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Sexual dimorphism in skin immunity is mediated by androgen-ILC2-dendritic cell axis [Bulk RNA-seq]

GSE253293 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/04/09 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 5 × RNAseq_keratinocytes_female_Sepi vs 5 × RNAseq_keratinocytes_male_Sepi vs 3 × RNAseq_keratinocytes_female_Ctrl vs 3 × RNAseq_keratinocytes_male_CtrlGroups 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
Sexual dimorphism in skin immunity is mediated by an androgen-ILC2-dendritic cell axisScience (New York, N.Y.) · 2024
Summary (written by the submitters)
Males and females exhibit profound differences in immune responses and disease susceptibility. However, the factors responsible for sex differences in tissue immunity remain poorly understood. Here, we uncover a dominant role for type 2 innate lymphoid cells (ILC2) in shaping sexual immune dimorphism within the skin. Mechanistically, negative regulation of ILC2 by androgens leads to a reduction in dendritic cell (DC) accumulation and activation in males, and reduced tissue immunity.
Read the full summary ↓
Collectively, this work uncovers an androgen-ILC2-DC axis in controlling sexual immune dimorphism. Moreover, this work proposes that tissue immune set-points are defined by the dual action of sex hormones and the microbiota, with sex hormones controlling the strength of local immunity and microbiota calibrating its tone.
Published in
Sexual dimorphism in skin immunity is mediated by an androgen-ILC2-dendritic cell axis
Chi L, Liu C, Gribonika I et al. · Science (New York, N.Y.) 2024 · PMID 38574174 · doi:10.1126/science.adk6200
This dataset
Open GSE253293 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 GSE253293_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 PRJNA1064989 and SRA study SRP483822. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38574174) ↗
Study design
5 × RNAseq_keratinocytes_female_Sepi vs 5 × RNAseq_keratinocytes_male_Sepi vs 3 × RNAseq_keratinocytes_female_Ctrl vs 3 × RNAseq_keratinocytes_male_Ctrl

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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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