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A developmental coordinate of the spectrum of pluripotency among mice, monkeys, and humans

GSE74767 Macaca fascicularis; Mus musculus Single-cell RNA-seq 492 samples Submitted 2016/08/24 Platform GPL19944Platform GPL15907
At a glance

Single-cell RNA-seq · Macaca fascicularis; Mus musculus · 492 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
Macaca fascicularis; Mus musculus
Samples
492 samples
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 epiblast (EPI) is the origin of all somatic and germ cells in mammals, and of the spectrum of pluripotent stem cells (PSCs) in vitro. To explore the ontogeny of human/primate pluripotency, we performed comprehensive single-cell RNA sequencing for pre- and post-implantation EPI development in cynomolgus monkeys. Here we show that after specification in the blastocysts [embryonic day (E)7], cyEPI undergoes major transcriptome changes upon implantation.
Read the full summary ↓
Thereafter, cyEPI, while generating gastrulating cells (~E13), maintains its transcriptome relatively stably over a week, retaining a unique set of pluripotency genes while acquiring properties for “neuron differentiation.” h/cyPSCs show the highest similarity to post-implantation late cyEPI (~E17), which, despite co-existing with gastrulating cells, bears characteristics of pre-gastrulating mouse EPI (E5.5) and epiblast-like cells (EpiLCs) in vitro. These findings not only reveal divergence/coherence of EPI development, but also identify a developmental coordinate of the spectrum of pluripotency among key species, providing a basis for better regulation of human pluripotency in vitro.
This dataset
Open GSE74767 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 GSE74767_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 PRJNA301445 and SRA study SRP065899. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27556940) ↗
Samples in this study

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+ 492 more — browse all 492 samples with per-sample file links →

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