GEO series

The Arp2/3 complex maintains genome integrity and survival of epidermal Langerhans cells

GSE288480 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/05/20 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: 8 conditions, mostly in triplicateGroups 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)

Myeloid cells use intracellular actin networks for key cellular processes, including cell migration and chemotaxis, phagocytosis or macropinocytosis, as well as immune synapse formation. However, whether these networks play any role in the development and/or survival of myeloid cells in tissues remains open. Here, we found that the Arp2/3 complex, which is responsible for the nucleation of branched actin networks, is needed for the in vivo maintenance of epidermal Langerhans cells (LCs) throughout life.

Read the full summary ↓

Mice harboring a genetic deletion of the Arpc4 subunit of the complex form LC networks at birth, but these cells decline in numbers following a process reminiscent of premature cellular aging. By combining in vivo analyses of LCs with in vitro experiments on bone-marrow-derived dendritic cells, we found that Arpc4-deficient cells manage to progress through the cell cycle but accumulate DNA damage associated with aberrant nuclear shapes and events of nuclear envelope rupture. These results provide the first evidence for a physiological role of Arp2/3 in maintenance of genome integrity and survival of immune cells in tissues.

This dataset

Open GSE288480 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 GSE288480_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 PRJNA1217845 and SRA study SRP560894. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 conditions, mostly in triplicate

D7_WT ×3 D8_WT ×3 D9_WT ×3 D10_WT ×3 D7_KO ×3 D8_KO ×3 D9_KO ×3 D10_KO ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 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

GSM8768598 D7_WT63 D7_WT
GSM8768599 D7_WT65 D7_WT
GSM8768600 D7_WT66 D7_WT
GSM8768601 D8_WT63 D8_WT
GSM8768602 D8_WT65 D8_WT
GSM8768603 D8_WT66 D8_WT
GSM8768604 D9_WT63 D9_WT
GSM8768605 D9_WT65 D9_WT
GSM8768606 D9_WT66 D9_WT
GSM8768607 D10_WT63 D10_WT
GSM8768608 D10_WT65 D10_WT
GSM8768609 D10_WT66 D10_WT
GSM8768610 D7_KO64 D7_KO
GSM8768611 D7_KO67 D7_KO
GSM8768612 D7_KO68 D7_KO
GSM8768613 D8_KO64 D8_KO
GSM8768614 D8_KO67 D8_KO
GSM8768615 D8_KO68 D8_KO
GSM8768616 D9_KO64 D9_KO
GSM8768617 D9_KO67 D9_KO
GSM8768618 D9_KO68 D9_KO
GSM8768619 D10_KO64 D10_KO
GSM8768620 D10_KO67 D10_KO
GSM8768621 D10_KO68 D10_KO

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.