Transcriptomic analysis reveals differential gene expression patterns during cannabis leaf morphogenesis and phase transition
Bibliographic record
Abstract
Understanding the molecular mechanisms governing leaf morphogenesis and phase transition in Cannabis sativa is critical for optimizing its growth, development and yield. In this study, we conducted a comparative transcriptomic analysis to investigate the gene expression patterns associated with leaf development and the transition from vegetative to reproductive phases in cannabis plants. Following germination, cannabis plants display a distinct leaf developmental pattern. While the specific number of leaflets varies among cultivars, here we focused on the White Widow cultivar as a model. It showed an increase in the number of serrated leaflets from one (L1) to nine (L5) in a node-specific manner. Subsequently, the number of leaflets decreased from eight (L6) to three (L9). The transition from vegetative to reproductive phases, marked by the appearance of solitary flowers and a shift from opposite to alternate leaf phyllotaxy, occurred at node 7 and node 12, respectively. Analysis of gene expression revealed 1358 differentially expressed genes, with 1,182 genes showing differential expression across all leaves. Notably, several genes involved in leaf morphogenesis (e.g. YAB, AGO5, and TCP4) were found to be upregulated in compound leaves (L2) compared to simple leaves (L1), implying a role in leaflet formation and overall leaf morphology. Furthermore, several genes associated with phase transition and flowering (e.g. SPLs, ELFs, SOC1, and CEN-Like) exhibited specific expression patterns during the transition from vegetative to reproductive phases. These findings provide valuable insights into the genetic regulation of leaf morphogenesis and phase transition in cannabis.
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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 | 0.000 | 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".