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    New England Biolabs cropseq guide puro
    T4 DNA Ligase Reaction Buffer
    T4 DNA Ligase Reaction Buffer 6 0 ml
    https://www.bioz.com/result/cropseq guide puro/product/New England Biolabs
    Average 92 stars, based on 2607 article reviews
    Price from $9.99 to $1999.99
    cropseq guide puro - by Bioz Stars, 2020-09
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    1) Product Images from "Pooled CRISPR screening with single-cell transcriptome read-out"

    Article Title: Pooled CRISPR screening with single-cell transcriptome read-out

    Journal: Nature methods

    doi: 10.1038/nmeth.4177

    CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.
    Figure Legend Snippet: CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.

    Techniques Used: CRISPR, Transduction, RNA Sequencing Assay, Knock-Out, Derivative Assay, Construct, Clone Assay

    2) Product Images from "Pooled CRISPR screening with single-cell transcriptome read-out"

    Article Title: Pooled CRISPR screening with single-cell transcriptome read-out

    Journal: Nature methods

    doi: 10.1038/nmeth.4177

    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 analysis separated naive and anti-CD3/CD28-stimulated cells. Genes with absolute loading values for principal component 1 that exceeded the 99 th percentile were included in the TCR induction signature (n = 165). The signature was enriched for genes with a known role in TCR signaling (inset). d) Median relative expression (column z-score) across the 165 pathway signature genes (columns), aggregating cells that express gRNAs targeting the same gene (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) Gene signature concordance between CROP-seq and bulk RNA-seq in an arrayed validation screen. Known positive and negative regulators of the TCR pathway are highlighted. g) Concordance of the CD69 marker of TCR induction between CROP-seq and an arrayed validation screen with flow cytometry readout. h) Changes in TCR pathway induction detected by 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 CROP-seq signatures in a downsampling analysis at the gene and gRNA levels, evaluated against bulk RNA-seq data.
    Figure Legend Snippet: 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 analysis separated naive and anti-CD3/CD28-stimulated cells. Genes with absolute loading values for principal component 1 that exceeded the 99 th percentile were included in the TCR induction signature (n = 165). The signature was enriched for genes with a known role in TCR signaling (inset). d) Median relative expression (column z-score) across the 165 pathway signature genes (columns), aggregating cells that express gRNAs targeting the same gene (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) Gene signature concordance between CROP-seq and bulk RNA-seq in an arrayed validation screen. Known positive and negative regulators of the TCR pathway are highlighted. g) Concordance of the CD69 marker of TCR induction between CROP-seq and an arrayed validation screen with flow cytometry readout. h) Changes in TCR pathway induction detected by 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 CROP-seq signatures in a downsampling analysis at the gene and gRNA levels, evaluated against bulk RNA-seq data.

    Techniques Used: CRISPR, Plasmid Preparation, Sequencing, Expressing, RNA Sequencing Assay, Marker, Flow Cytometry, Cytometry

    CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.
    Figure Legend Snippet: CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.

    Techniques Used: CRISPR, Transduction, RNA Sequencing Assay, Knock-Out, Derivative Assay, Construct, Clone Assay

    3) Product Images from "Split mix assembly of DNA libraries for ultrahigh throughput on-bead screening of functional proteins"

    Article Title: Split mix assembly of DNA libraries for ultrahigh throughput on-bead screening of functional proteins

    Journal: Nucleic Acids Research

    doi: 10.1093/nar/gkaa270

    Design of bead surface and solid-phase manipulations of DNA. ( A ) Beads were designed to display both azide (labelled ‘N 3 ’) and SpyTag (labelled ‘ST’) moieties (surface modification described in Supplementary Figure S1 ). ( B ) Flow cytometric analysis of beads for fluorescein-derived fluorescence intensity before (grey) and after (black) immobilisation of fluorescein and DBCO-functionalised DNA (top histogram), after Esp3I treatment (2 hours at 37°C) of the DNA-coated beads (middle histogram) and after exposure of Esp3I-treated beads to a fluorescein-labelled DNA duplex that had a 5′-overhang complementary to the 5′-overhang of bead-immobilised DNA, in T4 DNA ligase buffer, with (black) or without (grey) T4 DNA ligase (bottom histogram). Details of the DNA sequences used for the generation of this panel are set out in Supplementary Figure S4 . ( C ) Schematic overview of on-bead assembly allowing potential saturation of three codons in close proximity. The final, bead-attached DNA assembly is shown at the top of the panel, with the three DNA fragments used in the construction are shown below. Restriction sites are depicted in red, target codons in green and sequences used for hybridisation during ligation in blue. The first, PCR-generated amplicon (frag 3 ) was attached to bead ( via copper-free click chemistry) and digested by Esp3I. DNA on the bead was extended using an oligonucleotide duplex (frag 2 ) carrying a 5′-phosphorylated cohesive end; the sequence used to ensure stability of the duplex (stability stuffer) prior to ligation is indicated in a diagonal pattern. Once this duplex had been appended to the bead by ligation, a new cohesive end was generated (and stability stuffer removed) through BspQI digestion. Finally, another PCR amplicon (frag 1 ), separately prepared with a cohesive end (using BspQI) was ligated to the bead-immobilised DNA. Details of the DNA sequences used for the generation of this panel are set out in Supplementary Figure S5 . ( D ) Flow cytometric analysis of untreated beads (top trace), beads carrying full length starting template (i.e. with FAM at one end and DBCO at the other, middle trace) and beads having gone through the 3-codon SpliMLiB process described in C. ( E ) Sanger sequencing chromatogram (templated by a PCR amplicon obtained directly from beads) of the exemplary bead-surface assembled construct shown in panel C where codons to be mutated were designed to be in close proximity (bottom). As in panel C, the green coloring refers to mutated positions, while the blue coloring refers to sequences used for ligations.
    Figure Legend Snippet: Design of bead surface and solid-phase manipulations of DNA. ( A ) Beads were designed to display both azide (labelled ‘N 3 ’) and SpyTag (labelled ‘ST’) moieties (surface modification described in Supplementary Figure S1 ). ( B ) Flow cytometric analysis of beads for fluorescein-derived fluorescence intensity before (grey) and after (black) immobilisation of fluorescein and DBCO-functionalised DNA (top histogram), after Esp3I treatment (2 hours at 37°C) of the DNA-coated beads (middle histogram) and after exposure of Esp3I-treated beads to a fluorescein-labelled DNA duplex that had a 5′-overhang complementary to the 5′-overhang of bead-immobilised DNA, in T4 DNA ligase buffer, with (black) or without (grey) T4 DNA ligase (bottom histogram). Details of the DNA sequences used for the generation of this panel are set out in Supplementary Figure S4 . ( C ) Schematic overview of on-bead assembly allowing potential saturation of three codons in close proximity. The final, bead-attached DNA assembly is shown at the top of the panel, with the three DNA fragments used in the construction are shown below. Restriction sites are depicted in red, target codons in green and sequences used for hybridisation during ligation in blue. The first, PCR-generated amplicon (frag 3 ) was attached to bead ( via copper-free click chemistry) and digested by Esp3I. DNA on the bead was extended using an oligonucleotide duplex (frag 2 ) carrying a 5′-phosphorylated cohesive end; the sequence used to ensure stability of the duplex (stability stuffer) prior to ligation is indicated in a diagonal pattern. Once this duplex had been appended to the bead by ligation, a new cohesive end was generated (and stability stuffer removed) through BspQI digestion. Finally, another PCR amplicon (frag 1 ), separately prepared with a cohesive end (using BspQI) was ligated to the bead-immobilised DNA. Details of the DNA sequences used for the generation of this panel are set out in Supplementary Figure S5 . ( D ) Flow cytometric analysis of untreated beads (top trace), beads carrying full length starting template (i.e. with FAM at one end and DBCO at the other, middle trace) and beads having gone through the 3-codon SpliMLiB process described in C. ( E ) Sanger sequencing chromatogram (templated by a PCR amplicon obtained directly from beads) of the exemplary bead-surface assembled construct shown in panel C where codons to be mutated were designed to be in close proximity (bottom). As in panel C, the green coloring refers to mutated positions, while the blue coloring refers to sequences used for ligations.

    Techniques Used: Modification, Derivative Assay, Fluorescence, Hybridization, Ligation, Polymerase Chain Reaction, Generated, Amplification, Sequencing, Construct

    4) Product Images from "Pooled CRISPR screening with single-cell transcriptome read-out"

    Article Title: Pooled CRISPR screening with single-cell transcriptome read-out

    Journal: Nature methods

    doi: 10.1038/nmeth.4177

    CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.
    Figure Legend Snippet: CROP-seq enables pooled CRISPR screening with single-cell transcriptome readout a) Pooled screens detect changes in gRNA abundance among bulk populations of cells, which limits them to simple readouts based on cell frequencies. b) Arrayed screens support complex readouts such as transcriptome profiling, but cells transduced with different gRNAs have to be physically separated. c) CROP-seq uses droplet-based single-cell RNA-seq to profile 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 effect of specific gRNAs on these signatures. e) The CROP-seq lentiviral construct includes a gRNA cassette within the 3’ long terminal repeat (LTR), which is duplicated during viral integration. It expresses an RNA polymerase III transcript for genome editing and a polyadenylated RNA polymerase II transcript detected by single-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-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 bars, 95% CI. j) Performance statistics across all CROP-seq experiments.

    Techniques Used: CRISPR, Transduction, RNA Sequencing Assay, Knock-Out, Derivative Assay, Construct, Clone Assay

    5) Product Images from "Phage-delivered CRISPR-Cas9 for strain-specific depletion and genomic deletions in the gut microbiota"

    Article Title: Phage-delivered CRISPR-Cas9 for strain-specific depletion and genomic deletions in the gut microbiota

    Journal: bioRxiv

    doi: 10.1101/2020.07.09.193847

    Flow cytometry on co-cultures at 8 h and 24 h after addition of NT M13 or GFPT M13 shows decreased relative abundance of the GFP strain under targeting conditions. Co-cultures of GFP-marked and mCherry-marked E. coli F+ were infected with phage and carbenicillin was added to select for phage infection. The relative abundance of GFP+ events is decreased in GFPT conditions at 8 h and further decreased by 24 h. Non-targeting phagemids are pCas9-NT-f1A and pCas9-NT-f1B; GFP-targeting phagemids are pCas9-GFPT-f1A and pCas9-GFPT-f1B.
    Figure Legend Snippet: Flow cytometry on co-cultures at 8 h and 24 h after addition of NT M13 or GFPT M13 shows decreased relative abundance of the GFP strain under targeting conditions. Co-cultures of GFP-marked and mCherry-marked E. coli F+ were infected with phage and carbenicillin was added to select for phage infection. The relative abundance of GFP+ events is decreased in GFPT conditions at 8 h and further decreased by 24 h. Non-targeting phagemids are pCas9-NT-f1A and pCas9-NT-f1B; GFP-targeting phagemids are pCas9-GFPT-f1A and pCas9-GFPT-f1B.

    Techniques Used: Flow Cytometry, Infection

    Related Articles

    Amplification:

    Article Title: Tagsteady: a metabarcoding library preparation protocol to avoid false assignment of sequences to samples
    Article Snippet: .. End-repair without T4 DNA Polymerase: for treatments −/+ and −/−, an end-repair mastermix was made by combining 4 μl T4 DNA ligase reaction buffer (New England Biolabs, NEB, Ipswich, Massachusetts, US), 0.5 μl dATP (10mM) (Thermo-Fisher), 2 μl reaction booster mix (consisting of 25 % PEG-4000 (Sigma Aldrich, 50%), 2 mg/ml BSA (Thermo-Fisher) and 400 mM NaCl) , 2 μl T4 PNK (NEB, cat#M0201S, 10 U/μl) and 1.5 μl Klenow Fragment (3’- > 5’ exo-) (NEB, cat#M0212S, 5 U/μl) per amplicon pool reaction. .. Ten μl of this mastermix was then added to each 30 μl amplicon pool, mixed well by pipetting and incubated for 30 minutes at 37°C followed by 30 minutes at 65°C and finally cooled to 4°C.

    Ligation:

    Article Title: Comparative analysis of the end-joining activity of several DNA ligases
    Article Snippet: .. Reactions included 1 μM of the DNA ligase, 100 nM of the substrate and reaction conditions consisting of either T4 DNA ligase reaction buffer (50 mM Tris-HCl pH 7.5 @ 25°C, 1 mM ATP and 10 mM MgCl2 ) or NEBNext® Quick Ligation reaction buffer (66 mM Tris pH 7.6 @ 25°C, 10 mM MgCl2 , 1 mM DTT, 1 mM ATP, 6% Polyethylene glycol (PEG 6000)). (TIF) Click here for additional data file. .. Fluorescence anisotropy DNA binding curves.

    Article Title: Comparative analysis of the end-joining activity of several DNA ligases
    Article Snippet: .. Reactions included 1 μM of the DNA ligase, 100 nM of the substrate and reaction conditions consisting of either T4 DNA ligase reaction buffer + 150 mM NaCl (50 mM Tris-HCl pH 7.5 @ 25°C, 150 mM NaCl, 1 mM ATP and 10 mM MgCl2 ) or NEBNext® Quick Ligation reaction buffer (66 mM Tris pH 7.6 @ 25°C, 10 mM MgCl2 , 1 mM DTT, 150 mM NaCl, 1 mM ATP, 6% Polyethylene glycol (PEG 6000)). ..

    Article Title: Construction and characterization of mismatch-containing circular DNA molecules competent for assessment of nick-directed human mismatch repair in vitro
    Article Snippet: .. A final ligation, which creates the nicked circular substrate, was carried out at a DNA concentration of 10 ng/µl in T4 ligase buffer supplemented with 50 mM NaCl, Eco RI (2 U/µg plasmid), T4 ligase (100 U/µg plasmid) and 100 µg/ml bovine serum albumin. ..

    Purification:

    Article Title: Next-Generation DNA Curtains for Single-Molecule Studies of Homologous Recombination
    Article Snippet: .. TE buffer: 10m M Tris–HCl [pH 8.0]; 0.1m M EDTA RAD51 buffer: 40m M Tris–HCl [pH 8.0]; 1m M MgCl2 ; 5m M CaCl2 ; 100m M KCl; 1m M DTT; 1m M ATP; 0.2 mgmL−1 BSA; 1m M Trolox (Sigma-Aldrich); 1.0% glucose (w/v); 500units catalase (Sigma-Aldrich); 70units glucose oxidase (Sigma-Aldrich) 10× T4 DNA ligase reaction buffer (B0202S; NEB) T4 DNA ligase (M0202; NEB) Primer oligo (/Biosg/TC TCC TCC TTC T—HPLC purified; Integrated DNA Technologies) Template oligo (/5Phos/AG GAG AAA AAG AAA AAA AGA AAA GAA GG—PAGE purified; Integrated DNA Technologies) Nuclease-free water BSA, Molecular Biology Grade (B9000S; NEB) Thermocycler (Mastercycler pro S; Eppendorf ) 10× phi29 DNA polymerase reaction buffer (B0269S; NEB) phi29 DNA polymerase (homemade 5 μ M stock) Deoxynucleotide (dNTP) solution set (N0446S; NEB) .. Prepare a 49 μL ligation reaction containing: (i) 5 μL 10× T4 ligase reaction buffer; (ii) 2 μL template oligo (10 μ M stock in TE buffer); (iii) 1.8 μL primer oligo (10 μ M stock in TE buffer); and (iv) 40.2 μL nuclease-free water.

    Concentration Assay:

    Article Title: Construction and characterization of mismatch-containing circular DNA molecules competent for assessment of nick-directed human mismatch repair in vitro
    Article Snippet: .. A final ligation, which creates the nicked circular substrate, was carried out at a DNA concentration of 10 ng/µl in T4 ligase buffer supplemented with 50 mM NaCl, Eco RI (2 U/µg plasmid), T4 ligase (100 U/µg plasmid) and 100 µg/ml bovine serum albumin. ..

    Incubation:

    Article Title: Construction and characterization of mismatch-containing circular DNA molecules competent for assessment of nick-directed human mismatch repair in vitro
    Article Snippet: .. The reaction was incubated for 10 min at 37°C in T4 ligase buffer (New England Biolabs) containing 100 µg/ml bovine serum albumin, 75 mM KCl and the heteroduplex oligo recovered after Dpn II digestion (estimated to be a ∼100-fold molar excess over the plasmid ends). .. The reaction was then cooled on ice, whereupon 100 cohesive end ligation units of T4 ligase per microgram of plasmid (1500 U in this example) were added and the reaction incubated at 16°C overnight.

    Plasmid Preparation:

    Article Title: Construction and characterization of mismatch-containing circular DNA molecules competent for assessment of nick-directed human mismatch repair in vitro
    Article Snippet: .. A final ligation, which creates the nicked circular substrate, was carried out at a DNA concentration of 10 ng/µl in T4 ligase buffer supplemented with 50 mM NaCl, Eco RI (2 U/µg plasmid), T4 ligase (100 U/µg plasmid) and 100 µg/ml bovine serum albumin. ..

    Article Title: Construction and characterization of mismatch-containing circular DNA molecules competent for assessment of nick-directed human mismatch repair in vitro
    Article Snippet: .. The reaction was incubated for 10 min at 37°C in T4 ligase buffer (New England Biolabs) containing 100 µg/ml bovine serum albumin, 75 mM KCl and the heteroduplex oligo recovered after Dpn II digestion (estimated to be a ∼100-fold molar excess over the plasmid ends). .. The reaction was then cooled on ice, whereupon 100 cohesive end ligation units of T4 ligase per microgram of plasmid (1500 U in this example) were added and the reaction incubated at 16°C overnight.

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    New England Biolabs t4 polynucleotide kinase
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