Gene expression in primed, coculture with mouse ESC, coculture-derived naïve-like state, and chemically reset (cR) naïve human H9 ESCs.
RNA-seq (gene expression) · human · 12 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
- 12 samples: 3 × H9, primed hESC, vs 3 × H9, hESC cocultured with mESC, vs 3 × H9, coculture-derived converted hESC, vs 3 × H9, cR hESC,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
- Intercellular mRNA transfer alters the human pluripotent stem cell stateProceedings of the National Academy of Sciences of the United States of America · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE272112_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1135136 and SRA study SRP519607. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 replicated groups read from 12 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.
- GSM8393395 H9, primed hESC, bio rep 1 H9, primed hESC,
- GSM8393396 H9, primed hESC, bio rep 2 H9, primed hESC,
- GSM8393397 H9, primed hESC, bio rep 3 H9, primed hESC,
- GSM8393398 H9, hESC cocultured with mESC, bio rep 1 H9, hESC cocultured wit…
- GSM8393399 H9, hESC cocultured with mESC, bio rep 2 H9, hESC cocultured wit…
- GSM8393400 H9, hESC cocultured with mESC, bio rep 3 H9, hESC cocultured wit…
- GSM8393401 H9, coculture-derived converted hESC, bio rep 1 H9, coculture-derived c…
- GSM8393402 H9, coculture-derived converted hESC, bio rep 2 H9, coculture-derived c…
- GSM8393403 H9, coculture-derived converted hESC, bio rep 3 H9, coculture-derived c…
- GSM8393404 H9, cR hESC, bio rep 1 H9, cR hESC,
- GSM8393405 H9, cR hESC, bio rep 2 H9, cR hESC,
- GSM8393406 H9, cR hESC, bio rep 3 H9, cR hESC,
- GSE238256 Rapid and synchronous chemical induction of replicative-like senescence via a small molecule inhibitor 51 samples shares esc, ve-like
- GSE255685 Age-related transcriptomic differences in peripheral blood of adolescents with major depressive disorder 279 samples shares esc
- GSE284666 SenCat: Redefining human cell senescence through multiomic profiling of multiple senescent cell types 190 samples shares esc
- GSE324210 Exercise Training Attenuates the Monocyte Transcriptome Response to Acute Exercise in Adolescents: Evidence for Sex-Specific Molecular Adaptations 83 samples shares esc
- GSE202805 Global Transcriptomic analysis of PBMC derived from COVID-19 acute-severe patients and convalescents 80 samples shares esc
- GSE240377 Distinct functions of wild-type and mutant Δ133p53α R273H differentially regulate glioblastoma aggressiveness and therapy-induced senescence 72 samples shares esc
- GSE317512 Age-stratified transcriptomic profiling reveals biologically distinct molecular phenotypes across pediatric, adolescent, and adult osteosarcoma 70 samples shares esc
- GSE297352 Defective RNA processing and ELOA-mediated transcriptional elongation in reversible cellular senescence suggest aging by transcription 58 samples shares esc
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.