← BioTransfer GEO Dataset Finder
GEO series

Reversible methylation of m6Am in the 5′ cap controls mRNA stability

GSE78040 Homo sapiens (human) DNA methylation 28 samples Submitted 2016/12/21 Platform GPL16791Platform GPL17021
At a glance

DNA methylation · human · 28 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
28 samples: 12 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)
Internal bases in mRNA can be subjected to modifications that influence the fate of mRNA in cells. One of the most prevalent modified bases is found at the 5′ end of mRNA, at the first encoded nucleotide adjacent to the 7-methylguanosine cap. Here we show that this nucleotide, N6,2′-O-dimethyladenosine (m6Am), is a reversible modification that influences cellular mRNA fate.
Read the full summary ↓
Using a transcriptome-wide map of m6Am we find that m6Am-initiated transcripts are markedly more stable than mRNAs that begin with other nucleotides. We show that the enhanced stability of m6Am-initiated transcripts is due to resistance to the mRNA-decapping enzyme DCP2. Moreover, we find that m6Am is selectively demethylated by fat mass and obesity-associated protein (FTO). FTO preferentially demethylates m6Am rather than N6-methyladenosine (m6A), and reduces the stability of m6Am mRNAs. Together, these findings show that the methylation status of m6Am in the 5′ cap is a dynamic and reversible epitranscriptomic modification that determines mRNA stability.
This dataset
Open GSE78040 in finder → Find more 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 GSE78040_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 PRJNA312400 and SRA study SRP070463. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28002401) ↗
Study design
12 conditions, mostly in duplicate
Fto knockout fto_ko ×3 Control for Fto knockout fto_wt ×3 Control for ALKBH5 knockdown ×2 ALKBH5 knockdown ×2 Control for DCP2 knockout ×2 DCP2 knockout ×2 Control for FTO knockdown ×2 FTO knockdown ×2 +6 more

Supports a case/control comparison: 9 samples read as cases, 4 as controls.

How we read this: 12 replicated groups read from 28 sample titles; they account for 26 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

Search all 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.