Genomic selection strategies to improve maternal traits in Norwegian White Sheep

This study tested and compared different implementation strategies for genomic selection for Norwegian White Sheep, aiming to increase genetic gain for maternal traits. These strategies were evaluated for their genetic gain ingrowth, carcass and maternal traits, total genetic gain, a weighted sum of the gain in each trait and rates of inbreeding through a full-scale stochastic simulation. Results showed genomic selection schemes to increase genetic gain for maternal traits but reduced genetic gain for other traits. This could also be obtained by selecting rams for artificial selection at a higher age. Implementation of genomic selection in the current breeding structure increased genetic gain for maternal traits up to 57%, outcompeted by reducing the generation interval for artificial insemination rams from current 3 to 2 years. Then, total genetic gain for maternal traits increased by 65%-77% and total genetic gain by18%-20%, but at increased rates of inbreeding.

Towards Improving the Outcomes of Assisted Reproductive Technologies of Cattle and Sheep, with Particular Focus on Recipient Management

The Australian agricultural industry contributes AUD 47 billion to the Australian economy, and Australia is the world's largest exporter of sheep meat and the third largest for beef. Within Australia, sheep meat consumption continues to rise, with beef consumption being amongst the highest in the world; therefore, efficient strategies to increase herd/flock size are integral to the success of these industries. Reproductive management is crucial to increasing the efficiency of Australian breeding programs. The use of assisted reproductive technologies (ARTs) has the potential to increase efficiency significantly. The implementation of multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilization and embryo transfer (JIVET) in combination with genomic selection and natural mating and AI is the most efficient way to increase genetic gain, and thus increase reproductive efficiency within the Australian livestock industries. However, ARTs are costly, and high variation, particularly between embryo transfer recipients in their ability to maintain pregnancy, is a significant constraint to the widespread commercial adoption of ARTs. The use of a phenotypic marker for the selection of recipients, as well as the better management of recipient animals, may be an efficient and cost-effective means to increase the productivity of the Australian livestock industry.

Genotyping strategies of selection candidates in livestock breeding programmes

Benefits of genomic selection (GS) in livestock breeding operations are well known particularly where traits are sex-limited, hard to measure, have a low heritability and/or measured later in life. Sheep and beef breeders have a higher cost:benefit ratio for GS compared to dairy. Therefore, strategies for genotyping selection candidates should be explored to maximize the economic benefit of GS. The aim of the paper was to investigate, via simulation, the additional genetic gain achieved by selecting proportions of male selection candidates to be genotyped via truncation selection. A two-trait selection index was used that contained an easy and early-in-life measurement (such as post-weaning weight) as well as a hard-to-measure trait (such as intra-muscular fat). We also evaluated the optimal proportion of female selection candidates to be genotyped in breeding programmes using natural mating and/or artificial insemination (NatAI), multiple ovulation and embryo transfer (MOET) or juvenile in vitro fertilization and embryo transfer (JIVET). The final aim of the project was to investigate the total dollars spent to increase the genetic merit by one genetic standard deviation (SD) using GS and/or reproductive technologies. For NatAI and MOET breeding programmes, females were selected to have progeny by 2 years of age, while 1-month-old females were required for JIVET. Genomic testing the top 20% of male selection candidates achieved 80% of the maximum benefit from GS when selection of male candidates prior to genomic testing had an accuracy of 0.36, while 54% needed to be tested to get the same benefit when the prior selection accuracy was 0.11. To achieve 80% of the maximum benefit in female, selection required 66%, 47% and 56% of female selection candidates to be genotyped in NatAI, MOET and JIVET breeding programmes, respectively. While JIVET and MOET breeding programmes achieved the highest annual genetic gain, genotyping male selection candidates provides the most economical way to increase rates of genetic gain facilitated by genomic testing.

Optimizing female allocation to reproductive technologies considering merit, inbreeding and cost in nucleus breeding programmes with genomic selection

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilization and embryo transfer (JIVET) have been shown to accelerate genetic gain by increasing selection intensity and decreasing generation interval. Genomic selection (GS) increases the accuracy of selection of young candidates which can further accelerate genetic gain. Optimal contribution selection (OCS) is an effective method of keeping the rate of inbreeding at a sustainable level while increasing genetic merit. OCS could also be used to selectively and optimally allocate reproductive technologies in mate selection while accounting for their cost. This study uses stochastic simulation to simulate breeding programmes that use a combination of artificial insemination (AI) or natural mating (N), MOET and JIVET with GS. OCS was used to restrict inbreeding to 1.0% increase per generation and also to optimize use of reproductive technologies, considering their effect on genetic gain as well as their cost. Two Australian sheep breeding objectives were used as an example to illustrate the methodology-a terminal sire breeding objective (A) and a dual-purpose self-replacing breeding objective (B). The objective function used for optimization considered genetic merit, constrained inbreeding and cost of technologies where costs were offset by a premium paid to the seedstock breeder investing in female reproductive technologies. The premium was based on the cumulative discounted expression of genetic merit in the progeny of a commercial tier in the breeding programme multiplied by the proportion of that benefit received by the breeder. With breeding objective B, the highest premium of 64% paid to the breeder resulted in the highest allocation of reproductive technologies (4%-10% for MOET and 19%-54% for JIVET) and hence the highest annual genetic gain. Conversely, breeding objective A, which had a lower dollar value of the breeding objective and a maximum of 5% mating types for JIVET and zero for MOET were optimal, even when highest premiums were paid. This study highlights that the level of investment in breeding technologies to accelerate genetic gain depends on the investment of genetic improvement returned to the breeder per index point gain achieved. It also demonstrates that breeding programmes can be optimized including allocation of reproductive technologies at the individual animal level. Accounting for revenue to the breeder and cost of the technologies can facilitate more practical decision support for beef and sheep breeders.