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Single-Cell Multimodal Atlas Reveals Regulatory Programs in the Human Brain

GSE327101 Homo sapiens (human) Single-cell RNA-seq 220 samples Submitted 2026/06/26 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 220 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
220 samples: 67 conditions, mostly in duplicateGroups 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.
Paper
Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human BrainbioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Directly measuring chromatin states alongside transcription is essential for understanding how cell-type-specific regulatory programs are established and maintained in the adult human brain. We present a large-scale single-cell multimodal atlas generated by jointly profiling transcriptome with active (H3K27ac) and repressive (H3K27me3) histone modifications across 18 brain regions.
Read the full summary ↓
We profile >750,000 nuclei spanning 160 cell types and integrate these data with chromatin accessibility, DNA methylation, 3D genome architecture, and spatial transcriptome. This framework annotates >500,000 regulatory elements and resolves cell-type-specific chromatin states. We link enhancers to target genes, infer gene regulatory networks, and classify chromatin interactions, revealing neuron-enriched long-range Polycomb repression of developmental genes. Integrating these maps with GWAS data and sequence-based model prioritizes noncoding variants, effector genes, and vulnerable cell types for neuropsychiatric disorders. Finally, cross-species comparisons show conserved activation but more divergent repression. Together, this study provides a functional reference for interpreting noncoding variants, epigenetic memory, and brain organization.
Published in
Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain
Xie Y, Chang L, Zhong G et al. · bioRxiv : the preprint server for biology 2026 · PMID 41676679 · doi:10.64898/2026.02.02.703166
This dataset
Open GSE327101 in finder → Find more human 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 GSE327101_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1449449 and SRA study SRP689626. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41676679) ↗
Study design
67 conditions, mostly in duplicate
RNA, Donor2, CBL (Cerebellum) ×6 RNA, Donor4, CBV (Cerebellum) ×6 H3K27me3, Donor2, CBL (Cerebellum) ×4 RNA, Donor4, CBL (Cerebellum) ×4 H3K27me3, Donor4, CBV (Cerebellum) ×4 RNA, Donor4, V1C (Cortex) ×4 RNA, Donor2, ITG (Cortex) ×3 RNA, Donor4, Idg (Cortex) ×3 +113 more

Supports a between-group comparison across 166 samples.

How we read this: 67 replicated groups read from 220 sample titles; they account for 166 of them. 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

+ 180 more — browse all 220 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.