Relationship between milk urea content and important milk traits in Holstein cattle.

Breeding cattle with low nitrogen emissions has been proposed as a countermeasure against eutrophication due to dairy production. Milk urea content (MU) could potentially serve as a new readily measured indicator trait for nitrogen emissions by cows. Therefore, we estimated genetic parameters related to MU and its relationship with other milk traits. We analysed 4 178 735 milk samples collected between January 2008 and June 2019 from 261 866 German Holstein dairy cows during their first, second, and third lactations. Restricted maximum likelihood estimation was conducted using univariate and bivariate random regression sire models in WOMBAT. We obtained moderate average daily heritability estimates for the daily MU of 0.24 in first lactation cows, 0.23 in second lactation cows, and 0.21 in third lactation cows with average daily genetic SDs of 25.16 mg/kg, 24.93 mg/kg, and 23.75 mg/kg, respectively. Averaged over days in milk, the repeatability estimates were low at 0.41 in first, second, and third lactation cows. A strong positive genetic correlation was found between MU and milk urea yield (MUY; 0.72 on average). In addition, 305-day heritabilities were estimated as 0.50, 0.52, and 0.50 in first, second, and third lactation cows, respectively, with genetic correlations of 0.94 or higher for MU in different lactations. By contrast, the averaged estimates of the genetic correlations between MU and other milk traits were low (-0.07 to 0.15). Moderate heritability estimates clearly allow the possible selection for MU, and the near-zero estimates of genetic correlations indicate no risk of undesired correlated selection responses in other milk traits. However, a relationship still needs to be established between MU as an indicator trait and the target trait, defined as total individual nitrogen emissions.

Parsimonious model for analyzing parent-of-origin effects related to beef traits in dual-purpose Simmental.

Genomic imprinting occurs when allelic effects depend on their parental origin. These parent-of-origin effects (POE) occur because of epigenetic DNA modifications during gametogenesis according to the sex of an animal. Animal breeding programs give little consideration to imprinting, although its relationship to important traits has been shown in different agricultural species. To incorporate imprinting, a previously proposed model (imprinting model) contains the genetic effects of the sire and dam, and it provides an estimate of the variance component due to POE, which is referred to as imprinting variance. Large volumes of data are sometimes available for commercial populations, so the dimension of mixed-model equations can become very large or even excessively large when estimating imprinting variances and other genetic parameters. To address this issue, we replaced the genetic effect as dam with the effect of the maternal grandsire in the imprinting model. When combined with appropriate weightings of the observations, this replacement yields an imprinting model with a parsimonious number of genetic effects for male parents and ancestors of slaughter animals, and it enables the inclusion of large volumes of data. In addition, we derived an equivalent model to facilitate the direct estimation of POE and their prediction error variances. We applied the parsimonious model to 1,366,160 fattening bulls as well as a pedigree of 2,637,761 ancestors to investigate the relevance of POE for beef performance in dual-purpose Simmental. We analyzed the killing-out percentage, net BW gain, carcass muscularity, and fat score as slaughter traits. The parsimonious model was applied as both linear and generalized linear versions with a logit-link function. The proportions of the total genetic variance attributable to POE ranged between 8.6% and 17.1%. For 3 of the 4 traits, the maternal gamete accounted for a greater proportion of the imprinting variance. The effects of POE and their reliabilities were estimated for up to 27,567 bulls and all traits, where the reliabilities ranged between 0.38 and 0.99. Thus, our new parsimonious model is appropriate for estimating the imprinting variance using large pedigree data sets. Our results highlight the need to consider POE in genetic evaluations.

A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data.

Genomic imprinting is a phenomenon that arises when the expression of genes depends on the parental origin of alleles. Epigenetic mechanisms may induce the full or partial suppression of maternal or paternal alleles, thereby leading to different types of imprinting. However, imprinting effects have received little consideration in animal breeding programmes, although their relevance to some agricultural important traits has been demonstrated. A recently proposed model (imprinting model) with two path-of-transmission (male and female)-specific breeding values for each animal accounts for all types of imprinting simultaneously (paternal, maternal, full and partial). Imprinting effects (or more generally: parent-of-origin effects (POE)) are determined by taking the difference between the two genetic effects in each animal. However, the computation of their prediction error variance (PEV) is laborious; thus, we propose a new model that is equivalent to the aforementioned imprinting model, which facilitates the direct estimation of imprinting effects instead of taking the differences and the PEV is readily obtained. We applied the new model to slaughterhouse data for Brown Swiss cattle, among which imprinting has never been investigated previously. Data were available for up to 173 051 fattening bulls, where the pedigrees contained up to 428 710 animals representing the entire Brown Swiss population of Austria and Germany. The traits analysed comprised the net BW gain, fat score, EUROP class and killing out percentage. The analysis demonstrated that the net BW gain, fat score and EUROP class were influenced significantly by POE. After estimating the POE, the new model yielded estimates with reliabilities ranging between 0.4 and 0.9. On average, the imprinting variances accounted for 9.6% of the total genetic variance, where the maternal gamete was the main contributor. Moreover, our results agreed well with those obtained using linear models when the EUROP class and fat score were treated as categorical traits by applying a GLMM with a logit link function.