Evidence map›Paper›PMID 35865001›Full record

ArticleFrontiers in genome editing2022

Optimizing CRISPR/Cas9 Editing of Repetitive Single Nucleotide Variants.

Inga Usher, Lorena Ligammari, Sara Ahrabi, Emily Hepburn, Calum Connolly, Gareth L Bond, Adrienne M Flanagan, Lucia Cottone

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genome editing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Inga UsherDepartment of Pathology (Research), UCL Cancer Institute, University College London, London, United Kingdom.
Lorena LigammariDepartment of Pathology (Research), UCL Cancer Institute, University College London, London, United Kingdom.
Sara AhrabiDepartment of Haematology, UCL Cancer Institute, University College London, London, United Kingdom.
Emily HepburnUCL Medical School, University College London, London, United Kingdom.
Calum ConnollyUCL Medical School, University College London, London, United Kingdom.
Gareth L BondInstitute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.
Adrienne M FlanaganDepartment of Pathology (Research), UCL Cancer Institute, University College London, London, United Kingdom.
Lucia CottoneDepartment of Pathology (Research), UCL Cancer Institute, University College London, London, United Kingdom.
University College London · GBCRUK Lung Cancer Centre of Excellence · GBINC Research (United Kingdom) · GBUniversity of Birmingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CRISPR/Cas9, base editors and prime editors comprise the contemporary genome editing toolbox. Many studies have optimized the use of CRISPR/Cas9, as the original CRISPR genome editing system, in substituting single nucleotides by homology directed repair (HDR), although this remains challenging. Studies describing modifications that improve editing efficiency fall short of isolating clonal cell lines or have not been validated for challenging loci or cell models. We present data from 95 transfections using a colony forming and an immortalized cell line comparing the effect on editing efficiency of donor template modifications, concentration of components, HDR enhancing agents and cold shock. We found that

Indexed as

cell lineCRISPRCRISPR/Cas9genome editinghomology directed repair (HDR)prime editingstem cells

Identifiers

PMID35865001
PMCPMC9294353
OpenAlexW4283817551

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.