Absence of MutSβ leads to the formation of slipped-DNA for CTG/CAG contractions at primate replication forks
Bibliographic record
Abstract
Typically disease-causing CAG/CTG repeats expand, but rare affected families can display high levels of contraction of the expanded repeat amongst offspring. Understanding instability is important since arresting expansions or enhancing contractions could be clinically beneficial. The MutSβ mismatch repair complex is required for CAG/CTG expansions in mice and patients. Oddly, by unknown mechanisms MutSβ-deficient mice incur contractions instead of expansions. Replication using CTG or CAG as the lagging strand template is known to cause contractions or expansions respectively; however, the interplay between replication and repair leading to this instability remains unclear. Towards understanding how repeat contractions may arise, we performed in vitro SV40-mediated replication of repeat-containing plasmids in the presence or absence of mismatch repair. Specifically, we separated repair from replication: Replication mediated by MutSβ- and MutSα-deficient human cells or cell extracts produced slipped-DNA heteroduplexes in the contraction- but not expansion-biased replication direction. Replication in the presence of MutSβ disfavoured the retention of replication products harbouring slipped-DNA heteroduplexes. Post-replication repair of slipped-DNAs by MutSβ-proficient extracts eliminated slipped-DNAs. Thus, a MutSβ-deficiency likely enhances repeat contractions because MutSβ protects against contractions by repairing template strand slip-outs. Replication deficient in LigaseI or PCNA-interaction mutant LigaseI revealed slipped-DNA formation at lagging strands. Our results reveal that distinct mechanisms lead to expansions or contractions and support inhibition of MutSβ as a therapeutic strategy to enhance the contraction of expanded 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".