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A hierarchical Rorc(γt) cis-regulatory cascade orchestrates differentiation of RORγt⁺ innate immune cells [BulkRNA-seq_vitro]

GSE278518 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/03/24 Platform GPL17021Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 4 × fetal liver, E14.5, BulkRNA-seq, RORgtmid_gtpos_Runx3pos vs 4 × fetal liver, E14.5, BulkRNA-seq, CD127posRunx3negRORgtneg_gtposRunx3negGroups 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
A hierarchical Rorc(γt) cis-regulatory cascade orchestrates differentiation of RORγt⁺ innate immune cellsImmunity · 2026
Summary (written by the submitters)
Although ILC3s are known to differentiate in RORγt-dependent manner, besides ILC3s, RORγt-dependent developmental program is shared among several lymphocytes.However, little is known about the regulatory mechanism of RORγt expression specific to ILC3s. Our data newly idetified cell lineage-specific and two-step regulation of RORγt expression in ILC3 including LTi cells.
Published in
A hierarchical Rorc(γt) cis-regulatory cascade orchestrates differentiation of RORγt⁺ innate immune cells
Fukui T, Watanabe M, Kobayashi R et al. · Immunity 2026 · PMID 41881028 · doi:10.1016/j.immuni.2026.02.002
This dataset
Open GSE278518 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 GSE278518_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 PRJNA1167692 and SRA study SRP535962. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41881028) ↗
Study design
4 × fetal liver, E14.5, BulkRNA-seq, RORgtmid_gtpos_Runx3pos vs 4 × fetal liver, E14.5, BulkRNA-seq, CD127posRunx3negRORgtneg_gtposRunx3neg

Supports a between-group comparison across 8 samples.

How we read this: 2 replicated groups read from 9 sample titles; they account for 8 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

Search all mouse RNA-seq datasets in GEO →

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