Chen, Xiaoyin, Fischer, Stephan, Rue, Mara CP, Zhang, Aixin, Mukherjee, Didhiti, Kanold, Patrick O, Gillis, Jesse, Zador, Anthony M (April 2024) Whole-cortex in situ sequencing reveals input-dependent area identity. Nature. ISSN 0028-0836
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Abstract
The cerebral cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture1,2, connectivity3,4 and neuronal activity5,6, are wired into modular networks3,4,7. However, it remains unclear whether these spatial organizations are reflected in neuronal transcriptomic signatures and how such signatures are established in development. Here we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell-type marker genes in 10.3 million cells, including 4,194,658 cortical neurons over nine mouse forebrain hemispheres, at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types consistent with previous single-cell RNA sequencing studies8,9. The composition of transcriptomic types is highly predictive of cortical area identity. Moreover, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with areas that are highly connected, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. To explore how the transcriptomic profiles of cortical neurons depend on development, we assessed cell-type distributions after neonatal binocular enucleation. Notably, binocular enucleation caused the shifting of the cell-type compositional profiles of visual areas towards neighbouring cortical areas within the same module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules. Enabled by the high throughput, low cost and reproducibility of BARseq, our study provides a proof of principle for the use of large-scale in situ sequencing to both reveal brain-wide molecular architecture and understand its development.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics bioinformatics > genomics and proteomics neurobiology neurobiology > neuroscience neurobiology > neuroscience > systems neuroscience |
| CSHL Authors: | |
| Communities: | CSHL labs > Gillis Lab CSHL labs > Zador lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 24 April 2024 |
| Date Deposited: | 26 Apr 2024 14:33 |
| Last Modified: | 26 Apr 2024 14:33 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/41516 |
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