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Sensor Systems of KEAP1 Uniquely Detecting Oxidative and Electrophilic Stresses Separately In Vivo

GSE276818 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/10/09 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 8 × Trspfl/fl vs 4 × AlbCre vs 4 × Trspfl/fl::AlbCreGroups 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
Sensor systems of KEAP1 uniquely detecting oxidative and electrophilic stresses separately In vivoRedox biology · 2024
Summary (written by the submitters)
In the KEAP1-NRF2 stress response system, KEAP1 acts as a sensor for oxidative and electrophilic stresses through formation of S-S bond and C-S bond, respectively. Of the many questions left related to the sensor activity, following three appear important; whether these KEAP1 sensor systems are operating in vivo, whether oxidative and electrophilic stresses are sensed by the similar or distinct systems, and how KEAP1 equips highly sensitive mechanisms detecting oxidative and electrophilic stresses in vivo.
Read the full summary ↓
To address these questions, we conducted a series of analyses utilizing KEAP1-cysteine substitution mutant mice, conditional selenocysteine-tRNA (Trsp) knockout mice, and human cohort whole genome sequence (WGS) data. The Trsp-knockout provokes severe deficiency of selenoproteins and compensatory activation of NRF2. However, mice lacking homozygously a pair of critical oxidative stress sensor cysteine residues of KEAP1 fail to activate NRF2 in the Trsp-knockout livers. Secondly, this study provides evidence for the differential utilization of KEAP1 sensors for oxidative and electrophilic stresses in vivo. Thirdly, theoretical calculations show that the KEAP1 dimer equips quite sensitive sensor machinery in which modification of a single molecule of KEAP1 within the dimer is sufficient to affect the activity. WGS examinations of rare variants identified seven non-synonymous variants in the oxidative stress sensors in human KEAP1, while no variant was found in electrophilic sensor cysteine residues, supporting the fail-safe nature of the KEAP1 oxidative stress sensor activity. These results provide valuable information for our understanding how mammals respond to oxidative and electrophilic stresses efficiently.
Published in
Sensor systems of KEAP1 uniquely detecting oxidative and electrophilic stresses separately In vivo
Sato M, Yaguchi N, Iijima T et al. · Redox biology 2024 · PMID 39307045 · doi:10.1016/j.redox.2024.103355
This dataset
Open GSE276818 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 GSE276818_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 PRJNA1159162 and SRA study SRP531826. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39307045) ↗
Study design
8 × Trspfl/fl vs 4 × AlbCre vs 4 × Trspfl/fl::AlbCre

Supports a between-group comparison across 16 samples.

How we read this: 3 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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