# Optical Functional Genomics

> **NIH NIH DP2** · BROAD INSTITUTE, INC. · 2024 · $1,008,000

## Abstract

PROJECT ABSTRACT:
Mammalian cell biology happens in 3 dimensions. Advances in high-throughput genomics and cellular profiling
‘omics methods have made massively-parallel cell biology experiments routine for many labs, but the vast
majority of these studies in human cells have been limited to homogeneous 2-dimensional models. This
drastically reduces the range of cell types and interactions that can be studied ex vivo. And, despite advances
in the growth of organoids and microtissues for the study of human biology in 3D, next generation ‘omics
approaches still require the dissociation of these structures and the destruction of their cells to extract
biomolecules for study. Researchers need tools that can interrogate human biology at scale and in situ to
generate rich phenotyping data from single cells while still preserving complex spatial relationships and
interactions between cells in 3D. The lack of such tools is a major limitation in biomedical research. Here I
propose a technology that combines the discovery potential of genome scale screening with the information
content of high-dimensional single-cell profiling, with full integration of 3D spatial information to enable rich in
situ phenotypic readout of complex cellular phenomena at scale.

## Key facts

- **NIH application ID:** 11014640
- **Project number:** 4DP2GM146252-02
- **Recipient organization:** BROAD INSTITUTE, INC.
- **Principal Investigator:** James Thomas Neal
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,008,000
- **Award type:** 4N
- **Project period:** 2021-09-23 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11014640

## Citation

> US National Institutes of Health, RePORTER application 11014640, Optical Functional Genomics (4DP2GM146252-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11014640. Licensed CC0.

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