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Assessing the impact of microplastics in inflammatory liver conditions using spatial single cell transcriptomics

GSE294180 Mus musculus (mouse) Single-cell RNA-seq 19 samples Submitted 2026/04/27 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 19 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
19 samples: 5 × Liver_MD vs 5 × Liver_CD_MP vs 5 × Liver_MD_MP vs 4 × Liver_CDGroups 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
Spatial transcriptome mapping identifies Ppara-Anxa2 cross-talk in microplastic-induced hepatotoxicityScience advances · 2026
Summary (written by the submitters)
Recent evidence highlights the multisystem effects of microplastics. We investigated the effect of the most common microplastic, polyethylene, on liver conditions. We included 4 experimental groups of mice; chow diet, chow diet and microplastics, high-fat/fructose/cholesterol diet, high-fat/fructose/cholesterol diet and microplastics. Following tissue collection after treatment, bulk RNA sequencing was carried out to profile transcriptomic activity of each group.
Published in
Spatial transcriptome mapping identifies Ppara-Anxa2 cross-talk in microplastic-induced hepatotoxicity
Jung W, Abushukair H, Patil NY et al. · Science advances 2026 · PMID 42308314 · doi:10.1126/sciadv.aec8681
This dataset
Open GSE294180 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 GSE294180_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1248512 and SRA study SRP577557. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42308314) ↗
Study design
5 × Liver_MD vs 5 × Liver_CD_MP vs 5 × Liver_MD_MP vs 4 × Liver_CD

Supports a between-group comparison across 19 samples.

How we read this: 4 replicated groups read from 19 sample titles; they account for 19 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.