Translational Control of Splicing Factors Directs Hematopoietic Stem Cell Fate [RNA-Seq]
RNA-seq (gene expression) · mouse · 8 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
- 8 samples: 4 × Control vs 4 × Sf1_5UTR_delGroups 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.
- Paper
- Translational Regulation of Sf1 Integrates Alternative Splicing and Hematopoietic Stem Cell FateBlood · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE294393_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1249375 and SRA study SRP577761. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 2 replicated groups read from 8 sample titles; they account for 8 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.
- GSM8903845 Control_rep1 Control
- GSM8903846 Sf1_5UTR_del_rep1 Sf1_5UTR_del
- GSM8903847 Control_rep2 Control
- GSM8903848 Sf1_5UTR_del_rep2 Sf1_5UTR_del
- GSM8903849 Control_rep3 Control
- GSM8903850 Sf1_5UTR_del_rep3 Sf1_5UTR_del
- GSM8903851 Control_rep4 Control
- GSM8903852 Sf1_5UTR_del_rep4 Sf1_5UTR_del
- GSE266509 A Bcl11a-driven mechanism maintaining hematopoietic stem cell functionality gives rise to dysfunction during aging [RNA-Seq] 52 samples shares hematopoietic, rna-seq, stem
- GSE306116 Caspase-3 Control of RNA Splicing and Mitochondrial Dynamics in Microglia during Parkinson’s Disease [RNA-Seq] 12 samples shares splicing, control, rna-seq
- GSE302791 Targeted CRISPR-Cas9 screening identifies core transcription factors controlling murine haemato-endothelial fate commitment [RNA-seq] 12 samples shares control, factors, rna-seq
- GSE222941 Endomucin marks quiescent long-term multi-lineage repopulating hematopoietic stem cells and is essential for their transendothelial migration [RNA-seq: wildtype_EMCN] 11 samples shares hematopoietic, rna-seq, stem
- GSE277443 EMP1 preserves hematopoietic stem cell potential under homeostasis and radiation-induced injury by alleviating ER stress [ER-stress RNA-seq] 10 samples shares hematopoietic, rna-seq, stem
- GSE282096 Diminished transcriptional activity and splicing changes drive gene length-biased rewiring in the aging transcriptome (RNA-Seq) 94 samples shares splicing, rna-seq
- GSE276628 Reciprocal genetic screens identify epigenetics factors controlling epidermal cell activation. [RNAseq_MiniBulk] 41 samples shares control, factors
- GSE325832 RNA-seq analysis of skeletal muscle from control (Cre) and Terf2 knockout (KO) mice in gastrocnemius-plantaris-soleus (GPS) and tibialis anterior (TA) 35 samples shares control, rna-seq
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.