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SETD1A Regulates Psychiatric Gene Networks Involved in Genomic Stability and Synaptic Function in Rare and Sporadic Schizophrenia [bulk RNA-seq]

GSE293155 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/09/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 24 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
SETD1A regulates psychiatric gene networks involved in genomic stability and synaptic function in rare and sporadic schizophreniaNature communications · 2025
Summary (written by the submitters)
Rare loss-of-function (LoF) mutations in SETD1A are associated with schizophrenia (SCZ). However, how SETD1A haploinsufficiency leads to SCZ-associated phenotypes and its relevance to patients without these rare mutations is unknown. Here, we identify SETD1A bound loci and regulated genes in human prenatal cortex and isogenic pluripotent stem cell-derived neuronal models engineered with SETD1A LoF variants, including the most common patient mutation.
Read the full summary ↓
SETD1A preferentially binds the promoters of SCZ and Bipolar risk loci that regulate chromatin remodeling, DNA repair, and synaptic function. Additionally, SETD1A binds to DNA damage prone sites in neural progenitor cells and postmitotic neurons. SETD1A haploinsufficiency causes accelerated neurogenesis, reduced neuronal complexity, and DNA damage accumulation in postmitotic neurons that is rescued by inhibiting the H3K4me2/3 demethylase KDM5. In postmortem SCZ cortical tissue, individuals who lack SETD1A mutations exhibit reduced SETD1A expression, associated with downregulation of SETD1A-regulated genes, implicating SETD1A-H3K4me dysfunction in sporadic SCZ cases. Therefore, restoring the SETD1A-H3K4me epigenetic imbalance may benefit individuals with SETD1A haploinsufficiency as well as a broader psychiatric population without SETD1A mutations.
Published in
SETD1A regulates psychiatric gene networks involved in genomic stability and synaptic function in rare and sporadic schizophrenia
Sawada T, Feltrin AS, Wang Y et al. · Nature communications 2025 · PMID 41422157 · doi:10.1038/s41467-025-67154-0
This dataset
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.

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 GSE293155_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1242963 and SRA study SRP573713. Searching any of these in the dataset finder brings you back here.

Study design
24 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 24 sample titles: 24 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
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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.