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Transfer RNA (tRNA) processing and RNA m5C-methylation profiles of mouse skin squamous tumours

GSE72065 Mus musculus (mouse) DNA methylation 16 samples Submitted 2016/06/16 Platform GPL9250
At a glance

DNA methylation · mouse · 16 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
16 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)
Purpose: High-throughput RNA sequencing has accelerated discovery of the complex regulatory roles of small RNAs, such those derived from tRNAs. Also recent advances in high-throughput RNA sequencing has revealed the complex RNA modification landscape and the complex role these nucleosides modifactions have in cell signalling, stem cell biology, development and cancer.
Read the full summary ↓
The goal of this study is to establish how m5C-tRNA methylation and tRNA-derived small RNAs can affect stem cell fucntion in cancer. Methods: four replicates of tRNAs and RNA buisulphite sequencing of wild-type (WT) and NSun2 -/- mouse skin squamous tumours were generated by deep sequencing, using Illumina HiSeq platform. Results: Our analyses reveal that inhibition of post-transcriptional cytosine-5 methylation locks stem cells in this distinct translational inhibition programme that results in tumour progression but that also sentizes cancer cells to genotoxic stress.
This dataset
Open GSE72065 in finder → Find more mouse methylation 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 GSE72065_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 PRJNA292863 and SRA study SRP062408. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27306184) ↗
Samples in this study

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+ 16 more — browse all 16 samples with per-sample file links →

Datasets on a similar topic

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