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NSun2-mediated cytosine-5 methylation in Vault non-coding RNA determines its processing into small RNAs [RNA-seq]

GSE44384 Homo sapiens (human) DNA methylation 8 samples Submitted 2013/07/23 Platform GPL9115
At a glance

DNA methylation · human · 8 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
8 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)
Autosomal-recessive loss of the NSUN2 gene has been recently identified as a causative link to intellectual disability disorders in humans. NSun2 is an RNA methyltransferase modifying cytosine-5 in transfer RNAs (tRNA). Whether NSun2 methylates additional RNA species is currently debated. Here, we adapted the individual-nucleotide resolution UV cross-linking and immunoprecipitation method (iCLIP) to identify NSun2-mediated methylation in RNA transcriptome.
Read the full summary ↓
We confirm site-specific methylation in tRNA and identify messenger and non-coding RNAs as potential methylation targets for NSun2. Using RNA bisulfite sequencing we establish Vault non-coding RNAs as novel substrates for NSun2 and identified six cytosine-5 methylated sites. Furthermore, we show that loss of cytosine-5 methylation in Vault RNAs causes aberrant processing into argonaute-associating small RNA fragments (svRNA). Thus, impaired Vault non-coding RNA processing may be an important contributor to the etiology of NSUN2-deficieny human disorders.
This dataset
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.

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 GSE44384_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA189716 and SRA study SRP018786. Searching any of these in the dataset finder brings you back here.

Samples in this study

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