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Maternal microRNAs Linked To Birth Deficits Due To Prenatal Alcohol Exposure Are Dominant Modifiers of Gene Expression in Invasive Trophoblast Cells

GSE324021 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/05/19 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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)
Prenatal alcohol exposure (PAE) can impair placental development and result in fetal growth restriction. However, the underlying molecular mechanisms are unclear. We previously found that PAE in some, but not all pregnancies, resulted in significantly elevated circulating levels of 11 microRNAs (HEamiRNAs) in the 2nd trimester.
Read the full summary ↓
This subgroup of PAE women experienced adverse infant birth outcomes due to PAE, Subsequently, these HEamiRNAs collectively but not individually, were found to inhibit a defined set of placental epithelial-mesenchymal transition (EMT) genes and, inhibited invasiveness of placental trophoblast cells. Here we extend these findings by performing whole-transcriptome analysis to dissect the contribution of ethanol compared to HEamiRNAs in HTR-8/SVneo cells, a model for invasive, human extravillous trophoblasts. We observed a large, distinct and statistically dominant effect of HEamiRNAs mimics on trophoblast transcript profiles irrespective of ethanol exposure, specifically on EMT, extracellular matrix, angiogenesis and immune signaling pathways among others. Weighted gene co-expression network analysis (WGCNA) identified additional placental growth networks related to epithelial cell proliferation and differentiation and MAPK/PI3K, Hippo and Rap1 signaling. This study provides a mechanistic framework to explain that the effects of PAE vary across pregnancies, because they are contingent in part, on the elevation key maternal circulating miRNAs.
This dataset
Open GSE324021 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 GSE324021_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 PRJNA1432989 and SRA study SRP681359. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
PRE_EtOHpos_miRmimics ×3 POST_EtOHpos_miRCtrl ×3 POST_EtOHpos_miRmimics ×3 EtOHneg_miRCtrl ×3 EtOHneg_miRmimics ×3 PRE_EtOHpos_miRCtrl ×2 PRE_EtOHpos_miCtrl ×1

Supports a between-group comparison across 17 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 17 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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