CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo
Open accessAbstract
CRISPR-Cas9 technology provides a powerful system for genome engineering. However, variable activity across different single guide RNAs (sgRNAs) remains a significant limitation. We analyzed the molecular features that influence sgRNA stability, activity and loading into Cas9 in vivo. We observed that guanine enrichment and adenine depletion increased sgRNA stability and activity, whereas differential sgRNA loading, nucleosome positioning and Cas9 off-target binding were not major determinants. We also identified sgRNAs truncated by one or two nucleotides and containing 5' mismatches as efficient alternatives to canonical sgRNAs. On the basis of these results, we created a predictive sgRNA-scoring algorithm, CRISPRscan, that effectively captures the sequence features affecting the activity of CRISPR-Cas9 in vivo. Finally, we show that targeting Cas9 to the germ line using a Cas9-nanos 3' UTR led to the generation of maternal-zygotic mutants, as well as increased viability and decreased somatic mutations. These results identify determinants that influence Cas9 activity and provide a framework for the design of highly efficient sgRNAs for genome targeting in vivo.
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Most gRNA prediction tools rely on either traditional algorithms or deep learning and focus only on SpCas9-WT; few models are specific to variants.
“Although some gRNA prediction tools have been developed, most of them rely on either traditional algorithms (Rule Set 1, CRISPRscan, etc.) or deep learning (DeepCRISPR, DeepCas9, etc.) and focus only on SpCas9-WT; few models are specific to variants (DeepSpCas9variants, DeepSmallCas9, GuideVar, DeepSniper, etc.).”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [34]
The pattern of SpCas9-NG is similar to SpCas9-WT.
“The pattern of SpCas9-NG is similar to SpCas9-WT.”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [34]
The Results section on sgRNA sequence describes nucleotide patterns associated with Cas9 activity, but does not compare SpCas9-NG with SpCas9-WT. Searches for those variants and their targeting patterns found no comparison in our copy; page numbers were not available. (LLM, conf=0.75)
Experimental — accuracy not yet measured
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works
A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A., & Charpentier, E. (2012) · Science · doi:10.1126/science.1225829 · Cited by 17,116 · see citing works
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339 · see citing works
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210 · see citing works
Development and Applications of CRISPR-Cas9 for Genome Engineering
Hsu, P. D., Lander, E. S., & Zhang, F. (2014) · Cell · doi:10.1016/j.cell.2014.05.010 · Cited by 5,762 · see citing works
Lorenz, R., Bernhart, S. H., Höner zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P. F., & Hofacker, I. L. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-26 · Cited by 5,098 · see citing works
Wang, H., Yang, H., Shivalila, C. S., Dawlaty, M. M., Cheng, A. W., Zhang, F., & Jaenisch, R. (2013) · Cell · doi:10.1016/j.cell.2013.04.025 · Cited by 3,495 · see citing works
Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity
Ran, F. A., Hsu, P. D., Lin, C.-Y., Gootenberg, J. S., Konermann, S., Trevino, A. E., Scott, D. A., Inoue, A., Matoba, S., Zhang, Y., et al. (2013) · Cell · doi:10.1016/j.cell.2013.08.021 · Cited by 3,299 · see citing works
Efficient genome editing in zebrafish using a CRISPR-Cas system
Hwang, W. Y., Fu, Y., Reyon, D., Maeder, M. L., Tsai, S. Q., Sander, J. D., Peterson, R. T., Yeh, J.-R. J., & Joung, J. K. (2013) · Nature Biotechnology · doi:10.1038/nbt.2501 · Cited by 2,937 · see citing works
Genetic screens in human cells using the CRISPR-Cas9 system
Wang, T., Wei, J. J., Sabatini, D. M., & Lander, E. S. (2014) · Science · doi:10.1126/science.1246981 · Cited by 2,856 · see citing works
GMAP: A genomic mapping and alignment program for mRNA and EST sequences
Wu, T. D., & Watanabe, C. K. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti310 · Cited by 2,354 · see citing works
Meinshausen, N., & Bühlmann, P. (2010) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2010.00740.x · Cited by 2,314 · see citing works
RNA-programmed genome editing in human cells
Jinek, M., East, A., Cheng, A., Lin, S., Ma, E., & Doudna, J. (2013) · eLife · doi:10.7554/elife.00471 · Cited by 2,098 · see citing works
Improving CRISPR-Cas nuclease specificity using truncated guide RNAs
Fu, Y., Sander, J. D., Reyon, D., Cascio, V. M., & Joung, J. K. (2014) · Nature Biotechnology · doi:10.1038/nbt.2808 · Cited by 1,993 · see citing works
Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation
Doench, J. G., Hartenian, E., Graham, D. B., Tothova, Z., Hegde, M., Smith, I., Sullender, M., Ebert, B. L., Xavier, R. J., & Root, D. E. (2014) · Nature Biotechnology · doi:10.1038/nbt.3026 · Cited by 1,617 · see citing works
Normal Table of Xenopus Laevis (Daudin)
Gerhart, J. C., & Kirschner, M. W. (2020) · Garland Science eBooks · doi:10.1201/9781003064565 · Cited by 1,578 · see citing works
Transparent Adult Zebrafish as a Tool for In Vivo Transplantation Analysis
White, R. M., Sessa, A., Burke, C., Bowman, T., LeBlanc, J., Ceol, C., Bourque, C., Dovey, M., Goessling, W., Burns, C. E., et al. (2008) · Cell Stem Cell · doi:10.1016/j.stem.2007.11.002 · Cited by 1,408 · see citing works
Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system
Jao, L.-E., Wente, S. R., & Chen, W. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308335110 · Cited by 1,261 · see citing works
CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing
Montague, T. G., Cruz, J. M. B. S., Gagnon, J. A., Church, G. M., & Valen, E. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku410 · Cited by 1,203 · see citing works
MicroRNAs Regulate Brain Morphogenesis in Zebrafish
Giraldez, A. J., Cinalli, R. M., Glasner, M. E., Enright, A. J., Thomson, J. M., Baskerville, S., Hammond, S. M., Bartel, D. P., & Schier, A. F. (2005) · Science · doi:10.1126/science.1109020 · Cited by 1,124 · see citing works
Self-citationCunningham, F., Amode, M. R., Barrell, D., Beal, K., Billis, K., Brent, S., Carvalho-Silva, D., Clapham, P., Coates, G., Fitzgerald, S., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1010 · Cited by 1,115 · see citing works
TAL effectors: customizable proteins for DNA targeting
Bogdanove, A. J., & Voytas, D. F. (2011) · Science · doi:10.1126/science.1204094 · Cited by 984 · see citing works
Heritable genome editing in C. elegans via a CRISPR-Cas9 system
Friedland, A. E., Tzur, Y. B., Esvelt, K. M., Colaiácovo, M. P., Church, G. M., & Calarco, J. A. (2013) · Nature Methods · doi:10.1038/nmeth.2532 · Cited by 899 · see citing works
Gagnon, J. A., Valen, E., Thyme, S. B., Huang, P., Ahkmetova, L., Pauli, A., Montague, T. G., Zimmerman, S., Richter, C., & Schier, A. F. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098186 · Cited by 861 · see citing works
A Novel miRNA Processing Pathway Independent of Dicer Requires Argonaute2 Catalytic Activity
Cifuentes, D., Xue, H., Taylor, D. W., Patnode, H., Mishima, Y., Cheloufi, S., Ma, E., Mane, S., Hannon, G. J., Lawson, N. D., et al. (2010) · Science · doi:10.1126/science.1190809 · Cited by 836 · see citing works
Genome-wide analysis reveals characteristics of off-target sites bound by the Cas9 endonuclease
Kuscu, C., Arslan, S., Singh, R., Thorpe, J., & Adli, M. (2014) · Nature Biotechnology · doi:10.1038/nbt.2916 · Cited by 777 · see citing works
Zygotic Genome Activation During the Maternal-to-Zygotic Transition
Lee, M. T., Bonneau, A. R., & Giráldez, A. J. (2014) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100913-013027 · Cited by 643 · see citing works
Duquette, M. L., Handa, P., Vincent, J. A., Taylor, A. F., & Maizels, N. (2004) · Genes & Development · doi:10.1101/gad.1200804 · Cited by 528 · see citing works
Method for Isolation of PCR-Ready Genomic DNA from Zebrafish Tissues
Meeker, N. D., Hutchinson, S. A., Ho, L., & Trede, N. S. (2007) · BioTechniques · doi:10.2144/000112619 · Cited by 522 · see citing works
The microRNA-producing enzyme Dicer1 is essential for zebrafish development
Wienholds, E., Koudijs, M., van Eeden, F. V., Cuppen, E., & Plasterk, R. (2003) · Nature Genetics · doi:10.1038/ng1251 · Cited by 519 · see citing works
High-throughput gene targeting and phenotyping in zebrafish using CRISPR/Cas9Preprint
Varshney, G. K., Pei, W., LaFave, M. C., Idol, J., Xu, L., Gallardo, V. E., Carrington, B., Bishop, K. S., Jones, M. S., Li, M., et al. (2015) · Genome Research · doi:10.1101/gr.186379.114 · Cited by 510 · see citing works
A zebrafish nanos -related gene is essential for the development of primordial germ cellsPreprint
Köprunner, M., Thisse, C., Thisse, B., et al. (2001) · Genes & Development · doi:10.1101/gad.212401 · Cited by 510 · see citing works
Induction of muscle pioneers and floor plate is distinguished by the zebrafish no tail mutation
Halpern, M. E., Ho, R. K., Walker, C., & Kimmel, C. B. (1993) · Cell · doi:10.1016/s0092-8674(05)80087-x · Cited by 508 · see citing works
Four-stranded nucleic acids: structure, function and targeting of G-quadruplexes
Huppert, J. (2008) · Chemical Society Reviews · doi:10.1039/b702491f · Cited by 496 · see citing works
Mutations affecting the cardiovascular system and other internal organs in zebrafish
Chen, J., Haffter, P., Odenthal, J., Vogelsang, E., Brand, M., van Eeden, F. J. M., Furutani‐Seiki, M., Granato, M., Hammerschmidt, M., Heisenberg, C., et al. (1996) · Development · doi:10.1242/dev.123.1.293 · Cited by 444 · see citing works
Zinc-finger Nucleases: The Next Generation Emerges.
Cathomen, T., & Joung, J. (2008) · Molecular Therapy · doi:10.1038/mt.2008.114 · Cited by 361 · see citing works
Rapid reverse genetic screening using CRISPR in zebrafish
Shah, A. N., Davey, C. F., Whitebirch, A. C., Miller, A. C., & Moens, C. B. (2015) · Nature Methods · doi:10.1038/nmeth.3360 · Cited by 343 · see citing works
Ren, X., Yang, Z., Jiang, X., Sun, J., Mao, D., Hu, Y., Yang, S., Qiao, H., Wang, X., Hu, Q., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.09.044 · Cited by 305 · see citing works
Expression of zebrafish goosecoid and no tail gene products in wild-type and mutant no tail embryos
Schulte‐Merker, S., Hammerschmidt, M., Beuchle, D., Cho, K. W., Robertis, E. M. D., & Nüsslein‐Volhard, C. (1994) · Development · doi:10.1242/dev.120.4.843 · Cited by 300 · see citing works
Differential Regulation of Germline mRNAs in Soma and Germ Cells by Zebrafish miR-430
Mishima, Y., Giraldez, A. J., Takeda, Y., Fujiwara, T., Sakamoto, H., Schier, A. F., & Inoue, K. (2006) · Current Biology · doi:10.1016/j.cub.2006.08.086 · Cited by 276 · see citing works
Self-citation5′-UTR G-quadruplex structures acting as translational repressors
Beaudoin, J.-D., & Perreault, J.-P. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq557 · Cited by 255 · see citing works
Self-citationTechniques and probes for the study of <i>Xenopus tropicalis</i> development
Khokha, M. K., Chung, C., Bustamante, E. L., Gaw, L. W. K., Trott, K. A., Yeh, J., Lim, N., Lin, J. C. Y., Taverner, N., Amaya, E., et al. (2002) · Developmental Dynamics · doi:10.1002/dvdy.10184 · Cited by 241 · see citing works
Self-citationDramatic Enhancement of Genome Editing by CRISPR/Cas9 Through Improved Guide RNA Design
Farboud, B., & Meyer, B. J. (2015) · Genetics · doi:10.1534/genetics.115.175166 · Cited by 234 · see citing works
Production of maternal-zygotic mutant zebrafish by germ-line replacement
Ciruna, B. G., Weidinger, G., Knaut, H., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.222459999 · Cited by 229 · see citing works
CRISPR/Cas9 and Genome Editing in Drosophila
Bassett, A. R., & Liu, J. (2013) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2013.12.004 · Cited by 209 · see citing works
Beaudoin, J.-D., & Perreault, J. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt265 · Cited by 169 · see citing works
Self-citationCanonical nucleosome organization at promoters forms during genome activationPreprint
Zhang, Y., Vastenhouw, N. L., Feng, J., Fu, K., Wang, C., Ge, Y., Pauli, A., Hummelen, P. V., Schier, A., & Liu, X. (2014) · Genome Research · doi:10.1101/gr.157750.113 · Cited by 104 · see citing works
In-line probing of RNA G-quadruplexes
Beaudoin, J.-D., Jodoin, R., & Perreault, J. (2013) · Methods · doi:10.1016/j.ymeth.2013.02.017 · Cited by 35 · see citing works
Self-citationViso, F. D., Bhattacharya, D., Kong, Y., Gilchrist, M. J., & Khokha, M. K. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-649 · Cited by 21 · see citing works
Self-citation
Flagged first, then by citations
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Sorted by citations
Kosicki, M., Tomberg, K., & Bradley, A. (2018) · Nature Biotechnology · doi:10.1038/nbt.4192 · Cited by 1,883 · see citing works
Haeussler, M., Schönig, K., Eckert, H., Eschstruth, A., Mianné, J., Renaud, J.-B., Schneider-Maunoury, S., Shkumatava, A., Teboul, L., Kent, J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1012-2 · Cited by 1,756 · see citing works
Off-target Effects in CRISPR/Cas9-mediated Genome Engineering
Zhang, X.-H., Tee, L. Y., Wang, X.-G., Huang, Q.-S., & Yang, S.-H. (2015) · Molecular Therapy - Nucleic Acids · doi:10.1038/mtna.2015.37 · Cited by 1,273 · see citing works
Delivering CRISPR: a review of the challenges and approaches
Lino, C. A., Harper, J. C., Carney, J. P., & Timlin, J. A. (2018) · Drug Delivery · doi:10.1080/10717544.2018.1474964 · Cited by 1,185 · see citing works
DeepCRISPR: Optimized CRISPR guide RNA design by deep learning
Chuai, G., Ma, H., Yan, J., Chen, M., Hong, N., Xue, D., Zhou, C., Zhu, C., Chen, K., Duan, B., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1459-4 · Cited by 641 · see citing works
Advances in the delivery of RNA therapeutics: from concept to clinical reality
Kaczmarek, J. C., Kowalski, P. S., & Anderson, D. G. (2017) · Genome Medicine · doi:10.1186/s13073-017-0450-0 · Cited by 656 · see citing works
Wang, H.-X., Li, M., Lee, C. M., Chakraborty, S., Kim, H.-W., Bao, G., & Leong, K. W. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00799 · Cited by 560 · see citing works
Latest Developed Strategies to Minimize the Off-Target Effects in CRISPR-Cas-Mediated Genome Editing
Naeem, M., Majeed, S., Hoque, M. Z., & Ahmad, I. (2020) · Cells · doi:10.3390/cells9071608 · Cited by 457 · see citing works
Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs
Listgarten, J., Weinstein, M., Kleinstiver, B. P., Sousa, A. A., Joung, J. K., Crawford, J., Gao, K., Hoang, L., Elibol, M., Doench, J. G., et al. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0178-6 · Cited by 336 · see citing works
CRISPR-STOP: gene silencing through base-editing-induced nonsense mutations
Kuscu, C., Parlak, M., Tufan, T., Yang, J., Szlachta, K., Wei, X., Mammadov, R., & Adli, M. (2017) · Nature Methods · doi:10.1038/nmeth.4327 · Cited by 344 · see citing works
Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning
Wang, D., Zhang, C., Wang, B., Li, B., Wang, Q., Liu, D., Wang, H., Zhou, Y., Shi, L., Lan, F., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12281-8 · Cited by 331 · see citing works
Highly Efficient Genome Editing of Murine and Human Hematopoietic Progenitor Cells by CRISPR/Cas9
Gundry, M. C., Brunetti, L., Lin, A., Mayle, A. E., Kitano, A., Wagner, D., Hsu, J. I., Hoegenauer, K. A., Rooney, C. M., Goodell, M. A., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.09.092 · Cited by 265 · see citing works
“EXPERIMENTAL PROCEDURES Production of sgRNA and electroporation Protospacer sequences for each target gene were identified using the CRISPRscan algorithm (www.crisprscan.org) (Moreno-Mateos et al., 2015).”
MethodJensen, K. T., Fløe, L., Petersen, T. S., Huang, J., Xu, F., Bolund, L., Luo, Y., & Lin, L. (2017) · FEBS Letters · doi:10.1002/1873-3468.12707 · Cited by 225 · see citing works
Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning
Xiang, X., Corsi, G. I., Anthon, C., Qu, K., Pan, X., Liang, X., Han, P., Dong, Z., Liu, L., Zhong, J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23576-0 · Cited by 209 · see citing works
Isolated polycystic liver disease genes define effectors of polycystin-1 function
Besse, W., Dong, K., Choi, J., Punia, S., Fedeles, S. V., Choi, M., Gallagher, A.-R., Huang, E. B., Gulati, A., Knight, J., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci90129 · Cited by 203 · see citing works
RSPO2 inhibition of RNF43 and ZNRF3 governs limb development independently of LGR4/5/6
Szenker-Ravi, E., Altunoglu, U., Leushacke, M., Bosso-Lefèvre, C., Khatoo, M., Thi Tran, H., Naert, T., Noelanders, R., Hajamohideen, A., Beneteau, C., et al. (2018) · Nature · doi:10.1038/s41586-018-0118-y · Cited by 190 · see citing works
Pflueger, C., Tan, D., Swain, T., Nguyen, T., Pflueger, J., Nefzger, C., Polo, J. M., Ford, E., & Lister, R. (2018) · Genome Research · doi:10.1101/gr.233049.117 · Cited by 188 · see citing works
Organelle degradation in the lens by PLAAT phospholipases
Morishita, H., Eguchi, T., Tsukamoto, S., Sakamaki, Y., Takahashi, S., Saito, C., Koyama-Honda, I., & Mizushima, N. (2021) · Nature · doi:10.1038/s41586-021-03439-w · Cited by 111 · 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
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
DIG-Seq: A genome-wide CRISPR off-target profiling method using chromatin DNA
Kim, D., & Kim, J.-S. (2018) · Genome Research · doi:10.1101/gr.236620.118 · Cited by 108 · see citing works
Transcriptional regulation with CRISPR-Cas9: principles, advances, and applications
Didovyk, A., Borek, B., Tsimring, L., & Hasty, J. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.06.003 · Cited by 90 · see citing works
De novo identification of essential protein domains from CRISPR-Cas9 tiling-sgRNA knockout screens
He, W., Zhang, L., Villarreal, O. D., Fu, R., Bedford, E., Dou, J., Patel, A. Y., Bedford, M. T., Shi, X., Chen, T., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12489-8 · Cited by 69 · see citing works
Interaction of heterotrimeric kinesin-II with IFT-B–connecting tetramer is crucial for ciliogenesis
Funabashi, T., Katoh, Y., Okazaki, M., Sugawa, M., & Nakayama, K. (2018) · Journal of Cell Biology · doi:10.1083/jcb.201801039 · Cited by 65 · see citing works
Advances in Genome Editing and Application to the Generation of Genetically Modified Rat Models
Chenouard, V., Remy, S., Tesson, L., Ménoret, S., Ouisse, L.-H., Cherifi, Y., & Anegon, I. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.615491 · Cited by 57 · see citing works
Kulcsár, P. I., Tálas, A., Tóth, E., Nyeste, A., Ligeti, Z., Welker, Z., & Welker, E. (2020) · Nature Communications · doi:10.1038/s41467-020-15021-5 · Cited by 45 · see citing works
Senescence-induced cellular reprogramming drives cnidarian whole-body regeneration
Salinas-Saavedra, M., Febrimarsa, Krasovec, G., Horkan, H. R., Baxevanis, A. D., & Frank, U. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112687 · Cited by 45 · see citing works
G-quadruplex-based CRISPR photoswitch for spatiotemporal control of genomic modulation
Deng, H., Xu, H., Wang, Y., Jia, R., Ma, X., Feng, Y., & Chen, H. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad178 · Cited by 45 · see citing works
Technical considerations for the use of CRISPR/Cas9 in hematology research
Gundry, M. C., Dever, D. P., Yudovich, D., Bauer, D. E., Haas, S., Wilkinson, A. C., & Singbrant, S. (2017) · Experimental Hematology · doi:10.1016/j.exphem.2017.07.006 · Cited by 26 · see citing works
Li, J., Wu, P., Cao, Z., Huang, G., Lu, Z., Yan, J., Zhang, H., Zhou, Y., Liu, R., Chen, H., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113765 · Cited by 26 · see citing works
BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models
Zarate, O. A., Yang, Y., Wang, X., & Wang, J.-P. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-04998-z · Cited by 17 · see citing works
Okada, K., Aoki, K., Tabei, T., Sugio, K., Imai, K., Bonkohara, Y., & Kamachi, Y. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac100 · Cited by 14 · see citing works
Chromatin structure and context-dependent sequence features control prime editing efficiency
Kim, S., Yuan, J. B., Woods, W. S., Newton, D. A., Perez-Pinera, P., & Song, J. S. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1222112 · Cited by 12 · see citing works
Bamundo, M., Palumbo, S., D'Auria, L., Missero, C., & Di Girolamo, D. (2024) · Current Protocols · doi:10.1002/cpz1.70056 · Cited by 4 · see citing works
- Authors
- Moreno-Mateos, M. A., Vejnar, C. E., Beaudoin, J.-D., Fernandez, J. P., Mis, E. K., Khokha, M. K., & Giraldez, A. J.
- Affiliations
- Yale University (US)
- Venue
- Nature Methods
- Published
- 2015-08-31
- Volume
- 12
- Issue
- 10
- Pages
- 982-988
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC4589495
- OpenAlex
- W1915704240
- Cited by
- 1,290
- References
- 51
- Citations by year
- 2026: 107 · 2025: 130 · 2024: 123 · 2023: 124 · 2022: 135 · 2021: 131 · 2020: 139 · 2019: 112 · 2018: 115 · 2017: 94 · 2016: 67 · 2015: 10 · 2014: 1
- FWCI
- 41.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (148600)
- National Heart, Lung, and Blood Institute (R33HL120783)
- National Institute of General Medical Sciences (R01GM081602, R01GM102251, R01GM103789, GM081602, R01GM101108)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R21HD073768, R01HD081379, R01HD074078)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Keywords
- CRISPR/Cas9, single guide RNA design, nucleosome positioning, somatic mutations
- MeSH terms
- RNA, Guide, CRISPR-Cas Systems, Adenine, Algorithms, Animals, Embryo, Nonmammalian, Female, Gene Expression Regulation, Genetic Engineering, Guanine, Mutation, Xenopus, Zebrafish, Genome, RNA, Guide, Kinetoplastida, Gene Targeting, 3' Untranslated Regions, Zebrafish Proteins, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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