GEO series

Trancriptome-wide mapping of TET2-regulated m5C sites in mouse embryonic stem cells (mESCs)

GSE138534 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/09/21 Platform GPL13112Platform GPL21626

At a glance

RNA-seq (gene expression) · mouse · 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: Mus musculus (mouse)
Samples: 18 samples: 6 conditions, mostly in duplicateGroups 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)

We mapped the transcriptome-wide distribution of m5C sites, which are under the regulation TET2, using immunoprecipitation with specific anti-5mC antibodies followed by next-generation high-throughput sequencing in Tet2 KO mESCs in comparison to wild-type mESCs. Our data revealed that TET2-mediated m5C modifications primarily localize in 3’UTR of mRNA. Moreover, transcripts containing TET2-regulated m5C sites are stabilized with longer lifetime in Tet2 deficiency mESCs, indicated by the lifetime-seq.

This dataset

Open GSE138534 in finder → Find more mouse 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 GSE138534_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 PRJNA576264 and SRA study SRP224667. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in duplicate

m5CIP-seq WT ×2 input WT ×2 m5CIP-seq Tet2KO ×2 input Tet2KO ×2 BS-seq mESC WT ×2 BS-seq mESC Tet2KO ×2 RNA-seq WT 0h ×1 RNA-seq WT 3h ×1 +4 more

Supports a between-group comparison across 12 samples.

How we read this: 6 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

GSM4110761 m5CIP-seq WT rep1 m5CIP-seq WT
GSM4110762 m5CIP-seq WT rep2 m5CIP-seq WT
GSM4110763 input WT rep1 input WT
GSM4110764 input WT rep2 input WT
GSM4110765 m5CIP-seq Tet2KO rep1 m5CIP-seq Tet2KO
GSM4110766 m5CIP-seq Tet2KO rep2 m5CIP-seq Tet2KO
GSM4110767 input Tet2KO rep1 input Tet2KO
GSM4110768 input Tet2KO rep2 input Tet2KO
GSM4110769 RNA-seq WT 0h
GSM4110770 RNA-seq WT 3h
GSM4110771 RNA-seq WT 6h
GSM4110772 RNA-seq Tet2KO 0h
GSM4110773 RNA-seq Tet2KO 3h
GSM4110774 RNA-seq Tet2KO 6h
GSM4851394 BS-seq mESC WT rep1 BS-seq mESC WT
GSM4851395 BS-seq mESC WT rep2 BS-seq mESC WT
GSM4851396 BS-seq mESC Tet2KO rep1 BS-seq mESC Tet2KO
GSM4851397 BS-seq mESC Tet2KO rep2 BS-seq mESC Tet2KO

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Search all mouse RNA-seq datasets in GEO →

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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.