Abstract
Single-cell RNA sequencing (scRNA-seq) has revolutionized transcriptomic studies by providing unprecedented cellular and molecular throughputs, but spatial information of individual cells is lost during tissue dissociation. While imaging-based technologies such as in situ sequencing show great promise, technical difficulties currently limit their wide usage. Here we hypothesize that cellular spatial organization is inherently encoded by cell identity and can be reconstructed, at least in part, by ligand-receptor interactions, and we present CSOmap, a computational tool to infer cellular interaction de novo from scRNA-seq. We show that CSOmap can successfully recapitulate the spatial organization of multiple organs of human and mouse including tumor microenvironments for multiple cancers in pseudo-space, and reveal molecular determinants of cellular interactions. Further, CSOmap readily simulates perturbation of genes or cell types to gain novel biological insights, especially into how immune cells interact in the tumor microenvironment. CSOmap can be a widely applicable tool to interrogate cellular organizations based on scRNA-seq data for various tissues in diverse systems.
Highlights
High-throughput single-cell RNA sequencing has emerged as a revolutionary approach to dissect cellular compositions and characterize molecular properties of complex tissues,[1] and has been applied to a wide range of fields resulting in profound discoveries.[2]
The spatial organization of individual cells has recently been shown to be self-assembled via ligand-receptor interactions,[11,12] implying that cellular spatial organization is inherently encoded by their identity
Overview of CSOmap With the hypothesis that cell spatial organization is inherently encoded by cell identity, we formulate the computation process from scRNA-seq data to cell spatial organization based on three assumptions: (1) the potential of cellular interactions can be approximated by a function of the abundance of interacting ligands and receptors, and their affinity; (2) cells with high interacting potentials tend to locate in close proximity; (3) cells compete for their interacting partners due to physiological and spatial constraints
Summary
High-throughput single-cell RNA sequencing (scRNA-seq) has emerged as a revolutionary approach to dissect cellular compositions and characterize molecular properties of complex tissues,[1] and has been applied to a wide range of fields resulting in profound discoveries.[2] spatial information of individual cells is lost during the process of tissue dissociation. We argue that the spatial relationship of cells may be reconstructed de novo, at least in part, by integrating scRNAseq data with ligand-receptor interaction information. We formulate this hypothesis as a mathematical model, referred to as CSOmap (Cellular Spatial Organization mapper), and evaluate its performance computationally and experimentally on a diverse scRNA-seq datasets for various human and mouse tissues. We applied CSOmap to tumorinfiltrating immune cells and gained new insights into the role of regulatory T cells in tumor immunity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
