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SRSF2 mutations impair hematopoiesis and alter exon recognition

GSE65349 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2015/05/12 Platform GPL11154Platform GPL13112
At a glance

RNA-seq (gene expression) · human · 14 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)
Topic
Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples
14 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)
Mutations within genes encoding spliceosomal proteins are the most common class of mutations in patients with myelodysplastic syndromes, yet it is currently not well understood how these mutations impact hematopoiesis or RNA splicing. Here we report that mutations affecting the splicing factor SRSF2 alter its normal RNA recognition activity, resulting in impaired hematopoietic differentiation and myelodysplasia.
Read the full summary ↓
Commonly occurring SRSF2 mutations impaired wildtype SRSF2’s normal RNA-binding avidity and preference for specific exonic splicing enhancer RNA motifs. Integration of murine and human transcriptome data identified recurrent mis-splicing of key transcriptional regulators in the presence of mutant SRSF2, including promotion of a highly conserved “poison” exon of EZH2 that results in nonsense-mediated decay and contributes to impaired hematopoiesis. These data provide a mechanistic basis for the enrichment of specific mutations in spliceosomal proteins in myelodysplasia, and suggest that altered RNA recognition activity is a novel mechanism of leukemogenesis.
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 GSE65349_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 PRJNA273749 and SRA study SRP052874. Searching any of these in the dataset finder brings you back here.

Samples in this study

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