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Identification and quantification of gene isoforms during the differentiation of human embryonic stem cells into pharyngeal endoderm and primordial germ cell-like cells

GSE265988 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/02/17 Platform GPL28975Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 3 × ESC, Illumina, vs 3 × DE, Illumina, vs 3 × PE, Illumina, vs 3 × PGC, Illumina,Groups 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
Improving gene isoform quantification with miniQuantNature biotechnology · 2026
Summary (written by the submitters)
Long-read RNA-seq is now widely applied for gene isoform identification and efforts to long-read RNA-seq for gene isoform quantification are emerging. We develop a software named miniQuant to quantify gene isoforms using long reads alone or in combination with short reads. We demonstrate the utility of miniQuant by its application in uncovering the expression dynamics of gene isoforms during the differentiation of human embryonic stem cells (ESC) into pharyngeal endoderm (PE) and primordial germ cell-like cells (PGC).
Published in
Improving gene isoform quantification with miniQuant
Li H, Wang D, Gao Q et al. · Nature biotechnology 2026 · PMID 40461779 · doi:10.1038/s41587-025-02633-9
This dataset
Open GSE265988 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 GSE265988_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 PRJNA1105096 and SRA study SRP504249. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40461779) ↗
Study design
3 × ESC, Illumina, vs 3 × DE, Illumina, vs 3 × PE, Illumina, vs 3 × PGC, Illumina,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 18 sample titles; they account for 12 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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