<i>Arabidopsis thaliana</i> siRNA biogenesis mutants have the lower frequency of homologous recombination
Bibliographic record
Abstract
Small interfering RNAs (siRNAs) are involved in the regulation of plant development and response to stress. We have previously shown that mutants impaired in Dicer-like 2 (DCL2), DCL3 and DCL4, RDR2, RDR6 and NPRD1 are partially impaired in their response to stress and dcl2 and dcl3 plants are also impaired in transgenerational response to stress, including changes in homologous recombination frequency (HRF). Here, we have analyzed genome stability of dcl2, dcl3, dcl4, dcl2 dcl3, dcl2 dcl3 dcl4 and rdr6 mutants by measuring the non-induced and the stress-induced recombination frequency. We found that all mutants had the lower spontaneous HRF. The analysis of strand breaks showed that all tested Arabidopsis mutants had a higher level of spontaneous strand breaks, suggesting that the lower HRF is not due to the unusually low level of breaks. Exposure to methyl methane sulfonate (MMS) resulted in an increase in the level of strand breaks in wild-type plants and a decrease in mutants. All mutants had the higher methylation of cytosines at CpG sites under non-induced conditions. Exposure to MMS resulted in a decrease in methylation level in wild-type plants and an increase in methylation in all dcl mutants. The expression of several DNA repair genes was altered in dcl4 plants under non-induced and induced conditions. Our data suggest that siRNA biogenesis may be essential for the maintenance of the genome stability and stress response in Arabidopsis.
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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) | 0.000 | 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 | 0.001 |
| 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".