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Quantitative analysis of small RNA pseudouridylation reveals interplay of PUS enzymes in tRNA anticodon stem-loop

GSE299274 Homo sapiens (human) Single-nucleus RNA-seq 27 samples Submitted 2025/11/27 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 27 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
27 samples: 9 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
Quantitative analysis of small RNA pseudouridylation reveals interplay of PUS enzymes in tRNA anticodon stem-loopNature communications · 2026
Summary (written by the submitters)
Pseudouridine (Ψ) is an abundant modification in small RNA and is catalyzed by multiple pseudouridine synthases (PUSs). However, the substrate specificity of human PUSs are not fully understood. In this study, we adopted PRAISE, a quantitative Ψ detection method, to profile pseudouridylation in small RNA, including cytosolic and mitochondrial tRNAs, snRNA, and snoRNA.
Read the full summary ↓
We found that pseudouridylation of snoRNAs can be mediated not only by RNA-guided DKC1, but also stand-alone enzyme PUS7. Interestingly, we found that several PUS enzymes, which install nearby Ψ sites within tRNA anticodon stem-loop, can influence pseudouridylation level catalyzed by other PUSs. Typical examples include PUS1, RPUSD1, and PUS7, revealing a novel interplay among human PUSs during Ψ formation. For the three RluA family enzymes, we found that in addition to the canonical substrate Ψ30, RPUSD1 also catalyzes Ψ72 of tRNA-Arg isoacceptors. RPUSD2 pseudouridylates Ψ31 of mt-tRNALeu(CUN), and Ψ32 of mt-tRNAPro and mt-tRNACys, and hence is functionally similar to yeast Pus9. RPUSD3 does not modify tRNA at all, consistent with its lack of a catalytic residue. Together, using quantitative Ψ profiling, our study characterized the tRNA substrates of PUS enzymes and revealed unexpected interplay among human PUSs in tRNA pseudouridylation.
Published in
Quantitative analysis of small RNA pseudouridylation reveals interplay of PUS enzymes in tRNA anticodon stem-loop
Liu W, Ma Y, Wang L et al. · Nature communications 2026 · PMID 41698914 · doi:10.1038/s41467-026-69177-7
This dataset
Open GSE299274 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 GSE299274_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1273737 and SRA study SRP590758. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41698914) ↗
Study design
9 conditions, mostly in duplicate
HEK293T, small RNA, PRAISE treated, ×2 HEK293T, DKC1NC, small RNA, PRAISE treated, ×2 HEK293T, DKC1KD, small RNA, PRAISE treated, ×2 HEK293T, PUS1KO, small RNA, PRAISE treated, ×2 HEK293T, RPUSD1KO, small RNA, PRAISE treated, ×2 HEK293T, RPUSD2KO, small RNA, PRAISE treated, ×2 HEK293T, RPUSD3KO, small RNA, PRAISE treated, ×2 HEK293T, PUS7KO, small RNA, PRAISE treated, ×2 +10 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 18 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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