# Developing next-generation high-content image-based genetic screens for multi-omic spatial phenotypes

> **NIH NIH R01** · YALE UNIVERSITY · 2024 · $653,880

## Abstract

Project Summary/Abstract
Spatial organization of the genome, nucleome and transcriptome is key to their control of many essential
genomic and cellular functions. Yet existing tools limit our ability to identify regulators of these spatial
organizations. We are developing a high-content, image-based CRISPR screen to discover three-dimensional
(3D) genome regulators, a first-in-kind technology to uncover the regulatome of 3D genome architectures
across multiple length scales. Our proof-of-concept screen targeting hundreds of candidate regulators
identified many novel chromatin organization regulators. The goal of this application is to advance our
technology to develop a highly-efficient, large scale, and multi-omic screening platform to discover the
molecular regulators of the spatial genome, nucleome and transcriptome. In Aim 1, we will develop a
generalizable, large scale screening platform compatible with in situ spatial omics techniques. In Aim 2, we will
develop multimodal detection and perturbation methods for comprehensive large scale screens of 3D
nucleome regulators. In Aim 3, we will develop integrative methods for large scale screens of spatial
transcriptome phenotypes to allow efficient discovery of the regulatory mechanisms of subcellular RNA
transport and localization. We expect that these proposed developments will provide the research field with
brand-new, broadly applicable technologies for mechanistic studies of the spatial genome, nucleome and
transcriptome in a wide range of biomedical contexts.

## Key facts

- **NIH application ID:** 10856698
- **Project number:** 1R01HG013503-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Siyuan Wang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $653,880
- **Award type:** 1
- **Project period:** 2024-09-17 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10856698

## Citation

> US National Institutes of Health, RePORTER application 10856698, Developing next-generation high-content image-based genetic screens for multi-omic spatial phenotypes (1R01HG013503-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10856698. Licensed CC0.

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