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In beef cattle maternally influenced traits, estimates of direct-maternal genetic correlations (rdm) are usually reported to be negative. In international evaluations, rdm can differ both within countries (rdm_WC) and between countries (rdm_BC). The rdm_BC are difficult to estimate and are assumed to be zero in the current model for international beef cattle evaluations (Interbeef). Our objective was to investigate re-ranking of international estimated breeding values (IEBVs) in international beef cattle evaluations between models that either used estimated values for rdm or assumed them to be 0. Age-adjusted weaning weights and pedigree data were available for Limousin beef cattle from ten European countries. International EBVs were obtained using a multi-trait animal model with countries modeled as different traits. We compared IEBVs from a model that uses estimated rdm_BC (ranging between −0.14 and +0.14) and rdm_WC (between −0.33 and +0.40) with IEBVs obtained either from the current model that assumes rdm_BC to be 0, or from an alternative model that assumes both rdm_BC and rdm_WC to be 0. Direct and maternal IEBVs were compared across those three scenarios for different groups of animals. The ratio of population accuracies from the linear regression method was used to further investigate the impact of rdm on international evaluations, for both the whole set of animals in the evaluation and the domestic ones. Ignoring rdm_BC, i.e., replacing estimated values with 0, resulted in no (rank correlations > 0.99) or limited (between 0.98 and 0.99) re-ranking for direct and maternal IEBVs, respectively. Both rdm_BC and rdm_WC had less impact on direct IEBVs than on maternal IEBVs. Re-ranking of maternal IEBVs decreased with increasing reliability. Ignoring rdm_BC resulted in no re-ranking for sires with IEBVs that might be exchanged across countries and limited re-ranking for the top 100 sires. Using estimated rdm_BC values instead of considering them to be 0 resulted in null to limited increases in population accuracy. Ignoring both rdm_BC and rdm_WC resulted in considerable re-ranking of animals’ IEBVs in all groups of animals evaluated. This study showed the limited impact of the current practice of ignoring rdm_BC in international evaluations for Limousin weaning weight, most likely because the estimated rdm_BC was close to 0. We expect that these conclusions can be extended to other traits that have reported rdm values in the range of rdm_WC values for weaning weight in Limousin. [ABSTRACT FROM AUTHOR]

This study aimed to compare estimates of (co)variances considering the effect of direct maternal genetic correlation (-0,50; -0,25; +0,25; +0,50); the ratios between the direct and maternal genetic variances (75:75; 50:100; 100:50) and two models which included (M2) or not (M1) the direct maternal genetic covariance. Stochastic simulation of twenty replicates of a closed and randomly mated herd of cattle was carried out for twenty years of selection. The base population was not related, nonselected and randomly sampled. (Co)variance estimates were obtained under single trait animal model using MTDFREML application. The model was not significant on estimates of maternal permanent environmental variance. The genetic direct-maternal correlation influenced all (co)variance estimates significantly (P

Obtaining unbiased estimates of the direct-maternal genetic correlation proves far from straightforward for several reasons. Consequently, the use of such over- or underestimated correlations may introduce errors in genetic evaluation models. The objective of our study was to evaluate how the value of the direct-maternal genetic correlation affects EBV. Direct, maternal, and total breeding values were predicted for the ADG or weight at weaning for 3 different species (sheep, rabbits, and pigs) using models that differ depending on the fixed value of the directmaternal genetic correlation (ranging from -0.9 to 0.9) as well as a model in which the correlation was estimated. The results were consistent between species. The direct-maternal genetic correlation had a greater impact on the estimated maternal genetic effects than on direct effects. The lowest correlations between maternal breeding values obtained with different models were -0.20, -0.01, and -0.72 in pigs, sheep, and rabbits, respectively, whereas for the direct breeding value, the lowest correlations were 0.45, 0.90, and 0.95 in pigs, sheep, and rabbits, respectively. The total EBV, calculated as the unweighted sum of direct and maternal genetic effects, did not differ greatly between the models, the lowest correlations between total breeding values being 0.93, 0.98, and 0.97 for pigs, sheep, and rabbits, respectively. Given the uncertainty associated with estimating the direct-maternal genetic correlation, setting its value to 0 in genetic evaluation models appears to be a good compromise. [ABSTRACT FROM AUTHOR]

A long standing controversy in animal breeding is related to the strong negative estimates of the direct-maternal genetic correlation obtained when fitting data on maternally influenced traits. In this article, we focused on a model that introduces a new correlation parameter among dam-offspring records. The extant theory allows estimation of the parameter when dams have at most a single offspring. Our goal was to develop an inferential procedure in a more general setting. To do so, we applied a Bayesian approach and we showed that the estimation could be accomplished by introducing a Markov chain Monte Carlo (MCMC) step embedded into a regular Gibbs sampler program. The procedure was implemented by means of an MCMC algorithm known as the Griddy-Gibbs sampler, and a Fortran 90 library was created to accomplish the task. The computer program is available from http://www.agro.uba.ar/ catedras/mg_animal/software/RDBLK. With this tool at hand, we applied the inferential procedure to weaning weight records on beef cattle calves from an Argentinean Hereford herd, and we estimated the marginal distribution of the environmental dam-offspring correlation parameter. The distribution was unimodal and symmetric with a mean value of -0.14 (±0.03) and a 95% high posterior density interval between -0.20 and -0.07, indicating that the model placed a huge mass on negative values of the parameter. Noticeably, the magnitude of the direct-maternal genetic correlation diminished from -0.61 to -0.37 with respect to the standard maternal animal model. This result reinforces the idea that environmental covariances among dam-offspring records may bias the estimate of the direct-maternal genetic correlation. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to the application of an alternative model determination criterion conditional Akaike Information Criterion (cAIC) in the estimation of genetic parameters for body weight in commercial broilers. According to the study, cAIC can select different animal models than Bayesian Information Criterion (BIC) and the marginal Akaike Information Criterion (mAIC) with different biological properties.

This study aimed to compare estimates of (co)variances considering the effect of direct maternal genetic correlation (-0,50; -0,25; +0,25; +0,50); the ratios between the direct and maternal genetic variances (75:75; 50:100; 100:50) and two models which included (M2) or not (M1) the direct maternal genetic covariance. Stochastic simulation of twenty replicates of a closed and randomly mated herd of cattle was carried out for twenty years of selection. The base population was not related, nonselected and randomly sampled. (Co)variance estimates were obtained under single trait animal model using MTDFREML application. The model was not significant on estimates of maternal permanent environmental variance. The genetic direct-maternal correlation influenced all (co)variance estimates significantly (P<0,05). The ratios of genetic direct and maternal variances significantly affected (P<0,05) only estimates of genetic direct and maternal variances. Regarding negative direct-maternal genetic correlation, M1 underestimated direct and maternal variances while overestimated both when that correlation was positive. Reliable and accurate (co)variance estimates for weaning weight in beef cattle depend on the adequacy of the model as well as their actual values. [ABSTRACT FROM AUTHOR]

Genetic parameters of direct and maternal effects for calving ease in Dutch dairy cattle were estimated using 677,975 calving ease records from second calving. Particular emphasis was given to the presence and impact of environmental dam-offspring covariances on the estimated direct-maternal genetic correlation. Moreover, a measure of heritability for traits affected by maternal effects was developed. In contrast to previous parameters, this parameter reflects the amount of genetic variance that can be used to generate a response to selection in maternally affected traits. Estimated genetic correlations between direct and maternal effects on calving ease have often been moderately negative, particularly in beef cattle. Environmental dam-offspring covariances have been put forward as an explanation for such estimates. We investigated the impact of environmental dam-offspring covariances by fitting correlated residuals between dam and offspring records in the statistical model, and by comparing results of a sire-maternal grandsire model with those of an animal model. Results show that calving ease in Dutch dairy cattle has a direct heritability of approximately 0.08, a maternal heritability of approximately 0.04, a directmaternal genetic correlation of approximately -0.20, and a total heritable variance equal to approximately 11% of phenotypic variance. Results of animal models and sire-maternal grandsire models were very similar. The direct-maternal environmental covariance was near zero, and consequently had very little impact on the estimated genetic parameters. Transformation of observations to a liability scale did not affect the estimated genetic parameters and yielded a nearly identical ranking of sires. [ABSTRACT FROM AUTHOR]

Charolais calf records provided by the Mexican Charolais Breeders Association for an eight year period (1997-2005) were analyzed to estimate genetic and phenotypic parameters for birth weight (n=39,821), weaning weight adjusted to 205 d (n=39,556), and postweaning gain (n=21,831). Estimates of (co)variance components were obtained by REML with an EM algorithm and single-trait animal models. Maternal permanent environmental effects were unimportant for birth weight and postweaning gain and were not included in the final model. Estimates of direct heritability were 0.22, 0.33, and 0.45 for birth weight, adjusted weaning weight and postweaning gain, respectively. Estimates for the corresponding maternal component were 0.16, 0.17, and 0.14. Estimates of total heritability and direct-maternal genetic correlation were 0.12 and -0.65, 0.16 and -0.72, and 0.20 and -0.84 for birth weight, adjusted weaning weight and postweaning gain, respectively. For adjusted weaning weight, the estimated maternal permanent environmental variance (28.93 kg²) accounted for 4 % of the estimated total phenotypic variance (765.43 kg²). Expected response to single-trait selection for growth traits of Mexican Charolais cattle would be lessened due to highly negative direct-maternal genetic correlations. [ABSTRACT FROM AUTHOR]

A mother can influence a trait in her offspring both by the genes she transmits (Mendelian inheritance) and by maternal attributes that directly affect that trait in her offspring (maternal inheritance). Maternal inheritance can alter the direction, rate, and duration of adaptive evolution from standard Mendelian models and its impact on adaptive evolution is virtually unexplored in natural populations. In a hierarchical quantitative genetic analysis to determine the magnitude and structure of maternal inheritance in the winter annual plant, Collinsia verna, I consider three potential models of inheritance. These range from a standard Mendelian model estimating only direct (i.e., Mendelian) additive and environmental variance components to a maternal inheritance model estimating six additive and environmental variance components: direct additive (σAo2) and environmental (σEo2) variances; maternal additive (σAm2) and environmental (σEm2) variances; and the direct-maternal additive (σApAm) and environmental (σEm2) covariances. The structure of maternal inheritance differs among the 10 traits considered at four stages in the life cycle. Early in the life cycle, seed weight and embryo weight display substantial σAm2, a negative σAoAm, and a positive σEoEm. Subsequently, cotyledon diameter displays σAo2 and σAm2 of roughly the same magnitude and negative σAoAm. For fall rosettes, leaf number and length are best described by a Mendelian model. In the spring, leaf length displays maternal inheritance with significant σAo2 and σAm2 and a negative σAoAm. All maternally inherited traits show significant negative σAoAm. Predicted response to selection under maternal inheritance depends on σAo2 and σAm2 as well as σAoAm. Negative σAoAm results in predicted responses in the opposite direction to selection for seed weight and embryo weight and predicted responses near zero for all subsequent maternally inherited traits. Maternal inheritance persists through the life cycle of this annual plant for a number of size-related traits and will alter the direction and rate of evolutionary response in this population., (© 1998 The Society for the Study of Evolution.)