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. 2023 Dec 18;14(12):2232.
doi: 10.3390/genes14122232.

Transcriptome and Metabolome Analysis of Isoquinoline Alkaloid Biosynthesis of Coptis chinensis in Different Years

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Transcriptome and Metabolome Analysis of Isoquinoline Alkaloid Biosynthesis of Coptis chinensis in Different Years

Xinyi Min et al. Genes (Basel). .

Abstract

Coptis chinensis is a perennial herb of the Ranunculaceae family. The isoquinoline alkaloid is the main active component of C. chinensis, mainly exists in its rhizomes and has high clinical application potential. The in vitro synthesis of isoquinoline alkaloids is difficult because their structures are complex; hence, plants are still the main source of them. In this study, two-year and four-year rhizomes of C. chinensis were selected to investigate the effect of growth years on the accumulation of isoquinoline alkaloids. Two-year and four-year C. chinensis were selected for metabolomics detection and transcriptomic analysis. A total of 413 alkaloids were detected by metabolomics analysis, of which 92 were isoquinoline alkaloids. (S)-reticuline was a significantly different accumulated metabolite of the isoquinoline alkaloids biosynthetic pathway in C. chinensis between the two groups. The results of transcriptome analysis showed that a total of 464 differential genes were identified, 36 of which were associated with the isoquinoline alkaloid biosynthesis pathway of C. chinensis. Among them, 18 genes were correlated with the content of important isoquinoline alkaloids. Overall, this study provided a comprehensive metabolomic and transcriptomic analysis of the rapid growth stage of C. chinensis rhizome from the perspective of growth years. It brought new insights into the biosynthetic pathway of isoquinoline alkaloids and provided information for utilizing biotechnology to improve their contents in C. chinensis.

Keywords: Coptis chinensis; RNA-Seq; UPLC-MS/MS; biosynthesis; isoquinoline alkaloids.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Two-year and four-year C. chinensis samples. (A) Whole C. chinensis plant sample. The left side was a two-year C. chinensis, and the right side was a four-year C. chinensis. (B) Rhizome sample of C. chinensis. The left sample was the two-year sample and the right sample was the four-year.
Figure 2
Figure 2
(A) The numbers and proportion of DAMs detected in two-year and four-year C. chinensis. (B) The content heatmap of the differential accumulation of alkaloids. Each column represents a biological repeat, and each row represents a metabolite.
Figure 3
Figure 3
Enrichment of differential expression genes in different years of C. chinensis. The vertical coordinate in the graph corresponds to the biological metabolic pathway; the horizontal coordinate indicates the percentage of the number of genes enriched into each pathway; and the color of the bubbles represents the significance of the enrichment, which is indicated by the Q-value, with the more reddish color representing the smaller Q-value and the higher degree of enrichment. (A) KEGG Enrichment analysis of differential expression genes. (B) GO Enrichment analysis of differential genes.
Figure 4
Figure 4
(A) Phylogenetic relationships of OMTs form C. chinensis and various other plants. (B) Phylogenetic relationships of P450s form C. chinensis and various other plants. The sequence used for the construction is shown in Supplementary Table S8.
Figure 5
Figure 5
Biosynthetic pathways of isoquinoline alkaloids and expression patterns of related genes. Each column represents a group of biological repeats, and each row represents a gene.
Figure 6
Figure 6
Correlation network diagram between differentially expressed structured genes and important alkaloids. The thickness of the line represents the level of correlation, and the color of the line represents the size of the p-value.
Figure 7
Figure 7
qRT-PCR results of the 13 genes related to isoquinoline alkaloid biosynthesis. The error bars represent the standard error of three biological replicates. Data were calculated using the mean of three independent biological samples, and error bars were used to indicate the standard deviation. A Student’s t-test was used to compare the difference between the two treatments (n = 3, * p < 0.05, ** p < 0.01).

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