Plant Gene and Trait 2024, Vol.15, No.1, 15-22 http://genbreedpublisher.com/index.php/pgt 21 With the continuous advancement of bioinformatics and artificial intelligence technologies, researchers can better process and analyze large-scale GWAS data, discover more robust and reliable gene-phenotype associations, and accelerate the identification and verification process of disease resistance genes. Functional verification and mechanism analysis of GWAS research results are also important directions for future research, and the function of disease resistance genes is verified by gene editing and other technologies, and the mechanism of action in crop disease resistance is deeply explored. GWAS research also needs to pay more attention to the combination with actual breeding, quickly transform the discovered disease resistance genes into breeding applications, and speed up the breeding process of new varieties. Researchers also need to pay attention to the differences and commonalities of genetic mechanisms of disease resistance between different crops, so as to provide more comprehensive theoretical support for disease resistance breeding of different crops. GWAS research has great significance and potential in revealing the genetic mechanism of crop disease resistance. Future studies will pay more attention to the integration of multi-omics data, the application of new technologies and the combination with breeding practice, so as to provide more scientific basis and methodological support for crop disease resistance breeding and help the sustainable development of food production. Acknowledgments The author appreciates two anonymous peer reviewers for their suggestions during the review process, which helped to identify weaknesses in the study. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Ahmar S., Mahmood T., Fiaz S., Mora-Poblete F., Shafique M.S., Chattha M.S., and Jung K.H., 2021, Advantage of nanotechnology-based genome editing system and its application in crop improvement, Front. Plant Sci., 12: 663849. https://doi.org/10.3389/fpls.2021.663849 PMid:34122485 PMCid:PMC8194497 Andersen E.J., Ali S., Reese R.N., Yen Y., Neupane S., and Nepal M.P., 2016, Diversity and evolution of disease resistance genes in barley (Hordeum vulgare L.), Evolutionary Bioinformatics, 12: 99-108. https://doi.org/10.4137/EBO.S38085 PMid:27168720 PMCid:PMC4857794 Choi H.K., 2019, Translational genomics and multi-omics integrated approaches as a useful strategy for crop breeding, Genes & Genomics, 41: 133-146. https://doi.org/10.1007/s13258-018-0751-8 PMid:30353370 PMCid:PMC6394800 Deng Y., Ning Y., Yang D.L., Zhai K., Wang G.L., and He Z., 2020, Molecular basis of disease resistance and perspectives on breeding strategies for resistance improvement in crops, Molecular Plant, 13(10): 1402-1419. https://doi.org/10.1016/j.molp.2020.09.018 PMid:32979566 Fones H.N., Bebber D.P., Chaloner T.M., Kay W.T., Steinberg G., and Gurr S.J., 2020, Threats to global food security from emerging fungal and oomycete crop pathogens, Nat. Food, 1(6): 332-342. https://doi.org/10.1038/s43016-020-0075-0 PMid:37128085 Gallagher M.D., and Chen-Plotkin A.S., 2018, The post-GWAS era: from association to function, Am. J. Hum. Genet., 102(5): 717-730. https://doi.org/10.1016/j.ajhg.2018.04.002 PMid:29727686 PMCid:PMC5986732 Garrett K.A., Andersen K.F., Asche F., Bowden R.L., Forbes G.A., Kulakow P.A., and Zhou B., 2017, Resistance genes in global crop breeding networks, Phytopathology, 107(10): 1268-1278. https://doi.org/10.1094/PHYTO-03-17-0082-FI PMid:28742460
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