Animal Molecular Breeding 2024, Vol.14, No.1, 54-61 http://animalscipublisher.com/index.php/amb 60 selection of statistical models, which requires comprehensive consideration of factors such as model complexity, computational resource requirements, and model interpretability. In the face of the above challenges, researchers need to comprehensively use methods such as data collection and processing, genotype data quality control, and statistical model selection and optimization to continuously improve the effect and efficiency of genome-wide association analysis in the optimization of mutton production traits, and provide a better way for mutton. Provide more powerful support for the sustainable development of the industry. 6 Achievements and Prospects Genome-wide association analysis methods for optimization of mutton production traits have achieved a series of remarkable results. In terms of sample collection and data processing, the researchers established a large and diverse sheep breed resource library, covering sheep breeds with various geographical, environmental and genetic backgrounds. This provides sufficient data support for subsequent genome-wide association analysis. In terms of acquisition and quality control of genotype data, advanced sequencing technology and strict quality control standards are used to ensure the accuracy and reliability of the data. In terms of statistical models for genome-wide association analysis, researchers continue to improve and optimize the models, improving the accuracy and efficiency of analysis. Most importantly, in terms of identification and verification of key trait markers, researchers have successfully discovered multiple genetic loci closely related to mutton production traits, providing a basis and guidance for the optimization of mutton production traits (Li et al., 2023). Although certain results have been achieved, there are still some problems and challenges faced in genome-wide association analysis for optimization of mutton production traits (Su et al., 2023). Due to the diversity of sheep resources and the complexity of genetic background, there are still certain limitations in sample selection and data processing, and it is necessary to further expand the sample size and improve data analysis methods. In terms of identification and verification of key trait markers, since mutton production traits are affected by multiple factors, such as environment, management, and nutrition, more comprehensive research and verification are needed to ensure the accuracy and stability of markers. The genome-wide association analysis method itself also has certain limitations. For example, the detection ability of rare variants is weak, and it needs to be combined with other methods for comprehensive analysis and verification. People will continue to work hard on genome-wide association analysis for the optimization of mutton production traits, focusing on solving existing problems and challenges, further deepening research results, and exploring new research directions in future. Researchers will strengthen the collection and integration of sheep resources, establish a more complete sheep resource library, and provide richer and more diversified data support for genome-wide association analysis; they will continue to improve and optimize data processing and analysis methods to improve data The quality and precision of analysis to cope with the diversity of sheep resources and the complexity of genetic backgrounds. Researchers will strengthen cooperation with other disciplines and fields, conduct more comprehensive research, explore the internal mechanisms and regulatory networks of mutton production traits, and provide more in-depth and comprehensive theoretical support for the optimization of mutton production traits; and will also actively Explore new research methods and technologies, such as artificial intelligence and gene editing, to open up new ways and methods for the optimization of mutton production traits. This study is full of confidence in the genome-wide association analysis for the optimization of mutton production traits. It is believed that in the near future, humans will achieve more significant research results and make greater contributions to the development and growth of the mutton industry. References Asif H., Alliey-Rodriguez N., Keedy S., Tamminga C.A., Sweeney J.A., Pearlson G., Clementz B.A., Keshavan M.S., Buckley P., Liu C.Y., Neale B., and Gershon E.S., 2021, GWAS significance thresholds for deep phenotyping studies can depend upon minor allele frequencies and sample size, Molecular psychiatry, 26(6): 2048-2055. https://doi.org/10.1038/s41380-020-0670-3 PMid:32066829 PMCid:PMC7429341
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