Chromatin-associated SUMOylation controls the transcriptional switch between plant development and heat stress responses
Bibliographic record
Abstract
The post-translational protein modification known as SUMOylation has conserved roles in the heat stress responses of various species. The functional connection between the global regulation of gene expression and chromatin-associated SUMOylation in plant cells is unknown. Here, we uncovered a genome-wide relationship between chromatin-associated SUMOylation and transcriptional switches in Arabidopsis thaliana grown at room temperature, exposed to heat stress, and exposed to heat stress followed by recovery. The small ubiquitin-like modifier (SUMO)-associated chromatin sites, characterized by whole-genome ChIP-seq, were generally associated with active chromatin markers. In response to heat stress, chromatin-associated SUMO signals increased at promoter-transcriptional start site regions and decreased in gene bodies. RNA-seq analysis supported the role of chromatin-associated SUMOylation in transcriptional activation during rapid responses to high temperature. Changes in SUMO signals on chromatin were associated with the upregulation of heat-responsive genes and the downregulation of growth-related genes. Disruption of the SUMO ligase gene SIZ1 abolished SUMO signals on chromatin and attenuated rapid transcriptional responses to heat stress. The SUMO signal peaks were enriched in DNA elements recognized by distinct groups of transcription factors under different temperature conditions. These observations provide evidence that chromatin-associated SUMOylation regulates the transcriptional switch between development and heat stress response in plant cells.
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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".