ArticleJournal of stem cell and regenerative biology
Gene Editing in Human Pluripotent Stem Cells: Choosing the Correct Path.
Article in Journal of stem cell and regenerative biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Advance trends in targeting homology-directed repair for accurate gene editing: An inclusive review of small molecules and modified CRISPR-Cas9 systems.BioImpacts : BI · 2022Review
- Strategies to Improve the Safety of iPSC-Derived β Cells for β Cell Replacement in Diabetes.Transplant international : official journal of the European Society for Organ Transplantation · 2022Review
- Ways of improving precise knock-in by genome-editing technologies.Human genetics · 2019Review
- Improved bi-allelic modification of a transcriptionally silent locus in patient-derived iPSC by Cas9 nickase.Scientific reports · 2016Article
- Modeling simple repeat expansion diseases with iPSC technology.Cellular and molecular life sciences : CMLS · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The recent emergence of targeted nucleases has opened up new opportunities for performing genetic modifications with human pluripotent stem cells (hPSCs). These modifications can range from the creation of a routine knock-out to the more challenging single point-mutation. For both the new and established user, deciding on the best approach for the specific modification of interest can be an arduous task, as new and improved technologies are rapidly and continuously being developed. The choices between the reagents and methodologies depends entirely on the end-goal of the experiments and the locus to be modified. Investigators need to decide on the best nuclease to use for each experiment from among Zinc-Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 that would result in the highest likelihood of success with the fewest pitfalls. Furthermore, there have been significant improvements over the first-generation nucleases, such as the development of the dimeric CRISPR RNA-guided Fok1 nucleases (RFNs, marketed as NextGEN™ CRISPR) that reduces the "off-target" mutation rate, providing further options for investigators. Should researchers need to perform a point mutation, then considerations must be made between using single-stranded oligo-deoxynucleotides (ssODN) as the donor for homology-directed repair or utilizing a selection cassette within a donor vector in combination with an excision-only piggyBac™ transposase to leave a seamless edit. In this review, we will provide a general overview of the current technologies, along with methodologies for generating point mutations, while considering both their pros and cons.
Indexed as
Identifiers
26702451PMC4686154What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.