A genome-wide assessment of the population structure of thirteen admixed and pure Australian beef cattle breeds.

Abstract

Knowledge of population structure is a key factor for successful multi-breed genomic prediction, especially in single-step analysis when metafounders are considered. In Australia, current assessments mostly focus on single breeds using a single-step genomic prediction method. However, the effective integration of pedigree, phenotypic, and genomic data in a multi-breed framework still requires further research, especially for combined analyses including admixed and multi-breed populations. This study began with 602,952 genotyped individuals with 8K SNPs in common from 13 beef cattle breeds (Alexandria, Angus, Brahman, Brangus, Charolais, Droughtmaster, Hereford, Kynuna, Limousin, Santa Gertrudis, Shorthorn, Speckle Park, and Wagyu). Due to different numbers of animals being genotyped in each breed, a representative subset of animals was chosen by employing a validated sampling strategy using Gaussian Mixture Models (GMM) complemented by Principal Component Analysis (PCA) within each breed. Subsequently, a specific number of animals in each cluster were randomly selected to capture the entire genetic diversity per breed, with a total of 260 animals from each breed. The first three principal components explained 59.89% of the total variation, with PC1 (33.54%) clearly separating Bos indicus from Bos taurus lineages. Admixture analysis identified stable ancestral components and defined the genetic makeup of both pure and composite populations. The results showed extensive genetic diversity in some breeds and highlighted distinct genetic differences between Bos indicus and Bos taurus breeds. In addition, six composite breeds' admixture levels confirmed their origin and breed history, revealing a directional shift in ancestry proportions by a longitudinal increase in Brahman ancestry within tropical composites over time. Thus, the findings pave the way for more effective utilization of genetic diversity both within and across populations and provide a framework for designing multi-breed genetic evaluations and breeding programs to improve productivity and profitability in Australian beef production.