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PUS10-induced tRNA fragmentation impacts retrotransposon-driven inflammation [Polysome profiling]

GSE291043 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/06/13 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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)
Pseudouridine (Y) is the most widespread RNA modification type on cellular RNAs and is dynamically catalyzed by a family of Y synthases (PUSes) in response to pathophysiological cues. PUS10 has been previously shown to regulate miRNA biogenesis in addition to modifying tRNAs, however its role in adapting gene expression to stress remains elusive.
Read the full summary ↓
Here, we establish a novel role for PUS10 as a regulator of LTR retrotransposon-driven inflammatory response. Using Pus10 KO mice, we demonstrate that Pus10 depletion leads to upregulation of interferon-stimulated genes (ISGs) and increased resistance to viral infection in vitro and in vivo. Mechanistically, PUS10 regulates a subset of 5’-derived tRNA (tdR) fragment, 5’ tdR Gly-GCC, that via targeting specific LTR retroelements modulates RNA-DNA hybrids accumulation and cGAS/STING/IRF3 pathway. Importantly, reduced PUS10 activity correlate with chronic autoimmune conditions, pinpointing PUS10 as a potential contributor to human immune regulation.
This dataset
Open GSE291043 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 GSE291043_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 PRJNA1231450 and SRA study SRP567815. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
MEF_WTinp_n ×3 MEF_PUS10KOinp_n ×3 MEF_WTmono_n ×3 MEF_PUS10KOmono_n ×3 MEF_WTpoly_n ×3 MEF_PUS10KOpoly_n ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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