Home  ›  Pooled Crispr Screening With Single Cell Transcriptome Read Out

Pooled Crispr Screening With Single Cell Transcriptome Read Out

Written By Thursday, March 10, 2022 Add Comment Edit

. 2017 Mar;14(3):297-301.

doi: x.1038/nmeth.4177. Epub 2017 Jan 18.

Pooled CRISPR screening with single-cell transcriptome readout

Affiliations

  • PMID: 28099430
  • PMCID: PMC5334791
  • DOI: 10.1038/nmeth.4177

Free PMC article

Pooled CRISPR screening with unmarried-cell transcriptome readout

Paul Datlinger  et al. Nat Methods. 2017 Mar .

Free PMC article

Abstract

CRISPR-based genetic screens are accelerating biological discovery, but current methods have inherent limitations. Widely used pooled screens are restricted to simple readouts including cell proliferation and sortable marker proteins. Arrayed screens allow for comprehensive molecular readouts such as transcriptome profiling, but at much lower throughput. Here we combine pooled CRISPR screening with unmarried-prison cell RNA sequencing into a broadly applicable workflow, straight linking guide RNA expression to transcriptome responses in thousands of individual cells. Our method for CRISPR droplet sequencing (CROP-seq) enables pooled CRISPR screens with single-cell transcriptome resolution, which volition facilitate loftier-throughput functional autopsy of circuitous regulatory mechanisms and heterogeneous cell populations.

Conflict of involvement argument

Competing fiscal interests

The authors declare no competing fiscal interests.

Reprints and permissions data is available online at http://www.nature.com/reprints/alphabetize.html.

Figures

Figure 1
Figure ane. CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout

a) Pooled screens discover changes in gRNA abundance amidst bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support circuitous readouts such as transcriptome profiling, but cells transduced with different gRNAs have to exist physically separated. c) CROP-seq uses droplet-based unmarried-cell RNA-seq to contour each cell's transcriptome together with the expressed gRNA, and knockout signatures are derived by averaging across cells that express gRNAs for the same target gene. d) Data analysis identifies pathway signature genes and quantifies the result of specific gRNAs on these signatures. eastward) The CROP-seq lentiviral construct includes a gRNA cassette within the 3' long last repeat (LTR), which is duplicated during viral integration. Information technology expresses an RNA polymerase Three transcript for genome editing and a polyadenylated RNA polymerase 2 transcript detected by single-prison cell RNA-seq. f) Cloning the hU6-gRNA cassette into the 3' LTR to generate CROPseq-Guide-Puro does not compromise lentiviral function for gRNAs. In contrast, 1,885 bp of filler Dna result in a 98-fold reduction of the viral titer. g) Genome editing efficiencies and indel signatures are highly similar between LentiGuide-Puro and CROPseq-Guide-Puro. h) CROP-seq can detect gRNAs from single-prison cell transcriptomes. i) The rate of successful gRNA assignments is associated with single-cell transcriptome quality, expressed as the number of detected genes per cell. Most cells were assigned to one gRNA, except for a small fraction of cell doublets. Error confined, 95% CI. j) Performance statistics across all Ingather-seq experiments.

Figure 2
Effigy 2. CROP-seq analysis of T cell receptor signaling

a) Experimental design of a single-cell CRISPR screen for T cell receptor (TCR) pathway induction. b) Fold change of gRNA abundance between cell assignments from CROP-seq and gRNA counts from plasmid library sequencing. Values were normalized to the total of assigned cells or reads, respectively. c) Inference of pathway signature from Crop-seq data. Single-cell transcriptomes were aggregated by gRNA target genes, and principal component assay separated naive and anti-CD3/CD28-stimulated cells. Genes with absolute loading values for main component 1 that exceeded the 99th percentile were included in the TCR induction signature (due north = 165). The signature was enriched for genes with a known function in TCR signaling (inset). d) Median relative expression (column z-score) beyond the 165 pathway signature genes (columns), accumulation cells that limited gRNAs targeting the same cistron (rows). e) Distribution of signature intensity across single cells (left) and number of cells (right) for each gRNA target gene. The median is indicated with a white dot. f) Cistron signature concordance between Ingather-seq and bulk RNA-seq in an arrayed validation screen. Known positive and negative regulators of the TCR pathway are highlighted. k) Concordance of the CD69 marker of TCR induction between Ingather-seq and an arrayed validation screen with flow cytometry readout. h) Changes in TCR pathway induction detected past Crop-seq mapped onto a schematic of the T-cell receptor with key downstream regulators. i) CD69 marker levels in control cells and knockouts for important TCR activators or repressors. j) Robustness of Ingather-seq signatures in a downsampling assay at the gene and gRNA levels, evaluated against majority RNA-seq data.

Annotate in

  • Genetic screening enters the unmarried-cell era.

    Wagner DE, Klein AM. Wagner DE, et al. Nat Methods. 2017 Feb 28;fourteen(3):237-238. doi: 10.1038/nmeth.4196. Nat Methods. 2017. PMID: 28245215 No abstract bachelor.

  • Single-minded CRISPR screening.

    Lanning BR, Vakoc CR. Lanning BR, et al. Nat Biotechnol. 2017 Apr eleven;35(four):339-340. doi: 10.1038/nbt.3849. Nat Biotechnol. 2017. PMID: 28398325 No abstract bachelor.

Like articles

  • Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells.

    Mimitou EP, Cheng A, Montalbano A, Hao S, Stoeckius G, Legut Chiliad, Roush T, Herrera A, Papalexi Due east, Ouyang Z, Satija R, Sanjana NE, Koralov SB, Smibert P. Mimitou EP, et al. Nat Methods. 2019 May;16(v):409-412. doi: 10.1038/s41592-019-0392-0. Epub 2019 April 22. Nat Methods. 2019. PMID: 31011186 Gratis PMC article.

  • Model-based understanding of single-cell CRISPR screening.

    Duan B, Zhou C, Zhu C, Yu Y, Li M, Zhang S, Zhang C, Ye Ten, Ma H, Qu S, Zhang Z, Wang P, Sun S, Liu Q. Duan B, et al. Nat Commun. 2019 May 20;10(1):2233. doi: 10.1038/s41467-019-10216-x. Nat Commun. 2019. PMID: 31110232 Gratuitous PMC article.

  • Ultra-loftier-throughput unmarried-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing.

    Datlinger P, Rendeiro AF, Boenke T, Senekowitsch M, Krausgruber T, Barreca D, Bock C. Datlinger P, et al. Nat Methods. 2021 Jun;18(6):635-642. doi: ten.1038/s41592-021-01153-z. Epub 2021 May 31. Nat Methods. 2021. PMID: 34059827 Free PMC article.

  • In Silico Meets In Vivo: Towards Computational CRISPR-Based sgRNA Design.

    Chuai GH, Wang QL, Liu Q. Chuai GH, et al. Trends Biotechnol. 2017 January;35(one):12-21. doi: x.1016/j.tibtech.2016.06.008. Epub 2016 Jul 11. Trends Biotechnol. 2017. PMID: 27418421 Review.

  • Current and Futurity Methods for mRNA Assay: A Drive Toward Single Molecule Sequencing.

    Bayega A, Fahiminiya S, Oikonomopoulos Due south, Ragoussis J. Bayega A, et al. Methods Mol Biol. 2018;1783:209-241. doi: 10.1007/978-ane-4939-7834-2_11. Methods Mol Biol. 2018. PMID: 29767365 Review.

Cited by 225 articles

  • Multi-Omics Profiling of the Tumor Microenvironment.

    Van Oekelen O, Laganà A. Van Oekelen O, et al. Adv Exp Med Biol. 2022;1361:283-326. doi: x.1007/978-3-030-91836-1_16. Adv Exp Med Biol. 2022. PMID: 35230695

  • CRISPR in cancer biology and therapy.

    Katti A, Diaz BJ, Caragine CM, Sanjana NE, Dow LE. Katti A, et al. Nat Rev Cancer. 2022 Feb 22. doi: ten.1038/s41568-022-00441-west. Online ahead of print. Nat Rev Cancer. 2022. PMID: 35194172 Review.

  • Electric current applications and future perspective of CRISPR/Cas9 gene editing in cancer.

    Wang SW, Gao C, Zheng YM, Yi Fifty, Lu JC, Huang XY, Cai JB, Zhang PF, Cui YH, Ke AW. Wang SW, et al. Mol Cancer. 2022 Feb 21;21(1):57. doi: x.1186/s12943-022-01518-8. Mol Cancer. 2022. PMID: 35189910 Complimentary PMC commodity. Review.

  • Base of operations editing sensor libraries for high-throughput applied science and functional assay of cancer-associated single nucleotide variants.

    Sánchez-Rivera FJ, Diaz BJ, Kastenhuber ER, Schmidt H, Katti A, Kennedy 1000, Tem V, Ho YJ, Leibold J, Paffenholz SV, Barriga FM, Chu K, Goswami S, Wuest AN, Simon JM, Tsanov KM, Chakravarty D, Zhang H, Leslie CS, Lowe SW, Dow LE. Sánchez-Rivera FJ, et al. Nat Biotechnol. 2022 Feb 14. doi: 10.1038/s41587-021-01172-3. Online ahead of print. Nat Biotechnol. 2022. PMID: 35165384

  • CRISPR Approaches for the Diagnosis of Human Diseases.

    Puig-Serra P, Casado-Rosas MC, Martinez-Lage Thou, Olalla-Sastre B, Alonso-Yanez A, Torres-Ruiz R, Rodriguez-Perales S. Puig-Serra P, et al. Int J Mol Sci. 2022 Feb three;23(3):1757. doi: 10.3390/ijms23031757. Int J Mol Sci. 2022. PMID: 35163678 Free PMC commodity. Review.

References

    1. Blomen VA, et al. Gene essentiality and synthetic lethality in haploid human cells. Science. 2015;350:1092–1096. - PubMed
    1. Wang T, et al. Identification and characterization of essential genes in the human genome. Scientific discipline. 2015;350:1096–1101. - PMC - PubMed
    1. Shalem O, et al. Genome-calibration CRISPR-Cas9 knockout screening in human cells. Science. 2014;343:84–87. - PMC - PubMed
    1. Marceau CD, et al. Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature. 2016;535:159–163. - PMC - PubMed
    1. Lamb J. The Connectivity Map: a new tool for biomedical research. Nat Rev Cancer. 2007;7:54–60. - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources

  • Total Text Sources

    • Europe PubMed Central
    • Nature Publishing Group
    • PubMed Fundamental

  • Other Literature Sources

    • Faculty Opinions
    • The Lens - Patent Citations
    • scite Smart Citations

  • Enquiry Materials

    • Addgene Non-profit plasmid repository

shiresheary1947.blogspot.com

Source: https://pubmed.ncbi.nlm.nih.gov/28099430/

0 Response to "Pooled Crispr Screening With Single Cell Transcriptome Read Out"

Post a Comment

Subscribe to: Post Comments (Atom)

Iklan Atas Artikel

Iklan Tengah Artikel 1

Iklan Tengah Artikel 2

Iklan Bawah Artikel