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. 2022 Nov 21;15(2):298-309.
doi: 10.1016/j.chmed.2022.11.002. eCollection 2023 Apr.

Combined analysis of transcriptomics and metabolomics revealed complex metabolic genes for diterpenoids biosynthesis in different organs of Anoectochilus roxburghii

Affiliations

Combined analysis of transcriptomics and metabolomics revealed complex metabolic genes for diterpenoids biosynthesis in different organs of Anoectochilus roxburghii

Yicong Wei et al. Chin Herb Med. .

Abstract

Objective: Diterpenoids with a wide variety of biological activities from Anoectochilus roxburghii, a precious medicinal plant, are important active components. However, due to the lack of genetic information on the metabolic process of diterpenoids in A. roxburghii, the genes involved in the molecular regulation mechanism of diterpenoid metabolism are still unclear. This study revealed the complex metabolic genes for diterpenoids biosynthesis in different organs of A. roxburghii by combining analysis of transcriptomics and metabolomics.

Methods: The differences in diterpenoid accumulation in roots, stems and leaves of A. roxburghii were analyzed by metabonomic analysis, and its metabolic gene information was obtained by transcriptome sequencing. Then, the molecular mechanism of differential diterpenoid accumulation in different organs of A. roxburghii was analyzed from the perspective of gene expression patterns.

Results: A total of 296 terpenoid metabolites were identified in the five terpenoid metabolic pathways in A. roxburghii. There were 38, 34, and 18 diterpenoids with different contents between roots and leaves, between leaves and stems, and between roots and stems, respectively. Twenty-nine metabolic enzyme genes with 883 unigenes in the diterpenoid synthesis process were identified, and the DXS and FDPS in the terpenoid backbone biosynthesis stage and CPA, GA20ox, GA3ox, GA2ox, and MAS in the diterpenoid biosynthesis stage were predicted to be the key metabolic enzymes for the accumulation of diterpenoids. In addition, 14 key transcription factor coding genes were predicted to be involved in the regulation of the diterpenoid biosynthesis. The expression of genes such as GA2ox, MAS, CPA, GA20ox and GA3ox might be activated by some of the 14 transcription factors. The transcription factor NTF-Y and PRE6 were predicted to be the most important transcription factors.

Conclusion: This study determined 29 metabolic enzyme genes and predicted 14 transcription factors involved in the molecular regulation mechanism of diterpenoid metabolism in A. roxburghii, which provided a reference for the further study of the molecular regulation mechanism of the accumulation of diterpenoids in different organs of A. roxburghii.

Keywords: Anoectochilus roxburghii (Wall.) Lindl.; diterpenoid metabolic pathway; leaves; metabolomics; roots; stems; transcriptome.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Principal component analysis (PCA) among the roots, stems and leaves of A. roxburghii in positive (B) and negative (B) modes (Differential metabolites with fold change ≥1.2 or ≤0.8333 and P-value <0.05 were used in the multivariate statistical analysis).
Fig. 2
Fig. 2
Cluster of Orthologous Groups (COG) classification of unigenes derived from A. roxburghii. (In total, 186,865 unigenes were grouped into 25 COG classification).
Fig. 3
Fig. 3
Graphical representation of diterpenoid biosynthesis process included Mevalonate pathway, MEP pathway and diterpenoid biosynthesis pathway, by which diterpenoids are produced in A. roxburghii. The KEGG entries of the specific enzymes that participate in the pathways are shown in red as alongside the number of contigs identified (shown in black) that putatively encode for these enzymes.
Fig. 4
Fig. 4
Gene co-expression network of diterpenoid biosynthesis genes with three subgroups (A, B, and C). Nodes in the network represent genes, and edges represent a significant correlation between gene expression levels in a pair of nodes.
Fig. 5
Fig. 5
Gene co-expression network of diterpenoid biosynthesis genes and their possible regulatory transcription factor genes with two subgroups (A and B). Nodes in the network represent genes, and edges represent a significant correlation between gene expression levels in a pair of nodes.
Fig. 6
Fig. 6
qRT-PCR verification of key genes associated with diterpenoid metabolic pathway in A. roxburghii. mRNA levels were measured by qRT-PCR. R, S, and L represent roots, stems, and leaves, respectively. All values are expressed as the mean FC values ± SEMs (n = 3 per group). **P < 0.01 vs R group.

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