Animal Molecular Breeding 2024, Vol.14, No.1, 45-53 http://animalscipublisher.com/index.php/amb 50 based on the genetic contribution and importance of different traits helps achieve more precise and effective selective breeding. GWAS allows for a comprehensive assessment and analysis of the genetic background of livestock populations. Keeping up with the population's genetic characteristics and issues helps adjust breeding strategies and better guide genetic improvement efforts. 4.3 Practical cases of genetic marker-assisted selection In practice, many livestock genetic improvement projects have started to adopt GWAS-assisted selection strategies and achieved certain successes. For example, in dairy cow production trait improvement, GWAS analysis has successfully identified a series of genes and genetic markers related to milk yield and protein content. Based on this information, breeders can more precisely select individuals with excellent production traits as parental groups, thereby enhancing the genetic level of offspring. Similarly, genetic improvement projects for pigs, chickens, and other poultry are actively adopting GWAS-assisted selection strategies and achieving certain results. In beef cattle breeding, GWAS technology has identified genetic markers and genes related to meat quality and growth rate (Raza et al., 2020). Through genetic marker-assisted selection, beef cattle breeds with better meat quality and faster growth were successfully bred, greatly improving the efficiency and quality of beef cattle breeding. In dairy cattle breeding, GWAS is widely used to discover genetic markers and genes related to key traits such as milk yield and fat percentage (Figure 3). Based on this information and through genetic marker-assisted selection, dairy cattle strains with higher milk yield and better fat percentages were successfully bred, providing high-quality raw materials for dairy production. In poultry breeding, GWAS has also achieved significant results. Using this technology, poultry strains with faster growth rates and stronger disease resistance were successfully bred, injecting new vitality into the poultry farming industry (Tang et al., 2024). Figure 3 Associations between 124,743 SNPs and milk traits (Liu et al., 2020) Note: FY: fat yield; PY: protein yield; FP: fat percentage; PP: protein percentage
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