs.

Twelve models were fitted to early growth data of two Swiss sheep breeds to investigate their suitability for evaluation of breeding values. Models were identical for fixed parity, litter size, sex and lambing season effects, random flock-year, and direct genetic effects but differed for combinations of random litter, permanent environmental, ram-flock, and maternal genetic effects. Records of average daily gain to 30 d of 25,564 lambs of the Black-Brown Mountain Sheep (SBS) and of 26,391 lambs of the White Alpine Sheep (WAS) born 1989 to 1995 and their pedigrees were available. A single-trait animal model was fitted by the restricted maximum likelihood method. The information criterion of a particular model (i.e., the maximum of the likelihood function adjusted for the number of independently estimated parameters) was used to evaluate the models for their fitting power. The litter effect accounted for between 26 and 31% of the phenotypic variance, with little variation within breed. Models containing the ram-flock effect provided a better fit of the data than otherwise identical models. This effect contributed 6 and 4% to the phenotypic variance in the two breeds and strongly influenced estimates of other components. The proportion of phenotypic variance due to the flock-year effect was 23 and 25% without and 19 and 23% including the ram-flock effect in the model in the two breeds. Including permanent environmental effect of the ewe in addition to litter effect led to a better fit of the data. Depending on the model, it then contributed between 3 and 6% to the phenotypic variance. Fitting the ram-flock effect reduced heritability considerably and increased the breed difference of the estimates of this parameter. Estimates ranging from .16 to .10 and from .08 to .14 were obtained for the SBS and WAS breeds, respectively. For models without the ram-flock effect, negative estimates of the direct-maternal correlation of between -.38 and -.45 were observed. Including the ram-flock effect reduced this correlation substantially to between -.08 and -.17. Including the direct-maternal covariance in addition to the ram-flock effect did not improve the fit any further in either breed. Ranking of the models investigated differed between breeds, but the same model provided the best fit. It contained the random litter, permanent environmental, ram-flock, direct, and maternal genetic effects, but not the covariance between the last two.

Influence of sire misidentification on sire x year interaction variance and direct-maternal genetic covariance for weaning weight in beef cattle.

Biased estimates of the genetic correlation between direct and maternal effects may occur when sire x year interaction (SY) effects are ignored in analytical models used to estimate (co)variance components for weaning weight in beef cattle. Using simulation, sire misidentification was explored as a source contributing to estimates of SY variance. Identifications were falsified for 20% of sires of nonparents only or for 20% of sires of all animals. Sire misidentification influenced estimates of genetic and environmental parameters. In populations in which misidentification occurred only in nonparents, heritability estimates for direct growth were reduced, and heritability estimates of maternal effects were inflated. Also, spurious SY variance and direct-maternal covariance were produced. Direct-maternal covariance was biased in a positive direction, and SY variance was on the order of 1 to 3% of the phenotypic variance.

Cumulative selection and genetic change for weaning or yearling weight or for yearling weight plus muscle score in Hereford cattle.

Selection in three lines of Hereford cattle for 1) weaning weight (WWL), 2) yearling weight (YWL), and 3) an index of yearling weight and muscle score (IXL) was studied. Remnant foundation cows and semen from seven foundation sires were used to establish an unselected control line for the last 11 yr of the experiment. Performance data collected over a 23-yr period on birth weight (BWT), weaning weight (WWT), postweaning gain (PWG), yearling weight (YWT), muscle score (MSC), and an index (IDX) giving equal weight to standard deviations of yearling weight and muscle score were analyzed. Generation interval of midparents was about 4.16 yr in each selected line. Sire and dam selection differentials, in standard deviation units per generation, for primary criteria were, respectively, 1.59 and .33 for WWT in WWL, 1.75 and .25 for YWT in YWL, and 1.42 and .25 for IDX in IXL. Components of direct and maternal genetic variances, direct-maternal covariance, and dam permanent environmental variance were estimated by REML. The average annual response of males and females in actual units for each trait in WWL, YWL, and IXL was, respectively, BWT, .22, .24, and .27 kg; WWT, .98, .63, and 1.26 kg; YWT, 2.43, 2.64, and 3.44 kg; and MSC, .053, .009, and .104 scores. Average selection responses in BWT, WWT, YWT, MSC, and IDX per unit of primary criteria in each selection line (all in standard deviation units) were .22, .20, .31, .10, and .24 for WWT in WWL; .23, .12, .32, .04, and .21 for YWT in YWL; and .27, .22, .40, .20, and .36 for IDX in IXL. Responses in bold type are realized heritability and others are correlated responses. Realized genetic correlations were .78 for WWT and YWT, .87 for WWT and IDX, and .86 for YWT and IDX. Responses for all traits in IXL were greater than in other selected lines.

Evaluation of cytoplasmic genetic effects in Miles City Line 1 Hereford cattle.

Mixed-model techniques were used to evaluate the importance of cytoplasmic genetic effects on growth traits in beef cattle. The data used were records on birth weight (BWT, n = 4,716), preweaning average daily gain (PREADG, n = 4,428), and postweaning average daily gain (POSTADG, n = 3,476) collected from 1935 through 1989 in a closed line of Hereford cattle (Miles City Line 1). Selection criterion was adjusted yearling weight. Cytoplasmic genetic effects were evaluated as both potential fixed and random genetic effects. Cytoplasmic sources (n = 26) were determined based on the foundation female in the maternal lineage of each animal. All foundation females were at least five generations removed from any descendant that produced a performance record. An animal model was used to account for all nuclear additive genetic variation among animals. Direct additive effects were estimated for all traits. Maternal additive and permanent environmental effects were estimated for BWT and PREADG. Fixed effects included year of birth, age of dam, sex of calf, and regressions on inbreeding of calf, inbreeding of dam, and age off postweaning gain test (POSTADG only). When cytoplasm was fit as a fixed effect, F-tests for cytoplasmic effects were not significant (P = .10 to .99) for any trait. Inclusion of cytoplasmic source (fixed) in the statistical model reduced residual standard deviations less than .1%. Variance components for cytoplasmic genetic effects were estimated simultaneously with variance components for direct, maternal, direct-maternal covariance, and maternal permanent environment using REML techniques. Cytoplasmic source accounted for .40, .00 and .00% of the phenotypic variance for BWT, PREADG, and POSTADG, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

Genetic analysis of crossfostering data with sire and dam records.

A method is presented for the analysis of data from crossfostering experiments in which parts of litters are reciprocally interchanged at birth. Observed variances and covariances of differently related individuals are expressed as functions of theoretical causal components of phenotypic variance (additive direct, dominance direct, additive maternal, dominance maternal, direct-maternal covariance, and environmental). Causal components are estimated by weighted least squares analysis of this system of equations, including a ridge-regression procedure to examine consequences of correlation between observed components. Ridge regression suggests that dominance direct genetic variance is generally underestimated, but that narrow-sense heritability estimates are reliable.