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A RiboCancer cell line panel reveals that CLL-associated Rps15 mutations translationally rewire transcription through codon-specific tRNA accommodation defects

GSE310057 Mus musculus (mouse) RNA-seq (gene expression) 48 samples Submitted 2025/11/18 Platform GPL19057Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 48 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
48 samples: 16 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.
Paper
A RiboCancer cell line panel reveals that CLL-associated Rps15 mutations translationally rewire transcription through codon-specific tRNA accommodation defectsHemaSphere · 2026
Summary (written by the submitters)
Various somatic deletions and point mutations targeting ribosomal proteins (RPs) have been identified in cancer. To assess how these affect ribosomal translation, we applied genomewide translatome analysis (proteome, Ribo-seq and total RNA-seq) on an isogenic cell line library modeling the most recurrent RP defects (Rpl5+/-, Rpl11+/- , Rpl22+/- , Rpl22-/-, Rpl10 R98S, Rps15 P131S and Rps15 H137Y).
Read the full summary ↓
We detected little translational changes in the RP knock-out models. In contrast, RP point mutations were associated with a significant number of translation efficiency changes, reaching up to 10% of expressed genes in Rps15 mutants associated with Chronic Lymphocytic Leukemia (CLL). Further cryo-electron microscopy and biochemical analyses revealed that these Rps15 mutations alter the stability of the C-terminal Rps15 domain, affecting the translation elongation cycle dynamics of these mutant ribosomes, and deregulating accommodation of aminoacylated tRNAs at the ribosomal A-site. Using Ribo-seq and translation reporter assays, we show that this accommodation defect shows codon specificity, explaining the reduced translation efficiency of genes enriched for these codons in Rps15 mutant cells, such as histones. Finally, the genes presenting reduced translation efficiency in Rps15 mutants are enriched for transcriptional regulators such as transcription factor Runx3, resulting in downregulation of Runx3 target genes involved in immune regulation. Overall, this study compares the translational rewiring imposed by the most frequent somatic RP mutations. We provide unprecedented mechanistic insights in the translation defects induced by CLL-associated Rps15 mutations, and reveal an unappreciated cross-talk between translational and transcriptional dysregulation in these RP mutant cells.
Published in
A RiboCancer cell line panel reveals that CLL-associated Rps15 mutations translationally rewire transcription through codon-specific tRNA accommodation defects
Astier A, Caruso M, Vereecke S et al. · HemaSphere 2026 · PMID 42255948 · doi:10.1002/hem3.70377
This dataset
Open GSE310057 in finder → Find more mouse datasets →
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.

Series matrix ↓
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 GSE310057_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1365082 and SRA study SRP644933. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42255948) ↗
Study design
16 conditions, mostly in triplicate
RNAseq Ba/F3 Rpl22 -/- # ×3 RNAseq Ba/F3 Rpl11 +/- # ×3 RNAseq Ba/F3 Rps15 P131S # ×3 RNAseq Ba/F3 Rpl22 +/- # ×3 RNAseq Ba/F3 Rpl5 +/- # ×3 RNAseq Ba/F3 Rpl10 R98S/R98S #A ×3 RNAseq Ba/F3 Rps15 H137Y/H137Y # ×3 RNAseq Ba/F3 WT # ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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