Newly developed quantitative transactivation system shows difference in activation by Vitis CBF transcription factors on DRE/CRT elements
Bibliographic record
Abstract
BACKGROUND: Agroinfiltration-based transactivation systems can determine if a protein functions as a transcription factor, and via which promoter element. However, this activation is not always a yes or no proposition. Normalization for variation in plasmid delivery into plant cells, sample collection and protein extraction is desired to allow for a quantitative comparison between transcription factors or promoter elements. RESULTS: We developed new effector and reporter plasmids which carry additional reporter genes, as well as a procedure to assay all three reporter enzymes from a single extract. The applicability of these plasmids was demonstrated with the analysis of CBF transcription factors and their target promoter sequence, DRE/CRT. Changes in the core DRE/CRT sequence abolished activation by Vitis CBF1 or Vitis CBF4, whereas changes in the surrounding sequence lowered activation by Vitis CBF1 but much less so for Vitis CBF4. The system also detected a reduction in activation due to one amino acid change in Vitis CBF1. CONCLUSIONS: The newly developed effector and reporter plasmids improve the ability to quantitatively compare the activation on two different promoter elements by the same transcription factor, or between two different transcription factors on the same promoter element. The quantitative difference in activation by VrCBF1 and VrCBF4 on various DRE/CRT elements support the hypothesis that these transcription factors have unique roles in the cold acclimation process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".