Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 310 8 Concluding Remarks The recent advances in tea genomics have significantly enhanced our understanding of the genetic networks regulating quality characters such as flavor, aroma, and secondary metabolite composition. Precise pangenome assemblies and genome-wide association studies (GWAS) have identified numerous allelic variants and candidate genes connected with useful phenotypes, which include bud flush date, leaf color, and catechin, theanine, and caffeine biosynthesis. These findings provide a sound foundation for the explanation of tea quality's complex genetic composition and for the development of molecular markers to guide breeding programs. The integration of multi-omics approaches—encompassing genomics, transcriptomics, metabolomics, and epigenomics—has enabled the construction of gene co-expression networks and the identification of hub genes and regulatory modules. Weighted gene co-expression network analysis (WGCNA) and other systems biology tools have revealed coordinated regulation among secondary metabolic pathways and highlighted the influence of environmental factors, such as light and stress, on metabolite accumulation. These systems-level insights are essential for understanding the dynamic and interconnected nature of tea quality trait regulation. Unlocking the genetic networks controlling tea quality traits paves the way for precision molecular breeding. The application of genomic selection, marker-assisted selection, and gene editing technologies' potential to enhance the effectiveness and accuracy of breeding high-quality tea varieties. As more comprehensive multi-omics data become increasingly available and candidate genes are functionally validated, the prospects of breeding elite tea cultivars with improved quality traits will be further enhanced. Ultimately, these advances will enable the sustainable improvement of tea quality and world competitiveness of the tea industry. Acknowledgments The authors sincerely thank Dr. Wang for reviewing the manuscript and providing valuable suggestions, which contributed to its improvement. Additionally, heartfelt gratitude is extended to the two anonymous peer reviewers for their comprehensive evaluation of the 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. Reference Cheng H., Wu W., Liu X., Wang Y., and Xu P., 2022, Transcription factor CsWRKY40 regulates L-theanine hydrolysis by activating the CsPDX2.1 promoter in tea leaves during withering, Horticulture Research, 9: uhac025. https://doi.org/10.1093/hr/uhac025 Fan F., Huang C., Tong Y., Guo H., Zhou S., Ye J., and Gong S., 2021, Widely targeted metabolomics analysis of white peony teas with different storage time and association with sensory attributes, Food Chemistry, 362: 130257. https://doi.org/10.1016/j.foodchem.2021.130257 Fan F., Zhou S., Qian H., Zong B., Huang C., Zhu R., Guo H., and Gong S., 2022, Effect of yellowing duration on the chemical profile of yellow tea and the associations with sensory traits, Molecules, 27(3): 940. https://doi.org/10.3390/molecules27030940 Gu D., Wu S., Yu Z., Zeng L., Qian J., Zhou X., and Yang Z., 2022, Involvement of histone deacetylase CsHDA2 in regulating (E)-nerolidol formation in tea (Camellia sinensis) exposed to tea green leafhopper infestation, Horticulture Research, 9: uhac158. https://doi.org/10.1093/hr/uhac158 Guo Y., Shen Y., Hu B., Ye H., Guo H., Chu Q., and Chen P., 2023, Decoding the chemical signatures and sensory profiles of Enshi Yulu: Insights from diverse tea cultivars, Plants, 12(21): 3707. https://doi.org/10.3390/plants12213707 Kong W., Kong X., Xia Z., Li X., Wang F., Shan R., Chen Z., You X., Zhao Y., Hu Y., Zheng S., Zhong S., Zhang S., Zhang Y., Fang K., Wang Y., Liu H., Zhang Y., Li X., Wu H., Chen G., Zhang X., and Chen C., 2025, Genomic analysis of 1,325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement, Nature Genetics, 57: 997-1007. https://doi.org/10.1038/s41588-025-02135-z Li J., Li H., Liu Z., Wang Y., Chen Y., Yang N., Hu Z., Li T., and Zhuang J., 2023, Molecular markers in tea plant (Camellia sinensis): Applications to evolution, genetic identification, and molecular breeding, Plant Physiology and Biochemistry, 198: 107704. https://doi.org/10.1016/j.plaphy.2023.107704
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