Journal of Tea Science Research, 2025, Vol.15, No.1, 1-11 http://hortherbpublisher.com/index.php/jtsr 8 Emerging synthetic biology tools, such as heterologous gene expression and metabolic engineering, are providing new avenues for improving tea quality and resistance. Functional validation by expressing candidate genes in model plants, as well as restructuring the synthesis of specific compounds, through metabolic pathway engineering, can help rapidly translate genomic discoveries into practical breeding outcomes (Zhang et al., 2020; Wang et al., 2023). 6.3 Challenges and future directions The main challenge still faced at present is how to establish an effective connection between gene functions and complex quantitative traits, which are often controlled by multiple genes and significantly influenced by environmental factors. To solve this difficult problem, it is necessary to integrate multi-omics data, high-resolution positioning technology and functional verification methods, so as to achieve precise regulation of the target trait (Wang et al., 2023). In the future, tea tree breeding will move towards the construction of an intelligent platform, integrating genomics, phenomics and bioinformatics, making full use of big data, machine learning and advanced molecular techniques to promote the development of sustainable breeding strategies and cultivate new tea tree varieties with high yield, stress resistance and high quality (Xia et al., 2020b; Li et al., 2023b). 7 Concluding Remarks Over the past two decades, the research progress in tea plant functional genomics has been quite rapid. Technically, the construction of high-quality reference genomes, and pan-genomes has indeed played a key role. Especially behind core traits such as flavor, stress resistance and leaf color, researchers have identified a number of key genes and allelic variations. Meanwhile, the integration of multi-omics data, such as transcriptomics, metabolomics, and epigenomics, has also enabled us to gain a deeper understanding of the formation of tea tree quality and the mechanism of environmental adaptation. Further, some changes at the genetic structure level, such as the expansion of gene families, tandem repeats and large-scale structural variations, have been confirmed to be closely related to the formation of the diversity of tea plant traits, especially in the synthesis of secondary metabolites and responses to stress. For instance, SNPS in the flavonoid synthesis pathway, have been associated with quality traits such as catechins. The discovery of structural differences, like presence/absence variations (PAVs), has also helped us better understand the genetic basis of tea plants in terms of cold resistance, disease resistance and flavor characteristics, providing a fundamental support for subsequent molecular breeding. But, to truly implement these research results, there are still many practical problems to be faced. Although functional genomics has been continuously integrated with breeding techniques such as molecular marker-assisted selection, genomic selection and gene editing, it is still not easy to precisely match complex traits. Nowdays, there is still room for breakthroughs in data sharing, cross-platform integration and practical transformation. Tasks such as establishing a complete database and a bioinformatics tool platform, though not conspicuous, are indispensable parts of promoting intelligent breeding. How to link the functions of key genes with actual agronomic traits and rapidly transform, and apply them in the breeding system still relies on the coordination of multi-disciplinary collaboration, high-throughput phenotypic technology and gene function verification. Tea plant functional genomics research is at a critical stage of transition from "information accumulation" to "precision application," promising to provide more solid theoretical and technical support for improving tea quality, enhancing environmental adaptability, and accelerating the development of new varieties. Acknowledgments The authors are particularly grateful to the two anonymous peer reviewers for their thorough evaluation of the manuscript.
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