Transgenerational response to stress in plants and its application for breeding
Bibliographic record
Abstract
A growing number of reports indicate that plants possess the ability to maintain a memory of stress exposure throughout their ontogenesis and even transmit it faithfully to the following generation. Some of the features of transgenerational memory include elevated genome instability, a higher tolerance to stress experienced by parents, and a cross-tolerance. Although the underlying molecular mechanisms of this phenomenon are not clear, a likely contributing factor is the absence of full-scale reprogramming of the epigenetic landscape during gametogenesis; therefore, epigenetic marks can occasionally escape the reprogramming process and can be passed on to the progeny. To date, it is not entirely clear which part of the epigenetic landscape is more likely to escape the reprogramming events, and whether such a process is random or directed and sequence specific. The identification of specific epigenetic marks associated with specific stressors would allow generation of stress-tolerant plants through the recently discovered techniques for precision epigenome engineering. The engineered DNA-binding domains (e.g. ZF, TALE, and dCas9) fused to particular chromatin modifiers would make it possible to target epigenetic modifications to the selected loci, probably allowing stress tolerance to be achieved in the progeny. This approach, termed epigenetic breeding, along with other methods has great potential to be used for both the assessment of the propagation of epigenetic marks across generations and trait improvement in plants. In this communication, we provide a short overview of recent reports demonstrating a transgenerational response to stress in plants, and discuss the underlying potential molecular mechanisms of this phenomenon and its use for plant biotechnology applications.
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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 | 0.001 | 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".