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Placental gene co-expression networks and mediation analysis identifies pathways and genes associated with birthweight

GSE325907 Homo sapiens (human) RNA-seq (gene expression) 319 samples Submitted 2026/06/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 319 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
319 samples: 319 × Placenta sample X31303Groups 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)
The Developmental Origin of Health and Disease (DOHaD) concept postulates that birthweight (BW), a proxy of the in utero environment shaped by environmental and genetic factors, can impact future health. The placenta plays a key role in fetal growth and metabolic programming, thus essential to BW. However, the mechanisms by which intrauterine environment shapes BW, potentially via placenta, remain largely unknown.
Read the full summary ↓
To investigate the placental contribution to BW, we profiled the placental transcriptome from two large U.S. birth cohorts. We constructed weighted gene co-expression networks (WGCN) from all (N=673), female (N=331) and male (N=342) placentae, and identified 23, 24, and 22 modules, respectively. Pathway enrichment analyses of these networks revealed consistent functional processes related to signal transduction, lysosomes, brain development, immune, and HIF-1 hypoxia pathways. Seven modules were associated with BW in each network, and differential expression analysis within these modules identified 441, 467 and 227 genes in the overall, female, and male networks, respectively. We also identified 14, 12, and 8 genes mediating the impact of WGCN modules on BW, including genes related to oxidative stress (SLC25A27, MCTP1 and CD9), brain development (NFIA and SEMA3D) and maternal-fetal immune tolerance (TLR1 and TLR6). Together, these placenta WGCNs revealed pathways and genes mediating the effect of placental transcriptome on BW offering mechanistic insights, including sex-specific mechanisms, on fetal programing. These findings support DOHaD and improve the understanding of how the intrauterine environment influences BW and later-life traits.
This dataset
Open GSE325907 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 GSE325907_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 PRJNA1442199. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
319 × Placenta sample X31303

Supports a between-group comparison across 319 samples.

How we read this: 1 replicated groups read from 319 sample titles; they account for 319 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

+ 279 more — browse all 319 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.