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TGF-β specifies TFH versus TH17 cell fates in murine CD4+ T cells through c-Maf (Seq03, bulk-RNAseq)

GSE197425 Mus musculus (mouse) RNA-seq (gene expression) 34 samples Submitted 2024/03/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 34 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
34 samples: 6 conditions, mostly with about 6 replicates eachGroups 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
TGF-β specifies T(FH) versus T(H)17 cell fates in murine CD4(+) T cells through c-MafScience immunology · 2024
Summary (written by the submitters)
Different numbers of naive murine CD4+ T cells were cultured at different seeding cell densities and under different polarizing conditions in 96-well plates coated with anti-CD3/anti-CD28 for 3.5 days in the presence of 2 or 5 ng/ml TGF-β (Tfh2 or Tfh5) or with anti-TGF-β (TfhA), sorted by flow cytometry, and subjected to bulk RNA-seq.
Published in
TGF-β specifies T(FH) versus T(H)17 cell fates in murine CD4(+) T cells through c-Maf
Chang Y, Bach L, Hasiuk M et al. · Science immunology 2024 · PMID 38427718 · doi:10.1126/sciimmunol.add4818
This dataset
Open GSE197425 in finder → Find more mouse RNA-seq datasets →
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.

Series matrix ↓
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 GSE197425_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA810195 and SRA study SRP361392. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38427718) ↗
Study design
6 conditions, mostly with about 6 replicates each
Seq03_Tfh2_4e4 ×6 Seq03_Tfh2_6e4 ×6 Seq03_Tfh5_4e4 ×6 Seq03_Tfh2_1e4 ×6 Seq03_Tfh2_2e4 ×5 Seq03_TfhA_4e4 ×5

Supports a between-group comparison across 34 samples.

How we read this: 6 replicated groups read from 34 sample titles; they account for 34 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.