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Small intestinal lymph node identity is defined by medullary stromal cells in humans and mice [CD169_RPL22HA_lns_RNAseq]

GSE281209 Mus musculus (mouse) RNA-seq (gene expression) 37 samples Submitted 2025/11/01 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 37 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
37 samples: 12 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)
Lymph nodes (LNs) along the murine gastrointestinal tract are immunologically distinct. Here, we investigated what defines gut LN identity at large in humans and mice and drives their regional differences. Using transcriptional profiling and imaging, we found that stromal cells in the LN medulla and sinus are susceptible to location along the intestine, with high conservation between human and mouse.
Read the full summary ↓
Specifically, the medulla of small intestine-draining LNs was enriched for fibroblastic reticular cell subpopulations implicated in extracellular matrix remodeling and stromal cell replenishment, lymphatic endothelial cells, and macrophages compared to LNs draining colon and other sites like lung. In mice, this unique medullary cellular network was established around weaning age by Vitamin A, while the gut microbiota regulated the effect’s amplitude. Our study posits the LN medulla as a location for tissue-specific immune responses and uncovers privileged access to lipid-soluble vitamins as a pivotal driving force for small intestinal LN properties.
This dataset
Open GSE281209 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 GSE281209_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 PRJNA1182729 and SRA study SRP543507. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
Duodenal LN_cd169 ×3 Jejunal LN_cd169 ×3 Ileal LN_cd169 ×3 Ceco-colonic LN_cd169 ×3 Inguinal LN_cd169 ×3 Liver LN_cd169 ×3 Celiac LN_cd169 ×3 Super Cervical LN_cd169 ×3 +6 more

Supports a between-group comparison across 35 samples.

How we read this: 12 replicated groups read from 37 sample titles; they account for 35 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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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.