Bayesian and REML analysis of twinning and fertility in Thoroughbred horses

Horses have low fertility, which affects profitability of breeding. Additional economic loss is generated by various complications accompanying twin pregnancies which are particularly prevalent in Thoroughbred horses. Therefore it is important to identify environmental and genetic factors influencing this trait. The analysis was based on studbooks from 1994 to 2004 provided by the Czech Jockey Club in Prague. The dataset contained 7703 records of 2161 Thoroughbred mares born between 1975 and 1996. Variance components for twinning rate and fertility were estimated using the ASREML and MCMCglmm/R packages, with a threshold animal model and a threshold sire model with binary distribution and a LOGIT link function. Estimates of additive genetic variance for fertility were much higher for the Bayesian methods than for REML. This resulted in higher heritabilities, though the credible interval for the Bayesian estimates was wide. Fertility traits, such as twinning rate should be modelled with generalised linear mixed-effects models (GLMMs). The GLMMs are much more suited for traits having a binary distribution than linear models. For twining, a trait with low frequency, sire model provided more precise estimates than animal model.