GEO series

SLF2 and SMC5 dysfunction drives HSC aging and predisposes to MDS, defining a new inherited bone marrow failure syndrome [ATAC-seq]

GSE316079 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 6 samples Submitted 2026/08/06 Platform GPL30173

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 6 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Topic: Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples: 6 samples: 2 × mutant #1 vs 2 × corrected #1 vs 2 × corrected #2Groups 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)

Pathogenic variants in SLF2 and SMC5 cause a developmental disorder known as Atelis Syndrome, characterized by microcephaly, short stature, and hematological abnormalities, most notably anemia and lymphopenia. However, its clinical relevance to hematology has not yet been established, and the underlying pathogenic mechanisms remain largely unknown.

Read the full summary ↓

Prompted by our longitudinal follow-up and re-evaluation revealing that some patients with Atelis Syndrome developed myelodysplastic syndromes (MDS) or MDS-like features, we elucidated the hematopoietic defects using hematopoietic stem and progenitor cells (HSPCs) derived from patient-specific induced pluripotent stem cells carrying compound heterozygous SLF2 mutations (mutant HSPCs) and gene-corrected isogenic controls. Mutant HSPCs exhibited impaired colony-forming capacity and defective erythroid differentiation with a myeloid bias. Crucially, in vivo xenotransplantation revealed that mutant HSPCs had significantly reduced long-term engraftment capacity. Knockdown of SMC5 in human cord blood CD34+ cells similarly impaired colony formation. Mechanistically, disruption of the SLF2–SMC5 axis induces increased genomic instability, p53/p21 activation, and transcriptional signatures of senescence. Furthermore, ATAC sequencing uncovered epigenetic features of hematopoietic stem cell (HSC) aging, including increased accessibility at PU.1 motifs, driving myeloid bias. In conclusion, we establish that SLF2 and SMC5 dysfunction drives premature HSC aging and predisposes to MDS, defining Atelis Syndrome as a distinct entity within the inherited bone marrow failure syndromes (IBMFS). These findings highlight the need to incorporate Atelis Syndrome into the diagnostic framework of IBMFS, improving genetic diagnosis and guiding clinical management of hematological abnormalities.

This dataset

Open GSE316079 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE316079_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1400558 and SRA study SRP661051. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

2 × mutant #1 vs 2 × corrected #1 vs 2 × corrected #2

Supports a between-group comparison across 6 samples.

How we read this: 3 replicated groups read from 6 sample titles; they account for 6 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

GSM9444260 mutant #1-1 mutant #1
GSM9444261 corrected #1-1 corrected #1
GSM9444262 corrected #2-1 corrected #2
GSM9444263 mutant #1-2 mutant #1
GSM9444264 corrected #1-2 corrected #1
GSM9444265 corrected #2-2 corrected #2

More Myelodysplastic syndromes datasets

GSE316081 SLF2 and SMC5 dysfunction drives HSC aging and predisposes to MDS, defining a new inherited bone marrow failure syndrome [RNA-seq] 6 samples same disease briefing · shares slf2, smc5, hsc, mds, dysfunction, predisposes, inherited, defining
GSE270760 PRC2-mediated apoptosis evasion is a therapeutic target of MDS/AML harboring inv(3)/t(3;3) and monosomy 7 (CUT&Tag) 24 samples same disease briefing · shares mds
GSE298729 Chromatin accessibility of hematopoietic stem/progenitor cells (HSPCs) derived from MDS patients before and after disease progression 2 samples same disease briefing · shares mds
GSE264117 Investigating microenvironment in MDS II 503 samples same disease briefing · shares mds
GSE298020 PU.1-Activated Genomic Regions Define Low-risk MDS Subsets Characterized by Immune Dysregulation and Disease Progression. 493 samples same disease briefing · shares mds
GSE275000 Clinical response to azacitidine in MDS is associated with distinct DNA methylation changes in HSPCs 104 samples same disease briefing · shares mds
GSE281562 Unique epigenomic signatures identify biologically significant subtypes of MDS and predict response to azacytidine [RNA-Seq] 83 samples same disease briefing · shares mds
GSE31174 Affymetrix SNP array data for myelodysplastic syndromes (MDS) and related neoplasms 58 samples same disease briefing · shares mds

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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.