Evidence map›Paper›PMID 40011813›Full record

ArticleBMC genomics2025

A benchmark comparison of CRISPRn guide-RNA design algorithms and generation of small single and dual-targeting libraries to boost screening efficiency.

Sebastian Lukasiak, Alex Kalinka, Nikhil Gupta, Angelos Papadopoulos, Khalid Saeed, Ultan McDermott, Gregory James Hannon, Douglas Ross-Thriepland, David Walter

Abstract readComparative Study
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

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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

9 authors.

Sebastian Lukasiak *Joint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Alex Kalinka *Joint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Nikhil GuptaJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Angelos PapadopoulosJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Khalid SaeedJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Ultan McDermottJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Gregory James HannonJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK.
Douglas Ross-ThrieplandJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK. Douglas.Ross-Thriepland@astrazeneca.com.
David WalterJoint Astrazeneca-Cancer Research Horizons Functional Genomics Centre, Cambridge, UK. David.Walter@cancer.org.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide CRISPR sgRNA libraries have emerged as transformative tools to systematically probe gene function. While these libraries have been iterated over time to be more efficient, their large size limits their use in some applications. Here, we benchmarked publicly available genome-wide single-targeting sgRNA libraries and evaluated dual targeting as a strategy for pooled CRISPR loss-of-function screens. We leveraged this data to design two minimal genome-wide human CRISPR-Cas9 libraries that are 50% smaller than other libraries and that preserve specificity and sensitivity, thus enabling broader deployment at scale.

Indexed as

AlgorithmsCRISPR-Cas SystemsGene LibraryRNA, Guide, CRISPR-Cas SystemsBenchmarkingGene EditingHumansRNA, Guide, CRISPR-Cas SystemsCRISPR-Cas9Genome-widePooled CRISPR screeningSgRNA selection algorithm

Identifiers

PMID40011813
PMCPMC11863645

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.