Yuan, Li, Chen, Xiaoyin, Zhan, Huiqing, Henry, Gilbert L, Zador, Anthony M (September 2024) Massive multiplexing of spatially resolved single neuron projections with axonal BARseq. Nature Communications, 15 (1). p. 8371. ISSN 2041-1723 (Public Dataset)
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Abstract
Neurons in the cortex are heterogeneous, sending diverse axonal projections to multiple brain regions. Unraveling the logic of these projections requires single-neuron resolution. Although a growing number of techniques have enabled high-throughput reconstruction, these techniques are typically limited to dozens or at most hundreds of neurons per brain, requiring that statistical analyses combine data from different specimens. Here we present axonal BARseq, a high-throughput approach based on reading out nucleic acid barcodes using in situ RNA sequencing, which enables analysis of even densely labeled neurons. As a proof of principle, we have mapped the long-range projections of >8000 primary auditory cortex neurons from a single male mouse. We identified major cell types based on projection targets and axonal trajectory. The large sample size enabled us to systematically quantify the projections of intratelencephalic (IT) neurons, and revealed that individual IT neurons project to different layers in an area-dependent fashion. Axonal BARseq is a powerful technique for studying the heterogeneity of single neuronal projections at high throughput within individual brains.
| Item Type: | Paper |
|---|---|
| Subjects: | Investigative techniques and equipment organs, tissues, organelles, cell types and functions > tissues types and functions > auditory cortex Investigative techniques and equipment > BARseq organs, tissues, organelles, cell types and functions organs, tissues, organelles, cell types and functions > tissues types and functions |
| CSHL Authors: | |
| Communities: | CSHL labs > Zador lab CSHL labs > Zhan lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 27 September 2024 |
| Date Deposited: | 30 Sep 2024 12:57 |
| Last Modified: | 30 Sep 2024 12:57 |
| PMCID: | PMC11437104 |
| Related URLs: | |
| Dataset ID: |
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| URI: | https://repository.cshl.edu/id/eprint/41687 |
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