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An ageing bone marrow exacerbates lung fibrosis via a dysregulated regulatory T cell driven axis, fuelling profibrotic macrophage persistence.

GSE274253 Mus musculus (mouse) RNA-seq (gene expression) 44 samples Submitted 2024/12/02 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 44 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
44 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)
Pulmonary fibrosis is an incurable disease, which increasingly manifests with advanced age. Yet, how the ageing hematopoietic niche influences immune cell function and fibrosis progression in the lungs remains elusive. Using heterochronic transplant mouse models, we discovered that an aged bone marrow exacerbates lung fibrosis irrespective of lung tissue age.
Read the full summary ↓
Upon lung injury, there was an increased pulmonary infiltration of monocyte-derived alveolar macrophages (Mo-AMs) from an aged bone marrow. These Mo-AMs displayed an enhanced profibrotic profile and a delayed transition in acquiring a homeostatic tissue-resident phenotype. This impaired Mo-AM differentiation was attributed to diminished numbers of regulatory T cells (Tregs) and the reduced availability of the anti-inflammatory cytokine IL-10 in the lung microenvironment of mice engrafted with aged bone marrow. Mechanistically, we show that Tregs are crucial providers of IL-10 that promote timely Mo-AM maturation and attenuate fibrosis progression. Our findings demonstrate the critical influence of an aged bone marrow on the development of lung fibrosis and identify a Treg-mediated resolutory axis as a potential therapeutic target for accelerated tissue repair.
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 GSE274253_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 PRJNA1145463 and SRA study SRP524782. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 44 more — browse all 44 samples with per-sample file links →

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