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Argonaute3-SF3B3 complex controls pre-mRNA splicing to restrain Type-2 immunity [RNA-seq: cultured cells]

GSE243700 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2024/10/31 Platform GPL21103
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: 4 × WT TH2 7d vs 4 × Ago134 TH2 7d vs 3 × WT TH2 14d vs 3 × Ago134 TH2 14dGroups 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)
Argonaute (AGO) proteins execute Micro-RNA (miRNA) mediated gene silencing. However it is currently debated whether all 4 mammalian AGO proteins (AGO1, AGO2, AGO3 and AGO4) are required for miRNA activity. To address this, we generated a mouse with deleted Ago1, Ago3 and Ago4 genes (Ago134), and found that these Argonaute proteins are completely redundant for miRNA biogenesis, miRNA homeostasis or miRNA function, a role that is carried out exclusively by AGO2.
Read the full summary ↓
Instead, AGO1/3/4 are required to curtail the expansion of Type-2 adaptive immunity in mice via regulation of precursor-mRNA (pre-mRNA) splicing in CD4+ TH lymphocytes. Gain- and loss-of-function experiments demonstrate that nuclear AGO3 interacts directly with SF3B3, a component of the U2 spliceosome complex, to aid global mRNA splicing. Our work uncouples AGO1, AGO3 and AGO4 from miRNA-mediated RNAi, discovers a new AGO3:SF3B3 complex in the cellular nucleus, and reveals an underappreciated mechanism by which AGO proteins prevent hyper-inflammatory disease.
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 GSE243700_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 PRJNA1019659 and SRA study SRP462472. Searching any of these in the dataset finder brings you back here.

Study design
4 × WT TH2 7d vs 4 × Ago134 TH2 7d vs 3 × WT TH2 14d vs 3 × Ago134 TH2 14d

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 14 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.