The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
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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“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]
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“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]
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“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]
In the citing paper
“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]
In the citing paper
“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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Metadata
- 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
- 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
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