Mapping the Genetic Landscape of Human Cells
Open accessAbstract
Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.
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Direct capture Perturb-seq can be used to study genetic interactions between cholesterol biosynthesis and DNA repair genes.
“we next explored the use of direct capture Perturb-seq to study genetic interactions, specifically a complex set of GIs we recently identified between genes that control cholesterol biosynthesis (e.g. FDPS, MVD, and IDI1) and genes that facilitate DNA repair (e.g. ATR and genes encoding components of the 9–1-1 complex)28.”
From Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing (2020) · cites this paper as [28]
An earlier model held that repressing cholesterol biosynthesis causes toxic intermediates to accumulate, producing replication stress and arrest after genotoxin exposure.
“We previously proposed a model for GIs between cholesterol biosynthesis and DNA repair genes wherein repression of the former leads to the buildup of toxic metabolic intermediates in cells, which then cause replicative stress and genotoxin-activated cell cycle arrest28.”
From Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing (2020) · cites this paper as [28]
In the data, rates of novel sgRNA pairs varied from 0.09 to 0.15 across experiments, roughly consistent with a previous report.
“In our data, we observed rates of novel pairs varying from 0.09–0.15 across experiments, which is roughly consistent with a previous report28.”
From Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing (2020) · cites this paper as [28]
Functionally related genes interact similarly, making the genetic interaction manifold highly constrained and enabling imputation strategies.
“We and others have established that functionally related genes interact similarly—in geometric terms the GI manifold is therefore highly constrained, enabling imputation strategies (1, 2, 7, 12, 29).”
From Exploring genetic interaction manifolds constructed from rich single-cell phenotypes (2019) · cites this paper as [12]
Primary human cell types such as skin fibroblasts or blood cells can be reprogrammed into iPSCs by transient expression of four transcription factors, including the Yamanaka factors.
“Primary cell types readily obtained from human adult donors, such as skin fibroblasts or peripheral blood cells, can be reprogrammed to become induced pluripotent stem cells (iPSCs) by the transient expression of four transcription factors, such as the so-called “Yamanaka factors”89,90”
From CRISPR-based functional genomics for neurological disease (2020) · cites this paper as [89]
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Cites
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336 · see citing works
Szklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N. T., Roth, A., Bork, P., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw937 · Cited by 6,980 · see citing works
Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression
Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A., Weissman, J. S., Arkin, A. P., & Lim, W. A. (2013) · Cell · doi:10.1016/j.cell.2013.02.022 · Cited by 5,016 · see citing works
Self-citationCytoscape 2.8: new features for data integration and network visualization
Smoot, M. E., Ono, K., Ruscheinski, J., Wang, P., & Ideker, T. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq675 · Cited by 4,770 · see citing works
CRISPR-Mediated Modular RNA-Guided Regulation of Transcription in Eukaryotes
Gilbert, L. A., Larson, M. H., Morsut, L., Liu, Z., Brar, G. A., Torres, S. E., Stern-Ginossar, N., Brandman, O., Whitehead, E. H., Doudna, J. A., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.044 · Cited by 3,696 · see citing works
Self-citationDefining a Cancer Dependency Map
Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., Gill, S., Harrington, W. F., Pantel, S., Krill-Burger, J. M., et al. (2017) · Cell · doi:10.1016/j.cell.2017.06.010 · Cited by 3,276 · see citing works
Open source clustering software
de Hoon, M., Imoto, S., Nolan, J., & Miyano, S. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth078 · Cited by 3,043 · see citing works
Java Treeview—extensible visualization of microarray data
Saldanha, A. J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth349 · Cited by 2,991 · see citing works
A subcellular map of the human proteome
Thul, P. J., Åkesson, L., Wiking, M., Mahdessian, D., Geladaki, A., Ait Blal, H., Alm, T., Asplund, A., Björk, L., Breckels, L. M., et al. (2017) · Science · doi:10.1126/science.aal3321 · Cited by 2,813 · 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
Self-citationThe Genetic Landscape of a Cell
Costanzo, M., Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., Ding, H., Koh, J. L. Y., Toufighi, K., Mostafavi, S., et al. (2010) · Science · doi:10.1126/science.1180823 · Cited by 2,162 · see citing works
Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants
Tong, A. H. Y., Evangelista, M., Parsons, A. B., Xu, H., Bader, G. D., Pagé, N., Robinson, M., Raghibizadeh, S., Hogue, C. W. V., Bussey, H., et al. (2001) · Science · doi:10.1126/science.1065810 · Cited by 2,138 · 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
The DNA Damage Response: Ten Years After
Harper, J. W., & Elledge, S. J. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.11.015 · Cited by 1,705 · see citing works
Identification and characterization of essential genes in the human genome
Wang, T., Birsoy, K., Hughes, N. W., Krupczak, K. M., Post, Y., Wei, J. J., Lander, E. S., & Sabatini, D. M. (2015) · Science · doi:10.1126/science.aac7041 · Cited by 1,617 · see citing works
High-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
MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins
Calvo, S. E., Clauser, K. R., & Mootha, V. K. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1003 · Cited by 1,251 · 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
High-throughput functional genomics using CRISPR-Cas9
Shalem, O., Sanjana, N. E., & Zhang, F. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3899 · Cited by 1,233 · 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
Self-citationHorlbeck, M. A., Gilbert, L. A., Villalta, J. E., Adamson, B., Pak, R. A., Chen, Y., Fields, A. P., Park, C. Y., Corn, J. E., Kampmann, M., et al. (2016) · eLife · doi:10.7554/elife.19760 · Cited by 894 · see citing works
Self-citationSchuldiner, M., Collins, S. R., Thompson, N. J., Denic, V., Bhamidipati, A., Punna, T., Ihmels, J., Andrews, B., Boone, C., Greenblatt, J. F., et al. (2005) · Cell · doi:10.1016/j.cell.2005.08.031 · Cited by 870 · see citing works
Self-citationCollins, S. R., Miller, K. M., Maas, N. L., Roguev, A., Fillingham, J., Chu, C. S., Schuldiner, M., Gebbia, M., Recht, J., Shales, M., et al. (2007) · Nature · doi:10.1038/nature05649 · Cited by 869 · see citing works
Self-citationPrinciples for the Buffering of Genetic Variation
Hartman IV, J. L. (2001) · Science · doi:10.1126/science.291.5506.1001 · Cited by 808 · see citing works
Principles for the buffering of genetic variation
Hartman, J. L., Garvik, B., & Hartwell, L. (2001) · Science · doi:10.1126/science.1056072 · Cited by 808 · see citing works
CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells
Liu, S. J., Horlbeck, M. A., Cho, S. W., Birk, H. S., Malatesta, M., He, D. X., Attenello, F. J., Villalta, J. E., Cho, M. Y., Chen, Y., et al. (2016) · Science · doi:10.1126/science.aah7111 · Cited by 734 · see citing works
Self-citationComprehensive Characterization of Genes Required for Protein Folding in the Endoplasmic Reticulum
Jonikas, M. C., Collins, S. R., Denic, V., Oh, E., Toyama, E. Q., Schmid, V., Weibezahn, J., Schwappach, B., Walter, P., Weissman, J. S., et al. (2009) · Science · doi:10.1126/science.1167983 · Cited by 713 · see citing works
Self-citationWang, T., Yu, H., Hughes, N. W., Liu, B., Kendirli, A., Klein, K., Chen, W. W., Lander, E. S., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.01.013 · Cited by 632 · see citing works
Global, quantitative and dynamic mapping of protein subcellular localization
Itzhak, D. N., Tyanova, S., Cox, J., & Borner, G. H. H. (2016) · eLife · doi:10.7554/elife.16950 · Cited by 595 · see citing works
Accessory subunits are integral for assembly and function of human mitochondrial complex I
Stroud, D. A., Surgenor, E. E., Formosa, L. E., Reljić, B., Frazier, A. E., Dibley, M. G., Osellame, L. D., Stait, T. L., Beilharz, T. H., Thorburn, D. R., et al. (2016) · Nature · doi:10.1038/nature19754 · Cited by 591 · see citing works
Modular epistasis in yeast metabolism
Segrè, D., DeLuna, A., Church, G. M., & Kishony, R. (2005) · Nature Genetics · doi:10.1038/ng1489 · Cited by 575 · see citing works
A DNA Integrity Network in the Yeast Saccharomyces cerevisiae
Pan, X., Ye, P., Yuan, D., Wang, X., Bader, J. S., & Boeke, J. D. (2006) · Cell · doi:10.1016/j.cell.2005.12.036 · Cited by 538 · 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
Rewiring of Genetic Networks in Response to DNA Damage
Bandyopadhyay, S., Mehta, M., Kuo, D., Sung, M.-K., Chuang, R., Jaehnig, E. J., Bodenmiller, B., Licon, K., Copeland, W., Shales, M., et al. (2010) · Science · doi:10.1126/science.1195618 · Cited by 447 · see citing works
Nucleosomes impede Cas9 access to DNA in vivo and in vitro
Horlbeck, M. A., Witkowsky, L. B., Guglielmi, B., Replogle, J. M., Gilbert, L. A., Villalta, J. E., Torigoe, S. E., Tjian, R., & Weissman, J. S. (2016) · eLife · doi:10.7554/elife.12677 · Cited by 415 · see citing works
Self-citationAlendronate Is a Specific, Nanomolar Inhibitor of Farnesyl Diphosphate Synthase
Bergstrom, J. D., Bostedor, R. G., Masarachia, P. J., Reszka, A. A., & Rodan, G. A. (2000) · Archives of Biochemistry and Biophysics · doi:10.1006/abbi.1999.1502 · Cited by 402 · 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
Self-citationCombinatorial 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 · see citing works
Cholesterol Biosynthesis: A Mechanistic Overview
Cerqueira, N. M. F. S. A., Oliveira, E. F., Gesto, D., Santos‐Martins, D., Moreira, C., Moorthy, H. N., Ramos, M. J., & Fernandes, P. A. (2016) · Biochemistry · doi:10.1021/acs.biochem.6b00342 · Cited by 353 · see citing works
A Robust Toolkit for Functional Profiling of the Yeast Genome
Pan, X., Yuan, D., Xiang, D., Wang, X., Sookhai-Mahadeo, S., Bader, J. S., Hieter, P., Spencer, F. A., & Boeke, J. D. (2004) · Molecular Cell · doi:10.1016/j.molcel.2004.09.035 · Cited by 314 · 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
Genetic interaction mapping in mammalian cells using CRISPR interference
Du, D., Roguev, A., Gordon, D. E., Chen, M., Chen, S., Shales, M., Shen, J. P., Ideker, T. E., Mali, P., Qi, L. S., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4286 · Cited by 164 · see citing works
Functional Repurposing Revealed by Comparing S. pombe and S. cerevisiae Genetic Interactions
Frost, A. S., Elgort, M., Brandman, O., Ives, C., Collins, S. R., Miller-Vedam, L. E., Weibezahn, J., Hein, M. Y., Poser, I., Mann, M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.028 · Cited by 161 · see citing works
Self-citationDual gene activation and knockout screen reveals directional dependencies in genetic networks
Boettcher, M., Tian, R., Blau, J. A., Markegard, E., Wagner, R. T., Wu, D., Mo, X., Biton, A., Zaitlen, N., Fu, H., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4062 · Cited by 152 · see citing works
Self-citationHigh-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe
Roguev, A., Wirén, M., Weissman, J. S., & Krogan, N. J. (2007) · Nature Methods · doi:10.1038/nmeth1098 · Cited by 144 · see citing works
Self-citationBabu, M., Arnold, R. R., Bundalovic-Torma, C., Gagarinova, A. G., Wong, K. S., Kumar, A., Stewart, G., Samanfar, B., Aoki, H., Wagih, O., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004120 · Cited by 133 · see citing works
Kampmann, M., Bassik, M. C., & Weissman, J. S. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1307002110 · Cited by 123 · see citing works
Self-citationA map of directional genetic interactions in a metazoan cell
Fischer, B., Sandmann, T., Horn, T. L., Billmann, M., Chaudhary, V., Huber, W. K., & Boutros, M. (2015) · eLife · doi:10.7554/elife.05464 · Cited by 105 · see citing works
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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
A layout algorithm for undirected compound graphs
Doğrusöz, U., Giral, E., Çetintaş, A., Çivril, A., & Demir, E. (2008) · Information Sciences · doi:10.1016/j.ins.2008.11.017 · Cited by 103 · see citing works
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Jost, M., & Weissman, J. S. (2018) · ACS Chemical Biology · doi:10.1021/acschembio.7b00965 · Cited by 88 · see citing works
Self-citationSources of Error in Mammalian Genetic Screens
Sack, L. M., Davoli, T., Xu, Q., Li, M. Z., & Elledge, S. J. (2016) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.116.030973 · Cited by 76 · see citing works
Rosenbluh, J., Mercer, J., Shrestha, Y., Oliver, R., Tamayo, P., Doench, J. G., Tirosh, I., Piccioni, F., Hartenian, E., Horn, H., et al. (2016) · Cell Systems · doi:10.1016/j.cels.2016.09.001 · Cited by 68 · see citing works
Yu, Z., Surface, L. E., Park, C. Y., Horlbeck, M. A., Wyant, G. A., Abu-Remaileh, M., Peterson, T. R., Sabatini, D. M., Weissman, J. S., & O’Shea, E. K. (2018) · eLife · doi:10.7554/elife.36620 · Cited by 55 · see citing works
Self-citationIRBIT is a novel regulator of ribonucleotide reductase in higher eukaryotes
Arnaoutov, A., & Dasso, M. (2014) · Science · doi:10.1126/science.1251550 · Cited by 48 · see citing works
Zhu, B., Wei, H., Wang, Q., Li, F., Dai, J., Yan, C., & Cheng, Y. (2017) · Talanta · doi:10.1016/j.talanta.2017.11.054 · Cited by 45 · see citing works
Baldwin, K. L., Dinh, E. M., Hart, B. M., & Masson, P. (2013) · FEBS Letters · doi:10.1016/j.febslet.2013.02.041 · Cited by 31 · see citing works
Active interaction mapping reveals the hierarchical organization of autophagy
Kramer, M. H., Farré, J.-C., Mitra, K., Yu, M. K., Ono, K., Demchak, B., Licon, K., Flagg, M., Balakrishnan, R., Cherry, J. M., et al. (2017) · Molecular Cell · doi:10.1016/j.molcel.2016.12.024 · Cited by 31 · see citing works
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Oughtred, R., Stark, C., Breitkreutz, B., Rust, J., Boucher, L., Chang, C., Kolas, N. K., O’Donnell, L., Leung, G. C., McAdam, R. F., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1079 · Cited by 1,440 · see citing works
Past, present, and future of CRISPR genome editing technologies
Pacesa, M., Pelea, O., & Jinek, M. (2024) · Cell · doi:10.1016/j.cell.2024.01.042 · Cited by 609 · see citing works
Bock, C., Datlinger, P., Chardon, F. M., Coelho, M. A., Dong, M. B., Lawson, K. A., Lu, T., Maroc, L., Norman, T. M., Song, B., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00093-4 · Cited by 591 · see citing works
Self-citationOpenCell: Endogenous tagging for the cartography of human cellular organization
Cho, N. H., Cheveralls, K. C., Brunner, A.-D., Kim, K., Michaelis, A. C., Raghavan, P., Kobayashi, H., Savy, L., Li, J. Y., Canaj, H., et al. (2022) · Science · doi:10.1126/science.abi6983 · Cited by 567 · see citing works
Self-citationSynthetic 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
Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing
Replogle, J. M., Norman, T. M., Xu, A., Hussmann, J. A., Chen, J., Cogan, J. Z., Meer, E. J., Terry, J. M., Riordan, D. P., Srinivas, N., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0470-y · Cited by 465 · see citing works
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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
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
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Norman, T. M., Horlbeck, M. A., Replogle, J. M., Ge, A. Y., Xu, A., Jost, M., Gilbert, L. A., & Weissman, J. S. (2019) · Science · doi:10.1126/science.aax4438 · Cited by 392 · see citing works
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CRISPR RNA-guided integrases for high-efficiency, multiplexed bacterial genome engineering
Vo, P. L. H., Ronda, C., Klompe, S. E., Chen, E. E., Acree, C., Wang, H. H., & Sternberg, S. H. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-00745-y · Cited by 346 · see citing works
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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
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Bock, C., Datlinger, P., Chardon, F. M., Coelho, M. A., Dong, M. B., Lawson, K. A., Lu, T., Maroc, L., Norman, T. M., Song, B., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00098-7 · Cited by 254 · see citing works
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Chen, Y. E., Bousbaine, D., Veinbachs, A., Atabakhsh, K., Dimas, A., Yu, V. K., Zhao, A., Enright, N. J., Nagashima, K., Belkaid, Y., et al. (2023) · Science · doi:10.1126/science.abp9563 · Cited by 191 · see citing works
Self-citationDevelopment of CRISPR-Cas systems for genome editing and beyond
Zhang, F. (2019) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583519000052 · Cited by 185 · see citing works
CRISPR-based functional genomics for neurological disease
Kampmann, M. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-0373-z · Cited by 163 · see citing works
Self-citationIto, 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
Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors
Replogle, J. M., Bonnar, J. L., Pogson, A. N., Liem, C. R., Maier, N. K., Ding, Y., Russell, B. J., Wang, X., Leng, K., Guna, A., et al. (2022) · eLife · doi:10.7554/elife.81856 · Cited by 150 · see citing works
Self-citationGonatopoulos-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
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
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 136 · 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
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
Tieu, V., Sotillo, E., Bjelajac, J. R., Chen, C., Malipatlolla, M. B., Guerrero, J. A., Xu, P., Quinn, P. J., Fisher, C., Klysz, D. D., et al. (2024) · Cell · doi:10.1016/j.cell.2024.01.035 · Cited by 119 · see citing works
Niche-Selective Inhibition of Pathogenic Th17 Cells by Targeting Metabolic Redundancy
Wu, L., Hollinshead, K. E. R., Hao, Y., Au, C., Kroehling, L., Ng, C., Lin, W.-Y., Li, D., Silva, H. M., Shin, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.014 · Cited by 117 · see citing works
The Hyaluronidase, TMEM2, Promotes ER Homeostasis and Longevity Independent of the UPRER
Schinzel, R. T., Higuchi‐Sanabria, R., Shalem, O., Moehle, E. A., Webster, B. M., Joe, L. K., Bar‐Ziv, R., Frankino, P. A., Durieux, J., Pender, C. L., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.018 · Cited by 115 · 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
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
Identifying Epistasis in Cancer Genomes: A Delicate Affair
van de Haar, J., Canisius, S., Yu, M., Voest, E. E., Wessels, L. F. A., & Ideker, T. E. (2019) · Cell · doi:10.1016/j.cell.2019.05.005 · Cited by 99 · see citing works
Gene-Environment Interaction in the Era of Precision Medicine
Li, J., Li, X., Zhang, S., & Snyder, M. P. (2019) · Cell · doi:10.1016/j.cell.2019.03.004 · Cited by 98 · see citing works
Idiosyncratic epistasis leads to global fitness–correlated trends
Bakerlee, C. W., Ba, A. N. N., Shulgina, Y., Echenique, J. I. R., & Desai, M. M. (2022) · Science · doi:10.1126/science.abm4774 · Cited by 99 · see citing works
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 84 · see citing works
A census of pathway maps in cancer systems biology
Kuenzi, B. M., & Ideker, T. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0240-7 · Cited by 79 · see citing works
Image-based pooled whole-genome CRISPRi screening for subcellular phenotypes
Kanfer, G., Sarraf, S. A., Maman, Y., Baldwin, H. A., Domínguez‐Martín, E., Johnson, K. R., Ward, M. E., Kampmann, M., Lippincott‐Schwartz, J., & Youle, R. J. (2020) · The Journal of Cell Biology · doi:10.1083/jcb.202006180 · Cited by 78 · see citing works
Self-citationComplex synthetic lethality in cancer
Ryan, C. J., Devakumar, L. J. P. S., Pettitt, S. J., & Lord, C. J. (2023) · Nature Genetics · doi:10.1038/s41588-023-01557-x · Cited by 79 · see citing works
Modulating the expression of long non‐coding RNAs for functional studies
Liu, S. J., & Lim, D. A. (2018) · EMBO Reports · doi:10.15252/embr.201846955 · Cited by 72 · see citing works
Ba, A. N. N., Lawrence, K. R., Rego‐Costa, A., Gopalakrishnan, S., Temko, D., Michor, F., & Desai, M. M. (2022) · eLife · doi:10.7554/elife.73983 · Cited by 65 · 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
Comprehensive interrogation of synthetic lethality in the DNA damage response
Fielden, J., Siegner, S. M., Gallagher, D. N., Schröder, M., Stritto, M. R. D., Lam, S., Kobel, L., Schlapansky, M. F., Jackson, S. P., Ćejka, P., et al. (2025) · Nature · doi:10.1038/s41586-025-08815-4 · Cited by 66 · see citing works
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 · see citing works
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 63 · see citing works
High‐resolution mapping of cancer cell networks using co‐functional interactions
Boyle, E. A., Pritchard, J. K., & Greenleaf, W. J. (2018) · Molecular Systems Biology · doi:10.15252/msb.20188594 · Cited by 58 · see citing works
Idiosyncratic and dose-dependent epistasis drives variation in tomato fruit size
Aguirre, L., Hendelman, A., Hutton, S. F., McCandlish, D. M., & Lippman, Z. B. (2023) · Science · doi:10.1126/science.adi5222 · Cited by 59 · see citing works
Li, H., Rukina, D., David, F. P. A., Li, T. Y., Oh, C., Gao, A. W., Katsyuba, E., Sleiman, M. S. B., Komljenović, A., Huang, Q. D., et al. (2019) · Genome Research · doi:10.1101/gr.251983.119 · Cited by 56 · see citing works
In vivo functional screening for systems-level integrative cancer genomics
Weber, J., Braun, C. J., Saur, D., & Rad, R. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0275-9 · Cited by 57 · 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
A landscape of response to drug combinations in non-small cell lung cancer
Nair, N. U., Greninger, P., Zhang, X., Friedman, A. A., Amzallag, A., Cortez, E., Sahu, A. D., Lee, J. S., Dastur, A., Egan, R. K., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-39528-9 · Cited by 58 · see citing works
Hundley, F. V., Sanvisens, N., Marin, H. C., Carr, K. L., Tian, R., & Toczyski, D. P. (2021) · Molecular Cell · doi:10.1016/j.molcel.2021.01.014 · Cited by 55 · see citing works
Mitochondrial respiration contributes to the interferon gamma response in antigen-presenting cells
Kiritsy, M. C., McCann, K. J., Mott, D., Holland, S. M., Behar, S. M., Sassetti, C. M., & Olive, A. J. (2021) · eLife · doi:10.7554/elife.65109 · Cited by 56 · see citing works
Thinking About Schizophrenia in an Era of Genomic Medicine
Weinberger, D. R. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.18111275 · Cited by 53 · 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
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
“Especially as the depth and types of mutations increases, another potential future direction is to merge base editing screens with combinatorial technologies (Han et al., 2017; Horlbeck et al., 2018; Najm et al., 2017; Sanson et al., 2019) to enable screens with multiple edits per cell.”
Prediction of Synthetic Lethal Interactions in Human Cancers Using Multi-View Graph Auto-Encoder
Hao, Z., Wu, D., Fang, Y., Wu, M., Cai, R., & Li, X. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3079302 · Cited by 48 · 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
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 44 · see citing works
Defining the ATPome reveals cross-optimization of metabolic pathways
Bennett, N. K., Nguyen, M. K., Darch, M. A., Nakaoka, H. J., Cousineau, D., ten Hoeve, J., Graeber, T. G., Schuelke, M., Maltepe, E., Kampmann, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18084-6 · Cited by 39 · see citing works
Self-citationLeveraging genetic interactions for adverse drug-drug interaction prediction
Qian, S., Liang, S., & Yu, H. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007068 · Cited by 41 · see citing works
GEARS: Predicting transcriptional outcomes of novel multi-gene perturbationsPreprint
Roohani, Y., Huang, K., & Leskovec, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.12.499735 · Cited by 40 · see citing works
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 38 · see citing works
Miyahira, A. K., Sharp, A., Ellis, L., Jones, J. C., Kaochar, S., Larman, H. B., Quigley, D. A., Ye, H., Simons, J. W., Pienta, K. J., et al. (2019) · The Prostate · doi:10.1002/pros.23934 · Cited by 38 · see citing works
Nucleotide depletion promotes cell fate transitions by inducing DNA replication stress
Do, B. T., Hsu, P. P., Vermeulen, S. Y., Wang, Z., Hirz, T., Abbott, K. L., Aziz, N., Replogle, J. M., Bjelosevic, S., Paolino, J. D., et al. (2024) · Developmental Cell · doi:10.1016/j.devcel.2024.05.010 · Cited by 36 · see citing works
Self-citationCheng, Z., Wu, J., Liu, J., Min, D., Liu, D., Li, W., & Yu, H. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac554 · Cited by 38 · 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
Cellular response to small molecules that selectively stall protein synthesis by the ribosome
Liaud, N., Horlbeck, M. A., Gilbert, L. A., Gjoni, K., Weissman, J. S., & Cate, J. H. D. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1008057 · Cited by 36 · see citing works
Self-citationHazelbaker, D. Z., Beccard, A., Angelini, G., Mazzucato, P., Messana, A., Lam, D., Eggan, K. C., & Barrett, L. E. (2020) · Scientific Reports · doi:10.1038/s41598-020-57500-1 · Cited by 36 · 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
Emergence and propagation of epistasis in metabolic networks
Kryazhimskiy, S. (2021) · eLife · doi:10.7554/elife.60200 · Cited by 32 · see citing works
Mevalonate pathway activity as a determinant of radiation sensitivity in head and neck cancer
Ricco, N., Flor, A. C., Wolfgeher, D., Efimova, E. V., Ramamurthy, A., Appelbe, O. K., Brinkman, J. A., Truman, A. W., Spiotto, M. T., & Kron, S. J. (2019) · Molecular Oncology · doi:10.1002/1878-0261.12535 · Cited by 32 · see citing works
Genomics-guided pre-clinical development of cancer therapies
Francies, H. E., McDermott, U., & Garnett, M. J. (2020) · Nature Cancer · doi:10.1038/s43018-020-0067-x · Cited by 32 · 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
Bennett, N. K., Lee, M., Orr, A. L., & Nakamura, K. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2307904121 · Cited by 32 · see citing works
Self-citationCRISPRi–TnSeq maps genome-wide interactions between essential and non-essential genes in bacteria
Jana, B., Liu, X., Dénéréaz, J., Park, H., Leshchiner, D. R., Liu, B., Gallay, C., Zhu, J., Veening, J., & van Opijnen, T. (2024) · Nature Microbiology · doi:10.1038/s41564-024-01759-x · Cited by 36 · see citing works
A model and test for coordinated polygenic epistasis in complex traits
Sheppard, B. K., Rappoport, N., Loh, P., Sanders, S., Zaitlen, N., & Dahl, A. W. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1922305118 · 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
CRISPRi functional genomics in bacteria and its application to medical and industrial research
Enright, A. L., Heelan, W. J., Ward, R. D., & Peters, J. M. (2024) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00170-22 · Cited by 31 · see citing works
Mapping the protein–protein and genetic interactions of cancer to guide precision medicine
Bouhaddou, M., Eckhardt, M., Naing, Z. Z. C., Kim, M., Ideker, T., & Krogan, N. J. (2019) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2019.04.005 · Cited by 30 · see citing works
Drainas, A. P., Lambuta, R. A., Ivanova, I., Serçin, Ö., Sarropoulos, I., Smith, M. L., Efthymiopoulos, T., Raeder, B., Stütz, A. M., Waszak, S. M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.03.029 · Cited by 30 · see citing works
Chen, G. M., Azzam, A., Ding, Y., Barrett, D. M., Grupp, S. A., & Tan, K. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-3888 · Cited by 28 · see citing works
Synthetic lethal gene pairs: Experimental approaches and predictive models
Tang, S., Gökbağ, B., Fan, K., Shao, S., Huo, Y., Wu, X., Cheng, L., & Li, L. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.961611 · Cited by 27 · see citing works
She, R., Luo, J.-C., & Weissman, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad329 · Cited by 23 · see citing works
Self-citationThe biological essence of synthetic lethality: Bringing new opportunities for cancer therapy
Ge, M., Luo, J., Wu, Y., Shen, G., & Kuang, X. (2024) · MedComm – Oncology · doi:10.1002/mog2.70 · Cited by 28 · see citing works
A Quantitative Genetic Interaction Map of HIV Infection
Gordon, D. E., Watson, A., Roguev, A., Zheng, S., Jang, G. Μ., Kane, J., Xu, J., Guo, J. Z., Stevenson, E. J., Swaney, D. L., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.02.004 · Cited by 24 · see citing works
Semesta, K. M., Tian, R., Kampmann, M., von Zastrow, M., & Tsvetanova, N. G. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009103 · Cited by 26 · see citing works
Self-citationMapping genetic interactions in cancer: a road to rational combination therapies
Tutuncuoglu, B., & Krogan, N. J. (2019) · Genome Medicine · doi:10.1186/s13073-019-0680-4 · Cited by 25 · see citing works
Cold shock domain–containing protein E1 is a posttranscriptional regulator of the LDL receptor
Smith, G. A., Padmanabhan, A., Lau, B. H.-F., Pampana, A., Li, L., Lee, C. Y., Pelonero, A., Nishino, T., Sadagopan, N., Xia, V. Q., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj8670 · Cited by 25 · see citing works
Sun, S., Baryshnikova, A., Brandt, N., & Gresham, D. (2020) · Molecular Systems Biology · doi:10.15252/msb.20199167 · Cited by 24 · see citing works
ATRAID regulates the action of nitrogen-containing bisphosphonates on bone
Surface, L. E., Burrow, D. T., Li, J., Park, J., Kumar, S., Lyu, C., Song, N., Yu, Z., Rajagopal, A., Bae, Y., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aav9166 · Cited by 25 · see citing works
Self-citationMulti-view graph convolutional network for cancer cell-specific synthetic lethality prediction
Fan, K., Tang, S., Gökbağ, B., Cheng, L., & Li, L. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2022.1103092 · Cited by 24 · see citing works
Vasudevan, H. N., Payne, E., Delley, C. L., Liu, S. J., Mirchia, K., Sale, M. J., Lastella, S., Nunez, M. S., Lucas, C. G., Eaton, C. D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44755-9 · Cited by 23 · see citing works
McFaline‐Figueroa, J. L., Srivatsan, S. R., Hill, A. J., Gasperini, M. J., Jackson, D. L., Saunders, L. M., Domcke, S., Regalado, S. G., Lazarchuck, P., Alvarez, S., et al. (2024) · Cell Genomics · doi:10.1016/j.xgen.2023.100487 · Cited by 23 · see citing works
Applications of CRISPR-Cas in Bioengineering, Biotechnology, and Translational Research
Lau, C. (2018) · The CRISPR Journal · doi:10.1089/crispr.2018.0026 · Cited by 22 · see citing works
Highly Combinatorial Genetic Interaction Analysis Reveals a Multi-Drug Transporter Influence Network
Celaj, A., Gebbia, M., Musa, L., Coté, A. G., Snider, J. D., Wong, V., Ko, M., Fong, T., Bansal, P., Mellor, J. C., et al. (2019) · Cell Systems · doi:10.1016/j.cels.2019.09.009 · Cited by 23 · see citing works
- Authors
- Horlbeck, M. A., Xu, A., Wang, M., Bennett, N. K., Park, C. Y., Bogdanoff, D., Adamson, B., Chow, E. D., Kampmann, M., Peterson, T. R., Nakamura, K., Fischbach, M. A., Weissman, J. S., & Gilbert, L. A.
- Affiliations
- Howard Hughes Medical Institute (US)
- Stanford University (US)
- Gladstone Institutes (US)
- University of California, San Francisco (US)
- Corresponding author
- Weissman, Jonathan S.
- Gilbert, Luke A.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 174
- Issue
- 4
- Pages
- 953-967.e22
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6426455
- OpenAlex
- W2883377762
- Cited by
- 319
- References
- 57
- Citations by year
- 2026: 29 · 2025: 42 · 2024: 50 · 2023: 32 · 2022: 31 · 2021: 33 · 2020: 53 · 2019: 37 · 2018: 11 · 2017: 1
- FWCI
- 12.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- NIH (P50 GM102706, U01 CA168370, U01 CA217882, R01 DA036858, R00 CA204602, RO1NS091902, DP1 DK113598)
- Goldberg-Benioff Endowed Professorship in Prostate Cancer Translational Biology
- DARPA (HR0011-17-2-0043)
- Byers Family Discovery
- the Damon Runyon Cancer Research Foundation (DRG-[2182-14)
- Stand Up to Cancer Innovative Research Grant
- HHMI-Simons Faculty Scholars Award
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- genetic interactions, CRISPR interference, gene function prediction, cancer cell lines, electron transport chain, cholesterol biosynthesis, synthetic lethality
- MeSH terms
- Cholesterol, Epistasis, Genetic, Humans, Biomarkers, Jurkat Cells, K562 Cells, Protein Interaction Mapping, Gene Regulatory Networks, High-Throughput Nucleotide Sequencing, Clustered Regularly Interspaced Short Palindromic Repeats
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 ›
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