GEO series

Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome

GSE73941 Homo sapiens (human) DNA methylation 24 samples Submitted 2016/02/05 Platform GPL16791

At a glance

DNA methylation · human · 24 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 24 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)

N1-Methyladenosine (m1A) is a prevalent post-transcriptional RNA modification, yet little is known about its abundance, topol- ogy and dynamics in mRNA. Here, we show that m1A is prevalent in Homo sapiens mRNA, which shows an m1A/A ratio of ~0.02%. We develop the m1A-ID-seq technique, based on m1A immunoprecipitation and the inherent ability of m1A to stall reverse tran- scription, as a means for transcriptome-wide m1A profiling.

Read the full summary ↓

m1A-ID-seq identifies 901 m1A peaks (from 600 genes) in mRNA and noncoding RNA and reveals a prominent feature, enrichment in the 5' untranslated region of mRNA transcripts, that is dis- tinct from the pattern for N6-methyladenosine, the most abundant internal mammalian mRNA modification. Moreover, m1A in mRNA is reversible by ALKBH3, a known DNA/RNA demethylase. Lastly, we show that m1A methylation responds dynamically to stimuli, and we identify hundreds of stress-induced m1A sites. Collectively, our approaches allow comprehensive analysis of m1A modification and provide tools for functional studies of potential epigenetic regulation via the reversible and dynamic m1A methylation.

This dataset

Open GSE73941 in finder → Find more human 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 GSE73941_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 PRJNA298568 and SRA study SRP064738. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26863410) ↗

Samples in this study

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+ 24 more — browse all 24 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.