Increased genetic gains in multi-trait sheep indices using female reproductive technologies combined with optimal contribution selection and genomic breeding values

Abstract

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilisation and embryo transfer (JIVET) can produce multiple offspring per mating in sheep and cattle. In breeding programs this allows for higher female selection intensity and, in the case of JIVET, a reduction in generation interval, resulting in higher rates of genetic gain. Low selection accuracy of young females entering JIVET has often dissuaded producers from using this technology. However, genomic selection (GS) could increase selection accuracy of candidates at a younger age to help increase rates of genetic gain. This increase might vary for different traits in multiple trait breeding programs depending on genetic parameters and the practicality of recording, particularly for hard to measure traits. This study used both stochastic (animals) and deterministic (GS) simulation to evaluate the effect of reproductive technologies on the genetic gain for various traits in sheep breeding programs, both with and without GS. Optimal contribution selection was used to manage inbreeding and to optimally assign reproductive technologies to individual selection candidates. Two Australian sheep industry indexes were used – a terminal sire index that focussed on growth and carcass traits (the ‘Lamb 2020’ index) and a Merino index that focuses on wool traits, bodyweight, and reproduction (MP+). We observed that breeding programs using artificial insemination or natural mating (AI/N) + MOET, compared with AI/N alone, yielded an extra 39% and 27% genetic gain for terminal and Merino indexes without GS, respectively. However, the addition of JIVET to AI/N + MOET without GS only yielded an extra 1% genetic gain for terminal index and no extra gain in the Merino index. When GS was used in breeding programs, we observed AI/N + MOET + JIVET outperformed AI/N + MOET by 21% and 33% for terminal and Merino indexes, respectively. The implementation of GS increased genetic gain where reproductive technologies were used by 9–34% in Lamb 2020 and 37–98% in MP+. Individual trait response to selection varied in each breeding program. The combination of GS and reproductive technologies allowed for greater genetic gain in both indexes especially for hard to measure traits, but had limited effect on the traits that already had a large amount of early age records.