Untargeted Metabolomics and Transcriptomics Reveal the Mechanism of Metabolite Differences in Spring Tender Shoots of Tea Plants of Different Ages

Abstract

The metabolites in the tender shoots of the tea plant are the material basis for the determination of tea quality. The composition and abundance of these metabolites are affected by many key factors, and the tea plant’s age is one of them. However, the effect of plant age on the tender shoot metabolites of tea cultivars of different genotypes is poorly understood. Therefore, we used a combination of untargeted metabolomics and transcriptomics to analyze the differential mechanism behind the differences in the metabolites of the spring tender shoots of 7- and 40-year-old tea plants of two tea cultivars of different genotypes. We found that plant age could significantly change the metabolites in the spring tender shoots of tea plants and that flavonoids, and amino acids and their derivatives, were predominant among the differential metabolites. The quantities of most flavonoids in the aged tea plants of different genotypes were upregulated, which was caused by the upregulated expression of differential genes in the flavonoid biosynthesis pathway. We further discovered that 11 key structural genes play key regulatory roles in the changes in the flavonoid contents of tea plants of different plant ages. However, the influence of plant age on amino acids and their derivatives might be cultivar-specific. By characterizing and evaluating the quality-related metabolites of tea cultivars of two different genotypes at different plant ages, we found that whether an old tea plant (40 years old) can produce high-quality tea is related to the genotype of the tea plant.

Characterization of the Difference between Day and Night Temperatures on the Growth, Photosynthesis, and Metabolite Accumulation of Tea Seedlings

“…Furthermore, glutamate and ethylamine together participate in the theanine synthesis through the catalysis of theanine synthase (TS) [ 57 , 58 ]. Unfortunately, there were no differentially expressed genes in the theanine synthesis pathway by transcriptome analysis, and a similar result was also found by Yue et al [ 49 ]. This could have been due to the main synthetic site of theanine being the root, rather than the new shoot that was used in the study [ 59 ].…”

“…Here, 3 genes of LAR from the 10 °C DIF treatment had the lowest expression levels, which was consistent with the low abundance of C and GC. It was demonstrated that anthocyanidin reductase ( ANR ) cooperated with anthocyanidin synthase ( ANS ) and dihydroflavonol-4-reductase ( DFR ) to participate in the biosyntheses of epicatechin (EC) and epigallocatechin (EGC) [ 49 ]. Although ANR was not differentially expressed in this study, 2 DFR and 1 ANS were identified, with the lowest expression levels of all the genes in the 10 °C DIF treatment, suggesting that it was probably related to the lower contents of EC and EGC.…”

Differential characterization of volatile components and aroma sensory properties of different types of Hehong tea (Congou black tea)

“…Therefore, the combination of univariate and multivariate analyses can be used to more accurately screen out the marker differential compounds. This method has been widely used for differential metabolite screening in metabolomics 27,28 . According to the principle of VIP > 1, P < .05, 28 compounds with important contributions to the discrimination of the three types of Hehong tea were screened.…”

“…This method has been widely used for differential metabolite screening in metabolomics. 27,28 According to the principle of VIP > 1, P < .05, 28 compounds with important contributions to the discrimination of the three types of Hehong tea were screened. A total of 18 compounds with important contributions were screened, and their structural formula names are shown in Figure 2C.…”

Identification of characteristic aroma and bacteria related to aroma evolution during long-term storage of compressed white tea

“…Samples were effectively distinguished in the score chart ( Figure 4A ), and cross-validation informed that the model was not overfitted (green points were below blue points) ( Figure 4B ). With VIP > 1, P < 0.05 as the criterion ( 32 ), 23 differential VOCs were screened. The screening of characteristic differential VOCs is based on the variable variation trend of differential VOCs in the heat map ( Figure 3B ).…”