CRISPR-Switch regulates sgRNA activity by Cre recombination for sequential editing of two loci
Bibliographic record
Abstract
CRISPR-Cas9 is an efficient and versatile tool for genome engineering in many species. However, inducible CRISPR-Cas9 editing systems that regulate Cas9 activity or sgRNA expression often suffer from significant limitations, including reduced editing capacity, off-target effects, or leaky expression. Here, we develop a precisely controlled sgRNA expression cassette that can be combined with widely-used Cre systems, termed CRISPR-Switch (SgRNA With Induction/Termination by Cre Homologous recombination). Switch-ON facilitates controlled, rapid induction of sgRNA activity. In turn, Switch-OFF-mediated termination of editing improves generation of heterozygous genotypes and can limit off-target effects. Furthermore, we design sequential CRISPR-Switch-based editing of two loci in a strictly programmable manner and determined the order of mutagenic events that leads to development of glioblastoma in mice. Thus, CRISPR-Switch substantially increases the versatility of gene editing through precise and rapid switching ON or OFF sgRNA activity, as well as switching OVER to secondary sgRNAs.
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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".