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Transcriptional and functional architecture of the whole neutrophil compartment [RNA-seq sorted_cells]

GSE301186 Mus musculus (mouse) Single-cell RNA-seq 11 samples Submitted 2026/06/30 Platform GPL17021
At a glance

Single-cell RNA-seq · mouse · 11 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
11 samples: 3 × CD14pos_PDL1neg_neutrophils vs 3 × CD14neg_PDL1pos_neutrophils vs 3 × CD14pos_PDL1pos_neutrophils vs 2 × Double_Negative_CD14neg_PDL1neg_neutrophilsGroups 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)
In this study, we present NeuMAP, a comprehensive single-cell analysis of neutrophils spanning over 40 anatomical, physiological, and pathological contexts in mice. NeuMAP confirms and expands previous models of neutrophil diversity, revealing the organization of neutrophils into distinct functional hubs under both normal and pathological conditions.
Read the full summary ↓
Furthermore, we delineate prototypical trajectories as key organizers of granulopoiesis and examine neutrophil dynamics along these trajectories during acute inflammation and cancer. Integrating insights from fate mapping, mutant mouse models, and in vitro experiments, we identified immunological signals guiding neutrophil through these typical trajectories of granulopoiesis, that balance immune protection, tissue homeostasis and repair. Specifically, we identified IFNB, GMCSF, and TGFB as drivers of pro-inflammatory, cancer-associated, and mature neutrophil states, respectively and found that the transcription factor JUNB drives the angiogenic and immunosuppressive function of neutrophils. Additionally, we uncover conserved transcriptional signatures for human neutrophil states, validate their prognostic significance in cancer patients, and introduce a proof-of-concept strategy for exploring the diagnostic potential of neutrophil functional diversity across various diseases using single-cell transcriptomics of blood neutrophils. Our study provides a model that delineates the global architecture of the neutrophil compartment in mammals, and stablishes a robust framework for further exploration of neutrophil biology.
This dataset
Open GSE301186 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 GSE301186_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 PRJNA1284250 and SRA study SRP596084. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × CD14pos_PDL1neg_neutrophils vs 3 × CD14neg_PDL1pos_neutrophils vs 3 × CD14pos_PDL1pos_neutrophils vs 2 × Double_Negative_CD14neg_PDL1neg_neutrophils

Supports a between-group comparison across 11 samples.

How we read this: 4 replicated groups read from 11 sample titles; they account for 11 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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