Metabolic Variations among Three New Tea Varieties Cultivated in Shandong, China.

Cultivar identification is a necessary step in tea breeding programs. Rapid identification methods would greatly improve these breeding processes. To preliminarily identify the three new Lucha tea varieties (LC6, LC7, and LC17) cultivated in Shandong, we measured their main agronomic characters and biochemical components. Then, we analyzed the metabolic profiles of these tea varieties and Fuding Dabaicha (FD) using a UPLC-ESI-MS/MS system. Their biochemical components indicated that the Lucha varieties had excellent varietal characteristics, with higher amino acid contents. Furthermore, secondary metabolism changed a lot in the Lucha tea varieties compared with that in the FD, with their accumulations of flavonoids and phenolic acids showing significant differences. These differential flavonoids were dominated by flavones and flavanone, flavonols, flavonoid carbonosides, and flavanols monomer. Flavanols especially, including epicatechin glucoside, epicatechin-3-(3″-O-methyl)gallate, epigallocatechin-3-O-(3,5-O-dimethyl)gallate, and epitheaflavic acid-3-O-Gallate, showed higher levels in the Lucha varieties. The phenolic acids containing caffeoyl groups showed higher levels in the Lucha varieties than those in the FD, while those containing galloyl groups showed a reverse pattern. Nitrogen metabolism, including amino acids, also showed obvious differences between the Lucha varieties and FD. The differential amino acids were mainly higher in the Lucha varieties, including 5-L-glutamyl-L-amino acid, N-monomethyl-L-arginine, and N-α-acetyl-L-ornithine. By using these approaches, we found that LC6, LC7, and LC17 were excellent varieties with a high yield and high quality for making green teas in Shandong.

Effect of shading on physiological attributes and comparative transcriptome analysis of Camellia sinensis cultivar reveals tolerance mechanisms to low temperatures.

Tea is a vital beverage crop all over the world, including in China. Low temperatures restrict its growth, development, and terrestrial distribution, and cold event variability worsens cold damage. However, the physiological and molecular mechanisms of Camellia sinensis under shade in winter remain unclear. In our study, tea leaves were utilized for physiological attributes and transcriptome analysis in November and December in three shading groups and no-shade control plants. When compared to the no-shade control plants, the shading group protected tea leaves from cold damage, increased photochemical efficiency (Fv/Fm) and soil plant analysis development (SPAD), and sustained chlorophyll a, chlorophyll b, chlorophyll, and carotenoid contents by physiological mean. Then, transcriptome analysis revealed 20,807 differentially expressed genes (DEGs) and transcription factors (TFs) in November and December. A comparative study of transcriptome resulted in 3,523 DEGs and many TFs under SD0% vs. SD30%, SD0% vs. SD60%, and SD0% vs. SD75% of shading in November and December. Statistically, 114 DEGs were downregulated and 72 were upregulated under SD0% vs. SD30%. SD0% vs. SD60% resulted in 154 DEGs, with 60 downregulated and 94 upregulated. Similarly, there were 505 DEGs of which 244 were downregulated and 263 were upregulated under SD0% vs. SD75% of shading throughout November. However, 279 DEGs were downregulated and 105 were upregulated under SD0% vs. SD30%. SD0% vs. SD60% resulted in 296 DEGs, with 172 downregulated and 124 upregulated. Finally, 2,173 DEGs were regulated in December, with 1,428 downregulated and 745 upregulated under SD0% vs. SD75%. These indicate that the number of downregulated DEGs in December was higher than the number of upregulated DEGs in November during low temperatures. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes were highly regulated in the photosynthesis, plant hormone signal transduction, and mitogen-activated protein kinase (MAPK) signaling pathways. However, qRT-PCR and RNA-seq relative expression of photosynthetic (DEGs) Lhcb2 in both November and December, plant hormone (DEGs) BRI1 and JAZ in November and IAA and ERF1 in December, and key DEGs of MAPK signal transduction FLS2, CHIB, and MPK4 in November and RBOH, MKK4_5, and MEKK1 in December in three shading groups and no-shade control plants responded to tea cold tolerance. The enhanced expression of light-harvesting photosystem I gene Lhca5, light-harvesting photosystem II gene Lhcb2, and mitogen-activated protein kinases MEKK1 and MPK4/6 enhance the cold-tolerance mechanism of C. sinensis. These comprehensive transcriptomic findings are significant for furthering our understanding of the genes and underlying regulatory mechanisms of shade-mediated low-temperature stress tolerance in horticultural crops.

Effect of Shading on Physiological Attributes and Proteomic Analysis of Tea during Low Temperatures.

Shading is an important technique to protect tea plantations under abiotic stresses. In this study, we analyzed the effect of shading (SD60% shade vs. SD0% no-shade) on the physiological attributes and proteomic analysis of tea leaves in November and December during low temperatures. The results revealed that shading protected the tea plants, including their soil plant analysis development (SPAD), photochemical efficiency (Fv/Fm), and nitrogen content (N), in November and December. The proteomics analysis of tea leaves was determined using tandem mass tags (TMT) technology and a total of 7263 proteins were accumulated. Further, statistical analysis and the fold change of significant proteins (FC < 0.67 and FC > 1.5 p < 0.05) revealed 14 DAPs, 11 increased and 3 decreased, in November (nCK_vs_nSD60), 20 DAPs, 7 increased and 13 decreased, in December (dCK_vs_dSD60), and 12 DAPs, 3 increased and 9 decreased, in both November and December (nCK_vs_nSD60). These differentially accumulated proteins (DAPs) were dehydrins (DHNs), late-embryogenesis abundant (LEA), thaumatin-like proteins (TLPs), glutathione S-transferase (GSTs), gibberellin-regulated proteins (GAs), proline-rich proteins (PRPs), cold and drought proteins (CORA-like), and early light-induced protein 1, which were found in the cytoplasm, nucleus, chloroplast, extra cell, and plasma membrane, and functioned in catalytic, cellular, stimulus-response, and metabolic pathways. In conclusion, the proliferation of key proteins was triggered by translation and posttranslational modifications, which might sustain membrane permeability in tea cellular compartments and could be responsible for tea protection under shading during low temperatures. This study aimed to investigate the impact of the conventional breeding technique (shading) and modern molecular technologies (proteomics) on tea plants, for the development and protection of new tea cultivars.

Prediction of Tea Polyphenols, Free Amino Acids and Caffeine Content in Tea Leaves during Wilting and Fermentation Using Hyperspectral Imaging.

The withering and fermentation degrees are the key parameters to measure the processing technology of black tea. The traditional methods to judge the degree of withering and fermentation are time-consuming and inefficient. Here, a monitoring model of the biochemical components of tea leaves based on hyperspectral imaging technology was established to quantitatively judge the withering and fermentation degrees of fresh tea leaves. Hyperspectral imaging technology was used to obtain the spectral data during the withering and fermentation of the raw materials. The successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and uninformative variable elimination (UVE) are used to select the characteristic bands. Combined with the support vector machine (SVM), random forest (RF), and partial least square (PLS) methods, the monitoring models of the tea polyphenols (TPs), free amino acids (FAA) and caffeine (CAF) contents were established. The results show that: (1) CARS performs the best among the three feature band selection methods, and PLS performs the best among the three machine learning models; (2) the optimal models for predicting the content of the TPs, FAA, and CAF are CARS-PLS, SPA-PLS, and CARS-PLS, respectively, and the coefficient of determination of the prediction set is 0.91, 0.88, and 0.81, respectively; and (3) the best models for quantitatively judging the withering and fermentation degrees are FAA-SPA-PLS and TPs-CARS-PLS, respectively. The model proposed in this study can improve the monitoring efficiency of the biochemical components of tea leaves and provide a basis for the intelligent judgment of the withering and fermentation degrees in the process of black tea processing.

Red and Blue Light Affect the Formation of Adventitious Roots of Tea Cuttings (Camellia sinensis) by Regulating Hormone Synthesis and Signal Transduction Pathways of Mature Leaves.

Light is an important environmental factor which affects plant growth, through changes of intensity and quality. In this study, monochromatic white (control), red (660 nm), and blue (430 nm) light-emitting diodes (LEDs) were used to treat tea short cuttings. The results showed the most adventitious roots in blue light treated tea cuttings, but the lowest roots in that treated by red light. In order to explore the molecular mechanism of light quality affecting adventitious root formation, we performed full-length transcriptome and metabolome analyses of mature leaves under three light qualities, and then conducted weighted gene co-expression network analysis (WGCNA). Phytohormone analysis showed that Indole-3-carboxylic acid (ICA), Abscisic acid (ABA), ABA-glucosyl ester (ABA-GE), trans-Zeatin (tZ), and Jasmonic acid (JA) contents in mature leaves under blue light were significantly higher than those under white and red light. A crosstalk regulatory network comprising 23 co-expression modules was successfully constructed. Among them, the "MEblue" module which had a highly positive correlation with ICA (R = 0.92, P = 4e-04). KEGG analysis showed that related genes were significantly enriched in the "Plant hormone signal transduction (ko04075)" pathway. YUC (a flavin-containing monooxygenase), AUX1, AUX/IAA, and ARF were identified as hub genes, and gene expression analysis showed that the expression levels of these hub genes under blue light were higher than those under white and red light. In addition, we also identified 6 auxin transport-related genes, including PIN1, PIN3, PIN4, PILS5, PILS6, and PILS7. Except PILS5, all of these genes showed the highest expression level under blue light. In conclusion, this study elucidated the molecular mechanism of light quality regulating adventitious root formation of tea short cutting through WGCNA analysis, which provided an innovation for "rapid seedling" of tea plants.

Transcriptomic analysis of flower development in tea (Camellia sinensis (L.)).

Flowering is a critical and complicated process in plant development, involving interactions of numerous endogenous and environmental factors, but little is known about the complex network regulating flower development in tea plants. In this study, de novo transcriptome assembly and gene expression analysis using Illumina sequencing technology were performed. Transcriptomic analysis assembles gene-related information involved in reproductive growth of C. sinensis. Gene Ontology (GO) analysis of the annotated unigenes revealed that the majority of sequenced genes were associated with metabolic and cellular processes, cell and cell parts, catalytic activity and binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction were enriched among the DEGs. Furthermore, 207 flowering-associated unigenes were identified from our database. Some transcription factors, such as WRKY, ERF, bHLH, MYB and MADS-box were shown to be up-regulated in floral transition, which might play the role of progression of flowering. Furthermore, 14 genes were selected for confirmation of expression levels using quantitative real-time PCR (qRT-PCR). The comprehensive transcriptomic analysis presents fundamental information on the genes and pathways which are involved in flower development in C. sinensis. Our data also provided a useful database for further research of tea and other species of plants.