← BioTransfer GEO Dataset Finder
GEO series

A systematic dissection of determinants and consequences of snoRNA-guided pseudouridylation of human mRNA

GSE159749 Homo sapiens (human) RNA-seq (gene expression) 44 samples Submitted 2024/06/02 Platform GPL18573Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 44 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)
Samples
44 samples: 37 distinct titles, 7 of them repeatedGroups 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 systematic dissection of determinants and consequences of snoRNA-guided pseudouridylation of human mRNANucleic acids research · 2022
Summary (written by the submitters)
RNA can be extensively modified post-transcriptionally with >170 covalent modifications, expanding its functional and structural repertoire. Pseudouridine (Ψ), the most abundant modified nucleoside in rRNA and tRNA, has recently been found within mRNA molecules. Due to technical challenges, it remained unclear whether pseudouridylation of mRNA can be snoRNA-guided, which has important implications for understanding the physiological target spectrum of snoRNAs and for their potential therapeutic exploitation in genetic diseases.
Read the full summary ↓
Here, using a massively parallel reporter based strategy we simultaneously interrogate Ψ levels across hundreds of synthetic constructs with predesigned complementarity against endogenous snoRNAs. Our results demonstrate that snoRNA-mediated pseudouridylation can occur on mRNA targets. However, this is typically achieved at low efficiencies, and is constrained by the localization of mRNA, by the expression levels of snoRNAs and by the length of the snoRNA:mRNA complementarity stretches. We exploited these insights for the design of snoRNAs targeting pseudouridylation at premature termination codons, which was previously suggested to suppress translational termination. However, in contrast to previous studies, in this and follow-up experiments we observe no evidence for readthrough of pseudouridylated stop codons. Our study enhances our understanding of the scope, ‘design rules’ and constraints of snoRNA-mediated pseudouridylation, and challenges a key functional outcome associated with this modification.
Published in
A systematic dissection of determinants and consequences of snoRNA-guided pseudouridylation of human mRNA
Nir R, Hoernes TP, Muramatsu H et al. · Nucleic acids research 2022 · PMID 35536311 · doi:10.1093/nar/gkac347
This dataset
Open GSE159749 in finder → Find more human 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 GSE159749_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 PRJNA670650 and SRA study SRP288148. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35536311) ↗
Study design
37 distinct titles, 7 of them repeated
Exp1_Pol1_CMC ×2 Exp1_Pol1_Input ×2 Exp1_Pol2_CMC ×2 Exp1_Pol2_Input ×2 Exp5_totalRNA_CMC ×2 Exp7_DMDreporter_WTsno61_CMC ×2 Exp7_DMDreporter_sno61Modified_CMC ×2

Supports a case/control comparison: 2 samples read as cases, 7 as controls.

How we read this: Read from 44 sample titles: 37 distinct titles with little repetition. 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

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.