GEO series

MicroRNA Network Regulation of Developmental Bone Toxicity in a Human Embryonic Stem Cell Osteogenic Model [RNA-Seq]

GSE324491 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2026/05/31 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 30 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: 30 samples: 30 samples, each with a distinct title — no replicated groupsGroups 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)

Developmental exposure to environmental toxicants is a cause of skeletal abnormalities. Yet the molecular mechanisms linking early exposure to impaired bone formation remain undefined. Skeletal tissues arise from both neural crest- and mesoderm-derived lineages that rely on shared osteogenic differentiation programs, suggesting that disruption of common regulatory processes may contribute to diverse skeletal outcomes.

Read the full summary ↓

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene networks and have appeared as indicators of toxicant-induced perturbation. In this study, we examined whether developmentally relevant toxicants are associated with miRNA regulatory networks during osteogenic differentiation. Using a human embryonic stem cell (hESC)-based osteogenic differentiation model, we assessed the effects of nine toxicants spanning distinct primary mechanisms. Toxicant exposure impaired osteogenic differentiation at their IC50, as reflected by altered expression of osteogenic markers and transcriptional remodeling. Global miRNA profiling revealed dysregulation of miRNAs enriched for bone-related biological processes, including regulators of osteogenic commitment and differentiation timing. Integrated miRNA–mRNA network analysis identified a subset of miRNAs linked to core osteogenic and lineage-associated pathways, including RUNX2-dependent transcription and BMP and Wnt signaling. Modulation of representative miRNAs produced osteogenic outcomes consistent with those observed following toxicant exposure and, in some cases, was associated with partial restoration of differentiation in exposed cultures. Collectively, these findings indicate that chemically diverse developmental toxicants are associated with miRNA-mediated regulatory patterns during osteogenic differentiation. Identification of conserved miRNA signatures provides mechanistic insight into developmental bone toxicity and supports the use of miRNA network analysis as a human-relevant endpoint for skeletal hazard identification.

This dataset

Open GSE324491 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 GSE324491_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 PRJNA1435452 and SRA study SRP682711. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

30 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 30 sample titles: 30 distinct titles with little repetition. 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

GSM9578582 UNT replicate 1 RNA-seq
GSM9578583 UNT replicate 2 RNA-seq
GSM9578584 UNT replicate 3 RNA-seq
GSM9578585 5FU replicate 1 RNA-seq
GSM9578586 5FU replicate 2 RNA-seq
GSM9578587 5FU replicate 3 RNA-seq
GSM9578588 CPA replicate 1 RNA-seq
GSM9578589 CPA replicate 2 RNA-seq
GSM9578590 CPA replicate 3 RNA-seq
GSM9578591 CYCLO replicate 1 RNA-seq
GSM9578592 CYCLO replicate 2 RNA-seq
GSM9578593 CYCLO replicate 3 RNA-seq
GSM9578594 H2O2 replicate 1 RNA-seq
GSM9578595 H2O2 replicate 2 RNA-seq
GSM9578596 H2O2 replicate 3 RNA-seq
GSM9578597 MAA replicate 1 RNA-seq
GSM9578598 MAA replicate 2 RNA-seq
GSM9578599 MAA replicate 3 RNA-seq
GSM9578600 MENOL replicate 1 RNA-seq
GSM9578601 MENOL replicate 2 RNA-seq
GSM9578602 MENOL replicate 3 RNA-seq
GSM9578603 MTX replicate 1 RNA-seq
GSM9578604 MTX replicate 2 RNA-seq
GSM9578605 MTX replicate 3 RNA-seq
GSM9578606 OGM replicate 1 RNA-seq
GSM9578607 OGM replicate 2 RNA-seq
GSM9578608 OGM replicate 3 RNA-seq
GSM9578609 VPA replicate 1 RNA-seq
GSM9578610 VPA replicate 2 RNA-seq
GSM9578611 VPA replicate 3 RNA-seq

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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.