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Genetic lineage tracing defines myofibroblast origin and function in the injured heart

GSE83337 Mus musculus (mouse) RNA-seq (gene expression) 185 samples Submitted 2016/06/14 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 185 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
185 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)
Cardiac fibroblasts convert to myofibroblasts with injury to mediate healing after acute myocardial infarction and to mediate long-standing fibrosis with chronic disease. Myofibroblasts remain a poorly defined cell-type in terms of their origins and functional effects in vivo. Methods: Here we generate Postn (periostin) gene-targeted mice containing a tamoxifen inducible Cre for cellular lineage tracing analysis.
Read the full summary ↓
This Postn allele identifies essentially all myofibroblasts within the heart and multiple other tissues. Results: Lineage tracing with 4 additional Cre-expressing mouse lines shows that periostin-expressing myofibroblasts in the heart derive from tissue-resident fibroblasts of the Tcf21 lineage, but not endothelial, immune/myeloid or smooth muscle cells. Deletion of periostin+ myofibroblasts reduces collagen production and scar formation after myocardial infarction. Periostin-traced myofibroblasts also revert back to a less activated state upon injury resolution. Conclusions: Our results define the myofibroblast as a periostin-expressing cell-type necessary for adaptive healing and fibrosis in the heart, which arises from Tcf21+ tissue-resident fibroblasts.
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 GSE83337_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 PRJNA325633 and SRA study SRP076540. Searching any of these in the dataset finder brings you back here.

Samples in this study

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