Zhang Shihua, Zhang Liang, Tai Yuling, Wang Xuewen, Ho Chi-Tang, Wan Xiaochun
State Key Laboratory of Tea Plant Biology and Utilization, Institute of Applied Mathematics, Anhui Agricultural University, Hefei, China.
School of Life Sciences, Anhui Agricultural University, Hefei, China.
Front Plant Sci. 2018 Jun 4;9:480. doi: 10.3389/fpls.2018.00480. eCollection 2018.
Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant () 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.
茶树中的特征性次生代谢产物,包括黄酮类化合物、茶氨酸和咖啡因,是茶叶丰富风味、清新口感和健康益处的主要来源。参与这些特征性成分合成的基因解码工作仍明显滞后,这为应用遗传改良和代谢工程带来了障碍。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,如基因共表达网络和基因-代谢物网络,已成为植物次生代谢基因发现的有力工具。因此,总结和介绍此类基于系统的策略对于促进茶树(或其他植物)特征性代谢途径的基因鉴定至关重要。在本综述中,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,并通过模式植物和非模式植物中的成功案例突出基于“组学”的网络策略。此外,我们总结了茶树特征性代谢物基因鉴定的“组学”分析的最新进展。通过与基于“组学”的网络方法比较,讨论了当前策略的局限性。最后,我们展示了在茶树中引入此类网络策略的潜力,并对茶树特征性代谢物基因的网络发现前景进行了展望。