Animal Molecular Breeding 2024, Vol.14, No.1, 45-53 http://animalscipublisher.com/index.php/amb 52 Despite the significant role of GWAS in revealing the genetic factors of livestock production traits, there remain challenges and room for improvement (Li and Ritchie, 2021). Sample size and quality are crucial in conducting GWAS. Future research should aim to increase sample sizes and adopt effective methods to control data quality, enhancing the reliability and accuracy of research findings. In identifying key genes and genetic markers, further exploration into their functions and regulatory mechanisms is needed. This will help better understand the molecular mechanisms behind the formation of livestock production traits and provide more theoretical support for future genetic improvement strategies. GWAS involves knowledge from multiple disciplines, such as bioinformatics and genetics. Future research needs to strengthen interdisciplinary collaboration and communication to address technical and methodological challenges. Active promotion of data sharing and openness is also essential to provide researchers with more resources and support. Livestock production traits are influenced by multiple genes, so a single genetic improvement strategy may not meet the needs of different livestock types and production environments. Future research should develop diverse genetic improvement strategies, optimizing livestock's genetic background based on GWAS results for better production trait improvement outcomes (Yu et al., 2024). GWAS is an evolving field, and future studies should enhance technological innovation and method optimization, continuously improving analysis efficiency and accuracy. Especially in data processing, statistical analysis, and functional prediction, related techniques and methods need ongoing refinement. Future research should continue to explore the potential of GWAS in livestock production trait improvement, strengthen interdisciplinary cooperation and data sharing, develop diverse genetic improvement strategies, and keep pushing for technological innovation and method optimization. This will contribute more significantly to the continuous improvement of livestock production traits and the enhancement of agricultural productivity. References Berghof T.V., Poppe M., and Mulder H.A., 2019, Opportunities to improve resilience in animal breeding programs, Frontiers in genetics, 9: 410180. https://doi.org/10.3389/fgene.2018.00692 PMid:30693014 PMCid:PMC6339870 Fang Z.H., and Pausch H., 2019, Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle, BMC genomics, 20: 1-15. https://doi.org/10.1186/s12864-019-6066-6 PMid:31481029 PMCid:PMC6724290 Hagan B.A., Moro-Mendez J., and Cue R.I., 2020, Realized genetic selection differentials in Canadian Holstein dairy herds, Journal of dairy science, 103(2): 1651-1666. https://doi.org/10.3168/jds.2019-16890 PMid:31759593 Li B.L., and Ritchie M.D., 2021, From GWAS to gene: transcriptome-wide association studies and other methods to functionally understand GWAS discoveries, Frontiers in Genetics, 12: 713230. https://doi.org/10.3389/fgene.2021.713230 PMid:34659337 PMCid:PMC8515949 Li F.Y., Li C.X., Chen Y.H., Liu J.H., Zhang C.Y., Irving B., Fitzsimmons C., Plastow G., and Guan L.L., 2019, Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle, Microbiome, 7: 1-17. https://doi.org/10.1186/s40168-019-0699-1 PMid:31196178 PMCid:PMC6567441 Liu L.Y., Zhou J.H., Chen C.J., Zhang J., Wen W., Tian J., Zhang Z.W., and Gu Y.L., 2020, GWAS-based identification of new loci for milk yield, fat, and protein in Holstein cattle, Animals, 10(11): 2048. https://doi.org/10.3390/ani10112048 PMid:33167458 PMCid:PMC7694478 Raza S.H.A., Khan S., Amjadi M., Abdelnour S.A., Ohran H., Alanazi K.M., El-Hack M.E.A., Taha A.E., Khan R., Gong C., Schreurs N.M., Zhao C.P., Wei D.W., and Zan L.S., 2020, Genome-wide association studies reveal novel loci associated with carcass and body measures in beef cattle, Archives of Biochemistry and Biophysics, 694: 108543. https://doi.org/10.1016/j.abb.2020.108543 PMid:32798459
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