Manipulation of 7-Finger Zinc Finger Nuclease Increases the Efficiency of Genome Editing in Human Cells
Bibliographic record
Abstract
Genome editing tools have great potential for medicinal use. Among them, zinc finger nucleases (ZFNs) are smaller in size than transcriptional activator-like effector nucleases and CRISPR-Cas9. Therefore, ZFNs are easily packed into a viral vector with limited cargo space, including adeno-associated viral vectors. Furthermore, because ZFN patents expired in 2020, high patent royalties are not required for application. Although functional 6-finger ZFNs can be easily prepared by modular assembly, it has been extremely difficult to produce functional 7-finger ZFNs, which are expected to have higher target specificity than 6-finger ZFNs in some cases. Herein we describe the construction of 7-finger ZFNs and the improvement in genome editing efficiency, which is generally lower in 7-finger ZFNs than in 6-finger ZFNs. Modular assembly of 7-finger ZFNs was achieved using a specific mutation, and the original genome editing efficiency was increased by up to 19%. Furthermore, 7-finger ZFNs showed reduced off-target effects, exhibiting higher target specificity than the corresponding 6-finger ZFNs. Our study provides critical insights for safer and more specific genome editing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".