Spatial organization of cell types in the mouse cortex revealed by multiplexed single-molecule fluorescent in situ hybridization
Lars E. Borm1,*, Simone Codeluppi1,2,*, Josina A. Van Lunteren3, Gioele La Manno1, Amit Zeisel1, Sten Linnarsson1
1Unit of Molecular Neurobiolology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden;2Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden;3Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
*The authors contributed equally and will present the poster
The recent developments in single cell transcriptomics enable the unbiased classification of cell types, revealing the heterogeneity and complexity of many brain regions. However, since single cell RNA sequencing requires tissue dissociation, the spatial information is absent from the generated datasets. Therefore, while the molecular identity of the tissue constituents is known, it remains poorly understood how all these cell types are spatially organized in the tissue. The aim of this work is to generate a quantitative high resolution spatial cell-type map of the mouse somatosensory cortex, hippocampal CA1 and ventricle using multiplexed single molecule fluorescent in situ hybridization (MsmFISH). We quantified the expression level of 35 marker genes in 14000 cells by sequentially applying a three-target smFISH protocol. Along with the cell’s position in the tissue, the molecular identity of each cell was classified based on cell types identified by single cell RNA-seq. These quantitative spatial data provide important insights into the abundance, patterning and region specific distribution of cell types. Furthermore, it gives a comprehensive view on complex functional units that involve many different cell types, such as the ones that regulate blood vessels function in the brain. This study demonstrates the potential of MsmFISH as an extremely versatile technique that can reconnect single cell data with the tissue of origin. Moreover, it can be used to make a quantitative high resolution whole brain cell type map, which will be a valuable resource for neuroscience.
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