International Journal of Molecular Zoology 2024, Vol.14, No.1, 44-53 http://animalscipublisher.com/index.php/ijmz 52 livestock behavioral traits, providing valuable scientific evidence for understanding the genetic mechanisms of behavioral traits, guiding livestock genetic improvement and enhancing animal welfare. The application of GWAS has enabled researchers to identify key genes and genetic variants associated with behavioral traits in livestock on a genome-wide scale. These findings have not only improved the understanding of the mechanisms of genetic regulation of animal behavior, but also provided new selection criteria for breeding programs that can help to optimize the production performance and behavioral welfare of domestic animals. Through GWAS, it has been possible to identify multiple genetic markers associated with key traits such as stress response, social behavior, and maternal behavior in different livestock species, and the discovery of these markers has provided new perspectives and approaches for livestock genetic improvement and management. Although GWAS have provided insights into the genetics of behavioral traits in livestock, the mechanisms underlying the inheritance of behavioral traits are extremely complex and are influenced by a combination of polygenic and environmental factors. Ongoing research efforts are necessary to reveal more key genetic variants, understand genetic-environmental interactions, and explore the role of epigenetics in the formation of behavioral traits. With the development of new technologies, such as gene editing and integrated multi-omics analyses, future studies are expected to provide more detailed and comprehensive biological information, further advancing the field of livestock behavioral genetics (Wang et al., 2022). GWAS research is not only important for scientific understanding, but the application of its results can also directly contribute to improved livestock productivity and animal welfare. Through genetic selection, it is possible to breed livestock breeds that are better adapted to the production environment and have better behavioral traits. For example, by selecting for individuals with lower stress responses and better social interactions, behavioral problems during breeding can be reduced, improving the overall welfare and productivity of the population. A better understanding of the genetic basis of behavioral traits in livestock can also help to design more humane management and breeding strategies, thereby improving the quality of life of the animals. In summary, GWAS has made significant progress in the genetic study of behavioral traits in livestock, providing a new scientific basis and methodology for genetic improvement, breed selection and welfare enhancement. Despite the many challenges, continued research and the application of new technologies will continue to advance the field and are expected to make greater contributions to the sustainable development of the livestock industry and the improvement of animal welfare. As research progresses, the livestock of the future will not only be more efficient in production, but also healthier and happier in behavior. References Deng Y.Y., Liu X., Wang T., He C.Q., Guo S.C., and Qu X.Y., 2022, Research progress of genome-wide association study(gwas)in gene mapping of important economic traits in chicken, Zhongguo Jiaqing (China Poultry), 44(9): 80-86. Fonseca P., Santos F., Lam S., Suárez-Vega A., Miglior F., Schenkel F., Diniz L., Id-Lahoucine S., Carvalho M., and Cánovas Á., 2018, Genetic mechanisms underlying spermatic and testicular traits within and among cattle breeds: systematic review and prioritization of GWAS results, Journal of animal science, 96(12): 4978-4999. https://doi.org/10.1093/jas/sky382 Freebern E., Santos D., Fang L., Jiang J., Gaddis K., Liu G., VanRaden P., Maltecca C., Cole J., and Ma L., 2019, GWAS and fine-mapping of livability and six disease traits in Holstein cattle, BMC Genomics, 21(1): 41. https://doi.org/10.1186/s12864-020-6461-z Guo J.Z., Zhong J., Li P.F., Li L., and Zhang H.P., 2021, Advances of genetic loci affecting phenotypic variations of ear type in livestock, Xibei Nongye Xuebao (Acta Agriculturae Boreali-occidentalis Sinica), 30(1): 1-7. Guo Y.Y., Du S.Z., Qiao Y.L., and Liang D., 2023, Advances in the applications of deep learning technology for livestock smart farming, Zhihui Nongye Zhongyingwen (Smart Agriculture), 5(1): 52-65. Nguyen P.L.L., Syed M., McGue M., 2021, Behavior genetics research on personality: moving beyond traits to examine characteristic adaptations, Social and Personality Psychology Compass, 15(8): e12628. https://doi.org/10.1111/spc3.12628 Niu A.R., Zhang X., Yang Y.T., Yan Z.C., Gong H.Z., Ding R.N., and Ma L., 2023, Progresses in research on genome-wide association studies in pig breeding, Xumu yu Shouyi (Animal Husbandry & Veterinary Medicine), 55(5): 139-147.
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