henhaobio
Sign in

bioRxivMolecular BiologyPreprint

snoCLASH Reveals Extensive snoRNA-mRNA Interaction Networks

Brittany A. ElliottiD, Gene Yang, Alex K. Choi, Yinzhou ZhuiD, Wesley R. Freeman, Christopher L. HolleyiD

PDFDOI
Citations
1

Abstract

Small nucleolar RNAs (snoRNAs) are classically defined as guides for modification of ribosomal RNA (rRNA) and small nuclear RNA (snRNA), yet increasing evidence suggests that box C/D snoRNAs also interact with non-canonical transcripts. Systematic discovery of such interactions has been hindered by overwhelming rRNA abundance and technical limitations in RNA-RNA capture. Here, we present snoCLASH, an optimized snoRNA:RNA binding protein (RBP)-based crosslinking, ligation, and sequencing framework that integrates phenol-toluol extraction, polyA enrichment, nuclear fractionation, rRNA depletion, and dual-reference chimeric read analysis to enable transcriptome-scale identification of snoRNA-non-rRNA interactions. Applying this approach reveals thousands of snoRNA-associated mRNA regions spanning coding and regulatory elements and enriched for RBPs linked to epitranscriptomic regulation. Using this framework, we identify high-confidence snoRNA-mRNA interactions and functionally validate OGA mRNA as a snoCLASH-discovered target undergoes snoRNA-dependent 2-O-methylation with downstream effects on protein expression. Together, this work establishes snoCLASH as a platform for discovering and validating non-canonical snoRNA targets beyond rRNA. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=56 SRC="FIGDIR/small/693487v2_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@13d9a4corg.highwire.dtl.DTLVardef@15d12fdorg.highwire.dtl.DTLVardef@189ac06org.highwire.dtl.DTLVardef@17ceeea_HPS_FORMAT_FIGEXP M_FIG C_FIG

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSong '25Gumienny '16Dunn-Davies '21Deschamps-F '22Song '26Soulé '20
69% semantic matchGenomics
Zhuoyi Song, Bongmin Bae, S. Schnabl+7 more·Genome biology·Feb 25, 2025· 13 citations