Animal Molecular Breeding 2024, Vol.14, No.1, 86-94 http://animalscipublisher.com/index.php/amb 93 The application of advanced computational technologies such as artificial intelligence and machine learning will greatly enhance the capability and accuracy of genetic data analysis, offering strong support for identifying and interpreting genetic variations. The development of these technologies will not only advance in-depth research on the genetics of sheep flocking behavior but also provide scientific bases for more precise breeding and management strategies, which are important for improving sheep productivity and welfare (Zhang et al., 2022). As technology continues to advance, we can look forward to achieving more significant results in the field of genetic research on sheep flocking behavior. 6 Conclusion and Outlook This study, through a comprehensive review and analysis of recent research on the genetic basis of flocking behavior in sheep, especially the application of Genome-Wide Association Studies (GWAS), highlights the significant contributions of GWAS technology in revealing the genetic mechanisms of sheep social behavior. By identifying genetic markers and regions significantly associated with flocking behavior, these studies not only enrich our understanding of the genetics of sheep behavior but also provide a scientific basis for future breeding and management practices. The findings of these studies have profound implications for biotechnology and agriculture. In biotechnology, the application of GWAS has facilitated innovation in genetic research methodologies and advancements in technology. In agriculture, a deeper understanding of the genetic foundations of sheep flocking behavior helps optimize breeding strategies, enhancing the social adaptability and productivity of sheep, thus advancing agricultural production towards more efficient and sustainable directions (Esmaeili-Fard et al., 2021). Discoveries in the genetics of sheep flocking behavior have direct practical significance for breeding, sheep management, and the improvement of animal welfare. Utilizing genetic markers identified by GWAS, breeders can make more accurate genetic selections, developing sheep better suited for flocking life, thereby enhancing the overall performance and welfare levels of the flock (Barbosa et al., 2023). Additionally, these research outcomes offer new ideas and strategies for sheep management, such as improving breeding environments and adjusting group structures to promote harmonious interactions among sheep. The close connection between scientific research and practical application ensures that research outcomes can be transformed into tangible productivity, contributing to animal welfare, enhancing agricultural production efficiency, and supporting sustainable agricultural development. Future research will continue to delve into the genetic basis of sheep flocking behavior, especially functional validation and mechanistic studies of genetic markers identified by GWAS, to more comprehensively understand the genetic regulation mechanisms of sheep social behavior (Wang et al., 2017). Moreover, with the development of new technologies and methods, it is expected that more genetic variations will be discovered, providing more genetic resources for breeding and management. The importance of interdisciplinary collaboration is increasingly highlighted, and close cooperation among genetics, ethology, bioinformatics, and other fields will be key to future research. Additionally, technological innovations, such as CRISPR/Cas9 gene editing and single-cell sequencing technologies, will bring new breakthroughs to the study of sheep behavioral genetics. In summary, continuous exploration of the genetic basis of sheep flocking behavior, strengthening interdisciplinary cooperation and technological innovation, will provide strong support for addressing future challenges and promote further development in the fields of biotechnology and agriculture. References Almasi M., Zamani P., Mirhoseini S., and Moradi M., 2020, Genome-wide association study of weaning traits in Lori-Bakhtiari sheep, Annals of Animal Science, 20: 811-824. https://doi.org/10.2478/aoas-2020-0014 Barbosa B., Silva A., Castro D., Castro G., Silva T., Vieira R., Sena L., Torres T., Pereira E., Silva L., Borges L., Oliveira M., and Sarmento J., 2023, Overview of the use of genomic data in animal breeding, Ciência Rural, 53.
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