Genomic selection strategies to optimize the use of multiple ovulation and embryo transfer schemes in dairy cattle breeding programs

Abstract

The aim of this study was to assess the impact of varying features of an open multiple ovulation and embryo transfer (MOET) nucleus used in a genomic dairy cattle breeding scheme on both genetic gain and inbreeding rates. The Viking Red breeding scheme served as a case study to design scenarios that were stochastically simulated. We analyzed the number of AI sires used in the breeding population, the number of flushed heifers, the number of flushings per heifer and the genotyping capacity allocated to young females. The results supported that setting up a MOET program in a genomic dairy cattle scheme increases genetic gain without increasing inbreeding rates when the MOET nucleus size and the number of AI sires in service are large enough. Secondly, it was shown that increasing the number of genotyped heifers could not compensate the loss in genetic gain caused by closing the MOET nucleus. On the contrary, when extending the flushing capacity of the MOET program, increasing the number of flushings per heifer had a greater impact on genetic gain, but also on inbreeding rates, than increasing the number of flushed females. So, when a constraint applies on the flushing capacity in an open MOET scheme and the achieved inbreeding rate permits it, it seems more relevant to increase the number of flushings per heifer than the number of flushed heifers. Results also indicated that the number of genotypings allocated to females had to be sufficient to get maximal returns from the MOET scheme. In this case study, little extra genetic gain could be obtained by extending the MOET scheme size with the initial genotyping strategy (800 genotyped females). Indeed, the genotyping capacity should permit to genotype all heifers produced in the MOET scheme to discriminate the best heifers within families, and should be also sufficient to identify the best heifers outside the MOET nucleus.