GEO series

Intragenic DNA methylation modulates alternative splicing by recruiting MeCP2 to promote exon recognition [RNA-Seq]

GSE47488 Homo sapiens (human) DNA methylation 12 samples Submitted 2013/08/13 Platform GPL9115Platform GPL11154

At a glance

DNA methylation · human · 12 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 12 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)

Although the function of DNA methylation in gene promoter regions is well established in transcriptional repression, the function of the evolutionarily conserved widespread distribution of DNA methylation in gene body regions remains incompletely understood. Here, we show that DNA methylation is enriched in included alternatively spliced exons (ASEs) and inhibiting DNA methylation results in aberrant splicing of ASEs.

Read the full summary ↓

The methyl-CpG binding protein MeCP2 is enriched in included ASEs, particularly those that are also highly DNA methylated, and inhibition of DNA methylation disrupts specific targeting of MeCP2 to exons. Interestingly, ablation of MeCP2 results in increased nucleosome acetylation and aberrant skipping events of ASEs. We further show that inhibition of histone deacetylases leads to a highly significant overlap of exon skipping events caused by knocking-down MeCP2. Together, our data indicate that intragenic DNA methylation operates in exon definition to modulate alternative splicing and can enhance exon recognition via recruitment of the multifunctional protein MeCP2, which thereby maintains local histone hypoacetylation through its established interaction with HDACs.

This dataset

Open GSE47488 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 GSE47488_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 PRJNA205857 and SRA study SRP023270. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23938295) ↗

Samples in this study

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+ 12 more — browse all 12 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.