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Multi omics reveals mesodermal fate bias and enables predictive cell state control in human pluripotent stem cell biomanufacturing

GSE331399 Homo sapiens (human) RNA-seq (gene expression) 41 samples Submitted 2026/05/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 41 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
41 samples: 13 conditions, mostly in triplicateGroups 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)
Despite accelerating interest in using human induced pluripotent stem cell (hiPSC)–derived products for disease modeling and therapeutic development, there is substantial evidence that conventional culture approaches do not fully recapitulate natural embryonic nor lineage committed states. It remains poorly understood how in vitro environmental conditions cause divergence from natural developmental trajectories, and current strategies emphasize restricted characterization of phenotype without appreciating the complexity of biology in maintaining pluripotency and driving differentiation.
Read the full summary ↓
To address this knowledge gap, we examined hiPSC cell state during short term culture in stirred suspension bioprocesses under varying oxygen and agitation conditions. We profiled intracellular metabolic, transcriptional, and proteomic changes to characterize cellular responses to engineered environments and implications for cell phenotype. Using a random forest framework, we modeled population dynamics over time across metabolic and transcriptional programs and mapped those predictions onto hallmark biological signatures. This integrative approach captures and identifies environmentally reinforced programs, offering a framework to guide optimization of pluripotent cell state maintenance and differentiation.
This dataset
Open GSE331399 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 GSE331399_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 PRJNA1468064 and SRA study SRP701991. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 conditions, mostly in triplicate
PGPC14 iPSC, Effective Day 0 Control ×5 PGPC14 iPSC, Day 2, Hypoxia, 100 RPM, Sample ×3 PGPC14 iPSC, Day 4, Hypoxia, 100 RPM, Sample ×3 PGPC14 iPSC, Day 2, Hypoxia, 120 RPM, Sample ×3 PGPC14 iPSC, Day 4, Hypoxia, 120 RPM, Sample ×3 PGPC14 iPSC, Day 2, Hypoxia, 150 RPM, Sample ×3 PGPC14 iPSC, Day 4, Hypoxia, 150 RPM, Sample ×3 PGPC14 iPSC, Day 2, Normoxia, 100 RPM, Sample ×3 +6 more

Supports a between-group comparison across 40 samples.

How we read this: 13 replicated groups read from 41 sample titles; they account for 40 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

+ 1 more — browse all 41 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.