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ACKR2 aids the regulation of bone marrow eosinophils to promote monocyte differentiation and anti-bacterial immunity

GSE334547 Mus musculus (mouse) RNA-seq (gene expression) 26 samples Submitted 2026/06/17 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 26 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
Mus musculus (mouse)
Samples
26 samples: 6 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)
Chemokine receptors control cell migration within the body. Here we reveal interactions between eosinophils and monocytes in the bone marrow, indirectly controlled by the atypical chemokine receptor ACKR2. In the absence of ACKR2, there are decreased numbers of eosinophils in the bone marrow. As a result, eosinophil and monocyte interactions are reduced within the bone marrow niche, and are associated with changes in monocyte gene expression.
Read the full summary ↓
Monocytes from ACKR2-/- mice are recruited to the tissues but are fundamentally altered in their ability to differentiate into macrophages, in the lung, peritoneal cavity and cavity wall. Bacterial elimination is impaired in ACKR2-/- mice during peritoneal infection. ACKR2 is therefore a key regulator of eosinophil-driven monocyte education in the bone marrow, required for full monocyte differentiation and macrophage function within the tissues.
This dataset
Open GSE334547 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 GSE334547_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 PRJNA1475436 and SRA study SRP707218. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
WT_MHCneg ×5 KO_MHCneg ×5 WT_mono ×4 KO_mono ×4 WT_SPM ×4 KO_SPM ×4

Supports a between-group comparison across 26 samples.

How we read this: 6 replicated groups read from 26 sample titles; they account for 26 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
Datasets on a similar topic

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