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Bulk RNAseq analysis of Cx3cr1+ macrophages with and without IL4Ra deletion during bleomycin-induced lung fibrosis.

GSE272105 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/07/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 4 × saline_IL4Ra WT vs 4 × Bleomycin_IL4Ra WT vs 4 × Bleomycin_IL4Ra KOGroups 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)
Wound healing in response to acute injury is mediated by the coordinated and transient activation of parenchymal, stromal, and immune cells that resolves to homeostasis. Environmental, genetic, and epigenetic factors associated with inflammation and aging can lead to persistent activation of the microenvironment and fibrosis. Here, we identify opposing roles of IL-4 cytokine signaling in interstitial macrophages and type II alveolar epithelial cells (ATIIs).
Read the full summary ↓
We show that IL4Ra signaling in macrophages promotes regeneration of the alveolar epithelium after bleomycin-induced lung injury. Using organoids and mouse models, we show that IL-4 directly acts on a subset of ATIIs to induce the expression of the transcription factor SOX9 and reprograms them toward a progenitor-like state with both airway and alveolar lineage potential. In the contexts of aging and bleomycin-induced lung injury, this leads to aberrant epithelial cell differentiation and bronchiolization, consistent with cellular and histological changes observed in interstitial lung disease.
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 GSE272105_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 PRJNA1135117 and SRA study SRP519547. Searching any of these in the dataset finder brings you back here.

Study design
4 × saline_IL4Ra WT vs 4 × Bleomycin_IL4Ra WT vs 4 × Bleomycin_IL4Ra KO

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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
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