Immunology Driven by Large-Scale Single-Cell Sequencing. Issue 11 (November 2019) - Gomes, Tomás; Teichmann, Sarah A.; Talavera-López, Carlos
Abstract : The immune system encompasses a large degree of phenotypic diversity and plasticity in its cell types, and more is to be uncovered. We argue that large, multiomic datasets of single-cell resolution, in conjunction with improved computational methods, will be essential to resolving immune cell identity. Existing datasets, combined with 'big data' methodologies, can serve as a platform to support future studies in immunology. Technical and analytical advances in multiomics and spatial integration can provide a reference for gene regulation and cellular interactions in spatially structured tissue contexts. We posit that these developments may allow guided functional studies of immune cell populations and lay the groundwork for informed cell engineering and precision medicine. Highlights: Cell-type references generated from collections of single-cell RNA sequencing data can accelerate the functional characterization of diseases. Computational methods process and analyze sequencing data for a detailed characterization of cellular phenotypes. Single-cell profiling of different molecular layers can give further functional context to cell-type identity. The addition of spatial information can reveal immune cell function in tissue contexts.