Carcass traits of young bulls in dual-purpose cattle: genetic parameters and genetic correlations with veal calf, type and production traits.

The profitability of dual-purpose breeding farms can be increased through genetic improvement of carcass traits. To develop a genetic evaluation of carcass traits of young bulls, breed-specific genetic parameters were estimated in three French dual-purpose breeds. Genetic correlations between these traits and veal calf, type and milk production traits were also estimated. Slaughter performances of 156 226 Montbeliarde, 160 361 Normande and 8691 Simmental young bulls were analyzed with a multitrait animal model. In the three breeds, heritabilities were moderate for carcass weight (0.12 to 0.19±0.01 to 0.04) and carcass conformation (0.21 to 0.26±0.01 to 0.04) and slightly lower for age at slaughter (0.08 to 0.17±0.01 to 0.03). For all three breeds, genetic correlations between carcass weight and carcass conformation were moderate and favorable (0.30 to 0.52±0.03 to 0.13). They were strong and favorable (-0.49 to -0.71±0.05 to 0.15) between carcass weight and age at slaughter. Between age at slaughter and carcass conformation, they were low and unfavorable to moderate and favorable (-0.25 to 0.10±0.06 to 0.18). Heavier young bulls tend to be better conformed and slaughtered earlier. Genetic correlations between corresponding young bulls and veal production traits were moderate and favorable (0.32 to 0.70±0.03 to 0.09), implying that selecting sires for veal calf production leads to select sires producing better young bulls. Genetic correlations between young bull carcass weight and cow size were moderately favorable (0.22 to 0.45±0.04 to 0.10). Young bull carcass conformation had moderate and favorable genetic correlations (0.11 to 0.24±0.04 to 0.10) with cow width but moderate and unfavorable genetic correlations (-0.21 to -0.36±0.03 to 0.08) with cow height. Taller cows tended to produce heavier young bulls and thinner cows to produce less conformed ones. Genetic correlations between carcass traits of young bulls and cow muscularity traits were low to moderate and favorable. Finally, genetic correlations between carcass traits of young bulls and milk production traits were low and unfavorable to moderate and favorable. These results indicate the existence for all three breeds of genetic variability for the genetic improvement of carcass traits of young bulls as well as favorable genetic correlations for their simultaneous selection and no strong unfavorable correlation with milk production traits.

Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers.

The objective of the study was to develop a genomic evaluation for French beef cattle breeds and assess accuracy and bias of prediction for different genomic selection strategies. Based on a reference population of 2,682 Charolais bulls and cows, genotyped or imputed to a high-density SNP panel (777K SNP), we tested the influence of different statistical methods, marker densities (50K versus 777K), and training population sizes and structures on the quality of predictions. Four different training sets containing up to 1,979 animals and a unique validation set of 703 young bulls only known on their individual performances were formed. BayesC method had the largest average accuracy compared to genomic BLUP or pedigree-based BLUP. No gain of accuracy was observed when increasing the density of markers from 50K to 777K. For a BayesC model and 777K SNP panels, the accuracy calculated as the correlation between genomic predictions and deregressed EBV (DEBV) divided by the square root of heritability was 0.42 for birth weight, 0.34 for calving ease, 0.45 for weaning weight, 0.52 for muscular development, and 0.27 for skeletal development. Half of the training set constituted animals having only their own performance recorded, whose contribution only represented 5% of the accuracy. Using DEBV as a response brought greater accuracy than using EBV (+5% on average). Considering a residual polygenic component strongly reduced bias for most of the traits. The optimal percentage of polygenic variance varied across traits. Among the methodologies tested to implement genomic selection in the French Charolais beef cattle population, the most accurate and less biased methodology was to analyze DEBV under a BayesC strategy and a residual polygenic component approach. With this approach, a 50K SNP panel performed as well as a 777K panel.

Trends of the genetic connectedness measures among Nelore beef cattle herds.

Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 1999-2003 to the 2004-2008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.

A sampling method for estimating the accuracy of predicted breeding values in genetic evaluation.

A sampling-based method for estimating the accuracy of estimated breeding values using an animal model is presented. Empirical variances of true and estimated breeding values were estimated from a simulated n-sample. The method was validated using a small data set from the Parthenaise breed with the estimated coefficient of determination converging to the true values. It was applied to the French Salers data file used for the 2000 on-farm evaluation (IBOVAL) of muscle development score. A drawback of the method is its computational demand. Consequently, convergence can not be achieved in a reasonable time for very large data files. Two advantages of the method are that a) it is applicable to any model (animal, sire, multivariate, maternal effects...) and b) it supplies off-diagonal coefficients of the inverse of the mixed model equations and can therefore be the basis of connectedness studies.

Genetic correlation estimations between artificial insemination sire performances and their progeny beef traits both measured in test stations.

In France, beef traits of artificial insemination (AI) beef bulls are improved through the sequential selection for their own performances and for their male progeny performances, both being recorded in test stations. The efficiency of such programmes mainly depends on the genetic correlations between sire performances and progeny beef traits. Such correlations were independently estimated, using the multivariate REML (restricted maximum likelihood) method in a Limousin and a Charolais programme. In both breeds, high genetic correlations were observed between sires and progeny analogous morphology scores (from 0.64 to 0.82). Genetic correlations estimated between sires and progeny growth (from 0.41 to 0.70) were lower probably due to the difference of diet in central and progeny stations. Correlations between sire muscling scores and progeny skeletal frames (and vice-versa) were negative (from -0.05 to -0.58). The genetic correlations of sire traits with progeny dressing percentage (DPp) and carcass fatness score (CFp) were only low to moderate. These results show that the selection of bulls at the end of performance testing in test stations may be efficient in improving progeny growth and morphology. However, such a selection is insufficient in improving their dressing percentage and carcass composition.