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Melatonin modulates inflammasome and antioxidant signaling in trophoblasts and decidual macrophages

GSE313629 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/06/03 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 36 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
36 samples: 8 conditions, mostly with about 5 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)
This study investigates how melatonin regulates inflammatory and oxidative stress pathways at the maternal–fetal interface. We profiled transcriptomic responses in JEG-3 trophoblast-like cells and primary human decidual macrophages treated with melatonin at different doses. Cells were exposed to vehicle, 1 nM, or 1000 nM melatonin under defined inflammatory conditions.
Read the full summary ↓
RNA-seq libraries were prepared using a strand-specific poly(A)-selected protocol and sequenced on a BGISEQ platform. Differential expression and pathway analyses focused on inflammasome and NRF2-related pathways. These data support a role for melatonin in modulating redox–inflammatory balance in placenta-relevant cell types.
This dataset
Open GSE313629 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 GSE313629_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 PRJNA1380434 and SRA study SRP654851. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly with about 5 replicates each
JEG-3_No_Treatment ×5 JEG-3_Vehicle ×5 JEG-3_MEL_1nM ×5 JEG-3_MEL_1000nM ×5 Decidual_Macro_No_Treatment ×4 Decidual_Macro_Vehicle ×4 Decidual_Macro_MEL_1nM ×4 Decidual_Macro_MEL_1000nM ×4

Supports a between-group comparison across 36 samples.

How we read this: 8 replicated groups read from 36 sample titles; they account for 36 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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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.