Bidirectional transcription stimulates expansion and contraction of expanded (CTG)•(CAG) repeats
Bibliographic record
Abstract
More than 12 neurogenetic disorders are caused by unstable expansions of (CTG)•(CAG) repeats. The expanded repeats are unstable in germline and somatic cells, with potential consequences for disease severity. Previous studies have shown that contractions of (CAG)(95) are more frequent when the repeat tract is transcribed. Here we determined whether transcription can promote repeat expansion, using (CTG)•(CAG) repeat tracts in the size range that is typical for myotonic dystrophy type 1. We derived normal human fibroblasts having single-copy genomic integrations of 800 CTG repeats. The repeat tract showed modest instability when it was not transcribed, yielding an estimated mutation rate of 0.28% per generation. Instability was enhanced several-fold by transcription in the forward or reverse transcription, and 30-fold by bidirectional transcription, yielding many expansions and contractions of more than 200 repeats. These results suggest that convergent bidirectional transcription, which has been reported at several disease loci, could contribute to somatic instability of highly expanded (CTG)•(CAG) repeats.
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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 | 0.000 |
| 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".