Whole transcriptome analysis of three leaf stages in two cultivars and one of their F1 hybrid of Camellia sinensis L. with differing EGCG content

Tea ( Camellia sinensis (L.) O. Kuntze) is one of the most beneficial beverages due to its health attributes. Whole leaf transcriptome analysis of three leaf stages of C. sinensis has the potential to reveal candidate genes associated with these major beneficial compounds. Epigallocatechin-3-gallate...

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Veröffentlicht in:Tree genetics & genomes 2017-02, Vol.13 (1), Article 13
Hauptverfasser: Lin, Jinke, Wilson, Iain W., Ge, Guoping, Sun, Guiling, Xie, Fuliang, Yang, Yanfang, Wu, Liangyu, Zhang, Baohong, Wu, Jianqiang, Zhang, Yue, Qiu, Deyou
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Sprache:eng
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Zusammenfassung:Tea ( Camellia sinensis (L.) O. Kuntze) is one of the most beneficial beverages due to its health attributes. Whole leaf transcriptome analysis of three leaf stages of C. sinensis has the potential to reveal candidate genes associated with these major beneficial compounds. Epigallocatechin-3-gallate (EGCG) is one of the most important bioactive catechin (antioxidant) in tea drink derived. EGCG has many important physiological functions and positive effects on human health, such as anticancer, antioxidation, controlling blood pressure, and blood sugar content. Although the major metabolic pathways of tea-specific compounds have been established, knowledge of the genes involved in the regulation and synthesis of EGCG in C. sinensis is limited. To gain insight into the molecular mechanisms that regulate EGCG levels, leaf transcriptomes were sequenced at three developmental stages (bud, second leaf, and fourth leaf) of two C. sinensis cultivars and one F 1 hybrid line #1005 that possess varying EGCG levels. Approximately 470.9 M of quality controlled-filtered sequencing paired-end reads corresponding to 47.09 G nucleotides were obtained from which 130,762 unique sequences were identified. Genes whose expression correlated with changes in EGCG levels were identified, which may be associated with EGCG content. Prediction of the potential targets of microRNAs (miRNAs), the specific subset of long noncoding RNAs (LncRNAs), and mRNA-like noncoding RNAs (mlncRNAs) indicated that miRNAs may play a role in the expression regulation of the genes involved in EGCG levels.
ISSN:1614-2942
1614-2950
DOI:10.1007/s11295-016-1089-5