Trichostatin A and 5-Aza-2′-Deoxycytidine influence the expression of cold-induced genes in<i>Arabidopsis</i>
Bibliographic record
Abstract
The expression of cold-induced genes is critical for plants to survive under freezing stress. However, the underlying mechanisms for the decision of when, where, and which genes to express are unclear when a plant meets a sudden temperature drop. Previous studies have demonstrated epigenetics to play a central role in the regulation of gene expression in plant responses to environmental stress. DNA methylation and histone deacetylation are the two most important epigenetic modifications. This study was conducted to investigate the effects of inhibiting DNA methylation and histone deacetylation on gene expression, and to explore the potential role of epigenetics in plant responses to cold stress. The results revealed that histone deacetylase inhibitors (trichostatin A) and DNA methylation inhibitors (5-Aza-2'-deoxycytosine) treatment enhanced cold tolerance. DNA microarray analysis and the gene ontology method revealed 76 cold-induced differently expressed genes in Arabidopsis thaliana seedlings that were treated to 0°C for 24 h following Trichostatin A and 5-Aza-2'-Deoxycytidine. Furthermore, analyses of metabolic pathways and transcription factors of 3305 differentially expressed genes were performed. Each four metabolic pathways were significantly affected (p < 0.01) by Trichostatin A and 5-Aza-2'-Deoxycytidine. Finally, 10 genes were randomly selected and verified via qPCR analysis. Our study indicated that Trichostatin A and 5-Aza-2'-Deoxycytidine can improve the plant cold resistance and influence the expression of the cold-induced gene in A. thaliana. This result will advance our understanding of plant freezing responses and may provide a helpful strategy for cold tolerance improvement in crops.
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 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 | 0.001 | 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".