Structure and Functional Analysis of Wheat ICE (Inducer of CBF Expression) Genes
Bibliographic record
Abstract
Two different inducers of CBF expression (ICE1-like genes), TaICE41 and TaICE87, were isolated from a cDNA library prepared from cold-treated wheat aerial tissues. TaICE41 encodes a protein of 381 aa with a predicted MW of 39.5 kDa while TaICE87 encodes a protein of 443 aa with a predicted MW of 46.5 kDa. TaICE41 and TaICE87 share 46% identity while they share 50 and 47% identity with Arabidopsis AtICE1 respectively. Expression analysis revealed that mRNA accumulation was not altered by cold treatment suggesting that both genes are expressed constitutively. Gel mobility shift analysis showed that TaICE41 and TaICE87 bind to different MYC elements in the wheat TaCBFIVd-B9 promoter. Transient expression assays in Nicotiana benthamiana, showed that both TaICE proteins can activate TaCBFIVd-B9 transcription. The different affinities of TaICE41 and TaICE87 for MYC variants suggest that ICE binding specificity may be involved in the differential expression of wheat CBF genes. Furthermore, analysis of MYC elements demonstrates that a specific variant is present in the wheat CBF group IV that is associated with freezing tolerance. Overexpression of either TaICE41 or TaICE87 genes in Arabidopsis enhanced freezing tolerance only upon cold acclimation suggesting that other factors induced by low temperature are required for their activity. The increased freezing tolerance in transgenic Arabidopsis is associated with a higher expression of the cold responsive activators AtCBF2, AtCBF3, and of several cold-regulated genes.
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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".