Characterization of network hierarchy reflects cell state specificity in genome organization

Sep 24, 2026

Dynamic chromatin structure governs transcription programs during critical processes such as cancer progression and cell development, yet a unified way to characterize chromatin structural evolution is lacking. This study applies graph inference to Hi-C datasets to derive chromatin contact networks and quantifies information transmission changes. Results show reduced network efficiency in colorectal cancer and T-ALL versus matched controls, shallower hierarchy depths in patient chromatin, early-embryo reversals, and tissue-specific conservation of hierarchy order, with cancer showing attenuated top-down chromatin organization.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Introduction

Dynamic chromatin structure and transcription regulation

Hi-C and cancer-associated chromatin disruptions

Limitations of nested hierarchy methods

Results

Graph statistics reveal altered contact networks in cancer and differentiation

Characterization of network hierarchy reflects cell state specificity in genome organization Jingyao Wang, 1,4 Yue Xue, 1,4 Yueying He, 1 Hui Quan, 1 Jun Zhang, 3 and Yi Qin Gao 1,2,3 1Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China; 2Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China; 3 Changping Laboratory, Beijing, 102206, China Dynamic chromatin structure acts as the regulator of transcription program in crucial processes including cancer and cell development, but a unified framework for characterizing chromatin structural evolution remains to be established. Here, we performed graph inferences on Hi-C data sets and derived the chromatin contact networks. We discovered significant decreases in information transmission efficiencies in chromatin of colorectal cancer (CRC) and T-cell acute lymphoblastic leukemia (T-ALL) compared to corresponding normal controls through graph statistics. Using network embedding in the Poincar disk, the hierarchy depths of chromatin from CRC and T-ALL patients were found to be significantly shallower compared to their normal controls. A reverse trend of change in chromatin structure was observed during early embryo development. We found tissue-specific conservation of hierarchy order in chromatin contact networks. Our findings reveal the top-down hierarchy of chromatin organization, which is significantly attenuated in cancer. [Supplemental material is available for this article.] Genome architecture plays an important role in transcription regulation (Liu et al. 2018; Deng et al. 2022; He et al. 2022) . Instead of maintaining a static configuration, chromatin structure is dynamic (Barth et al. 2020) . A large and diverse set of gene regulatory elements in chromatin are found to regulate transcription through long-range interactions. For example, promoter–enhancer interactions regulate the dynamic activation of genes (Cloney 2016), whereas insulators and repressors play the opposite roles (Yang and Corces 2012) . Graph theory has been widely used in deciphering biological networks including protein interaction and gene expression networks (Koutrouli et al. 2020) . Dynamic information transmission in networks is vital for maintaining functionalities (Eisenberg et al. 2000; Brazhnik et al. 2002) . Chromatin structure evolves during crucial life processes including cancer and cell development. Although extensive studies have attributed oncogenesis to gene mutations (Fujimoto et al. 1992; Brekelmans et al. 2001; Davies et al. 2002; Sprucket al. 2002), targeting chromatin structure for diagnosis and therapy has increasingly gained attention (Kaur et al. 2019) . Conventional microscopic observation of aberrant chromatin was used for cancer diagnosis (Zink et al. 2004). The recently developed Hi-C technology allows detailed inspection of aberrant chromatin structure in cancer. Pathological cancer tissues were observed to be accompanied by disturbances in compartments and TAD structures in Hi-C (Johnstone et al. 2020; Iyyanki et al. 2021; Yang et al. 2021) . On the other side, the similarity between embryonic stem cells and cancer cells has also attracted attention (Kim and Orkin 2011; Malta et al. 2018; Feng et al. 2021). The characteristics shared by embryonic stem cells and cancer cells include unlimited proliferation and high cellular plasticity (Seftor et al. 2002; Hendrix et al. 2007) . However, the similarity in chromatin structure between embryo tissues and pathological cancer tissues has not been extensively studied. Although a number of methods have been reported to delineate the hierarchy of Hi-C data, they are confined to the notion of nested hierarchy, which describes a containment relationship of units. For example, Soler-Vila et al. introduced TADpole to identify the hierarchical subdivisions of TADs in intrachromosomal Hi-C (Soler-Vila et a

FAQs

How does the study characterize chromatin structural evolution?

It performs graph inferences on Hi-C datasets to derive chromatin contact networks and applies graph statistics and network embedding to quantify hierarchy properties and information transmission.

What network-level changes are observed in colorectal cancer and T-ALL?

Both show significant decreases in information transmission efficiencies compared with corresponding normal controls, and their chromatin hierarchy depths are significantly shallower.

Are chromatin hierarchy patterns consistent across tissues or developmental stages?

The study finds tissue-specific conservation of hierarchy order in chromatin contact networks and observes a reverse trend during early embryo development, indicating stage-dependent structural changes.

Sep 24, 2026

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