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ERH regulates type II interferon immune signaling through post-transcriptional regulation of JAK2 mRNA [1]

GSE274069 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/08/22 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
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.
Paper
ERH regulates type II interferon immune signaling through post-transcriptional regulation of JAK2 mRNANucleic acids research · 2025
Summary (written by the submitters)
Type II interferon (IFNγ) signaling is essential for innate immunity and critical for effective immunological checkpoint blockade in cancer immunotherapy. Genetic screen identification of post-transcriptional regulators of this pathway has been challenging since such factors are often essential for cell viability. Here, we utilize our inducible CRISPR/Cas9 approach to screen for key post-transcriptional regulators of IFNγ signaling, and in this way identify ERH and the ERH-associated splicing and RNA export factors MAGOH, SRSF1, and ALYREF.
Read the full summary ↓
Loss of these factors impairs post-transcriptional mRNA maturation of JAK2, a crucial kinase for IFNγ signaling, resulting in abrogated JAK2 protein levels and diminished IFNγ signaling. Further analysis highlights a critical role for ERH in preventing intron retention in AU-rich regions in specific transcripts, such as JAK2. This regulation is markedly different from previously described retention of GC-rich introns. Overall, these findings reveal that post-transcriptional JAK2 processing is a critical rate-limiting step for the IFNγ-driven innate immune response.
Published in
ERH regulates type II interferon immune signaling through post-transcriptional regulation of JAK2 mRNA
Soderholm A, Vunjak M, de Almeida M et al. · Nucleic acids research 2025 · PMID 40586312 · doi:10.1093/nar/gkaf545
This dataset
Open GSE274069 in finder → Find more human 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 GSE274069_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 PRJNA1144894 and SRA study SRP524614. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40586312) ↗
Study design
6 conditions, mostly in triplicate
RKO-dox-Cas9, sgAAVS1, non-treated, biol ×3 RKO-dox-Cas9, sgERH, non-treated, biol ×3 RKO-dox-Cas9, sgAAVS1, IFNgamma, biol ×3 RKO-dox-Cas9, sgERH, IFNgamma, biol ×3 RKO-dox-Cas9, sgAAVS1, IL-1beta, biol ×3 RKO-dox-Cas9, sgERH, IL-1beta, biol ×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
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