Combined analysis of lipidomics and transcriptomics revealed the key pathways and genes of lipids in light-sensitive albino tea plant (Camellia sinensis cv. Baijiguan).

Currently, the mechanism by which light-sensitive albino tea plants respond to light to regulate pigment synthesis has been only partially elucidated. However, few studies have focused on the role of lipid metabolism in the whitening of tea leaves. Therefore, in our study, the leaves of the Baijiguan (BJG) tea tree under shade and light restoration conditions were analyzed by a combination of lipidomics and transcriptomics. The leaf color of BJG was regulated by light intensity and responded to light changes in light by altering the contents and proportions of lipids. According to the correlation analysis, we found three key lipid components that were significantly associated with the chlorophyll SPAD value, namely, MGDG (36:6), DGDG (36:6) and DGDG (34:3). Further weighted gene coexpression network analysis (WGCNA) showed that HY5 TF and GLIP genes may be hub genes involved lipid regulation in albino tea leaves. Our results lay a foundation for further exploration of the color changes in albino tea leaves.

De novo Sequencing of the Leaf Transcriptome Reveals Complex Light-Responsive Regulatory Networks in Camellia sinensis cv. Baijiguan.

Tea plants (Camellia sinensis L.) possess high genetic diversity that is important for breeding. One cultivar, Baijiguan, exhibits a yellow leaf phenotype, reduced chlorophyll (Chl) content, and aberrant chloroplast structures under high light intensity. In contrast, under low light intensity, the flush shoot from Baijiguan becomes green, the Chl content increases significantly, and the chloroplasts exhibit normal structures. To understand the underlying molecular mechanisms for these observations, we performed de novo transcriptome sequencing and digital gene expression (DGE) profiling using Illumina sequencing technology. De novo transcriptome assembly identified 88,788 unigenes, including 1652 transcription factors from 25 families. In total, 1993 and 2576 differentially expressed genes (DEGs) were identified in Baijiguan plants treated with 3 and 6 days of shade, respectively. Gene Ontology (GO) and pathway enrichment analyses indicated that the DEGs are predominantly involved in the ROS scavenging system, chloroplast development, photosynthetic pigment synthesis, secondary metabolism, and circadian systems. The light-responsive gene POR (protochlorophyllide oxidoreductase) and transcription factor HY5 were identified. Quantitative real-time PCR (qRT-PCR) analysis of 20 selected DEGs confirmed the RNA-sequencing (RNA-Seq) results. Overall, these findings suggest that high light intensity inhibits the expression of photosystem II 10-kDa protein (PsbR) in Baijiguan, thus affecting PSII stability, chloroplast development and chlorophyll biosynthesis.

Discrimination of Chinese teas with different fermentation degrees by stepwise linear discriminant analysis (S-LDA) of the chemical compounds.

This study aimed to construct objective and accurate analytical models of tea categories based on their polyphenols and caffeine. A total of 522 tea samples of 4 commonly consumed teas with different fermentation degrees (green tea, white tea, oolong tea, and black tea) were analyzed by high-performance liquid chromatography (HPLC) coupled with spectrophotometry, utilizing ISO 14502, as analytical tools. The content of polyphenols and caffeine varied significantly according to differently fermented teas, indicating that these active constituents may discriminate fermentation degrees effectively. By principal component analysis (PCA) and stepwise linear discriminant analysis (S-LDA), the vast majority of tea samples could be successfully differentiated according to their chemical markers. This study yielded three discriminant functions with the capacity to simultaneously discriminate the four tea categories with a 97.8% correct rate. In classification of oolong and other teas, there were one discriminant function and two equations with best discriminant capacity. Furthermore, the classification of different degrees of fermentation of oolong and external validation achieved the desired results. It is suggested that polyphenols and caffeine are the distinct variables to establish internationally recognized models of teas.