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Limited activation interdependence, and differing patterns of the in vivo effects, of IKK1 and IKK2 downstream of NIK

GSE306633 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/09/01 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 9 conditions, mostly in duplicateGroups 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
Limited activation interdependence and differing patterns of the in vivo effects of IKK1 and IKK2 downstream of NIKCell reports · 2025
Summary (written by the submitters)
The protein kinase NIK controls numerous immune functions by signaling for the processing of NF-kB2 and for the activation of other NF-kB proteins. NIK associates with IKK1 and has been suggested to exert all its effects via IKK1 activation. In this study, we demonstrate that NIK, by binding to IKK1, also associates with IKK2 and NEMO, allowing NIK to dictate the phosphorylation of IKK2 independently of IKK1's enzymatic function.
Read the full summary ↓
IKK2 activation is also maintained when the phosphorylation of NF-κB2 is compromised by a mutation of NIK that affects its interaction with IKK1 and NF-kB2. Analyzing mice with this mutation reveals the differing dependencies of various effects of NIK on the activation of IKK1 or IKK2 and on the activation of differing NF-kB proteins. These findings indicate that NIK’s signaling mechanisms for the activation of different NF-kB proteins by the two IKKs are not strictly coupled.
Published in
Limited activation interdependence and differing patterns of the in vivo effects of IKK1 and IKK2 downstream of NIK
Liang X, Nagarajan A, Du J et al. · Cell reports 2025 · PMID 41060807 · doi:10.1016/j.celrep.2025.116404
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 GSE306633_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 PRJNA1311535 and SRA study SRP613625. Searching any of these in the dataset finder brings you back here.

Study design
9 conditions, mostly in duplicate
WT_0h ×4 WT_24h ×4 WT_6h ×4 KO_0h ×2 KO_24h ×2 KO_6h ×2 MUT_0h ×2 MUT_24h ×2 +1 more

Supports a between-group comparison across 24 samples.

How we read this: 9 replicated groups read from 24 sample titles; they account for 24 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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