Animal Molecular Breeding 2024, Vol.14, No.1, 27-35 http://animalscipublisher.com/index.php/amb 30 Through GWAS, scientists have successfully identified multiple key genes and variations that affect milk production. For example, genes such as DGAT1, GHR, and ABCG2 have been found to be significantly correlated with milk yield and milk fat content. These genes are involved in different biological pathways of milk production, including fatty acid metabolism, growth hormone signaling, and milk secretion. 2.2 Analyze how these genes and variations are used for selection and breeding strategies How these findings can be applied to selection and breeding strategies is an important issue in modern animal husbandry, as genome-wide association studies (GWAS) have revealed key genes and variations that affect milk production. By applying the findings of GWAS to practical breeding, scientists and breeders can more accurately improve the yield and quality of milk. Direct selection: the selection of breeding animals based directly on the presence of specific genes or SNPs. For example, if a SNP is positively correlated with high milk yield, then animals with that SNP will be preferentially selected for breeding. Genomic selection (GS): Selection is based not only on individual genes or SNPs, but on the use of genome-wide information to estimate the genetic value of an animal. This approach allows for a more comprehensive consideration of the interaction of multiple genes and environmental factors that affect milk yield. Mixed model evaluation: Combining phenotypic data, genotypic data and relevant genetic background information, statistical models are used to estimate the genetic potential of each animal, providing a more scientific basis for selection. The application of GWAS technology has greatly contributed to the development of modern animal husbandry, especially in increasing milk production and improving dairy quality. By accurately identifying key genes and variants that affect milk yield, GWAS provides a strong scientific basis for breeding. Translating these scientific findings into practical selection and breeding strategies not only accelerates the rate of genetic improvement, but also improves breeding efficiency and economic benefits. 2.3 Example analysis: a case study of successful breeding In Holstein dairy cows in China, a study conducted a genome-wide association study (GWAS) of traits including milk yield, fat and protein by using the Illumina BovineSNP150 BeadChip. The study identified ten significant single nucleotide polymorphisms (SNPs) associated with milk fat and protein, six of which were located within previously reported quantitative trait loci (QTL) regions (Yu et al., 2023). Specifically, the study confirmed the effect of the DGAT1 gene on milk fat and protein and identified several new candidate genes. These findings provide a valuable basis for molecular breeding in dairy cattle (Figure 2). Another study on utilized international breeding assessment data for GWAS to identify major loci affecting production traits and body size (Gutierrez-Reinoso et al., 2021). Analyzed using linear mixed models, the study identified 74 genome-wide significant SNPs associated with nine traits, which were distributed across 12 chromosomes. For example, traits affecting milk yield and body depth covered almost the same region on BTA25, highlighting significant SNPs and candidate genes including IGFAL, HAGH, and HS3ST6.By utilizing a large sample size of the global Brown Swiss population, this study provided insight into loci important for selection under the major production traits of this breed. A study in Xinjiang Brown cattle focused on milk, reproductive and health traits using the FarmCPU method for GWAS and incorporating demographic corrections (Zhang et al., 2023).Twelve SNPs were associated with six of the ten traits studied, demonstrating the complexity of trait genetics. This study not only identified significant markers associated with traits such as percent fat and somatic cell score, but also mapped candidate genes in the vicinity of these SNPs, demonstrating the contribution of this study to understanding the genetic basis of important traits in dual-purpose cattle.
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