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Activation of the Imprinted Gene Network is a conserved signature of MASLD induced by the early life environment

GSE293127 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2025/04/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Samples
28 samples: 7 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)
Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 30% of the world population. Its prevalence in the pediatric population is increasing, suggesting that the early life environment plays a role in the programming of MASLD. We previously proposed that imprinted genes, defined by their expression from a single parental allele, are strong candidates for driving MASLD in response to early life environmental exposures because of their susceptibility to environmental stress and their roles in liver metabolism.
Read the full summary ↓
In support of this hypothesis, we previously showed that early life exposure to the toxic metal cadmium (Cd) or maternal metabolic syndrome (MetS) induce MASLD in juvenile mice and activate a transcriptional network in the liver enriched for imprinted genes termed the Imprinted Gene Network (IGN). Furthermore, artificial activation of the IGN in cultured hepatocytes or in vivo leads to MASLD-related phenotypes. Here, using publicly available bulk liver RNA-seq datasets, we tested whether early life exposure to other types of environmental stress that program juvenile MASLD also activate the IGN. We demonstrate that diverse types of stressors, including toxic metals, diet, and endocrine disruptors, activate the IGN in the liver. We also developed an in vitro model of toxicant exposure and show that the IGN is activated upon exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in a cell autonomous manner. Overall, our findings confirm the IGN as a conserved mechanism that could be targeted to mitigate the effects of multiple developmental stressors on liver disease.
This dataset
Open GSE293127 in finder → Find more human 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 GSE293127_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 PRJNA1242859 and SRA study SRP573668. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly with about 4 replicates each
HepG2 cells, control H2O ×4 HepG2 cells, CdCl2 ×4 HepG2 cells, control DMSO, ×4 HepG2 cells, TCDD, ×4 HepG2 cells, PFOS, ×4 HepG2 cells, BPA, ×4 HepG2 cells, TBTCl, ×4

Supports a between-group comparison across 28 samples.

How we read this: 7 replicated groups read from 28 sample titles; they account for 28 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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