Exploring genetic interaction manifolds constructed from rich single-cell phenotypes

Thomas M. Norman, Max A. Horlbeck, Joseph M. Replogle, Alex Y. Ge, Albert Xu, Marco Jost, Luke A. Gilbert, Jonathan S. Weissman

Science · 2019 · 374 citations · 29 references

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Abstract

Manifold destiny Mapping of genetic interactions (GIs) is usually based on cell fitness as the phenotypic readout, which obscures the mechanistic origin of interactions. Norman et al. developed a framework for mapping and understanding GIs. This approach leverages high-dimensional single-cell RNA sequencing data gathered from CRISPR-mediated, pooled perturbation screens. Diverse transcriptomic phenotypes construct a “manifold” representing all possible states of the cell. Each perturbation and GI projects the cell state to a particular position on this manifold, enabling unbiased ordering of genes in pathways and systematic classifications of GIs. Science , this issue p. 786

References

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