JTSR_2024v14n3

Journal of Tea Science Research, 2024, Vol.14, No.3, 134-147 http://hortherbpublisher.com/index.php/jtsr 144 Acknowledgments The HortHerb Publisher appreciate the feedback from two anonymous peer reviewers on the manuscript of this study. Funding This work was supported by the National Natural Science Foundation of China[3210077] and the Guizhou Academy of Agricultural Sciences Talent Special Project [2022-02 and 2023-02]. 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 Beshir L., 2020, A framework to ethically approach incidental findings in genetic research, EJIFCC, 31(4): 302-309. Chao H., Zhang S., Hu Y., Ni Q., Xin S., Zhao L., Ivanisenko V., Orlov Y., and Chen M., 2024, Integrating omics databases for enhanced crop breeding, Journal of Integrative Bioinformatics, 20(4): 20230012. https://doi.org/10.1515/jib-2023-0012 PMid:37486120 PMCid:PMC10777369 Chen L., Qu H., Xia L., Liu Y., Jiang H., Sun Y., Liang M., and Jiang C., 2019, Transcriptome profiling of the fertile parent and sterile hybrid in tea plant flower buds, Hereditas, 156: 1-10. https://doi.org/10.1186/s41065-019-0090-z PMid:31019434 PMCid:PMC6474060 Chen Q., Shi J., Mu B., Chen Z., Dai W., and Lin Z., 2020, Metabolomics combined with proteomics provides a novel interpretation of the changes in nonvolatile compounds during white tea processing, Food Chemistry, 332: 127412. https://doi.org/10.1016/j.foodchem.2020.127412 PMid:32623128 Chen Y., Li E.M., and Xu L.Y., 2022, Guide to metabolomics analysis: a bioinformatics workflow, Metabolites, 12(4): 357. https://doi.org/10.3390/metabo12040357 PMid:35448542 PMCid:PMC9032224 Crandall S.G., Gold K.M., Jiménez-Gasco M.D.M., Filgueiras C.C., and Willett D.S., 2020, A multi-omics approach to solving problems in plant disease ecology, PLOS ONE, 15(9): e0237975. https://doi.org/10.1371/journal.pone.0237975 PMid:32960892 PMCid:PMC7508392 Dai W., Hu Z., Xie D., Tan J., and Lin Z., 2020, A novel spatial-resolution targeted metabolomics method in a single leaf of the tea plant (Camellia sinensis), Food Chemistry, 311: 126007. https://doi.org/10.1016/j.foodchem.2019.126007 PMid:31855776 Damiani C., Gaglio D., Sacco E., Alberghina L., and Vanoni M., 2020, Systems metabolomics: From metabolomic snapshots to design principles, Current Opinion in Biotechnology, 63: 190-199. https://doi.org/10.1016/j.copbio.2020.02.013 PMid:32278263 Dikobe T., Masenya K., and Manganyi M.C., 2023, Molecular technologies ending with 'omics': the driving force toward sustainable plant production and protection, F1000Research, 12: 480. https://doi.org/10.12688/f1000research.131413.1 Evangelatos N., Satyamourthy K., Levidou G., Brand H., Bauer P., Kouskouti C., and Brand A., 2018, Use of free/libre open source software in sepsis "-omics" research: A bibliometric, comparative analysis among the United States, EU-28 Member States, and China, OMICS: A Journal of Integrative Biology, 22(5): 365-372. https://doi.org/10.1089/omi.2018.0032 PMid:29698120 Futschik M.E., Morkel M., Schäfer R., and Sers C., 2018, The human transcriptome: implications for understanding, diagnosing, and treating human disease, in Molecular Pathology, 135-164. Academic Press. https://doi.org/10.1016/B978-0-12-802761-5.00007-9 Horton R., and Lucassen A., 2023, Ethical considerations in research with genomic data, The New Bioethics, 29(1): 37-51. https://doi.org/10.1080/20502877.2022.2060590 PMid:35484929 Hu L., Liu J., Zhang W., Wang T., Zhang N., Lee Y.H., and Lu H., 2020, Functional metabolomics decipher biochemical functions and associated mechanisms underlie small-molecule metabolism, Mass Spectrometry Reviews, 39(5-6): 417-433. https://doi.org/10.1002/mas.21611

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