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PAC1 constrains type II inflammation through promotion of CGRP signaling in ILC2s [RNA-seq]

GSE272723 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2024/09/29 Platform GPL17021
At a glance

Single-cell RNA-seq · mouse · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
16 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)
Dysfunction of group II innate lymphoid cells (ILC2s) plays an important role in the development of type II inflammation-related diseases such as asthma and pulmonary fibrosis. Notably, neural signals are increasingly recognized as pivotal regulators of ILC2s. However, how ILC2s intrinsically modulate their responsiveness to these neural signals is still largely unknown.
Read the full summary ↓
Here, using single-cell RNA sequencing and bulk mRNA sequencing, we report that the immune regulatory molecule PAC1 (phosphatase of activated cells 1) selectively promotes the signaling of neuropeptide CGRP (calcitonin gene-related peptide) in ILC2s. Moreover, PAC1 is necessary for ensuring the expression of CGRP-response genes by influencing chromatin accessibility. In summary, our study demonstrates that PAC1 is an important regulator of ILC2 responses and we propose that PAC1 is a potential target for therapeutic interventions of type II inflammation-related 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 GSE272723_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1138422 and SRA study SRP521211. Searching any of these in the dataset finder brings you back here.

Samples in this study

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