← BioTransfer GEO Dataset Finder
GEO series

α-Synuclein blocks endoplasmic reticulum protein translocation in Parkinson’s disease [bulk RNA-seq]

GSE276377 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/07/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 12 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)
The primary mechanism and subcellular localisation of α-synuclein toxicity in Parkinson’s disease pathogenesis remain unknown. We spatially and temporally resolved proteomic and transcriptomic changes in human iPSC-derived dopaminergic neurons with increasing burden of pathological α-synuclein. We found that misfolded α-synuclein proteoforms, signified by the formation of nanoscale intraneuronal puncta, are associated with impaired translocon function at the endoplasmic reticulum (ER).
Read the full summary ↓
We show that α-synuclein interacts with Sec61A in iPSC-derived dopaminergic neurons and in post-mortem brain tissue from patients with Parkinson’s disease. This interaction interferes with the co-translational translocation of ER-processed proteins including the vacuolar-type ATPase V0a1 subunit, glucocerebrosidase, and Cathepsin B, causing defective organelle function such as reduced lysosomal acidification, leading to increased extracellular vesicle release of α-synuclein. Defective ER-translocation was associated with increased ribosomal UFMylation and proteasomal recruitment but not activation of the unfolded protein response. Reduction of pathological α-synuclein by either CRISPRi to decrease α-synuclein expression or pharmacological activation of proteasomal degradation with repurposed drugs mitigates the ER defect. Our study offers a unifying mechanistic link between α-synuclein pathology and dysregulation of diverse organelle-associated proteins that are both Sec61A translocon substrates and genetic modifiers of Parkinson’s disease risk. Our data also provide a therapeutic rationale for proteasomal activation in early Parkinson’s disease.
This dataset
Open GSE276377 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 GSE276377_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 PRJNA1156797 and SRA study SRP530773. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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
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.