Evidence map›Paper›PMID 42619843›Full record

ArticlebioRxiv : the preprint server for biology2026

Integrative spatial profiling of 3D genome organization and gene expression in tissue.

Pengfei Guo, Yan Cui, Jincan He, Abraham J Waldman, Jiaxin Zhu, Yufan Chen, Zhi Huang, Jingtian Zhou, Jennifer E Phillips-Cremins, Yanxiang Deng

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

5 · Who and what money

Authors and funding

10 authors.

Pengfei Guo
Yan Cui
Jincan He
Abraham J Waldman
Jiaxin Zhu
Yufan Chen
Zhi Huang
Jingtian Zhou
Jennifer E Phillips-Cremins
Yanxiang Deng

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interplay between 3D genome architecture and transcriptional activity is fundamental to gene regulation. However, existing methodologies cannot simultaneously measure these modalities within intact tissues, limiting our understanding of how genome organization coordinates transcriptional programs across diverse cell types and spatial microenvironments. Here, we introduce Spatial Hi-C-RNA, a spatial multi-omics technology that enables the genome-wide co-mapping of chromatin conformation and transcriptome directly from the same tissue section at near- single-cell resolution. Applied to the mouse embryo and adult brains, Spatial Hi-C-RNA generated high-resolution tissue maps revealing that chromatin organization and gene expression jointly define spatially coherent domains aligned with histological structures. While concordant features were observed across modalities, distinct domain patterns also emerged, indicating that chromatin structure and transcription each contribute complementary layers of spatial regulation. We further demonstrated the robustness and biological insight of Spatial Hi-C-RNA in human melanoma, where both modalities delineated tumor boundaries and microenvironmental niches. Notably, chromatin maps revealed fine-scale tumor subdomains undetectable by transcriptomic profiling alone, highlighting the added resolution provided by spatial chromatin architecture. Integrated analysis revealed that multiscale 3D genome features, from A/B compartments and topologically associating domains to chromatin loops, are closely coupled with domain- and cell-type-specific transcriptional programs. In addition, Spatial Hi-C-RNA resolves spatiotemporal dynamics underlying embryonic lineage specification and tumor progression. Together, these capabilities extend the spatial omics landscape beyond transcriptome and epigenome profiling to the level of chromatin organization, establishing an integrative framework for understanding tissue biology across development and disease.

Identifiers

PMID42619843
PMCPMC13484291

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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.