Transcriptome<i>‐</i>wide isolation and expression of <scp><i>NF‐Y</i></scp> gene family in male cone development and hormonal treatment of <scp><i>Pinus tabuliformis</i></scp>
Bibliographic record
Abstract
It is known that nuclear factor Y (NF-Y) transcription factors play an important role in flowering time regulation and hormone response (ABA, GA) in angiosperms, but, little known in conifers. Moreover, the NF-Y gene family has not been comprehensively reported in conifers. Here, we identified 9 NF-YA, 9 NF-YB and 10 NF-YC genes in Pinus tabuliformis using Arabidopsis NF-Y protein sequences as queries. Additionally, by comparing conserved regions and phylogenetic relationships of the PtNF-Ys, we found that NF-Ys were both conserved and altered during evolution. PtTFL2, PtCO, PtNF-YC1 and PtNF-YC4 were exploited by expression profile in male cone development and correlation analysis. Furthermore, NF-YC1/4 and DPL (DELLA protein of P. tabuliformis) were interacted by yeast two-hybrid and BiFC assays, which suggested that NF-YC1/4 may be involved in gibberellins signaling pathway. Moreover, the multiple types of phytohormones-responsive cis-elements (ABA, JA, IAA, SA) have been found, and gene expression profile analysis showed that many NF-Y genes responded positively to SA and as opposed to IAA and JA, revealing the potential role of NF-Ys in conifers resistance. In summary, this study provided the basis for further investigation of the function of NF-Y genes in conifers.
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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) | 0.001 | 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".