Forward cross-validation analyses were used to quantify the changes in BREEDPLAN EBVs from single-step genetic evaluations compared to traditional pedigree-based evaluations for Angus, Brahman, Hereford, Santa Gertrudis and Wagyu breeds. EBVs were generated from full multi-trait evaluations for each breed and compared to EBVs from an evaluation where all the phenotypic records were removed from the last four year drops of animals (termed Validation). Results for the sub-set of validation animals that were SNP genotyped showed the population-based accuracy of single-step EBVs were higher than pedigree-based accuracies for all breeds and traits. However, the magnitudes of the accuracy increases differed across breeds and traits, and generally reflected differences in the size of the training populations for each trait. The largest increase in accuracy, averaged across all traits in a breed, was observed for Angus (24%) and the smallest for Santa Gertrudis (5%). Across breeds, the largest increases in accuracy occurred for the growth trait EBVs compared to smaller increases for abattoir carcase, female reproduction and NFI EBVs. This study has shown the benefits of single-step genomic evaluations, and the opportunity to increase rates of genetic progress, through the increased accuracy generated. The study also highlighted breeds and traits which could benefit from additional recording to increase accuracies from single-step.

This study aimed to detect genomic regions associated with scrotal circumference in Australian Brahman, Hereford, and Wagyu beef cattle breeds. The presence of selection signatures was based on the FST test, using data on the genotype and BREEDPLAN estimated breeding values for SC of 100,990 animals. Signals of selection for scrotal circumference were identified in genomic regions on several chromosomes, especially chromosome 14 in Brahman with most candidate genes under selection associated with male fertility or growth. The findings of this study may be applicable to breeding programs using more informative markers and assigning higher weights to them to increase the accuracy of genomic predictions and improve the reproductive performance of beef cattle.

Increasingly the northern beef industry is selecting for more polled animals. However, a common industry perception is this selection will be associated with decreased performance. Single trait selection for any trait can lead to genetically inferior animals and this could occur if selection was only to occur for polled. From a selection viewpoint it is important to establish if the polled locus is genetically linked to other economically important traits. The recording and design of the Repronomics project (Johnston et al. 2017) provides a unique dataset to examine the association between polled status (both genotypic and phenotypic) and early growth traits. This was achieved by analysing the effects of polled status within large half sib-families where the polled gene is segregating in 3 tropically adapted beef breeds (viz. Brahman, Droughtmaster and Santa Gertrudis).

Genetic improvement requires selection for all traits in the breeding objective and increasingly this includes consideration of traits associated with animal welfare and social licence. A unique program called the 'Polled Accelerator' was developed for a large beef cattle population to rapidly increase the frequency of polledness. The program was constructed using a unique combination of existing and emerging genomic technologies and methods including DNA tests for polled/horn and Pompe's disease, DNA sire assignment, genomic breed composition, imputation and single-step genomic evaluation. Phenotypically polled young males were harvested from the commercial tier and through the program, high genetic merit polled animals were eligible for promotion to the multiplier and nucleus tiers of the breeding program. The application of multiple genomic technologies will allow the rapid introgression of polledness into this population without compromising the composite breed composition, breeding program structure, future genetic progress or genetic diversity.

Northern Australia is characterised by high temperatures, seasonally fluctuating feed quality and unique parasitic challenges. Bos indicus and bos indicus derived breeds are favoured for their ability to withstand these challenges and produce in the harsh northern Australian environment. Cow reproduction is an important driver for breeding profitable beef enterprises but has typically been difficult to select for with traits generally being lowly heritable, sex-limited and expressed late in life. The key cow reproduction trait in the Australian BREEDPLAN genetic evaluation is days to calving which has been demonstrated to be highly correlated with calving success (i.e. did the cow calve or not). The development of two highly heritable ovarian ultrasound scan traits when implemented as part of genomic selection may be a game changer in creating opportunities for genetic improvement of cow reproduction in northern beef herds. Age at puberty and lactation anoestrus interval are both highly heritable (h² estimates of approximately 0.50 and 0.40, respectively) and correlated to days to calving -the key cow reproduction trait currently analysed in BREEDPLAN. The purpose of this chapter was first to outline the current genetic improvement program for female reproduction in northern Australia beef cattle breeds, and secondly to show how the incorporation of ovarian scan traits and genomic selection are providing a new and exciting opportunity to make significant genetic improvement for female reproduction.

Net feed intake (NFI) is the residual portion of daily feed intake (DFI) not explained by growth or maintenance requirements. The NFI phenotype (NFIp) is based on a 70-day test period where DFI and fortnightly weights (to calculate average daily gain (ADG) and maintenance as metabolic mid-weight (MMWT)) are measured. Recording NFIp is costly, and shortening the test length would be advantageous. However, research has shown that ADG cannot be accurately measured from a shortened test. Genetic NFI EBVs (NFIg) were calculated using DFI EBV adjusted for ADG and MMWT EBV and were shown to have a Pearson correlation of 0.99 with the NFIp EBV from 3,088 Angus steers. The regression slope between NFIg and NFIp EBVs was 1.14. Alternative NFIg models where growth and maintenance requirements were obtained from BREEDPLAN live weight traits instead of live weights recorded in the test period, demonstrated high Pearson correlations (r=0.87 to 0.93) and regression slopes between 0.63 and 0.97 with NFIp EBVs. Results suggest that genetic NFI EBVs can be obtained, with growth and maintenance requirements being determined from BREEDPLAN live weight traits. This provides the opportunity to determine if the length of the test to measure DFI can be shortened, reducing the cost of recording NFI per animal.

Research has shown that to maximise benefits (i.e. EBV accuracy and spread and decreased generation interval) of genomic selection, reference populations of genotyped and phenotyped animals need to be large, diverse in relationships and closely related to the selection generation. In practice, applying these design principles can be challenging as metrics to aid decision making are often not available. This paper applies a metric that objectively describes reference populations and their impact on accuracy for seven Australian beef populations. All populations for live weight and abattoir carcase had different levels of phenotyping, genotyping and overall size. Carcase traits had the lowest reference population size, and assessment of average relatedness in almost all the breeds showed there were herds that were not currently represented in the reference population. Generally, increasing reference size resulted in increased accuracy, but there were some exceptions. The metrics described in this paper are easy to apply and can assist in the construction of reference populations.

BREEDPLAN net feed intake (NFI) EBV is derived from a phenotypic regression based on a 70-day feed intake test. Genetic NFI (NFIg) EBVs have been proposed as an alternative EBV and this recent development may also allow for a shortened feed intake test period. This study used feed intake records of 3,088 Angus steers from the full 70-day test and compared them to daily feed intake (DFI) from shortened test periods. Results showed DFI from shortened test periods had similar means but increased phenotypic variation. Phenotypic correlation with DFI from the full test period decreased as the test period decreased in weekly intervals and ranged between 0.75 and 0.99. NFIg EBVs were predicted using DFI from different length tests. The mean of all NFIg EBVs was close to zero, but the EBV standard deviation increased as the test period decreased. Pearson correlations between NFIg EBVs from a full test period and reduced test periods ranged between 0.73 and 0.99, the regression slope of NFIg from reduced test periods on NFIg from the full test period ranged between 0.73 and 0.95, and the bias ranged between 0.00 and 0.02. These results indicate that as the test period decreases, the spread of EBVs increases, resulting in extreme animals having overestimated NFIg EBVs. A shortened DFI test period could be used to estimate NFIg EBVs.

Optimum polygenic and genomic weights enhance the accuracy of breeding value estimates in single-step genomic evaluations. This study estimated the contribution from marker information to total additive genetic variation referred as λ using an extended single-step model in a multi-trait variance component estimation based procedure using data for six Australian Angus carcase traits. The λ for these traits ranged from 0.54 (for carcass intramuscular fat) to 0.79 (for carcass eye muscle area). Heritabilities were similar between the pedigree only and the extended single-step multi-trait model when using the total genetic variance, and ranged from 0.37 (for carcass rib fat) to 0.53 (for carcass weight), suggesting that the single-step model did not explain more genetic variance than pedigree based models. Results suggest that the scalar λ in the current single-step routine evaluation could be replaced by an extended single-step model allowing for different proportions of the additive genetic co-variance explained by markers for all elements of the genetic co-variance matrix.