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RNA-seq analysis of macrophage NFATc3 or ASK1 effects on metabolic dysfunction-associated steatohepatitis

GSE314637 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2026/01/20 Platform GPL13112Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 28 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
28 samples: 6 conditions, mostly with about 4 replicates eachGroups 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.
Summary (written by the submitters)
To explore the roles of macrophage NFATc3 and ASK1 in metabolic dysfunction-associated steatohepatitis, we generated macrophage-specific Nfatc3 knockout mice (Nfatc3-MKO), macrophage-specific Ask1 knockout mice (Ask1-MKO),macrophage-specific double knockout (MDKO) mice, macrophage-specific Nfatc3 knockin mice (Nfatc3-MKI), and macrophage-specific Ask1 knockin mice (Ask1-MKI).
Read the full summary ↓
Lyz2-Cre mice were used as control. Eight-week-old male Lyz2-Cre, Nfatc3-MKO, Ask1-MKO, and MDKO mice were treated with methionine- and choline-deficient (MCD) diet for 4 weeks. Subsequently, mouse liver tissues were isolated and subjected to RNA sequencing analysis. In addition, mouse bone marrow-derived macrophages (BMDMs) were isolated from Lyz2-Cre, Nfatc3-MKI, and Ask1-MKI mice and were also subjected to RNA sequencing analysis.
This dataset
Open GSE314637 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 GSE314637_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 PRJNA1392352 and SRA study SRP657192. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
Lyz2-Cre ×4 NFATc3-MKO ×4 ASK1-MKO ×4 MDKO ×4 NFATc3-MKI ×3 ASK1-MKI ×3 Control_1 (for NFATc3-MKI) ×1 Control_2 (for NFATc3-MKI) ×1 +4 more

Supports a between-group comparison across 22 samples.

How we read this: 6 replicated groups read from 28 sample titles; they account for 22 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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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.