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Downregulated transcription in chromosomal domains of midbrain dopamine neurons linked to schizophrenia. [RNA-Seq]

GSE311978 Homo sapiens (human) RNA-seq (gene expression) 97 samples Submitted 2026/06/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 97 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
97 samples: 97 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.
Paper
Downregulated transcription in chromosomal domains of midbrain dopamine neurons linked to schizophreniaNature communications · 2026
Summary (written by the submitters)
Ventral midbrain dopaminergic neurons are a key cell type for schizophrenia pathophysiology but information about cell type-specific genomic dysregulation in diseased brains is missing. We generated a unique midbrain functional genomics resource with 98 RNA-seq and 34 Hi-C chromosomal contact libraries for Nurr1+/NeuN+ dopaminergic and their surrounding Nurr1-/NeuN- nuclei, collected from donors diagnosed with schizophrenia (SCZ), bipolar disorder (BD) and compared to neurotypical controls.
Read the full summary ↓
Among the 954 dopamine neuron genes specifically dysregulated in SCZ, 331 were downregulated, with selective enrichment for risk-associated synaptic plasticity and neuronal connectivity pathways and embedded within dopamine neuron-specific topologically associated chromosomal domains (TAD). Transcript-resolved analysis revealed 2,350 transcripts with altered expression in SCZ dopamine neurons, affecting key susceptibility genes such as the FOXP1, MAPK10, PCM1 and NRNX1. Therefore, genomic dysregulation in the ventral midbrain of subjects diagnosed with SCZ selectively affects dopaminergic neurons, and includes a unilateral association of genetic risk with down-, but not upregulated transcription at the sites of highly organized chromosomal domains harboring neuron-specific genes with complex transcriptional architectures.
Published in
Downregulated transcription in chromosomal domains of midbrain dopamine neurons linked to schizophrenia
Singh S, Iskhakova M, Lambert TY et al. · Nature communications 2026 · PMID 41942462 · doi:10.1038/s41467-026-71281-7
This dataset
Open GSE311978 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 GSE311978_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1372006 and SRA study SRP650289. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41942462) ↗
Study design
97 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 97 sample titles: 97 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

+ 57 more — browse all 97 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.