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Metabolite-driven remodeling of hepatic lipid metabolism by the plasticizer di-isononyl phthalate

GSE313258 Mus musculus (mouse) RNA-seq (gene expression) 54 samples Submitted 2026/06/30 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 54 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
54 samples: 14 × CONTROL vs 14 × 150 vs 13 × 1.5 vs 13 × 15Groups 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)
Phthalates are widely used as plasticizers and solvents in common consumer products and are suspected to be metabolism-disrupting chemicals (MDCs). Di-isononyl phthalate (DINP) is a commonly used phthalate, which has been shown to induce liver damage, but the mechanisms and human relevance remain unclear. The effects of DINP on hepatic lipid metabolism were studied using a diet-induced obesity model of C56BL/6J male mice.
Read the full summary ↓
The mice were orally exposed to 0, 1.5, 15 or 150 mg/kg bw/d DINP for 20 weeks next to a high-fat diet (HFD) with 45% calories from fat (Research Diets D12451), followed by assessment of the liver transcriptome.
This dataset
Open GSE313258 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 GSE313258_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 PRJNA1378853 and SRA study SRP654093. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 × CONTROL vs 14 × 150 vs 13 × 1.5 vs 13 × 15

Supports a between-group comparison across 54 samples.

How we read this: 4 replicated groups read from 54 sample titles; they account for 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.