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Transcriptomic implications of low herbicide concentrations in hepatic cells: Insights into the individual and combined effects of 2,4-D, glyphosate, and AMPA

GSE292868 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2025/03/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples
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
Are glyphosate or glyphosate-based herbicides linked to metabolic dysfunction-associated steatotic liver disease (MASLD)? The weight of current evidenceEnvironmental toxicology and pharmacology · 2025
Summary (written by the submitters)
Glyphosate and 2,4-D are among the most widely used herbicides globally, leading to environmental presence, food contamination, and human contact. Investigations based on current toxicological limits or populational-based herbicide exposures are warranted, and in vitro bioassays provide useful tools for toxicological screening. Thus, this study evaluated the transcriptomic implications of non-cytotoxic exposures to glyphosate, its metabolite aminomethylphosphonic acid (AMPA), or 2,4-D - or to their mixes - on hepatic cells.
Read the full summary ↓
The half maximal effective concentration (IC50) of each herbicide was calculated (cell viability) in human hepatic C3A cells and 1000-fold lower concentrations were used for transcriptomic analysis (RNA-Seq) after 48h exposure, resembling current toxicological limits and considering herbicide water levels (glyphosate: 0.95 µg/mL; AMPA: 3.7 µg/mL; 2,4-D: 0.56 µg/mL). Glyphosate exposure enriched MAPK-related biological processes (upregulated TNF, FOS, IGF1, and PDGFB), and downregulated genes associated with lipid metabolism (CD36 and PPARA). Many AMPA exposure-related differentially expressed genes (DEGs, such as PFKFB3, HK2, and ALDOA) were associated with glucose metabolic pathways. Glyphosate and its metabolite yielded a common molecular signature, as illustrated by principal component analysis and the function of 212 shared DEGs. The exposure to 2,4-D was associated with the JNK cascade and the solute carrier family annotations. The herbicide mixtures had a discrete effect on enhancing the impact of individual herbicides, although important epithelial-mesenchymal transition genes were exclusively modified by the mixes (COL11A2, LOXL3, SNAI1). Altogether, our data reveals new perspectives on the short-term molecular effects of herbicide exposure in liver cells, emphasizing potential avenues for further exploration.
Published in
Are glyphosate or glyphosate-based herbicides linked to metabolic dysfunction-associated steatotic liver disease (MASLD)? The weight of current evidence
Riechelmann-Casarin L, Valente LC, Otton R et al. · Environmental toxicology and pharmacology 2025 · PMID 40311787 · doi:10.1016/j.etap.2025.104705
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 GSE292868_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 PRJNA1241787 and SRA study SRP572977. Searching any of these in the dataset finder brings you back here.

Samples in this study

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