# Image-directed nanoscale photo-crosslinking for the study of sub-nuclear structures

> **NIH NIH R21** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $206,250

## Abstract

Title: Image-directed nanoscale photo-crosslinking for the study of subnuclear structures
Mammalian genomes encode genetic information in linear sequence, yet proper expression of cell-specific
genes depends on higher order nuclear organization, from the folding of chromosomes to the assembly of
chromosomal domains and nuclear compartments. Defining the dynamic assembly, structure and interaction
of these sub-nuclear components is critical to understanding the basic mechanisms of cellular functions and
regulations. Cutting-edge imaging methods are revealing the details of the nucleus at increasingly higher
resolutions; genomic methods such as Hi-C enable genome-wide analysis of chromatin folding and interactions
at the molecular level. However, few technologies are available to integrate the imaging and genomic analyses
together. The proposed studies aim to develop an image-directed nanoscale photo-crosslinking technology
(INPX) to instantly capture genomic DNA in a selected nuclear volume to enable high resolution spatial and
temporal studies of sub-nuclear structures at the single cell level. INPX will greatly facilitate the structure and
function study of nuclear organization and subnuclear compartments.
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## Key facts

- **NIH application ID:** 10011896
- **Project number:** 5R21HG010528-02
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** LIN CHEN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $206,250
- **Award type:** 5
- **Project period:** 2019-09-06 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10011896

## Citation

> US National Institutes of Health, RePORTER application 10011896, Image-directed nanoscale photo-crosslinking for the study of sub-nuclear structures (5R21HG010528-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10011896. Licensed CC0.

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