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Patient Derived Neomorphic SEPTIN6 Mutations Induce Hematopoietic Stem Cell Senescence Underlying Congenital Neutropenia and Myelodysplasia

GSE338788 Homo sapiens (human) RNA-seq (gene expression) 8 samples Submitted 2026/07/18 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 8 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)
Topic
Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples
8 samples: 2 × EV Control vs 2 × SEPT6 shmiR+GM1+SMGroups 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)
Septins are RAS-like GTP-binding proteins involved in cytoskeletal organization and cellular division. We previously described two pediatric patients harboring SEPT6 germline mutations (GM1:SEPT6 c.1282T>C and GM2:SEPT6 c.1282T>A) presenting with congenital neutropenia associated with the development of myelodysplastic syndrome. In one patient, an additional somatic mutation (SM:SEPT6 c.43C>T) was detected at a low allelic fraction in the BM.
Read the full summary ↓
Here, we describe the consequences of these mutations on hematopoiesis. Transgenic expression or gene editing of GM1 or GM2 in human CD34+ cells led to enlarged, multinucleated cells associated with accelerated exhaustion and premature senescence of hematopoietic stem and progenitor cells (HSPCs). Senescence defects were associated with the upregulation of mTOR phosphorylation; and pharmacologic inhibition of the mTOR pathway resulted in rescue of senescence. In parallel, HSPCs exhibited marked mitochondrial abnormalities, including increased expression of OPA1, a key regulator of mitochondrial fusion, and enhanced oxygen consumption during mitochondrial respiration. Introduction of SM in cis with GM1 mitigated all observed defects. Collectively, our findings demonstrate a gain-of-function mechanism underlying marrow failure in patients carrying germline SEPT6 mutations and suggest that acquisition of a secondary somatic SEPT6 variant may confer a compensatory effect within hematopoietic cells.
This dataset
Open GSE338788 in finder → Find more human RNA-seq datasets → Myelodysplastic syndromes landscape →
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 GSE338788_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 PRJNA1495887 and SRA study SRP718350. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
2 × EV Control vs 2 × SEPT6 shmiR+GM1+SM

Supports a between-group comparison across 4 samples.

How we read this: 2 replicated groups read from 8 sample titles; they account for 4 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
More Myelodysplastic syndromes datasets

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.