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Multi-omics data-driven investigations of metabolic diversity of plant triterpenoids.

Yi ShangSanwen Huang
Published in: The Plant journal : for cell and molecular biology (2018)
The vast majority of structurally diverse metabolites play essential roles in mediating the interactions between plant and environment, and constitute a valuable resource for industrial applications. Recent breakthroughs in sequencing technology have greatly accelerated metabolic studies of natural plant products, providing opportunities to investigate the molecular basis underlying the diversity of specialized plant metabolites through large-scale analysis. Here, we focus on the biosynthesis of plant triterpenoids, especially the three diversifying reactions (cyclization, oxidation and glycosylation) that largely contribute to the structural diversity of triterpenoids. Gene mining through large-scale omics data and functional characterization of metabolic genes including enzymes, transcription factors and transporters could provide important insights into the evolution of specialized plant metabolism and pave the way for the production of high-value metabolites or derivatives using synthetic biology approaches.
Keyphrases
  • cell wall
  • ms ms
  • single cell
  • genome wide
  • gene expression
  • heavy metals
  • wastewater treatment
  • machine learning
  • nitric oxide
  • deep learning
  • plant growth
  • genome wide analysis