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RNA-sequencing of inguinal white adipose tissue (iWAT) from kynurenine 3-monooxygenase (Kmo) knockout mice and wild-type littermates on chow and high-fat diets.

GSE277692 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/02/08 Platform GPL34290
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: 4 × iWAT, wild-type, chow, vs 4 × iWAT, Kmo-KO, chow, vs 4 × iWAT, wild-type, HFD, vs 4 × iWAT, Kmo-KO, HFD,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
Constitutive loss of kynurenine-3-monooxygenase changes circulating kynurenine metabolites without affecting systemic energy metabolismAmerican journal of physiology. Endocrinology and metabolism · 2025
Summary (written by the submitters)
To investigate if chronically elevated circulating kynurenic acid (KYNA) and reduced quinolinic acid (QUIN) levels affect whole-body energy metabolism, we used a knockout-first gene targeting strategy to eliminate Kmo gene expression in mice. We conducted a series of metabolic assessments on male and female mice fed either a chow or high-fat diet (HFD) and performed RNA-sequencing on the inguinal white adipose tissue (iWAT) from male Kmo-defficient mice and their wild-type littermate controls on chow and high-fat diets.
Published in
Constitutive loss of kynurenine-3-monooxygenase changes circulating kynurenine metabolites without affecting systemic energy metabolism
Dumont KD, Jannig PR, Porsmyr-Palmertz M et al. · American journal of physiology. Endocrinology and metabolism 2025 · PMID 39805032 · doi:10.1152/ajpendo.00386.2024
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 GSE277692_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 PRJNA1163367 and SRA study SRP533889. Searching any of these in the dataset finder brings you back here.

Study design
4 × iWAT, wild-type, chow, vs 4 × iWAT, Kmo-KO, chow, vs 4 × iWAT, wild-type, HFD, vs 4 × iWAT, Kmo-KO, HFD,

Supports a between-group comparison across 16 samples.

How we read this: 4 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
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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.