Genetic evaluation of horses for performance in dressage competitions in Great Britain

Effects of Selection on Breed Contribution in the Caballo de Deporte Español

The equine breeding industry for sport’s performance has evolved into a fairly profitable economic activity. In particular, the Caballo de Deporte Español (CDE) is bred for different disciplines with a special focus on Show Jumping. The main aim of this study was to determine the effects of 15 years of selection and to find out whether it has been effective and adequate regarding the CDE main breeding objectives. The whole pedigree of 19,045 horses registered as CDE was used, comprising 47,884 animals (18,799 males and 29,085 females). An analysis performed to check for the pedigree completeness level yielded a number of equivalent complete generations (t) equal to 1.95, an average generation interval (GI) of 10.87 years, mean inbreeding coefficient (F) of 0.32%, an average relatedness coefficient (AR) of 0.09% and an effective population size (Ne) of 204. For the analyses, animals were divided into fourteen breed groups. Additionally, in order to study the evolution of these breeds over time and their influence on CDE pedigree, five different periods were considered according to the year of birth of the animals. Performance data used in the analyses were the estimated breeding values (EBV) of the Show Jumping sport discipline of 12,197 horses in the CDE pedigree, available from the 2020 routine genetic evaluations of the CDE breeding program (starting in 2004). Dressage and Eventing EBV values were also assessed. Results showed values of F higher than expected under random mating; this pointed to some degree of inbred matings. With regard to the evolution of breeding values, we found that, in general, EBVs of offspring were higher than the EBVs of parents. Notwithstanding, there is still a need for improvement in population management and the coordination of the breeders to get higher responses but controlling the loss of genetic diversity in the CDE breed.

An overview of international genetic evaluations of show jumping in sport horses

The breeding of sport horses to compete in the Olympic disciplines of show jumping, eventing, and dressage is fast becoming a global industry with the increased use of reproductive technologies, including artificial insemination and embryo transfer. Reproductive technologies have facilitated the dissemination of genetics from elite horses across multiple countries and breeds as breeders are no longer limited by location. Due to this increased level of crossbreeding, there is an increased need for estimated breeding values (EBVs) for sport horse performance that can be compared across breeds and countries. However, the implementation of across-breed or across-country genetic evaluations has been limited by the differences in each studbook’s individual breeding programs and genetic evaluations. Consequently, the aim of this review was to compare the genetic evaluations for show jumping of sport horse studbooks worldwide. The top sport horse studbooks in the world according to the World Breeding Federation for Sport Horses Studbook Rankings 2019 were contacted by email to request information on their current breeding programs and genetic evaluations. Twenty-six of the 51 studbooks contacted replied to this request but only 18 of these studbooks conducted their own genetic evaluations or were part of a larger genetic evaluation in their country of origin. The other eight studbooks were not involved in genetic evaluations at present but expressed an interest in the implementation of such in the future. Overall, many differences were identified among the genetic evaluations of each studbook or each country. The definition of show jumping performance differed within each evaluation and the methods and models utilized also differed. Despite some stallions and mares being registered in multiple studbooks or having progeny in multiple studbooks, these differences make comparison of EBVs across studbooks difficult. Further transparency and collaboration of sport horse studbooks with organizations such as Interstallion, will be essential to facilitate any future implementation of international genetic evaluations for show jumping performance.

Should We Agree to Disagree? An Evaluation of the Inter-Rater Reliability of Gait Quality Traits in Franches-Montagnes Stallions

Gait quality, that is, the way horses move according to functional and aesthetic principles, englobes many traits that are scored by experts during breeding competitions. The experts can score a trait on a subjective valuating (SV) scale or on a linear profiling (LP) scale representing the biological extremes of the population. However, the reliability of the appraisal of gait quality traits has not been extensively evaluated. In this study, seven breed experts appraised the walk and trot quality of 24 Franches-Montagnes stallions presented in hand on a sand track. Inter-rater reliabilities of six traits (five SV and one LP) at the walk and eight traits (five SV and three LP) at the trot were estimated with intraclass correlation coefficients (ICCs). The inter-rater reliabilities were poor (ICC < 0.50). The scale anchoring varied between experts, and the variance of scores was low. There were no systematic differences in inter-rater reliability between LP and SV traits. Future studies should determine whether the inter-rater reliabilities may be increased by a more precise definition of the scores within each trait to improve the absolute agreement between experts, by a more uniform scale anchoring between experts, and by decreasing the number of scale items. However, considering the inherent limitations of the human eye in observing high-speed movement, the use of a field-applicable kinematic measurement system may support breeding experts in the appraisal of gait quality traits in the future.

Crossbreed genetic performance study in the eventing horse competition

Eventing is an equestrian discipline combining dressage, show jumping and cross-country exercises. The Spanish Sport Horse (SSH) was used in this study as an example to develop a method to ascertain the influence of parental breeds on particular performances by linking their parental genetic contribution with the individual phenotype value computing the optimal breed contribution for each trait evaluated in eventing. Data included 1220 eventing records from 210 SSH animals. The genetic contribution of six main founder populations were computed for each SSH: the Spanish Purebreed (SPB), Arab Horse (A), Thoroughbred (TB), Selle Français (SF), German breeds (G) and North(-west) European (N) breeds. For this analysis we used BLUP (best linear unbiased predictor) animal models for five defined traits and for the total score. The genetic contribution as linear and quadratic adjustment and the interaction between genetic contributions were included as covariates in the genetic model to separate the possible combining ability from the breeding values. The optimal breed genetic contribution for each trait was maximised by using a simplex method. The best combination for conformation was 51% SPB and 49% N, for cross-country aptitude 23% SPB and 77% N, for dressage 48% SF and 52% N, and for show jumping 64% A and 36% N. For cross-country the best performance was predicted using 100% N genetic contribution and for the total score of 24% SF and 76% N. The combination of two breeds (group of breeds) seemed to be the best option for most of the traits. Although the results should be interpreted with caution, the importance of this paper is that it can be considered as a starting point of the analysis. The methodology applied here performed nicely in searching for the best contribution of several breeds to find the best combination for particular interests and could, therefore, be useful for other species/populations.

Modelling genetic evaluation for dressage in Pura Raza Español horses with focus on the rider effect

The most popular use of the Pura Raza Español horse in sport is for dressage competitions. Tests on young sport horses were first established in 2004 in Spain to collect data for the genetic evaluation of this breed's suitability for dressage. The aim of this study was to compare eight different models to find out the most appropriate way to include the rider in the genetic evaluation of dressage. A progressive removal of systematic effects from model was also analysed. A total of 8867 performance records collected between 2004 and 2011 from 1234 horses aged between 4 and 6 years old were used. The final score in the dressage test was used as the performance trait. The pedigree matrix contained 8487 individuals. A BLUP animal model was applied using a Bayesian approach with TM software. The horse's age, gender, travelling time, training level, stud of birth and event were included as systematic effects in all the models. Apart from the animal and residual effects that were present in all models, different models were compared combining random effects such as the rider, match (i.e. rider-horse interaction) and permanent environmental effects. A cross-validation approach was used to evaluate the models' prediction ability. The best model included the permanent environmental, rider and match random effects. As far as systematic effects are concerned, the event or the stud of birth was essential effects needed to fit the data.

Estimating variance components and predicting breeding values for eventing disciplines and grades in sport horses

Eventing competitions in Great Britain (GB) comprise three disciplines, each split into four grades, yielding 12 discipline-grade traits. As there is a demand for tools to estimate (co)variance matrices with a large number of traits, the aim of this work was to investigate different methods to produce large (co)variance matrices using GB eventing data. Data from 1999 to 2008 were used and penalty points were converted to normal scores. A sire model was utilised to estimate fixed effects of gender, age and class, and random effects of sire, horse and rider. Three methods were used to estimate (co)variance matrices. Method 1 used a method based on Gibbs sampling and data augmentation and imputation. Methods 2a and 2b combined sub-matrices from bivariate analyses; one took samples from a multivariate Normal distribution defined by the covariance matrix from each bivariate analysis, then analysed these data in a 12-trait multivariate analysis; the other replaced negative eigenvalues in the matrix with positive values to obtain a positive definite (co)variance matrix. A formal comparison of models could not be conducted; however, estimates from all methods, particularly Methods 2a/2b, were in reasonable agreement. The computational requirements of Method 1 were much less compared with Methods 2a or 2b. Method 2a heritability estimates were as follows: for dressage 7.2% to 9.0%, for show jumping 8.9% to 16.2% and for cross-country 1.3% to 1.4%. Method 1 heritability estimates were higher for the advanced grades, particularly for dressage (17.1%) and show jumping (22.6%). Irrespective of the model, genetic correlations between grades, for dressage and show jumping, were positive, high and significant, ranging from 0.59 to 0.99 for Method 2a and 0.78 to 0.95 for Method 1. For cross-country, using Method 2a, genetic correlations were only significant between novice and pre-novice (0.75); however, using Method 1 estimates were all significant and low to moderate (0.36 to 0.70). Between-discipline correlations were all low and of mixed sign. All methods produced positive definite 12 × 12 (co)variance matrices, suitable for the prediction of breeding values. Method 1 benefits from much reduced computational requirements, and by performing a true multivariate analysis.