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A new era in functional genomics screens

Abstract

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

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Fig. 1: Common types of CRISPR screening modalities indicating advances in CRISPR methods.
Fig. 2: Leveraging DepMap for co-correlation analysis.
Fig. 3: Combining screening modalities to broaden cell model and assay parameter space.
Fig. 4: CRISPR-based strategies to link GWAS-identified SNP variants to gene expression.
Fig. 5: Mapping genetic interactions using CRISPR.

References

  1. 1.

    Doudna, J. A. & Charpentier, E. Genome editing. The new frontier of genome engineering with CRISPR–Cas9. Science 346, 1258096 (2014).

    PubMed  Article  CAS  Google Scholar 

  2. 2.

    Nakamura, M., Gao, Y., Dominguez, A. A. & Qi, L. S. CRISPR technologies for precise epigenome editing. Nat. Cell Biol. 23, 11–22 (2021).

    CAS  PubMed  Article  Google Scholar 

  3. 3.

    Holtzman, L. & Gersbach, C. A. Editing the epigenome: reshaping the genomic landscape. Annu. Rev. Genomics Hum. Genet. 19, 43–71 (2018).

    CAS  PubMed  Article  Google Scholar 

  4. 4.

    Shalem, O., Sanjana, N. E. & Zhang, F. High-throughput functional genomics using CRISPR–Cas9. Nat. Rev. Genet. 16, 299–311 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Doench, J. G. Am I ready for CRISPR? A user’s guide to genetic screens. Nat. Rev. Genet. 19, 67–80 (2018). This Review describes several important practical aspects for running CRISPR screens, including crucial quality control metrics to monitor at different screening steps.

    CAS  PubMed  Article  Google Scholar 

  6. 6.

    Hanna, R. E. & Doench, J. G. Design and analysis of CRISPR–Cas experiments. Nat. Biotechnol. 38, 813–823 (2020). This review highlights data analysis strategies and pipelines for CRISPR screens that are a fundamental part of screen interpretation and analysis not covered in the present Review.

    CAS  PubMed  Article  Google Scholar 

  7. 7.

    Knott, G. J. & Doudna, J. A. CRISPR–Cas guides the future of genetic engineering. Science 361, 866–869 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. 8.

    Wang, H., La Russa, M. & Qi, L. S. CRISPR/Cas9 in genome editing and beyond. Annu. Rev. Biochem. 85, 227–264 (2016).

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Pickar-Oliver, A. & Gersbach, C. A. The next generation of CRISPR–Cas technologies and applications. Nat. Rev. Mol. Cell Biol. 20, 490–507 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    Dixit, A. et al. Perturb-seq: dissecting molecular circuits with scalable single cell RNA profiling of pooled genetic screens. Cell 167, 1853–1866.e17 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11.

    Adamson, B. et al. A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response. Cell 167, 1867–1882.e21 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Jaitin, D. A. et al. Dissecting immune circuits by linking CRISPR-pooled screens with single-cell RNA-seq. Cell 167, 1883–1896.e15 (2016). Together with Dixit et al. (2016) and Adamson et al. (2016), this seminal scFG CRISPR paper demonstrates the potential for using pooled single-cell CRISPR screens as a discovery platform.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    Warren, H. R. et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat. Genet. 49, 403–415 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Lambert, J. C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  15. 15.

    Horlbeck, M. A. et al. Mapping the genetic landscape of human cells. Cell 174, 953–967.e22 (2018). This large-scale CRISPRi genetic interaction map demonstrates the utility of this approach in mammalian cells and serves as a broad resource and blueprint for future studies.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Norman, T. M. et al. Exploring genetic interaction manifolds constructed from rich single-cell phenotypes. Science 365, 786–793 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  17. 17.

    Costanzo, M. et al. Global genetic networks and the genotype-to-phenotype relationship. Cell 177, 85–100 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Domingo, J., Baeza-Centurion, P. & Lehner, B. The causes and consequences of genetic interactions (Eeistasis). Annu. Rev. Genomics Hum. Genet. 20, 433–460 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  19. 19.

    Tian, R. et al. CRISPR interference-based platform for multimodal genetic screens in human iPSC-derived neurons. Neuron 104, 239–255.e12 (2019). This paper presents the first large-scale screen performed in iPS cell-derived cells, providing a template for future studies and revealing valuable information about neuronal differentiation and function.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. 20.

    O’Loughlin, T. A. & Gilbert, L. A. Functional genomics for cancer research: applications in vivo and in vitro. Annu. Rev. Cancer Biol. 3, 345–363 (2019).

    Article  Google Scholar 

  21. 21.

    Chow, R. D. & Chen, S. Cancer CRISPR screens in vivo. Trends Cancer 4, 349–358 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Li, C. & Kasinski, A. L. In vivo cancer-based functional genomics. Trends Cancer 6, 1002–1017 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  23. 23.

    Weber, J., Braun, C. J., Saur, D. & Rad, R. In vivo functional screening for systems-level integrative cancer genomics. Nat. Rev. Cancer 20, 573–593 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Winters, I. P., Murray, C. W. & Winslow, M. M. Towards quantitative and multiplexed in vivo functional cancer genomics. Nat. Rev. Genet. 19, 741–755 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25.

    Jasin, M. & Haber, J. E. The democratization of gene editing: insights from site-specific cleavage and double-strand break repair. DNA Repair 44, 6–16 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Rouet, P., Smih, F. & Jasin, M. Introduction of -strand breaks into the genome of mouse cells by expression of a rare-cutting endonuclease. Mol. Cell. Biol. 14, 8096–8106 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Yeh, C. D., Richardson, C. D. & Corn, J. E. Advances in genome editing through control of DNA repair pathways. Nat. Cell Biol. 21, 1468–1478 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  28. 28.

    Carroll, D. Genome engineering with zinc-finger nucleases. Genetics 188, 773–782 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Chandrasegaran, S. & Carroll, D. Origins of programmable nucleases for genome engineering. J. Mol. Biol. 428, 963–989 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Urnov, F. D., Rebar, E. J., Holmes, M. C., Zhang, H. S. & Gregory, P. D. Genome editing with engineered zinc finger nucleases. Nat. Rev. Genet. 11, 636–646 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  31. 31.

    Joung, J. K. & Sander, J. D. TALENs: a widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 14, 49–55 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  32. 32.

    Ousterout, D. G. & Gersbach, C. A. The development of TALE nucleases for biotechnology. Methods Mol. Biol. Clifton NJ 1338, 27–42 (2016).

    CAS  Article  Google Scholar 

  33. 33.

    Tebas, P. et al. Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV. N. Engl. J. Med. 370, 901–910 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Hoban, M. D. et al. Correction of the sickle cell disease mutation in human hematopoietic stem/progenitor cells. Blood 125, 2597–2604 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. 35.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT00842634 (2019).

  36. 36.

    US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02702115 (2020).

  37. 37.

    Beerli, R. R., Segal, D. J., Dreier, B. & Barbas, C. F. Toward controlling gene expression at will: specific regulation of the erbB-2/HER-2 promoter by using polydactyl zinc finger proteins constructed from modular building blocks. Proc. Natl Acad. Sci. USA 95, 14628–14633 (1998).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  38. 38.

    Konermann, S. et al. Optical control of mammalian endogenous transcription and epigenetic states. Nature 500, 472–476 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Gaj, T., Gersbach, C. A. & Barbas, C. F. ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering. Trends Biotechnol. 31, 397–405 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. 40.

    Mohr, S., Bakal, C. & Perrimon, N. Genomic screening with RNAi: results and challenges. Annu. Rev. Biochem. 79, 37–64 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Boettcher, M. & McManus, M. T. Choosing the right tool for the job: RNAi, TALEN, or CRISPR. Mol. Cell 58, 575–585 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Jackson, A. L. & Linsley, P. S. Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application. Nat. Rev. Drug Discov. 9, 57–67 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Jackson, A. L. et al. Expression profiling reveals off-target gene regulation by RNAi. Nat. Biotechnol. 21, 635–637 (2003).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  44. 44.

    Acevedo-Arozena, A. et al. ENU mutagenesis, a way forward to understand gene function. Annu. Rev. Genomics Hum. Genet. 9, 49–69 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Blomen, V. A. et al. Gene essentiality and synthetic lethality in haploid human cells. Science 350, 1092–1096 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  46. 46.

    Brockmann, M. et al. Genetic wiring maps of single-cell protein states reveal an off-switch for GPCR signalling. Nature 546, 307–311 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  47. 47.

    Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Kampmann, M. CRISPRi and CRISPRa screens in mammalian cells for precision biology and medicine. ACS Chem. Biol. 13, 406–416 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  49. 49.

    Konermann, S. et al. Genome-scale transcriptional activation by an engineered CRISPR–Cas9 complex. Nature 517, 583–588 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50.

    Xu, X. & Qi, L. S. A CRISPR–dCas toolbox for genetic engineering and synthetic biology. J. Mol. Biol. 431, 34–47 (2019).

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Anzalone, A. V., Koblan, L. W. & Liu, D. R. Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors. Nat. Biotechnol. 38, 824–844 (2020).

    CAS  PubMed  Article  Google Scholar 

  52. 52.

    Shalem, O. et al. Genome-scale CRISPR–Cas9 knockout screening in human cells. Science 343, 84–87 (2014).

    CAS  PubMed  Article  Google Scholar 

  53. 53.

    Wang, T., Wei, J. J., Sabatini, D. M. & Lander, E. S. Genetic screens in human cells using the CRISPR–Cas9 system. Science 343, 80–84 (2014). Together with Shalem et al. (2014), this paper presents a seminal genome-scale CRISPR screen demonstrating the enormous potential of CRISPR for next-generation functional genomics.

    CAS  PubMed  Article  Google Scholar 

  54. 54.

    Morgens, D. W., Deans, R. M., Li, A. & Bassik, M. C. Systematic comparison of CRISPR–Cas9 and RNAi screens for essential genes. Nat. Biotechnol. 34, 634–636 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. 55.

    le Sage, C. et al. Dual direction CRISPR transcriptional regulation screening uncovers gene networks driving drug resistance. Sci. Rep. 7, 17693 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  56. 56.

    Hart, T. et al. High-resolution CRISPR screens reveal fitness genes and genotype-specific cancer liabilities. Cell 163, 1515–1526 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  57. 57.

    Wang, T. et al. Identification and characterization of essential genes in the human genome. Science 350, 1096–1101 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  58. 58.

    Wang, T. et al. Gene essentiality profiling reveals gene networks and synthetic lethal interactions with oncogenic ras. Cell 168, 890–903.e15 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Koike-Yusa, H., Li, Y., Tan, E.-P., Velasco-Herrera, M. D. C. & Yusa, K. Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR–guide RNA library. Nat. Biotechnol. 32, 267–273 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  60. 60.

    Zhou, Y. et al. High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells. Nature 509, 487–491 (2014).

    CAS  PubMed  Article  Google Scholar 

  61. 61.

    Meyers, R. M. et al. Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells. Nat. Genet. 49, 1779–1784 (2017). This seminal publication of the DepMap data enables comparative large-scale analysis of CRISPR screening data across diverse cell types.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  62. 62.

    Chan, E. M. et al. WRN helicase is a synthetic lethal target in microsatellite unstable cancers. Nature 568, 551–556 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. 63.

    Behan, F. M. et al. Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens. Nature 568, 511–516 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  64. 64.

    Kampmann, M. CRISPR-based functional genomics for neurological disease. Nat. Rev. Neurol. 16, 465–480 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  65. 65.

    Mair, B. et al. Essential gene profiles for human pluripotent stem cells identify uncharacterized genes and substrate dependencies. Cell Rep. 27, 599–615.e12 (2019).

    CAS  PubMed  Article  Google Scholar 

  66. 66.

    Ihry, R. J. et al. Genome-scale CRISPR screens identify human pluripotency-specific genes. Cell Rep. 27, 616–630.e6 (2019).

    CAS  PubMed  Article  Google Scholar 

  67. 67.

    Puschnik, A. S., Majzoub, K., Ooi, Y. S. & Carette, J. E. A CRISPR toolbox to study virus–host interactions. Nat. Rev. Microbiol. 15, 351–364 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  68. 68.

    Marceau, C. D. et al. Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature 535, 159–163 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  69. 69.

    Jeng, E. E. et al. Systematic identification of host cell regulators of Legionella pneumophila pathogenesis using a genome-wide CRISPR screen. Cell Host Microbe 26, 551–563.e6 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. 70.

    Kory, N. et al. SFXN1 is a mitochondrial serine transporter required for one-carbon metabolism. Science 362, eaat9528 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  71. 71.

    Birsoy, K. et al. An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell 162, 540–551 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  72. 72.

    Lou, K. et al. KRASG12C inhibition produces a driver-limited state revealing collateral dependencies. Sci. Signal. 12, eaaw9450 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. 73.

    Jost, M. & Weissman, J. S. CRISPR approaches to small molecule target identification. ACS Chem. Biol. 13, 366–375 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Jost, M. et al. Combined CRISPRi/a-based chemical genetic screens reveal that rigosertib is a microtubule-destabilizing agent. Mol. Cell 68, 210–223.e6 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  75. 75.

    Zimmermann, M. et al. CRISPR screens identify genomic ribonucleotides as a source of PARP-trapping lesions. Nature 559, 285–289 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  76. 76.

    Huang, A., Garraway, L. A., Ashworth, A. & Weber, B. Synthetic lethality as an engine for cancer drug target discovery. Nat. Rev. Drug Discov. 19, 23–38 (2020).

    CAS  PubMed  Article  Google Scholar 

  77. 77.

    Kabir, S. et al. The CUL5 ubiquitin ligase complex mediates resistance to CDK9 and MCL1 inhibitors in lung cancer cells. eLife 8, e44288 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. 78.

    Fomicheva, M. & Macara, I. G. Genome-wide CRISPR screen identifies noncanonical NF-κB signaling as a regulator of density-dependent proliferation. eLife 9, e63603 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  79. 79.

    Wang, L. et al. High-throughput functional genetic and compound screens identify targets for senescence induction in cancer. Cell Rep. 21, 773–783 (2017).

    CAS  PubMed  Article  Google Scholar 

  80. 80.

    Schmid-Burgk, J. L. et al. A genome-wide CRISPR (clustered regularly interspaced short palindromic repeats) screen identifies NEK7 as an essential component of NLRP3 inflammasome activation. J. Biol. Chem. 291, 103–109 (2016).

    CAS  PubMed  Article  Google Scholar 

  81. 81.

    Findlay, G. M. et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature 562, 217–222 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  82. 82.

    Findlay, G. M., Boyle, E. A., Hause, R. J., Klein, J. & Shendure, J. Saturation editing of genomic regions by multiplex homology-directed repair. Nature 513, 120–123 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. 83.

    Hanna, R. E. et al. Massively parallel assessment of human variants with base editor screens. Cell 184, 1064–1080.e20 (2021).

    CAS  PubMed  Article  Google Scholar 

  84. 84.

    Cuella-Martin, R. et al. Functional interrogation of DNA damage response variants with base editing screens. Cell 184, 1081–1097.e19 (2021).

    CAS  PubMed  Article  Google Scholar 

  85. 85.

    Hess, G. T. et al. Directed evolution using dCas9-targeted somatic hypermutation in mammalian cells. Nat. Methods 13, 1036–1042 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  86. 86.

    Ma, L. et al. CRISPR–Cas9-mediated saturated mutagenesis screen predicts clinical drug resistance with improved accuracy. Proc. Natl Acad. Sci. USA 114, 11751–11756 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  87. 87.

    Liang, J. R. et al. A genome-wide ER-phagy screen highlights key roles of mitochondrial metabolism and ER-resident UFMylation. Cell 180, 1160–1177.e20 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  88. 88.

    Li, Q. V. et al. Genome-scale screens identify JNK/JUN signaling as a barrier for pluripotency exit and endoderm differentiation. Nat. Genet. 51, 999–1010 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  89. 89.

    Pusapati, G. V. et al. CRISPR screens uncover genes that regulate target cell sensitivity to the morphogen sonic hedgehog. Dev. Cell 44, 113–129.e8 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  90. 90.

    Torres, S. E. et al. Ceapins block the unfolded protein response sensor ATF6α by inducing a neomorphic inter-organelle tether. eLife 8, e46595 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  91. 91.

    Potting, C. et al. Genome-wide CRISPR screen for PARKIN regulators reveals transcriptional repression as a determinant of mitophagy. Proc. Natl Acad. Sci. USA 115, E180–E189 (2018).

    CAS  PubMed  Article  Google Scholar 

  92. 92.

    Henriksson, J. et al. Genome-wide CRISPR screens in T helper cells reveal pervasive crosstalk between activation and differentiation. Cell 176, 882–896.e18 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  93. 93.

    Dixon, G. et al. QSER1 protects DNA methylation valleys from de novo methylation. Science 372, eabd0875 (2021).

    CAS  PubMed  Article  Google Scholar 

  94. 94.

    Gretarsson, K. H. & Hackett, J. A. Dppa2 and Dppa4 counteract de novo methylation to establish a permissive epigenome for development. Nat. Struct. Mol. Biol. 27, 706–716 (2020).

    CAS  PubMed  Article  Google Scholar 

  95. 95.

    Rauch, J. N. et al. Tau internalization is regulated by 6-O sulfation on heparan sulfate proteoglycans (HSPGs). Sci. Rep. 8, 6382 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  96. 96.

    Park, R. J. et al. A genome-wide CRISPR screen identifies a restricted set of HIV host dependency factors. Nat. Genet. 49, 193–203 (2017).

    CAS  PubMed  Article  Google Scholar 

  97. 97.

    Park, J. S. et al. A FACS-based genome-wide CRISPR screen reveals a requirement for COPI in Chlamydia trachomatis invasion. iScience 11, 71–84 (2019).

    CAS  PubMed  Article  Google Scholar 

  98. 98.

    Liu, S. J. et al. CRISPRi-based genome-scale identification of functional long noncoding RNA lociin human cells. Science 355, aah7111 (2017).

    PubMed  Article  CAS  Google Scholar 

  99. 99.

    Chen, J. J. et al. Compromised function of the ESCRT pathway promotes endolysosomal escape of tau seeds and propagation of tau aggregation. J. Biol. Chem. 294, 18952–18966 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  100. 100.

    Mendelsohn, B. A. et al. A high-throughput screen of real-time ATP levels in individual cells reveals mechanisms of energy failure. PLoS Biol. 16, e2004624 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  101. 101.

    Bayraktar, E. C. et al. Metabolic coessentiality mapping identifies C12orf49 as a regulator of SREBP processing and cholesterol metabolism. Nat. Metab. 2, 487–498 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  102. 102.

    Wainberg, M. et al. A genome-wide atlas of co-essential modules assigns function to uncharacterized genes. Nat. Genet. 53, 638–649 (2021).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  103. 103.

    Yogodzinski, C., Arab, A., Pritchard, J. R., Goodarzi, H. & Gilbert, L. A. A global cancer data integrator reveals principles of synthetic lethality, sex disparity and immunotherapy. bioRxiv https://doi.org/10.1101/2021.01.08.425918 (2021).

    Article  Google Scholar 

  104. 104.

    Zhao, B., Rao, Y., Gilbert, L. & Pritchard, J. A common genetic architecture enables the lossy compression of large CRISPR libraries. bioRxiv https://doi.org/10.1101/2020.12.18.423506 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  105. 105.

    Cui, Y. et al. CRISP-view: a database of functional genetic screens spanning multiple phenotypes. Nucleic Acids Res. 49, D848–D854 (2021).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  106. 106.

    McKinley, K. L. & Cheeseman, I. M. Large-scale analysis of CRISPR/Cas9 cell-cycle knockouts reveals the diversity of p53-dependent responses to cell-cycle defects. Dev. Cell 40, 405–420.e2 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  107. 107.

    Wang, C., Lu, T., Emanuel, G., Babcock, H. P. & Zhuang, X. Imaging-based pooled CRISPR screening reveals regulators of lncRNA localization. Proc. Natl Acad. Sci. USA 116, 10842–10851 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  108. 108.

    de Groot, R., Lüthi, J., Lindsay, H., Holtackers, R. & Pelkmans, L. Large-scale image-based profiling of single-cell phenotypes in arrayed CRISPR–Cas9 gene perturbation screens. Mol. Syst. Biol. 14, e8064 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  109. 109.

    Strezoska, Ž. et al. High-content analysis screening for cell cycle regulators using arrayed synthetic crRNA libraries. J. Biotechnol. 251, 189–200 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  110. 110.

    Feldman, D. et al. Optical pooled screens in human cells. Cell 179, 787–799.e17 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  111. 111.

    Kanfer, G. et al. Image-based pooled whole-genome CRISPRi screening for subcellular phenotypes. J. Cell Biol. 220, e202006180 (2021).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  112. 112.

    Yan, X. et al. High-content imaging-based pooled CRISPR screens in mammalian cells. J. Cell Biol. 220, e202008158 (2021).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  113. 113.

    Wheeler, E. C. et al. Pooled CRISPR screens with imaging on microraft arrays reveals stress granule-regulatory factors. Nat. Methods 17, 636–642 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  114. 114.

    Datlinger, P. et al. Pooled CRISPR screening with single-cell transcriptome readout. Nat. Methods 14, 297–301 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  115. 115.

    Xie, S., Duan, J., Li, B., Zhou, P. & Hon, G. C. Multiplexed engineering and analysis of combinatorial enhancer activity in single cells. Mol. Cell 66, 285–299.e5 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  116. 116.

    Adamson, B., Norman, T. M., Jost, M. & Weissman, J. S. Approaches maximize sgRNA-barcode coupling Perturb-seq screens. bioRxiv https://doi.org/10.1101/298349 (2018).

    Article  Google Scholar 

  117. 117.

    Replogle, J. M. et al. Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing. Nat. Biotechnol. 38, 954–961 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  118. 118.

    Jin, X. et al. In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes. Science 370, eaaz6063 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. 119.

    Dhainaut, M. et al. Perturb-map enables CRISPR genomics with spatial resolution and identifies regulators of tumor immune composition. bioRxiv https://doi.org/10.1101/2021.07.13.451021 (2021).

    Article  Google Scholar 

  120. 120.

    Liu, J. et al. Pooled library screening with multiplexed Cpf1 library. Nat. Commun. 10, 3144 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  121. 121.

    Gonçalves, E. et al. Minimal genome-wide human CRISPR–Cas9 library. Genome Biol. 22, 40 (2021).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  122. 122.

    Peets, E. M. et al. Minimized double guide RNA libraries enable scale-limited CRISPR/Cas9 screens. bioRxiv https://doi.org/10.1101/859652 (2019).

    Article  Google Scholar 

  123. 123.

    Schraivogel, D. et al. Targeted Perturb-seq enables genome-scale genetic screens in single cells. Nat. Methods 17, 629–635 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  124. 124.

    Srivatsan, S. R. et al. Massively multiplex chemical transcriptomics at single-cell resolution. Science 367, 45–51 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  125. 125.

    Henkel, L., Rauscher, B., Schmitt, B., Winter, J. & Boutros, M. Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library. BMC Biol. 18, 174 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  126. 126.

    Datlinger, P. et al. Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing. Nat. Methods 18, 635–642 (2021).

    CAS  Article  Google Scholar 

  127. 127.

    Rosenberg, A. B. et al. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science 360, 176–182 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  128. 128.

    Subramanian, A. et al. A next generation connectivity map: L1000 platform and the first 1,000,000 profiles. Cell 171, 1437–1452.e17 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  129. 129.

    Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  130. 130.

    Richer, A. L., Riemondy, K. A., Hardie, L. & Hesselberth, J. R. Simultaneous measurement of biochemical phenotypes and gene expression in single cells. Nucleic Acids Res. 48, e59 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  131. 131.

    Wroblewska, A. et al. Protein barcodes enable high-dimensional single-cell CRISPR screens. Cell 175, 1141–1155.e16 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  132. 132.

    Quinn, J. J. et al. Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science 371, 6532 (2021).

    Article  CAS  Google Scholar 

  133. 133.

    Chan, M. M. et al. Molecular recording of mammalian embryogenesis. Nature 570, 77–82 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  134. 134.

    Rubin, A. J. et al. Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks. Cell 176, 361–376.e17 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  135. 135.

    Frangieh, C. J. et al. Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion. Nat. Genet. 53, 332–341 (2021).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  136. 136.

    Calin, G. A. & Croce, C. M. MicroRNA signatures in human cancers. Nat. Rev. Cancer 6, 857–866 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  137. 137.

    Alvarez-Garcia, I. & Miska, E. A. MicroRNA functions in animal development and human disease. Development 132, 4653–4662 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  138. 138.

    Schmitz, S. U., Grote, P. & Herrmann, B. G. Mechanisms of long noncoding RNA function in development and disease. Cell. Mol. Life Sci. 73, 2491–2509 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  139. 139.

    Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  140. 140.

    Joung, J. et al. Genome-scale activation screen identifies a lncRNA locus regulating a gene neighbourhood. Nature 548, 343–346 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  141. 141.

    Wallace, J. et al. Genome-wide CRISPR–Cas9 screen identifies microRNAs that regulate myeloid leukemia cell growth. PLoS ONE 11, e0153689 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  142. 142.

    Kurata, J. S. & Lin, R.-J. MicroRNA-focused CRISPR–Cas9 library screen reveals fitness-associated miRNAs. RNA 24, 966–981 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  143. 143.

    Covarrubias, S. et al. CRISPR/Cas-based screening of long non-coding RNAs (lncRNAs) in macrophages with an NF-κB reporter. J. Biol. Chem. 292, 20911–20920 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  144. 144.

    Bester, A. C. et al. An integrated genome-wide CRISPRa approach to functionalize lncRNAs in drug resistance. Cell 173, 649–664.e20 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  145. 145.

    Esposito, R. et al. Hacking the cancer genome: profiling therapeutically actionable long non-coding RNAs using CRISPR–Cas9 screening. Cancer Cell 35, 545–557 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  146. 146.

    Liu, Y. et al. Genome-wide screening for functional long noncoding RNAs in human cells by Cas9 targeting of splice sites. Nat. Biotechnol. 36, 1203–1210 (2018).

    CAS  Article  Google Scholar 

  147. 147.

    Phelan, J. D. & Staudt, L. M. CRISPR-based technology to silence the expression of IncRNAs. Proc. Natl Acad. Sci. USA 117, 8225–8227 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  148. 148.

    Zhu, S. et al. Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR library. Nat. Biotechnol. 34, 1279–1286 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  149. 149.

    Reber, S. et al. CRISPR-Trap: a clean approach for the generation of gene knockouts and gene replacements in human cells. Mol. Biol. Cell 29, 75–83 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  150. 150.

    Wolter, J. M. et al. Cas9 gene therapy for Angelman syndrome traps Ube3a-ATS long non-coding RNA. Nature 587, 281–284 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  151. 151.

    Bergadà-Pijuan, J., Pulido-Quetglas, C., Vancura, A. & Johnson, R. CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long non-coding RNAs. Bioinformatics 36, 1673–1680 (2020).

    PubMed  PubMed Central  Google Scholar 

  152. 152.

    Liu, Y., Liu, Z., Cao, Z. & Wei, W. Reply to: Fitness effects of CRISPR/Cas9-targeting of long noncoding RNA genes. Nat. Biotechnol. 38, 577–578 (2020).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  153. 153.

    Horlbeck, M. A., Liu, S. J., Chang, H. Y., Lim, D. A. & Weissman, J. S. Fitness effects of CRISPR/Cas9-targeting of long noncoding RNA genes. Nat. Biotechnol. 38, 573–576 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  154. 154.

    Tam, V. et al. Benefits and limitations of genome-wide association studies. Nat. Rev. Genet. 20, 467–484 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  155. 155.

    Giral, H., Landmesser, U. & Kratzer, A. Into the wild: GWAS exploration of non-coding RNAs. Front. Cardiovasc. Med. 5, 181 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  156. 156.

    Montefiori, L. E. et al. A promoter interaction map for cardiovascular disease genetics. eLife 7, e35788 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  157. 157.

    Mumbach, M. R. et al. Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements. Nat. Genet. 49, 1602–1612 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  158. 158.

    Nott, A. et al. Brain cell type-specific enhancer–promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  159. 159.

    Chiou, J. et al. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 594, 398–402 (2021).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  160. 160.

    Fulco, C. P. et al. Systematic mapping of functional enhancer–promoter connections with CRISPR interference. Science 354, 769–773 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  161. 161.

    Sanjana, N. E. et al. High-resolution interrogation of functional elements in the noncoding genome. Science 353, 1545–1549 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  162. 162.

    Cho, S. W. et al. Promoter of lncRNA gene PVT1 is a tumor-suppressor DNA boundary element. Cell 173, 1398–1412.e22 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  163. 163.

    Tycko, J. et al. Mitigation of off-target toxicity in CRISPR–Cas9 screens for essential non-coding elements. Nat. Commun. 10, 4063 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  164. 164.

    Klann, T. S. et al. Genome-wide annotation of gene regulatory elements linked to cell fitness. bioRxiv https://doi.org/10.1101/2021.03.08.434470 (2021).

    Article  Google Scholar 

  165. 165.

    Gasperini, M. et al. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176, 377–390.e19 (2019). This paper outlines an approach that has been widely adopted to assign relationships between non-coding enhancer/silencer regions of the genome and gene expression.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  166. 166.

    Klann, T. S. et al. CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nat. Biotechnol. 35, 561–568 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  167. 167.

    Fulco, C. P. et al. Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations. Nat. Genet. 51, 1664–1669 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  168. 168.

    Simeonov, D. R. et al. Discovery of stimulation-responsive immune enhancers with CRISPR activation. Nature 549, 111–115 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  169. 169.

    Hilton, I. B. et al. Epigenome editing by a CRISPR–Cas9-based acetyltransferase activates genes from promoters and enhancers. Nat. Biotechnol. 33, 510–517 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  170. 170.

    Kearns, N. A. et al. Functional annotation of native enhancers with a Cas9–histone demethylase fusion. Nat. Methods 12, 401–403 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  171. 171.

    Li, K. et al. Interrogation of enhancer function by enhancer-targeting CRISPR epigenetic editing. Nat. Commun. 11, 485 (2020).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  172. 172.

    Takahashi, K. & Yamanaka, S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663–676 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  173. 173.

    Masserdotti, G., Gascón, S. & Götz, M. Direct neuronal reprogramming: learning from and for development. Development 143, 2494–2510 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  174. 174.

    Kuzmin, E. et al. Systematic analysis of complex genetic interactions. Science 360, eaao1729 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  175. 175.

    Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).

    CAS  PubMed  Article  Google Scholar 

  176. 176.

    Costanzo, M. et al. A global genetic interaction network maps a wiring diagram of cellular function. Science 353, aaf1420 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  177. 177.

    Costanzo, M. et al. The genetic landscape of a cell. Science 327, 425–431 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  178. 178.

    Lehner, B., Crombie, C., Tischler, J., Fortunato, A. & Fraser, A. G. Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways. Nat. Genet. 38, 896–903 (2006).

    CAS  PubMed  Article  Google Scholar 

  179. 179.

    Ashworth, A. & Lord, C. J. Synthetic lethal therapies for cancer: what’s next after PARP inhibitors? Nat. Rev. Clin. Oncol. 15, 564–576 (2018).

    CAS  PubMed  Article  Google Scholar 

  180. 180.

    Han, K. et al. Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nat. Biotechnol. 35, 463–474 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  181. 181.

    Bassik, M. C. et al. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell 152, 909–922 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  182. 182.

    Du, D. et al. Genetic interaction mapping in mammalian cells using CRISPR interference. Nat. Methods 14, 577–580 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  183. 183.

    Roguev, A. et al. Quantitative genetic-interaction mapping in mammalian cells. Nat. Methods 10, 432–437 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  184. 184.

    Rosenbluh, J. et al. Genetic and proteomic interrogation of lower confidence candidate genes reveals signaling networks in β-catenin-active cancers. Cell Syst. 3, 302–316.e4 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  185. 185.

    Shen, J. P. et al. Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions. Nat. Methods 14, 573–576 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  186. 186.

    Wong, A. S. L. et al. Multiplexed barcoded CRISPR–Cas9 screening enabled by CombiGEM. Proc. Natl Acad. Sci. USA 113, 2544–2549 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  187. 187.

    DeWeirdt, P. C. et al. Optimization of AsCas12a for combinatorial genetic screens in human cells. Nat. Biotechnol. 39, 94–104 (2021).

    CAS  PubMed  Article  Google Scholar 

  188. 188.

    Najm, F. J. et al. Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens. Nat. Biotechnol. 36, 179–189 (2018).

    CAS  PubMed  Article  Google Scholar 

  189. 189.

    Liu, Y. et al. CRISPR activation screens systematically identify factors that drive neuronal fate and reprogramming. Cell Stem Cell 23, 758–771.e8 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  190. 190.

    Dixit, A., Kuksenko, O., Feldman, D. & Regev, A. Shuffle-seq: en masse combinatorial encoding for n-way genetic interaction screens. bioRxiv https://doi.org/10.1101/861443 (2019).

    Article  Google Scholar 

  191. 191.

    DeWeirdt, P. C. et al. Genetic screens in isogenic mammalian cell lines without single cell cloning. Nat. Commun. 11, 752 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  192. 192.

    Aregger, M. et al. Systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism. Nat. Metab. 2, 499–513 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  193. 193.

    Gonatopoulos-Pournatzis, T. et al. Genetic interaction mapping and exon-resolution functional genomics with a hybrid Cas9–Cas12a platform. Nat. Biotechnol. 38, 638–648 (2020).

    CAS  PubMed  Article  Google Scholar 

  194. 194.

    Boettcher, M. et al. Dual gene activation and knockout screen reveals directional dependencies in genetic networks. Nat. Biotechnol. 36, 170–178 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  195. 195.

    Zalatan, J. G. et al. Engineering complex synthetic transcriptional programs with CRISPR RNA scaffolds. Cell 160, 339–350 (2015).

    CAS  PubMed  Article  Google Scholar 

  196. 196.

    Cleary, B. & Regev, A. The necessity and power of random, under-sampled experiments in biology. Cornell University https://arxiv.org/abs/2012.12961 (2020).

  197. 197.

    Cleary, B., Cong, L., Cheung, A., Lander, E. S. & Regev, A. Efficient generation of transcriptomic profiles by random composite measurements. Cell 171, 1424–1436.e18 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  198. 198.

    Tian, R. et al. Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis. Nat. Neurosci. 24, 1020–1034 (2021).

    CAS  PubMed  Article  Google Scholar 

  199. 199.

    Konermann, S. et al. Transcriptome engineering with RNA-targeting type VI-D CRISPR effectors. Cell 173, 665–676.e14 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  200. 200.

    Wessels, H.-H. et al. Massively parallel Cas13 screens reveal principles for guide RNA design. Nat. Biotechnol. 38, 722–727 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  201. 201.

    Abudayyeh, O. O. et al. RNA targeting with CRISPR–Cas13. Nature 550, 280–284 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  202. 202.

    Wilson, C., Chen, P. J., Miao, Z. & Liu, D. R. Programmable m6A modification of cellular RNAs with a Cas13-directed methyltransferase. Nat. Biotechnol. 38, 1431–1440 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  203. 203.

    Li, J. et al. Targeted mRNA demethylation using an engineered dCas13b–ALKBH5 fusion protein. Nucleic Acids Res. 48, 5684–5694 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  204. 204.

    Kampmann, M., Bassik, M. C. & Weissman, J. S. Integrated platform for genome-wide screening and construction of high-density genetic interaction maps in mammalian cells. Proc. Natl Acad. Sci. USA 110, E2317–E2326 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  205. 205.

    Parnas, O. et al. A genome-wide CRISPR screen in primary immune cells to dissect regulatory networks. Cell 162, 675–686 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  206. 206.

    Jost, M. et al. CRISPR-based functional genomics in human dendritic cells. eLife 10, e65856 (2021).

    PubMed  PubMed Central  Article  Google Scholar 

  207. 207.

    Keys, H. R. & Knouse, K. A. A genome-wide screen in the mouse liver reveals sex-specific and cell non-autonomous regulation of cell fitness. bioRxiv https://doi.org/10.1101/2021.01.30.428976 (2021).

    Article  Google Scholar 

  208. 208.

    Shifrut, E. et al. Genome-wide CRISPR screens in primary human T cells reveal key regulators of immune function. Cell 175, 1958–1971.e15 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  209. 209.

    Hultquist, J. F. et al. A Cas9 ribonucleoprotein platform for functional genetic studies of HIV–host interactions in primary human T cells. Cell Rep. 17, 1438–1452 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  210. 210.

    Schumann, K. et al. Generation of knock-in primary human T cells using Cas9 ribonucleoproteins. Proc. Natl Acad. Sci. USA 112, 10437–10442 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  211. 211.

    Schumann, K. et al. Functional CRISPR dissection of gene networks controlling human regulatory T cell identity. Nat. Immunol. 21, 1456–1466 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  212. 212.

    Roth, T. L. et al. Reprogramming human T cell function and specificity with non-viral genome targeting. Nature 559, 405–409 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  213. 213.

    Roth, T. L. et al. Pooled knockin targeting for genome engineering of cellular immunotherapies. Cell 181, 728–744.e21 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  214. 214.

    Gate, R. E. et al. Mapping gene regulatory networks of primary CD4+ T cells using single-cell genomics and genome engineering. bioRxiv https://doi.org/10.1101/678060 (2019).

    Article  Google Scholar 

  215. 215.

    Ting, P. Y. et al. Guide Swap enables genome-scale pooled CRISPR–Cas9 screening in human primary cells. Nat. Methods 15, 941–946 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  216. 216.

    Cortez, J. T. et al. CRISPR screen in regulatory T cells reveals modulators of Foxp3. Nature 582, 416–420 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  217. 217.

    Chen, S. et al. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  218. 218.

    Dong, M. B. et al. Systematic immunotherapy target discovery using genome-scale in vivo CRISPR screens in CD8 T cells. Cell 178, 1189–1204.e23 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  219. 219.

    Kwart, D. et al. A large panel of isogenic APP and PSEN1 mutant human iPSC neurons reveals shared endosomal abnormalities mediated by APP β-CTFs, not Aβ. Neuron 104, 256–270.e5 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  220. 220.

    Nugent, A. A. et al. TREM2 regulates microglial cholesterol metabolism upon chronic phagocytic challenge. Neuron 105, 837–854.e9 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  221. 221.

    Andreone, B. J. et al. Alzheimer’s-associated PLCγ2 is a signaling node required for both TREM2 function and the inflammatory response in human microglia. Nat. Neurosci. 23, 927–938 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  222. 222.

    Renner, H. et al. A fully automated high-throughput workflow for 3D-based chemical screening in human midbrain organoids. eLife 9, e52904 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  223. 223.

    Brandenberg, N. et al. High-throughput automated organoid culture via stem-cell aggregation in microcavity arrays. Nat. Biomed. Eng. 4, 863–874 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

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Acknowledgements

L.A.G. is supported by a NIH New Innovator Award (DP2 CA239597), a Pew–Stewart Scholars for Cancer Research award as well as the Goldberg–Benioff Endowed Professorship in Prostate Cancer Translational Biology.

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The authors contributed equally to all aspects of the article.

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Correspondence to Laralynne Przybyla or Luke A. Gilbert.

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L.A.G. has filed patents on CRISPR functional genomics and is a co-founder of Chroma Medicine. The other authors declare no competing interests.

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Related links

BioGRID ORCS: https://orcs.thebiogrid.org/

Cancer Dependency Map (DepMap): https://depmap.org/portal/

Co-essentiality network analysis: http://coessentiality.net

CRISPick: https://portals.broadinstitute.org/gppx/crispick/public

CRISPRbrain: https://crisprbrain.org/

CRISP-view: http://crispview.weililab.org/

Glossary

CRISPR

(Clustered regularly interspaced short palindromic repeats). A family of DNA sequences containing short repetitions that are found in prokaryotic organisms as a form of immunity against viruses together with the Cas family of enzymes.

Genome-wide association studies

(GWAS). Large-scale genome-wide single-nucleotide polymorphism (SNP) analyses comparing genetic variants between a disease population and a control population to identify genetic loci associated with altered disease risk.

Cas9

(CRISPR-associated protein 9). An RNA-guided DNA endonuclease involved in bacterial immunity that has been co-opted for use in mammalian genetic engineering.

dCas9

(Dead Cas9). A catalytically inactive form of Cas9 generated by engineering loss-of-function mutations of the endonuclease domains (D10A and H840A).

Fluorescence-activated cell sorting

(FACS). A method for sorting cells based on their intrinsic properties such as size, shape and fluorescent intensity downstream of a reporter or fluorophore-linked antibody.

Genetic interactions

The sets of functional relationships between genes, which can be used to identify epistatic or synthetic lethal gene interactions.

Induced pluripotent stem cells

(iPS cells). Cells reprogrammed from somatic cells with the ability to self-renew by dividing as well as the ability to differentiate into any cell type in the adult organism, a property known as pluripotency.

Single-nucleotide polymorphism

(SNP). A variation in a single nucleotide in a DNA sequence.

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Przybyla, L., Gilbert, L.A. A new era in functional genomics screens. Nat Rev Genet (2021). https://doi.org/10.1038/s41576-021-00409-w

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