Biology subjects

Deschamps-Francoeur, G.

Publications and source records attributed to Deschamps-Francoeur, G..

6 recordsLinked to original sources

bioRxiv2026

A ribosomal pseudouridine drives an oncogenic translation program

Dynamic ribosome heterogeneity has emerged as a potential layer of translational regulation, but whether variation in ribosomal RNA (rRNA) modification stoichiometry can selectively control the translation of mRNAs with shared encoded features remains unclear. Here we show that SNORA81-guided pseudouridylation at U4636 controls a selective translational program in ovarian cancer cells. U4636 is partially pseudouridylated and lies within 28S rRNA near eL31 and the peptide exit tunnel. Depletion of SNORA81 reduces pseudouridylation at U4636 without broadly perturbing rRNA processing or bulk translation. Instead, it remodels codon-specific and nascent-peptide-associated pausing and the polysome association of SNORA81-dependent translationally altered mRNAs. These mRNAs display characteristic GC content and amino-acid composition, are enriched in cancer-related functions and show corresponding changes in protein levels. Our findings support a model in which a change in the abundance of a single snoRNA propagates from rRNA-modification stoichiometry through ribosome dynamics and selective mRNA translation to protein output and cancer cell proliferation. We term this multilevel amplification cascade the "sno-balling" effect.

cancer biology↗

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↗

bioRxiv2026

Comparative profiling of SARS-CoV-2 variant infections reveals diverse impacts on host cell RNA and RNA binding protein distribution and regulation

RNA viruses perturb cellular RNA metabolism to promote viral transcript expression and genome replication. However, the extent of host cell RNA reprogramming and the consequences on RNA binding protein (RBP) expression and localization remain poorly understood. Here, we utilized an integrated set of transcriptomics, proteomics, and high-content imaging approaches to compare the impact of different SARS-CoV-2 variants, including an early viral isolate and later emerging variants of concern (Alpha, Delta and Omicron) on the host cellular RNA and RBP landscapes. While all variants deeply remodelled the host transcriptome in a subcellular compartment-specific manner, we found that Omicron variants express lower levels of viral RNA products compared to earlier variants, while still driving efficient production of viral proteins. The surge in viral RNA expression correlated with altered subcellular RNA biotype distribution, cytoplasmic mRNA exclusion, the selective disruption of the localization of polyA-tail interacting proteins, and the nuclear accumulation of non-coding transcripts such as RN7SL family members and MALAT-1. Unexpectedly, we found many RBPs that exhibiting altered subcellular localization following abiotic innate immune stimulation with poly(I:C) but remained unaltered in cells infected with SARS-CoV-2 variants, revealing a capacity for these viruses to limit the overall impact on the RBP subcellular distribution. Our results further indicate that Omicron infection sustains higher expression levels of proteins components of the signal recognition particle and translation factors, which may enable a more effective production of immune response and viral components. Altogether, this work highlights the deep impact of SARS-CoV-2 infection on host cell RNA regulatory landscape and provides new insights to explain the differential impact of Omicron compared to early SARS-CoV-2 variants. HighlightsO_LISARS-CoV-2 variants drive varying degrees of viral RNA expression in infected Calu-3 cells C_LIO_LIInfection reshapes the host cell RNA landscape in a cell-compartment specific manner C_LIO_LIRN7SL RNA exhibits a strong increase in relative abundance and accumulates in the nucleus of infected cells C_LIO_LISARS-CoV-2 infections impact the localization of polyA-tail binding proteins while blocking the nuclear accumulation of immune response-sensitive RBPs C_LIO_LIOmicron infections are less disruptive to cellular function and sustain the production of translation factors and components of the SRP complex C_LI

molecular biology↗

bioRxiv2021

The snoGloBe interaction predictor enables a broader study of box C/D snoRNA functions and mechanisms

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.

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↗

bioRxiv2018

CoCo: RNA-seq Read Assignment Correction for Nested Genes and Multimapped Reads

MotivationNext generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage.\n\nResultsHere we present CoCo, a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bed-graph comparisons.\n\nAvailabilityThe CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/coco.\n\nContactmichelle.scott@usherbrooke.ca

bioinformatics↗