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 "slug": "genetic-screen",
 "title": "Genetic screen",
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 "excerpt": "A genetic screen systematically creates or introduces mutations across many genes in cells or organisms and identifies which genes affect a chosen phenotype, now often by pooled CRISPR sequencing.",
 "snippet": "A genetic screen systematically creates or introduces mutations across many genes in cells or organisms and identifies which genes affect a chosen phenotype, now often by pooled CRISPR sequencing.",
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 "markdown": "# Genetic screen\n\nA genetic screen systematically creates or introduces mutations across many genes in cells or organisms and identifies which genes affect a chosen phenotype or biological process. A screen yields three linked products: mutant strains or alleles, phenotypic measurements, and a ranked list of candidate genes. Modern pooled CRISPR screens deliver a guide RNA library into cells and read out enriched or depleted guides by deep sequencing.<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> Published screens have produced lists such as genes controlling melanoma resistance to vemurafenib<sup>[2](https://doi.org/10.1126/science.1247005)</sup> and the full set of expected [DNA mismatch repair](https://www.edgepedia.org/dna-mismatch-repair) genes recovered in a 6-thioguanine resistance screen.<sup>[3](https://doi.org/10.1126/science.1246981)</sup>\n\n| Key fact | Value |\n|---|---|\n| Primary output | Ranked gene lists, mutant alleles, and phenotypic measurements from selection or assay<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> |\n| GeCKO CRISPR library | 18,080 genes targeted by 64,751 unique guide sequences<sup>[2](https://doi.org/10.1126/science.1247005)</sup> |\n| Pooled-screen coverage | 200 cells per sgRNA at infection, 1,000 cells per sgRNA during selection and sequencing<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> |\n| ENU mutagenesis rate in mice | One point mutation every 0.5–16 Mb, depending on strain and dose<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup> |\n| Sequencing depth | Marginal benefit above 25 reads per guide; more guides at lower depth gives more power<sup>[5](https://link.springer.com/article/10.1186/s13059-020-01972-x)</sup> |\n| CRISPR vs shRNA essential-gene detection | At a 10% false-positive rate, ~4,500 genes (Cas9) vs ~3,100 (shRNA)<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)</sup> |\n\n## How it works\n\nThe core logic is to perturb many genes, apply a selection or measure a phenotype, and infer genotype–phenotype relationships from which perturbations change the outcome. In the standard CRISPR knockout format, the Streptococcus pyogenes Cas9 protein complexes with a 110-nucleotide sgRNA whose 20-nucleotide sequence binds the target DNA and induces a double-strand break; repair by non-homologous end joining typically destroys gene function.<sup>[5](https://link.springer.com/article/10.1186/s13059-020-01972-x)</sup> A pooled screen transduces an sgRNA plasmid library into cells expressing Cas9 for knockout, dCas9 fused to a repressor for CRISPRi, or dCas9 fused to an activator for CRISPRa, then selects on a phenotype and identifies enriched or depleted sgRNAs by deep sequencing.<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> Early Cas9 screens showed high consistency between independent guides targeting the same gene, high editing rates, and large phenotypic effects.<sup>[7](https://www.nature.com/articles/nrg3899)</sup>\n\n## How it is done\n\n**Classical mutagenesis screens** begin with a mutagen such as ENU, which in mice induces a point mutation every 0.5–16 Mb depending on strain and dose, about 100 times the spontaneous human per-generation rate, and acts mainly on spermatogonial stem cells.<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup> ENU-induced mutations are about 63% missense, 26% splicing, 10% nonsense, and 1% \"make-sense\", producing allelic series that include hypomorphs and dominant-negative alleles.<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup> Affected genes are then mapped by positional cloning, which takes several months to a year and requires up to 1,500 recombination opportunities, using genome-wide SNP panels.<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup>\n\n**Pooled CRISPR screens** follow a defined workflow: construct or obtain an sgRNA library, transduce cells at a virus dose giving 20%–50% infected cells so most cells carry roughly one sgRNA, maintain 200 cells per sgRNA at infection and 1,000 per sgRNA during selection, growth, and sequencing.<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> For drug screens, a resistance screen uses a sub-lethal concentration causing about 5% cell death in 24–48 h, while a sensitivity screen starts near 50% cell death.<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup> Analysis typically defaults to MAGeCK RRA, reported by [Wei Li](https://www.edgepedia.org/wei-li), X. Shirley Liu, and colleagues in 2014<sup>[8](https://doi.org/10.1186/s13059-014-0554-4)</sup>, with CRISPhieRmix, from Timothy P. Daley, [Lei S. Qi](https://www.edgepedia.org/lei-stanley-qi), and colleagues in 2018, preferred when guide efficiency is highly variable, as in CRISPRi and CRISPRa screens.<sup>[5](https://link.springer.com/article/10.1186/s13059-020-01972-x)</sup><sup> • </sup><sup>[9](https://doi.org/10.1186/s13059-018-1538-6)</sup> The casTLE package computes gene-level enrichment as a median-normalized log ratio of counts with a confidence score equal to twice the log-likelihood ratio.<sup>[1](https://doi.org/10.1016/j.xpro.2023.102201)</sup>\n\n**Validation** uses independent guides (consistency between guides targeting the same gene was high in the GeCKO screens<sup>[2](https://doi.org/10.1126/science.1247005)</sup>), transcriptional repression, protein inhibition, independent knockout generation, pathway-level analysis, and genetic complementation rescue, which is described as the strongest evidence.<sup>[10](https://mdpi-res.com/d_attachment/cancers/cancers-13-01591/article_deploy/cancers-13-01591-v3.pdf?version=1617938138)</sup> In forward screens, direct evidence means genetic rescue with a wild-type copy or complementation against a known allele.<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup>\n\n## Origin\n\nAn early related demonstration that mutations can be induced and assigned to genes came from G. W. Beadle and E. L. Tatum's work on genetic control of biochemical reactions in [Neurospora](https://www.edgepedia.org/neurospora), published in the [Proceedings of the National Academy of Sciences](https://www.edgepedia.org/proceedings-of-the-national-academy-of-sciences) in 1941.<sup>[11](https://doi.org/10.1073/pnas.27.11.499)</sup> Genome-scale CRISPR-Cas9 knockout screening in human cells was reported in 2013 in Science by Ophir Shalem and colleagues, whose GeCKO lentiviral sgRNA libraries targeted 18,080 genes with 64,751 unique guide sequences<sup>[2](https://doi.org/10.1126/science.1247005)</sup>, and in the same year by Tim Wang and colleagues, who used lentiviral genome-scale sgRNA libraries for genetic screens in human cells.<sup>[3](https://doi.org/10.1126/science.1246981)</sup> [High-throughput screening](https://www.edgepedia.org/high-throughput-screening) of a CRISPR/Cas9 library for functional genomics in human cells was reported by Yuexin Zhou and colleagues in Nature in 2014.<sup>[12](https://doi.org/10.1038/nature13166)</sup>\n\n## Variants\n\nForward screen designs include genome-wide, region-specific, modifier (suppressor/enhancer), non-complementation, and balancer screens; a modifier screen recovers new genes that suppress or enhance a phenotype of interest.<sup>[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)</sup> In the CRISPR era, CRISPRko libraries (~20,000 targeting molecules) serve loss-of-function and synthetic-lethal screens, CRISPRa libraries support gain-of-function screens, and CRISPRi libraries block transcription start sites.<sup>[10](https://mdpi-res.com/d_attachment/cancers/cancers-13-01591/article_deploy/cancers-13-01591-v3.pdf?version=1617938138)</sup> CRISPRi, reported by Lei S. Qi, Jonathan S. Weissman, Adam P. Arkin, [Wendell A. Lim](https://www.edgepedia.org/wendell-a-lim), and colleagues in Cell in 2013, uses a deactivated Cas effector to block transcription initiation or elongation reversibly<sup>[13](https://doi.org/10.1016/j.cell.2013.02.022)</sup>; genome-scale CRISPRi and CRISPRa screening was reported by [Luke A. Gilbert](https://www.edgepedia.org/luke-a-gilbert), Jonathan S. Weissman, and colleagues in 2014<sup>[14](https://doi.org/10.1016/j.cell.2014.09.029)</sup>, and genome-scale transcriptional activation with the engineered SAM complex by Silvana Konermann, Feng Zhang, and colleagues the same year.<sup>[15](https://doi.org/10.1038/nature14136)</sup>\n\nReadout variants include FACS-based screens on protein-level fluorescence, such as a genome-wide Hedgehog-regulator screen using the Brie library in an SHH-responsive GFP reporter line<sup>[10](https://mdpi-res.com/d_attachment/cancers/cancers-13-01591/article_deploy/cancers-13-01591-v3.pdf?version=1617938138)</sup>, optical pooled screens in human cells, reported by David Feldman, Paul C. Blainey, [Feng Zhang](https://www.edgepedia.org/feng-zhang), and colleagues in 2019, which read phenotypes by imaging while sequencing guides in the same population<sup>[16](https://doi.org/10.1016/j.cell.2019.09.016)</sup>, and single-cell readouts from Perturb-seq, reported by Atray Dixit, Aviv Regev, Jonathan S. Weissman, and colleagues in 2016<sup>[17](https://doi.org/10.1016/j.cell.2016.11.038)</sup>, and CROP-seq, reported by Paul Datlinger, Christoph Bock, and colleagues in 2017.<sup>[18](https://doi.org/10.1038/nmeth.4177)</sup> Combinatorial designs map genetic interactions de novo, as in the pairwise CRISPR–Cas9 screens reported by John Paul Shen, Trey Ideker, Prashant Mali, and colleagues in 2017<sup>[19](https://doi.org/10.1038/nmeth.4225)</sup>, the CDKO double-knockout system reported by Kyuho Han, Michael C. Bassik, and colleagues in 2017<sup>[20](https://doi.org/10.1038/nbt.3834)</sup>, and orthologous Cas9 enzymes for combinatorial screens reported by Fadi J. Najm, [John G. Doench](https://www.edgepedia.org/john-g-doench), and colleagues in 2017.<sup>[21](https://doi.org/10.1038/nbt.4048)</sup> [Prime editing](https://www.edgepedia.org/prime-editing), reported by Andrew V. Anzalone, David R. Liu, and colleagues in 2019, installs search-and-replace edits without double-strand breaks or donor DNA<sup>[22](https://doi.org/10.1038/s41586-019-1711-4)</sup>, enabling saturation prime editing of variant libraries, first implemented by Steven Erwood, Ronald D. Cohn, and colleagues in 2022<sup>[23](https://doi.org/10.1038/s41587-021-01201-1)</sup>, and base-editor variant screens reported by Ruth E. Hanna, John G. Doench, and colleagues in 2021.<sup>[24](https://doi.org/10.1016/j.cell.2021.01.012)</sup> Pooled CRISPR screening has also moved into whole animals and spatial readouts: AAV-Perturb-seq, reported by Antonio J. Santinha, Denis Jabaudon, Randall J. Platt, and colleagues in Nature in 2023, enables direct in vivo single-cell CRISPR screens in adult animals<sup>[25](https://doi.org/10.1038/s41586-023-06570-y)</sup><sup> • </sup><sup>[26](https://www.nature.com/articles/s41576-025-00873-8)</sup>, PerturbView, reported by Takamasa Kudo, Eric Lubeck, Aviv Regev, and colleagues in 2024, performs multiplexed image-based pooled screens in primary cells and tissues<sup>[27](https://doi.org/10.1038/s41587-024-02391-0)</sup>, Perturb-Multimodal, reported by Reuben A. Saunders, Xiaowei Zhuang, Jonathan S. Weissman, and colleagues in 2025, combines imaging and sequencing in intact mammalian tissue<sup>[28](https://doi.org/10.1016/j.cell.2025.05.022)</sup>, and CRISPR–StAR, reported by Esther C. H. Uijttewaal, Ulrich Elling, and colleagues in 2024, enables high-resolution screening in complex in vivo models.<sup>[29](https://doi.org/10.1038/s41587-024-02512-9)</sup>\n\n## Applications\n\nScreens are used across developmental biology, drug-response genetics, and target discovery. Drug-resistance screens identify genes whose loss confers resistance: the GeCKO vemurafenib screen in melanoma recovered the validated genes NF1 and MED12 plus novel hits NF2, CUL3, TADA2B, and TADA1<sup>[2](https://doi.org/10.1126/science.1247005)</sup>, while the etoposide screen identified TOP2A, as expected, and CDK6.<sup>[3](https://doi.org/10.1126/science.1246981)</sup> Genome-scale knockout screens across many cell lines support cancer therapeutic target prioritization, as in the framework reported by Fiona M. Behan, [Mathew J. Garnett](https://www.edgepedia.org/mathew-j-garnett), and colleagues in Nature in 2019<sup>[30](https://doi.org/10.1038/s41586-019-1103-9)</sup>, and pooled fitness screens map essential genes across cell types.<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)</sup>\n\n## Limitations and alternatives\n\n**Failure modes** are well characterized. In CRISPRko screens, cell death from excessive cutting in high copy-number regions creates false positives, and variability in guide efficiency causes both false positives and false negatives.<sup>[5](https://link.springer.com/article/10.1186/s13059-020-01972-x)</sup> sgRNA variability also arises because cutting creates a mixture of true knockouts, heterozygotes, and wild-type cells; in-frame indels that restore reading frames can interfere with results.<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)</sup> CRISPRi off-targets include bad-seed effects from short (4–5 nt) guide-target complementarity, and multiple guides per gene are needed for reliable hit-calling in larger genomes.<sup>[31](https://lirias.kuleuven.be/retrieve/8d901064-5a77-4aae-a5d1-c0b2777905b7)</sup> High dCas9 protein levels are associated with toxicity, and cellular compensation through redundant genes and protein-level buffering can mask perturbation effects, yielding reduced or no phenotype.<sup>[31](https://lirias.kuleuven.be/retrieve/8d901064-5a77-4aae-a5d1-c0b2777905b7)</sup> A typical [CRISPR screen](https://www.edgepedia.org/crispr-screen) has a false-negative rate of about 20%, part of which can be recovered computationally, though library design and modality-specific standards for evaluating false negatives and off-target effects continue to evolve.<sup>[7](https://www.nature.com/articles/nrg3899)</sup>\n\n**Comparison with RNAi.** In parallel K562 screens, a 25-hairpin-per-gene shRNA library and a 4-sgRNA-per-gene CRISPR library detected essential genes with similar precision (ROC AUC above 0.90 against a gold standard of 217 essential and 947 nonessential genes); at a 10% false-positive rate the Cas9 screen identified about 4,500 genes versus about 3,100 for shRNA, with about 1,200 found in both.<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)</sup> Combining both datasets raised the AUC to 0.98 and recovered over 85% of gold-standard essential genes at about 1% false-positive rate, suggesting the technologies reveal different biology.<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)</sup> A separate comparison found CRISPR knockout screening outperforms shRNA and CRISPRi for identifying essential genes, in a study reported by Bastiaan Evers, Rene Bernards, and colleagues in 2016.<sup>[32](https://doi.org/10.1038/nbt.3536)</sup> RNAi silencing is reversible with inducible promoters but shows polar and extensive off-target effects that generate false positives, and the RNAi machinery's cytoplasmic localization restricts its use.<sup>[31](https://lirias.kuleuven.be/retrieve/8d901064-5a77-4aae-a5d1-c0b2777905b7)</sup> Copy-number bias can be corrected computationally by CERES, reported by Robin M. Meyers, Aviad Tsherniak, and colleagues in 2017, but only in multi-cell-line experiments with known copy-number profiles.<sup>[5](https://link.springer.com/article/10.1186/s13059-020-01972-x)</sup><sup> • </sup><sup>[33](https://doi.org/10.1038/ng.3984)</sup>\n\n## References\n\n1. [Protocol for performing pooled CRISPR-Cas9 loss-of-function screens (STAR Protocols, 2023)](https://doi.org/10.1016/j.xpro.2023.102201)\n2. [Ophir Shalem and colleagues (2013). Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells. Science.](https://doi.org/10.1126/science.1247005)\n3. [Tim Wang and colleagues (2013). Genetic Screens in Human Cells Using the CRISPR-Cas9 System. Science.](https://doi.org/10.1126/science.1246981)\n4. [Creating a 'hopeful monster': Mouse forward genetic screens](https://pmc.ncbi.nlm.nih.gov/articles/PMC3827720/)\n5. [A benchmark of algorithms for the analysis of pooled CRISPR screens (Genome Biology)](https://link.springer.com/article/10.1186/s13059-020-01972-x)\n6. [Systematic comparison of CRISPR-Cas9 and RNAi screens for essential genes (Morgens et al., Nat Biotechnol 2016)](https://pmc.ncbi.nlm.nih.gov/articles/PMC4900911/)\n7. [High-throughput functional genomics using CRISPR–Cas9 (Nature Reviews Genetics)](https://www.nature.com/articles/nrg3899)\n8. [Wei Li and colleagues (2014). MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome biology.](https://doi.org/10.1186/s13059-014-0554-4)\n9. [Timothy P. Daley and colleagues (2018). CRISPhieRmix: a hierarchical mixture model for CRISPR pooled screens. Genome biology.](https://doi.org/10.1186/s13059-018-1538-6)\n10. [CRISPR Screens in Synthetic Lethality and Combinatorial Therapies for Cancer (Cancers, 2021)](https://mdpi-res.com/d_attachment/cancers/cancers-13-01591/article_deploy/cancers-13-01591-v3.pdf?version=1617938138)\n11. [G. W. Beadle, E. L. Tatum (1941). Genetic Control of Biochemical Reactions in Neurospora. Proceedings of the National Academy of Sciences.](https://doi.org/10.1073/pnas.27.11.499)\n12. [Yuexin Zhou and colleagues (2014). High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells. Nature.](https://doi.org/10.1038/nature13166)\n13. [Lei S. Qi and colleagues (2013). Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression. Cell.](https://doi.org/10.1016/j.cell.2013.02.022)\n14. [Luke A. Gilbert and colleagues (2014). Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation. Cell.](https://doi.org/10.1016/j.cell.2014.09.029)\n15. [Silvana Konermann and colleagues (2014). Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature.](https://doi.org/10.1038/nature14136)\n16. [David Feldman and colleagues (2019). Optical Pooled Screens in Human Cells. Cell.](https://doi.org/10.1016/j.cell.2019.09.016)\n17. [Atray Dixit and colleagues (2016). Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens. Cell.](https://doi.org/10.1016/j.cell.2016.11.038)\n18. [Paul Datlinger and colleagues (2017). Pooled CRISPR screening with single-cell transcriptome readout. Nature Methods.](https://doi.org/10.1038/nmeth.4177)\n19. [John Paul Shen and colleagues (2017). Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions. Nature Methods.](https://doi.org/10.1038/nmeth.4225)\n20. [Kyuho Han and colleagues (2017). Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nature Biotechnology.](https://doi.org/10.1038/nbt.3834)\n21. [Fadi J Najm and colleagues (2017). Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens. Nature Biotechnology.](https://doi.org/10.1038/nbt.4048)\n22. [Andrew V. Anzalone and colleagues (2019). Search-and-replace genome editing without double-strand breaks or donor DNA. Nature.](https://doi.org/10.1038/s41586-019-1711-4)\n23. [Steven Erwood and colleagues (2022). Saturation variant interpretation using CRISPR prime editing. Nature Biotechnology.](https://doi.org/10.1038/s41587-021-01201-1)\n24. [Ruth E. Hanna and colleagues (2021). Massively parallel assessment of human variants with base editor screens. Cell.](https://doi.org/10.1016/j.cell.2021.01.012)\n25. [Antonio J. Santinha and colleagues (2023). Transcriptional linkage analysis with in vivo AAV-Perturb-seq. Nature.](https://doi.org/10.1038/s41586-023-06570-y)\n26. [Methods and applications of in vivo CRISPR screening (Nature Reviews Genetics, 2025)](https://www.nature.com/articles/s41576-025-00873-8)\n27. [Takamasa Kudo and colleagues (2024). Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView. Nature Biotechnology.](https://doi.org/10.1038/s41587-024-02391-0)\n28. [Reuben A. Saunders and colleagues (2025). Perturb-Multimodal: A platform for pooled genetic screens with imaging and sequencing in intact mammalian tissue. Cell.](https://doi.org/10.1016/j.cell.2025.05.022)\n29. [Esther C. H. Uijttewaal and colleagues (2024). CRISPR-StAR enables high-resolution genetic screening in complex in vivo models. Nature Biotechnology.](https://doi.org/10.1038/s41587-024-02512-9)\n30. [Fiona M. Behan and colleagues (2019). Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens. Nature.](https://doi.org/10.1038/s41586-019-1103-9)\n31. [The rise and future of CRISPR-based approaches for high-throughput genomics (Vercauteren et al., review)](https://lirias.kuleuven.be/retrieve/8d901064-5a77-4aae-a5d1-c0b2777905b7)\n32. [Bastiaan Evers and colleagues (2016). CRISPR knockout screening outperforms shRNA and CRISPRi in identifying essential genes. Nature Biotechnology.](https://doi.org/10.1038/nbt.3536)\n33. [Robin M Meyers and colleagues (2017). Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells. Nature Genetics.](https://doi.org/10.1038/ng.3984)\n\n---\n*Topic: Encyclopedia › Life and health › Biological foundations › Genetics and genomic reference › Mutation and mutagenesis*\n\n*Initially written Sep 29, 2026 · Edited: Oct 15, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n",
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 "speakable": "A genetic screen systematically creates or introduces mutations across many genes in cells or organisms and identifies which genes affect a chosen phenotype, now often by pooled CRISPR sequencing."
}