NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction

Chromatin loops play a crucial role in gene regulation and cellular function, providing key insights into understanding the 3D structure of the genome and its impact on cellular homeostasis. Nanopore sequencing technology, with its advantages in simultaneously detecting sequences and methylation patterns, brings new opportunities for studying 3D genome structures. We introduce NanoLoop, the first algorithmic framework attempting to predict genome-wide chromatin interactions using Nanopore data. In experiments across four human lymphoblastoid cell lines, NanoLoop demonstrated excellent predictive performance and cross-cell line generalization capabilities. We also discovered four distinct methylation patterns at loop anchors that influence histone modification levels and determine various loop types. NanoLoop further predicted previously uncharacterized long-range chromatin loops, highlighting the potential link between DNA methylation and 3D genome organization and providing new insights into the complex regulatory relationships between epigenetic modifications and 3D genome organization.

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Publication Details

Journal
Advanced Science
Published
2026-02-13
DOI
https://doi.org/10.1002/advs.202517692
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction

Matthew C. Hill, Yonghao Zhang, Li Tang, Min Li et al.
Advanced Science
Genomics and Chromatin Dynamics
article

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction

Matthew C. Hill, Yonghao Zhang, Li Tang, Min Li, Jun Xie
article en

Abstract

Chromatin loops play a crucial role in gene regulation and cellular function, providing key insights into understanding the 3D structure of the genome and its impact on cellular homeostasis. Nanopore sequencing technology, with its advantages in simultaneously detecting sequences and methylation patterns, brings new opportunities for studying 3D genome structures. We introduce NanoLoop, the first algorithmic framework attempting to predict genome-wide chromatin interactions using Nanopore data. In experiments across four human lymphoblastoid cell lines, NanoLoop demonstrated excellent predictive performance and cross-cell line generalization capabilities. We also discovered four distinct methylation patterns at loop anchors that influence histone modification levels and determine various loop types. NanoLoop further predicted previously uncharacterized long-range chromatin loops, highlighting the potential link between DNA methylation and 3D genome organization and providing new insights into the complex regulatory relationships between epigenetic modifications and 3D genome organization.

Advanced Science
Broad Institute (US), Central South University (CN), Massachusetts General Hospital (US)
National Natural Science Foundation of China, Central South University
Openalex Percentile: Top 56%
Genomics and Chromatin Dynamics
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NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction — Matthew C. Hill, Yonghao Zhang, et al. · Advanced Science (2026) | TGRS Research Map | TGRS