Isolated short CTG/CAG DNA slip-outs are repaired efficiently by hMutSβ, but clustered slip-outs are poorly repaired
Bibliographic record
Abstract
Expansions of CTG/CAG trinucleotide repeats, thought to involve slipped DNAs at the repeats, cause numerous diseases including myotonic dystrophy and Huntington's disease. By unknown mechanisms, further repeat expansions in transgenic mice carrying expanded CTG/CAG tracts require the mismatch repair (MMR) proteins MSH2 and MSH3, forming the MutSbeta complex. Using an in vitro repair assay, we investigated the effect of slip-out size, with lengths of 1, 3, or 20 excess CTG repeats, as well as the effect of the number of slip-outs per molecule, on the requirement for human MMR. Long slip-outs escaped repair, whereas short slip-outs were repaired efficiently, much greater than a G-T mismatch, but required hMutSbeta. Higher or lower levels of hMutSbeta or its complete absence were detrimental to proper repair of short slip-outs. Surprisingly, clusters of as many as 62 short slip-outs (one to three repeat units each) along a single DNA molecule with (CTG)50*(CAG)50 repeats were refractory to repair, and repair efficiency was reduced further without MMR. Consistent with the MutSbeta requirement for instability, hMutSbeta is required to process isolated short slip-outs; however, multiple adjacent short slip-outs block each other's repair, possibly acting as roadblocks to progression of repair and allowing error-prone repair. Results suggest that expansions can arise by escaped repair of long slip-outs, tandem short slip-outs, or isolated short slip-outs; the latter two types are sensitive to hMutSbeta. Poor repair of clustered DNA lesions has previously been associated only with ionizing radiation damage. Our results extend this interference in repair to neurodegenerative disease-causing mutations in which clustered slip-outs escape proper repair and lead to expansions.
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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 | 0.000 |
| 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".