Comparing Bayesian models for the genetic evaluation of oocytes and embryo counts in Dairy Gir cattle

Abstract

Count traits are usually explored in livestock breeding programs, and they usually do not fit into normal distribution, requiring alternatives to adjust the phenotype to estimate accurate genetic parameters and breeding values. Alternatively, distribution such as Poisson can be used to evaluate count traits. This study aimed to compare and discuss the genetic evaluation for oocyte and embryo counts considering Gaussian (untransformed variable — LIN; transformed by logarithm — LOG; transformed by Anscombe — ANS) and Poisson (POI) distributions. The data comprised 11,343 total oocytes (TO), viable oocytes (VO), cleaved embryos (CE), and viable embryo (VE) records of ovum pick-up from 1740 Dairy Gir heifers and cows. The genetic parameters and breeding values were estimated by the MCMCglmm package of the R software. The posterior means of heritability varied from 0.40 (LIN) to 0.49 (POI) for TO, 0.39 (LIN) to 0.49 (POI) for VO, 0.30 (LOG) to 0.41 (POI) for cleaved embryos, and 0.19 (LIN) to 0.32 (POI) for viable embryos. The posterior means of repeatability varied from 0.56 (LIN) to 0.65 (POI) for TO, 0.53 (LOG) to 0.63 (POI) for VO, 0.44 (LOG) to 0.60 (POI) for CE, and 0.36 (LOG) to 0.56 (POI) for VE. Deviance information criterion and mean squared residuals indicated that POI model should be used for the genetic evaluation of embryo and oocyte count traits. Spearman’s rank correlation between estimated breeding value (EBV) for embryo and oocyte count traits computed by POI, LOG, and ANS models was high (ranging from 0.77 to 0.99), indicating little reranking among the best animals. The POI model is the most adequate for genetic evaluation, resulting in more reliable EBV of oocyte and embryo count traits for Dairy Gir cattle.