Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens

Cytochrome c and dATP-Dependent Formation of Apaf-1/Caspase-9 Complex Initiates an Apoptotic Protease Cascade

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

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

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

Mitochondrial membrane permeabilization in cell death

Kroemer, G., Galluzzi, L., & Brenner, C. (2007) · Physiological Reviews · doi:10.1152/physrev.00013.2006 · Cited by 3,598

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

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

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

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

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

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 2,089

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 2,392

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

A GPX4-dependent cancer cell state underlies the clear-cell morphology and confers sensitivity to ferroptosis

Zou, 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

Cytochrome 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 753

Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells

Mimitou, 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

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 567

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

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 490

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 457

Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects

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 433

Continuous 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

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

Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks

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

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

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

SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance

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 238

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 215

Design and analysis of CRISPR–Cas experiments

Hanna, R. E., & Doench, J. G. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0490-7 · Cited by 216

Synthetic 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 214

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 197

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 171

Applications 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 180

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 160

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

Highly efficient multiplex editing: one‐shot generation of 8× Nicotiana benthamiana and 12× Arabidopsis mutants

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 143

Paralog knockout profiling identifies DUSP4 and DUSP6 as a digenic dependence in MAPK pathway-driven cancers

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 154

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens

Pan, 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 134

ALC1 links chromatin accessibility to PARP inhibitor response in homologous recombination-deficient cells

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 142

Genetic interaction mapping and exon-resolution functional genomics with a hybrid Cas9–Cas12a platform

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

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 150

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 138

RNAi/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 140

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 141

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

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 135

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 134

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

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 120

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 112

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 122

Systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism

Aregger, M., Lawson, K. A., Billmann, M., Costanzo, M., Tong, A. H. Y., Chan, K., Rahman, M., Brown, K. R., Ross, C., Usaj, M., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-0211-z · Cited by 115

Modular one-pot assembly of CRISPR arrays enables library generation and reveals factors influencing crRNA biogenesis

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 106

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 106

Francisella novicida Cas9 interrogates genomic DNA with very high specificity and can be used for mammalian genome editing

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 102

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

Combinatorial GxGxE CRISPR screen identifies SLC25A39 in mitochondrial glutathione transport linking iron homeostasis to OXPHOS

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 104

Pooled genome-wide CRISPR screening for basal and context-specific fitness gene essentiality in Drosophila cells

Viswanatha, R., Li, Z., Hu, Y., & Perrimon, N. (2018) · eLife · doi:10.7554/elife.36333 · Cited by 79

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 103

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 102

A 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 85

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 93

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 93

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 91

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 85

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 91

CRISPRai for simultaneous gene activation and inhibition to promote stem cell chondrogenesis and calvarial bone regeneration

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

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 79

Master Regulators and Cofactors of Human Neuronal Cell Fate Specification Identified by CRISPR Gene Activation Screens

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

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 81

Functional Genomics for Cancer Drug Target Discovery

Haley, B., & Roudnicky, F. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.04.006 · Cited by 75

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

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 76

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 67

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 66

Uncoupling of sgRNAs from their associated barcodes during PCR amplification of combinatorial CRISPR screens

Hegde, M., Strand, C., Hanna, R. E., & Doench, J. G. (2018) · PLOS ONE · doi:10.1371/journal.pone.0197547 · Cited by 66

Efficient gene knockout and genetic interaction screening using the in4mer CRISPR/Cas12a multiplex knockout platform

Anvar, 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

In 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 64

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

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 55

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

Breaking the Convention: Sialoglycan Variants, Coreceptors, and Alternative Receptors for Influenza A Virus Entry

Karakus, U., Pohl, M. O., & Stertz, S. (2019) · Journal of Virology · doi:10.1128/jvi.01357-19 · Cited by 55

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 54

Recognition of CRISPR/Cas9 off-target sites through ensemble learning of uneven mismatch distributions

Peng, H., Zheng, Y., Zhao, Z., Liu, T., & Li, J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty558 · Cited by 57

GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens

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

Integrating genetic and protein–protein interaction networks maps a functional wiring diagram of a cell

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 50

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 52

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

A 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

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 49

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 48

Technologies 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 45

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

Benchmarking 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 41

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 42

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

CRISPR–Cas9 Genetic Analysis of Virus–Host Interactions

Gebre, M. S., Nomburg, J., & Gewurz, B. E. (2018) · Viruses · doi:10.3390/v10020055 · Cited by 37

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 33

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 37

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 38

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

Combining orthogonal CRISPR and CRISPRi systems for genome engineering and metabolic pathway modulation in Escherichia coli

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

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

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

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

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 33

Discovery of putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in acute myeloid leukemia cells

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 31

Prediction 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

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

Multiplex genome editing eliminates lactate production without impacting growth rate in mammalian cells

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

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 37

Abstract 2950: CRISPR/saCas9 and CRISPR/spCas9 systems for combinatorial genetic screens (CRISPR-KO, CRISPRa, CRISPRi)

Isachenko, N., Aleksanyan, G., Diehl, P., & Tedesco, D. (2024) · Cancer Research · doi:10.1158/1538-7445.am2024-2950

PrePAIRing Cas9s for screening success

Zhou, Z. L., & Wei, W. (2018) · Nature Biotechnology · doi:10.1038/nbt.4075 · Cited by 2

Generation of dual-gRNA library for combinatorial CRISPR screening of synthetic lethal gene pairs

Tang, S., Wu, X., Liu, J., Zhang, Q., Wang, X., Shao, S., Gökbağ, B., Fan, K., Liu, X., Li, F., et al. (2022) · STAR Protocols · doi:10.1016/j.xpro.2022.101556 · Cited by 14

Big Papi uncovers genetic interactions

(2018) · Nature Methods · doi:10.1038/nmeth.4589