On 2017 Jun 15, Feng Zhang commented:

A number of researchers have inquired about the presence of duplicate sgRNAs (same sgRNA for more than one gene) in the GeCKOv2 library (Sanjana et al., Nature Methods 2014) and non-specific sgRNAs that have additional exact matches in the genome. We would like to further clarify the design considerations for GeCKOv2 (Supplementary Methods, Sanjana et al., Nature Methods 2014).

For the GeCKOv2 libraries we decided to take the “best” sgRNA (i.e. with the fewest off-targets) we could find for a given gene, even if in some cases our “best” sgRNA had more than one targeting location in the genome. This was done to sample as many targets as possible and minimize false negatives, since false positives that are due to an sgRNA with more than one target or off target effects can be easily eliminated in post-screen validation experiments or through a gene-based analysis that selects hits based on the consistent effect of multiple unique sgRNAs. Regardless, each candidate obtained through a GeCKO screen needs to be validated through rigorous experimentation, including testing using new guides targeting each screen hit.

A special example are gene families with high homology, in such cases our algorithm was not able to find a unique sgRNA targeting a constitutive exon. The approach that we took was to leave in these sgRNAs to give users the greatest range of options (and potential targets) during post-screen validation experiments. For example, in the human GeCKOv2 library, there are 5,664 non-specific sgRNAs. This works out to be ~4% of all guides in the library. Those redundant sgRNAs can always be removed computationally, following a screen, to simplify data analysis. (A table of these sgRNAs and genes targeted with multiple non-specific sgRNAs is available here: [link]). In contrast, GeCKOv1 did not include as many non-specific guides and consequently only targets a smaller number of genes.

To clarify this and help users in their analysis we previously provided the GeCKOv2 sgRNA database with information about the number of off-target target hits (e.g. [link]). We also have provided an additional sgRNA index for both human and mouse GeCKOv2 libraries that lists only unique sgRNAs such that when multiple genes are targeted all of those are listed under gene_id [link].

The GeCKOv2 libraries have already been successfully used by many groups to generate a number of interesting biological findings (e.g. Golden et al., Nature, 2017, Erb et al., Nature, 2017; Xu et al., PNAS, 2017; Jain et al., Science, 2016; Marcaeu et al., Nature, 2016; Zhang et al., Nature, 2016; Meitinger et al., JCB, 2016; Wallace et al., PLoS One, 2016; Parnas et al., Cell, 2015; Chen et al., Cell, 2015). In addition to GeCKOv2, there are a number of alternative libraries (e.g. Wang et al., Science, 2015; Doench et al., Nat. Biotechnol., 2016; Hart et al., Cell, 2015), including libraries that were designed to avoid duplicate sgRNAs by targeting fewer genes. A list of different libraries is available on Addgene’s pooled CRISPR libraries page: [link].

We would like to specifically thank Joey Riepsaame and Timokratis Karamitros for recently bringing this issue to our attention. We also thank the GeCKO users who contacted us through the CRISPR Genome Engineering online forum and by email for additional helpful discussions.

Neville E. Sanjana (nsanjana at nygenome.org)

Ophir Shalem (shalemo at email.chop.edu)

Joey Riepsaame (joey.riepsaame at path.ox.ac.uk)

Timokratis Karamitros (timokratis.karamitros at zoo.ox.ac.uk)

Feng Zhang (zhang at broadinstitute.org)

References Cited

Chen, S., Sanjana, N.E., Zheng, K., Shalem, O., Lee, K., Shi, X., Scott, D.A., Song, J., Pan, J.Q., Weissleder, R., et al. (2015). Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260.

Doench, J.G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E.W., Donovan, K.F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., et al. (2016). Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184–191.

Erb, M.A., Scott, T.G., Li, B.E., Xie, H., Paulk, J., Seo, H.-S., Souza, A., Roberts, J.M., Dastjerdi, S., Buckley, D.L., et al. (2017). Transcription control by the ENL YEATS domain in acute leukaemia. Nature 543, 270–274.

Golden, R.J., Chen, B., Li, T., Braun, J., Manjunath, H., Chen, X., Wu, J., Schmid, V., Chang, T.-C., Kopp, F., et al. (2017). An Argonaute phosphorylation cycle promotes microRNA-mediated silencing. Nature 542, 197–202.

Hart, T., Tong, A., Chan, K., van Leeuwen, J., Seetharaman, A., Aregger, M., Chandrashekhar, M., Hustedt, N., Seth, S., Noonan, A., et al. (2017). Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens. bioRxiv.

Jain, I.H., Zazzeron, L., Goli, R., Alexa, K., Schatzman-Bone, S., Dhillon, H., Goldberger, O., Peng, J., Shalem, O., Sanjana, N.E., et al. (2016). Hypoxia as a therapy for mitochondrial disease. Science 352, 54–61.

Marceau, C.D., Puschnik, A.S., Majzoub, K., Ooi, Y.S., Brewer, S.M., Fuchs, G., Swaminathan, K., Mata, M.A., Elias, J.E., Sarnow, P., et al. (2016). Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature 535, 159–163.

Meitinger, F., Anzola, J.V., Kaulich, M., Richardson, A., Stender, J.D., Benner, C., Glass, C.K., Dowdy, S.F., Desai, A., Shiau, A.K., et al. (2016). 53BP1 and USP28 mediate p53 activation and G1 arrest after centrosome loss or extended mitotic duration. J. Cell Biol. 214, 155–166.

Parnas, O., Jovanovic, M., Eisenhaure, T.M., Herbst, R.H., Dixit, A., Ye, C.J., Przybylski, D., Platt, R.J., Tirosh, I., Sanjana, N.E., et al. (2015). A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks. Cell 162, 675–686.

Sanjana, N.E., Shalem, O., and Zhang, F. (2014). Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784.

Wallace, J., Hu, R., Mosbruger, T.L., Dahlem, T.J., Stephens, W.Z., Rao, D.S., Round, J.L., and O’Connell, R.M. (2016). Genome-Wide CRISPR-Cas9 Screen Identifies MicroRNAs That Regulate Myeloid Leukemia Cell Growth. PloS One 11, e0153689.

Wang, T., Birsoy, K., Hughes, N.W., Krupczak, K.M., Post, Y., Wei, J.J., Lander, E.S., and Sabatini, D.M. (2015). Identification and characterization of essential genes in the human genome. Science 350, 1096–1101.

Xu, C., Qi, X., Du, X., Zou, H., Gao, F., Feng, T., Lu, H., Li, S., An, X., Zhang, L., et al. (2017). piggyBac mediates efficient in vivo CRISPR library screening for tumorigenesis in mice. Proc. Natl. Acad. Sci. U. S. A. 114, 722–727.

Zhang, R., Miner, J.J., Gorman, M.J., Rausch, K., Ramage, H., White, J.P., Zuiani, A., Zhang, P., Fernandez, E., Zhang, Q., et al. (2016). A CRISPR screen defines a signal peptide processing pathway required by flaviviruses. Nature 535, 164–168.

On 2017 Jun 15, Feng Zhang commented:

A number of researchers have inquired about the presence of duplicate sgRNAs (same sgRNA for more than one gene) in the GeCKOv2 library (Sanjana et al., Nature Methods 2014) and non-specific sgRNAs that have additional exact matches in the genome. We would like to further clarify the design considerations for GeCKOv2 (Supplementary Methods, Sanjana et al., Nature Methods 2014).

For the GeCKOv2 libraries we decided to take the “best” sgRNA (i.e. with the fewest off-targets) we could find for a given gene, even if in some cases our “best” sgRNA had more than one targeting location in the genome. This was done to sample as many targets as possible and minimize false negatives, since false positives that are due to an sgRNA with more than one target or off target effects can be easily eliminated in post-screen validation experiments or through a gene-based analysis that selects hits based on the consistent effect of multiple unique sgRNAs. Regardless, each candidate obtained through a GeCKO screen needs to be validated through rigorous experimentation, including testing using new guides targeting each screen hit.

A special example are gene families with high homology, in such cases our algorithm was not able to find a unique sgRNA targeting a constitutive exon. The approach that we took was to leave in these sgRNAs to give users the greatest range of options (and potential targets) during post-screen validation experiments. For example, in the human GeCKOv2 library, there are 5,664 non-specific sgRNAs. This works out to be ~4% of all guides in the library. Those redundant sgRNAs can always be removed computationally, following a screen, to simplify data analysis. (A table of these sgRNAs and genes targeted with multiple non-specific sgRNAs is available here: [link]). In contrast, GeCKOv1 did not include as many non-specific guides and consequently only targets a smaller number of genes.

To clarify this and help users in their analysis we previously provided the GeCKOv2 sgRNA database with information about the number of off-target target hits (e.g. [link]). We also have provided an additional sgRNA index for both human and mouse GeCKOv2 libraries that lists only unique sgRNAs such that when multiple genes are targeted all of those are listed under gene_id [link].

The GeCKOv2 libraries have already been successfully used by many groups to generate a number of interesting biological findings (e.g. Golden et al., Nature, 2017, Erb et al., Nature, 2017; Xu et al., PNAS, 2017; Jain et al., Science, 2016; Marcaeu et al., Nature, 2016; Zhang et al., Nature, 2016; Meitinger et al., JCB, 2016; Wallace et al., PLoS One, 2016; Parnas et al., Cell, 2015; Chen et al., Cell, 2015). In addition to GeCKOv2, there are a number of alternative libraries (e.g. Wang et al., Science, 2015; Doench et al., Nat. Biotechnol., 2016; Hart et al., Cell, 2015), including libraries that were designed to avoid duplicate sgRNAs by targeting fewer genes. A list of different libraries is available on Addgene’s pooled CRISPR libraries page: [link].

We would like to specifically thank Joey Riepsaame and Timokratis Karamitros for recently bringing this issue to our attention. We also thank the GeCKO users who contacted us through the CRISPR Genome Engineering online forum and by email for additional helpful discussions.

Neville E. Sanjana (nsanjana at nygenome.org)

Ophir Shalem (shalemo at email.chop.edu)

Joey Riepsaame (joey.riepsaame at path.ox.ac.uk)

Timokratis Karamitros (timokratis.karamitros at zoo.ox.ac.uk)

Feng Zhang (zhang at broadinstitute.org)

References Cited

Chen, S., Sanjana, N.E., Zheng, K., Shalem, O., Lee, K., Shi, X., Scott, D.A., Song, J., Pan, J.Q., Weissleder, R., et al. (2015). Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260.

Doench, J.G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E.W., Donovan, K.F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., et al. (2016). Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184–191.

Erb, M.A., Scott, T.G., Li, B.E., Xie, H., Paulk, J., Seo, H.-S., Souza, A., Roberts, J.M., Dastjerdi, S., Buckley, D.L., et al. (2017). Transcription control by the ENL YEATS domain in acute leukaemia. Nature 543, 270–274.

Golden, R.J., Chen, B., Li, T., Braun, J., Manjunath, H., Chen, X., Wu, J., Schmid, V., Chang, T.-C., Kopp, F., et al. (2017). An Argonaute phosphorylation cycle promotes microRNA-mediated silencing. Nature 542, 197–202.

Hart, T., Tong, A., Chan, K., van Leeuwen, J., Seetharaman, A., Aregger, M., Chandrashekhar, M., Hustedt, N., Seth, S., Noonan, A., et al. (2017). Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens. bioRxiv.

Jain, I.H., Zazzeron, L., Goli, R., Alexa, K., Schatzman-Bone, S., Dhillon, H., Goldberger, O., Peng, J., Shalem, O., Sanjana, N.E., et al. (2016). Hypoxia as a therapy for mitochondrial disease. Science 352, 54–61.

Marceau, C.D., Puschnik, A.S., Majzoub, K., Ooi, Y.S., Brewer, S.M., Fuchs, G., Swaminathan, K., Mata, M.A., Elias, J.E., Sarnow, P., et al. (2016). Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature 535, 159–163.

Meitinger, F., Anzola, J.V., Kaulich, M., Richardson, A., Stender, J.D., Benner, C., Glass, C.K., Dowdy, S.F., Desai, A., Shiau, A.K., et al. (2016). 53BP1 and USP28 mediate p53 activation and G1 arrest after centrosome loss or extended mitotic duration. J. Cell Biol. 214, 155–166.

Parnas, O., Jovanovic, M., Eisenhaure, T.M., Herbst, R.H., Dixit, A., Ye, C.J., Przybylski, D., Platt, R.J., Tirosh, I., Sanjana, N.E., et al. (2015). A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks. Cell 162, 675–686.

Sanjana, N.E., Shalem, O., and Zhang, F. (2014). Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784.

Wallace, J., Hu, R., Mosbruger, T.L., Dahlem, T.J., Stephens, W.Z., Rao, D.S., Round, J.L., and O’Connell, R.M. (2016). Genome-Wide CRISPR-Cas9 Screen Identifies MicroRNAs That Regulate Myeloid Leukemia Cell Growth. PloS One 11, e0153689.

Wang, T., Birsoy, K., Hughes, N.W., Krupczak, K.M., Post, Y., Wei, J.J., Lander, E.S., and Sabatini, D.M. (2015). Identification and characterization of essential genes in the human genome. Science 350, 1096–1101.

Xu, C., Qi, X., Du, X., Zou, H., Gao, F., Feng, T., Lu, H., Li, S., An, X., Zhang, L., et al. (2017). piggyBac mediates efficient in vivo CRISPR library screening for tumorigenesis in mice. Proc. Natl. Acad. Sci. U. S. A. 114, 722–727.

Zhang, R., Miner, J.J., Gorman, M.J., Rausch, K., Ramage, H., White, J.P., Zuiani, A., Zhang, P., Fernandez, E., Zhang, Q., et al. (2016). A CRISPR screen defines a signal peptide processing pathway required by flaviviruses. Nature 535, 164–168.