Role of Epigenetic Factors in Response to Stress and Establishment of Somatic Memory of Stress Exposure in Plants
Bibliographic record
Abstract
All species are well adapted to their environment. Stress causes a magnitude of biochemical and molecular responses in plants, leading to physiological or pathological changes. The response to various stresses is genetically predetermined, but is also controlled on the epigenetic level. Most plants are adapted to their environments through generations of exposure to all elements. Many plant species have the capacity to acclimate or adapt to certain stresses using the mechanism of priming. In most cases, priming is a somatic response allowing plants to deal with the same or similar stress more efficiently, with fewer resources diverted from growth and development. Priming likely relies on multiple mechanisms, but the differential expression of non-coding RNAs, changes in DNA methylation, histone modifications, and nucleosome repositioning play a crucial role. Specifically, we emphasize the role of BRM/CHR17, BRU1, FGT1, HFSA2, and H2A.Z proteins as positive regulators, and CAF-1, MOM1, DDM1, and SGS3 as potential negative regulators of somatic stress memory. In this review, we will discuss the role of epigenetic factors in response to stress, priming, and the somatic memory of stress exposures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".