Genome-wide identification and expression analysis of the calmodulin-binding transcription activator (CAMTA) gene family in wheat (Triticum aestivum L.)
Bibliographic record
Abstract
BACKGROUND: Plant calmodulin-binding transcription activator (CAMTA) proteins play important roles in hormone signal transduction, developmental regulation, and environmental stress tolerance. However, in wheat, the CAMTA gene family has not been systematically characterized. RESULTS: In this work, 15 wheat CAMTA genes were identified using a genome-wide search method. Their chromosome location, physicochemical properties, subcellular localization, gene structure, protein domain, and promoter cis-elements were systematically analyzed. Phylogenetic analysis classified the TaCAMTA genes into three groups (groups A, B, and C), numbered 7, 6, and 2, respectively. The results showed that most TaCAMTA genes contained stress-related cis-elements. Finally, to obtain tissue-specific and stress-responsive candidates, the expression profiles of the TaCAMTAs in various tissues and under biotic and abiotic stresses were investigated. Tissue-specific expression analysis showed that all of the 15 TaCAMTA genes were expressed in multiple tissues with different expression levels, as well as under abiotic stress, the expressions of each TaCAMTA gene could respond to at least one abiotic stress. It also found that 584 genes in wheat genome were predicted to be potential target genes by CAMTA, demonstrating that CAMTA can be widely involved in plant development and growth, as well as coping with stresses. CONCLUSIONS: This work systematically identified the CAMTA gene family in wheat at the whole-genome-wide level, providing important candidates for further functional analysis in developmental regulation and the stress response in wheat.
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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 | 0.001 | 0.001 |
| 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 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".