转录组和代谢组分析揭示了丹参中黄酮类化合物的生物合成。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2025-01-02 DOI:10.1002/pca.3492
Xuxia Liu, Haitang Ma, Xiaoling Liu, Xin Wang, Zhengjun Chen, Jie Yang, Wenrong Luo, Qin Li, Fude Yang, Fang Li
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引用次数: 0

摘要

简介丹参作为一种传统中药已有数百年的历史。它具有广泛的生物活性。黄酮类化合物是丹参中重要的生物活性成分之一,具有很强的清除自由基和抗氧化能力。然而,黄酮类化合物在 DS 中的生物合成过程仍不清楚:本研究旨在了解 DS 中黄酮类化合物的生物合成分子机制:本研究对DS进行了代谢组学研究和转录组测序。结果:通过高通量 RNA 测序(RNA-seq)数据分析和液相色谱-串联质谱分析,共发现了 256 种代谢物:结果:利用非靶向代谢组学,在 DS 的根、茎、叶和花中共鉴定出 256 种代谢物。其中,55种黄酮类化合物与黄酮类化合物的代谢密切相关,包括松柏苷、丁香苷、苦参苷、芹菜苷、木犀草素和麦角苷。此外,转录组学发现的差异表达基因主要集中在类黄酮、异黄酮、黄酮和黄酮醇的生物合成中。ANS、CCOAOMT、CHI、CHS、CYP75B1、CYP75A、CYP93B2_16、CYP98A/C3'H、DFR、F3H、FLS和HCT等多个基因可能调控DS不同组织中黄酮类化合物的产生。转录组和代谢组的综合分析揭示了DS中黄酮类化合物的生物合成网络,阐明了DS根、茎、叶、花中黄酮类化合物生物合成途径的多样性:我们的研究结果为 DS 黄酮类化合物的生物合成提供了分子基础和新见解,为培育新的有价值 DS 栽培品种奠定了基础。
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Transcriptomic and Metabolomic Analyses Provide Insights Into the Flavonoid Biosynthesis in Dangshen.

Introduction: Dangshen (DS) has been used for hundreds of years as a traditional Chinese medicine. It has a wide range of biological activities. Flavonoids are one of the important bioactive components with strong free radical scavenging and antioxidant capacity in DS. However, the biosynthesis process of flavonoids in DS remains unclear.

Objective: The aim of this study was to understand the biosynthesis molecular mechanism of flavonoids in DS.

Methods: In this study, metabolomics research and transcriptome sequencing for DS were carried out. Transcript and metabolite profiles were generated by high-throughput RNA sequencing (RNA-seq) data analysis and liquid chromatography-tandem mass spectrometry, respectively.

Results: In total, 256 metabolites were identified in the root, stem, leaf, and flower of DS using untargeted metabolomics. Among them, 55 flavonoids, including pinobanksin, butein, fustin, pelargonidin, apigenin, luteolin, and eriodictyol, were closely related to flavonoid metabolism, and most of them were upregulated in different tissues of DS. Furthermore, the differentially expressed genes identified by transcriptomics were mainly enriched in the biosynthesis of flavonoid, isoflavonoid, flavone, and flavonol. A number of genes, including ANS, CCOAOMT, CHI, CHS, CYP75B1, CYP75A, CYP93B2_16, CYP98A/C3'H, DFR, F3H, FLS, and HCT, may regulate the production of flavonoids in different tissues of DS. An integrated analysis of transcriptome and metabolome revealed the flavonoid biosynthetic network in DS and elucidated the diversity of flavonoid biosynthetic pathway in roots, stems, leaves, and flowers of DS.

Conclusion: Our findings provide a molecular basis and new insights into flavonoid biosynthesis in DS and lay the foundation for breeding new valuable DS cultivars.

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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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