Gene

Cell type

Neuroscience

Biology

Identification (biology)

Receptor

Computer science

Botany

Markov random field

Computational biology

Image segmentation

Genetics

Transcriptome

Segmentation

In situ hybridization

Glutamate receptor

Artificial intelligence

Cell

Single-cell analysis

Glutamatergic

Gene expression

Nature Biotechnology

How intrinsic gene-regulatory networks interact with a cell's spatial environment to define its identity remains poorly understood. We developed an approach to distinguish between intrinsic and extrinsic effects on global gene expression by integrating analysis of sequencing-based and imaging-based single-cell transcriptomic profiles, using cross-platform cell type mapping combined with a hidden Markov random field model. We applied this approach to dissect the cell-type- and spatial-domain-associated heterogeneity in the mouse visual cortex region. Our analysis identified distinct spatially associated, cell-type-independent signatures in the glutamatergic and astrocyte cell compartments. Using these signatures to analyze single-cell RNA sequencing data, we identified previously unknown spatially associated subpopulations, which were validated by comparison with anatomical structures and Allen Brain Atlas images.

Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data