# Developing a one-tube circularized ligation product sequencing (CLP-seq) method for the mapping of 3D genome architecture in small cell populations or single cells.

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $464,113

## Abstract

The 3D architecture of mammalian genome plays a key role in transcription regulation. Through DNA
looping, non-coding cis-regulatory elements may regulate target genes from hundreds of kilobases away.
Because of this complexity, generating a comprehensive map of long-range DNA looping interactions will
greatly facilitate our understanding of genome functions. Our previous work for the first time
demonstrated that it is feasible to map the 3D genome in mammalian cells with 3~5 billion Hi-C reads, at
a resolution of 5-10kb. At this resolution, interactions between individual cis-regulatory elements can be
revealed. Recently, single cell Hi-C approach has also been tested to reveal cell-to-cell variability of
chromosome structures. The fast growing field of 3D genome research calls for 3D genome maps in a
variety of cell or tissue types under different physiological or pathogenic perturbations. In order to achieve
broad applicability, 3D genome mapping technology must address the following challenges: (i) Ability to
assay rare bio-samples; (ii) Generating high-quality library for deep sequencing at a level of several billion
reads; (iii) The ability to analyze a large number of single cells for the analyses of complex tissue or
cellular heterogeneity. However, the library quality from Hi-C and its derivatives is usually poor when the
amount of starting material is small. The overall goal of this proposal is to develop a simple and efficient
3C-seq method (Circularized Ligation Products sequencing, or CLP-seq) to generate high-quality
libraries suitable for ultra-deep sequencing from a small number of cells. In contrast to Hi-C and its
derivatives, CLP-seq is unique because it enriches ligation junction products through a series of
enzymatic reactions without the need for biotin labeling and pull-down. From a pilot experiment, we
estimate that this new method requires less than 1% of cells as starting material to reach sequencing
depth at that level of a billion reads (over 100-fold improvement over Hi-C). Furthermore, because CLP-
seq avoids biotin labeling and pull-down, it is amenable to the development of a one-tube single cell CLP-
seq protocol (scCLP-seq) for massive scalable single cell analysis. In this project, we will establish and
optimize these new technologies, and as proof-of-principle, also produce a significant amount of valuable
data resources with these methods in the following three aims. In aim 1, we will optimize CLP-seq
protocol to generate high-complexity libraries for ultra-deep sequencing from small cell populations or
rare human tissues. In aim 2, we will develop a full-package CLP-seq data analysis pipeline to detect
and visualize DNA looping interactions at kilobase resolution. We will generate kilobase-resolution 3D
genome maps in a few difficult human tissues and perform preliminary functional annotation of non-
coding GWAS SNPs in relevant human diseases. In aim 3, we will further develop a one-tube scCLP-
seq protocol ...

## Key facts

- **NIH application ID:** 9968311
- **Project number:** 5R01HG009658-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Fulai Jin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $464,113
- **Award type:** 5
- **Project period:** 2017-08-09 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9968311

## Citation

> US National Institutes of Health, RePORTER application 9968311, Developing a one-tube circularized ligation product sequencing (CLP-seq) method for the mapping of 3D genome architecture in small cell populations or single cells. (5R01HG009658-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9968311. Licensed CC0.

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