Genome damage accumulated in seed ageing leads to plant genome instability and growth inhibition
Bibliographic record
Abstract
Successful germination and seedling establishment are important determinants of crop yields and plant survival in natural environments. Germination potential is compromised by suboptimal environmental conditions that result in seed ageing and high levels of genome damage. However, the mutagenic and growth inhibitory potential of DNA damage accumulated in seeds on subsequent seedling growth remains largely unknown. Arabidopsis seeds deficient in the chromosomal break repair factors DNA LIGASE 4 and DNA LIGASE 6 exhibited hypersensitivity to the effects of natural ageing, with reduced germination vigour and seedling biomass relative to wild type seed. Here, we identify that aged Arabidopsis seed display elevated levels of programmed cell death (PCD) in the root meristem which persists into seedling establishment, with higher levels of cell death in lines deficient in DNA double strand break repair. Reporter lines determined the effects of seed ageing on mutation levels and intrachromosomal recombination frequencies. Seed deterioration resulted in strikingly elevated levels of frameshift mutations and genome instability in germinated seedlings. Thus, elevated levels genome damage incurred in the seed stage of the plant life cycle potentially impacts significantly on subsequent plant development. Furthermore, the mutagenic effects of seed ageing has potentially long-term implications on the genome stability of plant populations and ecosystem fitness. Collectively, we identify genome damage accumulated in suboptimal quality seed impacts on subsequent plant growth and genome stability, with associated implications for crop yields and plant survival under changing climates.
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 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".