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Context-dependent role of type 3 innate lymphoid cells in mucosal protection

GSE270398 Mus musculus (mouse) RNA-seq (gene expression) 50 samples Submitted 2024/06/20 Platform GPL34475Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 50 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
50 samples
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)
How group 3 innate lymphoid cells (ILC3) regulate mucosal protection in the presence of T cells remains poorly understood. Here, we examined ILC3 function in intestinal immunity using ILC3-deficient mice that maintain endogenous T cells, Th17 cells, and secondary lymphoid organs. ILC3 were dispensable for generation of Th17 and Th22 cell responses to commensal and pathogenic bacteria, and absence of ILC3 did not affect IL-22-production by CD4 T cells before or during infection.
Read the full summary ↓
However, despite presence of IL-22-producing T cells, ILC3 and ILC3-derived IL-22 were required for maintaining homeostatic functions of the intestinal epithelium. T cell-sufficient, ILC3-deficient mice were capable of pathogen clearance and survived infection with low dose Citrobacter rodentium. However, ILC3 increased pathogen tolerance at early timepoints of infection by activating tissue-protective immune pathways. Consequently, ILC3 were indispensable for survival of high dose infection. Our results demonstrate a crucial context-dependent role for ILC3 in immune-sufficient animals and provide a blueprint for uncoupling of ILC3 and Th17 cell functions.
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 GSE270398_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: 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 PRJNA1085237 and SRA study SRP503451. Searching any of these in the dataset finder brings you back here.

Samples in this study

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