Increasing the Targeting Scope of CRISPR Base Editing System Beyond NGG
Bibliographic record
Abstract
Genome editing provides a new therapeutic strategy to cure genetic diseases. The recently developed CRISPR-Cas9 base editing technology has shown great potential to repair the majority of pathogenic point mutations in the patient's DNA precisely. Base editor is the fusion of a Cas9 nickase with a base-modifying enzyme that can change a nucleotide on a single strand of DNA without generating double-stranded DNA breaks. However, a major limitation in applying such a system is the prerequisite of a protospacer adjacent motif sequence at the desired position relative to the target site. Progress has been made to increase the targeting scope of base editors by engineering SpCas9 protein variants, establishing systems with broadened editing windows, characterizing new SpCas9 orthologs, and developing prime editing technology. In this review, we discuss recent progress in the development of CRISPR base editing, focusing on its targeting scope, and we provide a workflow for selecting a suitable base editor based on the target nucleotide sequences.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".