Estimation of heritability and genetic correlation for behavioural responses by Gibbs sampling in the Thoroughbred racehorse

Genetic variation of the behaviour of racehorses is one of the major concerns for racehorse breeders. In this study, the heritabilities of behavioural responses to the inspections of conjunctiva, auscultation and blood sampling and the genetic correlations among them were estimated in the Thoroughbred racehorse. The estimation was done with Bayesian analysis with Gibbs sampling based on the univariate or bivariate threshold animal models. The behavioural responses were scored with four categories at the first entrance quarantine in Miho Training Center of Japan Racing Association from 1993 to 1995. The behavioural responses were treated as categorical or binary traits, with both showing similar results. The estimated heritabilities were in the range of 0.23–0.28, suggesting a genetic component in the variation on these traits. The estimated genetic correlations among the traits were very high (approximately 0.9), suggesting that these behavioural responses may be measures of the same trait. Because of the high genetic correlations, repeatability threshold model was applied assuming the responses to be a genetically identical trait measured with three different tests. The estimated heritabilities (approximately 0.23) were at the lower bound of the former estimates. The revealed high repeatabilities (0.97–0.98) suggest a strong contribution of the individual temperament on the behaviour of racehorses.     

Estimation of genetic parameters for hip dysplasia in Czech Labrador Retrievers

The objective of this study was to estimate the genetic parameters, genetic trends and breeding values using linear model (LM) and threshold model (TM) for the development of hip dysplasia (HD) in Labrador Retrievers in the Czech Republic (n = 3151). The right and left hip joints were evaluated separately using the Fédération Cynologique Internationale scoring system. Four linear and four TMs were tested for the correct estimation of genetic parameters. All the tested models utilized fixed effects of sex, assessor, year of birth, regression of age at evaluation, random direct genetic effects and the effect of the animals' permanent environments. The models differed in the inclusion of the following effects: fixed effects of regression of inbreeding coefficient, random maternal effect and random effect of the maternal permanent environment. Compared to the TM, the LM provided lower coefficients of direct (0.25-0.29 versus 0.26-0.35) and maternal heritability (0.01-0.02 versus 0.03-0.05), repeatability (0.76-0.77 versus 0.78-0.83) and of the correlation between direct and maternal effects (-0.55 to -0.21 versus -0.80 to -0.27). In the tested models, no statistical significance was found for fixed regression of inbreeding coefficients or for the random effect of the permanent maternal environment. In spite of the similarity of the LM and TM results, the TM is recommended as the more suitable model for estimating genetic parameters and subsequent breeding values for HD in Labrador Retrievers in the Czech Republic.     

Comparison of repeatability and multiple trait threshold models for litter size in sheep using observed and simulated data in Bayesian analyses

Bayesian analyses were used to estimate genetic parameters on 5580 records of litter size in the first four parities from 1758 Mule ewes. To examine the appropriateness of fitting repeatability (RM) or multiple trait threshold models (MTM) to litter size of different parities, both models were used to estimate genetic parameters on the observed data and were thereafter compared in a simulation study. Posterior means of the heritabilities of litter size in different parities using a MTM ranged from 0.12 to 0.18 and were higher than the heritability based on the RM (0.08). Posterior means of the genetic correlations between litter sizes of different parities were positive and ranged from 0.24 to 0.71. Data sets were simulated based on the same pedigree structure and genetic parameters of the Mule ewe population obtained from both models. The simulation showed that the relative loss in accuracy and increase in mean squared error (MSE) was substantially higher when using the RM, given that the parameters estimated from the observed data using the opposite model are the true parameters. In contrast, Bayesian information criterion (BIC) selected the RM as most appropriate model given the data because of substantial penalty for the higher number of parameters to be estimated in the MTM model. In conclusion, when the relative change in accuracy and MSE is of main interest for estimation of breeding values of litter size of different parities, the MTM is recommended for the given population. When reduction in risk of using the wrong model is the main aim, the BIC suggest that the RM is the most appropriate model.     

Estimation of genetic parameters of feed intake and daily gain in Durocs using data from electronic swine feeders

Genetic parameters for daily feed intake (DFI, g/day) and daily gain (DG, g/day) were estimated using records of 1916 Duroc boars from electronic feeder stations. Management was limited and resulted in varied ranges of age and weight on test. Boars were housed in 102 pens, each equipped with one feeder, and allowed ad libitum feeding. Weekly averages of DFI and DG were used due to large variation in daily records. Six traits were defined as DFI and DG during 85–106 (period 1), 107–128 (period 2) and 129–150 days of age (period 3). A six‐trait model included age as a linear and a quadratic covariate for DFI and a linear covariate for DG with a fixed effect of year–week–pen and random effects of litter, additive genetic animal and permanent environmental animal. Variance components were estimated by a Bayesian approach using Gibbs sampling algorithm. Estimates of heritability for respective periods were 18%, 12% and 10% for DFI and 21%, 11% and 10% for DG. Genetic correlations between DFI and DG in the same period were 0.70, 0.73 and 0.32 for the respective periods. DFI and DG obtained from automatic feeders can be analysed to reveal variation across testing periods by using weekly averages when many monthly averages are incomplete.     

Estimation of direct and maternal genetic parameters for growth and carcass traits in a herd of Japanese Black cattle in Miyagi prefecture, using a multitrait animal model

Data from 1170 records of fattening calves were collected on growth and carcass traits from a Japanese Black cattle herd located in Miyagi prefecture, Japan. The objective was to determine direct and maternal heritabilities, direct and maternal genetic correlations and phenotypic correlations between bodyweight at the beginning of the fattening period (BWS), bodyweight at the end of the fattening period (BWF), carcass weight (CW), average daily gain during the fattening period (ADG), rib eye area (REA), rib thickness, subcutaneous backfat thickness (SFT), yield estimate (YE) and beef marbling score (BMS). Direct heritability estimates of 0.16 (SFT) and 0.07 (BMS) were low, whereas estimates of the other traits were medium to high and ranged between 0.44 (REA) and 0.78 (CW). Direct genetic correlations were all positive, except those that were between BWS and SFT, and between BWS and YE (?0.49 and ?0.14, respectively). The lowest positive genetic correlation was between BWS and BMS (0.04) and the highest was between BWF and CW (0.99). The phenotypic correlation coefficients ranged between ?0.41 (between SFT and YE) and 0.96 (between BWF and CW). Maternal heritability estimates were generally low and ranged between 0.00 for BMS and 0.08 for BWS, CW and ADG. Selection programs comprising information on growth and carcass traits of calves and maternal traits of dams were suggested.     

Estimation of genetic parameters for growth and feed utilization traits in Japanese Black cattle

Performance test results of 3250 sire candidates were used to estimate the genetic parameters of growth and feed utilization traits in Japanese Black cattle. Growth traits analyzed were six body measurements at the end of the performance test and daily gain (DG) during the test. Feed utilization traits were intakes and conversions of concentrate, roughage, digestible crude protein and total digestible nutrient (TDN). Genetic (co)variance components were estimated by the restricted maximum likelihood procedure using an expectation maximization algorithm under the two‐trait animal model. Heritabilities for growth traits ranged from 0.40 to 0.70 and for feed utilization traits from 0.21 to 0.74. Genetic correlations of DG were positive with feed intake (0.15–0.77) and negative with feed conversions (?0.63 to ?0.30). These relationships indicate that the selection based on DG improves feed efficiency but it simultaneously increases feed intake. Feed conversions showed genetic correlations ranging from ?0.09 to 0.03 with total available energy consumption, TDN intake. Thus the results suggested that feed conversions were not efficient selection criteria to decrease TDN intake and to improve comprehensive feed utilization ability.     

A comparison between multivariate Slash, Student's t and probit threshold models for analysis of clinical mastitis in first lactation cows

Robust threshold models with multivariate Student's t or multivariate Slash link functions were employed to infer genetic parameters of clinical mastitis at different stages of lactation, with each cow defining a cluster of records. The robust fits were compared with that from a multivariate probit model via a pseudo‐Bayes factor and an analysis of residuals. Clinical mastitis records on 36 178 first‐lactation Norwegian Red cows from 5286 herds, daughters of 245 sires, were analysed. The opportunity for infection interval, going from 30 days pre‐calving to 300 days postpartum, was divided into four periods: (i) ?30 to 0 days pre‐calving; (ii) 1–30 days; (iii) 31–120 days; and (iv) 121–300 days of lactation. Within each period, absence or presence of clinical mastitis was scored as 0 or 1 respectively. Markov chain Monte Carlo methods were used to draw samples from posterior distributions of interest. Pseudo‐Bayes factors strongly favoured the multivariate Slash and Student's t models over the probit model. The posterior mean of the degrees of freedom parameter for the Slash model was 2.2, indicating heavy tails of the liability distribution. The posterior mean of the degrees of freedom for the Student's t model was 8.5, also pointing away from a normal liability for clinical mastitis. A residual was the observed phenotype (0 or 1) minus the posterior mean of the probability of mastitis. The Slash and Student's t models tended to have smaller residuals than the probit model in cows that contracted mastitis. Heritability of liability to clinical mastitis was 0.13–0.14 before calving, and ranged from 0.05 to 0.08 after calving in the robust models. Genetic correlations were between 0.50 and 0.73, suggesting that clinical mastitis resistance is not the same trait across periods, corroborating earlier findings with probit models.     

Bayesian estimates of genetic parameters for metritis, retained placenta, milk fever, and clinical mastitis in Holstein dairy cows via Gibbs sampling

The objective of this study was to estimate heritability and genetic correlations between the liabilities of clinical mastitis (CM), milk fever (MF), metritis (MET), and retained placenta (RP) within the first three lactations of Holstein dairy cows. The records of 57,301 dairy cows from 20 large dairy herds in Iran between January 2005 and June 2009 were analysed with univariate and bivariate threshold animal models, using Gibbs sampling methodology. The final model included the fixed class effects of herd-year, season of calving, parity of dam, the linear covariate effect of age at calving, and the random direct genetic effect of animal. Posterior means of heritability for liabilities in first, second, and third lactations were 0.06, 0.08, and 0.09, respectively, for CM; 0.10, 0.12, and 0.11, respectively, for MF; 0.09, 0.07, and 0.10, respectively, for MET, and 0.07, 0.08, and 0.08, respectively, for RP. Posterior means of genetic correlations between disease liabilities were low or moderate (from −0.01 to 0.26). The results of this study indicated the importance of health traits for considering in the selection index of Iranian Holstein dairy cows.     

Development of a method for simultaneously genotyping multiple horse coat colour loci and genetic investigation of basic colour variation in Thoroughbred and Misaki horses in Japan

In order to develop a genotyping method that can be used in the registration procedure for Thoroughbreds, we developed a method for simultaneously genotyping multiple coat colour genes on the basis of single nucleotide polymorphism typing by using the SNaPshot^TM technique. This method enabled precise and reasonable detection of causal mutations; it was effective for genotyping of MC1R, ASIP, and SLC45A2 at the Extension (E), Agouti (A), Cream dilution (C) loci, and the possibility of identification of rare variants of MC1R, EDNRB and KIT at the E, Overo (O) and Sabino 1 (SB1) loci, respectively, was also indicated. It was considered that this genotyping method would provide information not only for the registration of Thoroughbreds but also for the preservation of phenotypic characters, such as coat colour, of endangered Misaki native horses in Japan. Therefore, genetic variations at the five coat colour loci were investigated in 1111 Thoroughbred and 99 Misaki native horses. Allele frequencies at the polymorphic E and A loci were estimated, and the proportions of basic coat colours that could be expected in the Thoroughbred population were bay, 0.662; black, 0.070; chestnut, 0.268. In the Misaki population, they were bay, 0.792; black, 0.129; chestnut, 0.080. The data presented were the first of its kind on genetic coat colour variation, and will be important with regard to the registration of Thoroughbreds and the management of Misaki horses.     

Estimation of genetic parameters for racing speed at different distances in young and adult Spanish Trotter horses using the random regression model

A total of 71 522 records (from 3154 horses) with the times per kilometre (TPK), recorded in Spanish Trotter horses (individual races) from racing performances held from 1991 to 2007, were available for this study. The TPK values for the different age groups (young and adult horses) and different distances (1600–2700 m) were considered as different traits, and a bi character random regression model (RRM) was applied to estimate the (co)variance components throughout the trajectory of age groups and distances. The following effects were considered as fixed: the combination of hippodrome‐date of race (404 levels); sex of the animals (3 levels); type of start (2 levels) and a fixed regression of Legendre polynomials (order 2). Those considered as random effects were the random regression Legendre polynomial (order 1) for animals (9201 animals in the pedigree); the individual environment permanent (3154 animals with data) and the driver (n = 957 levels). The residual variance was considered as heterogeneous with two classes (ages). The heritability estimated by distance ranged from 0.12 to 0.34, with a different trajectory for the two age groups. Within each age group, the genetic correlations between adjacent distances were high (>0.90), but decreased when the differences between them were over 400 metres for both age groups. The genetic correlations for the same distance across the age groups ranged from 0.47 to 0.78. Accordingly, the analysed trait (TPK) can be considered as positive genetic correlated but as different traits along the trajectory of distance and age. Therefore, some re‐ranking should be expected in the breeding value of the horses at different characteristics of the racing. The use of RRM is recommended because it allows us to estimate the breeding value along the whole trajectory of race competition.     

A robust method for simultaneous estimation of single gene and polygenic effects in dairy cows using externally estimated breeding values as prior information

The aim of this study was to develop a robust method to estimate single gene and random polygenic animal effects simultaneously in a small field dataset with limited pedigree information. The new method was based on a Bayesian approach using additional prior information on the distribution of externally estimated breeding values. The field dataset consisted of 40 269 test‐day records for milk performance traits for 1455 genotyped dairy cows for the 11 bp‐deletion in the coding sequence of the myostatin gene. For all traits, estimated additive effects of the favoured wild‐type allele (‘+’ allele) were smaller when applying the new method in comparison with the application of a conventional mixed inheritance test‐day model. Dominance effects of the myostatin gene showed the same behaviour but were generally lower than additive effects. Robustness of methods was tested using a data‐splitting technique, based on the correlation of estimated breeding values from two samples, with one‐half of the data eliminated randomly from the first sample and the remaining data eliminated from the second sample. Results for 100 replicates showed that the correlation between split datasets when prior information included was higher than the conventional method. The new method led to more robust estimations for genetic effects and therefore has potential for use when only a small number of genotyped animals with field data and limited pedigree information are available.     

Estimation of phenotypic and genetic parameters for weight gain and weight at fixed ages in the double-muscled Belgian Blue Beef breed using field records

In the double‐muscled Belgian Blue beef (DM‐BBB) breed, selection focuses on muscular conformation and not on weight gain and higher weight. There are very few studies on growth in the DM‐BBB using field records. Therefore, farms have no available useful figures on weight at fixed ages and weight gain for the DM‐BBB. This study describes and evaluates live weights of DM‐BBB animals. All the data were gathered on farms in Belgium. It was found that a male DM‐BBB weighs an average of 51 kg at birth, 98 kg at 3 months, 242 kg at 7 months, 430 kg at 13 months and 627 kg at 20 months. Between the age of 7 and 20 months, weight gain is more than 1200 g a day. Females weigh 47 kg at birth, 96 kg at 3 months, 189 kg at 7 months and 332 kg at 13 months. For males, estimates of heritability for weights at 7, 13 and 20 months were between 0.21 and 0.36. The heritability for weight gain between 13 and 20 months was 0.13. This demonstrates that it is possible to select for higher weights and for increased growth between 13 and 20 months. Animals having high weights at a young age (7 and 13 months) tend to have also high weight at slaughtering age (20 months; r_g between 0.81 and 0.98), but no additional growth between 13 and 20 months (r_g between −0.09 and 0.00). High weight at 20 months is partially due to growth between 13 and 20 months (r_g = 0.49).