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Friedreich’s ataxia transcriptomic dysregulation and identification of cell type-specific biomarkers: A systematic review and meta-analysis

GSE319887 Homo sapiens (human) RNA-seq (gene expression) 43 samples Submitted 2026/03/18 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 43 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
43 samples: 10 conditions, mostly with about 4 replicates eachGroups 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)
Friedreich’s ataxia (FRDA) is a progressive neurodegenerative disease caused by a guanine-adenine-adenine (GAA) trinucleotide repeat expansion within the first intron of the FXN gene. The GAA expansion in FRDA induces a transcriptionally repressive state that reduces expression of the protein product Frataxin. Despite Frataxin's ubiquitous expression, the dorsal root ganglia sensory neurons (SNs) are particularly affected, causing sensory/proprioceptive loss, while lower motor neurons (LMNs) are largely spared in FA.
Read the full summary ↓
The basis for this cell-type specific selective vulnerability remains a central unanswered question in FRDA pathophysiology. Here we generated induced pluripotent stem cell derived sensory neurons, lower motor neurons and neural crest cells from FRDA and isogenic corrected control cell lines. These were profiled using bulk RNA sequencing and used in the systematic review and meta-analysis of all human bulk RNA-seq datasets derived from FRDA and control samples. Our group performed a systematic review and meta-analysis of human bulk RNA-sequencing datasets in FRDA, reprocessing all studies through a unified analysis pipeline to enable direct cross-study comparison. We analysed 23 independent datasets comprising 94 FRDA and 99 control samples across 10 distinct cell types, spanning both disease-relevant (cardiomyocytes, sensory neurons) and unaffected cell types (fibroblasts, lymphocytes) of FRDA. This integrative approach allowed us to identify transcriptional changes that are consistently associated with FRDA across studies, while simultaneously delineating those that are cell-type specific. We have identified a panel of robust biomarkers of FRDA that would be useful readouts in in vitro drug screens, in clinical trials, as well as generating hypothesis as to how these biomarkers relate to the pathophysiological mechanisms of FRDA. All biomarkers, datasets and results can also be explored through the open-access FRDA Transcriptomic Atlas (https://marniemaddock.github.io/FRDATranscriptomicAtlas/).
This dataset
Open GSE319887 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 GSE319887_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 PRJNA1425480 and SRA study SRP678019. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly with about 4 replicates each
FA1, FRDA, iPSC-derived sensory neuron, ×5 FA1ic, isogenic corrected, iPSC-derived senso… ×5 FA1, FRDA, iPSC-derived neural crest cell, ×5 FA2, FRDA, iPSC-derived sensory neuron, ×4 FA2ic, isogenic corrected, iPSC-derived senso… ×4 FA1ic, isogenic corrected, iPSC-derived neura… ×4 FA2, FRDA, iPSC-derived neural crest cell, ×4 FA2ic, isogenic corrected, iPSC-derived neura… ×4 +2 more

Supports a between-group comparison across 43 samples.

How we read this: 10 replicated groups read from 43 sample titles; they account for 43 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

+ 3 more — browse all 43 samples with per-sample file links →

Datasets on a similar topic

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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.