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Tff1-expressing Tregs in lung prevents exacerbation of Bleomycin-induced pulmonary fibrosis (RNA-Seq)

GSE267864 Mus musculus (mouse) RNA-seq (gene expression) 2 samples Submitted 2024/08/19 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 2 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
2 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.
Paper
Tff1-expressing Tregs in lung prevent exacerbation of Bleomycin-induced pulmonary fibrosisFrontiers in immunology · 2024
Summary (written by the submitters)
Bleomycin (BLM) induces lung injury, leading to inflammation and pulmonary fibrosis. Regulatory T cells (Tregs) maintain self-tolerance and control host immune responses. However, little is known about their involvement in the pathology of pulmonary fibrosis. Here we show that a unique Treg subset that expresses trefoil factor family 1(Tff1) emerges in the BLM-injured lung.
Read the full summary ↓
These Tff1-expressing Tregs (Tff1-Tregs) were induced by IL-33. Moreover, although Tff1 ablation in Tregs had no impact, selective ablation of Tff1-Tregs using an intersectional genetic method promoted pro-inflammatory features of macrophages in the injured lung and exacerbated the fibrosis. Taken together, our study revealed the presence of a unique Treg subset expressing Tff1 in BLM-injured lungs and their critical role in the injured lung to ameliorate fibrosis.
Published in
Tff1-expressing Tregs in lung prevent exacerbation of Bleomycin-induced pulmonary fibrosis
Okamoto M, Kuratani A, Okuzaki D et al. · Frontiers in immunology 2024 · PMID 39286257 · doi:10.3389/fimmu.2024.1440918
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 GSE267864_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 PRJNA1113556 and SRA study SRP508655. Searching any of these in the dataset finder brings you back here.

Samples in this study

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