JTSR_2024v14n3

Journal of Tea Science Research, 2024, Vol.14, No.3, 134-147 http://hortherbpublisher.com/index.php/jtsr 146 Qiu H., Zhu X., Wan H., Xu L., Zhang Q., Hou P., Fan Z., Lyu Y., Ni D., Usadel B., Fernie A., and Wen W., 2020, Parallel metabolomic and transcriptomic analysis reveals key factors for quality improvement of tea plants, Journal of Agricultural and Food Chemistry, 68(19): 5483-5495. https://doi.org/10.1021/acs.jafc.0c00434 PMid:32302110 Ran X., Zhao F., Wang Y., Liu J., Zhuang Y., Ye L., Qi M., Cheng J., and Zhang Y., 2019, Plant Regulomics: a data-driven interface for retrieving upstream regulators from plant multi-omics data, The Plant Journal, 101(1): 237-248. https://doi.org/10.1111/tpj.14526 PMid:31494994 Rao A., Barkley D., França G.S., and Yanai I., 2021, Exploring tissue architecture using spatial transcriptomics, Nature, 596(7871): 211-220. https://doi.org/10.1038/s41586-021-03634-9 PMid:34381231 PMCid:PMC8475179 Riva L., and Petrini C., 2019, A few ethical issues in translational research for gene and cell therapy, Journal of Translational Medicine, 17: 1-6. https://doi.org/10.1186/s12967-019-02154-5 PMid:31779636 PMCid:PMC6883654 Savoi S., Santiago A., Orduña L., and Matus J.T., 2022, Transcriptomic and metabolomic integration as a resource in grapevine to study fruit metabolite quality traits, Frontiers in Plant Science, 13: 937927. https://doi.org/10.3389/fpls.2022.937927 PMid:36340350 PMCid:PMC9630917 Shade J., Coon H., and Docherty A.R., 2019, Ethical implications of using biobanks and population databases for genetic suicide research, American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 180(8): 601-608. https://doi.org/10.1002/ajmg.b.32718 PMid:30779308 PMCid:PMC6717044 Siddiqui J., Baskin E., Liu M., Cantemir-Stone C., Zhang B., Bonneville R., McElroy J., Coombes K., and Mathé E., 2018, IntLIM: integration using linear models of metabolomics and gene expression data, BMC Bioinformatics, 19: 1-12. https://doi.org/10.1186/s12859-018-2085-6 PMid:29506475 PMCid:PMC5838881 Perez de Souza L., Alseekh S., Naake T., and Fernie A., 2019, Mass spectrometry-based untargeted plant metabolomics, Current Protocols in Plant Biology, 4(4): e20100. https://doi.org/10.1002/cppb.20100 PMid:31743625 Tsimberidou A.M., Fountzilas E., Bleris L., and Kurzrock R., 2022, Transcriptomics and solid tumors: The next frontier in precision cancer medicine, in Seminars in Cancer Biology, 84: 50-59. https://doi.org/10.1016/j.semcancer.2020.09.007 PMid:32950605 Tyagi R., Kumar P., and Sharma U., 2021, Metabolomics techniques: A brief update, in Epigenetics and Metabolomics, 1-29. https://doi.org/10.1016/B978-0-323-85652-2.00007-5 Wang F., Chen Z., Pei H., Guo Z., Wen D., Liu R., and Song B., 2021, Transcriptome profiling analysis of tea plant (Camellia sinensis) using Oxford Nanopore long-read RNA-Seq technology, Gene, 769: 145247. https://doi.org/10.1016/j.gene.2020.145247 PMid:33096183 Wen M., Zhu M., Han Z., Ho C.T., Granato D., and Zhang L., 2023, Comprehensive applications of metabolomics on tea science and technology: Opportunities, hurdles, and perspectives, Comprehensive Reviews in Food Science and Food Safety, 22(6): 4890-4924. https://doi.org/10.1111/1541-4337.13246 PMid:37786329 Woodward A., Pandele A., Abdelrazig S., Ortori C., Khan I., Uribe M., May S., Barrett D., Grundy R., Kim D., and Rahman R., 2021, Integrated metabolomics and transcriptomics using an optimised dual extraction process to study human brain cancer cells and tissues, Metabolites, 11(4): 240. https://doi.org/10.3390/metabo11040240 PMid:33919944 PMCid:PMC8070957 Yang P., Jin L., Liao J., Shao X., Cheng J., Li L., Lu X., and Fan X., 2022, Modern research on Chinese medicine based on single-cell omics: Technologies and strategies, Zhongguo Zhong Yao Za Zhi= Zhongguo Zhongyao Zazhi= China Journal of Chinese Materia Medica, 47(15): 3977-3985. Yang Y., Saand M., Huang L., Abdelaal W., Zhang J., Wu Y., Li J., Sirohi M., and Wang F., 2021, Applications of multi-omics technologies for crop improvement, Frontiers in Plant Science, 12: 563953. https://doi.org/10.3389/fpls.2021.563953 PMid:34539683 PMCid:PMC8446515 Zeira R., Land M., Strzalkowski A., and Raphael B.J., 2022, Alignment and integration of spatial transcriptomics data, Nature Methods, 19(5): 567-575. https://doi.org/10.1038/s41592-022-01459-6 PMid:35577957 PMCid:PMC9334025

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