Exploring genetic interaction manifolds constructed from rich single-cell phenotypes

作者：Thomas M. Norman, Max A. Horlbeck, Joseph M. Replogle, Alex Y. Ge, Albert Xu, Marco Jost, Luke A. Gilbert, Jonathan S. Weissman · 发表于：Science · 年份：2019 · DOI：10.1126/science.aax4438 · 被引用次数：407 · 研究领域：Single-cell and spatial transcriptomics、Gene Regulatory Network Analysis、Bioinformatics and Genomic Networks

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