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edu-Ψ-seq Reveals snoRNA-guided mRNA Pseudouridylation that Regulates Protein Synthesis

GSE190820 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/10/18 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 8 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.
Summary (written by the submitters)
Purpose:Pseudouridine (Ψ) is the most abundant RNA epigenetic modification and plays vital roles in various biological processes. However, its biogenesis and functions in mRNAs remain elusive. Method:Here, we developed an approach for enriching Ψ sites with deep sequencing (edu-Ψ-seq), which utilizes both exoribonuclease and restriction endonuclease activity to eliminate other nucleosides or reads without Ψ modifications.
Read the full summary ↓
Results:Using edu-Ψ-seq approach in the dyskerin pseudouridine synthase 1 (DKC1) knockdown cells, we identified that more than 100 pseudouridines could be catalyzed by DKC1 in human mRNAs and non-coding RNAs (ncRNAs). Surprisingly, we discovered, for the first time, 10 pseudouridines in mRNAs might be guided by 11 small nucleolar ncRNAs (snoRNAs). Interestingly, we found that SNORA10 could guide DKC1 protein to induce the pseudouridylation of RPL15 mRNA. Importantly, loss of SNORA10 impaired the protein synthesis of RPL15 and inhibited cell proliferation. Conclusion:Overall, our study not only developed a powerful method for detecting Ψ sites but also uncovered another layer of gene expression regulation that involves crosstalk among snoRNAs, mRNA pseudouridylation and protein synthesis.
This dataset
Open GSE190820 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 GSE190820_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 PRJNA788526 and SRA study SRP350749. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
HEK293T CMC-treated ×2 HEK293T CMC-untreated ×2 HEK293T CMC-treated+Terminator ×2 HCT116 CMC-untreated ×2 HCT116 CMC-untreated knock down DKC1 ×2 HCT116 CMC-treated+Terminator ×2 HCT116 CMC-treated+Terminator knock down DKC1 ×2 HCT116 CMC-treated ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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