Selection-free, high frequency genome editing by homologous recombination of human pluripotent stem cells using Cas9 RNP and AAV6
Bibliographic record
Abstract
Abstract Combination of genome editing and human pluripotent stem cells (hPSCs) offers a platform for in vitro disease modeling, drug discovery and personalized stem cell therapeutics. However, incorporation of large modifications using CRISPR/Cas9-based genome editing in hPSCs typically requires the use of selection markers due to low editing efficiencies. Here we report a novel editing technology in hPSCs using Cas9 protein complexed with chemically modified single guide RNA (sgRNA) and recombinant AAV6 (rAAV6) vectors for donor delivery without marker selection. With these components, we demonstrate targeted integration of a 2.2 kb DNA expression cassette in hPSCs at frequencies up to 94% and 67% at the HBB and MYD88 loci, respectively. We used this protocol to correct the homozygous sickle cell disease (SCD) mutation in an iPSC line derived from a SCD patient with a frequency of 63%. This Cas9/AAV6 system allows for both the integration of large gene cassettes and the creation of single nucleotide changes in hPSCs at high frequencies, eliminating the need for multiple editing steps and marker selection, thus increasing the potential of editing human pluripotent cells for both research and translational applications.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".