Journal
NATURE BIOTECHNOLOGY
Volume 36, Issue 12, Pages 1183-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/nbt.4260
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Funding
- Claudia Barr Award
- Chan Zuckerberg Initiative Award
- Paul G. Allen Foundation Discovery Center, NIH [HD075605, TR01 OD024686]
- NIH [R01HL119099]
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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.
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