Evidence map›Paper›PMID 41330380›Full record

ArticleCell genomics2026

A genome-scale single-cell CRISPRi map of trans gene regulation across human pluripotent stem cell lines.

Claudia Feng, Elin Madli Peets, Yan Zhou, Luca Crepaldi, Sunay Usluer, Alistair Dunham, Jana M Braunger, Jing Su, Magdalena E Strauss, Daniele Muraro and 12 more

Abstract read
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. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

22 authors.

Claudia FengWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Elin Madli PeetsWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Yan ZhouWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Luca CrepaldiWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Sunay UsluerWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Alistair DunhamWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Jana M BraungerHeidelberg University, Heidelberg, Germany.
Jing SuWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Magdalena E StraussWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK.
Daniele MuraroWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Kimberly Ai Xian CheamWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Marc Jan BonderDeutsches Krebsforschungszentrum, Heidelberg, Germany.
Edgar Garriga NogalesWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Sarah CooperWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Andrew BassettWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Steven LeonardWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Yong GuWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Bo FussingWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
David BurkeKing's College London, London, UK.
Leopold PartsWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. Electronic address: leopold.parts@sanger.ac.uk.
Oliver StegleWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK; Deutsches Krebsforschungszentrum, Heidelberg, Germany; European Molecular Biology Laboratory, Heidelberg, Germany. Electronic address: oliver.stegle@embl.de.
Britta VeltenWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; Heidelberg University, Heidelberg, Germany. Electronic address: britta.velten@cos.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population-scale resources of genetic, molecular, and cellular information form the basis for understanding human genomes, charting the heritable basis of disease and tracing the effects of mutations. Pooled perturbation assays, probing the effect of many perturbations coupled with single-cell RNA sequencing (scRNA-seq) readout, are especially potent references for interpreting disease-linked mutations or gene-expression changes. However, the utility of existing maps has been limited by the comprehensiveness of perturbations conducted and the relevance of their cell-line context. Here, we present a genome-scale CRISPR interference perturbation map with scRNA-seq readout across many genetic backgrounds in human pluripotent cells. We map trans expression changes induced by knockdowns and characterize their variation across donors, with expression quantitative trait loci linked to higher genetic modulation of perturbation effects. This study pioneers population-scale CRISPR perturbations with high-dimensional readouts, which will fuel the future of effective modulation of cellular disease phenotypes.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsGene Expression RegulationGenome, HumanPluripotent Stem CellsSingle-Cell AnalysisCell LineHumansQuantitative Trait LociCRISPRCRISPRiCROP-seqeQTLgenome-scale Perturb-seqhuman induced pluripotent stem cellsiPSCsPerturb-seqscRNA-seq

Identifiers

PMID41330380
PMCPMC12903452

What Socratic 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 Socratic graph.