Evidence map›Paper›PMID 42664970›Full record

ArticleCell genomics2026

Optimized parameters for CRISPR-Cas9 interference library design.

Smriti Srikanth, Fengyi Zheng, Laura M Drepanos, Spencer T Shah, Eleanor G Kaplan, Daytan Gibson, Grace O Lynch, Allison T Uebele, Ganna Reint, Sarra Merzouk and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Smriti SrikanthGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Fengyi ZhengGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Laura M DrepanosGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Spencer T ShahGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Eleanor G KaplanGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Daytan GibsonGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Grace O LynchGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Allison T UebeleGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Ganna ReintGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Sarra MerzoukGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
John G DoenchGenetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address: jdoench@broadinstitute.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CRISPR interference (CRISPRi) is a powerful technology for studying loss-of-function phenotypes, enabling transient and reversible control of gene expression without the introduction of double-stranded DNA breaks. The cost of conducting large-scale CRISPR screens necessitates the selection of effective and specific single-guide RNAs for the design of compact libraries. While several genome-wide CRISPRi-Cas9 libraries have been created, updates to transcript annotations, the generation of higher-resolution chromatin accessibility datasets, and the development of newer on-target prediction models motivate an updated CRISPRi library design approach. Here, we generate large CRISPRi datasets tiling essential and nonessential genes. We compare the performance of multiple KRAB domain systems, develop an updated CRISPRi-specific on-target scoring scheme, and quantitatively characterize off-target effects associated with seed-sequence patterns. We leverage these findings to design an optimized CRISPRi-Cas9 library, Katsano, and validate its performance with genome-wide viability screens.

Indexed as

CRISPR-Cas SystemsGene LibraryHumansRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas SystemsCas9CRISPRifunctional genomicsgenetic screenssgRNA design

Identifiers

PMID42664970
PMCPMC13689501

What OpenQuestion holds

Textmetadata
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.