GEO series

Resetting Transcription Factor Control Circuitry Towards Ground State Pluripotency In Human

GSE60945 Homo sapiens (human) DNA methylation 6 samples Submitted 2014/09/10 Platform GPL15433

At a glance

DNA methylation · human · 6 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 6 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)

Current human pluripotent stem cells lack the transcription factor circuitry that governs the ground state of mouse embryonic stem cells (ESC). Here we report that short-term expression of two components, NANOG and KLF2, is sufficient to ignite other elements of the network and reset the human pluripotent state. Inhibition of ERK and protein kinase C signalling sustains a transgene-independent rewired state.

Read the full summary ↓

Reset cells self-renew continuously without ERK signalling, are phenotypically stable and karyotypically intact. They differentiate in vitro and form teratomas in vivo. Metabolism is reprogrammed in reset cells with activation of mitochondrial respiration as in ESC. DNA methylation is dramatically reduced and transcriptome state is globally realigned across multiple cell lines. Depletion of ground state transcription factors, TFCP2L1 or KLF4 has marginal impact on conventional human pluripotent stem cells, but collapses the reset state. These findings demonstrate feasibility of installing and propagating functional control circuitry for ground state pluripotency in human cells.

This dataset

Open GSE60945 in finder → Find more human methylation 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 GSE60945_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA259876 and SRA study SRP045902. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25215486) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 6 more — browse all 6 samples with per-sample file links →

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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.