Genomic selection (GS) plays a crucial role in livestock breeding. However, its implementation in Chinese beef cattle breeding is constrained by a limited reference population and incomplete data records. To address these challenges, this study aimed to identify more effective models for multi-population genomic selection. We simulated five different beef cattle populations and selected three populations with varying levels of kinship to investigate the impact of population relationships on genomic prediction. Utilizing results from a genome-wide association study (GWAS), we preselected different proportions of single nucleotide polymorphism (SNP). Subsequently, we employed three models—genomic best linear unbiased prediction (GBLUP), multi-genomic best linear unbiased prediction (MGBLUP), and weighted multi-genomic best linear unbiased prediction (WMGBLUP)—for within-population and multi-population genomic prediction. Our results showed that increasing the size of the training set improved within-population prediction accuracy. Furthermore, both MGBLUP and WMGBLUP outperformed GBLUP in terms of prediction accuracy for both within-population and multi-population analyses. Among the models evaluated, the WMGBLUP model, which utilized the top 5% of preselected SNPs based on GWAS findings, demonstrated superior performance, yielding an improvement of up to 11.1% in within-population prediction and 16.5% in multi-population prediction. In summary, both WMGBLUP and MGBLUP models exhibit enhanced efficacy in improving genomic prediction accuracy, and the incorporation of GWAS results can further optimize their performance.

As one of the five major indigenous yellow cattle breeds in China, Qinchuan cattle are characterized by stable genetic performance and desirable meat quality. However, compared with imported commercial breeds, Qinchuan cattle have a relatively slow growth rate. Therefore, improving the growth rate of Qinchuan cattle has become a top priority in Qinchuan cattle breeding. The CDC10 (Septin 7) gene, an important member of the Septin family, participates in various cellular physiological processes including intracellular substance transport, cell division, cell cycle regulation, and apoptosis. Studies have repeatedly mapped the CDC10 gene to quantitative trait loci influencing growth-related traits, such as body weight and carcass weight in many beef cattle breeds. Previous study has also demonstrated the high expression of CDC10 in JB cattle with high performance for carcass weight, however, the association between CDC10 and growth-related traits in Qinchuan cattle remain unclear. Therefore, in this study, we selected five individuals each from Chinese Simmental, Mongolian cattle, Luxi cattle, and Qinchuan cattle for direct sequencing, aiming to identify mutations within the CDC10 gene of native Chinese yellow cattle. Subsequently, we performed genotyping of 367 Qinchuan cattle using the MassARRAY technology, followed by genetic diversity analysis of the identified mutations and association analysis between these sites and growth-related traits of Qinchuan cattle. This study demonstrated high expression of the CDC10 gene in Qinchuan cattle with high performance for carcass weight. Furthermore, we identified the g.61303052G>C and c.225A>G SNPs in the promoter and exon regions, respectively, as being significantly associated with multiple growth-related traits in Qinchuan cattle. The c.225A>G SNP was also found to alter the secondary structure of the CDC10 protein. These findings provide reliable molecular markers for enhancing the growth rate of Qinchuan cattle and establish a solid theoretical foundation for the development of the beef cattle industry.