Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 309 6.3 Network visualization and functional enrichment analysis Visualization tools and databases, such as TeaCoN, facilitate the exploration of gene co-expression networks, module relationships, and hub gene connectivity. Functional enrichment analyses (e.g., GO and KEGG) are routinely used to interpret the biological significance of network modules, revealing enrichment in pathways related to secondary metabolism, stress response, and development. These analyses help prioritize candidate genes for functional studies and breeding (Zhang et al., 2020). 6.4 Tea-specific regulatory patterns and variation among germplasms Comparative network analyses across diverse tea cultivars and germplasms reveal both conserved and rewired regulatory modules, especially for secondary metabolism and environmental adaptation. SNP genotyping and GWAS have identified trait-linked polymorphisms and population structure differences, highlighting the genetic diversity underlying tea quality. These findings support the use of network-guided breeding and marker-assisted selection to improve tea quality traits. 7 Molecular Breeding Strategies and Future Perspectives 7.1 Development of quality-related molecular markers and QTL mapping Advances in genomics and high-throughput sequencing have enabled the development of diverse molecular markers, such as SNPs and indels, for tea quality traits. QTL mapping and genome-wide association studies (GWAS) have identified candidate genes and loci associated with key metabolites like free amino acids and polyphenols, providing a foundation for marker-assisted selection (MAS) and accelerating the breeding of high-quality tea cultivars (Wang et al., 2024). 7.2 Potential of gene editing in improving quality traits While direct applications of CRISPR in tea are still emerging, future prospects highlight gene editing as a promising tool for precise modification of quality-related genes. The integration of gene editing with multi-omics and molecular marker technologies is expected to enable targeted improvement of flavor, stress resistance, and other desirable traits (Lubanga et al., 2021). 7.3 Utilization of genetic diversity and identification of elite resources Comprehensive germplasm characterization using molecular markers and pangenome analyses has revealed extensive genetic diversity in tea. This diversity is crucial for identifying elite resources and broadening the genetic base for breeding programs. Studies have shown that genetic divergence is not strictly linked to geographic origin, emphasizing the importance of systematic evaluation and utilization of diverse germplasm (Wang et al., 2024). 7.4 Establishing a precision breeding system focusing on quality traits Genomic selection (GS) and genomics-assisted breeding strategies are being implemented to increase genetic gain, reduce breeding cycles, and enhance selection accuracy for complex quality traits. Integrating MAS, GS, and high-throughput phenotyping forms the basis of a precision breeding system tailored to tea quality improvement (Lubanga et al., 2022). 7.5 Current research limitations and future directions Despite significant progress, challenges remain, including the long generation time of tea, limited functional validation of candidate genes, and the need for more efficient transformation and gene editing systems. Future research should focus on integrating single-cell omics, pangenomics, and advanced gene editing, as well as leveraging plant-microbe interactions and epigenetic regulation to further accelerate tea quality improvement (Xia et al., 2020).
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