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Retinoic acid and TGF-β orchestrate organ-specific programs of tissue-residency [dnRA_Antag]

GSE277248 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2024/09/16 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 samples: 13 distinct titles, 1 of them repeatedGroups 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
Retinoic acid and TGF-β orchestrate organ-specific programs of tissue residencyImmunity · 2024
Summary (written by the submitters)
Tissue-resident memory T (TRM) cells are integral to tissue immunity, persisting in diverse anatomical sites where they adhere to a common transcriptional framework. How these cells integrate distinct local cues to adopt the common TRM cell fate remains poorly understood.
Read the full summary ↓
Here, we show that while skin TRM cells strictly require TGF-β for tissue residency, those in other locations utilize the metabolite retinoic acid (RA) to drive an alternative differentiation pathway, directing a TGF-β-independent tissue residency program in the liver and synergizing with TGF-β to drive the TRM cells in the small intestine.
Published in
Retinoic acid and TGF-β orchestrate organ-specific programs of tissue residency
Obers A, Poch T, Rodrigues G et al. · Immunity 2024 · PMID 39406245 · doi:10.1016/j.immuni.2024.09.015
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 GSE277248_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 PRJNA1161493 and SRA study SRP532870. Searching any of these in the dataset finder brings you back here.

Study design
13 distinct titles, 1 of them repeated
Naïve P14 ×2

How we read this: Read from 14 sample titles: 13 distinct titles with little repetition. 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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