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Updated: Jul 3, 2026
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Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex
Published on: September 5, 2018
Connecting single-cell transcriptomes to projectomes in the mouse visual cortex
Staci A Sorensen1, Nathan W Gouwens2, Yun Wang2
1Allen Institute for Brain Science, Seattle, WA, USA. stacis@alleninstitute.org.
Nature
|July 1, 2026
Summary
Researchers created a new way to classify brain cells by linking gene activity to their structure and electrical signals. This helps map neuron connections and understand brain circuitry, advancing our knowledge of the mammalian brain.
Area of Science:
- Neuroscience
- Genomics
- Computational Biology
Background:
- Mammalian brains have diverse neuron types with distinct functions.
- Single-cell RNA sequencing has enabled transcriptomic cell-type classification.
- Patch-seq links transcriptomics to morphology and electrophysiology, but axonal projections remain poorly understood.
Purpose of the Study:
- To integrate transcriptomic, morphological, and electrophysiological data to classify neuron types.
- To predict long-range axonal projection targets based on cell type.
- To establish a comprehensive taxonomy of cortical excitatory neuron types.
Main Methods:
- Collected Patch-seq data from 1,528 mouse visual cortex excitatory neurons.
- Acquired whole-neuron morphologies for 341 excitatory neurons.
- Developed a multistep classifier to integrate multimodal cell data and predict projection targets.
Main Results:
- Defined 17 morphoelectric-transcriptomic neuron types.
- Transcriptomic variation correlates with morphological and electrophysiological phenotypes.
- Gene expression and location predict projection targets, revealing novel signatures for layer 5 neurons.
Conclusions:
- Established a comprehensive, integrated taxonomy of cortical excitatory neurons.
- Developed a high-dimensional cell-type classification system applicable brain-wide and across species.
- Provided new insights into the axonal circuitry of specific neuron populations.
