Spatial Variation of Cell-Types, Cellular Colocalization, and Intercellular Communication Delineates Brain Tissue Architecture Beyond Morphological Layers

Spatial organization of cell-types, their colocalization patterns, and intercellular communication mechanisms are critical aspects of brain architecture and function. Understanding these aspects requires integrating data from single-cell RNA-Seq (scRNA-seq) and spatial transcriptomics (ST),the two cutting edge technologies that offer complementary insights into tissue architecture and function. Integrating these data types is non-trivial since they differ widely in the number of profiled genes and often do not share marker genes for given cell-types. We developed STANN, a neural network model that overcomes these methodological challenges for single-cell resolution ST data. We applied STANN to assign cell-types in a recent ST dataset (seqFISH+) of mouse olfactory bulb (MOB). Our analysis of STANN’s assigned cell-types revealed principles of MOB architecture and intercellular communication in unprecedented detail and beyond the conventional morphological layer-based description. We find that the proportions of cell-types are consistent within individual morphological layers of MOB, but vary widely between the layers. Surprisingly, even within a morphological layer, we find high spatial variation in cellular colocalization patterns and intercellular communication mechanisms. These observations imply the formation of spatially localized gene regulatory networks, and suggest that spatially localized receptor-ligand usage refines subtypes of major cell-types and play an important role in determining their colocalization patterns.