GEO series

SUMO2 Regulates Histone Pre-mRNA Processing by Stabilizing Histone Locus Body Interactions and Promoting U7 snRNP Assembly

GSE292809 Homo sapiens (human) Single-nucleus RNA-seq 12 samples Submitted 2025/03/29 Platform GPL16791

At a glance

Single-nucleus RNA-seq · human · 12 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: 12 samples
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: SUMO2 promotes histone pre-mRNA processing by stabilizing histone locus body interactions and facilitating U7 snRNP assemblyGenes & development · 2025

Summary (written by the submitters)

Histone mRNAs are the only non-polyadenylated mRNAs in eukaryotic cells and require specialized processing in nuclear organelles known as histone locus bodies (HLBs), where essential processing factors are concentrated, including the U7 snRNP complex. Recent studies have revealed that misregulation of histone pre-mRNA processing can lead to polyadenylation of histone mRNAs and disruption of histone protein homeostasis.

Read the full summary ↓

Despite the links to human disease, the factors contributing to polyadenylation of histone mRNAs and the mechanisms underlying HLB assembly and U7 snRNP biogenesis remain unclear. Here, we report novel functions of the small ubiquitin-related modifier 2 (SUMO2) in regulating histone pre-mRNA processing. Using a SUMO2 knockout osteosarcoma cell line, we identified a defect in 3’ end cleavage and a global increase in histone mRNA polyadenylation. Subsequent analysis of HLBs revealed increased dynamics and reduced levels of the U7 snRNP complex. By over-expressing U7 snRNP-specific components, Lsm11 and U7 snRNA, we partially rescued U7 snRNP levels and processing defects in SUMO2 knockout cells. Through analysis of Lsm11, we identified a SUMO-interacting motif in its N-terminus required for efficient incorporation into U7 snRNP complexes. Collectively, we demonstrate that SUMO2 promotes histone pre-mRNA 3’ end processing through stabilizing HLB interactions and facilitating U7 snRNP assembly

Published in

SUMO2 promotes histone pre-mRNA processing by stabilizing histone locus body interactions and facilitating U7 snRNP assembly

He S, Lyu P, Skinner MW et al. · Genes & development 2025 · PMID 40639911 · doi:10.1101/gad.352728.125

This dataset

Open GSE292809 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 GSE292809_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 PRJNA1241289 and SRA study SRP572765. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40639911) ↗

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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