Evaluating the Mutagenic Activity of Targeted Endonucleases Containing a <i>Sharkey</i> FokI Cleavage Domain Variant in Zebrafish
Bibliographic record
Abstract
Synthetic targeted endonucleases such as zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) have recently emerged as powerful tools for targeted mutagenesis, especially in organisms that are not amenable to embryonic stem cell manipulation. Both ZFNs and TALENs consist of DNA-binding arrays that are fused to the nonspecific FokI nuclease domain. In an effort to improve targeted endonuclease mutagenesis efficiency, we enhanced their catalytic activity using the Sharkey FokI nuclease domain variant. All constructs tested display increased DNA cleavage activity in vitro. We demonstrate that one out of four ZFN arrays containing the Sharkey FokI variant exhibits a dramatic increase in mutagenesis frequency in vivo in zebrafish. The other three ZFNs exhibit no significant alteration of activity in vivo. Conversely, we demonstrate that TALENs containing the Sharkey FokI variant exhibit absent or severely reduced in vivo mutagenic activity in zebrafish. Notably, Sharkey ZFNs and TALENs do not generate increased toxicity-related defects or mortality. Our results present Sharkey ZFNs as an effective alternative to conventional ZFNs, but advise against the use of Sharkey TALENs.
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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".