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Series GSE92872 Query DataSets for GSE92872
Status Public on Jan 18, 2017
Title Pooled CRISPR screening with single-cell transcriptome read-out
Organisms Homo sapiens; Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary We combined CRISPR genome editing with single-cell RNA sequencing to assess complex phenotypes in pooled cellular screens. Our method for CRISPR droplet sequencing (CROP-seq) comprises four key components: a gRNA vector that makes individual gRNAs detectable in single-cell transcriptomes, a high-throughput assay for single-cell RNA-seq, a computational pipeline for assigning single-cell transcriptomes to gRNAs, and a bioinformatic method for analyzing and interpreting gRNA-induced transcriptional profiles. CROP-seq allowed us to link gRNA expression to the associated transcriptome responses in thousands of single cells using a straightforward and broadly applicable screening workflow. Additional information are available from the CROP-seq website
Overall design Drop-seq species mixing experiment was performed with human HEK293T and mouse 3T3 cells in a 1:1 proportion as described by Macosko et al.

For CROP-seq, Jurkat cells were transduced with a gRNA library targeting high-level regulators of T cell receptor signaling and a set of transcription factors. After 10 days of antibiotic selection and expansion, cells were stimulated with anti-CD3 and anti-CD28 antibodies or left untreated. Both conditions were analyzed using CROP-seq, measuring TCR activation for each gene knockout. Our dataset comprises 5,905 high-quality single-cell transcriptomes with uniquely assigned gRNAs.

All CROP-seq raw data files are multiplexed with single-cell reads. Each read 1 contains the cell barcode (12 bp) and a molecule barcode (8 bp) and read 2 contains the transcriptome read. The libraries are pooled by nature but also intrinsically labelled. The file CROP-seq_Jurkat_TCR.digital_expression.csv.gz contains gene level expression quantifications of each gene for each cell which corresponds to the cell barcode in read1.

For the Drop-seq_HEK293T-3T3 sample (Drop-seq species mixing), reads aligning to two genomes were used to quantify for each cell barcode the amount of reads coming from each genome. In a similar way, in the CROP-seq_HEK293T sample (CROP-seq gRNA mixing), the number of gRNA molecules detected per cell barcode (which is possible due to the polyadenylation of these gRNA-containing transcripts when expressed from a Pol2 promoter as engineered) were counted.
Web link
Contributor(s) Datlinger P, Rendeiro AF, Schmidl C, Krausgruber T, Traxler P, Klughammer J, Schuster LC, Kuchler A, Alpar D, Bock C
Citation(s) 28099430
Submission date Dec 23, 2016
Last update date May 15, 2019
Contact name Christoph Bock
Organization name CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Street address Lazarettgasse 14
City Vienna
ZIP/Postal code 1090
Country Austria
Platforms (3)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
GPL19969 Illumina MiSeq (Homo sapiens; Mus musculus)
GPL20301 Illumina HiSeq 4000 (Homo sapiens)
Samples (100)
GSM2439080 CROP-seq_Jurkat_TCR_stimulated_run1
GSM2439081 CROP-seq_Jurkat_TCR_stimulated_run2
GSM2439082 CROP-seq_Jurkat_TCR_stimulated_run3
BioProject PRJNA358686
SRA SRP095602

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE92872_CROP-seq_Jurkat_TCR.count_matrix.csv.gz 1.5 Mb (ftp)(http) CSV
GSE92872_CROP-seq_Jurkat_TCR.digital_expression.csv.gz 17.3 Mb (ftp)(http) CSV
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Raw data are available in SRA
Processed data are available on Series record

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