# BRAIN CONNECTS: Synaptic resolution whole-brain circuit mapping of molecularly defined cell types using a barcoded rabies virus

> **NIH NIH U01** · STANFORD UNIVERSITY · 2024 · $1,970,302

## Abstract

ABSTRACT
Single-cell transcriptomics has revolutionized our understanding of neuronal diversity and enabled high-throughput
characterization of molecular cell types across brain areas and species. We and others have pioneered multi-
modal technologies such as Patch-seq and spatial transcriptomics to link molecularly-defined cell types with their
physiology, cytomorphology, and anatomical features, but we still lack high-throughput, cost-effective methods
that can provide comprehensive synaptic resolution wiring diagrams of entire mammalian brains and integrate
these connectomes with molecularly defined cell types.
 We propose to further develop and validate Rabies Barcode Interaction Detection followed by sequencing
(RaBID-seq) to enable high-throughput, scalable, and cost-effective mapping of brain-wide synaptic-level con-
nectivity and transcriptomic profiling of the mapped neurons. We have optimized rabies virus production and
packaging to achieve barcoded libraries containing more than 1.7 million unique barcodes, two orders of mag-
nitude higher compared to prior studies, enough to map the inputs to thousands of post-synaptic neurons in a
single animal. However, this technology still faces several experimental and computational challenges to realize
its full potential. In Aim 1, we will address three potential challenges that may arise when scaling RaBID-seq to
study brain-wide, densely labeled circuits: stochasticity of initial infection and spread, toxicity, and the potential
for polysynaptic events when many founder cells are labeled. In addition, we will develop a new variant of Ra-
bies featuring an evolvable barcode that can disambiguate monosynaptic vs polysynaptic spread in the setting of
dense labeling. In Aim 2, we will benchmark RaBID-seq connectomes against other gold standard techniques
measuring connectivity using multipatch-seq and spatial transcriptomics. In Aim 3, we will develop new algorithms
using graph neural networks to reconstruct monosynaptic connectomes from barcoded viral datasets, assess the
robustness of these algorithms under different experimental parameters in silico, and test whether an evolvable
barcode can improve monosynaptic circuit reconstruction. If successful, these studies will establish RaBID-seq
as a scalable, cost-effective tool for brain-wide connectivity mapping that can integrate transcriptomic cell types
with their synaptic-level wiring diagram at single-cell resolution.
 By reducing the problem of synaptic connectivity into a problem of barcode sequencing, our approach has
the potential to dramatically increase throughput, decrease costs and provide a direct link to the transcriptome
of each mapped cell. RaBID-seq will transform brain-wide circuit mapping into a routine experiment that can be
performed in any lab with modest resources, making it possible to explore how circuits differ between treatment
conditions, in disease states, between the sexes, and across the lifespan. We will also generate...

## Key facts

- **NIH application ID:** 11159346
- **Project number:** 7U01NS132353-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Andreas Tolias
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,970,302
- **Award type:** 7
- **Project period:** 2024-08-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11159346

## Citation

> US National Institutes of Health, RePORTER application 11159346, BRAIN CONNECTS: Synaptic resolution whole-brain circuit mapping of molecularly defined cell types using a barcoded rabies virus (7U01NS132353-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11159346. Licensed CC0.

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