Breed Development
A strong showing of Angus at AAABG Matt Reynolds, Breed Development Officer
For the first time in the conferences long history, the 24th Association for the Advancement of Animal Breeding and Genetics (AAABG) conference went online. The conference is widely considered the premier livestock breeding conference in Australia and New Zealand and provides an opportunity for researchers to showcase the latest livestock genetics research being conducted, with presentation detailing research in a number of animal industries, most notably beef cattle, dairy cattle and sheep. The event showcased a number of the research and development activities being undertaken at Angus Australia, and the strong collaborative links that Angus Australia has developed to continue to deliver value to members.
A key achievement of the 2021 conferences was the awarding of the ‘Editor’s choice: Best Special APS Issue paper’ award to CSIRO’s Brad Hine and his paper ‘Development Of Angus Steerselect - A Genomic Based Tool To Identify Performance Differences Of Australian Angus Steers During Feedlot Finishing: Phase 1 Validation’. A paper which explores the outcomes of a collaborative project between Angus Australia and CSIRO.
The Impact Of Reference Composition And Genome Build On The Accuracy Of Genotype Imputation In Australian Angus Cattle H. Aliloo1, S.A Clark1 1 School of Environmental and Rural Science, University of New England, Armidale, NSW 2350, Australia Genotype imputation is a statistical method to obtain a large quantity of DNA-based information at a low cost. Our proposed method improves the accuracy of imputed genotypes, which is of crucial importance for their utility. The presented method is straightforward and can be implemented at no extra cost to aid in genetic improvement of beef cattle.
Assessment Of Genomic Predictions For Feedlot And Carcase Traits In Australian Angus Steers P.A. Alexandre1 , Y. Li1 , B.C. Hine2 , C.J. Duff3 , A.B. Ingham1 , L.R. Porto-Neto1 and A. Reverter1 1 CSIRO, Agriculture and Food, Queensland Bioscience Precinct, St Lucia, QLD, Australia, 2 CSIRO, Agriculture and Food, F.D. McMaster Laboratory, Armidale, NSW, Australia, 3 Angus Australia, Armidale, NSW, Australia. Improving feedlot performance, carcase weight and quality is a primary goal of the beef industry globally. Here we used data from 3,408 Australian Angus steers from seven birth cohorts (2011 to 2017) with genotypes for 45,152 SNPs. We report genetic parameter estimates and accuracies of genomic estimated breeding values (GEBV) for feedlot and carcase traits, namely feedlot average daily gain (ADG), carcase weight (CWT) and carcase Meat Standard Australia marbling score (MBL). Prediction accuracies were estimated based on traditional method as well as method LR. The average prediction accuracies across cohorts assessed with the traditional method were 0.28 (ADG), 0.49 (CWT) and 0.50 (MBL), while method LR accuracies were 0.47 (ADG), 0.64 (CWT) and 0.59 (MBL). We found a strong correlation (0.74, P-value<0.001) between traditional accuracies and method LR accuracies. Heritability estimates were moderate to large (0.29 for ADG, 0.53 for CWT and 0.41 for MBL). The metrics of GEBV quality and heritabilities reported here suggest good potential for accurate genomic selection of Australian Angus for feedlot performance and carcase characteristics.
Ultra-Small Snp Panels To Uniquely Identify Individuals In Thousands Of Samples S. Dominik1, C.J Duff2, A.I Byrne2, H. Daetyler3,4, A. Reverter5 1 CSIRO Agriculture and Food, FD McMasters Laboratories, 9308 New England Highway, Armidale, NSW 2350, Australia, 2 Angus Australia, 86 Glen Innes Road, Armidale, NSW, 2350, Australia, 3 Agriculture Victoria, AgriBio Centre, 5 Ring Road, Bundoora, Vic. 3083, Australia, 4 La Trobe University, Plenty Road and Kingsbury Drive, Bundoora, Vic. 3083, Australia, 5 CSIRO Agriculture and Food, Queensland Bioprecinct, 306 Carmody Road, St Lucia, Qld 4067, Australia. Genomic information can be used for traceability of meat products. The present study explored the required number of genetic markers to generate unique marker profiles for each animal in the dataset. Ultra-small panels of genetic markers can provide an efficient method for the large-scale task of industrywide paddock to plate traceability. 76
