Expression Profiling and Bioinformatic Analyses of a Novel Cold Stress-Regulated and Chloroplast-Targeted Protein from Triticum aestivum and Aegilops Tauschii
Bibliographic record
Abstract
Cold acclimation is a multigenic trait that allows hardy plants to develop efficient tolerance mechanisms needed for winter survival. To determine the genetic nature of these mechanisms, several cold-responsive genes of unknown function were identified from cold-acclimated wheat (Triticum aestivum). To identify the putative functions and structural features of these new genes, integrated genomic approaches of data mining, expression profiling, and bioinformatic predictions were used. We herein report the structural heterogeneity of cDNAs, distribution, and low temperature-specificity and Protein structure of the identified Wcor14 gene. Analyses of the cDNA and genomic DNA sequences by Vector NTI 9.0 software, suggested that, Wcor14 and its related sequences constitute a small multigene family with different intron sizes. The deduced WCOR14 polypeptide is a hydrophobic polypeptide with 140 amino acids (MW=13.5 kDa), showed high homology to the previously identified wheat and barley COR proteins. No homologous sequences were found in other organisms suggesting that this family is specific to the plant kingdom. The highly homologous signal peptides of WCOR14, BCOR14b and WCS19 contained one putative 14-3-3 protein recognition motif. In this motif, S-residue was predicted as a phosphorylation site and besides this, four other putative phosphorylation sites in WCOR14 were predicted by the NetPhos version 2.0 software. Comparative analyses of gene expression profiling shows that the expression of this gene is correlated with the development of freezing tolerance in cereals.
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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".