Transcription is a major driving force for plastid genome instability in Arabidopsis
Bibliographic record
Abstract
Though it is an essential process, transcription can be a source of genomic instability. For instance, it may generate RNA:DNA hybrids as the nascent transcript hybridizes with the complementary DNA template. These hybrids, called R-loops, act as a major cause of replication fork stalling and DNA breaks. In this study, we show that lowering transcription and R-loop levels in plastids of Arabidopsis thaliana reduces DNA rearrangements and mitigates plastid genome instability phenotypes. This effect can be observed on a genome-wide scale, as the loss of the plastid sigma transcription factor SIG6 prevents DNA rearrangements by favoring conservative repair in the presence of ciprofloxacin-induced DNA damage or in the absence of plastid genome maintenance actors such as WHY1/WHY3, RECA1 and POLIB. Additionally, resolving R-loops by the expression of a plastid-targeted exogenous RNAse H1 produces similar results. We also show that highly-transcribed genes are more susceptible to DNA rearrangements, as increased transcription of the psbD operon by SIG5 correlates with more locus-specific rearrangements. The effect of transcription is not specific to Sigma factors, as decreased global transcription levels by mutation of heat-stress-induced factor HSP21, mutation of nuclear-encoded polymerase RPOTp, or treatment with transcription-inhibitor rifampicin all prevent the formation of plastid genome rearrangements, especially under induced DNA damage conditions.
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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 | 0.001 |
| 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".