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Leveraging dynamic cell responses to design new protocols for pluripotency maintenance

GSE298835 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2026/06/09 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 21 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
Mus musculus (mouse)
Samples
21 samples: 7 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)
Pluripotent stem cells have a high potential for research and development applications in biomedicine. They are unspecialized cells that can be indefinitely expanded retaining pluripotency or pushed into specific differentiated states by proper stimuli. Various protocols have been proposed to maintain mouse embryonic stem cells (mESCs) in the pluripotent state; state of the art cell culture protocols are based on serum-free media, and continuous provision of drugs inhibiting pathways associated to differentiation.
Read the full summary ↓
We explore here the possibility to avoid continuous drug exposure. First, we employ an external feedback control microfluidics/microscopy platform to steer the expression of a pluripotency reporter. Control experiments show a significant delay in cell response to drugs; these dynamics are confirmed by flow-cytometry open-loop experiments. We then harness such delays to design novel culture protocols with limited cell exposure to small-molecule inhibitors; in so doing, we reduce cell exposure to drug, but we maintain pluripotency. Our results suggest new approaches to design cell culture protocols based on the quantitative analysis and control of cellular dynamics.
This dataset
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.

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 GSE298835_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1271470 and SRA study SRP589563. Searching any of these in the dataset finder brings you back here.

Study design
7 conditions, mostly in triplicate
mESCs, 2i+LIF PO, ×3 mESCs, 2i+LIF LP, ×3 mESCs, CH+LIF LP, ×3 mESCs, LIF LP, ×3 mESCs, 2i+LIF HP, ×3 mESCs, CH+LIF HP, ×3 mESCs, LIF HP, ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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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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.