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Macrophages sense ECM mechanics and growth factor availability through cytoskeletal remodeling to regulate their tissue repair program [RNA-seq]

GSE239377 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/20 Platform GPL19057
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: 6 conditions, mostly in duplicateGroups 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
Mechanosensing regulates tissue repair program in macrophagesScience advances · 2024
Summary (written by the submitters)
Tissue resident macrophages play important roles in tissue homeostasis and repair. However, how macrophages monitor and maintain tissue integrity is not well understood. The extracellular matrix (ECM) is a key structural and organizational component of all tissues. Here, we find that macrophages sense the mechanical properties of the ECM in order to regulate a specific tissue repair program.
Read the full summary ↓
We show that macrophage mechanosensing is mediated by cytoskeletal remodeling and can be performed in three-dimensional environments through a non-canonical, integrin-independent mechanism analogous to amoeboid migration. We find that these cytoskeletal dynamics also integrate biochemical signaling by CSF1 and ultimately regulate chromatin accessibility to control the mechanosensitive gene expression program. This study suggests a distinct mode of ECM mechanosensing and growth factor signaling through which macrophages may regulate tissue repair and fibrosis.
Published in
Mechanosensing regulates tissue repair program in macrophages
Meizlish ML, Kimura Y, Pope SD et al. · Science advances 2024 · PMID 38478620 · doi:10.1126/sciadv.adk6906
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 GSE239377_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 PRJNA998932 and SRA study SRP451646. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
BMDMs, TC_Untx_24hrs ×2 BMDMs, TC_IL-4_24hrs ×2 BMDMs, 7mg_Untx_24hrs ×2 BMDMs, 7mg_IL-4_24hrs ×2 BMDMs, 2mg_Untx_24hrs ×2 BMDMs, 2mg_IL-4_24hrs ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 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
Datasets on a similar topic

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