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A Comprehensive Roadmap of the Mammalian Ribo-interactome Connects Metabolism Enzymes with Specialized ER-Ribosomes

GSE96998 Mus musculus (mouse) RNA-seq (gene expression) 6 samples Submitted 2017/06/01 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 6 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
Mus musculus (mouse)
Samples
6 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)
The ribosome has considerably increased in size during metazoan evolution in the form of an RNA shell that could serve as a platform for yet unknown protein interactions. Here, we have comprehensively identified the mammalian ‘ribo-interactome’ by establishing a ribosome affinity purification method. Our findings reveal a multitude of novel ribosome interacting factors, encompassing unanticipated functional categories including energy metabolism, cell redox homeostasis, as well as key protein and RNA modifying enzymes.
Read the full summary ↓
These findings led us to characterize ufmylation, a novel posttranslational modification on ribosomes, and define its substrates. We further show that pyruvate kinase, a key enzyme for stem cell and cancer metabolism, is an RNA binding protein that unexpectedly interacts with specialized sub-pools of ribosomes at the endoplasmic reticulum (ER) and coordinates the localization and translation of ER destined mRNAs. Collectively, these studies uncover that the ribo-interactome imbues a new layer of regulatory potential in translating the genome.
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 GSE96998_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: 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 PRJNA380363 and SRA study SRP102438. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 6 more — browse all 6 samples with per-sample file links →

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