Your browser doesn't support javascript.
loading
Gene Coexpression Networks Reveal Key Drivers of Flavonoid Variation in Eleven Tea Cultivars (Camellia sinensis).
Zheng, Chao; Ma, Jian-Qiang; Chen, Jie-Dan; Ma, Chun-Lei; Chen, Wei; Yao, Ming-Zhe; Chen, Liang.
Afiliação
  • Zheng C; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Ma JQ; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Chen JD; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Ma CL; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Chen W; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Yao MZ; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
  • Chen L; Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs , Tea Research Institute of the Chinese Academy of Agricultural Sciences , Hangzhou 310008 , China.
J Agric Food Chem ; 67(35): 9967-9978, 2019 Sep 04.
Article em En | MEDLINE | ID: mdl-31403784
ABSTRACT
Following the recent completion of the draft genome sequence of the tea plant, high-throughput decoding of gene function, especially for those involved in complex secondary metabolic pathways, has become a major challenge. Here, we profiled the metabolome and transcriptome of 11 tea cultivars, and then illustrated a weighted gene coexpression network analysis (WGCNA)-based system biological strategy to interpret metabolomic flux, predict gene functions, and mine key regulators involved in the flavonoid biosynthesis pathway. We constructed a multilayered regulatory network, which integrated the gene coexpression relationship with the microRNA target and promoter cis-regulatory element information. This allowed us to reveal new uncharacterized TFs (e.g., MADSs, WRKYs, and SBPs) and microRNAs (including 17 conserved and 15 novel microRNAs) that are potentially implicated in different steps of the catechin biosynthesis. Furthermore, we applied metabolic-signature-based association method to capture additional key regulators involved in catechin pathway. This provides important clues for the functional characterization of five SCPL1A acyltransferase family members, which might be implicated in the production balance of anthocyanins, galloylated catechins, and proanthocyanins. Application of an "omics"-based system biology strategy should facilitate germplasm utilization and provide valuable resources for tea quality improvement.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Flavonoides / Camellia sinensis / Redes Reguladoras de Genes Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Flavonoides / Camellia sinensis / Redes Reguladoras de Genes Idioma: En Ano de publicação: 2019 Tipo de documento: Article