GEO series

Dissecting RNA Selectivity Mediated by Tandem RNA-Binding Domains

GSE280076 Mus musculus (mouse) RNA-seq (gene expression) 66 samples Submitted 2025/01/31 Platform GPL18573Platform GPL35012Platform GPL19424

At a glance

RNA-seq (gene expression) · mouse · 66 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: 66 samples: 28 conditions, mostly in duplicateGroups 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: Dissecting RNA selectivity mediated by tandem RNA-binding domainsThe Journal of biological chemistry · 2025

Summary (written by the submitters)

RNA-protein interactions are pivotal to proper gene regulation. Many RNA-binding proteins possess multiple RNA-binding domains; however, how these domains interplay to specify and regulate RNA targets remains poorly understood. Here, we investigate three multi-domain proteins, Musashi-1, Musashi-2, and Unkempt, three factors which share a high degree of RNA specificity.

Read the full summary ↓

We use a combination of massively parallel in vitro assays with random or naturally derived RNA sequences and find that individual domains within a protein can have differing affinities, specificities, and spacing preferences. Further, we emphasize that while all three proteins have overlapping motif specificities, non-overlapping sequences may allow for target discrimination. We carry out large scale competition assays between these proteins and determine how individual protein specificities and affinities influence competitive binding. Integration of in vivo binding and regulation with in vitro specificities shows that target selection involves a combination of the protein intrinsic specificities described here, but cellular context is critical to drive these proteins to motifs in specific transcript regions. Finally, evolutionarily conserved RNA regions display evidence of binding multiple RBPs in vivo, and these RNA regions recapitulate this trend with the highest affinity in vitro. We highlight the importance of understanding features of complex RNA-protein interactions and how protein-target discrimination can be established.

Published in

Dissecting RNA selectivity mediated by tandem RNA-binding domains

Harris SE, Hu Y, Bridges K et al. · The Journal of biological chemistry 2025 · PMID 40120682 · doi:10.1016/j.jbc.2025.108435

This dataset

Open GSE280076 in finder → Find more RNA-seq 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 GSE280076_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 PRJNA1176144 and SRA study SRP540215. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40120682) ↗

Study design

28 conditions, mostly in duplicate

20mer_RNA_input ×4 pos_RNA_input ×4 MSI1 RRM1 RBNS, 1000, ×2 MSI1 RRM1 RBNS, 250, ×2 MSI1 RRM1 RBNS, 500, ×2 MSI1 RRM2 RBNS, 1000, ×2 MSI1 RRM2 RBNS, 250, ×2 MSI1 RRM2 RBNS, 500, ×2 +26 more

Supports a between-group comparison across 60 samples.

How we read this: 28 replicated groups read from 66 sample titles; they account for 60 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

GSM8587036 MSI1 RRM1 RBNS, 1000, rep1 MSI1 RRM1 RBNS, 1000,
GSM8587037 MSI1 RRM1 RBNS, 1000, rep2 MSI1 RRM1 RBNS, 1000,
GSM8587038 MSI1 RRM1 RBNS, 250, rep1 MSI1 RRM1 RBNS, 250,
GSM8587039 MSI1 RRM1 RBNS, 250, rep2 MSI1 RRM1 RBNS, 250,
GSM8587040 MSI1 RRM1 RBNS, 500, rep1 MSI1 RRM1 RBNS, 500,
GSM8587041 MSI1 RRM1 RBNS, 500, rep2 MSI1 RRM1 RBNS, 500,
GSM8587042 MSI1 RRM2 RBNS, 1000, rep1 MSI1 RRM2 RBNS, 1000,
GSM8587043 MSI1 RRM2 RBNS, 1000, rep2 MSI1 RRM2 RBNS, 1000,
GSM8587044 MSI1 RRM2 RBNS, 250, rep1 MSI1 RRM2 RBNS, 250,
GSM8587045 MSI1 RRM2 RBNS, 250, rep2 MSI1 RRM2 RBNS, 250,
GSM8587046 MSI1 RRM2 RBNS, 500, rep1 MSI1 RRM2 RBNS, 500,
GSM8587047 MSI1 RRM2 RBNS, 500, rep2 MSI1 RRM2 RBNS, 500,
GSM8587048 20mer_RNA_input_1 20mer_RNA_input
GSM8587049 20mer_RNA_input_2 20mer_RNA_input
GSM8587050 MSI2, RRM1 RBNS, 1000, rep1 MSI2, RRM1 RBNS, 1000,
GSM8587051 MSI2, RRM1 RBNS, 1000, rep2 MSI2, RRM1 RBNS, 1000,
GSM8587052 MSI2, RRM1 RBNS, 250, rep1 MSI2, RRM1 RBNS, 250,
GSM8587053 MSI2, RRM1 RBNS, 250, rep2 MSI2, RRM1 RBNS, 250,
GSM8587054 MSI2, RRM1 RBNS, 500, rep1 MSI2, RRM1 RBNS, 500,
GSM8587055 MSI2, RRM1 RBNS, 500, rep2 MSI2, RRM1 RBNS, 500,
GSM8587056 MSI2, RRM2 RBNS, 1000, rep1 MSI2, RRM2 RBNS, 1000,
GSM8587057 MSI2, RRM2 RBNS, 1000, rep2 MSI2, RRM2 RBNS, 1000,
GSM8587058 MSI2, RRM2 RBNS, 250, rep1 MSI2, RRM2 RBNS, 250,
GSM8587059 MSI2, RRM2 RBNS, 250, rep2 MSI2, RRM2 RBNS, 250,
GSM8587060 MSI2, RRM2 RBNS, 500, rep1 MSI2, RRM2 RBNS, 500,
GSM8587061 MSI2, RRM2 RBNS, 500, rep2 MSI2, RRM2 RBNS, 500,
GSM8587062 20mer_RNA_input_3 20mer_RNA_input
GSM8587063 20mer_RNA_input_4 20mer_RNA_input
GSM8587064 UNK ZnF4-6 RBNS, 1000, rep2
GSM8587065 UNK ZnF4-6 RBNS, 250, rep2
GSM8587066 UNK ZnF4-6 RBNS, 500, rep2
GSM8587067 MSI2 RBNS, 250, rep1 MSI2 RBNS, 250,
GSM8587068 MSI2 RBNS, 250, rep2 MSI2 RBNS, 250,
GSM8587069 MSI2 RBNS, 50, rep1 MSI2 RBNS, 50,
GSM8587070 MSI2 RBNS, 50, rep2 MSI2 RBNS, 50,
GSM8587071 UNK posRBNS, 100, rep1 UNK posRBNS, 100,
GSM8587072 pos_RNA_input_1 pos_RNA_input
GSM8587073 UNK posRBNS, 100, rep2 UNK posRBNS, 100,
GSM8587074 MSI1 posRBNS, 100, rep1 MSI1 posRBNS, 100,
GSM8587075 MSI1 posRBNS, 100, rep2 MSI1 posRBNS, 100,

+ 26 more — browse all 66 samples with per-sample file links →

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