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Next Generation Sequencing Analysis of Transcriptome Profile in CRISPR/Cas9 U90926KO IEC4.1 Cells Treated with IFN-gamma protein (IFNγ)

GSE245533 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/09/09 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 × IEC4.1cells, Ctrl, vs 3 × IEC4.1cells, Ctrl + IFNγ, vs 3 × IEC4.1cells, U90926KO, vs 3 × IEC4.1cells, U90926KO + IFNγ,Groups 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
Long non-coding RNA U90926 modulates IFN-γ-stimulated gene transcription and cell-intrinsic anti-Cryptosporidium defense in intestinal epithelial cellsInfection and immunity · 2025
Summary (written by the submitters)
Interferon-gamma protein (IFNγ) plays a key role in intestinal epithelial cell-autonomous defense against microbial infection. The underlying mechansims of host immune regulation remains obscure and increasing evidence has shown long non coding RNAs (lncRNAs) can regulating gene expression at both the transcriptional and posttranscitpional levels.
Read the full summary ↓
In the current study, we analyzed the transcriptome of murine intestinal epithelial cells (IEC4.1 cells) or stable CRISPR/cas9 U90926KO IEC4.1 cells following treatment with IFNγ to identify potential immune gene tragets of this lncRNA. Total RNA was collected for the genome-wide analysis, for sequencing using DNBSEQ platform.
Published in
Long non-coding RNA U90926 modulates IFN-γ-stimulated gene transcription and cell-intrinsic anti-Cryptosporidium defense in intestinal epithelial cells
Graham ML, Gong A-Y, Jin K et al. · Infection and immunity 2025 · PMID 40982010 · doi:10.1128/iai.00328-25
This dataset
Open GSE245533 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 GSE245533_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 PRJNA1028950 and SRA study SRP466709. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40982010) ↗
Study design
3 × IEC4.1cells, Ctrl, vs 3 × IEC4.1cells, Ctrl + IFNγ, vs 3 × IEC4.1cells, U90926KO, vs 3 × IEC4.1cells, U90926KO + 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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