High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing

Chen, X., Sun, Y. C., Zhan, H., Kebschull, J. M., Fischer, S., Matho, K., Huang, Z. J., Gillis, J., Zador, A. M. (October 2019) High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing. Cell, 179 (3). 772-786.e19. ISSN 0092-8674 (Public Dataset)

URL: https://www.ncbi.nlm.nih.gov/pubmed/31626774
DOI: 10.1016/j.cell.2019.09.023

Abstract

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single-neuron resolution and high throughput, a challenging combination with conventional methods. Here, we introduce barcoded anatomy resolved by sequencing (BARseq), a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3,579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (intratelencephalic [IT], pyramidal tract-like [PT-like], and corticothalamic [CT]) of projection neurons. In depth analysis uncovered a projection type restricted almost exclusively to transcriptionally defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

Item Type: Paper
Uncontrolled Keywords:
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene expression
neurobiology > neuroanatomy
Investigative techniques and equipment > Whole Brain Circuit Mapping
CSHL Authors:
Communities: CSHL labs > Gillis Lab
CSHL labs > Huang lab
CSHL labs > Zador lab
Watson School
Watson School > Publications
Depositing User: Matthew Dunn
Date: 17 October 2019
Date Deposited: 08 Nov 2019 18:07
Last Modified: 07 May 2020 17:26
Related URLs:
Dataset ID:
  • doi: 10.17632/mk82s9x82t.1, 10.17632/g7kdxznt6w.1, 10.17632/86wf7xfz5x.1, 10.17632/2w649fccnt.1
  • doi: 10.17632/mk82s9x82t.1, 10.17632/g7kdxznt6w.1, 10.17632/86wf7xfz5x.1, 10.17632/2w649fccnt.1
URI: https://repository.cshl.edu/id/eprint/38656

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