Journal of Tea Science Research, 2025, Vol.15, No.1, 1-11 http://hortherbpublisher.com/index.php/jtsr 2 of allele variations, and molecular markers associated with desirable traits (Xu et al., 2018; Chen et al., 2023). These advances are driving efficient and precise breeding of tea tree varieties, improving their quality, yield, and stress resistance (Koech et al., 2019; Yamashita et al., 2020). This study explores the latest advances in functional genomics of tea plants, based on the molecular mechanisms, and regulatory pathways of key agronomic, and quality traits. By integrating the research results of genomics, transcriptomics, and metabolomics in recent years, we hope to summarize existing achievements, identify current knowledge gaps, and propose research directions for the future application of functional genomics in tea tree improvement. 2 Key Technologies in Tea Functional Genomics 2.1 Transcriptome sequencing and gene expression profiling RNA sequencing (RNA-SEq) is a fundamental tool for studying gene expression in tea plants and can be used to identify differentially expressed genes and alternative splicing events in different tissues and developmental stages. Full-length transcript analysis using long-read sequencing technology further improved the gene model and revealed transcript diversity, which is important for functional annotation and trait association studies (Xia et al., 2019; 2020b). Transcriptome analysis at different tissues and developmental stages, revealed the spatiotemporal expression regulatory patterns of genes, which related to key metabolic pathways (such as polyphenol and caffeine biosynthesis) (Xia et al., 2019; Li et al., 2022b), provides important clues for understanding how gene expression patterns affect trait variation and quality formation in tea plants. 2.2 Gene editing and functional validation Although the technology for achieving stable genetic editing in tea plants with CRISPR/Cas9, is still under development, virus-induced gene silencing (VIGS) technology, has been successfully established and can serve as a rapid and efficient functional verification method. VIGS can achieve specific silencing of target genes. For example, the silencing of the caffeine synthase gene CsTCS1 reduces the caffeine content in tea plants, and verifies the function of this gene in vivo(Li et al., 2022a). The transient gene expression system, provides a practical alternative for tea plant functional genomics research, enabling gene overexpression, silencing and promoter function analysis without the need to establish a stable transformation system (Mohajer et al., 2022). 2.3 Multi-omics integration The multi-omics integration strategy combines genomic, transcriptomic and metabolomic data, which can comprehensively analyze the molecular mechanisms behind key traits. This integration helps to establish the mapping relationship from genotype to phenotype, identify candidate genes, and pathways involved in metabolite synthesis and stress response (Xia et al., 2019; 2020b; Li et al., 2022b). With the help of multi-omics datasets, researchers can reconstruct the gene regulatory network that regulates important agronomic traits and quality traits (Xia et al., 2020b). These networks, help identify key regulatory factors and their interactions, providing a theoretical basis and technical support for trait mining and precise tea tree breeding. 3 Functional Genomics of Tea Quality Traits 3.1 Pathways regulating catechin biosynthesis Catechins, the major polyphenolic compounds in tea, play a key role in tea's flavor and health benefits. Their synthesis occurs primarily through the flavonoid metabolic pathway. Genes encoding enzymes such as chalcone synthase (CHS), anthocyanidin reductase (ANR), leucocyanidin reductase (LAR), and flavonoid 3'5'-hydroxylase (F3'5'H) play a central role in this metabolic pathway. Studies have shown that, functional allelic variation in the F3'5'H gene determines the ratio of dihydroxy to trihydroxy catechins, and that specific single-nucleotide
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