Contribution of Reproduction Management and Technologies to Genetic Progress in Horse Breeding

J Equine Vet Sci. 2020 Jun:89:103016. doi: 10.1016/j.jevs.2020.103016. Epub 2020 Apr 28.

Abstract

Reproductive technologies aim at improving fertility with the ultimate result of improving genetic selection. In equidae, the respective contribution of different methods of horse management and breeding to genetic progress remain difficult to evaluate as breeding strategies affect the number of offspring per mare or stallion whereas different selection methods (based on pedigree, performance, genomics or progeny's performance) will be applicable at different ages, leading to different accuracy in the estimation of the breeding value. Here, a mathematical model was applied to evaluate theoretical genetic progress depending on breeding conditions in horses. The model showed that for breeding systems ranging from 0.6 to 2 foals/year/mare and from 10 to 150 foals/year for stallions, when selection of the best animals is strictly made by a truncation, the genetic progress is accelerated by (1) increasing the number of offspring per year, (2) the start of reproduction as soon as the age of 2 in both sexes, and (3) reducing the number of years of use for stallions from 10 to 5 years. The calculation showed that using all ways of improvement could provide an increase in genetic progress of up to +270% and +226% in mares and stallions, respectively, above the basal reference situation of 100%. In the Selle Français breed, the observed reproductive management parameters (10 years generation interval, 10 foals/stallion and 0.55 foals/mare) are close to the worst conditions of the model. In addition, the best mares are not selected for breeding. In conclusion, new reproductive technologies, genomic selection, and breeding younger animals will increase genetic gain.

Keywords: Equine; Genetics; Reproduction; Selection; Show-jumping.

MeSH terms

  • Animals
  • Female
  • Fertility*
  • Horses / genetics
  • Male
  • Pedigree
  • Reproduction* / genetics