GEO series

Nodal/Smad2 signaling sustains developmental pausing by repressing Pparg -mediated lipid metabolism [RNA-Seq]

GSE303716 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/06/22 Platform GPL34328

At a glance

RNA-seq (gene expression) · mouse · 24 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: Mus musculus (mouse)
Samples: 24 samples: 6 conditions, mostly with about 4 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)

Cells and organisms can enter transient dormant states to survive unfavorable conditions during development, physiological adult states and disease. One paradigmatic case of dormancy is diapause, whereby embryos transiently pause development and enter a state of suspended animation. In mammals, diapause occurs pre-implantation at the blastocyst state and involves global growth suppression and metabolic rewiring towards lipid usage as energy source.

Read the full summary ↓

The molecular regulation of diapause remains poorly understood, including whether it occurs by default or requires active signaling. Here, we identify the canonical TGF-β signaling pathway as an essential driver of transcriptional and metabolic reprogramming in diapause. TGF-β signaling was thought to only be required post-implantation, but we show that the ligand Nodal and its downstream effector Smad2 are essential for the survival of paused embryonic stem cells (ESCs) and blastocysts. Mechanistically, we found that Smad2 represses a Pparg, a transcription factor that is a master regulator of lipid storage, a process incompatible with pausing. Ablation of Pparg in Smad2-deficient ESCs rescues their survival and prevents excess lipid buildup in pausing conditions. These findings establish Nodal/Smad2 signaling as pivotal for sustaining embryonic diapause and suggest that the crosstalk between TGF-β signaling and the Pparg pathway may be broadly relevant for metabolic rewiring in dormancy contexts.

This dataset

Open GSE303716 in finder → Find more mouse 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 GSE303716_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 PRJNA1297148 and SRA study SRP603737. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly with about 4 replicates each

RNA, Ctrl, WT, ×4 RNA, Ctrl, Smad2_KO1, ×4 RNA, Ctrl, Smad2_KO2, ×4 RNA, Paused, WT, ×4 RNA, Paused, Smad2_KO1, ×4 RNA, Paused, Smad2_KO2, ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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

GSM9134534 RNA, Ctrl, WT, rep 1 RNA, Ctrl, WT,
GSM9134535 RNA, Ctrl, WT, rep 2 RNA, Ctrl, WT,
GSM9134536 RNA, Ctrl, WT, rep 3 RNA, Ctrl, WT,
GSM9134537 RNA, Ctrl, WT, rep 4 RNA, Ctrl, WT,
GSM9134538 RNA, Ctrl, Smad2_KO1, rep 1 RNA, Ctrl, Smad2_KO1,
GSM9134539 RNA, Ctrl, Smad2_KO1, rep 2 RNA, Ctrl, Smad2_KO1,
GSM9134540 RNA, Ctrl, Smad2_KO1, rep 3 RNA, Ctrl, Smad2_KO1,
GSM9134541 RNA, Ctrl, Smad2_KO1, rep 4 RNA, Ctrl, Smad2_KO1,
GSM9134542 RNA, Ctrl, Smad2_KO2, rep 1 RNA, Ctrl, Smad2_KO2,
GSM9134543 RNA, Ctrl, Smad2_KO2, rep 2 RNA, Ctrl, Smad2_KO2,
GSM9134544 RNA, Ctrl, Smad2_KO2, rep 3 RNA, Ctrl, Smad2_KO2,
GSM9134545 RNA, Ctrl, Smad2_KO2, rep 4 RNA, Ctrl, Smad2_KO2,
GSM9134546 RNA, Paused, WT, rep 1 RNA, Paused, WT,
GSM9134547 RNA, Paused, WT, rep 2 RNA, Paused, WT,
GSM9134548 RNA, Paused, WT, rep 3 RNA, Paused, WT,
GSM9134549 RNA, Paused, WT, rep 4 RNA, Paused, WT,
GSM9134550 RNA, Paused, Smad2_KO1, rep 1 RNA, Paused, Smad2_KO1,
GSM9134551 RNA, Paused, Smad2_KO1, rep 2 RNA, Paused, Smad2_KO1,
GSM9134552 RNA, Paused, Smad2_KO1, rep 3 RNA, Paused, Smad2_KO1,
GSM9134553 RNA, Paused, Smad2_KO1, rep 4 RNA, Paused, Smad2_KO1,
GSM9134554 RNA, Paused, Smad2_KO2, rep 1 RNA, Paused, Smad2_KO2,
GSM9134555 RNA, Paused, Smad2_KO2, rep 2 RNA, Paused, Smad2_KO2,
GSM9134556 RNA, Paused, Smad2_KO2, rep 3 RNA, Paused, Smad2_KO2,
GSM9134557 RNA, Paused, Smad2_KO2, rep 4 RNA, Paused, Smad2_KO2,

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