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Single cell sequencing of the effects of blocking lymphotoxin alpha in the mesenteric lymph node and spleen

GSE296503 Mus musculus (mouse) Single-cell RNA-seq 21 samples Submitted 2025/08/01 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 21 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
21 samples: 21 samples, each with a distinct title — no replicated groupsGroups 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
Distinct roles for B cell-derived LTα3 and LTα1β2 in TNF-mediated ileitisNature immunology · 2025
Summary (written by the submitters)
TNFDARE+/- mice develop TNF-driven transmural ileitis and mesenteric inflammation, and lose body mass, reminiscent of human Crohn’s disease. Here, we report that B cells regulate body mass and intestinal permeability during ileitis in a manner that is linked to lymphotoxin (LT)-a but not LTb, whereas B cell LTab2 promoted mesenteric TLS that suppressed lymphatic outflow.
Read the full summary ↓
Using genetic approaches and neutralizing reagents, we connect LTa3, a ligand for TNFRs, expressed by activated follicular B cells to their appearance in draining lymph nodes and the generation or persistence of IgA+ ileal plasma cells. Some of the same B cells also expressed TNF. Opposite to LTa, expression of TNF by B cells was disadvantageous to the development of IgA+ ileal plasma cells, suggesting counterbalancing interplay between LTa3 and TNF in ileitis. These data highlight a multi-faceted role of B cells in ileitis that includes an unexpected role for B cell-derived LTa3 in the maintenance of body weight.
Published in
Distinct roles for B cell-derived LTα3 and LTα1β2 in TNF-mediated ileitis
Erlich EC, Alayo QA, Kim A et al. · Nature immunology 2025 · PMID 40921841 · doi:10.1038/s41590-025-02263-y
This dataset
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.

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 GSE296503_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1259518 and SRA study SRP583407. Searching any of these in the dataset finder brings you back here.

Study design
21 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 21 sample titles: 21 distinct titles with little repetition. 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
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