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Transcriptomic profile of IEC4.1 cells treated with an ASO to lncRNA XR_001779380 in response to IFN-gamma

GSE245478 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/05/29 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × IEC4.1_ST vs 3 × IEC4.1_ST+ IFNγ vs 3 × IEC4.1_ASO4 vs 3 × IEC4.1_ASO4 + IFNγGroups 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
Targeting the interaction between long noncoding RNA XR_001779380 and Prdm1 to enhance IFN-γ immunity in murine neonatal intestinal epithelial cellsmBio · 2025
Summary (written by the submitters)
LncRNAs may play an important role in intestinal epithelial cell autonomous defense against microbial infection. Our previous study showed that lncRNA XR_001779380 can interact with Prdm1 to modulate gene transcriuption in intestinal epithelial cells and may regualte IFN-gamma-stimulated gene transcription. Here we designed an antisense oligos-morpholine (ASO4) targeting the sequence of lncRNA XR_001779380 to interfere with its interaction with PRDM1.
Read the full summary ↓
Murine intestinal epithelial cells (IEC4.1 cells) were treated with ASO4 or a standard control ASO-morpholine (ST) for 24h, followed by exposure to IFN-gamma (1 ng/ml) for 4 hours. Then total RNA was collected for sequencing via DNBSEQ platform to obtain a comprehensive view of the transcriptome.
Published in
Targeting the interaction between long noncoding RNA XR_001779380 and Prdm1 to enhance IFN-γ immunity in murine neonatal intestinal epithelial cells
Jin K, Gong A-Y, Wang S et al. · mBio 2025 · PMID 40497734 · doi:10.1128/mbio.00773-25
This dataset
Open GSE245478 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 GSE245478_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 PRJNA1028577 and SRA study SRP466579. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40497734) ↗
Study design
3 × IEC4.1_ST vs 3 × IEC4.1_ST+ IFNγ vs 3 × IEC4.1_ASO4 vs 3 × IEC4.1_ASO4 + IFNγ

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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