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Sensory neurons co-opt classical immune signaling pathways to mediate chronic itch

GSE90883 Mus musculus (mouse) RNA-seq (gene expression) 8 samples Submitted 2017/09/18 Platform GPL21493
At a glance

RNA-seq (gene expression) · mouse · 8 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
8 samples: 4 × Control vs 4 × MC903Groups 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.
Summary (written by the submitters)
Mammals have evolved neurophysiologic reflexes such as coughing and scratching to expel invading pathogens and noxious environmental factors. It is well established that these responses are also associated with chronic inflammatory diseases such as asthma and atopic dermatitis. However, the mechanisms by which inflammatory pathways promote sensations such as itch remain poorly understood.
Read the full summary ↓
Here, we show that the type 2 cytokines IL-4 and IL-13 directly stimulate sensory neurons and that chronic itch is dependent on neuronal IL-4Rα and JAK1 signaling. In proof-of-concept clinical studies, we further show that patients with recalcitrant chronic itch markedly improve when treated with JAK inhibitors. Thus, signaling mechanisms previously ascribed to the immune system may represent novel therapeutic targets within the nervous system. Collectively, these studies reveal an evolutionarily conserved paradigm in which the sensory nervous system employs classical immune signaling pathways to influence mammalian behavior.
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 GSE90883_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 PRJNA356278 and SRA study SRP094566. Searching any of these in the dataset finder brings you back here.

Study design
4 × Control vs 4 × MC903

Supports a between-group comparison across 8 samples.

How we read this: 2 replicated groups read from 8 sample titles; they account for 8 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
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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.