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Cancer associated SF3B1 hotspot mutations induce cryptic 3' splice site selection through use of a different branch point

GSE72790 Mus musculus (mouse) RNA-seq (gene expression) 72 samples Submitted 2015/09/08 Platform GPL11154Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 72 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
72 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)
Recurrent mutations in the spliceosome are observed in several human cancers but their functional and therapeutic significance remain elusive. SF3B1, the most frequently mutated component of the spliceosome in cancer, is involved in the recognition of the branch point sequence (BPS) during selection of the 3’ splice site (ss) in RNA splicing.
Read the full summary ↓
Here, we report that common and tumor-specific splicing aberrations are induced by SF3B1 mutations and establish aberrant 3’ ss selection as the most frequent splicing defect. Strikingly, mutant SF3B1 utilizes a BPS that differs from that used by wild-type SF3B1 and requires the canonical 3’ ss to enable aberrant splicing during the second step. Approximately 50% of the aberrantly spliced mRNAs are subjected to nonsense-mediated decay resulting in downregulation of gene and protein expression. These findings ascribe functional significance to the consequences of SF3B1 mutations in cancer.
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 GSE72790_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 PRJNA295064 and SRA study SRP063493. Searching any of these in the dataset finder brings you back here.

Samples in this study

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