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A Universal 6iL/E4 Culture System for Deriving and Maintaining Embryonic Stem Cells Across Mammalian Species

GSE325170 Homo sapiens (human) Single-cell RNA-seq 2 samples Submitted 2026/06/02 Platform GPL34290Platform GPL34284
At a glance

Single-cell RNA-seq · human · 2 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
Homo sapiens (human)
Samples
2 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 derivation of authentic embryonic stem cells (ESCs) across mammalian species remains a major challenge. Here, we report the development of a defined, serum-free culture system, termed 6iL/E4, that enables the derivation and long-term self-renewal of ESCs across diverse mammalian species. To further characterize the cellular states, we performed single-cell RNA sequencing (scRNA-seq) on 6iL-hiPSCs and 6iL-mESCs.
Read the full summary ↓
Library preparation was carried out using the Single Cell 3′ RNA Prep T2 kit (Illumina). For indexing, the Mix 7 index set was used for 6iL-hiPSC samples and the Mix 8 index set for 6iL-mESC samples. Sequencing was performed on a NovaSeq X Plus platform using paired-end 150 bp reads (2 × 150 bp), generating approximately 200 million reads per sample (100 million reads per direction).
This dataset
Open GSE325170 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 GSE325170_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 PRJNA1438756 and SRA study SRP684578. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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