GEO series

The proteomic landscape and temporal dynamics of human and mouse gastruloid development

GSE273813 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2024/09/06 Platform GPL30172Platform GPL30173

At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Mus musculus (mouse)
Samples: 18 samples: 9 conditions, mostly in duplicateGroups 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.
Paper: The proteomic landscape and temporal dynamics of human and mouse gastruloid developmentNature cell biology · 2026

Summary (written by the submitters)

Gastrulation is the highly coordinated process by which the early embryo breaks symmetry, establishes germ layers and a body plan, and sets the stage for organogenesis. As early mammalian development is challenging to study in vivo, stem cell-derived models have emerged as powerful surrogates, e.g. human and mouse gastruloids. However, although single cell RNA-seq (scRNA-seq) and high-resolution imaging have been extensively applied to characterize such in vitro embryo models, a paucity of measurements of protein dynamics and regulation leaves a major gap in our understanding.

Read the full summary ↓

Here we sought to address this by applying quantitative proteomics to human and mouse gastruloids at four key stages of their differentiation (naïve ESCs, primed ESCs, early gastruloids, late gastruloids). To the resulting data, we perform network analysis to map the dynamics of expression of macromolecular protein complexes and biochemical pathways, including identifying cooperative proteins that associate with them. With matched RNA-seq and phosphosite data from these same stages, we investigate pathway-, stage- and species-specific aspects of translational and post-translational regulation, e.g. finding peri-gastrulation stages of human vs. mice to be discordant with respect to the mitochondrial transcriptome vs. proteome, and nominating novel kinase-substrate relationships based on phosphosite dynamics. Finally, we leverage correlated dynamics to identify conserved protein networks centered around congenital disease genes. Altogether, our study showcases the potential of intersecting proteomics and in vitro embryo models to advance our understanding of early mammalian development in ways that may not be possible through transcriptomics alone.

Published in

The proteomic landscape and temporal dynamics of human and mouse gastruloid development

Garge RK, Lynch V, Fields R et al. · Nature cell biology 2026 · PMID 42032312 · doi:10.1038/s41556-026-01937-5

This dataset

Open GSE273813 in finder → Find more 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 GSE273813_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1143402 and SRA study SRP523874. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42032312) ↗

Study design

9 conditions, mostly in duplicate

Naive H9 ESCs, ×2 Primed H9 ESCs, ×2 Primed RUES2_GLR ESCs, ×2 Early RA-gastruloid, ×2 Late RA-gastruloid, ×2 Naive mESCs, ×2 Primed EpiLCs, ×2 Early gastruloid, ×2 +1 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 18 sample titles; they account for 18 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

GSM8437515 Naive H9 ESCs, replicate 1 Naive H9 ESCs,
GSM8437516 Naive H9 ESCs, replicate 2 Naive H9 ESCs,
GSM8437517 Primed H9 ESCs, replicate 1 Primed H9 ESCs,
GSM8437518 Primed H9 ESCs, replicate 2 Primed H9 ESCs,
GSM8437519 Primed RUES2_GLR ESCs, replicate 1 Primed RUES2_GLR ESCs,
GSM8437520 Primed RUES2_GLR ESCs, replicate 2 Primed RUES2_GLR ESCs,
GSM8437521 Early RA-gastruloid, replicate 1 Early RA-gastruloid,
GSM8437522 Early RA-gastruloid, replicate 2 Early RA-gastruloid,
GSM8437523 Late RA-gastruloid, replicate 1 Late RA-gastruloid,
GSM8437524 Late RA-gastruloid, replicate 2 Late RA-gastruloid,
GSM8437525 Naive mESCs, replicate 1 Naive mESCs,
GSM8437526 Naive mESCs, replicate 2 Naive mESCs,
GSM8437527 Primed EpiLCs, replicate 1 Primed EpiLCs,
GSM8437528 Primed EpiLCs, replicate 2 Primed EpiLCs,
GSM8437529 Early gastruloid, replicate 1 Early gastruloid,
GSM8437530 Early gastruloid, replicate 2 Early gastruloid,
GSM8437531 Late gastruloid, replicate 1 Late gastruloid,
GSM8437532 Late gastruloid, replicate 2 Late gastruloid,

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