A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response

By Britt Adamson, Thomas M. Norman, M. Jost, M. Cho, James K. Nuñez, Yuwen Chen, Jacqueline E. Villalta, Luke A. Gilbert, Max A. Horlbeck, Marco Y. Hein and 7 more. Cell, 2016

1,097 citations recorded by the source corpus.

SUMMARY Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ~100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.

Subfields: Biotechnology, Cardiology and Cardiovascular Medicine, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/119a59578a114c6274fc863d4a3212b0357b365d

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Citations in the corpus

Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain (2018, result): “We found that individual ICs corresponded to recognizable biological phenomena (Figures 1D and S2C–S2H) (Adamson et al., 2016), in contrast to results from principal components analysis (Figure S2A).”
Predicting transcriptional outcomes of novel multigene perturbations with GEARS (2023, neutral): “16 and 17 and Supplementary Note 20).”
Large Scale Foundation Model on Single-cell Transcriptomics (2023, positive): “Using Perturb-seq 51,52 data resources to train models for modeling cellular response to perturbations is a key task of computational biology 53–55 .”
The Human Cell Atlas (2017, neutral): “Finally, there has been progress in scRNA-Seq with RNA isolated from live cells in their natural microenvironment using transcriptome in vivo analysis (Lovatt et al., 2014).”
Massively-parallel single nucleus RNA-seq with DroNc-seq (2017, positive): “In addition, we identified signatures of up-regulated genes for each cluster (Supplementary Tables 4,5,8 and 9), which we used to further validate the identity of the cluster by matching these signatures with canonical cell-type marker genes and by testing for enriched pathways.”
Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens. (2016, methodology): “…Models: Organisms/Strains Cas9 Mouse Platt et al., 2014 Cas9 Mouse Recombinant DNA Perturb-seq vector, pBA439 This paper Addgene: 85967 (Adamson et al., 2016) Perturb-seq vector, pooled cloning, pPS This paper Addgene: 85801 Sequence-Based Reagents Primers for enrichment PCR This paper…”
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications (2017, background): “For instance, the use of CRISPR–Cas9 genome-editing techniques alongside barcoded guide RNA species has allowed high-throughput assessment of gene function in single cells [98, 99].”
Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq (2021, methodology): “124 Although Perturb-seq is compatible with a range of CRISPR-based perturbations including 125 knockout (10–12), knockdown (CRISPRi) (9), or activation (CRISPRa) (20), we elected to use 126 CRISPRi for several reasons.”