Mapping brain-wide monosynaptic inputs to single neurons with ROInet-seq.

Area of Science:

• Neuroscience
• Systems Neuroscience
• Molecular Biology

Background:

• Viral tracing methods like G-deleted rabies virus (ΔG-RV) map neuronal connections but lack single-cell resolution.
• Understanding mammalian brain connectomes requires methods that can trace networks at the cellular level.

Purpose of the Study:

• To develop a barcoded ΔG-RV system for quantitative RNA-sequencing to trace monosynaptic input networks at cell resolution.
• To create a scalable, accessible, and low-cost spatial assay, regions-of-interest network sequencing (ROInet-seq), for brain-wide single-neuron network mapping.

Main Methods:

• Implementation of a barcoded ΔG-RV for quantitative RNA-sequencing to distinguish individual input networks.
• Development of ROInet-seq, combining fluorescent imaging of tissue sections with targeted barcode sequencing.
• Integration with spatial transcriptomics assays to enhance resolution.

Main Results:

• Optimized barcode detection reliably distinguished monosynaptic input networks from multiple infected neurons in parallel.
• ROInet-seq enabled brain-wide mapping of single-neuron networks in fixed tissue sections.
• Analysis in the somatosensory cortex revealed dominant regional inputs and convergent cortical connections.

Conclusions:

• Barcoded ΔG-RV and ROInet-seq provide a scalable framework for resolving single-cell network architectures in mammalian brains.
• This approach facilitates detailed connectome mapping, advancing our understanding of brain circuitry.
• The developed assay is accessible and cost-effective for broad application in neuroscience research.