human knockout crispr v1 library Search Results


99
InvivoGen ht1080 egfp reporter cells
Gammaretrovirus-based Gag.MS2 chimera for CRISPR-Cas9 delivery (A) Design of the gammaretroviral Gag.MS2 (g.Gag.MS2) variant and non-retroviral SpCas9.TS and sgRNA.TS expression plasmids. The configuration of structural Gag and enzymatic Pol proteins within gammaretroviral wt Gag-Pol (wt g.Gag-Pol) is depicted at the top. It consists of matrix (MA), p12, capsid (CA), nucleocapsid (NC), protease (PR), reverse transcriptase (RT), and integrase (IN) subdomains, which are separated from each other by individual protease sites. In g.Gag.MS2, the MS2CP dimer (2× MS2CP) protein replaces NC while maintaining the natural retroviral protease site (black bold bar). To ensure specific packaging of CRISPR-Cas9 RNA into assembling g.Gag.MS2 particles, two copies of MS2 target site (TS) are incorporated downstream of EGFP within the SpCas9.TS expression plasmid or were placed in (TS.inc) or adjacent (TS.adj) to the sgRNA scaffold in respective sgRNA expression plasmids. Co-expression of EGFP and DsRedexp helped to monitor transfection during particle production. (B) Direct comparison of integrating (g.RIT) and non-integrating g.Gag.MS2 CRISPR.Tet2 particles. Indicated supernatant volumes were used to transduce human <t>HT1080-based</t> RFP657.Tet2 reporter cells. Each data point represents one individually generated supernatant (n = 3). CMV, promoter from cytomegalovirus; hU6, human RNA Pol III U6 promoter; pA, poly(A) signal; PRE, post-transcriptional regulatory element from woodchuck hepatitis virus; SFFV, promoter from spleen focus forming virus.
Ht1080 Egfp Reporter Cells, supplied by InvivoGen, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc bbsi digested px458
Gammaretrovirus-based Gag.MS2 chimera for CRISPR-Cas9 delivery (A) Design of the gammaretroviral Gag.MS2 (g.Gag.MS2) variant and non-retroviral SpCas9.TS and sgRNA.TS expression plasmids. The configuration of structural Gag and enzymatic Pol proteins within gammaretroviral wt Gag-Pol (wt g.Gag-Pol) is depicted at the top. It consists of matrix (MA), p12, capsid (CA), nucleocapsid (NC), protease (PR), reverse transcriptase (RT), and integrase (IN) subdomains, which are separated from each other by individual protease sites. In g.Gag.MS2, the MS2CP dimer (2× MS2CP) protein replaces NC while maintaining the natural retroviral protease site (black bold bar). To ensure specific packaging of CRISPR-Cas9 RNA into assembling g.Gag.MS2 particles, two copies of MS2 target site (TS) are incorporated downstream of EGFP within the SpCas9.TS expression plasmid or were placed in (TS.inc) or adjacent (TS.adj) to the sgRNA scaffold in respective sgRNA expression plasmids. Co-expression of EGFP and DsRedexp helped to monitor transfection during particle production. (B) Direct comparison of integrating (g.RIT) and non-integrating g.Gag.MS2 CRISPR.Tet2 particles. Indicated supernatant volumes were used to transduce human <t>HT1080-based</t> RFP657.Tet2 reporter cells. Each data point represents one individually generated supernatant (n = 3). CMV, promoter from cytomegalovirus; hU6, human RNA Pol III U6 promoter; pA, poly(A) signal; PRE, post-transcriptional regulatory element from woodchuck hepatitis virus; SFFV, promoter from spleen focus forming virus.
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Addgene inc genome wide crispr knockout screen
Figure 1. Genome-wide <t>CRISPR</t> screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.
Genome Wide Crispr Knockout Screen, supplied by Addgene inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc mouse gecko v2 library
Figure 1. Genome-wide <t>CRISPR</t> screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.
Mouse Gecko V2 Library, supplied by Addgene inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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OriGene human nat1 gene knockout crispr/cas9 kit kn221042
Figure 1. Genome-wide <t>CRISPR</t> screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.
Human Nat1 Gene Knockout Crispr/Cas9 Kit Kn221042, supplied by OriGene, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc human geckov2 crispr knockout pooled library
Figure 1. Genome-wide <t>CRISPR</t> screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.
Human Geckov2 Crispr Knockout Pooled Library, supplied by Addgene inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc human brunello crispr knockout pooled library
a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
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Addgene inc crispr cas9 knockout
a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
Crispr Cas9 Knockout, supplied by Addgene inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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OriGene kn204066
a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
Kn204066, supplied by OriGene, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc mouse crispr knockout library
a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
Mouse Crispr Knockout Library, supplied by Addgene inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Addgene inc envelope plasmid pcmv vsv g
a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
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a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional <t>CRISPR</t> features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.
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Image Search Results


Gammaretrovirus-based Gag.MS2 chimera for CRISPR-Cas9 delivery (A) Design of the gammaretroviral Gag.MS2 (g.Gag.MS2) variant and non-retroviral SpCas9.TS and sgRNA.TS expression plasmids. The configuration of structural Gag and enzymatic Pol proteins within gammaretroviral wt Gag-Pol (wt g.Gag-Pol) is depicted at the top. It consists of matrix (MA), p12, capsid (CA), nucleocapsid (NC), protease (PR), reverse transcriptase (RT), and integrase (IN) subdomains, which are separated from each other by individual protease sites. In g.Gag.MS2, the MS2CP dimer (2× MS2CP) protein replaces NC while maintaining the natural retroviral protease site (black bold bar). To ensure specific packaging of CRISPR-Cas9 RNA into assembling g.Gag.MS2 particles, two copies of MS2 target site (TS) are incorporated downstream of EGFP within the SpCas9.TS expression plasmid or were placed in (TS.inc) or adjacent (TS.adj) to the sgRNA scaffold in respective sgRNA expression plasmids. Co-expression of EGFP and DsRedexp helped to monitor transfection during particle production. (B) Direct comparison of integrating (g.RIT) and non-integrating g.Gag.MS2 CRISPR.Tet2 particles. Indicated supernatant volumes were used to transduce human HT1080-based RFP657.Tet2 reporter cells. Each data point represents one individually generated supernatant (n = 3). CMV, promoter from cytomegalovirus; hU6, human RNA Pol III U6 promoter; pA, poly(A) signal; PRE, post-transcriptional regulatory element from woodchuck hepatitis virus; SFFV, promoter from spleen focus forming virus.

Journal: Molecular Therapy. Nucleic Acids

Article Title: Improved alpharetrovirus-based Gag.MS2 particles for efficient and transient delivery of CRISPR-Cas9 into target cells

doi: 10.1016/j.omtn.2021.12.033

Figure Lengend Snippet: Gammaretrovirus-based Gag.MS2 chimera for CRISPR-Cas9 delivery (A) Design of the gammaretroviral Gag.MS2 (g.Gag.MS2) variant and non-retroviral SpCas9.TS and sgRNA.TS expression plasmids. The configuration of structural Gag and enzymatic Pol proteins within gammaretroviral wt Gag-Pol (wt g.Gag-Pol) is depicted at the top. It consists of matrix (MA), p12, capsid (CA), nucleocapsid (NC), protease (PR), reverse transcriptase (RT), and integrase (IN) subdomains, which are separated from each other by individual protease sites. In g.Gag.MS2, the MS2CP dimer (2× MS2CP) protein replaces NC while maintaining the natural retroviral protease site (black bold bar). To ensure specific packaging of CRISPR-Cas9 RNA into assembling g.Gag.MS2 particles, two copies of MS2 target site (TS) are incorporated downstream of EGFP within the SpCas9.TS expression plasmid or were placed in (TS.inc) or adjacent (TS.adj) to the sgRNA scaffold in respective sgRNA expression plasmids. Co-expression of EGFP and DsRedexp helped to monitor transfection during particle production. (B) Direct comparison of integrating (g.RIT) and non-integrating g.Gag.MS2 CRISPR.Tet2 particles. Indicated supernatant volumes were used to transduce human HT1080-based RFP657.Tet2 reporter cells. Each data point represents one individually generated supernatant (n = 3). CMV, promoter from cytomegalovirus; hU6, human RNA Pol III U6 promoter; pA, poly(A) signal; PRE, post-transcriptional regulatory element from woodchuck hepatitis virus; SFFV, promoter from spleen focus forming virus.

Article Snippet: HT1080 RFP657.Tet2 and HT1080 EGFP reporter cells were additionally cultured in the presence of 1 μg/mL puromycin (InvivoGen, Toulouse, France).

Techniques: CRISPR, Variant Assay, Retroviral, Expressing, Reverse Transcription, Plasmid Preparation, Transfection, Comparison, Transduction, Generated, Virus

Alpharetrovirus-based Gag.MS2 particles showed improved delivery of CRISPR-Cas9 components into target cells (A) Design of alpharetroviral Gag.MS2 (a.Gag.MS2) variants. The wt alpharetroviral Gag-Pol polyprotein (wt a.Gag-Pol) is shown at the top of the figure panel. In contrast to g.Gag-Pol, alpharetroviral PR is part of the Gag open reading frame (ORF) (and not Pol ORF). In the depicted a.Gag.MS2 variant, the MS2CP dimer was separated from NC by the naturally occuring viral protease site (black bold bar). (B) a.Gag.MS2.CRISPR.Tet2 particles containing the Tet2.TS.inc sgRNA variant depict higher knockout rates compared with their Tet2.TS.adj counterparts. Indicated volumes of supernatants were used to transduce HT1080-based RFP657.Tet2 reporter cells. The graph depicts RFP657.Tet2 knockout rates mediated by three independent supernatants (n = 3). (C) a.Gag.MS2.CRISPR.Tet2 particles are superior to their gammaretroviral counterparts. Direct comparison of three individually produced a.Gag.MS2- and g.Gag.MS2-based CRISPR.Tet2 supernatants in HT1080-based RFP657.Tet2 reporter cells is shown (n = 3). (D) a.Gag.MS2.CRISPR.Tet2 particles mediate efficient targeted gene knockout in hiPSCs. hiPSC-based RFP657.Tet2 reporter cells were transduced with indicated volumes of three different batches of g.Gag.MS2.CRISPR.Tet2 or a.Gag.MS2.CRISPR.Tet2 supernatants (n = 3). A LIT.CRISPR.Tet2 supernatant applied at MOI 2 (2.9 μL) or MOI 5 (7.4 μL) served as a positive control (n = 1).

Journal: Molecular Therapy. Nucleic Acids

Article Title: Improved alpharetrovirus-based Gag.MS2 particles for efficient and transient delivery of CRISPR-Cas9 into target cells

doi: 10.1016/j.omtn.2021.12.033

Figure Lengend Snippet: Alpharetrovirus-based Gag.MS2 particles showed improved delivery of CRISPR-Cas9 components into target cells (A) Design of alpharetroviral Gag.MS2 (a.Gag.MS2) variants. The wt alpharetroviral Gag-Pol polyprotein (wt a.Gag-Pol) is shown at the top of the figure panel. In contrast to g.Gag-Pol, alpharetroviral PR is part of the Gag open reading frame (ORF) (and not Pol ORF). In the depicted a.Gag.MS2 variant, the MS2CP dimer was separated from NC by the naturally occuring viral protease site (black bold bar). (B) a.Gag.MS2.CRISPR.Tet2 particles containing the Tet2.TS.inc sgRNA variant depict higher knockout rates compared with their Tet2.TS.adj counterparts. Indicated volumes of supernatants were used to transduce HT1080-based RFP657.Tet2 reporter cells. The graph depicts RFP657.Tet2 knockout rates mediated by three independent supernatants (n = 3). (C) a.Gag.MS2.CRISPR.Tet2 particles are superior to their gammaretroviral counterparts. Direct comparison of three individually produced a.Gag.MS2- and g.Gag.MS2-based CRISPR.Tet2 supernatants in HT1080-based RFP657.Tet2 reporter cells is shown (n = 3). (D) a.Gag.MS2.CRISPR.Tet2 particles mediate efficient targeted gene knockout in hiPSCs. hiPSC-based RFP657.Tet2 reporter cells were transduced with indicated volumes of three different batches of g.Gag.MS2.CRISPR.Tet2 or a.Gag.MS2.CRISPR.Tet2 supernatants (n = 3). A LIT.CRISPR.Tet2 supernatant applied at MOI 2 (2.9 μL) or MOI 5 (7.4 μL) served as a positive control (n = 1).

Article Snippet: HT1080 RFP657.Tet2 and HT1080 EGFP reporter cells were additionally cultured in the presence of 1 μg/mL puromycin (InvivoGen, Toulouse, France).

Techniques: CRISPR, Variant Assay, Knock-Out, Transduction, Comparison, Produced, Gene Knockout, Positive Control

Characterization of alpha- and gammaretroviral Gag.MS2.CRISPR.Tet2 supernatants In total, two different batches (white and black filled circles), each with three individually packaged supernatants for a.Gag.MS2 and g.Gag.MS2 CRISPR.Tet2 particles, were generated and characterized for their content of CRISPR-Cas9 components (n = 6). (A) SpCas9.TS mRNA and sgRNA.TS content in a.Gag.MS2- and g.Gag.MS2-based CRISPR.Tet2 supernatants. Total RNA copies per microliter supernatant were calculated using individual plasmid standards. (B) Gag.MS2.CRISPR.Tet2 supernatants contain SpCas9 protein. SpCas9 protein concentrations were assessed by an SpCas9 ELISA. (C) a.Gag.MS2.CRISPR.Tet2 supernatants had a higher Gag.MS2 precursor protein content. Immunoblot analysis of three individually packaged a.Gag.MS2.CRISPR.Tet2 and g.Gag.MS2.CRISPR.Tet2 supernatants is shown (batch 2; black filled circles) (n = 3). g.Gag.MS2 (82 kDa) and a.Gag.MS2 (89 kDa) precursor proteins were detected with an anti-MS2 antibody. Ponceau S staining of the membrane is shown below. (D) g.Gag.MS2.CRISPR.Tet2-mediated RFP657.Tet2 knockout rates can be adjusted by ∼10-fold higher supernatant volumes. Characterized supernatants from batch 2 were used to transduce HT1080 RFP657.Tet2 reporter cells at the depicted volumes (n = 3). (E) Normalization of supernatant volumes showed an ∼2-fold-higher potency for a.Gag.MS2-based CRISPR.Tet2 particles. The in (D) acquired datasets were replotted as % RFP657.Tet2 knockout against applied SpCas9.TS mRNA copies/cell (n = 3; mean values are depicted).

Journal: Molecular Therapy. Nucleic Acids

Article Title: Improved alpharetrovirus-based Gag.MS2 particles for efficient and transient delivery of CRISPR-Cas9 into target cells

doi: 10.1016/j.omtn.2021.12.033

Figure Lengend Snippet: Characterization of alpha- and gammaretroviral Gag.MS2.CRISPR.Tet2 supernatants In total, two different batches (white and black filled circles), each with three individually packaged supernatants for a.Gag.MS2 and g.Gag.MS2 CRISPR.Tet2 particles, were generated and characterized for their content of CRISPR-Cas9 components (n = 6). (A) SpCas9.TS mRNA and sgRNA.TS content in a.Gag.MS2- and g.Gag.MS2-based CRISPR.Tet2 supernatants. Total RNA copies per microliter supernatant were calculated using individual plasmid standards. (B) Gag.MS2.CRISPR.Tet2 supernatants contain SpCas9 protein. SpCas9 protein concentrations were assessed by an SpCas9 ELISA. (C) a.Gag.MS2.CRISPR.Tet2 supernatants had a higher Gag.MS2 precursor protein content. Immunoblot analysis of three individually packaged a.Gag.MS2.CRISPR.Tet2 and g.Gag.MS2.CRISPR.Tet2 supernatants is shown (batch 2; black filled circles) (n = 3). g.Gag.MS2 (82 kDa) and a.Gag.MS2 (89 kDa) precursor proteins were detected with an anti-MS2 antibody. Ponceau S staining of the membrane is shown below. (D) g.Gag.MS2.CRISPR.Tet2-mediated RFP657.Tet2 knockout rates can be adjusted by ∼10-fold higher supernatant volumes. Characterized supernatants from batch 2 were used to transduce HT1080 RFP657.Tet2 reporter cells at the depicted volumes (n = 3). (E) Normalization of supernatant volumes showed an ∼2-fold-higher potency for a.Gag.MS2-based CRISPR.Tet2 particles. The in (D) acquired datasets were replotted as % RFP657.Tet2 knockout against applied SpCas9.TS mRNA copies/cell (n = 3; mean values are depicted).

Article Snippet: HT1080 RFP657.Tet2 and HT1080 EGFP reporter cells were additionally cultured in the presence of 1 μg/mL puromycin (InvivoGen, Toulouse, France).

Techniques: CRISPR, Generated, Plasmid Preparation, Enzyme-linked Immunosorbent Assay, Western Blot, Staining, Membrane, Knock-Out, Transduction

Efficient CRISPR-mediated transition of EGFP to EBFP by a.Gag.MS2.CRISPR.HDR particles (A) Determined copies of CRISPR RNA and PT-modified ssODN molecules within a.Gag.MS2.CRISPR.HDR supernatants. (B and C) HT1080-based (B) or NuFF-based (C) EGFP reporter cells were transduced with 30 μL (1,980 copies SpCas9.TS mRNA/cell) of a.Gag.MS2.CRISPR.HDR supernatants in the absence (w/o) or presence of NHEJ or HDR inhibitors (inh) M3814 or YU238259, respectively. DMSO-treated cells served as solvent controls. The graphs display % EBFP + cells within treated cultures. Non-treated or DMSO-treated mock cultures indicate the degree of autofluorescence in the EBFP channel. Each data point reflects one independently prepared supernatant (n = 3–4).

Journal: Molecular Therapy. Nucleic Acids

Article Title: Improved alpharetrovirus-based Gag.MS2 particles for efficient and transient delivery of CRISPR-Cas9 into target cells

doi: 10.1016/j.omtn.2021.12.033

Figure Lengend Snippet: Efficient CRISPR-mediated transition of EGFP to EBFP by a.Gag.MS2.CRISPR.HDR particles (A) Determined copies of CRISPR RNA and PT-modified ssODN molecules within a.Gag.MS2.CRISPR.HDR supernatants. (B and C) HT1080-based (B) or NuFF-based (C) EGFP reporter cells were transduced with 30 μL (1,980 copies SpCas9.TS mRNA/cell) of a.Gag.MS2.CRISPR.HDR supernatants in the absence (w/o) or presence of NHEJ or HDR inhibitors (inh) M3814 or YU238259, respectively. DMSO-treated cells served as solvent controls. The graphs display % EBFP + cells within treated cultures. Non-treated or DMSO-treated mock cultures indicate the degree of autofluorescence in the EBFP channel. Each data point reflects one independently prepared supernatant (n = 3–4).

Article Snippet: HT1080 RFP657.Tet2 and HT1080 EGFP reporter cells were additionally cultured in the presence of 1 μg/mL puromycin (InvivoGen, Toulouse, France).

Techniques: CRISPR, Modification, Transduction, Solvent

Figure 1. Genome-wide CRISPR screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.

Journal: Molecular cell

Article Title: ZC3H14 facilitates backsplicing by binding to exon-intron boundary and 3' UTR.

doi: 10.1016/j.molcel.2024.10.001

Figure Lengend Snippet: Figure 1. Genome-wide CRISPR screen for regulators of circRNA biogenesis with circReporter cells (A) Illustration of circReporter cell construction. The circGFP minigene included circVN1R1 flanking sequences, inverted split-GFP fragments, and IRES. (B) GFP and mCherry protein levels in circReporter cells treated with siRNA (sicircGFP) against circGFP backsplicing junction (BSJ). siNC, negative control siRNA with scrambled sequences. (C) Procedure of genome-wide CRISPR knockout screen. (D) Overlapped positive and negative regulators identified from GFPhigh and GFPlow cells. (E) GO analysis of 83 overlapped regulators identified from GFPhigh and GFPlow cells. (F) 20 regulators enriched in the RNA-binding GO term.

Article Snippet: Genome-wide CRISPR knockout screen and data analysis The Human CRISPR knockout pooled library (Brunello) was purchased from the Addgene (https://www.addgene.org/).

Techniques: Genome Wide, CRISPR, Negative Control, Knock-Out, RNA Binding Assay

a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional CRISPR features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.

Journal: Nature Communications

Article Title: A pan-CRISPR analysis of mammalian cell specificity identifies ultra-compact sgRNA subsets for genome-scale experiments

doi: 10.1038/s41467-022-28045-w

Figure Lengend Snippet: a Schematic illustrating difference between classic synthetic lethality and our common genetic architecture . Synthetic lethality consists of many individual Y i functions. These functions are cell-type-specific models with single features. Our proposed common genetic architecture is hypothesized to connect these “private” functions with shared CERES features. A common genetic architecture has many redundant edges, and more interconnected nodes. More nodes suggest that more cell-type-specific phenotypes are predictable, and more edges suggest redundancy. b A network built from the aggregation of all multivariate models. Genes are represented as nodes and feature-target gene relations as edges. Colors represent distinct subnetwork communities that were identified by the Louvain method. c Network communities with (right) and without (left) nodes/edges involving functional CRISPR features for a single Louvain community, and a comparison with our hypothesis from ( a ). Edges are colored based upon the data source; and nodes are colored based on the model score (of top ten feature model) of the corresponding gene as target. d To quantitate the visual similarity between our hypothesis in ( a ) and the data in ( c ) across all Louvain communities, we examined the differences in the clustering coefficient, the average number of neighbors, and the network heterogeneity. e gprofiler2 plots examine the enrichment of functional categories. f Residual plot identifies GO terms that are more (residuals of −log10 P values >10) or less (residuals of -log10 P values < −10) enriched in predictor genes than in target genes. Dots represent shared GO terms among the 100 most significant terms in target and predictor gprofiler2 analysis result. The p- values from gprofiler2 for ( e ) and ( f ) are based on hypergeometric tests with multiple testing corrections using the g:SCS method. Source data are provided as a Source Data file.

Article Snippet: Human Brunello CRISPR knockout pooled library was a gift from David Root and John Doench (Addgene #73178).

Techniques: Functional Assay, CRISPR, Comparison

a Two separate pooled screens were performed in a cell line (PC9) that was not included in model training and validation. Experiment 1 was the full Brunello library. A 21-day dropout experiment was performed in PC9 cells. Measurements on 18,114 genes were direct and form the gold standard. The L200 can be computationally extracted from the full screen and compared to these gold-standard measurements. A new L200 standalone library of 800 guides targeting 200 genes was cloned. This library can be used to perform a small-scale lossy compression experiment. The data can then be compared to the gold standard. b Correlations of inferred vs measured CERES scores for both screens in ( a ) and a comparison of the predictions between the standalone sets and the computationally extracted L200 set in the Brunello library. c A Venn diagram describes the overlap in “Hits” in the 500 most differentially required genes for growth in PC9 cells. Both of the lossy compression screens from ( a ) and the gold-standard (measured) data are compared. Source data are provided as a Source Data file.

Journal: Nature Communications

Article Title: A pan-CRISPR analysis of mammalian cell specificity identifies ultra-compact sgRNA subsets for genome-scale experiments

doi: 10.1038/s41467-022-28045-w

Figure Lengend Snippet: a Two separate pooled screens were performed in a cell line (PC9) that was not included in model training and validation. Experiment 1 was the full Brunello library. A 21-day dropout experiment was performed in PC9 cells. Measurements on 18,114 genes were direct and form the gold standard. The L200 can be computationally extracted from the full screen and compared to these gold-standard measurements. A new L200 standalone library of 800 guides targeting 200 genes was cloned. This library can be used to perform a small-scale lossy compression experiment. The data can then be compared to the gold standard. b Correlations of inferred vs measured CERES scores for both screens in ( a ) and a comparison of the predictions between the standalone sets and the computationally extracted L200 set in the Brunello library. c A Venn diagram describes the overlap in “Hits” in the 500 most differentially required genes for growth in PC9 cells. Both of the lossy compression screens from ( a ) and the gold-standard (measured) data are compared. Source data are provided as a Source Data file.

Article Snippet: Human Brunello CRISPR knockout pooled library was a gift from David Root and John Doench (Addgene #73178).

Techniques: Biomarker Discovery, Clone Assay, Comparison