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Record W2208298605 · doi:10.1038/mt.2015.190

Silent IL2RG Gene Editing in Human Pluripotent Stem Cells

2015· article· en· W2208298605 on OpenAlexafffund
Li B. Li, Chao Ma, Génève Awong, Marion Kennedy, Germán G. Gornalusse, Gordon Keller, Dan S. Kaufman, David W. Russell

Bibliographic record

VenueMolecular Therapy · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsPrincess Margaret Cancer CentreSunnybrook HospitalUniversity of TorontoUniversity Health Network
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsInduced pluripotent stem cellBiologyChromatinHomologous recombinationGeneticsGene targetingTransgeneGenome editingGene knockinSelectable markerHuman artificial chromosomeGeneRetrotransposonCRISPRCell biologyGenomeEmbryonic stem cellTransposable elementChromosome

Abstract

fetched live from OpenAlex

Many applications of pluripotent stem cells (PSCs) require efficient editing of silent chromosomal genes. Here, we show that a major limitation in isolating edited clones is silencing of the selectable marker cassette after homologous recombination and that this can be overcome by using a ubiquitous chromatin opening element (UCOE) promoter-driven transgene. We use this strategy to edit the silent IL2RG locus in human PSCs with a recombinant adeno-associated virus (rAAV)-targeting vector in the absence of potentially genotoxic, site-specific nucleases and show that IL2RG is required for natural killer and T-cell differentiation of human PSCs. Insertion of an active UCOE promoter into a silent locus altered the histone modification and cytosine methylation pattern of surrounding chromatin, but these changes resolved when the UCOE promoter was removed. This same approach could be used to correct IL2RG mutations in X-linked severe combined immunodeficiency patient-derived induced PSCs (iPSCs), to prevent graft versus host disease in regenerative medicine applications, or to edit other silent genes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.016
GPT teacher head0.286
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2015
Admission routes2
Has abstractno

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