Genetic relationships between calving performance and beef production traits in Piemontese cattle

The aim of the study was to obtain estimates of genetic correlations between direct and maternal calving performance of heifers and cows and beef production traits in Piemontese cattle. Beef production traits were daily gain, live fleshiness, and bone thinness measured on 1,602 young bulls tested at a central station. Live fleshiness (six traits) and bone thinness were subjectively scored by classifiers using a nine-point linear grid. Data on calving performance were calving difficulty scores (five classes from unassisted to embryotomy) routinely recorded in the farms. Calving performance of heifers and cows were considered different traits. A total of 30,763 and 80,474 calving scores in first and later parities, respectively, were used to estimate covariance components with beef traits. Data were analyzed using bivariate linear animal models, including direct genetic effects for calving performance and beef traits and maternal genetic effects only for calving performance. Due to the nature of the data structure, which involved traits measured in different environments and on different animals, covariances were estimated mostly through pedigree information. Genetic correlations of daily gain were positive with direct calving performance (0.43 in heifers and 0.50 in cows) and negative with maternal calving performance (-0.23 and -0.28 for heifers and cows, respectively). Live fleshiness traits were moderately correlated with maternal calving performance in both parities, ranging from 0.06 to 0.33. Correlations between live fleshiness traits and direct calving performance were low to moderate and positive in the first parity, but trivial in later parities. Bone thinness was negatively correlated with direct calving performance (-0.17 and -0.38 in heifers and cows, respectively), but it was positively correlated to maternal calving performance (0.31 and 0.40). Estimated residual correlations were close to zero. Results indicate that, due to the existence of antagonistic relationships between the investigated traits, specific selection strategies need to be studied.     

Evaluation models and genetic parameters for calving difficulty in beef cattle

Calving difficulty was analyzed under threshold and linear models considering either a fixed or random herd-year effect. The aim of the study was to compare models for predicting breeding values according to the size of herd-year groups. When simulating data sets with small herds, in order to obtain an unbiased evaluation under a nonrandom and negative association of sire and herd effects, the best model for a practical evaluation was the fixed linear model. Field data included 246,576 records of the largest Charolais herds in France. Models were compared using the correlations of estimated breeding values between the different models. Although the best model from a theoretical point of view was a threshold model with a fixed herd-year effect, a linear model with a fixed herd-year effect was the best choice from a practical point of view for predicting direct effects for calving difficulty in beef cattle and was a sufficient choice for predicting the associated maternal effects for data set with large herds. Correlations between direct estimated breeding values under the reference model and the fixed linear model and the random threshold model were 0.94 and 0.91, respectively. Correlations between the corresponding maternal estimated breeding values were 0.94 and 0.98. Heritabilities of direct effects were 0.27 and 0.14 under fixed threshold and fixed linear models, respectively. The corresponding heritabilities of maternal effects were 0.18 and 0.13, and the genetic correlation between direct and maternal effects were -0.36 and -0.34, respectively.     

Genetic analysis of liability to clinical mastitis, with somatic cell score and production traits using bivariate threshold–linear and linear–linear models

Inferences about genetic and residual correlation estimates and sire evaluations involving a categorical trait with linear model are ambiguous and mostly based on data simulations. In this study, estimates of variance components and prediction of breeding values in a model with a categorical and a continuous trait were compared between threshold–linear (TLM) and linear–linear models (LLM) in analysis of large clinical mastitis (CM) field data. Data on CM, somatic cell score (SCS), 305-day milk (MY), protein (PY) and fat yield (FY) from first-lactation Finnish Ayrshire cows were used. Four bivariate analyses were made using a TLM in Bayesian analysis. Each analysis fitted CM and one continuous trait at a time. Corresponding bivariate analyses were made using a Gaussian linear model. Estimates of heritabilities for CM were 0.06 and 0.02 from TLM and LLM, respectively whilst heritability estimates of the continuous traits were similar from both models. Genetic correlations between CM–SCS, CM–MY, CM–PY, and CM–FY from TLM and LLM were 0.63 and 0.63; 0.36 and 0.36; 0.32 and 0.32; 0.30 and 0.29, respectively. Estimates of residual correlations were 0.11 and 0.06; − 0.04 and − 0.02; − 0.03 and − 0.02; − 0.05 and − 0.03 between CM–SCS, CM–MY, CM–PY, and CM–FY, respectively. Comparison between the models indicates similar estimates of genetic correlations with no underestimation with the linear model analysis. In CM evaluation, the comparison of model's predictive ability showed greater improvements in accuracy with the bivariate than with the univariate models. There was, however no clear advantage of univariate threshold model over univariate linear model, except for less accuracy sires.     

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33 155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85 118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice.     

Illustration of the maternal animal model used for genetic evaluation of beef cattle

National cattle evaluation programs for weaning weight in most beef breed associations involve implementation of the maternal animal model to predict direct and maternal EPD. With this model, direct breeding values are predicted for all animals with records or pedigree ties to animals with records, or both. Even though maternal genetic value is expressed only in animals that become dams, these effects are transmitted by all parents and inherited from parents by all animals, leading to maternal breeding values being predicted for all animals as well. A small example data set was simulated involving 12 parents, 8 nonparents, and 13 animals with weaning weight records. The pedigree was developed to include paternal and maternal half-sib families, full-sibs, and some inbreeding, similar to field populations of beef cattle. Assembly of the mixed model equations and solutions for the maternal animal model are illustrated explicitly to assist animal breeding students in their understanding of the properties of the maternal animal model and to explicitly implement the model. Model parameters and moments, fixed contemporary group solutions, adjustment of breeding values for merit of mates, interpretation of maternal permanent environmental effect solutions, and alternatives for the assembly of the equations are shown. This example should lead to increased student and producer understanding of genetic improvement programs for weaning weight in beef cattle.     

Comparison of threshold vs linear and animal vs sire models for predicting direct and maternal genetic effects on calving difficulty in beef cattle

This study compared the accuracy of several models for obtaining genetic evaluations of calving difficulty. The models were univariate threshold animal (TAM), threshold sire-maternal grandsire (TSM), linear animal (LAM), and linear sire-maternal grandsire (LSM) models and bivariate threshold-linear animal (TLAM), threshold-linear sire-maternal grandsire (TLSM), linear-linear animal (LLAM), and linear-linear sire-maternal grandsire (LLSM) models for calving difficulty and birth weight. Data were obtained from the American Gelbvieh Association and included 84,420 first-parity records of both calving difficulty and birth weight. Calving difficulty scores were distributed as 73.4% in the first category (no assistance), 18.7% in the second, 6.3% in the third, and 1.6% in the fourth. Included in the animal models were fixed sex of calf by age of dam subclasses, random herd-year-season effects, and random animal direct and maternal breeding values. Sire-maternal grandsire models were similar to the animal models, with animal and maternal effects replaced by sire and maternal grandsire effects. Models were compared using a data splitting technique based on the correlation of estimated breeding values from two samples, with one-half of the calving difficulty records discarded randomly in the first sample and the remaining calving difficulty records discarded in the second sample. Reported correlations are averages of 10 replicates. The results obtained using animal models confirmed the slight advantage of TAM over LAM (0.69 vs 0.63) and TLAM over LLAM (0.90 vs 0.86). Bivariate analyses greatly improved the accuracy of genetic prediction of direct effects on calving difficulty relative to univariate analyses. Similar ranking of the models was found for maternal effects, but smaller correlations were obtained for bivariate models. For sire-maternal grandsire models, no differences between sire or maternal grandsire correlations were observed for TLSM compared to LLSM, and small differences were observed between TSM and LSM. The threshold model offered advantages over the linear model in animal models but not in sire-maternal grandsire models. For genetic evaluation of calving difficulty in beef cattle, the threshold-linear animal model seems to be the best choice for predicting both direct and maternal effects.     

Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model: II. Comparison of models.

Several models were evaluated in terms of predictive ability for calving difficulty. Data included birth weight and calving difficulty scores provided by the American Gelbvieh Association from 26,006 calves born to first-parity cows and five simulated populations of 6,200 animals each. Included in the model were fixed age of dam x sex interaction effects, random herd-year-season effects, and random animal direct and maternal effects. Bivariate linear-threshold and linear-linear models for birth weight/calving ease and univariate threshold and linear models for calving ease were applied to the data sets. For each data set and model, one-half of calving ease records were randomly discarded. Predictive ability of the different models was defined with the mean square error (MSE) for the difference between a deleted calving ease score and its prediction obtained from the remaining data. In terms of correlation between simulated and predicted breeding values, the threshold models had a 1% advantage for direct genetic effects and 3% for maternal genetic effects. In simulation, the average MSE was .29 for linear-threshold, .32 for linear-linear, .37 for threshold, and .39 for linear model. For the field data set, the MSE was .31, .33, .39, and .40, respectively. Although the bivariate models for calving ease/birth weight were more accurate than univariate models, the threshold models showed a greater advantage under the bivariate model. For the purpose of genetic evaluation for calving difficulty in beef cattle, the use of the linear-threshold model seems justified. In dairy cattle, the evaluation for calving ease can benefit from recording birth weight.     

河北荷斯坦牛体型性状的参数分析

[目的]估测河北荷斯坦牛线性体型性状参数,为育种提供参考.[方法]利用MTD-FREML软件,配合单性状和多性状动物模型,估测了河北675头荷斯坦牛23个体型线性性状的表型参数和遗传参数.[结果]体型各性状评分的平均数范围为2.16～8.24.体型线性性状遗传力的范围为0.07～0.61.体型总分的遗传力为0.49.结...     

Effects of parent‐of‐origin models with different pedigree information on beef carcass traits and fatty acid composition in Japanese Black cattle

Genomic imprinting should be considered in animal breeding systems to avoid lead in bias in genetic parameter estimation. The objective of this study was to clarify the effects of pedigree information on imprinting variances for carcass traits and fatty acid composition in Japanese Black cattle. Carcass records [carcass weight, rib eye area, rib thickness (RT), subcutaneous fat thickness and beef marbling score (BMS)] and fatty acid composition were obtained for 11,855 Japanese Black feedlot cattle. To estimate and compare the imprinting variances for the traits, two imprinting models with different pedigree information [the sire–dam gametic relationship matrix (Model 1) and the sire–maternal grandsire (MGS) numerator relationship matrix (Model 2)] were fitted. The ratio of the imprinting variance to the total additive genetic variance for RT (6.33%) and BMS (19.00%) was significant in Model 1, but only that for BMS (21.09%) was significant in Model 2. This study revealed that fitting the sire–MGS model could be useful in estimating imprinting variance under certain conditions, such as when restricted pedigree information is available. Furthermore, the present result suggested that the maternal gametic effects on BMS should be included in breeding programmes for Japanese Black cattle to avoid selection bias caused by imprinting effects.     

Genetic relationships between temperament of calves at auction and carcass traits in Japanese Black cattle

Correlations of calves’ temperament with carcass traits were estimated to clarify the genetic relationships between them in Japanese Black cattle. The temperament records for 3128 calves during auction at a calf market were scored on a scale of 1 (calm) to 5 (nervous) as temperament score (TS ), and the TS were divided into two groups (TSG ): TS 1 and 2 comprised TSG 1, and 3 to 5 constituted TSG 2. Carcass data were obtained from 33 552 fattened cattle. A threshold animal model was used for analyzing the underlying liability for TSG , whereas a linear one was used for TS and carcass traits. The heritability estimates for TS and TSG were 0.12 and 0.11, respectively. On the other hand, moderate to high heritability estimates were obtained for carcass traits (0.40 to 0.68). The temperament scores were negatively correlated with carcass weight, rib thickness and subcutaneous fat thickness (?0.13 to ?0.59). In contrast, weak to moderate positive correlations were found between the temperament scores and rib eye area or yield estimate (0.16 to 0.45). The temperament scores and beef marbling score had no correlation. These results showed that it is possible to improve temperament and carcass traits simultaneously.     

Genetic parameters for type classification of Nelore cattle on central performance tests at pasture in Brazil

The objective of this study was to characterize Nelore cattle on central performance tests in pasture, ranked by the visual classification method EPMURAS (structure, precocity, muscle, navel, breed, posture, and sexual characteristics), and to estimate genetic and phenotypic correlations between these parameters, including visual as well as production traits (initial and final weight on test, weight gain, and weight corrected for 550 days). The information used in the study was obtained on 21,032 Nelore bulls which were participants in the central performance test at pasture of the Brazilian Association for Zebu Breeders (ABCZ). Heritabilities obtained were from 0.19 to 0.50. Phenotypic correlations were positive from 0.70 to 0.97 between the weight traits, from 0.65 to 0.74 between visual characteristics, and from 0.29 to 0.47 between visual characteristics and weight traits. The genetic correlations were positive ranging from 0.80 to 0.98 between the characteristics of structure, precocity and musculature, from 0.13 to 0.64 between the growth characteristics, and from 0.41 to 0.97 between visual scores and weight gains. Heritability and genetic correlations indicate that the use of visual scores, along with the selection for growth characteristics, can bring positive results in selection of beef cattle for rearing on pasture.     

"Quasi-REML" correlation estimates between production and health traits in the presence of selection and confounding: a simulation study

Performance of the "quasi-REML" method for estimating correlations between a continuous trait and a categorical trait, and between two categorical traits, was studied with Monte Carlo simulations. Three continuous, correlated traits were simulated for identical populations and three scenarios with either no selection, selection for one moderately heritable trait (Trait 1, h2 = .25), and selection for the same trait plus confounding between sires and management groups. The "true" environmental correlations between Traits 2 (h2 = .10) and 3 (h2 = .05) were always of the same absolute size (.20), but further data scenarios were generated by setting the sign of environmental correlation to either positive or negative. Observations for Traits 2 and 3 were then reassigned to binomial categories to simulate health or reproductive traits with incidences of 15 and 5%, respectively. Genetic correlations (r(g12), r(g13), and r(g23) and environmental correlations (r(e12), r(e13), and r(e23)) were estimated for the underlying continuous scale (REML) and the visible categorical scales ("quasi-REML") with linear multiple-trait sire and animal models. Contrary to theory, practically all "quasi-REML" genetic correlations were underestimated to some extent with the sire and animal models. Selection inflated this negative bias for sire model estimates, and the sign of r(e23) noticeably affected r(g23) estimates for the animal model, with greater bias and SD for estimates when the "true" r(e23) was positive. Transformed "quasi-REML" environmental correlations between a continuous and a categorical trait were estimated with good efficiency and little bias, and corresponding correlations between two categorical traits were systematically overestimated. Confounding between sires and contemporary groups negatively affected all correlation estimates on the underlying and the visible scales, especially for sire model "quasi-REML" estimates of genetic correlation. Selection, data structure, and the (co)variance structure influences how well correlations involving categorical traits are estimated with "quasi-REML" methods.     

Analyses of growth curves of nellore cattle by multiple-trait and random regression models

The purpose of this study was to compare estimates of genetic parameters for sequential growth of beef cattle using two models and two data sets. Growth curves of Nellore cattle were analyzed using body weights measured at ages 1 (birth weight) to 733 d. Two data samples were created, one with 71,867 records sampled from all herds (MISS), and the other with 74,601 records sampled from herds with no missing traits (NMISS). Records preadjusted to a fixed age were analyzed by a multiple-trait model (MTM), which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were by REML, with five traits at a time. The random regression model (RRM) included the effects of age of animal, contemporary group, age of dam class, additive direct, additive maternal, permanent environment, and maternal permanent environment. All effects were modeled as cubic Legendre polynomials. These analyses were also by REML. Shapes of estimates of variances by MTM were mostly similar for both data sets for all except late ages, where estimates for MISS were less regular, and for birth weight with MISS. Genetic correlations among ages for the direct and maternal effects were less smooth with MISS. Genetic correlations between direct and maternal effects were more negative for NMISS, where few sires were maternal grandsires. Parameter estimates with RRM were similar to MTM cept that estimates of variances showed more artifacts for MISS; the estimates of additive direct-maternal correlations were more negative with both data sets and approached -1.0 for some ages with NMISS. When parameters of a growth model obtained by used for genetic evaluation, these parameters should be examined for consistency with parameters from MTM and prior information, and adjustments may be required to eliminate artifacts.     

Genetic parameters for calving difficulty, stillbirth, and birth weight for Hereford and Charolais at first and later parities

The aim of this study was to estimate direct and maternal genetic parameters for calving difficulty score, stillbirth, and birth weight at first and later parities for Charolais and Hereford cattle in Sweden. Calving traits have long been recorded for pure-bred beef cattle in Sweden, but only birth weight has been used in the selection in order to avoid calving difficulties. Linear animal model analyses included records on birth weight for 60,309 Charolais and 30,789 Hereford calves born from 1980 to 1999, and calving traits for 74,538 Charolais and 37,077 Hereford calves born from 1980 to 2001. The frequencies of difficult calvings and stillbirths were approximately 6% at first and 1 to 2% at later parities for both breeds. Fewer than half the stillborn calves were born from difficult calvings. Heritabilities estimated for birth weight in different univariate and bivariate analyses for Charolais and Hereford calves born at first and later parities ranged from 0.44 to 0.51 for direct effects and 0.06 to 0.15 for maternal effects. Heritabilities on the observable scale for calving difficulty score of Charolais and Hereford, scored in three classes, ranged from 0.11 to 0.16 for direct and 0.07 to 0.12 for maternal effects at first parity, and lower at later parities. All estimated heritabilities for stillbirth were very low (0.002 to 0.016 on the observable scale). Direct-maternal genetic correlations were negative, with few exceptions. Genetic correlations between the traits and between parities within traits were generally moderate to high and positive. Calving difficulty score should be included in the genetic evaluation of beef breeds in Sweden, whereas progeny groups in Swedish beef populations are too small for stillbirth to be considered directly.     

Genetic evaluation of growth in nellore cattle by multiple-trait and random regression models

The objective of this study was to identify issues in genetic evaluation of beef cattle for growth by a random regression model (RRM). Genetic evaluation data included 2,946,847 records of up to nine sequential weights of 812,393 Nellore cattle measured at ages ranging from birth to 733 d. Models considered were a five-trait multiple-trait model (MTM) and a cubic RRM. The MTM included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Both additive effects were assumed correlated. The RRM included the same effects as MTM, with the addition of permanent and random error effects. The purpose of the random error effect, which was in addition to a residual effect with constant variance, was to model heterogeneous residual variances. All effects in RRM were modeled as cubic Legendre polynomials. Expected progeny differences (EPD) were obtained iteratively using a preconditioned conjugate gradient algorithm. Numerically accurate solutions with RRM were not obtained until the random regressions were orthogonalized. Computing requirements of RRM were reduced by more than 50%, without affecting the accuracy by removing regressions corresponding to very low eigen-values and by replacing the random error effects with weights. Afterward, the correlations between EPD from RRM and from MTM for EPD on selected weights were between 0.84 and 0.89. For sires with at least 50 progeny, these correlations increased to 0.92 to 0.97. Low correlations were caused by differences in parameters. The RRM applied to growth i s prone to numerical problems. Estimates of EPD with RRM may be more accurate than those with MTM only if accurate parameters are applied.     

Genetic relationships among calving ease, calving interval, birth weight, and weaning weight in the Asturiana de los Valles beef cattle breed

The aim of this paper was to estimate direct and maternal genetic parameters for calving ease (CE), birth weight (BrW), weaning weight (WW), and calving interval (CI) to assess the possibility of including this information in beef cattle improvement programs. Field data, including a total of 59,813 animals (1,390 sires and 1,147 maternal grand sires) from the Asturiana de los Valles beef cattle breed, were analyzed with a multivariate linear model. Estimates of heritability for direct genetic effects (CED, CID, BrWD, and WWD) were 0.191 +/- 0.019, 0.121 +/- 0.013, 0.390 +/- 0.030, and 0.453 +/- 0.035, respectively, whereas those for maternal genetic effects (CEM, BrWM, and WWM) were 0.140 +/- 0.015, 0.208 +/- 0.020, and 0.138 +/- 0.022, respectively. Genetic correlations between direct or maternal genetic effects across traits were, in general, positive and moderate to low. However, genetic correlation for the pair CED-BrWD was positive and high (0.604 +/- 0.064). Genetic correlations between the direct and maternal genetic effects within a trait were negative and moderate (-0.219 +/- 0.097 for CE, -0.337 +/- 0.080 for BrW, and -0.440 +/- 0.102 for WW). Genetic correlations for CED-BrWM and CED-WWM were -0.121 +/- 0.090 and -0.097 +/- 0.113, respectively. The genetic correlation for CEM-CID was unfavorable (0.485 +/- 0.078), and those for CEM-BrWD (-0.094 +/- 0.079) and CEM-WWD (-0.125 +/- 0.082) were low and negative. The genetic correlation between CID and WWM was favorable (-0.148 +/- 0.106). Overall, the data presented here support the hypothesis that maternal effects for CE and BrW are not the same and that the genetic relationships between CI and maternal effects for WW in beef cattle follow a similar pattern to that reported between CI and milk yield in dairy cattle. Moreover, the need to include direct and maternal breeding values in beef cattle selection programs is suggested.     

Genetic parameters for calving rate and calf survival from linear, threshold, and logistic models in a multibreed beef cattle population

Generalized mixed linear, threshold, and logistic sire models and Markov chain, Monte Carlo simulation procedures were used to estimate genetic parameters for calving rate and calf survival in a multibreed beef cattle population. Data were obtained from a 5-generation rotational crossbreeding study involving Angus, Brahman, Charolais, and Hereford (1969 to 1995). Gelbvieh and Simmental bulls sired terminal-cross calves from a sample of generation 5 cows. A total of 1,458 cows sired by 158 bulls had a mean calving rate of 78% based on 4,808 calving records. Ninety-one percent of 5,015 calves sired by 260 bulls survived to weaning. Mean heritability estimates and standard deviations for daughter calving rate from posterior distributions were 0.063 +/- 0.024, 0.150 +/- 0.049, and 0.130 +/- 0.047 for linear, threshold, and logistic models, respectively. For calf survival, mean heritability estimates and standard deviations from posterior distributions were 0.049 +/- 0.022, 0.160 +/- 0.058, and 0.190 +/- 0.078 from linear, threshold, and logistic models, respectively. When transformed to an underlying normal scale, linear sire, mixed model, heritability estimates were similar to threshold and logistic sire mixed model estimates. Posterior density distributions of estimated heritabilities from all models were normal. Spearman rank correlations between sire EPD across statistical models were greater than 0.97 for daughter calving rate and for calf survival. Sire EPD had similar ranges across statistical models for daughter calving rate and for calf survival.     

Genetic relationships between calving and carcass traits for Charolais and Hereford cattle in Sweden

The objective of this study was to estimate genetic correlations between calving difficulty score and carcass traits in Charolais and Hereford cattle, treating first and later parity calvings as different traits. Genetic correlations between birth weight and carcass traits were also estimated. Field data on 59,182 Charolais and 27,051 Hereford calvings, and carcass traits of 5,260 Charolais and 1,232 Hereford bulls, were used in bivariate linear animal model analyses. Estimated heritabilities were moderate to high (0.22 to 0.50) for direct effects on birth weight, carcass weight, and (S)EUROP (European Community scale for carcass classification) grades for carcass fleshiness and fatness. Heritabilities of 0.07 to 0.18 were estimated for maternal effect on birth weight, and for direct and maternal effects on calving difficulty score at first parity. Lower heritabilities (0.01 to 0.05) were estimated for calving difficulty score at later parities. Carcass weight was positively genetically correlated (0.11 to 0.53) with both direct and maternal effects on birth weight and with direct effects on calving difficulty score. Carcass weight was, however, weakly or negatively (-0.70 to 0.07) correlated with maternal calving difficulty score. Higher carcass fatness grade was genetically associated with lower birth weight, and in most cases, also with less difficult calving. Genetic correlations with carcass fleshiness grade were highly variable. Moderately unfavorable correlations between carcass fleshiness grade and maternal calving difficulty score at first parity were estimated for both Charolais (0.42) and Hereford (0.54). This study found certain antagonistic genetic relationships between calving performance and carcass traits for both Charolais and Hereford cattle. Both direct and maternal calving performance, as well as carcass traits, should be included in the breeding goal and selected for in beef breeds.     

Fertility traits in spring-calving Aberdeen Angus cattle. 2. Model comparison

The aim of this study was to investigate the possible superiority of a threshold-linear (TL) approach for calving day (CD) and calving success (CS) analysis in beef cattle over 2 multiple-trait (MT), censored models, considering CD at the first 3 calving opportunities. The CD observations on animals that failed to calve in the latter models were defined as cows being assigned a penalty value of 21 d beyond the last observed CD record within contemporary group (PEN model) or censored CD values that were randomly obtained from a truncated normal distribution (CEN-model). In the TL model, CD records were treated as missing if a cow failed to calve, and parameters were estimated in a TL analysis including CS traits (TLMISS-model). The models included the effects of contemporary group (herd x year of calving x mating management), age at calving, physiological status at mating (lactating or nonlactating cow), animal additive genetic effects, and residual. Field data included 6,763 calving records obtained from first, second, and third parities of 3,442 spring-calving Uruguayan Aberdeen Angus cows. Models were contrasted using a data splitting technique, analyzing correlations between predicted breeding values (PBV) for each pair of subsamples, by rank correlations between PBV obtained with the different models, and by inspecting percentage of sires selected in common using the different approaches at 10 and 25% hypothetical percentages of animals selected. Breeding value correlations of CD between the subsamples for the TLMISS approach were greater (0.67 to 0.68) than correlations for the censored MT models (0.49 to 0.54). Average correlations between PBV of CD in 1 subsample obtained by CEN (PEN, TLMISS) and PBV of CS in the other subsample were -0.53 (-0.55, -0.60) in the first calving opportunity (CO), -0.54 (-0.58, -0.63) in the second CO, and -0.50 (-0.49, -0.58) in the third CO. Rank correlations between PBV for CD in PEN and CEN were high (0.93 to 0.97), but correlations of either method with PBV of CD in TLMISS ranged from 0.50 to 0.71. Common identification of bulls for the top 10% of sires (25% of sires), when selected with PEN/CEN models or the TLMISS model, varied between 50 (44%) and 60 (52%). The use of the TL animal model for genetic evaluation seems attractive for genetic evaluation of fertility traits in beef cattle.     

基于系谱和基因组信息估计荷斯坦青年母牛体重性状遗传参数

旨在设计利用不同信息来源的模型估计荷斯坦后备牛不同月龄体重性状的遗传参数。本研究于2014—2020年测定并收集了7 122头荷斯坦牛32 338条0～12月龄体重数据,分别利用系谱信息(linear mixed model with pedigree relationship matrix, LM＿A)和系谱-基因组信息构建亲缘关系矩阵(linear mixed model with genotype-pedigree joint relationship matrix, LM＿H),基于母体效应动物模型估计初生重,基于是否考虑初生重作为协变量的单性状动物模型估计2～12月龄各月龄体重遗传力,并利用双性状动物模型估计初生重与其它月龄体重的遗传相关。结果显示,对于初生重,根据赤池信息量准则(Akaike information criterion, AIC),LM＿H方法的拟合程度显著优于LM＿A方法,但两种方法估计的遗传参数相差不大：直接遗传力分别为0.30和0.32,母体遗传力分别为0.08和0.09,个体直接遗传效应和母体遗传效应遗传相关系数分别为-0.65和-0.64;对于2～...