Short-day-induced expression of <i>PtTFL2</i> triggers growth–defense tradeoffs during <i>Pinus tabuliformis</i> dormancy
Bibliographic record
Abstract
Conifers have developed intricate dormancy strategies to cope with extreme climates in winter. Among various environmental cues, shortened photoperiods in the fall induce conifers to enter dormancy, leading to growth cessation, bud set, and enhanced freezing tolerance. However, the molecular mechanisms of short-day-induced dormancy are not fully understood. In this study, we treated Pinus tabuliformis seedlings with different photoperiods and confirmed that short days rapidly induced and promoted dormancy. Transcriptomic analysis of photoperiod and annual cycle conditions revealed that the expression of TFL1-like (PtTFL2) was highly associated with various biological processes associated with dormancy. Heterologous overexpression studies showed that PtTFL2 promoted dormancy in poplar and delayed vegetative growth and enhanced freezing tolerance in both poplar and Arabidopsis thaliana. The transcription factor co-expression network centered on PtTFL2 identified for the co-transcription factors PtNF-YC18 and PtNAC67. PtTFL2 physically interacted with PtNF-YC18 to synergistically regulate both vegetative growth and growth cessation during dormancy. Additionally, PtTFL2 interacted with PtNAC67 to directly activate PtDHN2 expression, enhancing freezing tolerance during dormancy. Our findings highlight the role of PtTFL2 in conifer dormancy rapidly induced by short days and outline a regulatory network centered on PtTFL2 wherein 2 modules (PtTFL2-PtNF-YC18 and PtTFL2-PtNAC67) trigger growth-defense tradeoffs in the onset of winter dormancy.
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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".