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Alternate isoforms of IRF7 Differentially Regulate Interferon Expression

GSE285352 Homo sapiens (human) RNA-seq (gene expression) 74 samples Submitted 2025/07/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 74 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
74 samples: 58 distinct titles, 10 of them repeatedGroups 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
Alternatively spliced isoforms of IRF7 differentially regulate interferon expression to tune response to viral infectionCell reports · 2025
Summary (written by the submitters)
Interferon Regulatory Factor 7 (IRF7), and its homologue IRF3, are master transcriptional regulators of the innate immune response. IRF7 binds to promoters of interferon beta (IFNb) and several IFNas, as a homodimer or as a heterodimer with IRF3 to drive expression of these type I IFNs, which in turn activate additional signaling pathways to promote expression of anti-viral genes.
Read the full summary ↓
Here we demonstrate that retention of the first intron within the coding region of IRF7 is highly regulated across immune tissues and in response to viral infection and other immunologic signals. Importantly, retention of this intron generates an alternative translation start site, resulting in a N-terminally extended form of the protein (exIRF7). Using CRISPR gene editing to generate cells that only express exIRF7, or the canonical version of IRF7 (cIRF7), we demonstrate that exIRF7 uniquely activates a program of genes, including IFNb, in response to innate immune triggers. We conclude that alternative splicing of IRF7 is a previously unrecognized mechanisms used by human cells to tune the interferon response to viral infection and other immune challenges.
Published in
Alternatively spliced isoforms of IRF7 differentially regulate interferon expression to tune response to viral infection
Panthi A, Ferretti MB, Howard O et al. · Cell reports 2025 · PMID 40833856 · doi:10.1016/j.celrep.2025.116166
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 GSE285352_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 PRJNA1203213 and SRA study SRP553907. Searching any of these in the dataset finder brings you back here.

Study design
58 distinct titles, 10 of them repeated
JSL1 WT cells. Unstim, ×3 JSL1 IRF7 KO cells, clone 8. Unstim, ×3 JSL1 IRF7 KO cells, clone 8. IFNa stimulation, ×3 JSL1 IRF7 Can cells, clone 10. Unstim, ×3 JSL1 IRF7 Alt cells, clone 3. Unstim, ×3 JSL1 IRF7 Alt cells, clone 3. IFNa stimulatio… ×3 JSL1 IRF7 KO cells, clone 8. PIC stimulation, ×2 JSL1 IRF7 Can cells, clone 10. PIC stimulatio… ×2 +2 more

How we read this: Read from 74 sample titles: 58 distinct titles with little repetition. 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

+ 34 more — browse all 74 samples with per-sample file links →

Datasets on a similar topic

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