# BRAIN CONNECTS: Scalable Approaches for Bidirectional Brain-wide Trans-Neuronal Connectivity Mapping of Defined Cell Types

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $2,347,750

## Abstract

PROJECT SUMMARY
A major goal in modern neuroscience is to comprehensively map circuits of synaptically connected cell types
throughout the mammalian brain. The key technological gap this proposal will address is the need for
systematic, high-throughput methods to define neuronal wiring diagrams at the level of defined cell types. The
overall objectives of this application are to establish a suite of tools that combine spatial transcriptomics and
connectomics into scalable, high-throughput methods and analytical tools for linking the molecular identities of
neural cell types to their synaptic connectivity. The rationale for the proposed work is that scalable, rapid means
of unraveling circuit connectivity with cell type-specificity will accelerate efforts to unravel circuit structure and
function throughout the brain. These goals will be pursued in three specific aims: 1) Establish and validate a
spatial transcriptomic approach, TransA-MERFISH, for multiplexed, brain-wide mapping of the postsynaptic
neurons of genetically defined starter cells; 2) Establish and validate a spatial transcriptomic approach, TransR-
MERFISH, for multiplexed, brain-wide mapping of the presynaptic neurons of genetically defined starter cells;
and 3) Establish computational platforms to decode the information gathered from TransA- and TransR-
MERFISH. These collaborative experiments will draw on diverse expertise to merge connectomic methods
developed by the applicants with spatial transcriptomic methods and analytical tools. These methods will be
validated in the mouse brain, including multiple cortical and midbrain areas. The research proposed in this
application is innovative because it establishes new tools to comprehensively map in situ synaptic inputs and
outputs at the level of molecularly defined cell types. The proposed research will use commercial equipment to
facilitate the easy adoption of these techniques by other labs. However, the approaches are also easily extensible
to other spatial transcriptomics methods. The proposed research is significant because it is expected to yield a
scalable, user-friendly, rapid means of unraveling circuit connectivity with cell type-specificity and defining circuit
connectivity. Ultimately, the scalable tools developed here have the potential to accelerate investigations of
neural circuit assembly and function in a variety of model organisms.

## Key facts

- **NIH application ID:** 10867185
- **Project number:** 1U01NS136405-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Xin Duan
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,347,750
- **Award type:** 1
- **Project period:** 2024-08-15 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10867185

## Citation

> US National Institutes of Health, RePORTER application 10867185, BRAIN CONNECTS: Scalable Approaches for Bidirectional Brain-wide Trans-Neuronal Connectivity Mapping of Defined Cell Types (1U01NS136405-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10867185. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*