Half-life,clearance and production rate for oxytocin in cattle during lactation and mammary involution I

Basal concentration, production rate, metabolic clearance rate and $\text{T}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ for oxytocin were measured in Holstein cows at three lactational stages and during mammary involution. At each lactational stage, oxytocin was given intravenously at .5 IU/min or 1.0 IU/min for 60 min. Infusions were preceded by priming. During involution, the high dose was used. Mean basal concentrations of oxytocin ranged from 8.7 to 21.4 uU/ml. Mean basal values at early, middle, late lactation and involution were 17.57, 12.33, 15.15, 21.13 uU/ml, respectively and differed significantly. The mean “rapid” $\text{T}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ was 3.87 ± .1 min. Early, middle, late lactation and involution $\text{T}\text{1}\text{2}\text{s}$ were 4.2, 3.7, 4.0 and 3.5 min, respectively. The rapid $\text{T}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ was not affected by lactational stage. The mean “slow” $\text{T}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ was 25.53 ± 1 min. Early lactation and dry period means differed significantly. The overall mean oxytocin clearance rate was 8.41 ± .1 ml/kg^·min. Clearance rate declined through lactation and into the dry period. Mean values of 9.3, 8.8, 7.8 and 7.1 ml/kg^·min were obtained at early, middle, late lactation and involution, respectively. Clearance rates at late lactation and involution differed significantly from one another and from the early and middle stages. Mean entry rates for oxytocin at early, middle, late lactation and involution were 168.79, 106.03, 111.1 and 146.8 uU/kg^·min, respectively. Measurements at early lactation and involution were greater than values for middle and late lactation. To summarize, basal oxytocin concentrations can be measured in cows that are lactating or undergoing mammary involution and changes in concentrations during lactation are related to hormone production (entry rate) and metabolic clearance rates.     

Plasma clearance and tissue uptake of native and desialylated equine gonadotropins

Equine luteinizing hormone (eLH), equine follicle stimulating hormone (eFSH) and equne chorionic gonadotropin (eCG) were desialylated and their plasma disappearance, tissue uptake and degradation determined. Both native hormones and their desialylated derivatives were radioiodinated and injected intravenously into male rats. Plasma samples were taken at different time intervals and examined for both total and trichloroacetic acid (TCA) precipitable radioactivity. Disappearance curves for each hormone consisted of two exponential components: a fast clearance followed by a slow phase. The apparent $\text{t}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ of the fast component for native eCG, eLH and eFSH were 18.3 min, 17.0 min and 17.1 min, respectively; this is in contrast to their desialylated derivatives which had a $\text{t}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ of 2.8 min, 4.9 min and 7.1 min, respectively. The slower component for native and desialylated eCG had at $\text{t}{}_{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ of 355.5 min and 171.2 respectively. After TCA precipitation more than 90 percent of the radioactivity in plasma was in the pellet, whereas in urine almost 95 percent of the radioactivity was in the TCA supernatant. Coincident with the disappearance of the hormone from the plasma its uptake and release was observed in liver, kidney, testis, and muscle tissue. Gel filtration data on plasma and urine samples indicated that the former had mostly intact hormone in contrast with the latter. Together these results indicate that eLH, eFSH and eCG disappear from the plasma of male rats in a biphasic manner with a rate slower than their desialylated derivatives.     

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.     

Inclusion of sire by herd interaction effect in the genomic evaluation for weaning weight of American Angus

A spurious negative genetic correlation between direct and maternal effects of weaning weight (WW) in beef cattle has historically been problematic for researchers and industry. Previous research has suggested the covariance between sires and herds may be contributing to this relationship. The objective of this study was to estimate the variance components (VC) for WW in American Angus with and without sire by herd (S×H) interaction effect when genomic information is used or not. Five subsets of ~100k animals for each subset were used. When genomic information was included, genotypes were added for 15,637 animals. Five replicates were performed. Four different models were tested, namely, M1: without S×H interaction effect and with covariance between direct and maternal effect (σam) ≠ 0; M2: with S×H interaction effect and σam ≠ 0; M3: without S×H interaction effect and with σam = 0; M4: with S×H interaction effect and σam = 0. VC were estimated using the restricted maximum likelihood (REML) and single-step genomic REML (ssGREML) with the average information algorithm. Breeding values were computed using single-step genomic BLUP for the models above and one additional model, which had the covariance zeroed after the estimation of VC (M5). The ability of each model to predict future breeding values was investigated with the linear regression method. Under REML, when the S×H interaction effect was added to the model, both direct and maternal genetic variances were greatly reduced, and the negative covariance became positive (i.e., when moving from M1 to M2). Similar patterns were observed under ssGREML, but with less reduction in the direct and maternal genetic variances and still a negative covariance. Models with the S×H interaction effect (M2 and M4) had a better fit according to the Akaike information criteria. Breeding values from those models were more accurate and had less bias than the other three models. The rankings and breeding values of artificial insemination sires (N = 1,977) greatly changed when the S×H interaction effect was fit in the model. Although the S×H interaction effect accounted for 3% to 5% of the total phenotypic variance and improved the model fit, this change in the evaluation model will cause severe reranking among animals.     

Evaluation of animal models to explore the influence of maternal genetic and maternal permanent environment effect on reproductive performance of Jersey crossbred cattle

The present study was conducted on 1,002 reproductive records of 430 Jersey crossbred cattle, descended from 57 sires and 198 dams, maintained at the Eastern Regional Station of ICAR-National Dairy Research Institute, Kalyani, Nadia, West Bengal, India to investigate the influence of direct genetic, maternal genetic and maternal permanent environmental effect on three most important reproductive traits viz., number of service per conception (NSPC), days open (DO) and calving interval (CI) of Jersey crossbred cattle. Six single-trait animal models (including or excluding maternal genetic or permanent environmental effects) were fitted to analyse these traits, and the best model was chosen after testing the significant increase in the log-likelihood values when additional parameters were added in the model. Direct heritability estimates for NSPC, DO and CI from the best model were 0.10, 0.14 and 0.20, respectively. The maternal permanent environmental (c²) effects on reproductive traits accounted for almost negligible fraction of the total phenotypic variance in this study. The maternal genetic effects (m²) also contributed very little (0%–3%) to the total phenotypic variance except for CI where it was important and accounted for 20% of phenotypic variance. A significantly large negative genetic correlation was observed between direct and maternal genetic effects for all traits, suggesting the presence of antagonistic relationship between dam's direct additive component and daughter's additive genetic component. Results suggest that both direct and maternal effects were important only for CI but not for other traits. Therefore, both direct additive effects and maternal genetic effect need to be considered for improving this trait by selection.     

Some properties of lentogenic Australian newcastle disease virus

The Newcastle disease virus (NDV) occurring in Australia is apathogenic for chickens following natural infections. Some properties of the avirulent Australian V4 strain of NDV and of 12 new isolates of NDV were compared.The viruses grew to high titres following infection of chick embryos by the allantoic cavity and allantoic fluid had infectivity titres of from $\text{10}{}^{\mathrm{8·7}}\text{to}\text{10}{}^{\mathrm{9·5}}\text{EID}{}_{50}\text{0.2}\text{ml}$. With only two isolates did sufficient mortalities occur to allow calculation of mean death times and these were in excess of 140 h. Five of nine isolates failed to kill 100% of embryos when doses in excess of 10^7·9 EID₅₀ were used. When strain V4 was inoculated into the yolk sac of 10-day-old embryos, the LD₅₀ was similar to the ID₅₀ obtained with allantoic cavity inoculation, and the mean death time was 103 h.The intracerebral pathogenicity index for strain V4 was 0.91 and 1.02 in two experiments. The index was not significantly reduced when the virus was taken through a further cycle of plaque purification or when the inoculum was heated at 56°C for 30 min. Chickens with maternally derived antibody to NDV were not susceptible to intracerebral inoculation with strain V4. Chickens dying after intracerebral inoculation with strain V4 had haemorrhagic and necrotic liver lesions. The intracerbral pathogenicity indices for four other isolates varied from 0 to 0.22.The infectivity of V4 and three other isolates was relatively stable at 56°C and that of another eight isolates was labile. Haemagglutinins of all viruses studied were stable at 56°C for longer than 60 min. None of four isolates tested lost haemagglutinin activity on treatment with ether.Haemagglutination-elution patterns were variable but four isolates did not elute from chicken erythrocytes after 24 h at 4°C and strain V4 and isolate PM12 did not elute after 96 h at 4°C. Six viruses, including V4, agglutinated erythrocytes from all of six test horses. The haemagglutinin activity of the remaining viruses varied between horses.Four viruses including V4 haemolysed chicken erythrocytes. Gradient centrifugation allowed the separation of an infectious and a noniffectious haemagglutinin. Haemolytic activity was associated with the infectious haemagglutinin.     

Genetic parameter estimates for prenatal and postnatal mortality in Nellore cattle

The aim of this study was to estimate genetic parameters for prenatal (PRE) and postnatal (POS) mortality in Nellore cattle. A total of 13 141 (PRE) and 17 818 (POS) records from Nellore females were used. PRE and POS were recorded using binary scale scores: a score of ‘1’ was given to calves that were born alive (PRE) and those that were alive at weaning (POS), and a score of ‘0’ was given to calves that were not alive at or around birth (PRE), as well as to those weighed at birth but not at weaning (POS). The relationship matrix included 698 sires, 107 paternal grandsires and 69 maternal grandsires. Data were analysed using Bayesian inference and a sire–maternal grandsire threshold model, including contemporary groups as random effects, and the classes of dam age at the beginning of mating season (for PRE), and dam age at calving and birthweight (linear covariable) (for POS), as fixed effects. For both traits, the covariance between direct and maternal effects (r_D,M) was estimated (r_D,M≠ 0) or fixed at zero (r_D,M = 0). PRE and POS rates were 3.00 and 4.04%, respectively. Estimates of direct and maternal heritability were 0.07 and 0.17, respectively, for PRE, and 0.02 and 0.07, respectively, for POS, assuming r_D,M = 0. For r_D,M ≠ 0, these estimates were 0.07 and 0.12, respectively, for PRE, and 0.03 and 0.07, respectively, for POS. The correlation estimates between direct and maternal effects were ?0.71 (PRE) and ?0.33 (POS). PRE and POS show low genetic variability, indicating that these traits probably suffer major environmental influences. Additionally, our study shows that the maternal genetic component affects preweaning calf mortality twice as much (or more) as the direct genetic component. A large number of offspring per sire is necessary in progeny tests to genetically decrease calf mortality.     

Estimation of direct and social effects of feeding duration in growing pigs using records from automatic feeding stations

Automatic feeding systems in pig production allow for the recording of individual feeding behavior traits, which might be influenced by the social interactions among individuals. This study fitted mixed models to estimate the direct and social effects on visit duration at the feeder of group-housed pigs. The dataset included 74,413 records of each visit duration time (min) event at the automatic feeder from 135 pigs housed in 14 pens. The sequence of visits at the feeder was employed as a proxy for the social interaction between individuals. To estimate animal effects, the direct effect was apportioned to the animal feeding (feeding pig), and the social effect was apportioned to the animal that entered the feeder immediately after the feeding pig left the feeding station (follower). The data were divided into two subsets: “non-immediate replacement” time (NIRT, N = 6,256), where the follower pig occupied the feeder at least 600 s after the feeding pig left the feeder, and “immediate replacement” time (IRT, N= 58,255), where the elapsed time between replacements was less than or equal to 60 s. The marginal posterior distribution of the parameters was obtained by Bayesian method. Using the IRT subset, the posterior mean of the proportion of variance explained by the direct effect (Prpσ^d2) was 18% for all models. The proportion of variance explained by the follower social effect (Prpσ^f2) was 2%, and the residual variance (σ^e2) decreased, suggesting an improved model fit by including the follower effect. Fitting the models with the NIRT subset, the estimate of Prpσ^d2 was 20% but the Prpσ^f2 was almost zero and σ^e2 was identical for all models. For the IRT subset, the predicted best linear unbiased predictor (BLUP) of direct (Direct BLUP) and social (Follower BLUP) random effects on visit duration at the feeder of an animal was calculated. Feeder visit duration time was not correlated with traits, such as weight gain or average feed intake (P > 0.05), whereas for the daily feeder occupation time, the estimated correlation was positive with the Direct BLUP (r^= 0.51, P < 0.05) and negative with the Follower BLUP (r^= −0.26, P < 0.05). The results suggest that the visit duration of an animal at the single-space feeder was influenced by both direct and social effects when the replacement time between visits was less than 1 min. Finally, animals that spent a longer time per day at the feeder seemed to do so by shortening the meal length of the preceding individual at the feeder.     

Variance components and breeding values for growth traits from different statistical models.

Estimates of genetic parameters resulting from various analytical models for birth weight (BWT, n = 4,155), 205-d weight (WWT, n = 3,884), and 365-d weight (YWT, n = 3,476) were compared. Data consisted of records for Line 1 Hereford cattle selected for postweaning growth from 1934 to 1989 at ARS-USDA, Miles City, MT. Twelve models were compared. Model 1 included fixed effects of year, sex, age of dam; covariates for birth day and inbreeding coefficients of animal and of dam; and random animal genetic and residual effects. Model 2 was the same as Model 1 but ignored inbreeding coefficients. Model 3 was the same as Model 1 and included random maternal genetic effects with covariance between direct and maternal genetic effects, and maternal permanent environmental effects. Model 4 was the same as Model 3 but ignored inbreeding. Model 5 was the same as Model 1 but with a random sire effect instead of animal genetic effect. Model 6 was the same as Model 5 but ignored inbreeding. Model 7 was a sire model that considered relationships among males. Model 8 was a sire model, assuming sires to be unrelated, but with dam effects as uncorrelated random effects to account for maternal effects. Model 9 was a sire and dam model but with relationships to account for direct and maternal genetic effects; dams also were included as uncorrelated random effects to account for maternal permanent environmental effects. Model 10 was a sire model with maternal grandsire and dam effects all as uncorrelated random effects. Model 11 was a sire and maternal grandsire model, with dams as uncorrelated random effects but with sires and maternal grandsires assumed to be related using male relationships. Model 12 was the same as Model 11 but with all pedigree relationships from the full animal model for sires and maternal grandsires. Rankings on predictions of breeding values were the same regardless of whether inbreeding coefficients for animal and dam were included in the models. Heritability estimates were similar regardless of whether inbreeding effects were in the model. Models 3 and 9 best fit the data for estimation of variances and covariances for direct, maternal genetic, and permanent environmental effects. Other models resulted in changes in ranking for predicted breeding values and for estimates of direct and maternal heritability. Heritability estimates of direct effects were smallest with sire and sire-maternal grandsire models.     

Bayesian inference strategies for the prediction of genetic merit using threshold models with an application to calving ease scores in Italian Piemontese cattle

First parity calving difficulty scores from Italian Piemontese cattle were analysed using a threshold mixed effects model. The model included the fixed effects of age of dam and sex of calf and their interaction and the random effects of sire, maternal grandsire, and herd‐year‐season. Covariances between sire and maternal grandsire effects were modelled using a numerator relationship matrix based on male ancestors. Field data consisted of 23 953 records collected between 1989 and 1998 from 4741 herd‐year‐seasons. Variance and covariance components were estimated using two alternative approximate marginal maximum likelihood (MML) methods, one based on expectation‐maximization (EM) and the other based on Laplacian integration. Inferences were compared to those based on three separate runs or sequences of Markov Chain Monte Carlo (MCMC) sampling in order to assess the validity of approximate MML estimates derived from data with similar size and design structure. Point estimates of direct heritability were 0.24, 0.25 and 0.26 for EM, Laplacian and MCMC (posterior mean), respectively, whereas corresponding maternal heritability estimates were 0.10, 0.11 and 0.12, respectively. The covariance between additive direct and maternal effects was found to be not different from zero based on MCMC‐derived confidence sets. The conventional joint modal estimates of sire effects and associated standard errors based on MML estimates of variance and covariance components differed little from the respective posterior means and standard deviations derived from MCMC. Therefore, there may be little need to pursue computation‐intensive MCMC methods for inference on genetic parameters and genetic merits using conventional threshold sire and maternal grandsire models for large datasets on calving ease.     

Synthesis of direct and maternal genetic components of economically important traits from beef breed-cross evaluations

Published information on relative performance of beef breed crosses was used to derive combined estimates of purebred breed values for predominant temperate beef breeds. The sources of information were largely from the United States, Canada, and New Zealand, although some European estimates were also included. Emphasis was on maternal traits of potential economic importance to the suckler beef production system, but some postweaning traits were also considered. The estimates were taken from comparison studies undertaken in the 1970s, 1980s and 1990s, each with representative samples of beef breeds used in temperate agriculture. Weighting factors for breed-cross estimates were derived using the number of sires and offspring that contributed to that estimate. These weights were then used in a weighted multiple regression analysis to obtain single purebred breed effects. Both direct additive and maternal additive genetic effects were estimated for preweaning traits. Important genetic differences between the breeds were shown for many of the traits. Significant regression coefficients were estimated for the effect of mature weight on calving ease, both maternal and direct additive genetic, survival to weaning direct, and birth weight direct. The breeds with greater mature weight were found to have greater maternal genetic effects for calving ease but negative direct genetic effects on calving ease. A negative effect of mature weight on the direct genetic effect of survival to weaning was observed. A cluster analysis was done using 17 breeds for which information existed on nine maternal traits. Regression was used to predict breed-cross-specific heterosis using genetic distance. Only five traits, birth weight, survival to weaning, cow fertility, and preweaning and postweaning growth rate had enough breed-cross-specific heterosis estimates to develop a prediction model. The breed biological values estimated provide a basis to predict the biological value of crossbred suckler cows and their offspring.     

Heterosis, maternal and direct effects in double-muscled and normal cattle: I. Reproduction and growth traits

Data from a two-breed group diallel experiment involving double-muscled (DM) and normal (N) cattle were analyzed to evaluate the importance of heterosis, maternal and direct effects for reproduction and growth traits. The DM cattle were from a composite of primarily Angus, Charolais, Galloway and Hereford breeds, and N cattle were crossbred cattle with at least 50% Hereford breeding. The data comprised a total of 491 matings and 389 calvings in four breeding seasons. Records on calving performance, calving date, calf crop born and weaned, sex ratio of progeny and weight of calves were analyzed using least squares procedures. Significant heterosis of 5 to 12% was observed for all the calf crop and growth traits, except for birth weight. Heterosis resulted in 24% reduction in the incidence of dystocia and perinatal calf mortality (P less than .05). The significant heterosis was due mainly to poor production in DM X DM crosses. The DM cows were superior (P less than .05) to N cows in reciprocal crossing (maternal effect) for all the calf crop traits, but had higher incidence of calving difficulty and a higher proportion of male progeny. Significant direct effect was observed for all the traits except calving date and sex ratio among progeny. The N sires were superior for all the calf crop traits and caused less incidence of dystocia and perinatal mortality compared with the DM sires. Significant differences were obtained between the straightbreds for all the traits except calving date. The N straightbreds were superior to the DM straightbreds for all the significant traits.     

Postinduction butorphanol administration alters oxygen consumption to improve blood gases in etorphine-immobilized white rhinoceros

Objective

To investigate the effects of postinduction butorphanol administration in etorphine-immobilized white rhinoceros on respiration and blood gases.

Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs

Numerous methods have been suggested to incorporate crossbred (CB) phenotypes and genotypes into swine selection programs, yet little research has focused on the implicit trade-off decisions between generating data at the nucleus or commercial level. The aim of this study was to investigate the impact of altering the proportion of purebred (PB) and CB phenotypes and genotypes in genetic evaluations on the response to selection of CB performance. Assuming CB and PB performance with moderate heritabilities (h2=0.4), a three-breed swine crossbreeding scheme was simulated and selection was practiced for six generations, where the goal was to increase CB performance. Phenotypes, genotypes, and pedigrees for three PB breeds (25 and 175 mating males and females for each breed, respectively), F₁ crosses (400 mating females), and terminal cross progeny (2,500) were simulated. The genome consisted of 18 chromosomes with 1,800 quantitative trait loci and 72k single nucleotide polymorphism (SNP) markers. Selection was performed in PB breeds using estimated breeding value for each phenotyping/genotyping strategy. Strategies investigated were: 1) increasing the proportion of CB with genotypes, phenotypes, and sire pedigree relationships, 2) decreasing the proportion of PB phenotypes and genotypes, and 3) altering the genetic correlation between PB and CB performance (rpc). Each unique rpc scenario and data collection strategy was replicated 10 times. Results showed that including CB data improved the CB performance regardless of rpc or data collection strategy compared with when no CB data were included. Compared with using only PB information, including 10% of CB progeny per generation with sire pedigrees and phenotypes increased the response in CB phenotype by 134%, 55%, 33%, 23%, and 21% when rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively. When the same 10% of CB progeny were also genotyped, CB performance increased by 243%, 54%, 38%, 23%, and 20% when the rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively, compared with when no CB data were utilized. Minimal change was observed in the average CB phenotype when PB phenotypes were included or proportionally removed when CB were genotyped. Removal of both PB phenotypes and genotypes when CB were genotyped greatly reduced the response in CB performance. In practice, the optimal inclusion rate of CB and PB data depends upon the genetic correlation between CB and PB animals and the expense of additional CB data collection compared with the economic benefit associated with increased CB performance.     

Genetic (co)variances for calving difficulty score in composite and parental populations of beef cattle: I. Calving difficulty score, birth weight, weaning weight, and postweaning gain

Heritability of 2-yr-old heifer calving difficulty score was estimated in nine purebred and three composite populations with a total of 5,986 calving difficulty scores from 520 sires and 388 maternal grandsires. Estimates were 0.43 for direct (calf) genetic effects and 0.23 for maternal (heifer) genetic effects. The correlation between direct and maternal effects was -0.26. Direct effects were strongly positively correlated with birth weight and moderately correlated with 200-d weight and postweaning gain. Smaller negative correlations of maternal calving difficulty with direct effects of birth weight, weaning weight, and postweaning gain were estimated. Calving difficulty was scored from 1 to 7. Predicted heritabilities using seven optimal scores were similar to those using four scores. The predicted heritability using only two categories was reduced 23%. Phenotypic and direct genetic variance increased with increasing average population calving difficulty score. The estimated direct and maternal heritabilities for 2-yr-old calving difficulty score were larger than many literature estimates. These estimates suggested substantial variance for direct and maternal genetic effects. The direct effects of 2-yr-old calving difficulty score seemed to be much more closely tied to birth weight than were maternal effects.     

Calving performance and calf mortality

The most important maternal factor influencing calving performance is parity. Among calf factors, birth weight seems the most important. There are large differences between breeds and, generally speaking, heavier beef and dual-purpose breeds present more problems than smaller cattle. Variation in calving performance and stillbirth may be attributed to characters of both the calf and the dam. Genetic variation in calving performance and stillbirth at first calving has been demonstrated in several investigations for both the direct (calf) and the maternal character.In a Swedish investigation a heritability of 10% was found for both the direct and the maternal character. For stillbirth values were on average 3%. A strong genetic relationship was found between calving performance and birth weight as direct characters (r_GD = 0.98) but for the maternal characters it was considerably weaker (r_GM = 0.60). Correlations between stillbirth rate and birth weight were generally weaker, because the relationship was non-linear. Estimations of the genetic correlations between direct and maternal effects gave values between zero and ?0.5 for the characters investigated, indicating an antagonistic relationship between the genetic make-up of the cow and the calf. This implies that, in the long run, selection will not be as effective as the heritabilities suggest.A substantial improvement in calving performance and calf mortality can be achieved, however, through selection within breeds, optimal organization of breeding structures, choice of appropriate beef breeds for cross-breeding on heifers and cows, respectively, and timing calving to occur at favourable ages and in favourable seasons.     

Analysis of gestation length in American Simmental cattle

Records of gestation length (71,461) for Simmental cattle were distributed with mean 284.3 d and standard deviation 5.52 d. Gestation length was found to increase with percent Simmental and was 1.9 d longer for calves born to mature dams than for those born to heifer dams. Bull calves experienced gestation lengths 1.5 d longer than heifer calves. Sire, maternal grandsire, residual and total variances were estimated to be 2.42, .58, 22.78 and 25.78 d2, respectively, by Henderson's Method III. Heritability of gestation length was calculated to be .374 from the sire variance and .09 from the maternal grandsire variance. Direct additive genetic variance was considered to be of greater importance than maternal additive genetic variance. Correlations between the evaluations of sires for gestation length and heifer calving ease, birth weight and weaning weight were .26, .26 and .13, respectively.     

Maternal effects due to cytoplasmic inheritance in dairy cattle. Influence on milk production and reproduction traits

The objectives of this study were to determine the importance of effects of cytoplasmic origin on milk production and reproduction traits.Cow families at the experimental farm originated from randomly collected calves from 240 herds in two breeding districts. Cytoplasmic origin was defined as the first animal in the traced, maternal lineage. Milk production of 290 cows in first lactation from 1976 to 1982 was used. Reproduction records of the same cows as nulliparous and primiparous could be analysed in cow families.Cytoplasmic origin was a significant (P < 0.01) source of variation in kg fat plus protein, and milk returns (Dfl.) after adjustment for district of origin of the cytoplasmic source, sire's breed, calving year and season, breeding values of sires and material grandsires, and age at calving. Cytoplasmic origin accounted for maximal 10% and 13%, respectively, of the phenotypic variation in the two traits.Cytoplasmic origin was not a significant source of variation in nulliparous and primiparous reproduction traits after adjustment for effects of sire's breed, calving year and season. Although not significant, the cytoplasmic components accounted for 10 to 4% of the phenotypic variation in number of inseminations per first conception and for −0.04% to 13% of the phenotypic variation in age at first calving for the first and second generation, respectively. Some of these cytoplasmic components accounted for more phenotypic variation in reproductive traits of nulliparous heifers than most additive genetic components found in the literature.The effects of cytoplasmic inheritance on production and reproduction traits might have an impact on breeding policies in dairy cattle.     

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice. The genomic relationship matrix (G) used in both cases is dense, limiting computations depending on the number of genotyped animals. The algorithm for proven and young (APY) can be used to create a sparse inverse of G (GAPY~-1) with close to linear memory and computing requirements. In ssGREML, the inverse of the realized relationship matrix (H⁻¹) also includes the inverse of the pedigree relationship matrix, which can be dense with a long pedigree, but sparser with short. The main purpose of this study was to investigate whether costs of ssGREML can be reduced using APY with truncated pedigree and phenotypes. We also investigated the impact of truncation on variance components estimation when different numbers of core animals are used in APY. Simulations included 150K animals from 10 generations, with selection. Phenotypes (h² = 0.3) were available for all animals in generations 1–9. A total of 30K animals in generations 8 and 9, and 15K validation animals in generation 10 were genotyped for 52,890 SNP. Average information REML and ssGREML with G⁻¹ and GAPY~-1 using 1K, 5K, 9K, and 14K core animals were compared. Variance components are impacted when the core group in APY represents the number of eigenvalues explaining a small fraction of the total variation in G. The most time-consuming operation was the inversion of G, with more than 50% of the total time. Next, numerical factorization consumed nearly 30% of the total computing time. On average, a 7% decrease in the computing time for ordering was observed by removing each generation of data. APY can be successfully applied to create the inverse of the genomic relationship matrix used in ssGREML for estimating variance components. To ensure reliable variance component estimation, it is important to use a core size that corresponds to the number of largest eigenvalues explaining around 98% of total variation in G. When APY is used, pedigrees can be truncated to increase the sparsity of H and slightly reduce computing time for ordering and symbolic factorization, with no impact on the estimates.