# Bridging the gap: joint modeling of single-cell 1D and 3D genomics

> **NIH NIH R00** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2024 · $248,999

## Abstract

Advances in single-cell technologies have enabled three-dimensional (3D) genome structure profiling and 
simultaneous capture of the transcriptome and epigenome within a cell. Quantitative tools are, however, 
still unable to fully leverage the unprecedented resolution of single-cell high-throughput chromatin 
conformation (scHi-C) data and integrate it with other single-cell modalities. To address this challenge, I 
propose to (1) Develop a single-cell gene-body associating domain (scGAD) scoring system to explore 
single-cell 3D genomics data in units of genes. (2) Construct machine learning-based models to impute 
histone modification and 3D chromatin interaction for simultaneously profiling of each cell's epigenomic 
features and 3D chromatin architectures. Subsequently, I will develop an epigenomic regulatory score 
(ERS) model to infer the cell-type-specific promoter-enhancer regulation programs at the highest singlecell and single-gene resolution. (3) Validate and extend scGAD and ERS pipeline to CAR-T 
immunotherapy study to gain insights into the impact of distal gene regulation variations on patient 
responses. In Aim 1, preliminary analysis on human and mouse brain tissues demonstrated that scGAD 
extracts gene features agreeing well with the scRNA-seq data from the same system. As a result, scGAD 
facilitates the projection of cells from 3D genomics data onto reference panels constructed by scRNA-seq 
embeddings with known cell-type annotations. Hence, scGAD provides an unprecedentedly accessible 
and accurate cell type annotation method based on 3D chromatin architectures. Furthermore, the 
successful integration of cells from different modalities into the same network facilitates information sharing 
across 3D chromatin structures, the transcriptome, and the epigenome. Aim 2 leverages such multi-modal 
networks to build an ERS model. ERS jointly models the histone profiles at the promoter and distal 
neighborhoods of the target gene and the 3D spatial proximity between them. Therefore, the ERS scores 
quantify the regulatory effects of distal elements on a per gene and cell basis. Aim 3 will extend the 
integration framework in Aim 1 and 2 using scRNA-seq as a multi-modality bridge to CITE-seq data for a 
deeper annotation, especially for the Peripheral Blood Mononuclear Cells. This enables the in-depth 
investigation of the apheresis samples from the Acute Lymphoma Leukemia patients to gain insight into 
the roles of distal regulatory elements on gene expression and their impact on the CAR-T cell response.

## Key facts

- **NIH application ID:** 11141974
- **Project number:** 4R00HG012797-03
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** YE ZHENG
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $248,999
- **Award type:** 4N
- **Project period:** 2024-09-02 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11141974

## Citation

> US National Institutes of Health, RePORTER application 11141974, Bridging the gap: joint modeling of single-cell 1D and 3D genomics (4R00HG012797-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/11141974. Licensed CC0.

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