Spatial multi-omic profiling of non-autonomous transcriptomic and epigenomic responses to genetic perturbation

Abstract

Multicellular organisms develop and maintain differentiated cell states through a combination of cell-autonomous and non-autonomous regulatory mechanisms, including signal transduction pathways mediated by ligands, receptors, and kinases. Genetic perturbation through CRISPR pooled screening is widely used to study cell-autonomous regulatory mechanisms, but the challenges of cellular-resolution in situ measurement have limited the study of non-autonomous regulatory mechanisms. We developed Perturb-Tags, a spatial multi-omic technique for pooled CRISPR screening that tags nuclei with spatial barcodes, allowing joint measurement of single-nucleus gene expression, CRISPR guide RNAs, chromatin accessibility, and spatial positions within intact tissue. Perturb-Tags achieves cellular-resolution, unbiased gene expression and multi-omic profiling, and higher sensitivity than previous spatial perturbation approaches. We used Perturb-Tags to systematically perturb ligands, receptors, and all expressed kinases in human embryoid bodies. These experiments revealed extensive non-autonomous gene expression changes after perturbation, including distance-dependent loss of signaling pathway activity upon ligand knockdown, compensatory upregulation of alternative signaling pathways, and responses to receptor and kinase knockdown that vary with cell microenvironment. We also identified changes in the spatial organization of cells with ligand and kinase knockdowns. Finally, we trained a graph neural network to model the combined effects of genetic perturbations on gene expression and chromatin accessibility across an entire tissue. Our work provides a powerful experimental and computational platform for mechanistic studies of non-autonomous regulatory mechanisms across healthy and diseased tissues.