GEO series

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

GSE311199 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2026/07/24 Platform GPL34284Platform GPL34290

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Mus musculus (mouse)
Samples: 15 samples: 15 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Three-dimensional genome organization shapes transcriptional regulation, yet measuring its spatial coordination in situ within intact tissues remains challenging. We present Spatial Hi-C-RNA, a multimodal platform that simultaneously maps genome-wide chromatin contacts and transcriptomes from the same tissue section at near single-cell resolution.

Read the full summary ↓

Across mouse brain, developing embryos, and human melanoma, Spatial Hi-C-RNA generated multimodal maps that aligned with tissue anatomy while revealing complementary chromatin- and RNA-defined spatial patterns. Multiscale features, including A/B compartments, topologically associating domains, and chromatin loops, were associated with region- and cell-type-specific transcriptional programs. In mouse embryos, Spatial Hi-C-RNA resolved coordinated chromatin and transcriptional remodeling during neuronal maturation across developmental stages. In human melanoma, chromatin architecture delineated intratumoral subregions not detected by RNA alone and linked tumor-state transitions to changes in compartments, domain boundaries, and regulatory programs. Spatial Hi-C-RNA thus provides a broadly applicable framework for investigating genome structure–function relationships in development and disease within native tissue environments.

This dataset

Open GSE311199 in finder → Find more RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE311199_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1368795 and SRA study SRP648718. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM9320916 Spatial co-profiling,mouse brain_r1, Hi-C
GSM9320917 Spatial co-profiling,mouse brain_r1, RNA
GSM9320918 Spatial co-profiling,mouse brain_r2, Hi-C
GSM9320919 Spatial co-profiling,mouse brain_r2, RNA
GSM9320920 Spatial co-profiling,mouse embryo E11.5, Hi-C
GSM9320921 Spatial co-profiling,mouse embryo E11.5, RNA
GSM9320922 Spatial co-profiling,human melanoma, Hi-C
GSM9320923 Spatial co-profiling,human melanoma, RNA
GSM9320924 Spatial profiling, human melanoma, ATAC
GSM9738329 Spatial co-profiling,human melanoma_r2, Hi-C
GSM9738330 Spatial co-profiling,human melanoma_r2, RNA
GSM9738331 Spatial co-profiling,mouse embryo E13.5_r1, Hi-C
GSM9738332 Spatial co-profiling,mouse embryo E13.5_r1, RNA
GSM9738333 Spatial co-profiling,mouse embryo E13.5_r2, Hi-C
GSM9738334 Spatial co-profiling,mouse embryo E13.5_r2, RNA

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.