GEO series

A Polyamine-mediated Posttranslational Modification Required for Macrophage Tissue Residency [RNA-Seq]

GSE290686 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/01/15 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 24 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: 24 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.
Paper: The transition from monocyte to tissue-resident macrophage requires DHPSNature · 2026

Summary (written by the submitters)

Tissue-resident macrophages (RTMs) form during embryogenesis, self-renew locally, and regulate tissue homeostasis by clearing dead cells and debris. During tissue damage, however, bone marrow-derived monocytes enter tissue sites and differentiate into RTM, repairing the tissue and replenishing macrophages in the niche. Universal cell-intrinsic mechanisms that control the monocyte to RTM transition remain elusive.

Read the full summary ↓

We investigated mice with myeloid cell deletions in deoxyhypusine synthase (DHPS), an enzyme that mediates the polyamine-dependent hypusine modification of the translation factor eIF5A, and found that DHPS is required for cell adhesion and signaling programs critical for RTMs. Without DHPS expression, immature tissue macrophages form, but RTM and associated homeostatic functions are lost. Thus, the polyamine-hypusine pathway is a global, tissue-agnostic program driving the differentiation trajectory of monocyte-derived macrophages into RTM.

Published in

The transition from monocyte to tissue-resident macrophage requires DHPS

Carrizo GE, Lin P, Lee SH et al. · Nature 2026 · PMID 41565804 · doi:10.1038/s41586-025-09972-2

This dataset

Open GSE290686 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 GSE290686_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 PRJNA1229540 and SRA study SRP566823. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41565804) ↗

Study design

6 conditions, mostly with about 4 replicates each

Liver_KO ×4 Liver_WT ×4 Lung_KO ×4 Lung_WT ×4 P_KO ×4 P_WT ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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

GSM8819529 Liver_KO1 Liver_KO
GSM8819530 Liver_KO2 Liver_KO
GSM8819531 Liver_KO3 Liver_KO
GSM8819532 Liver_KO4 Liver_KO
GSM8819533 Liver_WT1 Liver_WT
GSM8819534 Liver_WT2 Liver_WT
GSM8819535 Liver_WT3 Liver_WT
GSM8819536 Liver_WT4 Liver_WT
GSM8819537 Lung_KO1 Lung_KO
GSM8819538 Lung_KO2 Lung_KO
GSM8819539 Lung_KO3 Lung_KO
GSM8819540 Lung_KO4 Lung_KO
GSM8819541 Lung_WT1 Lung_WT
GSM8819542 Lung_WT2 Lung_WT
GSM8819543 Lung_WT3 Lung_WT
GSM8819544 Lung_WT4 Lung_WT
GSM8819545 P_KO1 P_KO
GSM8819546 P_KO2 P_KO
GSM8819547 P_KO3 P_KO
GSM8819548 P_KO4 P_KO
GSM8819549 P_WT1 P_WT
GSM8819550 P_WT2 P_WT
GSM8819551 P_WT3 P_WT
GSM8819552 P_WT4 P_WT

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