The 25th Association for the Advancement of Animal Breeding and Genetics (AAABG) Conference was held from 26th to 28th July 2023 in Perth.
The conference is widely considered the premier livestock breeding conference in Australia and New Zealand and provides an opportunity for researchers, professionals, and enthusiasts in the field of animal breeding and genetics to get together in two-year intervals to share the latest developments in livestock genetics research.
Eighteen papers showcasing the recent advancements towards the Angus breed genetic improvement were presented at the AAABG conference by Angus Australia staff or Angus Australia’s key R&D collaborators.
A highlight was Dr Pamela Alexandre from CSIRO was awarded the Young Scientist Award in recognition of her contribution in developing the fertility indicator traits for the Angus HeiferSELECT genomic tool. This was the second occasion where the research related to Angus Australia’s genomic tools has been acknowledged. During the 2021 conference, the paper on the development and validation of Angus SteerSELECT was awarded as the Best Animal Production Science Issue Paper.
The 25th conference full proceedings and the papers in Animal Production Science – Special Issue can be downloaded by visiting the websites.
For further information, contact staff at Angus Australia.
P.A. Alexandre1, L.R. Porto-Neto1, B.C. Hine1, A.M. Samaraweera2, A.I. Byrne2, A.B. Ingham1, C.J. Duff2 and A. Reverter1, 1CSIRO, 3Angus Australia
Angus HeiferSELECT is a genomic tool designed to inform the selection of replacement heifers by providing genomic estimated breeding values (GEBV) for traits related to cow-calf production, feedlot performance, carcase quality, and resilience. Here, we explore the incorporation of fertility indicator measures into the gamut of traits using data from 9,155 heifers in the Angus Australia database. The heritability of age at first calving (AFC), days to calving (DC), and pregnancy test measured in weeks (PREG) were 0.25, 0.26 and 0.32, respectively. The three traits were favourably correlated. AFC and DC presented a genetic correlation of 0.45, while PREG presented negative correlations to the other traits (-0.23 and -0.45, respectively). The accuracy of the GEBVs varied from 0.24 for DC to 0.34 for PREG. Although the three traits showed low to moderate heritability and prediction accuracy, phenotypic differences between animals at the top and bottom quartiles when ranking animals based on GEBV demonstrate the positive impact that could be achieved by selecting for improved female fertility in commercial enterprises. The findings from this study have demonstrated that DC, AFC and PREG would all be suitable traits for inclusion in the Angus HeiferSELECT tool. READ MORE
Angus BreedCHECK – Validation using industry data
C.J. Duff1, A.M. Samaraweera1, A.I Byrne1, A.B. Ingham2, P.A. Alexandre2, L.R. Porto-Neto2 and A. Reverter2 1Angus Australia, 2CSIRO
Angus BREEDCHECK is a genomic based tool that predicts breed composition for 11 breeds with a focus on Angus content. In this study we compare the Angus BreedCHECK genomic breed composition (GBC) estimates to pedigree-based breed content estimates (PBC) for five animal classes (AC) recorded on the Angus Australia database. The AC populations being Herd Book Register (HBR), Angus Performance Register (APR), Angus Commercial Register (ACR), Angus HeiferSELECT (AHS) and the Multi Breed Register (MBR), including 143,879, 75,369, 6,379,25,710, and 2,780 animals, respectively.
Additionally, comparisons were made within a subset of Angus cross Bos indicus (n=1,201) and Angus cross Hereford (n=365) cattle, as determined by PBC, from the MBR. Across the 254,117 animals in this study, there is close alignment in the mean and standard deviation of Angus content as derived by GBC and PBC, with a mean of 99.3% and 99.4% and standard deviation of 3.6 and 4.1, respectively. While 97.7% of the study animals fell within ±10% in Angus content when comparing GBC to PBC. Within the AC populations, and across the sub-set of Angus cross Bos indicus and Angus cross Hereford cattle, close alignment was also observed in the comparative statistics. Using a large industry dataset, this study has validated the precision of Angus BreedCHECK to estimate beef cattle breed content, with an emphasis on Angus content. READ MORE
Breedplan single-step genomic evaluations delivers increased accuracies across all breeds and EBVs
D.J. Johnston, M.H. Ferdosi, N.K. Connors, J. Cook, C.J. Girard and A.A. Swan Animal Genetics Breeding Unit (AGBU)
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. READ MORE
Genomic prediction using imputed whole-genome sequence in Australian Angus cattle
N. Kamprasert1, H. Aliloo1, J. van der Werf1, C. Duff2 and S. Clark1 1 University of New England, 2Angus Australia
Using whole-genome sequence data in genomic prediction is expected to improve the predictive ability since the whole genome sequence may contain causal variants. This study aimed to compare the accuracy of genomic prediction with three densities of genotypes, 50k, high- density and wholegenome sequence. The genomic prediction was performed to estimate breeding values for selected growth and carcass traits in Australian Angus beef cattle. Genotype imputation was conducted to retrieve genotypes at high-density and whole-genome sequence level. The dataset was split into testing and reference group to compare the accuracy of breeding values obtained from different genotype densities and for animals with different degrees of relatedness to the reference. The prediction accuracies were similar across three different genotype densities for the traits studied. We found no substantial improvement in genomic prediction accuracy using the whole-genome sequence data in this study. READ MORE
Faecal microbiota of Angus cattle with divergent immune competence
B.N. Maslen1, B.C. Hine2, C. Duff3, P.A. Alexandre2, S.A. Clark4, J.H.J van der Werf4, J.D. White1 and S.D. Pant1
1Charles Sturt University, 2CSIRO, 3Angus Australia, 4University of New England
Microorganisms inhabiting the gut (gut microbiota) have been shown to inﬂuence immune responsiveness of the host in a variety of species. It has also been discovered that speciﬁc species of gut microbiota may contribute to immunity in multibreed cattle. In this study, faecal samples were obtained from Angus cattle that were concurrently phenotyped for cell-mediated and antibodymediated immune responsiveness (IR) at weaning. Both IR phenotypes, and an ImmuneDex score, were calculated and used to identify high, medium and low IR cohorts (n=20/group). 16s rRNA gene sequence data was used to infer the relative abundances of different phyla in the sampled animals. A total of 6 phyla were found to signiﬁcantly differ in relative abundances for at least one of the IR phenotypes. Of these, Bacteroidota, Euryarchaeota and Proteobacteria may be biologically relevant due to their relationship with gut health and disease. READ MORE
On the value of adding commercial data into the reference population of the Angus SteerSELECT genomic tool
Antonio Reverter1, Laercio Porto-Neto1, Brad C. Hine1, Pamela A. Alexandre1, Malshani Samaraweera2, Andrew I. Byrne2, Aaron B. Ingham1 and Christian J. Duff2 1CSIRO, 2Angus Australia
Angus SteerSELECT is a genomic tool designed to provide genomic estimated breeding values (GEBV) for nine traits related to growth, feedlot performance, carcase characteristics and immune competence. At present, GEBV for carcase characteristics are based on a reference population of 3766 Australian Angus steers. We aimed to investigate the potential beneﬁt of incorporating commercial data into the existing reference population of the Angus SteerSELECT. To this aim, we employ a population of 2124 genotyped commercial Angus steers with carcase performance data from four commercial feedlot operators. Commercial feedlot operators ﬁnishing animals with a strong Angus breed component will beneﬁt from having their data represented in the reference population of the Angus SteerSELECT genomic tool. READ MORE
Genetic evaluation of coat type for Australian Angus
A.M. Samaraweera1, H. Aliloo2, A. Byrne1, C.J. Duff1 and S.A. Clark2 1Angus Australia, 2University of New England
Animals with sleeker coats are commonly considered to have better heat tolerance, tick resistance, and a lower incidence of dags in feedlot environments. The objective of this study was to estimate genetic parameters for coat type traits and to estimate genetic correlations between coat type and scan and carcass weight traits using single-step methods. Two coat type traits were defined based on the month of scoring where scores recorded in April to October were considered as coat type 1 (CT1) and those recorded in November to March were categorized as coat type 2 (CT2). The coat type traits were moderately heritable, and the heritability of CT1 (0.36 ± 0.04) was higher than CT2 (0.32 ± 0.03). Genetic correlations between coat type traits and steer and heifer ultrasound scan traits (eye muscle area, intramuscular fat) were either low to moderate in strength, but favourable in direction. The outcomes of this study suggest selection for sleeker coat type is possible without any associated detrimental effect on scan and carcase traits. READ MORE
Appropriateness of combining carcass data from Angus sire benchmarking program and breeder herds in a single genetic evaluation
A.M. Samaraweera, A. Byrne and C.J. Duff Angus Australia
The objective of this study was to investigate whether the two different sources of abattoir carcass phenotypes that are currently submitted for inclusion in the TransTasman Angus Cattle Evaluation are genetically the same trait, being abattoir carcass phenotypes measured on cattle in the Angus Sire Benchmarking Program (ASBP), and abattoir carcass phenotypes measured on Angus animals in breeder herds. The abattoir carcass traits used were carcass MSA marble score (CMMS), carcass fat depth at p8 rump site (CP8, measured in mm), and dressed carcass weight (CWT, measured in kg). Additive genetic correlations between the same traits across the two sources were estimated with bivariate animal models. The additive genetic correlations for CP8, CMMS, and CWT were 0.99 ± 0.17, 0.84 ± 0.24, and 0.73 ± 0.23, respectively. Therefore, the two different sources of abattoir carcass phenotypes can be considered genetically to be the same trait and can be included in a unified genetic evaluation as the same trait. READ MORE
Longevity of reference populations in a trans-Tasman genetic evaluation: Review of the Angus Sire Benchmarking Program
S.F. Walkom1, C.J. Duff 2, C. Girard1 and K. Moore1 1Animal Genetics Breeding Unit, 2Angus Australia
The Angus Sire Benchmarking Program (ASBP) remains the cornerstone genomic reference behind Angus Australia’s TransTasman Angus Cattle Evaluation (TACE). The success of industry funded genomic reference populations depends on the ability to maintain a strong relationship of the seedstock population with the sires selected for the reference population. Results from a review of the ASBP show that, for hard to measure traits (eg. feed intake), the ASBP is influencing the accuracy of breeding value estimation across the registered population. However, the evolution of the genetic make-up of the Trans-Tasman herd means that the continued collection of hard to measure phenotypes via the ASBP or similar programs is essential. READ MORE
A few other interesting papers presented at the AAABG conference
Age at puberty, days to calving and first parity return to oestrus in Australian temperate beef breeds
K.A. Donoghue1, R. Rippon1, M. Wolcott2, K.L. Moore2, S.A. Clark3 and B.J. Walmsley1,2 1NSW Department of Primary Industries
2Animal Genetics and Breeding Unit, 3University of New England
Heritability and repeatability of paternal haplotype recombination rate in beef cattle autosomes
M.H. Ferdosi1, S. Masoodi2 and M. Khanseﬁd3, 1Animal Genetics Breeding Unit, 2University of Payam Noor, 3Agriculture Victoria
Validation of calving ease EBVs examining the impact of genetic groups and single-step on predictive ability
P.M. Gurman, L. Li, M.G. Jeyaruban, D.J. Johnston, C.J. Girard, and A.A. Swan Animal Genetics Breeding Unit
New module for prediction of reproductive traits EBV in Breedplan
M.G. Jeyaruban and D.J. Johnston Animal Genetics Breeding Unit
Approximating prediction error variances and accuracies of estimated breeding values from a SNP–BLUP model for genotyped individuals
L. Li, P.M. Gurman, A.A. Swan and B. Tier Animal Genetics Breeding Unit
Immune competence and micro-environmental sensitivity
M.D. Madsen1, J.H.J. van der Werf1, A. Ingham2, B. Hine2, A. Reverter2 and S. Clark1
1 University of New England, 2CSIRO
S.P. Miller, Animal Genetics Breeding Unit
Remodelling the genetic evaluation of NFI in beef cattle – Part 1: Developing an equivalent genetic model
L.Vargovic1, K.L. Moore1, D.J. Johnston1, G.M. Jeyaruban1, C.J. Girard1, J. Cook1, J.A. Torres-Vázquez2 and S.P. Miller1, 1Animal Genetics Breeding Unit 2University of Maryland
Remodelling the genetic evaluation of NFI in beef cattle – Part 2: Shortening the length of the feed intake test
L.Vargovic1, K.L. Moore1, D.J. Johnston1, G.M. Jeyaruban1, C.J. Girard1, J. Cook1, J.A. Torres-Vázquez2 and S.P. Miller1, 1Animal Genetics Breeding Unit, 2University of Maryland
Feature Image: Malshani Samaraweera, Geneticist, Dr Liam Mowbray, Research and Development Specialist & Christian Duff, General Manager – Genetic Improvement
— By Malshani Samaraweera, Geneticist