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The stress granule transcriptome reveals principles of mRNA accumulation in stress granules.

GSE99304 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2017/11/10 Platform GPL19756Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × U-2 OS Stress Granule RNA vs 3 × U-2 OS Total RNA vs 3 × Yeast SG RNA vs 3 × Yeast Total RNAGroups are read from the sample names, not from the paper. Check the list below.
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)
Stress granules are mRNA-protein assemblies formed on nontranslating mRNAs. Stress granules are important in the stress response, related to neuronal mRNP granules, and aberrant stress granules contribute to some degenerative diseases. By RNA-Seq and single molecule FISH, we describe the stress granule transcriptome in both yeast and mammalian cells.
Read the full summary ↓
This reveals that while essentially every mRNA, and some ncRNAs, can be targeted to stress granules, the efficiency of targeting can vary from <1% to 73%. mRNA accumulation in stress granules is increased by longer coding regions, poor translatability, and correlates with some RNA binding proteins. Standardizing the RNA-Seq analysis by single molecule FISH allows a quantitative description of the general and stress gra­nule transcriptome. Approximately 15% of the bulk mRNA molecules accumulate in stress granules suggesting their effect will be limited primarily to subsets of mRNAs highly accumulating in stress granules
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 GSE99304_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 PRJNA388080 and SRA study SRP108038. Searching any of these in the dataset finder brings you back here.

Study design
3 × U-2 OS Stress Granule RNA vs 3 × U-2 OS Total RNA vs 3 × Yeast SG RNA vs 3 × Yeast Total RNA

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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