Effects of Light Intensity and Spectral Composition on the Transcriptome Profiles of Leaves in Shade Grown Tea Plants ( L.) and Regulatory Network of Flavonoid Biosynthesis.

Black net shade treatment attenuates flavonoid biosynthesis in tea plants, while the effect of light quality is still unclear. We investigated the flavonoid and transcriptome profiles of tea leaves under different light conditions, using black nets with different shade percentages, blue, yellow and red nets to alter the light intensity and light spectral composition in the fields. Flavonol glycosides are more sensitive to light intensity than catechins, with a reduction percentage of total flavonol glycosides up to 79.

Magneto-Optical Characteristics of Streptavidin-Coated FeO@Au Core-Shell Nanoparticles for Potential Applications on Biomedical Assays.

Recently, gold-coated magnetic nanoparticles have drawn the interest of researchers due to their unique magneto-plasmonic characteristics. Previous research has found that the magneto-optical Faraday effect of gold-coated magnetic nanoparticles can be effectively enhanced because of the surface plasmon resonance of the gold shell. Furthermore, gold-coated magnetic nanoparticles are ideal for biomedical applications because of their high stability and biocompatibility.

Optimized sequencing depth and de novo assembler for deeply reconstructing the transcriptome of the tea plant, an economically important plant species.

Background: Tea is the oldest and among the world's most popular non-alcoholic beverages, which has important economic, health and cultural values. Tea is commonly produced from the leaves of tea plants (Camellia sinensis), which belong to the genus Camellia of family Theaceae. In the last decade, many studies have generated the transcriptomes of tea plants at different developmental stages or under abiotic and/or biotic stresses to investigate the genetic basis of secondary metabolites that determine tea quality.

Tea Plant Information Archive: a comprehensive genomics and bioinformatics platform for tea plant.

Tea is the world's widely consumed nonalcohol beverage with essential economic and health benefits. Confronted with the increasing large-scale omics-data set particularly the genome sequence released in tea plant, the construction of a comprehensive knowledgebase is urgently needed to facilitate the utilization of these data sets towards molecular breeding. We hereby present the first integrative and specially designed web-accessible database, Tea Plant Information Archive (TPIA; http://tpia.

MicroRNA-Mediated Gene Silencing in Plant Defense and Viral Counter-Defense.

MicroRNAs (miRNAs) are non-coding RNAs of approximately 20-24 nucleotides in length that serve as central regulators of eukaryotic gene expression by targeting mRNAs for cleavage or translational repression. In plants, miRNAs are associated with numerous regulatory pathways in growth and development processes, and defensive responses in plant-pathogen interactions. Recently, significant progress has been made in understanding miRNA-mediated gene silencing and how viruses counter this defense mechanism.

Transcriptome Profiling Using Single-Molecule Direct RNA Sequencing Approach for In-depth Understanding of Genes in Secondary Metabolism Pathways of .

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, are important components of , and their biosynthesis has attracted widespread interest. Previous studies on the biosynthesis of these major secondary metabolites using next-generation sequencing technologies limited the accurately prediction of full-length (FL) splice isoforms. Herein, we applied single-molecule sequencing to pooled tea plant tissues, to provide a more complete transcriptome of .

Absolute quantification of microRNAs in green tea (Camellia sinensis) by stem-loop quantitative real-time PCR.

Background: There are some studies to show that food-derived plant microRNAs (miRNAs) may be detected in mammals. The research evidence has provoked a considerable debate whether plant-derived miRNAs exert the same regulatory functions as endogenous animal miRNAs. To test the hypothesis, methods of highly sensitive absolute quantification miRNAs have been developed.

Differential transcriptome analysis of leaves of tea plant (Camellia sinensis) provides comprehensive insights into the defense responses to Ectropis oblique attack using RNA-Seq.

Tea is a very popular and healthy nonalcoholic beverage worldwide. As an evergreen woody plant, the cultivation of tea plants (Camellia sinensis) is challenged by biotic stresses, and one of which is feeding of Ectropis oblique. In China, E.

Molecular Cloning and Characterization of Hydroperoxide Lyase Gene in the Leaves of Tea Plant (Camellia sinensis).

Hydroperoxide lyase (HPL, E.C. 4.

Molecular cloning, functional analysis of three cinnamyl alcohol dehydrogenase (CAD) genes in the leaves of tea plant, Camellia sinensis.

Cinnamyl alcohol dehydrogenase (CAD; EC 1.1.1.

CsICE1 and CsCBF1: two transcription factors involved in cold responses in Camellia sinensis.

C-repeat/dehydration-responsive element binding factors (CBFs) can induce the expression of a suite of cold-responsive genes to increase plant cold tolerance, and inducer of CBF expression 1 (ICE1) is a major activator for CBF. In the present study, we isolated the full-length cDNAs of ICE1 and CBF from Camellia sinensis, designated as CsICE1 and CsCBF1, respectively. The deduced protein CsICE1 contains a highly conserved basic helix-loop-helix (bHLH) domain and C-terminal region of ICE1-like proteins.

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds.

Background: Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes.