Connecting single-cell transcriptomes to projectomes in mouse visual cortex

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.

Purpose of the Study:

• To develop an integrated classification system for excitatory neurons in the mouse visual cortex.
• To correlate transcriptomic, morphological, and electrophysiological properties with neuronal projection targets.
• To establish a comprehensive taxonomy of excitatory neuron types and their circuit-level organization.

Main Methods:

• Collected coordinated Patch-seq (transcriptomics, electrophysiology) and whole-brain morphology data from 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 and morphological datasets for cross-modality analysis.

Main Results:

• Transcriptomic variations within and across MET-types correlate with distinct morphological and electrophysiological phenotypes.
• Neuronal anatomical location and transcriptomic variation predict projection targets.
• Identified cell-type-specific, interhemispheric projections, providing new insights into infragranular circuits.

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.