Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Schematics of CRISPRi transcription repressor domains and general lentiviral expression construct used for all CRISPRi effectors. UCOE = ubiquitous chromatin opening element; SFFV = spleen focus-forming virus promoter; P2A = ribosomal skipping sequence; WPRE = woodchuck hepatitis virus post-transcriptional regulatory element. Further information on repressor domains and lentiviral expression constructs can be found in the main text and Materials and methods. ( B ) Experimental design to test effects of stable expression of each CRISPRi effector on growth and transcription in K562 cells. ( C ) Growth defects of effector-expressing cells, measured as the log 2 of the ratio of mCherry-negative (effector-expressing) to mCherry-positive (not effector-expressing) cells in each well normalized to the same ratio on day 0. mCherry levels were measured for 19 days after pooling cells. Data represent mean ± SD from three independent transductions of expression constructs. p-Values are from an unpaired two-tailed t-test comparing D19 values for each sample to the D19 value for the ‘no plasmid’ sample. Average percent growth defect per day is the log 2 D19 value divided by the number of days, multiplied by 100 for a percent value. ( D ) Clustered heatmap of correlation of transcript counts from K562 cells expressing indicated CRISPRi effectors or a GFP control. Correlations across samples were calculated using normalized counts (reads per million) for all genes with mean normalized count >1 and then clustered using the Ward variance minimization algorithm implemented in scipy. r 2 is squared Pearson correlation. Data represent three independent transductions of expression constructs. ( E ) Number of differentially expressed genes ( p <0.05) for cells expressing each effector versus cells expressing GFP only. p -Values were calculated using a Wald test and corrected for multiple hypothesis testing as implemented in DeSeq2. Figure 2—source data 1. p-Values and growth defects depicted in . Figure 2—source data 2. Data depicted in .

Article Snippet: A modified CROP-seq sgRNA lentiviral expression vector (pJR107) was derived from the parental vector pBA950 ( https://www.addgene.org/122239/ ) by incorporating a GFP fluorescent marker and a UCOE element upstream of the EF1alpha promoter to prevent marker silencing. sgRNA targeting sequences were appended with flanking sequence, BstX1/BlpI overhangs, and PCR adapters.

Techniques: Expressing, Construct, Virus, Sequencing, Two Tailed Test, Plasmid Preparation, Control

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet:

Article Snippet: A modified CROP-seq sgRNA lentiviral expression vector (pJR107) was derived from the parental vector pBA950 ( https://www.addgene.org/122239/ ) by incorporating a GFP fluorescent marker and a UCOE element upstream of the EF1alpha promoter to prevent marker silencing. sgRNA targeting sequences were appended with flanking sequence, BstX1/BlpI overhangs, and PCR adapters.

Techniques: Stable Transfection, Marker, Flow Cytometry, Recombinant, Plasmid Preparation, Sequencing, Expressing, Purification, Amplification, Transfection, Software, Genome Wide

Journal: bioRxiv

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.1101/2022.07.13.499814

Figure Lengend Snippet: a. Schematics of CRISPRi transcription repressor domains and general lentiviral expression construct used for all CRISPRi effectors. b. Experimental design to test effects of stable expression of each CRISPRi effector on growth and transcription in K562 cells. c. Growth defects of effector-expressing cells, measured as the log 2 ratio of mCherry-negative (effector-expressing) to mCherry-positive (not effector-expressing) cells in each well. mCherry levels were measured for 19 days after pooling cells. Data represent mean ± SD from three independent transductions of expression constructs. p -values are from an unpaired two-tailed t-test comparing D19 values for each sample to the D19 value for the “no plasmid” sample. Average percent growth defect per day is the log 2 D19 value divided by the number of days, multiplied by 100 for a percent value. d. Clustered heatmap of correlation of transcript counts from K562 cells expressing indicated CRISPRi effectors or a GFP control. Correlations across samples were calculated using normalized counts (reads per million) for all genes with mean normalized count >1 and then clustered using the Ward variance minimization algorithm implemented in scipy. r 2 is squared Pearson correlation. Data represent three independent transductions of expression constructs. e. Number of differentially expressed genes ( p < 0.05) for cells expressing each effector versus cells expressing GFP only. p -values were calculated using a Wald test and corrected for multiple hypothesis testing as implemented in DeSeq2. See also .

Article Snippet: A modified CROP-seq sgRNA lentiviral expression vector (pJR107) was derived from the parental vector pBA950 ( https://www.addgene.org/122239/ ) by incorporating a GFP fluorescent marker and a UCOE element upstream of the EF1alpha promoter to prevent marker silencing. sgRNA targeting sequences were appended with flanking sequence, BstX1/BlpI overhangs, and PCR adapters.

Techniques: Expressing, Construct, Two Tailed Test, Plasmid Preparation

Journal: bioRxiv

Article Title: crisprQTL mapping as a genome-wide association framework for cellular genetic screens

doi: 10.1101/314344

Figure Lengend Snippet: (A)crisprQTL mapping uses the same framework as human eQTL studies, but with a population of human individuals replaced by a population of individual cells, natural genetic variation replaced by diverse combinations of gRNA-programmed perturbations in each cell, and tissue-level RNA-seq of each person replaced by scRNA-seq. (B) Multiplex perturbations increase power to detect changes in gene expression in single-cell genetic screens while greatly reducing the number of cells necessary to profile. Simulated power calculations show that increasing the average number of perturbations per cell ( e.g. , by increasing MOI in lentiviral delivery of gRNAs) strongly increases power to detect changes in gene expression, including for genes with low (0.10 mean UMIs per cell), medium (0.32) or high (1.00) levels of mean expression. X-axis corresponds to the simulated % change of transcript repressed by targeting CRISPRi to the associated enhancer. Calculations assume a fixed number of 45,000 cells profiled by scRNA-seq.

Article Snippet: The lentiviral CROP-seq gRNA-expression vector ( ) was modified by Q5-Site Directed Mutagenesis (New England BioLabs, F:5-acagcatagcaagtttAAATAAGGCTAGTCCGTTATC-3 R:5-ttccagcatagctcttAAACAGAGACGTACAAAAAAG-3) to incorporate the previously described gRNA-(F+E)-combined backbone optimized for CRISPRi ( )( ).

Techniques: RNA Sequencing Assay, Multiplex Assay, Expressing

Journal: bioRxiv

Article Title: crisprQTL mapping as a genome-wide association framework for cellular genetic screens

doi: 10.1101/314344

Figure Lengend Snippet: (A-E), Schematic of crisprQTL mapping. A, Candidate enhancers were chosen based on enhancer-associated features, and were each targeted by 2 gRNAs. B, gRNAs were cloned into the CRISPRi-optimized CROP-seq lentiviral vector, and delivered to K562 cells at a high MOI. C, scRNA-seq was performed on these cells, with concurrent identification of the combination of gRNAs present in each cell. D, For each candidate enhancer, cells were partitioned based on whether or not they contained a gRNA targeting it. E, For each such partition, we used Monocle to test for differential expression between the two populations for any gene within 1 Mb of the candidate enhancer. (F) Quantile-quantile (Q-Q) plot of the differential expression tests. Distributions of observed vs. expected P -values for candidate enhancer-targeting gRNAs (orange) and NTC gRNAs (gray; downsampled) are shown. (G) Expression of selected TSS and, β -globin LCR positive controls. Positive controls showed significant differential expression of the expected target genes between cells with versus without targeting gRNAs, in contrast with NTCs. (H) Distal enhancers of NMU identified as crisprQTLs. Targeting three candidate enhancers (labeled ii-iv ) located 93.4, 94.1 and 97.6 Kb upstream of NMU , significantly reduced expression of NMU , but targeting an intervening candidate enhancer (labeled i ) located 34.4 Kb upstream did not.

Article Snippet: The lentiviral CROP-seq gRNA-expression vector ( ) was modified by Q5-Site Directed Mutagenesis (New England BioLabs, F:5-acagcatagcaagtttAAATAAGGCTAGTCCGTTATC-3 R:5-ttccagcatagctcttAAACAGAGACGTACAAAAAAG-3) to incorporate the previously described gRNA-(F+E)-combined backbone optimized for CRISPRi ( )( ).

Techniques: Clone Assay, Plasmid Preparation, Expressing, Labeling