Genome-wide association study of eye muscle area and intramuscular fat in pure- and crossbred beef cattle

Abstract The genetic improvement of meat quality traits, such as eye muscle area (EMA) and intramuscular fat (IMF), is a primary goal for increasing the profitability and efficiency of the beef industry. However, it remains unclear how the genetic architecture of these traits differs across diverse breed types, which complicates the development of accurate multi-breed genomic evaluations. The objective of this study was to identify common genomic regions associated with ultrasound EMA and IMF across five beef cattle populations, including two purebreds (Angus and Hereford) and three crossbreds (Brangus, Santa Gertrudis, and Speckle Park). Genome-wide association studies (GWAS) were performed using a linear mixed model. Phenotypic and genomic data from 66,313 bulls and 56,200 heifers for EMA, and 65,230 bulls and 54,905 heifers for IMF, were analysed using medium-density SNP arrays. The results showed some associated genomic regions that were shared across breeds, likely due to their similar genetic origins or breeding objectives, for example: chromosome 2 at ∼0.57—14 Mb for both bull and heifer EMA and IMF in Santa Gertrudis and Speckle Park; chromosome 5 at positions ∼45—50 Mb for bull and heifer IMF in Brangus and Santa Gertrudis and for ∼105—106 for bull EMA in Angus and Hereford breeds; chromosome 7 at ∼90—91 Mb for bull EMA and heifer IMF in Angus and Hereford, chromosome 17 at ∼60—62 Mb for bull IMF in Angus and Hereford; and chromosome 20 at ∼4—5 Mb for heifer IMF in Angus and Hereford. Some genomic signals were breed-specific, likely reflecting differences in allele frequencies or linkage disequilibrium between pure- and crossbred populations. This research demonstrates that while some genetic drivers of meat quality are conserved across breeds, breed-specific markers are essential for accurate genomic prediction. These findings provide a biological basis for applying marker weighting in genomic evaluations to enhance selection accuracy for meat quality traits in multi-breed evaluations.