Review



oligonucleotide pool encoding grna and target sequence  (CustomArray Inc)

 
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 90

    Structured Review

    CustomArray Inc oligonucleotide pool encoding grna and target sequence
    High throughput measurement of repair outcomes. Constructs containing both a <t>gRNA</t> and its <t>target</t> <t>sequence</t> (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).
    Oligonucleotide Pool Encoding Grna And Target Sequence, supplied by CustomArray Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/oligonucleotide pool encoding grna and target sequence/product/CustomArray Inc
    Average 90 stars, based on 1 article reviews
    oligonucleotide pool encoding grna and target sequence - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence"

    Article Title: Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

    Journal: bioRxiv

    doi: 10.1101/400341

    High throughput measurement of repair outcomes. Constructs containing both a gRNA and its target sequence (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).
    Figure Legend Snippet: High throughput measurement of repair outcomes. Constructs containing both a gRNA and its target sequence (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).

    Techniques Used: High Throughput Screening Assay, Construct, Sequencing, Clone Assay, Amplification

    A.Example measured repair profile reproducibility of one gRNA-target pair. DNA sequence of the target (top) is edited to produce a range of outcomes in two synthetic replicates (green, blue bars) and one endogenous measurement (orange bars). The proportions (x-axis) of the four most frequent mutational outcomes (e.g. “D3” - deletion of three base pairs, “I1” - insertion of one base pair, etc.; y-axis) is consistent between the experiments. Stretches of microhomology (green) and inserted sequences (red) are highlighted at the cut site (dashed vertical line). B.Synthetic measurements faithfully capture endogenous outcomes. Symmetrized Kullback-Leibler divergence (white to black color scale) between the measured repair profiles (e.g. ) in our synthetic measurements in K562 cells (x-axis) when compared to the same individual gRNAs in endogenous measurements from van Overbeek et al. (y-axis). C.Synthetic measurements are reproducible and gRNA-specific. Box plots (orange median line, quartiles for box edges, 95% whiskers) of symmetrised KL divergences between replicate measurements of over 6000 gRNAs (left), as well as two different sets of randomly selected gRNA pairs (middle, right) using the same library of constructs (green boxes) and a separately cloned library of corresponding constructs (blue boxes). D.Frame information is reproducible between replicates, and well correlated with endogenous outcomes. In-frame percentages for one biological replicate of our synthetic measurements (y-axis) contrasted against another replicate (x-axis, blue markers, Pearson’s R=0.895), or endogenous measurements (x-axis, orange markers, Pearson’s R=0.78). E.Low coverage and large deletions are the main sources of discrepancy between endogenous and synthetic measurements. Symmetrized KL divergence (y-axis) between endogenous and synthetic measurements of the same gRNA editing outcomes (individual markers) is dependent on the sequencing coverage (log 10 (number of obtained reads), x-axis), and frequency of very large deletions (colors). Three target sequences that frequently give rise to very large deletions (red, purple) are not well captured by our assay by design.
    Figure Legend Snippet: A.Example measured repair profile reproducibility of one gRNA-target pair. DNA sequence of the target (top) is edited to produce a range of outcomes in two synthetic replicates (green, blue bars) and one endogenous measurement (orange bars). The proportions (x-axis) of the four most frequent mutational outcomes (e.g. “D3” - deletion of three base pairs, “I1” - insertion of one base pair, etc.; y-axis) is consistent between the experiments. Stretches of microhomology (green) and inserted sequences (red) are highlighted at the cut site (dashed vertical line). B.Synthetic measurements faithfully capture endogenous outcomes. Symmetrized Kullback-Leibler divergence (white to black color scale) between the measured repair profiles (e.g. ) in our synthetic measurements in K562 cells (x-axis) when compared to the same individual gRNAs in endogenous measurements from van Overbeek et al. (y-axis). C.Synthetic measurements are reproducible and gRNA-specific. Box plots (orange median line, quartiles for box edges, 95% whiskers) of symmetrised KL divergences between replicate measurements of over 6000 gRNAs (left), as well as two different sets of randomly selected gRNA pairs (middle, right) using the same library of constructs (green boxes) and a separately cloned library of corresponding constructs (blue boxes). D.Frame information is reproducible between replicates, and well correlated with endogenous outcomes. In-frame percentages for one biological replicate of our synthetic measurements (y-axis) contrasted against another replicate (x-axis, blue markers, Pearson’s R=0.895), or endogenous measurements (x-axis, orange markers, Pearson’s R=0.78). E.Low coverage and large deletions are the main sources of discrepancy between endogenous and synthetic measurements. Symmetrized KL divergence (y-axis) between endogenous and synthetic measurements of the same gRNA editing outcomes (individual markers) is dependent on the sequencing coverage (log 10 (number of obtained reads), x-axis), and frequency of very large deletions (colors). Three target sequences that frequently give rise to very large deletions (red, purple) are not well captured by our assay by design.

    Techniques Used: Sequencing, Construct, Clone Assay

    A.Single base insertions are most common, with a long tail of moderately long deletions. The frequency (y-axis) of deletion or insertion size (x-axis), averaged across genomic sequence targets. B.Editing outcome types are diverse. The average percent occurrence (area of wedge) of small (<4nt) and large (≥4nt) deletions, both microhomology-mediated and not, as well as small (1nt) and large (>1nt) insertions, measured in K562 cells, and averaged across genomic sequence targets. C.Per-gRNA event frequencies differ across indel classes. Number of individual indels (y-axis) as a percentage of all mutations observed for their gRNA (x-axis) separated by mutations class (rows). Colors as in (B). D.Specific single insertions and microhomology-mediated deletions are the most frequent reproducible mutation classes. The percent of gRNAs (area of wedge) that have the same specific indel as their most frequent mutation in all three replicates, stratified by indel class (colors). ‘No consensus’: inconsistent most frequent mutation across replicates. E.A single allele often accounts for a large fraction of editing outcomes for a gRNA. Number of gRNAs (y-axis) with the frequency of its most common outcome (x-axis) in K562 cells. F.A small number of outcomes explains most of the observed data, but many low frequency alleles are present. Cumulative fraction of observed data (y-axis) matching an increasing number of outcomes (x-axis) for each target in K562 cells (grey lines), and their average (blue line).
    Figure Legend Snippet: A.Single base insertions are most common, with a long tail of moderately long deletions. The frequency (y-axis) of deletion or insertion size (x-axis), averaged across genomic sequence targets. B.Editing outcome types are diverse. The average percent occurrence (area of wedge) of small (<4nt) and large (≥4nt) deletions, both microhomology-mediated and not, as well as small (1nt) and large (>1nt) insertions, measured in K562 cells, and averaged across genomic sequence targets. C.Per-gRNA event frequencies differ across indel classes. Number of individual indels (y-axis) as a percentage of all mutations observed for their gRNA (x-axis) separated by mutations class (rows). Colors as in (B). D.Specific single insertions and microhomology-mediated deletions are the most frequent reproducible mutation classes. The percent of gRNAs (area of wedge) that have the same specific indel as their most frequent mutation in all three replicates, stratified by indel class (colors). ‘No consensus’: inconsistent most frequent mutation across replicates. E.A single allele often accounts for a large fraction of editing outcomes for a gRNA. Number of gRNAs (y-axis) with the frequency of its most common outcome (x-axis) in K562 cells. F.A small number of outcomes explains most of the observed data, but many low frequency alleles are present. Cumulative fraction of observed data (y-axis) matching an increasing number of outcomes (x-axis) for each target in K562 cells (grey lines), and their average (blue line).

    Techniques Used: Sequencing, Mutagenesis

    A.Nearby matching sequences are used as substrate for microhomology-mediated repair more frequently than distant ones. Fraction of mutated reads (y-axis) for increasing distance between matching sequences of length 9 (x-axis) for individual targets (blue markers) in K562 cells, and a linear regression fit to the trend (solid line). B.Frequency of microhomology-mediated repair depends on the length of and distance between the matching sequences. Same as (A), but linear regression fits only for microhomologies of lengths 3 (gray, bottom) to 15 (yellow, top), with Pearson’s correlation noted in the legend. C.GC content influences microhomology-mediated repair fidelity. Percent gRNA reads with length 9 microhomology-mediated deletion (y-axis; boxes median and quartiles, whiskers 5% and 95%) across a range of GC contents (x-axis). D.Mutations in microhomology sequence reduce repair outcome frequency, but corresponding deletions are still present. For matched pairs of gRNAs, with and without mutations in the microhomologous sequence, the fraction of mutated reads associated with the particular microhomology with mismatches (y-axis) vs without mismatches (x-axis) (markers; blue: one mismatch, yellow: two mismatches; solid lines: linear regression fits). Dashed black line: y=x. E.The sequence context at the cut site influences which single base is inserted. PAM-distal (blue), PAM-proximal (green), and other (red) nucleotide insertion frequency of all single base insertions; if proximal and distal bases are identical (orange), no call can be made. F.Single base insertion rate depends on the PAM-distal base adjacent to the cut site. The average percent of per-gRNA mutations that are unambiguous PAM-distal 1bp insertions (y-axis), stratified by the PAM-distal nucleotide (x-axis).
    Figure Legend Snippet: A.Nearby matching sequences are used as substrate for microhomology-mediated repair more frequently than distant ones. Fraction of mutated reads (y-axis) for increasing distance between matching sequences of length 9 (x-axis) for individual targets (blue markers) in K562 cells, and a linear regression fit to the trend (solid line). B.Frequency of microhomology-mediated repair depends on the length of and distance between the matching sequences. Same as (A), but linear regression fits only for microhomologies of lengths 3 (gray, bottom) to 15 (yellow, top), with Pearson’s correlation noted in the legend. C.GC content influences microhomology-mediated repair fidelity. Percent gRNA reads with length 9 microhomology-mediated deletion (y-axis; boxes median and quartiles, whiskers 5% and 95%) across a range of GC contents (x-axis). D.Mutations in microhomology sequence reduce repair outcome frequency, but corresponding deletions are still present. For matched pairs of gRNAs, with and without mutations in the microhomologous sequence, the fraction of mutated reads associated with the particular microhomology with mismatches (y-axis) vs without mismatches (x-axis) (markers; blue: one mismatch, yellow: two mismatches; solid lines: linear regression fits). Dashed black line: y=x. E.The sequence context at the cut site influences which single base is inserted. PAM-distal (blue), PAM-proximal (green), and other (red) nucleotide insertion frequency of all single base insertions; if proximal and distal bases are identical (orange), no call can be made. F.Single base insertion rate depends on the PAM-distal base adjacent to the cut site. The average percent of per-gRNA mutations that are unambiguous PAM-distal 1bp insertions (y-axis), stratified by the PAM-distal nucleotide (x-axis).

    Techniques Used: Sequencing



    Similar Products

    90
    CustomArray Inc oligonucleotide pool encoding grna and target sequence
    High throughput measurement of repair outcomes. Constructs containing both a <t>gRNA</t> and its <t>target</t> <t>sequence</t> (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).
    Oligonucleotide Pool Encoding Grna And Target Sequence, supplied by CustomArray Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/oligonucleotide pool encoding grna and target sequence/product/CustomArray Inc
    Average 90 stars, based on 1 article reviews
    oligonucleotide pool encoding grna and target sequence - by Bioz Stars, 2026-04
    90/100 stars
      Buy from Supplier

    Image Search Results


    High throughput measurement of repair outcomes. Constructs containing both a gRNA and its target sequence (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).

    Journal: bioRxiv

    Article Title: Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

    doi: 10.1101/400341

    Figure Lengend Snippet: High throughput measurement of repair outcomes. Constructs containing both a gRNA and its target sequence (matched colors) in variable context (grey boxes) are cloned en masse into target vectors containing a human U6 promoter (green) (1), packaged into lentiviral particles, and used to infect cells (2), where they generate mutations at the target (3). DNA from the cells is extracted, the target sequence in its context amplified with common primers, and the repair outcomes determined by deep short read sequencing (4).

    Article Snippet: Library cloning started by PCR amplification of the 170 nt oligonucleotide pool of designed sequences (CustomArray) encoding gRNA and target sequence, separated by a spacer harbouring two BbsI restriction sites (Supplementary ).

    Techniques: High Throughput Screening Assay, Construct, Sequencing, Clone Assay, Amplification

    A.Example measured repair profile reproducibility of one gRNA-target pair. DNA sequence of the target (top) is edited to produce a range of outcomes in two synthetic replicates (green, blue bars) and one endogenous measurement (orange bars). The proportions (x-axis) of the four most frequent mutational outcomes (e.g. “D3” - deletion of three base pairs, “I1” - insertion of one base pair, etc.; y-axis) is consistent between the experiments. Stretches of microhomology (green) and inserted sequences (red) are highlighted at the cut site (dashed vertical line). B.Synthetic measurements faithfully capture endogenous outcomes. Symmetrized Kullback-Leibler divergence (white to black color scale) between the measured repair profiles (e.g. ) in our synthetic measurements in K562 cells (x-axis) when compared to the same individual gRNAs in endogenous measurements from van Overbeek et al. (y-axis). C.Synthetic measurements are reproducible and gRNA-specific. Box plots (orange median line, quartiles for box edges, 95% whiskers) of symmetrised KL divergences between replicate measurements of over 6000 gRNAs (left), as well as two different sets of randomly selected gRNA pairs (middle, right) using the same library of constructs (green boxes) and a separately cloned library of corresponding constructs (blue boxes). D.Frame information is reproducible between replicates, and well correlated with endogenous outcomes. In-frame percentages for one biological replicate of our synthetic measurements (y-axis) contrasted against another replicate (x-axis, blue markers, Pearson’s R=0.895), or endogenous measurements (x-axis, orange markers, Pearson’s R=0.78). E.Low coverage and large deletions are the main sources of discrepancy between endogenous and synthetic measurements. Symmetrized KL divergence (y-axis) between endogenous and synthetic measurements of the same gRNA editing outcomes (individual markers) is dependent on the sequencing coverage (log 10 (number of obtained reads), x-axis), and frequency of very large deletions (colors). Three target sequences that frequently give rise to very large deletions (red, purple) are not well captured by our assay by design.

    Journal: bioRxiv

    Article Title: Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

    doi: 10.1101/400341

    Figure Lengend Snippet: A.Example measured repair profile reproducibility of one gRNA-target pair. DNA sequence of the target (top) is edited to produce a range of outcomes in two synthetic replicates (green, blue bars) and one endogenous measurement (orange bars). The proportions (x-axis) of the four most frequent mutational outcomes (e.g. “D3” - deletion of three base pairs, “I1” - insertion of one base pair, etc.; y-axis) is consistent between the experiments. Stretches of microhomology (green) and inserted sequences (red) are highlighted at the cut site (dashed vertical line). B.Synthetic measurements faithfully capture endogenous outcomes. Symmetrized Kullback-Leibler divergence (white to black color scale) between the measured repair profiles (e.g. ) in our synthetic measurements in K562 cells (x-axis) when compared to the same individual gRNAs in endogenous measurements from van Overbeek et al. (y-axis). C.Synthetic measurements are reproducible and gRNA-specific. Box plots (orange median line, quartiles for box edges, 95% whiskers) of symmetrised KL divergences between replicate measurements of over 6000 gRNAs (left), as well as two different sets of randomly selected gRNA pairs (middle, right) using the same library of constructs (green boxes) and a separately cloned library of corresponding constructs (blue boxes). D.Frame information is reproducible between replicates, and well correlated with endogenous outcomes. In-frame percentages for one biological replicate of our synthetic measurements (y-axis) contrasted against another replicate (x-axis, blue markers, Pearson’s R=0.895), or endogenous measurements (x-axis, orange markers, Pearson’s R=0.78). E.Low coverage and large deletions are the main sources of discrepancy between endogenous and synthetic measurements. Symmetrized KL divergence (y-axis) between endogenous and synthetic measurements of the same gRNA editing outcomes (individual markers) is dependent on the sequencing coverage (log 10 (number of obtained reads), x-axis), and frequency of very large deletions (colors). Three target sequences that frequently give rise to very large deletions (red, purple) are not well captured by our assay by design.

    Article Snippet: Library cloning started by PCR amplification of the 170 nt oligonucleotide pool of designed sequences (CustomArray) encoding gRNA and target sequence, separated by a spacer harbouring two BbsI restriction sites (Supplementary ).

    Techniques: Sequencing, Construct, Clone Assay

    A.Single base insertions are most common, with a long tail of moderately long deletions. The frequency (y-axis) of deletion or insertion size (x-axis), averaged across genomic sequence targets. B.Editing outcome types are diverse. The average percent occurrence (area of wedge) of small (<4nt) and large (≥4nt) deletions, both microhomology-mediated and not, as well as small (1nt) and large (>1nt) insertions, measured in K562 cells, and averaged across genomic sequence targets. C.Per-gRNA event frequencies differ across indel classes. Number of individual indels (y-axis) as a percentage of all mutations observed for their gRNA (x-axis) separated by mutations class (rows). Colors as in (B). D.Specific single insertions and microhomology-mediated deletions are the most frequent reproducible mutation classes. The percent of gRNAs (area of wedge) that have the same specific indel as their most frequent mutation in all three replicates, stratified by indel class (colors). ‘No consensus’: inconsistent most frequent mutation across replicates. E.A single allele often accounts for a large fraction of editing outcomes for a gRNA. Number of gRNAs (y-axis) with the frequency of its most common outcome (x-axis) in K562 cells. F.A small number of outcomes explains most of the observed data, but many low frequency alleles are present. Cumulative fraction of observed data (y-axis) matching an increasing number of outcomes (x-axis) for each target in K562 cells (grey lines), and their average (blue line).

    Journal: bioRxiv

    Article Title: Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

    doi: 10.1101/400341

    Figure Lengend Snippet: A.Single base insertions are most common, with a long tail of moderately long deletions. The frequency (y-axis) of deletion or insertion size (x-axis), averaged across genomic sequence targets. B.Editing outcome types are diverse. The average percent occurrence (area of wedge) of small (<4nt) and large (≥4nt) deletions, both microhomology-mediated and not, as well as small (1nt) and large (>1nt) insertions, measured in K562 cells, and averaged across genomic sequence targets. C.Per-gRNA event frequencies differ across indel classes. Number of individual indels (y-axis) as a percentage of all mutations observed for their gRNA (x-axis) separated by mutations class (rows). Colors as in (B). D.Specific single insertions and microhomology-mediated deletions are the most frequent reproducible mutation classes. The percent of gRNAs (area of wedge) that have the same specific indel as their most frequent mutation in all three replicates, stratified by indel class (colors). ‘No consensus’: inconsistent most frequent mutation across replicates. E.A single allele often accounts for a large fraction of editing outcomes for a gRNA. Number of gRNAs (y-axis) with the frequency of its most common outcome (x-axis) in K562 cells. F.A small number of outcomes explains most of the observed data, but many low frequency alleles are present. Cumulative fraction of observed data (y-axis) matching an increasing number of outcomes (x-axis) for each target in K562 cells (grey lines), and their average (blue line).

    Article Snippet: Library cloning started by PCR amplification of the 170 nt oligonucleotide pool of designed sequences (CustomArray) encoding gRNA and target sequence, separated by a spacer harbouring two BbsI restriction sites (Supplementary ).

    Techniques: Sequencing, Mutagenesis

    A.Nearby matching sequences are used as substrate for microhomology-mediated repair more frequently than distant ones. Fraction of mutated reads (y-axis) for increasing distance between matching sequences of length 9 (x-axis) for individual targets (blue markers) in K562 cells, and a linear regression fit to the trend (solid line). B.Frequency of microhomology-mediated repair depends on the length of and distance between the matching sequences. Same as (A), but linear regression fits only for microhomologies of lengths 3 (gray, bottom) to 15 (yellow, top), with Pearson’s correlation noted in the legend. C.GC content influences microhomology-mediated repair fidelity. Percent gRNA reads with length 9 microhomology-mediated deletion (y-axis; boxes median and quartiles, whiskers 5% and 95%) across a range of GC contents (x-axis). D.Mutations in microhomology sequence reduce repair outcome frequency, but corresponding deletions are still present. For matched pairs of gRNAs, with and without mutations in the microhomologous sequence, the fraction of mutated reads associated with the particular microhomology with mismatches (y-axis) vs without mismatches (x-axis) (markers; blue: one mismatch, yellow: two mismatches; solid lines: linear regression fits). Dashed black line: y=x. E.The sequence context at the cut site influences which single base is inserted. PAM-distal (blue), PAM-proximal (green), and other (red) nucleotide insertion frequency of all single base insertions; if proximal and distal bases are identical (orange), no call can be made. F.Single base insertion rate depends on the PAM-distal base adjacent to the cut site. The average percent of per-gRNA mutations that are unambiguous PAM-distal 1bp insertions (y-axis), stratified by the PAM-distal nucleotide (x-axis).

    Journal: bioRxiv

    Article Title: Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

    doi: 10.1101/400341

    Figure Lengend Snippet: A.Nearby matching sequences are used as substrate for microhomology-mediated repair more frequently than distant ones. Fraction of mutated reads (y-axis) for increasing distance between matching sequences of length 9 (x-axis) for individual targets (blue markers) in K562 cells, and a linear regression fit to the trend (solid line). B.Frequency of microhomology-mediated repair depends on the length of and distance between the matching sequences. Same as (A), but linear regression fits only for microhomologies of lengths 3 (gray, bottom) to 15 (yellow, top), with Pearson’s correlation noted in the legend. C.GC content influences microhomology-mediated repair fidelity. Percent gRNA reads with length 9 microhomology-mediated deletion (y-axis; boxes median and quartiles, whiskers 5% and 95%) across a range of GC contents (x-axis). D.Mutations in microhomology sequence reduce repair outcome frequency, but corresponding deletions are still present. For matched pairs of gRNAs, with and without mutations in the microhomologous sequence, the fraction of mutated reads associated with the particular microhomology with mismatches (y-axis) vs without mismatches (x-axis) (markers; blue: one mismatch, yellow: two mismatches; solid lines: linear regression fits). Dashed black line: y=x. E.The sequence context at the cut site influences which single base is inserted. PAM-distal (blue), PAM-proximal (green), and other (red) nucleotide insertion frequency of all single base insertions; if proximal and distal bases are identical (orange), no call can be made. F.Single base insertion rate depends on the PAM-distal base adjacent to the cut site. The average percent of per-gRNA mutations that are unambiguous PAM-distal 1bp insertions (y-axis), stratified by the PAM-distal nucleotide (x-axis).

    Article Snippet: Library cloning started by PCR amplification of the 170 nt oligonucleotide pool of designed sequences (CustomArray) encoding gRNA and target sequence, separated by a spacer harbouring two BbsI restriction sites (Supplementary ).

    Techniques: Sequencing