Prime editing optimized RTT permits the correction of the c.8713C>T mutation in DMD gene
Bibliographic record
Abstract
Duchenne muscular dystrophy is a severe debilitating genetic disease caused by different mutations in the DMD gene leading to the absence of dystrophin protein under the sarcolemma. We used CRISPR-Cas9 prime editing technology for correction of the c.8713C>T mutation in the DMD gene and tested different variations of reverse transcription template (RTT) sequences. We increased by 3.8-fold the editing percentage of the target nucleotide located at +13. A modification of the protospacer adjacent motif sequence (located at +6) and a silent mutation (located at +9) were also simultaneously added to the target sequence modification. We observed significant differences in editing efficiency in interconversion of different nucleotides and the distance between the target, the nicking site, and the additional mutations. We achieved 22% modifications in myoblasts of a DMD patient, which led to dystrophin expression detected by western blot in the myotubes that they formed. RTT optimization permitted us to improve the prime editing of a point mutation located at +13 nucleotides from the nick site to restore dystrophin protein. Duchenne muscular dystrophy is a severe debilitating genetic disease caused by different mutations in the DMD gene leading to the absence of dystrophin protein under the sarcolemma. We used CRISPR-Cas9 prime editing technology for correction of the c.8713C>T mutation in the DMD gene and tested different variations of reverse transcription template (RTT) sequences. We increased by 3.8-fold the editing percentage of the target nucleotide located at +13. A modification of the protospacer adjacent motif sequence (located at +6) and a silent mutation (located at +9) were also simultaneously added to the target sequence modification. We observed significant differences in editing efficiency in interconversion of different nucleotides and the distance between the target, the nicking site, and the additional mutations. We achieved 22% modifications in myoblasts of a DMD patient, which led to dystrophin expression detected by western blot in the myotubes that they formed. RTT optimization permitted us to improve the prime editing of a point mutation located at +13 nucleotides from the nick site to restore dystrophin protein.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".