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

Benefits of MOET and JIVET in Optimised Sheep Breeding Programs

The additional genetic gain from implementing multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) additional to using artificial insemination (AI) and natural mating (N) in sheep breeding programs was assessed. This study was a stochastic simulation and selection based on optimum contributions for varying levels of inbreeding restriction. The genetic gain achieved after 20 years for an AI/N program was 4.89 and 5.16 units of genetic SD (h²=0.3) when inbreeding was restricted to 1% and 2% per generation, respectively. The additional gain from MOET was 23% and 28% and the additional gain from the addition of JIVET to MOET and AI/N increased genetic gain 60% and 56% for these two levels of inbreeding when compared to AI/N. With the addition of each technology, generation interval decreased, as did the number of breeding ewes

Accounting for the Cost of Reproductive Technologies During Selection in Sheep Breeding Programs

Female reproductive technologies, such as MOET and JIVET, have been shown to increase the rate of genetic gain. However, they incur substantial costs to breeders using them. In this work, optimal contribution selection was used to find the balance between genetic merit, co-ancestry and cost of reproductive technologies in sheep breeding programs. To offset the cost of using the reproductive technologies, breeders received a premium based on the value of the genetic gain achieved by the ram buyers. Australian terminal sire and Merino breeding programs were simulated, using industry indexes. For the terminal sire breeding program, the premium needed to be greater than 50% beforen reproductive technologies were used. In the Merino breeding program, where the standard deviation of the index is 3 times higher than the terminal index, reproductive technologies were used with lower premiums (6% and 32% premiums, respectively). For both breeding programs, the rate of genetic gain increased with more allocations of reproductive technologies. There was also a higher proportion of JIVET assigned compared to MOET, due to a lower cost per lamb. The benefits of genomic selection were greatest in the merino program, due to the higher use of JIVET. Assigning costs of reproductive technologies allows for robust and practical breeding programs to be designed

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

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

Increased genetic gains in sheep breeding programs from using female reproductive technologies combined with genomic selection

Reproductive technologies such as MOET and JIVET can boost rates of genetic gain but they can also increase rates of inbreeding. We used optimal contribution selection to explore these potential benefits while managing inbreeding and we evaluated the synergies that exists between genomic selection (GS) and reproductive technologies. When selecting for a trait that can be measured early in life and on both sexes, GS combined with MOET and JIVET gave 46% more gain. When selecting on a late measured trait, use of MOET was not beneficial without GS. However, breeding programs combining GS with MOET or MOET + JIVET had increased genetic gain of 39% and 83%, respectively, while the inbreeding was limited to a 10% increase over 20 years. This provides evidence that reproductive technologies and genomic selection can be useful tools for nucleus breeders

Optimised Livestock Breeding Programs Using Female Reproductive Technologies and Genomic Selection

This thesis explores various methods to optimise breeding programs that use female reproductive technologies and genomic selection. Simulation studies have shown that female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and transfer (JIVET) can increase rates of genetic gain through increased female selection intensity and decreased generation interval. Furthermore the use of genomic selection has facilitated better selection decisions to be made on younger selection candidates that may not have phenotypic measurements. When combining genomic selection with reproductive technologies the rate of genetic gain could be further accelerated. However intensive use of the best females in breeding programs can also increase the rate of inbreeding to unsustainable levels. This thesis aimed to stochastically simulate breeding programs where reproductive and genomic technologies are optimally implemented while maintaining a sustainable increase of inbreeding. The impacts of using reproductive technologies and/or genomic selection were evaluated for breeding programs across species. Furthermore, the thesis investigated a cost-benefit analysis of using reproductive technologies which led to a further study that optimized the use of reproductive technologies that considered their costs as well as future co-ancestry during selection

Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values

'Background': Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) can boost rates of genetic gain but they can also increase rates of inbreeding. Inbreeding can be managed using the principles of optimal contribution selection (OCS), which maximizes genetic gain while placing a penalty on the rate of inbreeding. We evaluated the potential benefits and synergies that exist between genomic selection (GS) and reproductive technologies under OCS for sheep and cattle breeding programs. 'Methods': Various breeding program scenarios were simulated stochastically including: (1) a sheep breeding program for the selection of a single trait that could be measured either early or late in life; (2) a beef breeding program with an early or late trait; and (3) a dairy breeding program with a sex limited trait. OCS was applied using a range of penalties (severe to no penalty) on co-ancestry of selection candidates, with the possibility of using multiple ovulation and embryo transfer (MOET) and/or juvenile in vitro embryo production and embryo transfer (JIVET) for females. Each breeding program was simulated with and without genomic selection. 'Results': All breeding programs could be penalized to result in an inbreeding rate of 1 % increase per generation. The addition of MOET to artificial insemination or natural breeding (AI/N), without the use of GS yielded an extra 25 to 60 % genetic gain. The further addition of JIVET did not yield an extra genetic gain. When GS was used, MOET and MOET + JIVET programs increased rates of genetic gain by 38 to 76 % and 51 to 81 % compared to AI/N, respectively. 'Conclusions': Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited. Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies. Applying a range of penalties to co-ancestry of selection candidates allows a comprehensive exploration of the inbreeding vs. genetic gain space

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