Integrated Transcriptomic and Metabolomic Analysis Reveals Tissue-Specific Flavonoid Biosynthesis and MYB-Mediated Regulation of UGT71A1 in Panax quinquefolius
Bibliographic record
Abstract
Panax quinquefolius is a globally valued medicinal plant rich in bioactive flavonoids, yet the molecular mechanisms underlying their biosynthesis remain poorly understood. In this study, we integrated transcriptomic and metabolomic analyses to investigate tissue-specific flavonoid accumulation and regulatory networks in roots, leaves, and flowers. Metabolomic profiling identified 141 flavonoid metabolites, with flavones, flavonols, and C-glycosylflavones predominantly enriched in aerial tissues (leaves and flowers), while specific glycosides like tricin 7-O-acetylglucoside showed root-specific accumulation. Transcriptome sequencing revealed 15,551–18,946 DEGs across tissues, and the reliability of the transcriptomic data was validated by qRT-PCR. KEGG and GO annotation analyses suggested that these DEGs may play a crucial role in the biosynthesis and metabolism of secondary metabolites. From the DEGs, UGTs and MYB TFs were identified and subjected to correlation analysis. Functional validation through in vitro enzymatic assays confirmed that PqUGT71A1 catalyzes apigenin and naringenin glycosylation at the 7-OH position. Additionally, subcellular localization and yeast one-hybrid assays demonstrated that PqMYB7 and PqMYB13 interact with the PqUGT71A1 promoter and activate its expression.. This study unveils the spatial dynamics of flavonoid metabolism in P. quinquefolius and establishes a MYB-UGT regulatory axis, providing critical insights for metabolic engineering and bioactive compound optimization in medicinal plants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".