GEO series

N6-methyladenosine Recruits HNRNPG for Alternative Splicing Regulation

GSE74085 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2017/03/09 Platform GPL11154

At a glance

RNA-seq (gene expression) · human · 22 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Homo sapiens (human)
Samples: 22 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)

Understanding how RNA-binding proteins interact with RNA transcripts for splicing regulation is fundamental to human biology and disease. N6-methyladenosine (m6A), the most abundant and dynamic internal modification of eukaryotic messenger RNA (mRNA), is important for RNA splicing, but its detailed mechanism remains unclear. We find the splicing factor heterogeneous nuclear ribonucleoprotein G (HNRNPG) selectively binds m6A-modified RNA in vitro and in vivo.

Read the full summary ↓

Transcriptome-wide identification of HNRNPG binding sites reveals the binding sequence specificity of HNRNPG (AGRAC, R=A/G), which embeds the m6A consensus motif. The m6A methylation makes the binding sequence more accessible to facilitate HNRNPG binding. In total, we identify 13,191 high-confidence m6A sites recruiting HNRNPG in HEK293T cells. Furthermore, m6A writers depletion decreases HNRNPG binding at m6A sites, and consequently cause alternative splicing changes similar as HNRNPG depletion on the m6A-containing RNA transcripts. These findings indicate that m6A RNA methylation facilitates HNRNPG binding to regulate mRNA alternative splicing.

This dataset

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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 GSE74085_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA298926 and SRA study SRP064870. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28334903) ↗

Samples in this study

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+ 22 more — browse all 22 samples with per-sample file links →

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