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Inflammation perturbs hematopoiesis by remodeling specific compartments of the bone marrow niche

GSE276784 Mus musculus (mouse) Single-cell RNA-seq 89 samples Submitted 2025/10/27 Platform GPL24247Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 89 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
89 samples: 16 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.
Paper
Inflammation perturbs hematopoiesis by remodeling specific compartments of the bone marrow nicheBlood · 2026
Summary (written by the submitters)
Hematopoietic stem and progenitor cells (HSPC) are regulated by interactions with stromal cells in the bone marrow (BM) cavity, which can be segregated into two spatially defined central marrow (CM) and endosteal (Endo) compartments. However, the importance of this spatial compartmentalization for BM responses to inflammation and neoplasia remains largely unknown.
Read the full summary ↓
Here, we extensively validate a combination of scRNA-seq profiling and matching flow cytometry isolation that reproducibly identifies 7 key CM and Endo populations across mouse strains and accurately surveys both niche locations. We demonstrate that different perturbations exert specific effects on different compartments, with type I interferon responses causing CM mesenchymal stromal cells to adopt an inflammatory phenotype associated with overproduction of chemokines modulating local monocyte dynamics in the surrounding microenvironment. Our results provide a comprehensive method for molecular and functional stromal characterization and highlight the importance of altered stomal cell activity in regulating hematopoietic responses to inflammatory challenges.
Published in
Inflammation perturbs hematopoiesis by remodeling specific compartments of the bone marrow niche
Swann JW, Zhang R, Verovskaya EV et al. · Blood 2026 · PMID 41060335 · doi:10.1182/blood.2025029513
This dataset
Open GSE276784 in finder → Find more mouse 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 GSE276784_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1158854 and SRA study SRP531691. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41060335) ↗
Study design
16 conditions, mostly with about 4 replicates each
SMARTseq_pIC_iMSCL_A ×7 SMARTseq_pIC_iMSCL_B ×7 SMARTseq_pIC_iMSCL_C ×7 SMARTseq_pIC_iMSCL_F ×6 SMARTseq_Old_iMSCL_D ×5 SMARTseq_pIC_iMSCL_E ×5 SMARTseq_Old_iMSCL_A ×4 SMARTseq_Old_iMSCL_C ×4 +25 more

Supports a between-group comparison across 72 samples.

How we read this: 16 replicated groups read from 89 sample titles; they account for 72 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

+ 49 more — browse all 89 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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