Comparative analysis of CRISPR off-target discovery tools following ex vivo editing of CD34(+) hematopoietic stem and progenitor cells
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Abstract
While a number of methods exist to investigate CRISPR off-target (OT) editing, few have been compared head-to-head in primary cells after clinically relevant editing processes. Therefore, we compared in silico tools (COSMID, CCTop, and Cas-OFFinder) and empirical methods (CHANGE-Seq, CIRCLE-Seq, DISCOVER-Seq, GUIDE-Seq, and SITE-Seq) after ex vivo hematopoietic stem and progenitor cell (HSPC) editing. We performed editing using 11 different gRNAs complexed with Cas9 protein (high-fidelity [HiFi] or wild-type versions), then performed targeted next-generation sequencing of nominated OT sites identified by in silico and empirical methods. We identified an average of less than one OT site per guide RNA (gRNA) and all OT sites generated using HiFi Cas9 and a 20-nt gRNA were identified by all OT detection methods with the exception of SITE-seq. This resulted in high sensitivity for the majority of OT nomination tools and COSMID, DISCOVER-Seq, and GUIDE-Seq attained the highest positive predictive value (PPV). We found that empirical methods did not identify OT sites that were not also identified by bioinformatic methods. This study supports that refined bioinformatic algorithms could be developed that maintain both high sensitivity and PPV, thereby enabling more efficient identification of potential OT sites without compromising a thorough examination for any given gRNA.
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GUIDE-seq is more sensitive than the IDLV method because dsODNs integrate more efficiently and precisely into DSBs, while IDLV integration events are low in number and can distribute as far as 500 bp away from the actual DSB sites.
“GUIDE-seq is more sensitive than the IDLV method because dsODNs integrate more efficiently and precisely into DSBs, while the integration events of IDLV is low in number and can distribute as far as 500bp away from the actual DSB sites (Tsai et al., 2015; Cromer et al., 2023).”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Cromer et al., 2023
The Figure 2 discussion (p. 9) identifies GUIDE-Seq as one of the empirical methods with the highest sensitivity and positive predictive value. It does not compare GUIDE-Seq with IDLV or support the proposed explanation about dsODN integration efficiency, low IDLV integration counts, or events up to 500 bp from a break; searches for IDLV and those integration details found no relevant passage. (LLM, conf=0.86)
Experimental — accuracy not yet measuredDiscover-seq is broadly applicable for various types of tissue or cell samples.
“Because good ChIP-grade MRE11 antibodies are available and there is no need to deliver any exogenous components to the body, Discover-seq is broadly applicable for various types of tissue or cell samples (Wienert et al., 2019; Cromer et al., 2023).”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Cromer et al., 2023
The paper compares DISCOVER-Seq with other off-target discovery methods following ex vivo editing of primary CD34+ hematopoietic stem and progenitor cells (opening summary, p. 2). That supports its use in this cell type, but the cited paper does not establish broad applicability across various tissue or cell samples or give the stated antibody and exogenous-component rationale. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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Cites
DNA targeting specificity of RNA-guided Cas9 nucleases
Hsu, P. D., Scott, D. A., Weinstein, J. A., Ran, F. A., Konermann, S., Agarwala, V., Li, Y., Fine, E. J., Wu, X., Shalem, O., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2647 · Cited by 4,741 · see citing works
High-Frequency off-Target Mutagenesis Induced by CRISPR-Cas Nucleases in Human Cells
Fu, Y., Foden, J. A., Khayter, C., Maeder, M. L., Reyon, D., Joung, J. K., & Sander, J. D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2623 · Cited by 3,292 · see citing works
Bae, S., Park, J., & Kim, J.-S. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu048 · Cited by 2,339 · see citing works
GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases
Tsai, S. Q., Zheng, Z., Nguyen, N. T., Liebers, M., Topkar, V. V., Thapar, V., Wyvekens, N., Khayter, C., Iafrate, A. J., Le, L. P., et al. (2015) · Nature Biotechnology · doi:10.1038/nbt.3117 · Cited by 2,268 · see citing works
CRISPR-Cas9 Gene Editing for Sickle Cell Disease and β-Thalassemia
Frangoul, H., Altshuler, D., Cappellini, M. D., Chen, Y.-S., Domm, J., Eustace, B. K., Foell, J., de la Fuente, J., Grupp, S., Handgretinger, R., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2031054 · Cited by 1,962 · see citing works
CRISPR-Cas9 In Vivo Gene Editing for Transthyretin Amyloidosis
Gillmore, J. D., Gane, E., Taubel, J., Kao, J., Fontana, M., Maitland, M. L., Seitzer, J., O’Connell, D., Walsh, K. R., Wood, K., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2107454 · Cited by 1,766 · see citing works
Regulation of DNA double-strand break repair pathway choice
Shrivastav, M., De Haro, L. P., & Nickoloff, J. A. (2008) · Cell Research · doi:10.1038/cr.2007.111 · Cited by 1,329 · see citing works
CRISPR–Cas9 genome editing induces a p53-mediated DNA damage response
Haapaniemi, E., Botla, S., Persson, J., Schmierer, B., & Taipale, J. (2018) · Nature Medicine · doi:10.1038/s41591-018-0049-z · Cited by 1,264 · see citing works
p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells
Ihry, R. J., Worringer, K. A., Salick, M. R., Frias, E., Ho, D., Theriault, K., Kommineni, S., Chen, J., Sondey, M., Ye, C., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0050-6 · Cited by 978 · see citing works
Anchored multiplex PCR for targeted next-generation sequencing
Zheng, Z., Liebers, M. R., Zhelyazkova, B. H., Cao, Y., Panditi, D., Lynch, K. D., Chen, J., Robinson, H. E., Shim, H. S., Chmielecki, J., et al. (2014) · Nature Medicine · doi:10.1038/nm.3729 · Cited by 908 · see citing works
CRISPR/Cas9 β-globin gene targeting in human haematopoietic stem cells
Dever, D. P., Bak, R. O., Reinisch, A., Camarena, J., Washington, G., Nicolas, C. E., Pavel-Dinu, M., Saxena, N., Wilkens, A. B., Mantri, S., et al. (2016) · Nature · doi:10.1038/nature20134 · Cited by 864 · see citing works
Self-citationCIRCLE-Seq: A highly sensitive in vitro screen for genome-wide CRISPR-cas9 nuclease off-targets
Tsai, S. Q., Nguyen, N. T., Malagon-Lopez, J., Topkar, V. V., Aryee, M. J., & Joung, J. K. (2017) · Nature Methods · doi:10.1038/nmeth.4278 · Cited by 814 · see citing works
Vakulskas, C. A., Dever, D. P., Rettig, G. R., Turk, R., Jacobi, A. M., Collingwood, M. A., Bode, N. M., McNeill, M. S., Yan, S., Camarena, J., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0137-0 · Cited by 782 · see citing works
Chromothripsis as an on-target consequence of CRISPR–Cas9 genome editing
Leibowitz, M. L., Papathanasiou, S., Doerfler, P. A., Blaine, L. J., Sun, L., Yao, Y., Zhang, C.-Z., Weiss, M. J., & Pellman, D. (2021) · Nature Genetics · doi:10.1038/s41588-021-00838-7 · Cited by 583 · see citing works
Kim, M. Y., Yu, K., Kenderian, S. S., Ruella, M., Chen, S., Shin, T., Aljanahi, A. A., Schreeder, D. M., Klichinsky, M., Shestova, O. E., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.013 · Cited by 458 · see citing works
Mapping the genomic landscape of CRISPR-Cas9 cleavage
Cameron, P., Fuller, C. K., Donohoue, P. D., Jones, B. N., Thompson, M. S., Carter, M. M., Gradia, S., Vidal, B., Garner, E., Slorach, E. M., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4284 · Cited by 443 · see citing works
CCTOP: a Consensus Constrained TOPology prediction web server
Dobson, L., Reményi, I., & Tusnády, G. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv451 · Cited by 437 · see citing works
Unbiased detection of CRISPR off-targets in vivo using DISCOVER-Seq
Wienert, B., Wyman, S. K., Richardson, C. D., Yeh, C. D., Akcakaya, P., Porritt, M. J., Morlock, M., Vu, J. T., Kazane, K. R., Watry, H. L., et al. (2019) · Science · doi:10.1126/science.aav9023 · Cited by 434 · see citing works
An APOBEC3A-Cas9 base editor with minimized bystander and off-target activities
Gehrke, J. M., Cervantes, O., Clement, K., Wu, Y., Zeng, J., Bauer, D. E., Pinello, L., & Joung, J. K. (2018) · Nature Biotechnology · doi:10.1038/nbt.4199 · Cited by 433 · see citing works
Nucleosomes impede Cas9 access to DNA in vivo and in vitro
Horlbeck, M. A., Witkowsky, L. B., Guglielmi, B., Replogle, J. M., Gilbert, L. A., Villalta, J. E., Torigoe, S. E., Tjian, R., & Weissman, J. S. (2016) · eLife · doi:10.7554/elife.12677 · Cited by 415 · see citing works
COSMID: A Web-based Tool for Identifying and Validating CRISPR/Cas Off-target Sites
Cradick, T. J., Qiu, P., Lee, C. M., Fine, E. J., & Bao, G. (2014) · Molecular Therapy - Nucleic Acids · doi:10.1038/mtna.2014.64 · Cited by 408 · see citing works
The presence of extra chromosomes leads to genomic instability
Passerini, V., Ozeri-Galai, E., de Pagter, M. S., Donnelly, N., Schmalbrock, S., Kloosterman, W. P., Kerem, B., & Štorchová, Z. (2016) · Nature Communications · doi:10.1038/ncomms10754 · Cited by 294 · see citing works
Refined sgRNA efficacy prediction improves large- and small-scale CRISPR–Cas9 applications
Labuhn, M., Adams, F. F., Ng, M. S. W., Knoess, S., Schambach, A., Charpentier, E., Schwarzer, A., Mateo, J. L., Klusmann, J., & Heckl, D. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1268 · Cited by 289 · see citing works
CHANGE-seq reveals genetic and epigenetic effects on CRISPR–Cas9 genome-wide activity
Lazzarotto, C. R., Malinin, N. L., Li, Y., Zhang, R., Yang, Y., Lee, G., Cowley, E., He, Y., Lan, X., Jividen, K., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0555-7 · Cited by 283 · see citing works
Structural basis for mismatch surveillance by CRISPR–Cas9
Bravo, J. P. K., Liu, M., Hibshman, G. N., Dangerfield, T. L., Jung, K., McCool, R. S., Johnson, K. A., & Taylor, D. W. (2022) · Nature · doi:10.1038/s41586-022-04470-1 · Cited by 270 · see citing works
Hu, J., Meyers, R. M., Dong, J., Panchakshari, R. A., Alt, F. W., & Frock, R. L. (2016) · Nature Protocols · doi:10.1038/nprot.2016.043 · Cited by 261 · see citing works
Quantitative evaluation of chromosomal rearrangements in gene-edited human stem cells by CAST-Seq
Turchiano, G., Andrieux, G., Klermund, J., Blattner, G., Pennucci, V., el Gaz, M., Monaco, G., Poddar, S., Mussolino, C., Cornu, T. I., et al. (2021) · Cell stem cell · doi:10.1016/j.stem.2021.02.002 · Cited by 231 · see citing works
A New Class of Medicines through DNA Editing
Porteus, M. H. (2019) · New England Journal of Medicine · doi:10.1056/nejmra1800729 · Cited by 229 · see citing works
Self-citationMartin, R. M., Ikeda, K., Cromer, M. K., Uchida, N., Nishimura, T., Romano, R., Tong, A. J., Lemgart, V. T., Camarena, J., Pavel-Dinu, M., et al. (2019) · Cell stem cell · doi:10.1016/j.stem.2019.04.001 · Cited by 207 · see citing works
Genome editing of HBG1 and HBG2 to induce fetal hemoglobin
Métais, J.-Y., Doerfler, P. A., Mayuranathan, T., Bauer, D. E., Fowler, S. C., Hsieh, M. M., Katta, V., Keriwala, S., Lazzarotto, C. R., Luk, K., et al. (2019) · Blood Advances · doi:10.1182/bloodadvances.2019000820 · Cited by 177 · see citing works
Lattanzi, A., Camarena, J., Lahiri, P., Segal, H., Srifa, W., Vakulskas, C. A., Frock, R. L., Kenrick, J., Lee, C. M., Talbott, N., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abf2444 · Cited by 166 · see citing works
Park, S. H., Lee, C. M., Dever, D. P., Davis, T., Camarena, J., Srifa, W., Zhang, Y., Paikari, A., Chang, A. K., Porteus, M. H., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz475 · Cited by 147 · see citing works
Vaidyanathan, S., Salahudeen, A. A., Sellers, Z. M., Bravo, D. T., Choi, S. S., Batish, A., Le, W., Baik, R., Sean de la, O., Kaushik, M. P., et al. (2019) · Cell stem cell · doi:10.1016/j.stem.2019.11.002 · Cited by 135 · see citing works
UDiTaS™, a genome editing detection method for indels and genome rearrangements
Giannoukos, G., Ciulla, D., Marco, E., Abdulkerim, H. S., Barrera, L. A., Bothmer, A., Dhanapal, V., Gloskowski, S. W., Jayaram, H., Maeder, M. L., et al. (2018) · BMC Genomics · doi:10.1186/s12864-018-4561-9 · Cited by 131 · see citing works
Human genome-edited hematopoietic stem cells phenotypically correct Mucopolysaccharidosis type I
Gomez‐Ospina, N., Scharenberg, S. G., Mostrel, N., Bak, R. O., Mantri, S., Quadros, R. M., Gurumurthy, C. B., Lee, C. M., Bao, G., Suarez, C. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11962-8 · Cited by 119 · see citing works
CRISPR-based gene editing enables FOXP3 gene repair in IPEX patient cells
Goodwin, M., Lee, E., Lakshmanan, U., Shipp, S., Froessl, L. J., Barzaghi, F., Passerini, L., Narula, M., Sheikali, A., Lee, C. M., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz0571 · Cited by 113 · see citing works
Improved gRNA secondary structures allow editing of target sites resistant to CRISPR-Cas9 cleavage
Riesenberg, S., Helmbrecht, N., Kanis, P., Maricic, T., & Pääbo, S. (2022) · Nature Communications · doi:10.1038/s41467-022-28137-7 · Cited by 109 · see citing works
Tools for experimental and computational analyses of off-target editing by programmable nucleases
Bao, X. R., Pan, Y., Lee, C. M., Davis, T. H., & Bao, G. (2021) · Nature Protocols · doi:10.1038/s41596-020-00431-y · Cited by 106 · see citing works
Optimizing genome editing strategy by primer-extension-mediated sequencing
Yin, J., Liu, M., Liu, Y., Wu, J., Gan, T., Zhang, W., Li, Y., Zhou, Y., & Hu, J. (2019) · Cell Discovery · doi:10.1038/s41421-019-0088-8 · Cited by 103 · see citing works
Pharmacological interventions enhance virus-free generation of TRAC-replaced CAR T cells
Kath, J., Du, W., Pruene, A., Braun, T., Thommandru, B., Turk, R., Sturgeon, M. L., Kurgan, G., Amini, L., Stein, M., et al. (2022) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2022.03.018 · Cited by 95 · see citing works
Park, S. H., Cao, M., Pan, Y., Davis, T., Saxena, L., Deshmukh, H., Fu, Y., Treangen, T. J., Sheehan, V., & Bao, G. (2022) · Science Advances · doi:10.1126/sciadv.abo7676 · Cited by 92 · see citing works
Cromer, M. K., Camarena, J., Martin, R. M., Lesch, B. J., Vakulskas, C. A., Bode, N. M., Kurgan, G., Collingwood, M. A., Rettig, G. R., Behlke, M. A., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01284-y · Cited by 83 · see citing works
Prediction-based highly sensitive CRISPR off-target validation using target-specific DNA enrichment
Kang, S.-H., Lee, W.-J., An, J.-H., Lee, J., Kim, Y.-H., Kim, H., Oh, Y., Park, Y., Jin, Y. B., Jun, B., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17418-8 · Cited by 70 · see citing works
Landscape of target:guide homology effects on Cas9-mediated cleavage
Fu, B. X. H., Hansen, L. L., Artiles, K. L., Nonet, M. L., & Fire, A. Z. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1102 · Cited by 66 · see citing works
Boyle, E. A., Becker, W. R., Bai, H., Chen, J. S., Doudna, J. A., & Greenleaf, W. J. (2021) · Science Advances · doi:10.1126/sciadv.abe5496 · Cited by 59 · see citing works
Genomic Instability of iPSCs and Challenges in Their Clinical Applications
Yoshihara, M., Oguchi, A., & Murakawa, Y. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-31206-0_2 · Cited by 58 · see citing works
Genome-wide detection of CRISPR editing in vivo using GUIDE-tag
Liang, S.-Q., Liu, P., Smith, J. L., Mintzer, E., Maitland, S., Dong, X., Yang, Q., Lee, J., Haynes, C. M., Zhu, L. J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28135-9 · Cited by 54 · see citing works
Evaluation of Homology-Independent CRISPR-Cas9 Off-Target Assessment Methods
Chaudhari, H. G., Penterman, J. N., Whitton, H. J., Spencer, S. J., Flanagan, N., Zhang, M. C. L., Huang, E., Khedkar, A. S., Toomey, J. M., Shearer, C. A., et al. (2020) · The CRISPR Journal · doi:10.1089/crispr.2020.0053 · Cited by 44 · see citing works
The fractured genome of HeLa cells
Mittelman, D., & Wilson, J. H. (2013) · Genome biology · doi:10.1186/gb-2013-14-4-111 · Cited by 43 · see citing works
Kulcsár, P. I., Tálas, A., Ligeti, Z., Krausz, S. L., & Welker, E. (2022) · Nature Communications · doi:10.1038/s41467-022-34527-8 · Cited by 43 · see citing works
Cromer, M. K., Barsan, V. V., Jaeger, E. B., Wang, M., Hampton, J. P., Chen, F., Kennedy, D., Xiao, J., Khrebtukova, I., Granat, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32233-z · Cited by 37 · see citing works
Zhong, H., Ceballos, C. C., Massengill, C. I., Muniak, M. A., Ma, L., Qin, M., Kaech, S., & Mao, T. (2021) · eLife · doi:10.7554/elife.64911 · Cited by 32 · see citing works
Kurgan, G., Turk, R., Li, H., Roberts, N., Rettig, G. R., Jacobi, A. M., Tso, L., Sturgeon, M. L., Mertens, M., Noten, R., et al. (2021) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2021.03.024 · Cited by 30 · see citing works
Jing, C., Peng, H., Shaffer, B. C., Baskar, S., Wecken, I. C., Cyr, M. G., Martínez, G., Soden, J., Freeth, J., Wiestner, A. U., et al. (2018) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0102 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [5]5. [Shrivastav, M., de Haro, L.P., and Nickoloff, J.A. (2008). Regulation of DNA doublestrand break repair pathway choice. Cell Res. 18 , 134 -147.](http://refhub.elsevier.com/S1525-0016(23)00074-6/sref5)
Cited by
Sorted by citations
Off-target effects in CRISPR/Cas9 gene editing
Guo, C., Ma, X., Gao, F., & Guo, Y. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1143157 · Cited by 625 · see citing works
“Because good ChIP-grade MRE11 antibodies are available and there is no need to deliver any exogenous components to the body, Discoverseq is broadly applicable for various types of tissue or cell samples (Wienert et al., 2019; Cromer et al., 2023).”
BackgroundMethodSelvaraj, S., Feist, W. N., Viel, S., Vaidyanathan, S., Dudek, A. M., Gastou, M., Rockwood, S. J., Ekman, F. K., Oseghale, A., Xu, L., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01888-4 · Cited by 102 · see citing works
Genetic engineering meets hematopoietic stem cell biology for next-generation gene therapy
Ferrari, S., Valeri, E., Conti, A., Scala, S., Aprile, A., Micco, R. D., Kajaste‐Rudnitski, A., Montini, E., Ferrari, G., Aiuti, A., et al. (2023) · Cell stem cell · doi:10.1016/j.stem.2023.04.014 · Cited by 71 · see citing works
CRISPR nuclease off-target activity and mitigation strategies
Wienert, B., & Cromer, M. K. (2022) · Frontiers in Genome Editing · doi:10.3389/fgeed.2022.1050507 · Cited by 62 · see citing works
CRISPRoffT: comprehensive database of CRISPR/Cas off-targets
Wang, G., Liu, X., Wang, A., Wen, J., Kim, P., Song, Q., Liu, X., & Zhou, X. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1025 · Cited by 41 · see citing works
Clinical hematopoietic stem cell-based gene therapy
John, T., & Czechowicz, A. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.04.029 · Cited by 21 · see citing works
Clinical application of base editing for treating β-thalassaemia
Lai, Y., Liu, R., Wang, L., Ma, X.-K., Li, Y., Yang, G., Shi, L., Guo, Y., Wei, Z., Zhou, X., et al. (2026) · Nature · doi:10.1038/s41586-026-10342-9 · Cited by 17 · see citing works
Porreca, I., Blassberg, R. A., Harbottle, J. A., Joubert, B. C., Mielczarek, O., Stombaugh, J., Hemphill, K., Sumner, J., Pazeraitis, D., Touza, J. L., et al. (2024) · Molecular Therapy · doi:10.1016/j.ymthe.2024.06.033 · Cited by 15 · see citing works
Lemmens, M., Dorsheimer, L., Zeller, A., & Dietz, Y. (2024) · Mutation Research/Genetic Toxicology and Environmental Mutagenesis · doi:10.1016/j.mrgentox.2024.503767 · Cited by 13 · see citing works
Luna, S. E., Camarena, J., Hampton, J. P., Majeti, K. R., Charlesworth, C. T., Soupène, E., Selvaraj, S., Jia, K., Sheehan, V., Cromer, M. K., et al. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01222-6 · Cited by 17 · see citing works
Monitoring biological effects of somatic cell genome editing
Freedman, B., Bulte, J. W. M., Conklin, B. R., Judge, L. M., Dwinell, M. R., Geurts, A. M., Sitton, M. J., Mahajan, V., Kiani, S., Gersbach, C. A., et al. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-025-00916-0 · Cited by 12 · see citing works
Chu, S. N., Soupène, E., Sharma, D., Sinha, R., McCreary, T., Hernandez, B. N., Shen, H., Wienert, B., Bowman, C., Yin, H., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2024.115141 · Cited by 12 · see citing works
Precise measurement of CRISPR genome editing outcomes through single-cell DNA sequencing
Kalter, N., Gulati, S., Rosenberg, M., Ayaz, Q., Nguyen, J., Wang, S., Schroeder, B., Li, C.-Y., & Hendel, A. (2025) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2025.101449 · Cited by 11 · see citing works
Quantifying allele-specific CRISPR editing activity with CRISPECTOR2.0
Assa, G., Kalter, N., Rosenberg, M., Beck, A., Markovich, O., Gontmakher, T., Hendel, A., & Yakhini, Z. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae651 · Cited by 9 · see citing works
Methods for detecting off-target effects of CRISPR/Cas9
Xu, Y., Zhou, S., Wang, L.-Y., Zhang, R., Li, K., Qian, Z., & Li, X. (2025) · Biotechnology Advances · doi:10.1016/j.biotechadv.2025.108750 · Cited by 11 · see citing works
Ritter, M. U., Nasri, M., Dannenmann, B., Mir, P., Secker, B., Amend, D., Klimiankou, M., Welte, K., & Skokowa, J. (2024) · The CRISPR Journal · doi:10.1089/crispr.2024.0006 · Cited by 7 · see citing works
Montepeloso, A., Mattioli, D., Pellin, D., Peviani, M., Genovese, P., & Biffi, A. (2024) · Nature Communications · doi:10.1038/s41467-024-54515-4 · Cited by 6 · see citing works
Kinney, K. J., Jia, K., Zhang, H., Schmaljohn, E., Osborne, T., Thommandru, B., Murugan, K., Peña, A. S., West, S. C., Chen, S., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-74623-7 · Cited by 6 · see citing works
Shao, C., Liu, Q. F., Xu, J., Zhang, J.-X., Zhang, C., Ye, X., Ye, Y., Lin, B., Zhang, X., Cheng, L., et al. (2024) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2024.102371 · Cited by 5 · see citing works
Luna, S. E., Camarena, J., Hampton, J. P., Majeti, K. R., Charlesworth, C. T., Soupène, E., Selvaraj, S., Jia, K., Sheehan, V., Cromer, M. K., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.04.552064 · Cited by 5 · see citing works
Ng, K. P., Seng, M. S.-F., & Leung, W. H. (2025) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2025.101462 · Cited by 4 · see citing works
Design principle of successful genome editing applications using CRISPR-based toolkits
Sharma, J., Biswas, R. K., & Khare, P. S. (2025) · Journal of Applied Genetics · doi:10.1007/s13353-025-00979-z · Cited by 3 · see citing works
Precision T cell correction platform for inborn errors of immunity
Mamia, K., Kolbeinsdóttir, S., Labun, K., Li, Z., Komisarczuk, A. Z., Keskitalo, S., Reint, G., Haugen, F. L., Lindestad, B. O., Jensen, S. S., et al. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.08.018 · Cited by 4 · see citing works
Engineering with care: safety assessment platforms for CRISPR-modified natural killer cells
Fazeli, A., Ullrich, E., Cathomen, T., & Bexte, T. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1711414 · Cited by 3 · see citing works
Applications of genome editing technologies in the treatment of human diseases
Alshorman, J., Mehran, M. J., Tembo, K. M., Mostafavi, N., Bolideei, M., & Wang, Y. L. (2026) · Gene Therapy · doi:10.1038/s41434-026-00627-z · Cited by 3 · see citing works
Samson, C., du Rand, A., Hunt, J., Whitford, W., Jacobsen, J. C., & Sheppard, H. M. (2024) · Journal of the Royal Society of New Zealand · doi:10.1080/03036758.2024.2347968 · Cited by 3 · see citing works
Chu, S. N., Soupène, E., Wienert, B., Yin, H., Sharma, D., McCreary, T., Jia, K., Homma, S., Hampton, J. P., Gardner, J. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.01.555926 · Cited by 3 · see citing works
Targeting oncogenic fusion-driven NUT carcinoma with CRISPR-Cas9 genome editing
Carle, M. F., Gol, T. M., Antony, J. S., Roig-Merino, A., Carter, M. E., Lauer, U., Mezger, M., & Kloker, L. D. (2025) · Molecular therapy. Oncology · doi:10.1016/j.omton.2025.201068 · Cited by 4 · see citing works
White, N., Hu, Y., Chalk, J. A., Kurgan, G., Naseem, A., Schmaljohn, E., Sturgeon, M. L., Cavazza, A., Thrasher, A. J., & Turchiano, G. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag318 · Cited by 2 · see citing works
CRISPR/Cas9-engineering of Kell null erythrocytes to unveil host targeted irresistible antimalarial
Kumari, G., Gupta, P., Goswami, S. G., Jain, R., Anand, S., Biswas, S., Garg, S., Thakur, P., Saravanakumar, V., Arvinden, V. R., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07968-2 · Cited by 2 · see citing works
Pavel-Dinu, M., Viel, S., Selvaraj, S., Gastou, M., Feist, W. N., Perret, M., Rouvet, I., Nombel, A., Hacein‐Bey‐Abina, S., Bélot, A., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5090716/v1 · Cited by 2 · see citing works
Sharma, D., Sinha, R., Lesch, B. J., & Cromer, M. K. (2025) · STAR Protocols · doi:10.1016/j.xpro.2025.104018 · Cited by 1 · see citing works
Chromatic grains: Revolutionizing nutrition with pigmented cereals and fortified foods
Ahmed, S. S., Kumar, J., GARG, N. K., & Gahlaut, V. (2025) · Journal of Food Measurement & Characterization · doi:10.1007/s11694-025-03681-0 · Cited by 1 · see citing works
Naseem, A., Vetharoy, W., Whittaker, T. E., Zinghirino, F., Carusillo, A., Ghosh, R., Gómez‐Castañeda, E., Ali, H., Cipriani, C., Montini, E., et al. (2026) · Molecular Therapy Advances · doi:10.1016/j.omta.2026.201816 · Cited by 1 · see citing works
Chao, G., Appleton, E., Gutierrez, C. S., Evgeniou, L., Daifuku, T., Wannier, T. M., Mintzer, E., & Church, G. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.04.668540 · Cited by 1 · see citing works
Hundal, T., Luo, Y., Qie, Y., Gadd, M. E., Brim, A. D., Vazquez-Rosario, I. K., Guo, S., Kharfan‐Dabaja, M. A., & Qin, H. (2025) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2025.102778
Naseem, A., Vetharoy, W., Whittaker, T. E., Zinghirino, F., Ghosh, R., Gómez‐Castañeda, E., Ali, H.-J., Cipriani, C., Montini, E., Thrasher, A. J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.08.698401
DisTAL-Seq: A TALEN-specific adaptation of DISCOVER-Seq for off-target profiling
Kobel, L., van de Venn, L., Schröder, M., Bechter, L. V., Huang, D., Abdolazimi, Y., Pertel, T., Gopalakrishnan, S., Corn, J. E., & Kontarakis, Z. (2026) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2026.102883
TFU72 is a novel and potent DNA-PKcs inhibitor for enhancing homology-directed repair gene editingPreprint
Selvaraj, S., Schmiderer, L., Lamberth, J., Fuchß, T., Ekman, F. K., Russkamp, N. F., & Porteus, M. H. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.10.710954
Jia, K., Soupène, E., Sinha, R., Lesch, B. J., Pendergast, M. A., Choi, R., Zhang, X., Foppiani, E. M., Kostamo, Z., Chu, S. N., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.13.718029
Gene therapy for hereditary hematological disorders: From clinical breakthroughs to future horizons
Chen, Z., Wang, W., Wu, Y., Qiang, Y., Cheng, W., & Liu, F. (2026) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2026.103075
Protocol for non-viral HDR-based CRISPR/Cas9 platform for small custom editing in primary T cells
Mamia, K., Sollano, A. S. M., Lundberg, V., Vakkilainen, S., Kekäläinen, E., Schalin-Jäntti, C., Leinonen, E., Fevang, B., Grönholm, J., Martelius, T., et al. (2026) · Frontiers in Genome Editing · doi:10.3389/fgeed.2026.1817322
- Authors
- Cromer, M. K., Majeti, K. R., Rettig, G. R., Murugan, K., Kurgan, G. L., Bode, N. M., Hampton, J. P., Vakulskas, C. A., Behlke, M. A., & Porteus, M. H.
- Affiliations
- University of California, San Francisco (US)
- Stanford Medicine (US)
- Integrated DNA Technologies (United States) (US)
- ORCID
- Venue
- Molecular Therapy
- Publisher
- Elsevier BV
- Published
- 2023-04
- Volume
- 31
- Issue
- 4
- Pages
- 1074-1087
- ISSN
- 1525-0016 (ISSN-L)
- PMC
- PMC10124080
- OpenAlex
- W4320921285
- Cited by
- 42
- References
- 54
- Citations by year
- 2026: 12 · 2025: 14 · 2024: 10 · 2023: 5 · 2022: 1
- FWCI
- 3.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Molecular Therapy (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Funders
- U.S. Food and Drug Administration (U01FD005978)
- Stanford University
- U.S. Department of Health and Human Services
- Government of South Australia
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Health Sciences › Medicine › Oncology › CAR-T cell therapy research
- Keywords
- hematopoietic stem and progenitor cells, ex vivo gene editing, guide RNA, cosmids, GUIDE-seq, CIRCLE-seq, positive predictive value
- MeSH terms
- Gene Editing, CRISPR-Associated Protein 9, RNA, Guide, CRISPR-Cas Systems, Hematopoietic Stem Cells, Antigens, CD34, CRISPR-Cas Systems
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