Genetic improvement of litter size in sheep. A comparison of selection methods

Abstract

The objectives of this work were to examine the usefulness of measuring ovulation rate (OR) in order to improve genetic progress of litter size (LS) in sheep and to study different selection criteria combining OR and prenatal survival (ES) performance. Responses to selection for 5 generations within a population of 20 male and 600 female parents were compared using Monte-Carlo simulation techniques with 50 replicates per selection method. Two breeds with low (Merino) and medium (Lacaune) prolificacy were considered. Records were generated according to a bivariate threshold model for OR and ES. Heritabilities of OR and ES in the underlying scale were assumed constant over breeds and equal to 0.35 and 0.11, respectively, with a genetic correlation of -0.40 between these traits. Four methods of genetic evaluation were compared: univariate best linear unbiased prediction (BLUP) using LS records only (b-LS); univariate BLUP on OR records (b-OR); bivariate BLUP using OR and LS records (b-ORLS); and a maximum a posteriori predictor of a generalised linear model whereby OR was analysed as a continuous trait and ES as a binary threshold trait (t-ORES). Response in LS was very similar with b-LS, b-ORLS and t-ORES, whereas it was significantly lower with b-OR. Response in OR was maximum with b-OR and minimum with b-LS. In contrast, response in ES was maximum with b-LS. This study raised the question as to why selection based on indices combining information from both OR and ES did not perform better than selection using LS only. © 1995 Elsevier/INRA.