# From synapses to genes through morphology: an integrated characterization of cell types based on connectomics and transcriptomics data

> **NIH NIH RF1** · ALLEN INSTITUTE · 2021 · $1,441,184

## Abstract

Project Summary
The goal of this project is to create a unified framework for understanding the relationship between
neuronal gene expression and connectivity in mouse visual cortex, by using morphology as a key
linking modality. There now exist publicly available large-scale data sets that measure both these
modalities in mouse visual cortex. One dataset is a large set of Patch-seq experiments from single
cells, which provide measurements of gene expression, electrophysiological properties and
morphology for individual cells. A second dataset is from large scale Connectomics using electron
microscopy, which provides neuronal morphology; fine-scale and detailed cellular and ultrastructural
properties; and measurements of the connectivity between individual neurons. Our first aim is to
analyze these two datasets in an explicitly integrative fashion, in order to build better classifiers of
neuronal types, along with tools to translate type predictions between each data modality. Our second
aim builds on the first, by using those tools to characterize cell-type specific connectivity of mouse
visual cortex. This will allow us to describe how that connectivity relates to the likely molecular
composition of individual cells and provide insight into which molecular distinctions drive differences
in cell type specific connectivity patterns. Our third aim is to redistribute the results of our analysis
back into publicly available data repositories and create tools that allow other researchers to query
the gene expression, connectivity, electrophysiological and morphological descriptors of neurons in
the datasets, as well as apply those same tools to their own data. Like a Rosetta stone for cell types,
this will enable researchers using disparate methods to integrate their data with other modalities and
foster a rich environment for understanding the role of cell types in brain function and disease.

## Key facts

- **NIH application ID:** 10360840
- **Project number:** 1RF1MH125932-01A1
- **Recipient organization:** ALLEN INSTITUTE
- **Principal Investigator:** Forrest Christie Collman
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,441,184
- **Award type:** 1
- **Project period:** 2021-09-15 → 2024-09-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10360840

## Citation

> US National Institutes of Health, RePORTER application 10360840, From synapses to genes through morphology: an integrated characterization of cell types based on connectomics and transcriptomics data (1RF1MH125932-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10360840. Licensed CC0.

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