CRISPR-StAR enables high-resolution genetic screening in complex in vivo models

Pooled genetic screening with CRISPR-Cas9 has enabled genome-wide, high-resolution mapping of genes to phenotypes, but assessing the effect of a given genetic perturbation requires evaluation of each single guide RNA (sgRNA) in hundreds of cells to counter stochastic genetic drift and obtain robust results. However, resolution is limited in complex, heterogeneous models, such as organoids or tumors transplanted into mice, because achieving sufficient representation requires impractical scaling. This is due to bottleneck effects and biological heterogeneity of cell populations. Here we introduce CRISPR-StAR, a screening method that uses internal controls generated by activating sgRNAs in only half the progeny of each cell subsequent to re-expansion of the cell clone. Our method overcomes both intrinsic and extrinsic heterogeneity as well as genetic drift in bottlenecks by generating clonal, single-cell-derived intrinsic controls. We use CRISPR-StAR to identify in-vivo-specific genetic dependencies in a genome-wide screen in mouse melanoma. Benchmarking against conventional screening demonstrates the improved data quality provided by this technology.

Authors

Institutions

Publication Details

Journal
Nature Biotechnology
Published
2024-12-16
DOI
https://doi.org/10.1038/s41587-024-02512-9
Citations
18
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
4.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CRISPR-StAR enables high-resolution genetic screening in complex in vivo models

Gintautas Vainorius, Juliane Christina Baar, Anais Elewaut, Maria Novatchkova et al.
18 citations
Nature Biotechnology
CRISPR and Genetic Engineering
4.21
article

CRISPR-StAR enables high-resolution genetic screening in complex in vivo models

Gintautas Vainorius, Juliane Christina Baar, Anais Elewaut, Maria Novatchkova, Esther C. H. Uijttewaal, Daniel Schramek, S. Leij, Ulrich Elling, Annika Charlotte Sell, Christopher Lowden, Joonsun Lee, Jiaye Yang, Anna C. Obenauf, Milanka Gavrilovic, Julia Sinner, Naomi Botay, Tobias Potzler
article en
18 citations

Abstract

Pooled genetic screening with CRISPR-Cas9 has enabled genome-wide, high-resolution mapping of genes to phenotypes, but assessing the effect of a given genetic perturbation requires evaluation of each single guide RNA (sgRNA) in hundreds of cells to counter stochastic genetic drift and obtain robust results. However, resolution is limited in complex, heterogeneous models, such as organoids or tumors transplanted into mice, because achieving sufficient representation requires impractical scaling. This is due to bottleneck effects and biological heterogeneity of cell populations. Here we introduce CRISPR-StAR, a screening method that uses internal controls generated by activating sgRNAs in only half the progeny of each cell subsequent to re-expansion of the cell clone. Our method overcomes both intrinsic and extrinsic heterogeneity as well as genetic drift in bottlenecks by generating clonal, single-cell-derived intrinsic controls. We use CRISPR-StAR to identify in-vivo-specific genetic dependencies in a genome-wide screen in mouse melanoma. Benchmarking against conventional screening demonstrates the improved data quality provided by this technology.

Nature BiotechnologyVol. 43(11)
Institute of Molecular Biotechnology (AT), Mount Sinai Hospital (CA), University of Toronto (CA), Research Institute of Molecular Pathology (AT), Lunenfeld-Tanenbaum Research Institute (CA), Wiener Krankenanstaltenverbund (AT), Vienna Biocenter (AT), Medical University of Vienna (AT)
Canada Research Chairs, Österreichischen Akademie der Wissenschaften, Krembil Foundation, Terry Fox Research Institute, Staatssekretariat für Bildung, Forschung und Innovation
Openalex Percentile: Top 5%
CRISPR and Genetic Engineering
4.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.