← BioTransfer GEO Dataset Finder
GEO series

Tracking the fate of pathogenic CD4 T helper cells in vivo.

GSE68242 Mus musculus (mouse) RNA-seq (gene expression) 6 samples Submitted 2015/04/25 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 6 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
6 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)
Inflammation is a beneficial host response to infection, but it also contributes to inflammatory disease if unregulated. The Th17 lineage of T helper (Th) cells can cause severe human inflammatory diseases. These cells exhibit both instability (i.e., they can cease to express their signature cytokine, IL-17A) and plasticity (i.e., they can start expressing cytokines typical of other lineages) upon in vitro re-stimulation.
Read the full summary ↓
However technical limitations prevented the transcriptional profiling of pre- and post-conversion Th17 cells ex vivo during immune responses. Thus, it is unknown whether Th17 cell plasticity merely reflects change in expression of a few cytokines, or if Th17 cells physiologically undergo global genetic reprogramming driving their conversion from one T helper cell type to another, a process known as “transdifferentiation”. Furthermore, while Th17 cell instability/plasticity has been associated with pathogenicity, it is unknown whether this could present a therapeutic opportunity, whereby formerly pathogenic Th17 cells could adopt an anti-inflammatory fate. Here we used two novel fate-mapping mouse models to track Th17 cells during immune responses to show that CD4+ T cells that formerly expressed IL-17A go on to acquire an anti-inflammatory phenotype. The transdifferentiation of Th17 into regulatory T cells was illustrated by a global change in their transcriptome and the acquisition of potent regulatory capacity. Comparisons of the transcriptional profiles of pre- and post-conversion Th17 cells also revealed a role for canonical TGF- β signaling and the aryl hydrocarbon receptor (AhR) in conversion. Thus, Th17 transdifferentiate into regulatory cells, and contribute to the resolution of inflammation. Our data suggest Th17 cell instability and plasticity is a therapeutic opportunity for inflammatory diseases.
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 GSE68242_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 PRJNA282123 and SRA study SRP057639. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 6 more — browse all 6 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.