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 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 | 0.000 |
| 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) | 0.001 | 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".