Evidence map›Paper›PMID 42144428›Full record

ArticleScientific reports2026

Persistent homology-based multiscale Hi-C analysis uncovers TADs-mediated gene regulation.

Zhen Chiang, Yue Wu

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Zhen ChiangDepartment of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, No. 800 Dongchun Road, Minhang District, Shanghai, 200241, China.
Yue WuDepartment of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, No. 800 Dongchun Road, Minhang District, Shanghai, 200241, China. yuewujess@sjtu.edu.cn.

Funding

Fundamental Research Funds for the Central Universities YG2022QN001Science and Technology Commission of Shanghai Municipality BI0800044
6 · The paper itself

Abstract

Topologically associating domains (TADs), computationally defined 3D chromatin structures, play pivotal roles in gene expression regulation and genome organization. However, their structural basis and functional implications remain contentious. The interplay between TADs and other multiscale 3D chromatin structures has not been comprehensively computationally characterized. The extent and regulatory scope of TAD-mediated gene expression continue to be debated. Multiscale analyses spanning hierarchical 3D chromatin structures hold promise for establishing unified structural-functional frameworks for TADs. Here, we developed topoHiC-a computational framework enabling simultaneous identification of TADs and chromatin loops from Hi-C contact matrices via persistent homology. Benchmarking analyses demonstrated improved performance of topoHiC compared to four previously published loop callers and six TAD callers. We applied topoHiC to explore multiscale 3D chromatin remodeling and showed that spatial proximity relative to TAD boundaries could modulate differential gene expression probability. We proved the potential capacity of multiscale 3D structures to predict differential gene expression through a generalized regression model. Our findings demonstrated the functional roles of TADs as architectural compartmentalization through establishing structural relationships between TADs and chromatin loops and exploring inside genes and truncated genes respectively.

Indexed as

ChromatinChromatin Assembly and DisassemblyComputational BiologyGene Expression RegulationHumansChromatin3D genomeMultiscale analysisPersistent homologyTopologically associating domains

Identifiers

PMID42144428
PMCPMC13376733

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.