Integrated Metabolomic and Transcriptomic Analysis of Phenylpropanoid Biosynthesis in Silphium perfoliatum

<i>Silphium perfoliatum</i> is a promising economic plant rich in bioactive secondary metabolites, yet the molecular regulation of phenylpropanoid biosynthesis across development remains unclear. To elucidate the regulatory networks underlying these metabolic processes, we integrated metabolomic and transcriptomic analyses across six developmental stages, from cotyledon to flowering. LC-MS/MS identified 1964 metabolites, with phenylpropanoids representing the largest class (601 compounds). Differential accumulation analysis showed pronounced temporal dynamics in phenylpropanoid levels, especially chlorogenic acid and its derivatives, with many compounds peaking at the flowering stage. In parallel, RNA-seq revealed 31,624 differentially expressed genes (DEGs). Functional enrichment highlighted phenylpropanoid and flavonoid biosynthetic pathways as major metabolic hubs. Correlation analysis indicated that <i>PAL</i>, <i>4CL</i>, <i>HCT</i>, <i>F3H</i>, <i>FLS</i>, and <i>F3'H</i> expression was tightly coordinated with the accumulation of phenolic acids and flavonoids, suggesting these gene encoded enzymes may represent rate-limiting steps. Furthermore, weighted gene co-expression network analysis (WGCNA) identified a "blue" module strongly associated with phenylpropanoid accumulation and significantly enriched in pathway-related genes. Together, these results provide a comprehensive regulatory framework for phenylpropanoid biosynthesis in <i>S. perfoliatum</i> and offer valuable genetic targets for metabolic engineering and molecular breeding to enhance bioactive compound production.

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Publication Details

Journal
Current Issues in Molecular Biology
Published
2026-02-21
DOI
https://doi.org/10.3390/cimb48020230
Primary Topic
Plant Gene Expression Analysis
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article
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article

Integrated Metabolomic and Transcriptomic Analysis of Phenylpropanoid Biosynthesis in Silphium perfoliatum

Dejun Zhang, Guoying Zhang
Current Issues in Molecular Biology
Plant Gene Expression Analysis
article

Integrated Metabolomic and Transcriptomic Analysis of Phenylpropanoid Biosynthesis in Silphium perfoliatum

Dejun Zhang, Guoying Zhang
article en

Abstract

<i>Silphium perfoliatum</i> is a promising economic plant rich in bioactive secondary metabolites, yet the molecular regulation of phenylpropanoid biosynthesis across development remains unclear. To elucidate the regulatory networks underlying these metabolic processes, we integrated metabolomic and transcriptomic analyses across six developmental stages, from cotyledon to flowering. LC-MS/MS identified 1964 metabolites, with phenylpropanoids representing the largest class (601 compounds). Differential accumulation analysis showed pronounced temporal dynamics in phenylpropanoid levels, especially chlorogenic acid and its derivatives, with many compounds peaking at the flowering stage. In parallel, RNA-seq revealed 31,624 differentially expressed genes (DEGs). Functional enrichment highlighted phenylpropanoid and flavonoid biosynthetic pathways as major metabolic hubs. Correlation analysis indicated that <i>PAL</i>, <i>4CL</i>, <i>HCT</i>, <i>F3H</i>, <i>FLS</i>, and <i>F3'H</i> expression was tightly coordinated with the accumulation of phenolic acids and flavonoids, suggesting these gene encoded enzymes may represent rate-limiting steps. Furthermore, weighted gene co-expression network analysis (WGCNA) identified a "blue" module strongly associated with phenylpropanoid accumulation and significantly enriched in pathway-related genes. Together, these results provide a comprehensive regulatory framework for phenylpropanoid biosynthesis in <i>S. perfoliatum</i> and offer valuable genetic targets for metabolic engineering and molecular breeding to enhance bioactive compound production.

Current Issues in Molecular BiologyVol. 48(2)
NSF NCAR High Altitude Observatory (US), Shandong Institute of Food and Drug Inspection (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Plant Gene Expression Analysis
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