Efficient GBA1 editing via HDR with ssODNs by outcompeting pseudogene-mediated gene conversion upon CRISPR/Cas9 cleavage
Bibliographic record
Abstract
Introduction: CRISPR/Cas9-edited induced pluripotent stem cells (iPSCs) are valuable research models for mechanistic studies. However, gene conversion between a gene-pseudogene pair that share high sequence identity and form direct repeats in proximity on the same chromosome can interfere with the precision of gene editing. Mutations in the human beta-glucocerebrosidase gene (GBA1) are associated with Gaucher disease, Parkinson's disease, and Lewy body dementia. During the creation of a GBA1 KO iPSC line, we detected about 70% gene conversion from its pseudogene GBAP1. These events maintained the reading frame and resulted from GBA1-specific cleavage by CRISPR/Cas9, without disrupting the GBA1 gene. Method: To increase the percentage of alleles with out-of-frame indels for triggering nonsense-mediated decay of the GBA1 mRNA, we supplied the cells with two single-stranded oligodeoxynucleotide (ssODN) donors as homology-directed repair (HDR) templates. Results: We demonstrate that HDR using the ssODN templates effectively competes with gene conversion and enabled biallelic KO clone isolation, whereas the nonallelic homologous recombination (NAHR)-based deletion rate remained the same. Discussion: Here, we report a generalizable method to direct cellular DNA repair of double strand breaks at a target gene towards the HDR pathway using exogenous ssODN templates, allowing specific editing of one gene in a gene-pseudogene pair without disturbing the other.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".