← BioTransfer GEO Dataset Finder
GEO series

ATF3-dependent formation of inclusion bodies in polyQ-expressing human iPSC-derived neurons confers cellular protection [RNAseq]

GSE285810 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2026/04/01 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 22 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
22 samples: 8 conditions, mostly in triplicateGroups 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
ATF3-dependent formation of inclusion bodies in polyQ-expressing human iPSC-derived neurons confers cellular protectionCell death and differentiation · 2026
Summary (written by the submitters)
Huntington’s disease (HD) is an incurable, neurodegenerative disorder. While the causative mutation – CAG expansions within the coding region of the Huntingtin (HTT) gene – has been identified over 30 years ago, the pathological mechanisms underlying HD are still not clear. The abnormal CAG track encodes a polyglutamine (polyQ) expanded protein, which leads to HTT protein misfolding.
Read the full summary ↓
These polyQ aggregates can form insoluble inclusion bodies (IBs); however, whether IBs are protective or detrimental remains debatable. To ask whether IBs are protective or harmful in human neuronal cells, and to elucidate the pathological pathways involved in polyQ IB formation, we developed an iPSC-based human neuronal models for polyQ-related disorders. We ectopically expressed the first 21 exons of the HTT gene, containing either 18Q or 105Q fused with GFP in HD patient-derived iPSCs containing 180Q or their isogenic corrected cells, respectively, differentiated them into neuronal progenitor cells (NPCs), and enriched for a pure population of polyQ IBs-containing cells (IB+). Comparing gene expression profiles between IB+ and IB- NPCs, growing side-by-side, in both systems, we identified ATF3 as responsible for inducing neuroinflammatory genes specifically in IB+ cells. ChIP-seq for ATF3 confirmed direct binding at their promoters, exclusively in IB+ NPCs. Remarkably, knocking out (KO) ATF3 completely prevented polyQ-IB formation in NPCs and rendered the cells more vulnerable to induced stress. Finally, using time-lapse imaging comparing cell death in IB+ and IB- NPCs, we demonstrate that polyQ IBs have a significant protective effect. Taken together, our results highlight ATF3’s role in polyQ IB formation in human NPCs, acting as an activator of inflammatory genes, and demonstrate that polyQ IBs protect cells from stress-induced death.
Published in
ATF3-dependent formation of inclusion bodies in polyQ-expressing human iPSC-derived neurons confers cellular protection
Oweis W, Nissim-Rafinia M, Dvir E et al. · Cell death and differentiation 2026 · PMID 41922802 · doi:10.1038/s41418-026-01739-0
This dataset
Open GSE285810 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 GSE285810_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 PRJNA1206130 and SRA study SRP555139. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41922802) ↗
Study design
8 conditions, mostly in triplicate
NPC_105Q(IB-) ×3 NPC_105Q(IB+) ×3 NPC_180Q(IB-) ×3 NPC_180Q(IB+) ×3 NPC_105Q_ATF3KO ×3 NPC_105Q_ATF3WT ×3 HEK_105Q(IB-) ×2 HEK_105Q(IB+) ×2

Supports a between-group comparison across 22 samples.

How we read this: 8 replicated groups read from 22 sample titles; they account for 22 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.