Maize Genomics and Genetics 2024, Vol.15, No.1, 1-8 http://cropscipublisher.com/index.php/mgg 7 The application of GWAS in the study of corn grain quality traits has made important progress, providing valuable genetic information and molecular tools for corn quality improvement. However, to achieve sustained and fundamental improvements in corn quality, we still need to continue to study the molecular mechanisms of quality traits in depth, and at the same time, combine modern biotechnology to continuously explore and develop new breeding strategies. In the future, with the continuous progress of science and technology, I believe we can overcome the current challenges and make greater contributions to global food security and sustainable development. Acknowledgments We would like to express our gratitude to the two anonymous peer reviewers for their critical assessment and constructive suggestions on our manuscript. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Brachi B., Morris G.P., and Borevitz J.O., 2011, Genome-wide association studies in plants: the missing heritability is in the field, Genome Biology, 12: 1-8. https://doi.org/10.1186/gb-2011-12-10-232 PMid:22035733 PMCid:PMC3333769 Cortes L.T., Zhang Z., and Yu J., 2021, Status and prospects of genome-wide association studies in plants, The Plant Genome, 14(1): e20077. https://doi.org/10.1002/tpg2.20077 PMid:33442955 Dai H.X., Xiong Y.Z., and Niu J.H., 2007, Advances of inheritance of quality characters in sweet corn, Changjiang Shucai (Journal of Changjiang Vegetables), (10): 28-31. Guo J.J., Liu W.S., Zheng Y.X., Liu H., Zhao Y.F., Zhu L.Y., Huang Y.Q., Jia X.Y., and Chen J.T., 2019, Genome-wide association analysis of maize (Zeamays) grain quality related traits based on four test cross populations, Nongye Shengwu Jishu Xuebao (Journal of Agricultural Biotechnology), 27(5): 809-824. Guo X., Ge Z., Wang M., Zhao M., Pei Y., and Song X., 2023, Genome-wide association study of quality traits and starch pasting properties of maize kernels, BMC Genomics, 24(1): 59. https://doi.org/10.1186/s12864-022-09031-4 PMid:36732681 PMCid:PMC9893588 Hao H.Q., Liu L.L., Yao Y., Feng X., Li Z.G., Chao Q., Xia R., Liu H.T., Wang B.C., Qin F., Xie Q., and Jing H.C., 2018, Application and prospect of molecular module-based crop design technology in maize breeding, Zhongguo Kexueyuan Yuankan (Bulletin of Chinese Academy of Sciences), 33(9): 923-931. Li T.C., Yang H.Y., Liu G.H., Zhang W., Dong Q., Lei Y.L., Qian Y.L., Zhou Y.B., and Chen H.J., 2017, Advances on molecular mechanism of anthocyanins biosynthesis for maize seed, Molecular Plant Breeding, 15(7): 2623-2627. Liu Z., Garcia A., McMullen M.D., and Flint-Garcia S.A., 2016, Genetic analysis of kernel traits in maize-teosinte introgression populations, G3: Genes, Genomes, Genetics, 6(8): 2523-2530. https://doi.org/10.1534/g3.116.030155 PMid:27317774 PMCid:PMC4978905 Schaid D.J., Chen W., and Larson N.B., 2018, From genome-wide associations to candidate causal variants by statistical fine-mapping, Nature Reviews Genetics, 19(8): 491-504. https://doi.org/10.1038/s41576-018-0016-z PMid:29844615 PMCid:PMC6050137 Uffelmann E., Huang Q.Q., Munung N.S., De Vries J., Okada Y., Martin A.R., Lappalainen T., and Posthuma D., 2021, Genome-wide association studies, Nature Reviews Methods Primers, 1(1): 59. https://doi.org/10.1038/s43586-021-00056-9 Uffelmann E., Huang Q.Q., Munung N.S., De Vries J., Okada Y., Martin A.R., Martin H.C., Lappalainen T., and Posthuma D., 2021, Genome-wide association studies, Nature Reviews Methods Primers, 1(1): 59. https://doi.org/10.1038/s43586-021-00056-9 Wang C., Li H., Long Y., Dong Z., Wang J., Liu C., Wan X., and Wan X., 2023, A systemic investigation of genetic architecture and gene resources controlling kernel size-related traits in maize, International Journal of Molecular Sciences, 24(2): 1025. https://doi.org/10.3390/ijms24021025 PMid:36674545 PMCid:PMC9865405 Wen W., Li D., Li X., Gao Y., Li W., Li H., Chen W., Luo J., and Yan J., 2014, Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights, Nature Communications, 5(1): 3438. https://doi.org/10.1038/ncomms4438 PMid:24633423 PMCid:PMC3959190
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