Molecular identification and functional characterization of a transcription factor GeRAV1 from Gelsemium elegans
Bibliographic record
Abstract
BACKGROUND: Gelsemium elegans is a traditional Chinese medicinal plant and temperature is one of the key factors affecting its growth. RAV (related to ABI3/VP1) transcription factor plays multiple roles in higher plants, including the regulation of plant growth, development, and stress response. However, RAV transcription factor in G. elegans has not been reported. RESULTS: In this study, three novel GeRAV genes (GeRAV1-GeRAV3) were identified from the transcriptome of G. elegans under low temperature stress. Phylogenetic analysis showed that GeRAV1-GeRAV3 proteins were clustered into groups II, IV, and V, respectively. RNA-sequencing (RNA-seq) and real-time quantitative PCR (qRT-PCR) analyses indicated that the expression of GeRAV1 and GeRAV2 was increased in response to cold stress. Furthermore, the GeRAV1 gene was successfully cloned from G. elegans leaf. It encoded a hydrophilic, unstable, and non-secretory protein that contained both AP2 and B3 domains. The amino acid sequence of GeRAV1 protein shared a high similarity of 81.97% with Camptotheca acuminata CaRAV. Subcellular localization and transcriptional self-activation experiments demonstrated that GeRAV1 was a nucleoprotein without self-activating activity. The GeRAV1 gene was constitutively expressed in the leaves, stems, and roots of the G. elegans, with the highest expression levels in roots. In addition, the expression of the GeRAV1 gene was rapidly up-regulated under abscisic acid (ABA), salicylic acid (SA), and methyl jasmonate (MeJA) stresses, suggesting that it may be involved in hormonal signaling pathways. Moreover, GeRAV1 conferred improved cold and sodium chloride tolerance in Escherichia coli Rosetta cells. CONCLUSIONS: These findings provided a foundation for further understanding on the function and regulatory mechanism of the GeRAV1 gene in response to low-temperature stress in G. elegans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".