Journal of Tea Science Research 2024, Vol.14, No.6 http://hortherbpublisher.com/index.php/jtsr © 2024 HortHerb Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved.
Journal of Tea Science Research 2024, Vol.14, No.6 http://hortherbpublisher.com/index.php/jtsr © 2024 HortHerb Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Publisher HortHerb Publisher Edited by Editorial Team of Journal of Tea Science Research Email: edit@jtsr.hortherbpublisher.com Website: http://hortherbpublisher.com/index.php/jtsr Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada Journal of Tea Science Research (ISSN 1927-6494) is an open access, peer reviewed journal published online by HortHerb Publisher. The journal is publishing all the latest and outstanding research articles, letters and reviews in all aspects of tea research, containing the studies on tea cultivation, breeding, plant protection, tea processing, technical and economic, tea food and health products, medical care of tea, as well as the cloning and analysis of tea genes or genomics; the analytical and functional of tea molecular genetics. HortHerb Publisher is an international Open Access publisher specializing in horticulture, herbal sciences, and tea-related research registered at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. All the articles published in Journal of Tea Science Research are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. HortHerb Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
Journal of Tea Science Research (online), 2024, Vol. 14, No.6 ISSN 1927-6494 http://hortherbpublisher.com/index.php/jtsr © 2024 HortHerb Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content Unraveling the Genetic Networks Controlling Tea Quality Traits Jianmin Zheng, Zhou Jiayao Journal of Tea Science Research, 2024, Vol. 14, No. 6, 304-312 Secondary Metabolism in Tea Plants: Pathways and Regulatory Mechanisms Baofu Huang, Jie Zhang Journal of Tea Science Research, 2024, Vol. 14, No. 6, 313-321 Genetic Regulation of Key Aroma Compounds in Different Tea Varieties Xichen Wang, Lianming Zhang Journal of Tea Science Research, 2024, Vol. 14, No. 6, 322-334 Key Genetic Pathways Regulating Flavonoid Biosynthesis in Tea Plants Yufen Wang, Xiaocheng Wang Journal of Tea Science Research, 2024, Vol. 14, No. 6, 335-343 Synthesis and Regulation of Catechins in Tea Plants: A Research Review Lian Chen, Guangman Xu Journal of Tea Science Research, 2024, Vol. 14, No. 6, 344-352
Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 304 Research Insight Open Access Unraveling the Genetic Networks Controlling Tea Quality Traits Jianmin Zheng1, Jiayao Zhou2 1 Institute of Life Sciences, Jiyang Colloge of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China 2 Traditional Chinese Medicine Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, China Corresponding author: jiayao.zhou@cuixi.org Journal of Tea Science Research, 2024, Vol.14, No.6 doi: 10.5376/jtsr.2024.14.0028 Received: 10 Sep., 2024 Accepted: 21 Oct., 2024 Published: 08 Nov., 2024 Copyright © 2024 Zheng and Zhou, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Zheng J.M., and Zhou J.Y., 2024, Unraveling the genetic networks controlling tea quality traits, Journal of Tea Science Research, 14(6): 304-312 (doi: 10.5376/jtsr.2024.14.0028) Abstract Camellia sinensis, the tea plant, is a globally significant beverage crop with great economic, cultural, and nutritional value. Tea's quality traits, including flavor, aroma, mouthfeel, and major biochemical constituents, are very complex and are tightly regulated by multilevel genetic and metabolic networks. With advances in molecular biology and multi-omics technology, researchers have found more functional genes and key metabolic pathways involved in tea polyphenol biosynthesis, amino acids, caffeine, and aroma compounds. Quality-forming regulatory factors such as transcription factors, non-coding RNAs, and epigenetics also have vital roles. This review systematically integrates advances in genomics, transcriptomics, metabolomics, proteomics, and epigenomics, and considers how systems biology approaches (e.g., WGCNA, Bayesian networks, machine learning) could be applied to construct genetic regulatory networks underlying tea quality traits, and identify central regulators and tea-specific modules. It also considers the potential of molecular breeding technologies—e.g., molecular marker development, QTL mapping, and gene editing (e.g., CRISPR)—to enhance tea quality. A deep understanding of the genetic bases and regulatory mechanisms of tea quality traits is of great importance in the quest for enhancing molecular breeding, supporting high-quality industry development, and enhancing the international competitiveness of China's tea industry. Keywords Tea quality; Genetic network; Functional genes; Transcriptional regulation; Metabolomics; Molecular breeding 1 Introduction Tea (Camellia sinensis) is one of the most widely consumed beverages globally, with a long-standing cultural heritage and immense economic importance. As a major cash crop in countries such as China, India, Sri Lanka, Kenya, and Japan, tea supports the livelihoods of millions of smallholder farmers and plays a crucial role in international trade. According to the Food and Agriculture Organization (FAO), global tea production has continued to rise steadily, driven by increasing consumer demand for high-quality and health-promoting beverages (Wang et al., 2021; Moreira et al., 2024). The quality of tea is established by a complex array of properties, which include flavor, aroma, taste, appearance, and biochemical composition. Such properties are influenced by both genetic and environmental factors and are buttressed by highly advanced metabolic activities involving polyphenols (e.g., catechins and theaflavins), amino acids (in particular, theanine), caffeine, and a wide variety of volatile organic compounds (VOCs) (Kong et al., 2025). The sensory characteristics of tea—bitterness, astringency, umami, and roasty or floral aromas—result from highly controlled interactions among these compounds, which are differentially expressed in tea cultivars, cultivation conditions, and processing. An understanding of the genetic regulation of these quality traits is valuable to both basic and applied research. With next-generation sequencing (NGS), transcriptome profiling, metabolomics, and genome editing technologies, researchers have at their command the unparalleled tools to dissect the molecular foundation of tea quality. However, as information on single biosynthetic genes and pathways is being accumulated, the genetic networks that control trait integration and coordination are still largely unresolved. This has presented a challenge to the development of molecular markers and precise methods of improving tea quality through breeding (Xia et al., 2020).
Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 305 This study provides a comprehensive synthesis of recent advances in uncovering the genetic and regulatory networks that control tea quality traits, including the identification of key functional genes, transcriptional and epigenetic regulators, and multi-omics-based network construction. It also highlights the practical potential of integrating systems biology approaches with molecular breeding technologies—such as marker-assisted selection, quantitative trait loci (QTL) mapping, and CRISPR-based genome editing—to accelerate the development of high-quality tea cultivars. A deeper understanding of these genetic networks not only enhances knowledge of trait evolution and diversification in Camellia sinensis, but also lays a solid foundation for precision breeding and the sustainable improvement of global tea quality. 2 Classification and Phenotypic Characteristics of Tea Quality Traits 2.1 Quality traits related to chemical composition The tea quality is established essentially by the chemical composition of tea, and this contains amino acids, catechins, flavonoids, phenolic acids, caffeine, and other volatile compounds. These metabolites create color, taste, and flavor in tea. Amino acids, for example, contribute to brightness and fresh-sweet tastes, while catechins contribute bitterness and astringency. Specific metabolites such as 4-hydroxybenzoyl glucose and feruloyl quinic acid control color luminance, whereas volatile compounds such as linalool and 1-octen-3-ol control flower and fruity scents. The processing and storage transformation and equilibrium of such a compound dictate the final quality of tea products (Fan et al., 2021; 2022; Guo et al., 2023). 2.2 Sensory quality attributes Sensory characteristics of tea are appearance, aroma, taste and mouthfeel. Traditionally, these are determined by expert sensory panels, but objective determination utilizing sophisticated analytical technology has more recently been used. Sensory quality is regarded as being closely related to chemical make-up: sweetness and umami are enhanced by high soluble sugar and amino acid levels and reduced by low caffeine and polyphenol levels responsible for bitterness and astringency. Aroma characteristics result from a sophisticated mixture of volatile compounds imparting floral, fruity, chestnut, or woody notes according to their composition. Instrumental methods such as near-infrared spectroscopy (NIRS) and metabolomics are nowadays utilized broadly for determining quickly and objectively sensory features. For example, in Enshi Yulu tea, sensory assessment not only includes visual inspection of different samples (Figure 1A) but also a qualitative inspection of fragrance, flavor, and the total mouthfeel scores (Figure 1B) with close agreement of sensory characteristics and quality factors (Wang et al., 2022; Guo et al., 2023; Lu et al., 2023). Figure 1 Enshi Yulu tea samples and sensory evaluation (Adopted from Guo et al., 2023) Image caption: A: Appearance of three Enshi Yulu tea samples; B: Sensory traits and score (Adopted from Guo et al., 2023)
Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 306 2.3 Influence of environmental and management factors Sensory quality and chemical composition are determined by environmental conditions (altitude, soil, climate) and cultivation practice (methods of processing, storage, cultivar selection). For example, teas grown at high altitude are sweeter and fresher due to lower temperature and unique ecological conditions. Processing operations such as fermentation, withering, and yellowing alter the composition of major metabolites, therefore impacting taste and aroma. Soil properties and microbial population on the other hand are mainly accountable for the accrual of quality traits in tea leaves, and seasonal differences can cause significant changes in the amount of catechin, amino acids, and caffeine. All these combine to determine the regional and seasonal typic of the tea quality (Zhou et al., 2020; Yang et al., 2022; Wu et al., 2025). 3 Key Functional Genes and Metabolic Pathways Regulating Tea Quality 3.1 Genes involved in the biosynthesis of tea polyphenols and catechins Catechins and other polyphenols are major contributors to tea’s taste and health benefits. Their biosynthesis is controlled by structural genes such as chalcone synthase, flavonoid 3',5'-hydroxylase, leucoanthocyanidin dioxygenase, and polyphenol oxidase. MYB transcription factors (e.g., CsMYB8, CsMYB99) play central roles in regulating these pathways. Co-expression network analyses have identified hub genes and modules that coordinate catechin biosynthesis, and environmental factors like light also influence gene expression and metabolite accumulation (Tai et al., 2018; Lu et al., 2024). 3.2 Metabolic pathways related to amino acid synthesis Amino acids, particularly theanine, are responsible for tea's umami flavor. The genes like theanine synthetase and glutamine synthetase regulate the biosynthesis of theanine, being controlled by transcription factors like CsMYB9 and CsMYB49. WRKY transcription factors like CsWRKY53 and CsWRKY40 and abscisic acid (ABA) signaling play a significant role in theanine hydrolysis during postharvest treatment and influence the quality of finished tea. DNA methylation and other epigenetic mechanisms also control amino acid biosynthetic gene expression consistent with seasonal and environmental fluctuations (Qiao et al., 2019; Su et al., 2020; Li et al., 2023). 3.3 Genes involved in caffeine biosynthesis and degradation Caffeine content is determined by N-methyltransferase genes, which have expanded in tea. MYB transcription factors (e.g., CsMYB85, CsMYB86) are involved in caffeine biosynthesis regulation. Comparative genomics shows that tea’s caffeine pathway evolved independently from those in coffee and cacao, with higher expression of caffeine biosynthetic genes correlating with increased caffeine accumulation in certain cultivars (Su et al., 2020). 3.4 Biosynthetic pathways of aromatic compounds Aroma is shaped by the biosynthesis of volatile terpenoids, fatty acid-derived volatiles, and carotenoid-derived volatiles. Key genes include terpene synthases, carotenoid cleavage dioxygenases (CsCCD), and various glycosidases. MYB transcription factors (e.g., CsMYB68, CsMYB147) regulate the production of mono- and sesquiterpenoid volatiles. Alternative splicing and post-transcriptional regulation also play significant roles in modulating aroma compound biosynthesis during tea processing, such as withering and supplementary light exposure (Zhang et al., 2022; Ni et al., 2023; Lu et al., 2024). 4 Roles of Epigenetic Regulation and Transcription Factors in Quality Formation 4.1 Transcriptional regulatory networks Transcription factors (TFs) such as MYB, bHLH, WRKY, and GOLDEN 2-LIKE (GLK) play important roles in regulating the biosynthesis of prominent secondary metabolites (e.g., catechins, theanine, caffeine, flavonoids, and aroma compounds) to determine tea quality. For example, MYB TFs regulate flavonoid, caffeine, and theanine biosynthesis, while WRKY TFs can act as negative regulators of O-methylated catechin biosynthesis. The bHLH family is involved in trichome development and influencing resistance and quality (Qiao et al., 2019). Dynamic gene regulatory networks, especially wound- or environment-stimulated networks, organize the expression of
Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 307 biosynthetic genes and TFs, as noted by the quick transcriptional reprogramming in oolong tea production and upon UV-B light exposure (Cheng et al., 2022; Zheng et al., 2022) (Figure 2). Figure 2 Characteristics of the transcripts and alternative splicing events in the tea plant (Adopted from Qiao et al., 2019) Image caption: A: Circos visualization of the transcriptomic profiles; B: The coding protein length distribution of the predicted CDS; C: The summary of alternative splicing events; D: The differential alternative splicing (DAS) events in Bud and SL (Adopted from Qiao et al., 2019) 4.2 Multi-layered regulation involving microRNAs and lncRNAs Although the provided papers do not directly address the roles of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in tea quality formation, alternative splicing is highlighted as a key post-transcriptional regulatory mechanism. Alternative splicing events affect a significant proportion of flavor-related genes and TFs, especially during withering, and are closely correlated with changes in aroma compound accumulation. This suggests that multi-layered regulation beyond transcription, including RNA processing, is important for fine-tuning tea quality traits (Gu et al., 2022; Liu et al., 2023). 4.3 Epigenetic modifications and heritable variation Epigenetic marks such as DNA methylation and histone acetylation play critical roles in the regulation of biosynthesis of secondary metabolites in tea. The degree of DNA methylation in promoter regions may regulate TF (e.g., CsMYC2a) binding to the main biosynthetic genes and, therefore, the accumulation of compounds with aromas such as indole. Histone acetylation and methylation regulate the expression of genes for aroma and hormone biosynthesis, especially under stress or postharvest treatment. Erasable and heritable DNA methylation
Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 308 patterns are associated with seasonally varying secondary metabolisms with effects on flavonoid and theanine pathway gene expression and TFs. These epigenetic marks represent heritable sources of tea quality variation and exhibit putative targets for breeding (Han et al., 2024; Zheng et al., 2024). 5 Applications of Multi-Omics Integration in Tea Quality Research 5.1 Integration of genomics and transcriptomics to analyze key gene expression patterns Integrating genomics and transcriptomics enables the identification and functional analysis of genes involved in tea quality traits, such as polyphenol biosynthesis. This approach allows researchers to map gene expression patterns across developmental stages and processing conditions, revealing regulatory networks that underlie the accumulation of key metabolites in tea leaves. Such integration has been pivotal in understanding the genetic basis of polyphenol formation and changes during tea plant growth and processing (Zhang et al., 2020). 5.2 Metabolomics to reveal dynamic changes in secondary metabolism Metabolomics provides a comprehensive profile of secondary metabolites, including catechins, theanine, and aroma compounds, during tea plant development and processing. By tracking dynamic changes in metabolite levels, metabolomics helps elucidate the biochemical pathways and environmental factors influencing tea quality. When combined with transcriptomics, this approach links gene expression with metabolite accumulation, offering insights into the regulation of tea flavor and health-related compounds (Yang et al., 2021). 5.3 Roles of proteomics and epigenomics in regulatory network construction Proteomics complements transcriptomics by identifying and quantifying proteins that directly mediate metabolic processes, while epigenomics uncovers regulatory mechanisms such as DNA methylation and histone modification that affect gene expression. Together, these omics layers contribute to the construction of comprehensive regulatory networks governing tea quality formation, providing a holistic view of the molecular mechanisms involved. 5.4 Case study: Integrated omics approaches revealing regulatory pathways of theanine or aroma compounds In albino tea plants, integrated genomics, transcriptomics, and metabolomics have been used to dissect the regulatory pathways of theanine and catechin accumulation. These studies have identified key genes, enzymes, and metabolites involved in the unique flavor profile of albino tea, demonstrating the power of multi-omics approaches in uncovering the molecular basis of tea quality traits (Zhang et al., 2020). 6 Construction of Genetic Regulatory Networks and Systems Biology Analyses of Tea Quality Traits 6.1 Network construction methods: WGCNA, Bayesian networks, machine learning, etc. Weighted Gene Co-expression Network Analysis or WGCNA is widely used to identify gene modules and regulatory interactions in tea, especially in secondary metabolite pathways including catechins, theanine, and caffeine. WGCNA enables one to cluster gene expression data into modules with certain biological functions and identify hub genes. Bayesian machine learning techniques and clustering methods, such as genome-wide association studies (GWAS) and genomic prediction models, are also used to study population structure, trait association, and breeding values for quality traits (Zheng et al., 2022). 6.2 Identification of network modules and core regulatory factors Network analyses have revealed multiple co-expression modules significantly associated with tea quality traits. For example, WGCNA identified 35 modules, with 20 linked to catechin, theanine, and caffeine biosynthesis. Hub genes and transcription factors (e.g., MADS, WRKY, SBP) within these modules act as core regulators. Integrative approaches combining transcriptomics and metabolomics further clarify the roles of these core factors in controlling metabolite accumulation and quality variation (Tai et al., 2018; Zheng et al., 2020).
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).
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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Journal of Tea Science Research, 2024, Vol.14, No.6, 304-312 http://hortherbpublisher.com/index.php/jtsr 312 Zheng Y., Hu Q., Yang Y., Wu Z., Wu L., Wang P., Deng H., Ye N., and Sun Y., 2022, Architecture and dynamics of the wounding-induced gene regulatory network during the oolong tea manufacturing process (Camellia sinensis), Frontiers in Plant Science, 12: 788469. https://doi.org/10.3389/fpls.2021.788469 Zheng Y., Ou X., Li Q., Wu Z., Wu L., Li X., Zhang B., and Sun Y., 2024, Genome-wide epigenetic dynamics of tea leaves under mechanical wounding stress during oolong tea postharvest processing, Food Research International, 194: 114939. https://doi.org/10.1016/j.foodres.2024.114939 Zhou J., Yu X., He C., Qiu A., Li Y., Shu Q., Chen Y., and Ni D., 2020, Withering degree affects flavor and biological activity of black tea: A non-targeted metabolomics approach, LWT - Food Science and Technology, 130: 109535. https://doi.org/10.1016/j.lwt.2020.109535 Disclaimer/Publisher’s Note The statements, opinions, and data contained in all publications are solely those of the individual authors and contributors and do not represent the views of the publishing house and/or its editors. The publisher and/or its editors disclaim all responsibility for any harm or damage to persons or property that may result from the application of ideas, methods, instructions, or products discussed in the content. Publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Journal of Tea Science Research, 2024, Vol.14, No.6, 313-321 http://hortherbpublisher.com/index.php/jtsr 313 Research Insight Open Access Secondary Metabolism in Tea Plants: Pathways and Regulatory Mechanisms Baofu Huang1, JieZhang2 1 Traditional Chinese Medicine Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, China 2 Institute of Life Sciences, Jiyang Colloge of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China Corresponding author: jie.zhang@jicat.org Journal of Tea Science Research, 2024, Vol.14, No.6 doi: 10.5376/jtsr.2024.14.0029 Received: 28 Sep., 2024 Accepted: 30 Oct., 2024 Published: 20 Nov., 2024 Copyright © 2024 Huang and Zhang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Huang B.F., and Zhang J., 2024, Secondary metabolism in tea plants: pathways and regulatory mechanisms, Journal of Tea Science Research, 14(6): 313-321 (doi: 10.5376/jtsr.2024.14.0029) Abstract Camellia sinensis, the tea plant, is an economically valuable crop globally due to its unique flavor, nutritional content, and cultural significance. Tea quality is largely a result of a versatile array of secondary metabolites, such as polyphenols, alkaloids, amino acids, and volatile aroma compounds, which are also largely involved in plant defense and environmental tolerance. New findings in plant molecular biology have allowed the identification in great detail of major biosynthetic pathways like the phenylpropanoid-flavonoid pathway, the MVA/MEP terpenoid biosynthetic pathways, purine and caffeine metabolism, and the theanine biosynthesis. Moreover, studies in mechanisms of regulation—spanning from transcription factors and non-coding RNAs to epigenetic modifications —have unraveled multilayered control mechanisms governing the biosynthesis of metabolites. The integration of transcriptomics, metabolomics, proteomics, and epigenomics has further revealed the spatial-temporal gene expression and metabolic dynamics upon environmental stimuli. The recent advances in tea plant secondary metabolism research are reviewed, application of gene editing, marker-assisted selection, and synthetic biology in metabolic engineering highlighted, and prospects and challenges in the future are elaborated. Increased understanding of secondary metabolic networks and their regulation will provide the major tools for molecular breeding and ensure the introduction of sustainable development in the tea industry. Keywords Tea plant; Secondary metabolism; Biosynthetic pathway; Regulatory mechanism; Molecular breeding 1 Introduction Tea, derived from the leaves of Camellia sinensis, is one of the most widely consumed non-alcoholic beverages globally. It holds tremendous economic importance, particularly in countries such as China, India, Kenya, and Sri Lanka, where tea production and export constitute a significant share of agricultural revenue. In addition to its economic value, tea is also recognized for its nutritional and health-promoting properties. Rich in antioxidants, amino acids, polyphenols, and caffeine, tea has been associated with numerous health benefits, including cardiovascular protection, anti-inflammatory effects, and cognitive enhancement (Wei et al., 2018). Secondary metabolites in tea plants—such as catechins, theanine, caffeine, and volatile aromatic compounds—play a central role in defining tea's flavor, aroma, and mouthfeel. These metabolites are also key indicators of quality and are often used in the classification and valuation of tea products (Li et al., 2016). Beyond their contributions to sensory properties, many of these compounds are integral to the plant’s defense system. They help protect against herbivores, pathogens, and environmental stressors, thereby supporting the plant’s survival and fitness in diverse ecological niches. It is essential for basic research and applied breeding work to understand how secondary metabolites are biosynthesized and regulated in tea plants. Their biosynthesis includes complex, multi-step enzymatic pathways with stringent controls at transcriptional, post-transcriptional, and epigenetic levels. Identification of important genes, enzymes, and regulatory networks provides a foundation for molecular breeding for improved quality, stress tolerance, and adaptation of tea (Wang et al., 2016; Liao et al., 2021). Further, advances in gene editing and multi-omics technologies open up possibilities for precision editing of metabolite profiles in tea cultivars.
Journal of Tea Science Research, 2024, Vol.14, No.6, 313-321 http://hortherbpublisher.com/index.php/jtsr 314 The study provides a comprehensive overview of the recent advances in secondary metabolic pathways and their regulations in Camellia sinensis. It encapsulates the major secondary metabolites, biosynthetic pathways, and genetic and epigenetic regulations. By integrating multi-omics and functional studies, the review presents a shared framework to enhance an understanding of tea secondary metabolism. The acquired knowledge is important for onward basic plant science and has applied implications for molecular breeding for tea quality and stress tolerance enhancement, towards sustainable tea cultivation and industry development. 2 Major Secondary Metabolites in Tea Plants and Their Functions 2.1 Polyphenols and alkaloids Polyphenols, especially catechins, flavonoids, theaflavins, and thearubigins, are the most abundant and significant bioactive compounds in tea. They contribute to the antioxidant, anti-inflammatory, anticancer, and cardiovascular protective effects of tea, and are key determinants of tea’s taste, color, and health benefits (Li et al., 2022). Alkaloids such as caffeine, theobromine, and theophylline are present in tea leaves. Caffeine is the most prominent, contributing to tea’s stimulating effects and bitterness, while also playing a role in plant defense against herbivores and pathogens (Kottawa-Arachchi et al., 2018). 2.3 Volatile aromatic compounds Volatile compounds, including terpenoids, alcohols, aldehydes, and esters, are responsible for the characteristic aroma and flavor of tea. Key volatiles like linalool, geraniol, and methyl salicylate are crucial for tea quality and are influenced by both genetics and processing methods (Liu et al., 2024). 2.4 Amino acids and other functional compounds Amino acids, particularly theanine, contribute to the umami taste and sweetness of tea. They also have calming effects and are important for the overall flavor profile and health benefits of tea (Kang et al., 2024). Other notable compounds include polysaccharides, vitamins, minerals, and saponins, which contribute to the nutritional value, immune regulation, and additional health-promoting properties of tea (Luo et al., 2023). 3 Elucidation of Secondary Metabolic Pathways 3.1 Phenylpropanoid pathway and flavonoid biosynthesis Phenylpropanoid pathway is the central pathway in tea flavonoid biosynthesis, a group of compounds with primary importance to tea quality and resistance in plants. In plants, it is an enzyme cascade tightly controlled by transcription factors such as MYB, bHLH, and WD-repeat proteins. Recent transcriptomic research has discovered widespread gene expression and regulatory network differences among tea cultivars and identified AP2/ERF, WRKY, NAC, and MYB transcription factors to be involved in controlling both phenylpropanoid and flavonoid biosynthesis (Li et al., 2022). Flavonoid biosynthesis branches out into multiple sub-pathways to produce catechins, anthocyanins, and other compounds contributing to tea flavor and its health-promoting properties (Liu et al., 2021; Pratyusha and Sarada, 2022). 3.2 Terpenoid biosynthesis via MVA and MEP pathways Terpenoids, responsible for much of tea’s aroma, are synthesized through the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways. Transcriptome data reveal that tea flowers accumulate higher levels of terpenoids than leaves, largely due to elevated expression of terpene synthase genes. The regulation of terpenoid biosynthesis differs between tissues, suggesting specialized control mechanisms in flowers versus leaves (Xia et al., 2017). 3.3 Purine metabolism and caffeine biosynthesis Caffeine biosynthesis in tea plants proceeds via the purine alkaloid pathway, involving key enzymes such as S-adenosyl methionine synthase (SAMS), xanthosine methyltransferase (XMT), and caffeine synthase (TCS). Comparative transcriptomics between Camellia sinensis varieties have revealed that differences in caffeine and theobromine content are linked to the expression of these genes and their regulation by MYB and AP2/ERF transcription factors (Wang et al., 2025). The tea tree genome also shows lineage-specific expansions of caffeine biosynthetic genes, supporting the independent evolution of this pathway in tea.
Journal of Tea Science Research, 2024, Vol.14, No.6, 313-321 http://hortherbpublisher.com/index.php/jtsr 315 3.4 Amino acid metabolism and theanine biosynthetic mechanism Theanine is a unique amino acid in tea plants, which is primarily produced in the roots as an enzyme-catalyzed reaction between glutamic acid and ethylamine. It is catalyzed by theanine synthetase and is transported to the aerial parts of the plant produced as theanine. Both its biosynthesis and accumulation are controlled by environmental and transcriptional regulation, and a few MYB transcription factors participate in the process of regulation (Zhao et al., 2020). Similarly, catechins, being major secondary metabolites of tea plants, are biosynthesized through coordinated regulation of some significant structural genes and transcription factors. Experiments have shown that the catechin biosynthetic pathway is linked to gene expression and catalytic activity of genes such as CHS, CHI, F3H, F3′H, F3′5′H, DFR, ANS, LAR, ANR, and SCPL(Wei et al., 2018). These genes have tissue-specific expression modes, with higher expression levels in apical buds and young leaves, which are highly correlated with catechin accumulation. At the transcriptional level, co-expression network analysis has also demonstrated that various transcription factors (e.g., MYB and bHLH) are co-expressed with catechin biosynthetic genes, regulating their expression and metabolic processes in different tissues (Wei et al., 2018) (Figure 1). These findings reveal both the shared transcriptional processes and complex regulatory networks involved in the biosynthesis of secondary metabolites such as catechins and theanine in tea plants. Figure 1 Evolution and expression of key genes involved in catechins biosynthesis. (A) Biosynthetic pathway of the principal catechins. CHS, CHI, F3H, F3′H, F3′ 5′H, DFR, ANS, LAR, ANR, and SCPL represent genes encoding chalcone synthase, chalcone isomerase, flavanone 3-hydroxylase, flavonoid 3′-hydroxylase, flavonoid 3′,5′-hydroxylase, dihydroflavonol 4-reductase, anthocyanidin synthase, leucoanthocyanidin reductase, anthocyanidin reductase, and type 1A serine carboxypeptidase-like acyltransferases, respectively. (B) Expression profiles of key genes in different tissues of the tea plant in relation to their contents of different catechins. (B, Left) Expression levels of key genes associated with catechins biosynthesis in eight tea plant tissues: apical buds, young leaves, mature leaves, old leaves, young stems, flowers, young fruits, and tender roots. Expression data are plotted as log10 values. The horizontal axis of the boxplot (Right) shows statistics of catechins contents from different tissues, and the vertical axis exhibits different forms of catechins. “Cis” represents the contents of cis-flavan-3-ols, and “trans” represents the contents of trans-flavan-3-ols. The significant correlations of gene expression with the contents of ECG, EGCG, and cis-flavan-3-ols are indicated by black lines (Pearson’s correlation test, P< 0.05). The error bar represents the maximum and minimum catechins content in eight different tea plant tissues. (C) Transcriptional regulation of catechins biosynthetic genes. A coexpression network connecting structural genes in cat- echins biosynthesis with transcription factors represents the regulation of catechins biosynthetic genes. The color-filled hexagons represent the structural genes associated with catechins biosynthesis that was highly (green) or lowly (red) expressed in bud and leaf. Expression correlations between TFs (colored solid circles) and catechins-related genes (colored solid hexagons) are shown with colored lines (Pearson’s correlation test, P≤ 1e-6) (Adopted from Wei et al., 2018)
Journal of Tea Science Research, 2024, Vol.14, No.6, 313-321 http://hortherbpublisher.com/index.php/jtsr 316 3.5 Precursors and branched pathways of aroma compound biosynthesis Aroma compounds in tea are derived from multiple branched pathways, including those for terpenoids, phenylpropanoids, and amino acid derivatives. The expression of key biosynthetic genes and the interplay between different metabolic branches contribute to the diversity of volatile aromatic compounds in tea. Tissue-specific expression and developmental regulation further shape the aroma profile (Li et al., 2022). 4 Advances in Functional Genes and Key Enzymes 4.1 Cloning and expression regulation of structural genes Recent studies have succeeded in cloning and isolating genes of structural genes involved in secondary metabolism, such as genes encoding phenylalanine ammonia-lyase (PAL), flavonoid 3′-hydroxylase (F3′H), and some MYB transcription factors. These genes are regulated by sophisticated networks of regulators such as transcription factors MYB, bHLH, and WD40, which respond to environmental triggers and developmental cues (Jiao et al., 2023). The establishment of gene co-expression databases and integrative transcriptomic profiling has enabled the detection of conserved gene modules and regulatory elements controlling secondary metabolic pathways in tea plants (Zhang et al., 2020). 4.2 Functional identification of key metabolic enzymes Functional identification of key metabolic enzymes, such as those involved in proanthocyanidin and theanine biosynthesis, has been advanced through transient expression systems and recombinant protein assays. For example, subgroup 5 R2R3-MYB transcription factors have been shown to regulate proanthocyanidin biosynthesis, while specific MYB genes have been identified as regulators of theanine accumulation (Jiao et al., 2023). Transient transformation systems now allow for rapid gene function analysis and protein localization in tea leaves, accelerating the functional characterization of metabolic enzymes (Li et al., 2022). 4.3 Comparative analysis of varietal differences and expression patterns Comparative transcriptomic and metabolomic analyses across different tea cultivars have revealed significant varietal differences in gene expression and metabolite accumulation. Weighted gene co-expression network analysis (WGCNA) and multi-omics approaches have identified key drivers of flavonoid variation and stress response, as well as the impact of natural and artificial selection on gene family expansion and functional divergence, such as in glycosyltransferase (UGT) genes (Wang et al., 2024). These findings provide valuable resources for breeding programs aimed at improving tea quality and stress tolerance. 5 Regulatory Mechanisms at Transcriptional and Epigenetic Levels 5.1 Roles of transcription factors in regulation Transcription factors (TFs) like MYB, bHLH, WRKY, GRAS, and BZR1 families are key regulators of secondary metabolite biosynthesis in tea plants. MYB TFs, for instance, contribute to flavonoid, caffeine, theanine, and terpenoid biosynthesis, shoot development, and stress response (Li et al., 2022). BZR1 TFs are key factors in brassinosteroid signaling, integrating hormone and stress response, while WRKY and GRAS TFs play roles in abiotic stress resistance and developmental regulation. The TFs often act as components in complex regulatory networks, having responses to developmental and environmental cues in order to modulate the expression of metabolic genes. 5.2 Regulatory mechanisms involving non-coding RNAs Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), have emerged as important regulators of secondary metabolism in tea plants. They modulate the expression of key biosynthetic genes by acting as molecular sponges, forming competing endogenous RNA (ceRNA) networks, and targeting mRNAs for degradation or translational repression (Bordoloi et al., 2022). Recent studies have identified thousands of lncRNAs and miRNAs responsive to biotic and abiotic stresses, nitrogen application, and temperature, with many implicated in the regulation of catechin, theanine, and caffeine biosynthesis (Hu et al., 2023) (Figure 2).
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