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Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using ‘Omics’-Based Network Approaches: A Future Perspective

机译:基于组学的网络方法发现茶树(Camellia sinensis)特征性代谢途径的基因:未来展望

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摘要

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, ‘omics’-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight ‘omics’-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in ‘omics’ analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with ‘omics’-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant.
机译:茶树(茶树)中特征性的次生代谢产物,包括类黄酮,茶氨酸和咖啡因,是茶浓郁的口味,新鲜的口感和对健康有益的主要来源。涉及这些特征成分的基因的解码仍然明显滞后,这为应用遗传改良和代谢工程奠定了障碍。随着高通量转录组学和代谢组学的普及,基于“组学”的网络方法(例如基因共表达网络和基因-代谢网络)已成为植物专业(次级)代谢基因发现的强大工具。 。因此,总结和介绍这种基于系统的策略在促进茶树(或其他植物)中特征性代谢途径的基因鉴定中至关重要。在这篇综述中,我们描述了转录组学和代谢组学在转录本和代谢物谱分析方面的最新进展,并使用模型和非模型工厂中的成功实例重点介绍了基于“组学”的网络策略。此外,我们总结了“组学”分析在茶树中特征代谢物基因鉴定中的最新进展。通过与基于“组学”的网络方法进行比较,讨论了当前策略的局限性。最后,我们展示了在茶树中引入这种网络策略的潜力,并有望在茶树中发现有特征的代谢物基因的有前景的网络。

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