Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics

Abstract

The spatial organization of cell types in tissues fundamentally shapes cellular interactions and function, but the high-throughput spatial mapping of complex tissues remains a challenge. We present сell2location, a principled and versatile Bayesian model that integrates single-cell and spatial transcriptomics to map cell types in situ in a comprehensive manner. We show that сell2location outperforms existing tools in accuracy and comprehensiveness and we demonstrate its utility by mapping two complex tissues. In the mouse brain, we use a new paired single nucleus and spatial RNA-sequencing dataset to map dozens of cell types and identify tissue regions in an automated manner. We discover novel regional astrocyte subtypes including fine subpopulations in the thalamus and hypothalamus. In the human lymph node, we resolve spatially interlaced immune cell states and identify co-located groups of cells underlying tissue organisation. We spatially map a rare pre-germinal centre B-cell population and predict putative cellular interactions relevant to the interferon response. Collectively our results demonstrate how сell2location can serve as a versatile first-line analysis tool to map tissue architectures in a high-throughput manner.

Transcriptome-wide spatial RNA profiling maps the cellular architecture of the developing human neocortex

“…To accurately map cell types in WTA data, we incorporated CountCorrect into the cell2location spatial mapping algorithm 27 . The resulting cell2location-WTA model provides a scalable workflow to integrate scRNA-seq and WTA data and estimate the abundance of individual cell types in bulk or segmented WTA datasets.…”

“…Figures 6, 7 and 8c. We constructed cell type reference expression profiles by averaging the counts in each cell type cluster in the reference study 16,27 , resulting in 16 profiles for the main types and 78 profiles for the subtypes. We supplied raw (i.e.…”

“…WTA and scRNA-seq integration maps cell types at scale Spatial mapping of resident cell types across complex tissues can offer new perspectives into cellular signalling, tissue development and function. The integration of single-cell and spatial transcriptomic data, where cell types are defined using scRNA-seq and then resolved across spatially assayed tissue locations, offers a scalable workflow to map cell types in situ [26][27][28] .…”

“…Here, we sought to resolve cell types in WTA data and map their spatial distribution in the developing human neocortex. We computationally integrated our WTA dataset with a scRNA-seq reference of the mid-gestation human neocortex 16 using the cell2location model 27 . (Fig.…”

Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro

“…The spatial arrangement of cells is key to understanding a morphologically complex tissue such as the endometrium, where a cell's function may differ depending on signals it receives from neighbouring cells (16). Many spatiallyresolved transcriptomics methods are not quite at single-cell resolution, and rely on the computational integration of coupled single-cell (or single nuclei) transcriptomes to achieve this level of detail (17)(18)(19). These genomic technologies are the basis of the Human Cell Atlas initiative, which aims to map all cells in the human body (20).…”