GEO series

Multimodal Single-Cell Transcriptomic and Chromatin Accessibility Profiling Reveals Monocyte-Derived Macrophage Dynamics Following Ischemic Stroke [scATAC-seq]

GSE326118 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2026/05/15 Platform GPL34475

At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 2 samples
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: Multimodal Single-Cell Transcriptomic and Chromatin Accessibility Profiling Reveals Monocyte-Derived Macrophage Dynamics Following Ischemic StrokeInternational journal of molecular sciences · 2026

Summary (written by the submitters)

Ischemic stroke promotes monocyte recruitment to the injured brain and their differentiation into monocyte-derived macrophages (MDMs). These cells contribute to debris clearance but may also exacerbate neuroinflammation. However, the heterogeneity of macrophage subsets and the phenotypic transitions that shape MDM functional states during the subacute phase of stroke remain incompletely characterized.

Read the full summary ↓

To address this, we first performed single-cell RNA sequencing (scRNA-seq) to define the transcriptional landscape of the mouse brain 48 hours after transient middle cerebral artery occlusion/reperfusion compared with sham controls. Reclustering of macrophage-lineage cells identified multiple monocyte-derived subsets, including a distinct Cd68hi/Ctsdhi MDM subset enriched for lysosomal and lipid-processing gene expression programs. Cell trajectory inference supported a transition from inflammatory infiltrates toward the Cd68hi/Ctsdhi state, accompanied by induction of transcriptomic networks that drive macrophage function to favor a clearance-competent phenotype in response to ischemic stroke. Complementary single-cell ATAC sequencing (scATAC-seq) demonstrated cell type-specific chromatin remodeling after stroke and revealed MDM subclusters with accessibility at key loci regulating lysosomal function and lipid metabolism. Together, our findings define a cellular and regulatory framework of the subacute post-stroke brain and identify a lysosome-enriched Cd68hi/Ctsdhi MDM trajectory, highlighting endolysosomal and lipid-processing programs during early stroke recovery.

Published in

Multimodal Single-Cell Transcriptomic and Chromatin Accessibility Profiling Reveals Monocyte-Derived Macrophage Dynamics Following Ischemic Stroke

Hamblin MH, Murad R, Boese AC et al. · International journal of molecular sciences 2026 · PMID 42074294 · doi:10.3390/ijms27083657

This dataset

Open GSE326118 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE326118_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 PRJNA1443547 and SRA study SRP687027. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42074294) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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