Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens
Open accessAbstract
Combinatorial genetic screening using CRISPR-Cas9 is a useful approach to uncover redundant genes and to explore complex gene networks. However, current methods suffer from interference between the single-guide RNAs (sgRNAs) and from limited gene targeting activity. To increase the efficiency of combinatorial screening, we employ orthogonal Cas9 enzymes from Staphylococcus aureus and Streptococcus pyogenes. We used machine learning to establish S. aureus Cas9 sgRNA design rules and paired S. aureus Cas9 with S. pyogenes Cas9 to achieve dual targeting in a high fraction of cells. We also developed a lentiviral vector and cloning strategy to generate high-complexity pooled dual-knockout libraries to identify synthetic lethal and buffering gene pairs across multiple cell types, including MAPK pathway genes and apoptotic genes. Our orthologous approach also enabled a screen combining gene knockouts with transcriptional activation, which revealed genetic interactions with TP53. The "Big Papi" (paired aureus and pyogenes for interactions) approach described here will be widely applicable for the study of combinatorial phenotypes.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Direct capture of sgRNA molecules lets ECCITE-seq avoid the barcode-swapping problems reported for Perturb-seq.
“ECCITE-seq is readily applicable to any sgRNA library with the Cas9 S. pyogenes scaffold sequence and, by allowing direct capture of sgRNA molecules, overcomes documented problems of barcode swapping events observed with Perturb-seq that have the potential to confound single cell perturbation screens17–20.”
From Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells (2019) · cites this paper as [19]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Li, P., Nijhawan, D., Budihardjo, I., Srinivasula, S. M., Ahmad, M., Alnemri, E. S., & Wang, X. (1997) · Cell · doi:10.1016/s0092-8674(00)80434-1 · Cited by 7,289 · see citing works
Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy
Farmer, H., McCabe, N., Lord, C. J., Tutt, A. N. J., Johnson, D. A., Richardson, T. B., Santarosa, M., Dillon, K. J., Hickson, I., Knights, C., et al. (2005) · Nature · doi:10.1038/nature03445 · Cited by 6,683 · see citing works
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
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) · Nature Biotechnology · doi:10.1038/nbt.3437 · Cited by 4,637 · see citing works
Self-citationMitochondrial membrane permeabilization in cell death
Kroemer, G., Galluzzi, L., & Brenner, C. (2007) · Physiological Reviews · doi:10.1152/physrev.00013.2006 · Cited by 3,598 · see citing works
An inhibitor of Bcl-2 family proteins induces regression of solid tumours
Oltersdorf, T., Elmore, S. W., Shoemaker, A. R., Armstrong, R. C., Augeri, D. J., Belli, B., Bruncko, M., Deckwerth, T. L., Dinges, J., Hajduk, P. J., et al. (2005) · Nature · doi:10.1038/nature03579 · Cited by 3,407 · see citing works
Discovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096 · see citing works
ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets
Souers, A. J., Leverson, J. D., Boghaert, E. R., Ackler, S. L., Catron, N. D., Chen, J., Dayton, B. D., Ding, H., Enschede, S. H., Fairbrother, W. J., et al. (2013) · Nature Medicine · doi:10.1038/nm.3048 · Cited by 3,058 · see citing works
Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation
Gilbert, L. A., Horlbeck, M. A., Adamson, B., Villalta, J. E., Chen, Y., Whitehead, E. H., Guimaraes, C., Panning, B., Ploegh, H. L., Bassik, M. C., et al. (2014) · Cell · doi:10.1016/j.cell.2014.09.029 · Cited by 2,728 · see citing works
In vivo genome editing using Staphylococcus aureus Cas9
Ran, F. A., Cong, L., Yan, W. X., Scott, D. A., Gootenberg, J. S., Kriz, A. J., Zetsche, B., Shalem, O., Wu, X., Makarova, K. S., et al. (2015) · Nature · doi:10.1038/nature14299 · Cited by 2,687 · see citing works
Global Mapping of the Yeast Genetic Interaction Network
Tong, A. H. Y., Lesage, G., Bader, G. D., Ding, H., Xu, H., Xin, X., Young, J., Berriz, G. F., Brost, R. L., Chang, M., et al. (2004) · Science · doi:10.1126/science.1091317 · Cited by 2,070 · see citing works
COSMIC: somatic cancer genetics at high-resolution
Forbes, S. A., Beare, D., Boutselakis, H., Bamford, S., Bindal, N., Tate, J., Cole, C. G., Ward, S., Dawson, E., Ponting, L., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1121 · Cited by 1,922 · see citing works
Highly efficient Cas9-mediated transcriptional programming
Chavez, A., Scheiman, J., Vora, S., Pruitt, B. W., Tuttle, M., P R Iyer, E., Lin, S., Kiani, S., Guzman, C. D., Wiegand, D. J., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3312 · Cited by 1,622 · 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
Self-citationHigh-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities.
Hart, T., Chandrashekhar, M., Aregger, M., Steinhart, Z., Brown, K. R., MacLeod, G., Mis, M., Zimmermann, M., Fradet-Turcotte, A., Sun, S., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.015 · Cited by 1,571 · see citing works
A global genetic interaction network maps a wiring diagram of cellular function
Costanzo, M., VanderSluis, B., Koch, E. N., Baryshnikova, A., Pons, C., Tan, G., Wang, W., Usaj, M., Hanchard, J., Lee, S. D., et al. (2016) · Science · doi:10.1126/science.aaf1420 · Cited by 1,240 · see citing works
van Delft, M. F., Wei, A. H., Mason, K. D., Vandenberg, C. J., Chen, L., Czabotar, P. E., Willis, S. N., Scott, C. L., Day, C. L., Cory, S., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.08.027 · Cited by 1,237 · see citing works
Adamson, B., Norman, T. M., Jost, M., Cho, M. Y., Nuñez, J. K., Chen, Y., Villalta, J. E., Gilbert, L. A., Horlbeck, M. A., Hein, M. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.048 · Cited by 1,193 · see citing works
The MCL1 inhibitor S63845 is tolerable and effective in diverse cancer models
Kotschy, A., Szlavik, Z., Murray, J., Davidson, J., Maragno, A. L., Le Toumelin-Braizat, G., Chanrion, M., Kelly, G. L., Gong, J.-N., Moujalled, D. M., et al. (2016) · Nature · doi:10.1038/nature19830 · Cited by 1,047 · see citing works
Multiplex gene editing by CRISPR–Cpf1 using a single crRNA array
Zetsche, B., Heidenreich, M., Mohanraju, P., Fedorova, I., Kneppers, J., DeGennaro, E. M., Winblad, N., Choudhury, S. R., Abudayyeh, O. O., Gootenberg, J. S., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3737 · Cited by 926 · see citing works
Helleday, T. (2011) · Molecular Oncology · doi:10.1016/j.molonc.2011.07.001 · Cited by 859 · see citing works
Broadening the targeting range of Staphylococcus aureus CRISPR-Cas9 by modifying PAM recognition
Kleinstiver, B. P., Prew, M. S., Tsai, S. Q., Nguyen, N. T., Topkar, V. V., Zheng, Z., & Joung, J. K. (2015) · Nature Biotechnology · doi:10.1038/nbt.3404 · Cited by 611 · see citing works
Leverson, J. D., Phillips, D. C., Mitten, M. J., Boghaert, E. R., Diaz, D., Tahir, S. K., Belmont, L. D., Nimmer, P., Xiao, Y., Ma, X. M., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa4642 · Cited by 541 · see citing works
Han, K., Jeng, E., Hess, G., Morgens, D., Li, A., & Bassik, M. (2017) · Nature Biotechnology · doi:10.1038/nbt.3834 · Cited by 482 · see citing works
Zhu, S., Li, W., Liu, J., Chen, C.-H., Liao, Q., Xu, P., Xu, H., Xiao, T., Cao, Z., Peng, J., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3715 · Cited by 420 · see citing works
Structure-guided design of a selective BCL-XL inhibitor
Lessène, G., Czabotar, P. E., Sleebs, B. E., Zobel, K., Lowes, K. N., Adams, J. M., Baell, J. B., Colman, P. M., Deshayes, K., Fairbrother, W. J., et al. (2013) · Nature Chemical Biology · doi:10.1038/nchembio.1246 · Cited by 381 · see citing works
Akt inhibitors in cancer treatment: The long journey from drug discovery to clinical use (Review)
Nițulescu, G. M., Margina, D. M., Juzenas, P., Peng, Q., Olaru, O. T., Saloustros, E. S., Fenga, C., Spandidos, D. A., Libra, M., & Tsatsakis, A. M. (2015) · International Journal of Oncology · doi:10.3892/ijo.2015.3306 · Cited by 370 · see citing works
A Systematic Mammalian Genetic Interaction Map Reveals Pathways Underlying Ricin Susceptibility
Bassik, M. C., Kampmann, M., Lebbink, R. J., Wang, S., Hein, M. Y., Poser, I., Weibezahn, J., Horlbeck, M. A., Chen, S., Mann, M., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.030 · Cited by 365 · see citing works
Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions
Shen, J. P., Zhao, D., Sasik, R., Luebeck, J., Birmingham, A., Bojorquez-Gomez, A., Licon, K., Klepper, K., Pekin, D., Beckett, A. N., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4225 · Cited by 359 · cited 3× · see citing works
“Two efforts to achieve combinatorial CRISPR screens employed orthologous U6 promoters, from mouse and human 7,8 , although another study found that multiple copies of the S. pyogenes tracrRNA sequence were likewise prone to recombination 11 .”
p53 Suppresses the Nrf2-dependent Transcription of Antioxidant Response Genes
Faraonio, R., Vergara, P., Marzo, D. D., Pierantoni, G. M., Napolitano, M., Russo, T., & Cimino, F. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m605707200 · Cited by 350 · see citing works
Complex transcriptional modulation with orthogonal and inducible dCas9 regulators
Gao, Y., Xiong, X., Wong, S. S., Charles, E. J., Lim, W. A., & Qi, L. S. (2016) · Nature Methods · doi:10.1038/nmeth.4042 · Cited by 325 · see citing works
Dummler, B. A., Tschopp, O., Hynx, D., Yang, Z., Dirnhofer, S., & Hemmings, B. A. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.00722-06 · Cited by 283 · see citing works
ERK1 and ERK2 Map Kinases: Specific Roles or Functional Redundancy?
Buscà, R., Pouysségur, J., & Lenormand, P. (2016) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2016.00053 · Cited by 282 · see citing works
Friedland, A. E., Baral, R., Singhal, P., Loveluck, K., Shen, S., Sanchez, M. E., Marco, E., Gotta, G. M., Maeder, M. L., Kennedy, E. M., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0817-8 · Cited by 280 · see citing works
Cowling, V. H., & Downward, J. (2002) · Cell Death and Differentiation · doi:10.1038/sj.cdd.4401065 · Cited by 249 · see citing works
Sarosiek, K. A., Chi, X., Bachman, J. A., Sims, J. J., Montero, J., Patel, L., Flanagan, A., Andrews, D. W., Sorger, P. K., & Letai, A. G. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.08.048 · Cited by 247 · see citing works
Lentiviral Vector Design for Multiple shRNA Expression and Durable HIV-1 Inhibition
ter Brake, O., Hooft, K. '., Liu, Y. P., Centlivre, M., von Eije, K. J., & Berkhout, B. (2008) · Molecular Therapy · doi:10.1038/sj.mt.6300382 · Cited by 241 · see citing works
Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM
Wong, A. S. L., Choi, G. C. G., Cui, C. H., Pregernig, G., Milani, P., Adam, M., Perli, S. D., Kazer, S. W., Gaillard, A., Hermann, M., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517883113 · Cited by 236 · see citing works
Mapping of signaling networks through synthetic genetic interaction analysis by RNAi
Horn, T., Sandmann, T., Fischer, B., Axelsson, E., Huber, W., & Boutros, M. (2011) · Nature Methods · doi:10.1038/nmeth.1581 · Cited by 193 · see citing works
Hanzlíková, H., Gittens, W. H., Krejčíková, K., Zeng, Z., & Caldecott, K. W. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1246 · Cited by 192 · see citing works
Stordal, B., Timms, K. M., Farrelly, A. M., Gallagher, D., Busschots, S., Renaud, M., Thery, J., Williams, D., Potter, J., Tran, T., et al. (2013) · Molecular Oncology · doi:10.1016/j.molonc.2012.12.007 · Cited by 157 · see citing works
Feedback and redundancy in receptor tyrosine kinase signaling: relevance to cancer therapies
Sun, C., & Bernards, R. (2014) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2014.08.010 · Cited by 155 · see citing works
Rapid and efficient one-step generation of paired gRNA CRISPR-Cas9 libraries
Vidigal, J. A., & Ventura, A. (2015) · Nature Communications · doi:10.1038/ncomms9083 · Cited by 147 · see citing works
A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy
Srivas, R., Shen, J. P., Yang, C. C., Sun, S. M., Li, J., Gross, A. M., Jensen, J., Licon, K., Bojorquez-Gomez, A., Klepper, K., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.06.022 · Cited by 139 · see citing works
Ma, S. B., Nguyen, T. N., Tan, I., Ninnis, R., Iyer, S., Stroud, D. A., Menard, M., Kluck, R. M., Ryan, M. T., & Dewson, G. (2014) · Cell Death & Differentiation · doi:10.1038/cdd.2014.119 · Cited by 138 · see citing works
Inactivating CUX1 mutations promote tumorigenesis
Wong, C. C., Martin, S., Rust, A. G., Rashid, M., Alifrangis, C., Alexandrov, L. B., Tiffen, J. C., Kober, C., Green, A. R., Massie, C. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2846 · Cited by 132 · see citing works
Rotem, A., Janzer, A., Izar, B., Ji, Z., Doench, J. G., Garraway, L. A., & Struhl, K. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1505979112 · Cited by 126 · see citing works
Self-citationUzgare, A. R., & Isaacs, J. T. (2004) · Cancer Research · doi:10.1158/0008-5472.can-04-0968 · Cited by 121 · see citing works
Antiapoptotic potency of Bcl-2 proteins primarily relies on their stability, not binding selectivity
Rooswinkel, R. W., van de Kooij, B., de Vries, E., Paauwe, M., Braster, R., Verheij, M., & Borst, J. G. (2014) · Blood · doi:10.1182/blood-2013-08-519470 · Cited by 110 · see citing works
Quantitative genetic-interaction mapping in mammalian cells
Roguev, A., Talbot, D., Negri, G. L., Shales, M., Cagney, G., Bandyopadhyay, S., Panning, B., & Krogan, N. J. (2013) · Nature Methods · doi:10.1038/nmeth.2398 · Cited by 103 · see citing works
Chaudhuri, L., Vincelette, N. D., Koh, B. D., Naylor, R. M., Flatten, K. S., Peterson, K. L., McNally, A., Gojo, I., Karp, J. E., Mesa, R. A., et al. (2013) · Haematologica · doi:10.3324/haematol.2013.093187 · Cited by 78 · see citing works
Miura, Y., Kataoka, H., Joh, T., Tada, T., Asai, K., Nakanishi, M., Okada, N., & Okada, H. (2004) · Microbiology and Immunology · doi:10.1111/j.1348-0421.2004.tb03491.x · Cited by 33 · see citing works
A comparison of multiple shRNA expression methods for combinatorial RNAi
Mcintyre, G. J., Arndt, A. J., Gillespie, K. M., Mak, W. M., & Fanning, G. C. (2011) · Genetic Vaccines and Therapy · doi:10.1186/1479-0556-9-9 · Cited by 20 · see citing works
A High-Throughput Strategy for Dissecting Mammalian Genetic Interactions
Stockman, V. B., Ghamsari, L., Lasso, G., Honig, B. H., Shapira, S. D., & Wang, H. H. (2016) · PLoS ONE · doi:10.1371/journal.pone.0167617 · Cited by 5 · see citing works
Flagged first, then by citations
1 of the 54 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens
Concordet, J., & Haeussler, M. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky354 · Cited by 2,354 · see citing works
Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities
Sanson, K. R., Hanna, R. E., Hegde, M., Donovan, K. F., Strand, C., Sullender, M. E., Vaimberg, E. W., Goodale, A., Root, D. E., Piccioni, F., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07901-8 · Cited by 1,043 · see citing works
Self-citationZou, Y., Palte, M. J., Deik, A. A., Li, H., Eaton, J. K., Wang, W., Tseng, Y.-Y., Deasy, R., Kost-Alimova, M., Dančík, V., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09277-9 · Cited by 887 · see citing works
Self-citationCytochrome P450 oxidoreductase contributes to phospholipid peroxidation in ferroptosis
Zou, Y., Li, H., Graham, E. T., Deik, A., Eaton, J. K., Wang, W., Sandoval-Gomez, G., Clish, C. B., Doench, J. G., & Schreiber, S. L. (2020) · Nature Chemical Biology · doi:10.1038/s41589-020-0472-6 · Cited by 740 · see citing works
Self-citationMimitou, E. P., Cheng, A., Montalbano, A., Hao, S., Stoeckius, M., Legut, M., Roush, T., Herrera, A., Papalexi, E., Ouyang, Z., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0392-0 · Cited by 520 · see citing works
Multiplexed CRISPR technologies for gene editing and transcriptional regulation
McCarty, N. S., Graham, A. E., Studená, L., & Ledesma‐Amaro, R. (2020) · Nature Communications · doi:10.1038/s41467-020-15053-x · Cited by 547 · see citing works
The present and future of the Cancer Dependency Map
Arafeh, R., Shibue, T., Dempster, J. M., Hahn, W. C., & Vazquez, F. (2025) · Nature Reviews Cancer · doi:10.1038/s41568-024-00763-x · Cited by 454 · see citing works
Synthetic lethality as an engine for cancer drug target discovery
Huang, A., Garraway, L. A., Ashworth, A., & Weber, B. L. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0046-z · Cited by 470 · see citing works
CRISPR in cancer biology and therapy
Katti, A., Diaz, B. J., Caragine, C. M., Sanjana, N. E., & Dow, L. E. (2022) · Nature reviews. Cancer · doi:10.1038/s41568-022-00441-w · Cited by 440 · see citing works
Dempster, J. M., Boyle, I., Vázquez, F., Root, D. E., Boehm, J. S., Hahn, W. C., Tsherniak, A., & McFarland, J. M. (2021) · Genome biology · doi:10.1186/s13059-021-02540-7 · Cited by 400 · see citing works
Self-citationContinuous evolution of base editors with expanded target compatibility and improved activity
Thuronyi, B. W., Koblan, L. W., Levy, J. M., Yeh, W.-H., Zheng, C., Newby, G. A., Wilson, C., Bhaumik, M., Shubina-Oleinik, O., Holt, J. R., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0193-0 · Cited by 347 · see citing works
Massively parallel assessment of human variants with base editor screens
Hanna, R. E., Hegde, M., Fagre, C. R., DeWeirdt, P. C., Sangree, A. K., Szegletes, Z., Griffith, A., Feeley, M. N., Sanson, K. R., Baidi, Y., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.012 · Cited by 316 · see citing works
Rubin, A. J., Parker, K. R., Satpathy, A. T., Qi, Y., Wu, B., Ong, A. J., Mumbach, M. R., Ji, A. L., Kim, D. S., Cho, S. W., et al. (2019) · Cell · doi:10.1016/j.cell.2018.11.022 · Cited by 314 · see citing works
A new era in functional genomics screens
Przybyla, L., & Gilbert, L. A. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-021-00409-w · Cited by 281 · see citing works
Global Genetic Networks and the Genotype-to-Phenotype Relationship
Costanzo, M., Kuzmin, E., van Leeuwen, J., Mair, B., Moffat, J., Boone, C., & Andrews, B. (2019) · Cell · doi:10.1016/j.cell.2019.01.033 · Cited by 241 · see citing works
Kim, H. K., Kim, Y., Lee, S., Min, S., Bae, J. Y., Choi, J. W., Park, J., Jung, D., Yoon, S., & Kim, S. (2019) · Science Advances · doi:10.1126/sciadv.aax9249 · Cited by 235 · see citing works
Optimization of AsCas12a for combinatorial genetic screens in human cells
DeWeirdt, P. C., Sanson, K. R., Sangree, A. K., Hegde, M., Hanna, R. E., Feeley, M. N., Griffith, A. L., Teng, T., Borys, S. M., Strand, C., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0600-6 · Cited by 213 · see citing works
Self-citationDesign and analysis of CRISPR–Cas experiments
Hanna, R. E., & Doench, J. G. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0490-7 · Cited by 208 · see citing works
Self-citationSynthetic Lethality in Cancer Therapeutics: The Next Generation
Setton, J. S., Zinda, M. J., Riaz, N., Durocher, D., Zimmermann, M., Koehler, M. T., Reis-Filho, J. S., & Powell, S. N. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-1503 · Cited by 211 · see citing works
ACSL4 and polyunsaturated lipids support metastatic extravasation and colonization
Wang, Y., Hu, M., Cao, J., Wang, F., Han, J. R., Wu, T. W., Li, L., Yu, J., Fan, Y., Xie, G., et al. (2024) · Cell · doi:10.1016/j.cell.2024.10.047 · Cited by 191 · see citing works
Deubiquitinases Maintain Protein Homeostasis and Survival of Cancer Cells upon Glutathione Depletion
Harris, I. S., Endress, J. E., Coloff, J. L., Selfors, L. M., McBrayer, S. K., Rosenbluth, J. M., Takahashi, N., Dhakal, S., Koduri, V., Oser, M. G., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.01.020 · Cited by 168 · see citing works
Self-citationApplications of CRISPR/Cas System to Bacterial Metabolic Engineering
Cho, S., Shin, J., & Cho, B. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19041089 · Cited by 172 · see citing works
Simultaneous repression of multiple bacterial genes using nonrepetitive extra-long sgRNA arrays
Reis, A. C., Halper, S. M., Vezeau, G. E., Cetnar, D. P., Hossain, A., Clauer, P. R., & Salis, H. M. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0286-9 · Cited by 157 · see citing works
CRISPR ribonucleoprotein-mediated genetic engineering in plants
Zhang, Y., Iaffaldano, B. J., & Qi, Y. (2021) · Plant Communications · doi:10.1016/j.xplc.2021.100168 · Cited by 169 · see citing works
Stuttmann, J., Barthel, K., Martin, P., Ordon, J., Erickson, J. L., Herr, R., Ferik, F., Kretschmer, C., Berner, T., Keilwagen, J., et al. (2021) · The Plant Journal · doi:10.1111/tpj.15197 · Cited by 155 · see citing works
Ito, T., Young, M. J., Li, R., Jain, S. S., Wernitznig, A., Krill-Burger, J. M., Lemke, C. T., Monducci, D., Rodriguez, D. J., Chang, L., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00967-z · Cited by 148 · see citing works
Self-citationPan, J., Meyers, R. M., Michel, B. C., Mashtalir, N., Sizemore, A. E., Wells, J. N., Cassel, S. H., Vázquez, F., Weir, B. A., Hahn, W. C., et al. (2018) · Cell Systems · doi:10.1016/j.cels.2018.04.011 · Cited by 132 · see citing works
Verma, P., Zhou, Y., Cao, Z., Deraska, P. V., Deb, M., Arai, E., Li, W., Shao, Y., Puentes, L. N., Li, Y. H., et al. (2021) · Nature Cell Biology · doi:10.1038/s41556-020-00624-3 · Cited by 144 · see citing works
Gonatopoulos-Pournatzis, T., Aregger, M., Brown, K. R., Farhangmehr, S., Braunschweig, U., Ward, H. N., Ha, K. C. H., Weiss, A., Billmann, M., Durbic, T., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0437-z · Cited by 142 · see citing works
CRISPR-Cas-mediated transcriptional modulation: The therapeutic promises of CRISPRa and CRISPRi
Bendixen, L., Jensen, T. I., & Bak, R. O. (2023) · Molecular Therapy · doi:10.1016/j.ymthe.2023.03.024 · Cited by 144 · see citing works
Genetic screens in isogenic mammalian cell lines without single cell cloning
DeWeirdt, P. C., Sangree, A. K., Hanna, R. E., Sanson, K. R., Hegde, M., Strand, C., Persky, N. S., & Doench, J. G. (2020) · Nature Communications · doi:10.1038/s41467-020-14620-6 · Cited by 133 · see citing works
Self-citationRNAi/CRISPR Screens: from a Pool to a Valid Hit
Schuster, A. M., Erasimus, H., Fritah, S., Nazarov, P. V., Dyck, E. V., Niclou, S. P., & Golebiewska, A. (2018) · Trends in biotechnology · doi:10.1016/j.tibtech.2018.08.002 · Cited by 136 · see citing works
A widespread role for SLC transmembrane transporters in resistance to cytotoxic drugs
Girardi, E., César‐Razquin, A., Lindinger, S., Παπακώστας, Κ., Konecka, J., Hemmerich, J., Kickinger, S., Kartnig, F., Gürtl, B., Klavins, K., et al. (2020) · Nature Chemical Biology · doi:10.1038/s41589-020-0483-3 · Cited by 133 · see citing works
Automated design of thousands of nonrepetitive parts for engineering stable genetic systems
Hossain, A., Lopez, E., Halper, S. M., Cetnar, D. P., Reis, A. C., Strickland, D., Klavins, E., & Salis, H. M. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0584-2 · Cited by 133 · see citing works
High-performance CRISPR-Cas12a genome editing for combinatorial genetic screening
Gier, R. A., Budinich, K. A., Evitt, N. H., Cao, Z., Freilich, E., Chen, Q., Qi, J., Lan, Y., Kohli, R. M., & Shi, J. (2020) · Nature Communications · doi:10.1038/s41467-020-17209-1 · Cited by 133 · see citing works
Computational Tools and Resources for CRISPR/Cas Genome Editing
Li, C., Chu, W., Gill, R. A., Sang, S., Shi, Y., Hu, X., Yang, Y., Zaman, Q. U., & Zhang, B. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.02.006 · Cited by 131 · see citing works
Epistasis-driven identification of SLC25A51 as a regulator of human mitochondrial NAD import
Girardi, E., Agrimi, G., Goldmann, U., Fiume, G., Lindinger, S., Sedlyarov, V., Srndic, I., Gürtl, B., Agerer, B., Kartnig, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19871-x · Cited by 123 · see citing works
Combinatorial CRISPR screen identifies fitness effects of gene paralogues
Thompson, N., Ranzani, M., van der Weyden, L., Iyer, V., Offord, V., Droop, A., Behan, F. M., Gonçalves, E., Speak, A. O., Iorio, F., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21478-9 · Cited by 122 · see citing works
Discovery of synthetic lethal and tumor suppressor paralog pairs in the human genome
Parrish, P. C. R., Thomas, J. D., Gabel, A. M., Kamlapurkar, S., Bradley, R. K., & Berger, A. H. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109597 · Cited by 118 · see citing works
Recent advances in combinatorial drug screening and synergy scoring
Pemovska, T., Bigenzahn, J. W., & Superti‐Furga, G. (2018) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2018.07.008 · Cited by 117 · see citing works
Aregger, M., Lawson, K. A., Billmann, M., Costanzo, M., Tong, A. H. Y., Chan, K., Rahman, M., Brown, K. R., Ross, C., Ušaj, M., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-0211-z · Cited by 112 · see citing works
Liao, C., Ttofali, F., Slotkowski, R., Denny, S. R., Cecil, T. D., Leenay, R. T., Keung, A. J., & Beisel, C. L. (2019) · Nature Communications · doi:10.1038/s41467-019-10747-3 · Cited by 102 · see citing works
CRISPR technologies for stem cell engineering and regenerative medicine
Hsu, M., Chang, Y., Truong, V. A., Lai, P., Nguyen, T. K. N., & Hu, Y. (2019) · Biotechnology Advances · doi:10.1016/j.biotechadv.2019.107447 · Cited by 105 · see citing works
Acharya, S., Mishra, A., Paul, D., Ansari, A. H., Azhar, M., Kumar, M., Rauthan, R., Sharma, N., Aich, M., Sinha, D., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818461116 · Cited by 100 · see citing works
CRISPR screens in plants: approaches, guidelines, and future prospects
Gaillochet, C., Develtere, W., & Jacobs, T. B. (2021) · The Plant Cell · doi:10.1093/plcell/koab099 · Cited by 102 · see citing works
Shi, X., Reinstadler, B. M., Shah, H., To, T., Byrne, K., Summer, L. C., Calvo, S. E., Goldberger, O., Doench, J. G., Mootha, V. K., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30126-9 · Cited by 102 · see citing works
Self-citationViswanatha, R., Li, Z., Hu, Y., & Perrimon, N. (2018) · eLife · doi:10.7554/elife.36333 · Cited by 79 · see citing works
Functional Genomics via CRISPR–Cas
Ford, K. M., McDonald, D., & Mali, P. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.06.034 · Cited by 98 · see citing works
CRISPR screens for functional interrogation of immunity
Shi, H., Doench, J. G., & Chi, H. (2022) · Nature reviews. Immunology · doi:10.1038/s41577-022-00802-4 · Cited by 96 · see citing works
Self-citationA network of human functional gene interactions from knockout fitness screens in cancer cells
Kim, E., Dede, M., Lenoir, W. F., Wang, G., Srinivasan, S., Colic, M., & Hart, T. (2019) · Life Science Alliance · doi:10.26508/lsa.201800278 · Cited by 84 · see citing works
CRISPR-Cas9 library screening approach for anti-cancer drug discovery: overview and perspectives
Chan, Y.-T., Lu, Y., Wu, J., Zhang, C., Tan, H., Bian, Z., Wang, N., & Feng, Y. (2022) · Theranostics · doi:10.7150/thno.71144 · Cited by 91 · see citing works
Revolutionizing DNA repair research and cancer therapy with CRISPR–Cas screens
Awwad, S. W., Serrano-Benítez, A., Thomas, J. C., Gupta, V., & Jackson, S. P. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-022-00571-x · Cited by 87 · see citing works
Synthetic Lethality and Cancer – Penetrance as the Major Barrier
Ryan, C. J., Bajrami, I., & Lord, C. J. (2018) · Trends in cancer · doi:10.1016/j.trecan.2018.08.003 · Cited by 86 · see citing works
Single-Cell Multi-omics: An Engine for New Quantitative Models of Gene Regulation
Packer, J. S., & Trapnell, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.06.001 · Cited by 84 · see citing works
The tracrRNA in CRISPR Biology and Technologies
Liao, C., & Beisel, C. L. (2021) · Annual Review of Genetics · doi:10.1146/annurev-genet-071719-022559 · Cited by 82 · see citing works
Truong, V. A., Hsu, M., Nguyen, N. T. K., Lin, M., Shen, C., Lin, C., & Hu, Y. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz267 · Cited by 78 · see citing works
Modulating gene regulation to treat genetic disorders
Matharu, N. K., & Ahituv, N. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-0083-7 · Cited by 75 · see citing works
Black, J. B., McCutcheon, S. R., Dube, S., Barrera, A., Klann, T. S., Rice, G., Adkar, S. S., Soderling, S. H., Reddy, T. E., & Gersbach, C. A. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108460 · Cited by 71 · see citing works
Synthetic lethal strategies for the development of cancer therapeutics
Ngoi, N. Y. L., Gallo, D., Torrado, C., Nardo, M., Durocher, D., & Yap, T. A. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00966-z · Cited by 78 · see citing works
Functional Genomics for Cancer Drug Target Discovery
Haley, B., & Roudnicky, F. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.04.006 · Cited by 73 · see citing works
Multiplexed orthogonal genome editing and transcriptional activation by Cas12a
Breinig, M., Schweitzer, A. Y., Herianto, A. M., Revia, S., Schaefer, L. M., Wendler, L., Galvez, A. C., & Tschaharganeh, D. F. (2018) · Nature Methods · doi:10.1038/s41592-018-0262-1 · Cited by 68 · see citing works
Recent Advances in the Application of CRISPR/Cas9 Gene Editing System in Poultry Species
Khwatenge, C. N., & Nahashon, S. N. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.627714 · Cited by 72 · see citing works
Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines
Kegel, B. D., Quinn, N., Thompson, N., Adams, D. J., & Ryan, C. J. (2021) · Cell Systems · doi:10.1016/j.cels.2021.08.006 · Cited by 65 · see citing works
Gene editing and its applications in biomedicine
Li, G., Li, X., Zhuang, S., Wang, L., Zhu, Y., Chen, Y., Sun, W. C., Wu, Z., Zhou, Z. L., Chen, J., et al. (2022) · Science China Life Sciences · doi:10.1007/s11427-021-2057-0 · Cited by 65 · see citing works
Hegde, M., Strand, C., Hanna, R. E., & Doench, J. G. (2018) · PLOS ONE · doi:10.1371/journal.pone.0197547 · Cited by 66 · see citing works
Self-citationAnvar, N. E., Lin, C., Ma, X., Wilson, L., Steger, R., Sangree, A. K., Colic, M., Wang, S. H., Doench, J. G., & Hart, T. (2024) · Nature Communications · doi:10.1038/s41467-024-47795-3 · Cited by 62 · see citing works
Self-citationIn vivo profiling of metastatic double knockouts through CRISPR–Cpf1 screens
Chow, R. D.-W., Wang, G., Ye, L., Codina, A., Kim, H. R., Shen, L., Dong, M. B., Errami, Y., & Chen, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0371-5 · Cited by 63 · see citing works
Targeting synthetic lethal paralogs in cancer
Ryan, C. J., Mehta, I., Kebabci, N., & Adams, D. J. (2023) · Trends in cancer · doi:10.1016/j.trecan.2023.02.002 · Cited by 59 · see citing works
Minimized combinatorial CRISPR screens identify genetic interactions in autophagy
Diehl, V., Wegner, M., Grumati, P., Husnjak, K., Schaubeck, S., Gubaš, A., Shah, V. J., Polat, I. H., Langschied, F., Prieto‐Garcia, C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab309 · Cited by 54 · see citing works
SNP-CRISPR: A Web Tool for SNP-Specific Genome Editing
Chen, C., Rodiger, J., Chung, V., Viswanatha, R., Mohr, S. E., Hu, Y., & Perrimon, N. (2019) · G3 Genes Genomes Genetics · doi:10.1534/g3.119.400904 · Cited by 57 · see citing works
Karakus, U., Pohl, M. O., & Stertz, S. (2019) · Journal of Virology · doi:10.1128/jvi.01357-19 · Cited by 55 · see citing works
Towards quantitative and multiplexed in vivo functional cancer genomics
Winters, I. P., Murray, C. W., & Winslow, M. M. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0053-7 · Cited by 53 · see citing works
Peng, H., Zheng, Y., Zhao, Z., Liu, T., & Li, J. (2018) · Bioinform. · doi:10.1093/bioinformatics/bty558 · Cited by 52 · see citing works
Zamanighomi, M., Jain, S. S., Ito, T., Pal, D., Daley, T., & Sellers, W. R. (2019) · Genome biology · doi:10.1186/s13059-019-1745-9 · Cited by 53 · see citing works
VanderSluis, B., Costanzo, M., Billmann, M., Ward, H. N., Myers, C. L., Andrews, B., & Boone, C. M. (2018) · Current Opinion in Microbiology · doi:10.1016/j.mib.2018.06.004 · Cited by 49 · see citing works
Computational methods, databases and tools for synthetic lethality prediction
Wang, J., Zhang, Q., Han, J., Zhao, Y., Zhao, C., Yan, B., Dai, C., Wu, L., Wen, Y., Zhang, Y., et al. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac106 · Cited by 50 · see citing works
Massively parallel assessment of human variants with base editor screens
Hanna, R. E., Hegde, M., Fagre, C. R., DeWeirdt, P. C., Sangree, A. K., Szegletes, Z., Griffith, A., Feeley, M. N., Sanson, K. R., Baidi, Y., et al. (2020) · doi:10.1101/2020.05.17.100818 · Cited by 314 · see citing works
Self-citationA Three-Way Combinatorial CRISPR Screen for Analyzing Interactions among Druggable Targets
Zhou, P., Chan, B. K. C., Wan, Y. K., Yuen, C. T. L., Choi, G. C. G., Li, X., Tong, C. S. W., Zhong, S. S. W., Sun, J., Bao, Y., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108020 · Cited by 46 · see citing works
Bidirectional epigenetic editing reveals hierarchies in gene regulation
Pacalin, N. M., Steinhart, Z., Shi, Q., Belk, J. A., Dorovskyi, D., Kraft, K., Parker, K. R., Shy, B. R., Marson, A., & Chang, H. Y. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02213-3 · Cited by 48 · see citing works
Time for remodeling: SNF2-family DNA translocases in replication fork metabolism and human disease
Joseph, S. A., Taglialatela, A., Leuzzi, G., Huang, J., Cuella-Martin, R., & Ciccia, A. (2020) · DNA repair · doi:10.1016/j.dnarep.2020.102943 · Cited by 47 · see citing works
Cytokinins: A Genetic Target for Increasing Yield Potential in the CRISPR Era
Mandal, S., Ghorai, M., Anand, U., Roy, D., Kant, N., Mishra, T., Mane, A. B., Jha, N. K., Lal, M. K., Tiwari, R. K., et al. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.883930 · Cited by 45 · see citing works
RetractedTechnologies and Computational Analysis Strategies for CRISPR Applications
Clement, K., Hsu, J. Y., Canver, M. C., Joung, J. K., & Pinello, L. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.06.012 · Cited by 44 · see citing works
Chronos: a CRISPR cell population dynamics modelPreprint
Dempster, J. M., Boyle, I., Vázquez, F., Root, D. E., Boehm, J. S., Hahn, W. C., Tsherniak, A., & McFarland, J. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.25.432728 · Cited by 44 · see citing works
Self-citationBenchmarking machine learning methods for synthetic lethality prediction in cancer
Feng, Y., Long, Y., Wang, H., Ouyang, Y., Li, Q., Wu, M., & Zheng, J. (2024) · Nature Communications · doi:10.1038/s41467-024-52900-7 · Cited by 38 · see citing works
Review of applications of CRISPR-Cas9 gene-editing technology in cancer research
Zhao, Z., Li, C., Tong, F., Deng, J., Huang, G., & Sang, Y. (2021) · Biological Procedures Online · doi:10.1186/s12575-021-00151-x · Cited by 40 · see citing works
Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality
Benfatto, S., Serçin, Ö., Dejure, F. R., Abdollahi, A., Zenke, F. T., & Mardin, B. R. (2021) · Molecular Cancer · doi:10.1186/s12943-021-01405-8 · Cited by 37 · see citing works
CRISPR–Cas9 Genetic Analysis of Virus–Host Interactions
Gebre, M. S., Nomburg, J., & Gewurz, B. E. (2018) · Viruses · doi:10.3390/v10020055 · Cited by 36 · see citing works
Genetic interaction networks in cancer cells
Mair, B., Moffat, J., Boone, C. M., & Andrews, B. (2019) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2019.03.002 · Cited by 32 · see citing works
Comparative optimization of combinatorial CRISPR screens
Li, R., Klingbeil, O., Monducci, D., Young, M. J., Rodriguez, D. J., Bayyat, Z., Dempster, J. M., Kesar, D., Yang, X., Zamanighomi, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30196-9 · Cited by 36 · see citing works
Tutorial: design and execution of CRISPR in vivo screens
Braun, C. J., Adames, A. C., Saur, D., & Rad, R. (2022) · Nature Protocols · doi:10.1038/s41596-022-00700-y · Cited by 35 · see citing works
Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch
Kinsler, G., Schmidlin, K., Newell, D., Eder, R., Apodaca, S., Lam, G., Petrov, D. A., & Geiler‐Samerotte, K. (2023) · Journal of Molecular Evolution · doi:10.1007/s00239-023-10114-3 · Cited by 34 · see citing works
Sung, L., Wu, M., Lin, M., Hsu, M., Truong, V. A., Shen, C., Tu, Y., Hwang, K., Tu, A. P., Chang, Y., et al. (2019) · Biotechnology and Bioengineering · doi:10.1002/bit.26915 · Cited by 34 · see citing works
A Road Map to Personalizing Targeted Cancer Therapies Using Synthetic Lethality
Parameswaran, S., Kundapur, D., Vizeacoumar, F. S., Freywald, A., Uppalapati, M., & Vizeacoumar, F. J. (2018) · Trends in cancer · doi:10.1016/j.trecan.2018.11.001 · Cited by 34 · see citing works
MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Klingbeil, O., Skopelitis, D. S., Tonelli, C., Yoshimoto, T., Alpsoy, A., Panepinto, M. C., Minicozzi, F., Merrill, J. R., Cafiero, A. M., Aggarwal, D., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-1529 · Cited by 31 · see citing works
CRISPR and Target-Specific DNA Endonucleases for Efficient DNA Knock-in in Eukaryotic Genomes.
Lee, S. H., Kim, S., & Hur, J. K. (2018) · Europe PMC (PubMed Central) · doi:10.14348/molcells.2018.0408 · Cited by 32 · see citing works
EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction
Wan, F., Li, S., Tian, T., Lei, Y., Zhao, D. Y., & Zeng, J. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00112 · Cited by 31 · see citing works
Lenoir, W. F., Morgado, M. C., DeWeirdt, P. C., McLaughlin, M. E., Griffith, A. L., Sangree, A. K., Feeley, M. N., Anvar, N. E., Kim, E., Bertolet, L. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26867-8 · Cited by 29 · see citing works
Self-citationPrediction and diversity of tracrRNAs from type II CRISPR-Cas systems
Chyou, T., & Brown, C. M. (2018) · RNA Biology · doi:10.1080/15476286.2018.1498281 · Cited by 31 · see citing works
Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens
Srivatsa, S., Montazeri, H., Bianco, G., Coto‐Llerena, M., Marinucci, M., Ng, C. K. Y., Piscuoglio, S., & Beerenwinkel, N. (2022) · Nature Communications · doi:10.1038/s41467-022-35378-z · Cited by 29 · see citing works
Hefzi, H., Martínez‐Monge, I., de Mas, I. M., Cowie, N. L., Toledo, A. G., Noh, S. M., Karottki, K. J. L. C., Decker, M., Arnsdorf, J., Camacho-Zaragoza, J. M., et al. (2025) · Nature Metabolism · doi:10.1038/s42255-024-01193-7 · Cited by 28 · see citing works
- Authors
- Najm, F. J., Strand, C., Donovan, K. F., Hegde, M., Sanson, K. R., Vaimberg, E. W., Sullender, M. E., Hartenian, E., Kalani, Z., Fusi, N., Listgarten, J., Younger, S. T., Bernstein, B. E., Root, D. E., & Doench, J. G.
- Affiliations
- Broad Institute (US)
- Microsoft Research New England (United States) (US)
- Corresponding author
- Doench, John G
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2017-12-18
- Volume
- 36
- Issue
- 2
- Pages
- 179-189
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC5800952
- OpenAlex
- W2781417302
- Cited by
- 279
- References
- 54
- Citations by year
- 2026: 16 · 2025: 22 · 2024: 26 · 2023: 32 · 2022: 26 · 2021: 45 · 2020: 39 · 2019: 36 · 2018: 37
- FWCI
- 12.51
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Cancer Institute (DP1CA216873)
- National Institute of General Medical Sciences (T32GM007226)
- 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 › Genetics › Virus-based gene therapy research
- Keywords
- CRISPR/Cas9, SaCas9, SpCas9, single guide RNA design, dual targeting, synthetic lethality, MAPK signaling, apoptosis, TP53, transcriptional activation, lentiviral vectors
- MeSH terms
- Machine Learning, RNA, Guide, CRISPR-Cas Systems, Epistasis, Genetic, Genetic Testing, Humans, Staphylococcus aureus, Streptococcus pyogenes, Signal Transduction, Tumor Suppressor Protein p53, Apoptosis, Gene Targeting, Mitogen-Activated Protein Kinase Kinases, Gene Knockout Techniques, 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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review