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Related Experiment Video

Updated: Jul 6, 2025

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Published on: September 5, 2018

Connecting single-cell transcriptomes to projectomes in mouse visual cortex.

Staci A Sorensen¹, Nathan W Gouwens¹, Yun Wang¹

¹Allen Institute for Brain Science.

Biorxiv : the Preprint Server for Biology

|January 3, 2024

Summary

This summary is machine-generated.

Researchers created a new method to classify brain cells by combining gene activity, shape, and electrical properties. This approach helps predict how different neuron types connect across the brain, advancing our understanding of neural circuits.

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Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

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Published on: October 26, 2018

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Last Updated: Jul 6, 2025

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Published on: September 5, 2018

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

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Published on: November 21, 2023

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Published on: October 26, 2018

Area of Science:

Neuroscience
Genomics
Computational Biology

Background:

The mammalian brain contains diverse neuron types crucial for function.
Single-cell RNA sequencing has defined transcriptomic cell types.
Integrating transcriptomics with morphology and electrophysiology is key to understanding neural circuits.

Approach:

Collected coordinated Patch-seq and whole-brain morphology data for mouse visual cortex excitatory neurons.
Defined 16 integrated morpho-electric-transcriptomic (MET)-types using Patch-seq data.
Developed a multi-step classifier to unify transcriptomic, morphological, and electrophysiological data.

Key Points:

Transcriptomic variations correlate with morphological and electrophysiological phenotypes.
Cellular properties and anatomical location predict neuron projection targets.
New insights into infragranular cell types and their specific long-range projections were revealed.

Conclusions:

Established a comprehensive, integrated taxonomy of excitatory neuron types in the mouse visual cortex.
Created a system for high-dimensional cell type classification applicable brain-wide.
This integrated approach can be extended across species for broader neuroscience research.