Biology subjects

Faucher-Giguere, L.

Publications and source records attributed to Faucher-Giguere, L..

4 recordsLinked to original sources

bioRxiv2026

Nanopore Direct RNA Sequencing Enables Reproducible, Site-Resolved Pseudouridine Quantification in Human Ribosomal RNA

Pseudouridine is the most abundant post-transcriptional modification in human ribosomal RNA, with over 110 annotated sites and variable stoichiometry across biological contexts. Existing quantification methods are low-throughput or constrained to predefined panels. We benchmarked nanopore direct RNA sequencing using the Dorado v5.1 model against mass spectrometry-validated sites in human liver tissue, induced pluripotent stem cells, and HeLa cells. Nanopore sequencing detected 95 of 117 validated sites and accurately quantified stoichiometry at 85% of sites with high reproducibility. Low GC-content environments were the primary source of failure. These results establish nanopore sequencing as a scalable tool for epitranscriptomic pseudouridine profiling.

biochemistry↗

bioRxiv2026

snoFlake: A network model for snoRNA-RBP complexes reveals SNORD22 as a U5 snRNP-associated splicing regulator

Small nucleolar RNAs (snoRNAs) are canonically viewed as stable components of ribonucleoprotein complexes dedicated to RNA modification. Here, we developed snoFlake, a snoRNA-centric interaction network integrating physical and functional associations between box C/D snoRNAs and RNA-binding proteins (RBPs), challenging this narrow view. Using snoFlake, we systematically identified snoRNAs predicted to form noncanonical complexes with diverse RBPs, extending their roles into post-transcriptional regulation. We found 23 high-confidence network motifs enriched for RNA-processing functions, including a top-ranked module linking SNORD22 to U5 snRNP components PRPF8 and EFTUD2. SNORD22 co-binds with these spliceosomal RBPs at splice sites showing reduced U5 snRNP occupancy, suggesting a role in reinforcing spliceosomal engagement at suboptimal exons. Consistently, SNORD22 depletion promotes exclusion of weak cassette exons, altering transcript isoform composition and predicted coding output. Beyond SNORD22, snoFlake reveals snoRNAs with similar network profiles, providing a resource for uncovering previously uncharacterized snoRNA-RBP complexes and expanding the functional snoRNome.

bioinformatics↗

bioRxiv2025

SnoBIRD: A tool to identify C/D box snoRNAs and refine their annotation across all eukaryotes

Small nucleolar RNAs (snoRNAs), a group of noncoding RNAs present amongst all eukaryotes, are most extensively characterized for their regulation of ribosome biogenesis and splicing. Despite their central roles, current snoRNA annotations remain incomplete. Several eukaryote genome annotations contain few or no snoRNAs, and none distinguish expressed snoRNAs from their pseudogenes--a recently characterized snoRNA subclass with distinct features and expression levels. To address this, we developed SnoBIRD, a BERT-based C/D box snoRNA predictor trained on snoRNAs spanning all eukaryote kingdoms. We show that SnoBIRD outperforms existing tools and is the only predictor capable of identifying snoRNA pseudogenes using biologically relevant signal. Applied on the fission yeast and human genomes, we demonstrate that only SnoBIRD scales well with genome size in terms of runtime, and we identify and experimentally validate several new SnoBIRD-predicted C/D box snoRNAs. By running SnoBIRD on multiple eukaryote genomes, we identify hundreds of novel snoRNA candidates and highlight SnoBIRDs usefulness to determine the evolutionary paths of snoRNAs distributed across different species. Overall, SnoBIRD represents a user-friendly and efficient tool for reliably predicting C/D box snoRNAs and their pseudogenes across any eukaryote genome. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/646650v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@99b390org.highwire.dtl.DTLVardef@dbe375org.highwire.dtl.DTLVardef@32358aorg.highwire.dtl.DTLVardef@58fb3a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

High-grade Ovarian Cancer Associated H/ACA snoRNAs Promote Cancer Cell Proliferation and Survival

Small nucleolar RNAs (snoRNAs) are an omnipresent class of non-coding RNAs involved in the modification and processing of ribosomal RNA (rRNA). As snoRNAs are required for ribosome production, the increase of which is a hallmark of cancer development, their expression would be expected to increase in proliferating cancer cells. However, the nature and extent of snoRNAs contribution to the biology of cancer cells remain largely unexplored. In this study, we examined the abundance patterns of snoRNA in high-grade serous ovarian carcinomas (HGSC) and serous borderline tumours (SBT) and identified a subset of snoRNA associated with increased invasiveness. This subgroup of snoRNA accurately discriminates between SBT and HGSC underlining their potential as biomarkers of tumour aggressiveness. Remarkably, knockdown of HGSC-associated H/ACA snoRNAs, but not their host genes, inhibits cell proliferation and induces apoptosis of model ovarian cancer cell lines. Wound healing and cell migration assays confirmed the requirement of these HGSC-associated snoRNA for cell invasion and increased tumour aggressiveness. Together our data indicate that H/ACA snoRNAs promote tumour aggressiveness through the induction of cell proliferation and resistance to apoptosis.

cancer biology↗