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ORIGINAL RESEARCH article

Front. Plant Sci.
Sec. Plant Bioinformatics
Volume 15 - 2024 | doi: 10.3389/fpls.2024.1418585

Integrative Analysis of the Metabolome and Transcriptome Reveals the Mechanism of Polyphenol Biosynthesis in Taraxacum mongolicum

Provisionally accepted
Xing Zhao Xing Zhao 1Yiguo Li Yiguo Li 2Yuanchong Huang Yuanchong Huang 1Jun Shen Jun Shen 1Huini Xu Huini Xu 1Kunzhi Li Kunzhi Li 1*
  • 1 Kunming University of Science and Technology, Kunming, China
  • 2 Independent researcher, Kunming, China

The final, formatted version of the article will be published soon.

    Dandelion is widely used in clinical practice due to its beneficial effects. Polyphenolic compounds are considered the main anti-inflammatory active ingredient of dandelion, but the gene expression patterns of polyphenolic compounds in different dandelion tissues are still unclear. In this study, we combined a nontargeted metabolome, PacBio Iso-seq transcriptome, and Illumina RNA-seq transcriptome to investigate the relationship between polyphenols and gene expression in roots, flowers, and leaves of flowering dandelion plans. Eighty-eight flavonoids and twenty-five phenolic acids were identified, and 64 candidate genes involved in flavonoid biosynthesis and 63 candidate genes involved in chicoric acid biosynthesis were identified. Most flavonoid and chicoric acidrelated genes demonstrated the highest content in flowers. RNA-seq analysis revealed that genes involved in polyphenol biosynthesis pathways, such as CHS, CHI, F3H, F3'H, FLS, HQT, and CAS, which are crucial for the accumulation of flavonoids and chicoric acid, were upregulated in flowers. The combination of transcriptomic and metabolomic data can help us better understand the biosynthetic pathways of polyphenols in dandelion. These results provide abundant genetic resources for further studying the regulatory mechanism of dandelion polyphenol biosynthesis.

    Keywords: dandelion, polyphenol, Flavonoid, Chicoric acid, metabolome and transcriptome

    Received: 16 Apr 2024; Accepted: 31 Jul 2024.

    Copyright: © 2024 Zhao, Li, Huang, Shen, Xu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Kunzhi Li, Kunming University of Science and Technology, Kunming, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.