<b>Supplementary Table 1.</b> QTL regions for each of these three sets of phenotypes from the QTL database

The application of Genomic Selection (GS) in beef cattle breeding programs is somewhat limited, despite its numerous advantages. Computer simulations are powerful tools to enhance our understanding of GS applications across different scenarios and are invaluable as an initial step before implementing this technique in "real" breeding programs. In this study, we utilized real SNP data from Indicus and Taurus breeds to simulate three crossbred breeding schemes: F1 crosses, grading up, and rotational crosses. Phenotypes were selected for shear force, growth, and tolerance traits. We compared the predictive accuracy of three 50k SNP chips that differed in SNP selection methodologies: random selection, selection based on minimum allele frequency differences between breeds, and selection based on minimum allele frequency differences between breeds with a threshold of 0.09 in Taurus. Our findings indicate that rotational crossing demonstrates optimal predictive accuracy, while selecting markers based on allele frequency differences between breeds does not yield significant benefits and may even be detrimental.