Insights from multi-omics integration into seed germination of Taxus chinensis var mairei
Bibliographic record
Abstract
The transition from deep dormancy to seed germination is essential for the life cycle of plants, but how this process occurs in the gymnosperm Chinese yew (Taxus chinensis var mairei), the natural source of the anticancer drug paclitaxel, remains unclear. Herein, we analyse the transcriptome, proteome, spatial metabolome, and spatial lipidome of the Chinese yew and present the multi-omics profiles of dormant and germinating seeds. Our results show that abscisic acid and gibberellic acid 12 homoeostasis is closely associated with gene transcription and protein translation, and the balance between these phytohormones thereby determines if seeds remain dormant or germinate. We find that an energy supply of carbohydrates from glycolysis and the TCA cycle feed into the pentose phosphate pathway during seed germination, and energy supplied from lipids are mainly derived from the lipolysis of triacylglycerols. Using mass spectrometry imaging, we demonstrate that the spatial distribution of plant hormones and phospholipids has a remarkable influence on embryo development. We also provide an atlas of the spatial distribution of paclitaxel C in Chinese yew seeds for the first time. The data from this study enable exploration of the germination mechanism of Chinese yew seeds across several omics levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".