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Differential IRES-initiated translation during homeostatic stem cell differentiation and stress

GSE277603 synthetic construct; Mus musculus RNA-seq (gene expression) 36 samples Submitted 2026/04/02 Platform GPL19057Platform GPL15228
At a glance

RNA-seq (gene expression) · synthetic construct; Mus musculus · 36 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
synthetic construct; Mus musculus
Samples
36 samples: 12 conditions, mostly in triplicateGroups 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)
Cell stress commonly induces preferentially reduced m7G-cap-dependent translation initiation while cap-indendepent, IRES-mediated initiation persists. We investigated differential translation initiation in the highly regulated protein production of somatic stem cells by generating a reporter mouse quantifying the ratio of IRES-mediated to cap-dependent translation in vivo.
Read the full summary ↓
Both hematopoietic and epithelial stem cells exhibited minimal IRES utilization that progressively increased with differentiation. Notably, even within defined differentiation states, lower IRES/Cap was associated with increased clonogenicity regardless of cell cycle and among HSCs, with greater long-term multi-lineage regeneration. The RNA binding protein PTBP1 is a key modulator of IRES utilization during differentiation by CRISPR/Cas9i screening. Even within IRES-low immature stem/progenitor cells, nutrient stress upregulated IRES utilization, pointing to distinct roles of IRES in cell behavior depending on physiologic state.
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 GSE277603_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 PRJNA1162885 and SRA study SRP533643. Searching any of these in the dataset finder brings you back here.

Study design
12 conditions, mostly in triplicate
Low IRES,Cap SLAM-LKS ×3 Mid IRES,Cap SLAM-LKS ×3 High IRES,Cap SLAM-LKS ×3 Low IRES,Cap GMP ×3 Mid IRES,Cap GMP ×3 High IRES,Cap GMP ×3 Low IRES,Cap MEP ×3 Mid IRES,Cap MEP ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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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