Biology subjects

Eyras, E.

Publications and source records attributed to Eyras, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Integrated analysis of ribosomal DNA copy number and methylation using nanopore long-read sequencing

Ribosomal RNA (rRNA) provides the structural and catalytic core of ribosomes and is encoded by ribosomal RNA genes (rDNA) arranged in tandem repeat arrays. rDNA copy number (CN) is highly dynamic, representing a clinically relevant form of structural variation, but its accurate quantification has been challenging due to its highly repetitive and GC-rich nature. Here, we present RICO (Ribosomal DNA Integrated Copy Number and Methylation Analysis), a novel computational pipeline for integrated estimation of rDNA CN and methylation using nanopore long-read sequencing. RICO leverages long sequencing reads that span entire rDNA repeats, mapped to an rDNA-augmented reference genome, and normalizes coverage using an array of single-copy genes. We show that RICO provides accurate rDNA CN estimates in simulated datasets and reproducible measurements across human samples, with strong agreement to short-read sequencing and PCR-based methods. As biological validation, RICO detects a [~]40% reduction in rDNA CN in Atrx-knockout mouse cells, consistent with established effects of ATRX loss on rDNA CN, and captures detected increased total and active rDNA CN in malignant cells from a MYC-driven B-cell lymphoma mouse model, in line with prior psoralen-based chromatin studies. Applying RICO to independent human cohorts, we uncover that individuals with higher total rDNA CN consistently exhibited higher fractions of high-methylated rDNA copies, suggesting a dosage compensation mechanism that potentially maintains a similar number of active rDNA copies across individuals. Together, RICO enables integrated analysis of rDNA CN and methylation state, providing a scalable framework for investigating rDNA regulation across population and disease studies.

bioinformatics↗

bioRxiv2025

ModkitOpt: Systematic optimisation of modkit parameters for accurate nanopore-based RNA modification detection

Despite enabling single-molecule detection of RNA modifications, nanopore direct RNA sequencing lacks standardised approaches for modification site calling. This requires accurately quantifying per-site modification stoichiometry and selecting an appropriate stoichiometry cutoff to classify sites. Here, we show that modkit, the de facto standard tool for estimating modification stoichiometry, is highly sensitive to parameter selection, and its heuristic parameter choice consistently leads to markedly sub-optimal site calling, which is exacerbated in datasets where dorado prediction confidence is heterogeneous. We also demonstrate that the choice of stoichiometry cutoff significantly affects false positive and false negative rates for called sites, leading to divergent biological conclusions. To address both limitations we introduce ModkitOpt, a pipeline that identifies then applies the optimal modkit parameters and stoichiometry cutoff for any modification type given a set of validated sites, producing optimised site calls for any nanopore sequencing dataset. Across multiple modification types and biological contexts, ModkitOpt consistently recovers the precision and recall of called sites, establishing a robust framework for standardised RNA modification stoichiometry estimation and site calling from nanopore direct RNA sequencing. ModkitOpt is available at https://github.com/comprna/modkitopt.

bioinformatics↗

bioRxiv2025

SWARM: A Single-Molecule Workflow for High-Precision Profiling of RNA Modifications

Nanopore direct RNA sequencing promises to decode the epitranscriptome by detecting multiple modifications on individual RNA molecules, but its potential for biological discovery is hampered by high false-positive rates. We present SWARM, an AI-based framework designed to overcome this fundamental limitation. Its key innovation is a crosstalk-aware training strategy that incorporates non-target modifications and orthogonally validated cellular signals, enabling high-precision detection of m6A, pseudouridine ({Psi}), and m5C at single-nucleotide and single-molecule resolution. Using rigorous in vitro and cellular RNA benchmarks, SWARM outperforms existing tools and maintains strong agreement with orthogonal methods. Applying SWARM across mammalian tissues reveals thousands of novel modification sites with confirmed motifs and localisation patterns. Our high-resolution multi-tissue modification map revealed no evidence of widespread m6A-{Psi} interplay in predominant writer contexts, challenging models of a coordinated epitranscriptomic code. We further discovered a previously unrecognised splicing-shaped mode of {Psi} deposition, whereby TRUB1-mediated pseudouridylation preferentially occurs after exon-exon ligation, consistent with local RNA structure stabilisation. SWARM provides a robust, universally applicable tool for epitranscriptome discovery.

bioinformatics↗

bioRxiv2025

Nano-Mod-Amp reveals RNA sequence, structural and cell type specific features of pseudouridylation by PUS7

Pseudouridines are abundant mRNA modifications that can impact splicing, translation, and stability to tune gene expression. PUS7 is one of the major mRNA pseudouridine synthase whose dysregulation leads to neurodevelopmental disorders and cancer, underscoring the critical function of PUS7-dependent pseudouridines. Beyond a short and degenerate consensus sequence, the molecular mechanisms underlying PUS7-mediated pseudouridylation remain unknown. A lack of targeted, high-throughput pseudouridine detection methods limits simultaneous interrogation of PUS7 regulatory features across many experimental conditions. We developed novel Nanopore sequencing tools, including Nano-Mod-Amp, to reveal pseudouridine stoichiometry, its RNA structural context, and dependence on PUS7 levels at specific sites across biological conditions. We identified a novel RNA structural signature that is associated with more efficient mRNA modification by PUS7. Pseudouridines are largely responsive to modulations in PUS7 protein levels, demonstrating the regulatory potential of varying PUS7 levels across cellular conditions. Conversely, PUS7 activity is also regulated in a cell-type specific manner, independent of PUS7 expression levels in a manner consistent with regulation by RNA structure and RNA binding proteins. Together, we developed Nanopore sequencing tools and uncovered new mechanisms of PUS7 regulation with a framework that can be applied to other RNA-modifying enzymes to query the regulation of the epitranscriptome. HighlightsO_LINanopore direct RNA sequencing identifies PUS7-dependent pseudouridines with stoichiometry. C_LIO_LINano-Mod-Amp quantifies PUS7-dependent pseudouridines at hundreds of sites in high-throughput. C_LIO_LIMPRAs define RNA sequence and structural features associated with modification by PUS7. C_LIO_LIIndividual PUS7 target pseudouridines are substoichiometric and poised for regulation. C_LIO_LIPUS7 activity is regulated by cell type in the absence of differences in PUS7 protein levels. C_LI

molecular biology↗

bioRxiv2025

CB1 receptor inhibition in fragile X syndrome mice impacts alternative splicing alterations in hippocampal synaptoneurosomal transcriptome

BackgroundFragile X syndrome (FXS) conveys the most frequent heritable genetic cause of intellectual disability and autism. It is caused by a CGG repeat expansion in FMR1 gene that leads to the loss of fragile X messenger ribonucleoprotein 1 (FMRP). FMRP is highly abundant in synapses, where regulates mRNAs to maintain synaptic plasticity. Treatments under development significantly ameliorate neurological and behavioral landmarks in the mouse model of the disorder, the Fmr1 knockout (FX) mouse. Specifically, previous studies revealed that pharmacological and genetic inhibition of cannabinoid type-1 receptor (CB1R) restored phenotypic traits in FX mice. However, the molecular hallmarks associated with this experimental therapeutic intervention are largely unknown. MethodsFirst, we aimed to evaluate the validity of synaptoneurosomes preparations to investigate specific mRNA modifications at synapses. Afterwards, combining in silico high-throughput analysis and biochemical determinations, we analyzed the hippocampal synaptoneurosomal transcriptome after pharmacological inhibition of CB1R with the specific antagonist/inverse agonist rimonabant in FX male mice ResultsWe verified that synaptoneurosomes provide an accurate representation of synaptic composition and function. Then, we found that rimonabant treatment had a limited impact at gene expression level but produced significant modifications in transcript expression. Indeed, detailed analysis of alternative splicing events revealed a relevant number of events in which splicing was reverted from the FX form to the WT form by the treatment. LimitationsWe demonstrated that rimonabant treatment alters the AS landscape in FX hippocampal synaptoneurosomes; however, further studies are needed to elucidate if other neural components also contribute to the modifications and whether the findings are specific to rimonabant treatment or to CB1R inhibition at synapses. In addition, additional research could be required to clarify whether the changes in AS events could be affected by interindividual variability or technical protocols. ConclusionsWe determined that the AS landscape is modified in FX hippocampal synaptoneurosomes and that these changes are sensitive to rimonabant treatment which could explain the beneficial effects of this experimental therapeutic approach in FXS. Altogether, our results reveal a new level of complexity in the effect of pharmacological treatment to improve symptoms in the context of FXS.

neuroscience↗

bioRxiv2025

Single-molecule multimodal timing of in vivo mRNA synthesis

mRNA synthesis requires extensive pre-mRNA maturation, the organisation of which remains unclear. Here, we directly sequence pre-mRNA without metabolic labelling or amplification to resolve transcription and multimodal pre-mRNA processing at single-molecule resolution. Using poly(A) tail measurement, we distinguish transcriptionally engaged pre-mRNA from polyadenylated transcripts, revealing that splicing is substantially delayed compared to previous estimates. Splicing is rare for at least 10 kb behind elongating RNA polymerase II such that thousands of genes remain largely unspliced during transcription, revising the notion that splicing is predominantly co-transcriptional. Progressive splicing becomes apparent only on polyadenylated transcripts, suggesting that splicing is commonly activated after 3' end formation. Unexpectedly, we find abundant m6A on unspliced pre-mRNA, indicating that a substantial portion of RNA methylation precedes splicing. This m6A methylation is suppressed around exon boundaries, indicating that m6A topology is established prior to exon junction complex deposition. Finally, we demonstrate that 3' end cleavage occurs multiple kilobases behind transcription in coordination with efficient transcription termination, and further highlight recursive 3' end formation across hundreds of genes. Conserved from human cells to mouse tissues, we illustrate a revised timeline for mRNA synthesis wherein cleavage, termination, and m6A deposition occur earlier than, or at least partially decoupled from, the bulk of splicing, reframing the sequence of early mammalian gene expression.

genomics↗

bioRxiv2025

The novel RNA polymerase I transcription inhibitor PMR-116 exploits a critical therapeutic vulnerability in a broad-spectrum of high MYC malignancies.

Ribosome biogenesis (RiBi) is a key determinant of cell growth and proliferation and is highly elevated in cancer due to the activation by oncogenes such as MYC. First-generation RiBi inhibitor CX-5461, while demonstrating clinical potential for cancer treatment, also induces DNA damage through off-target inhibition of TOP2 and potentially other mechanisms, bringing into question RiBi as a target for cancer therapy. In this study, we test second-generation RiBi inhibitor, PMR-116. PMR-116 exhibits improved drug-like properties compared to first-generation RiBi inhibitors and has robust anti-tumour activity in the absence of global DNA damage signalling in a broad range of pre-clinical models of haematologic and solid cancers, particularly in malignancies where MYC is either the driver of disease or is elevated. Thus, our work demonstrates that RiBi is a genuine target for cancer therapy and highlights the potential to exploit a critical therapeutic vulnerability in high-MYC human cancers with dismal therapeutic outcomes. Statement of significanceDespite the development of new cancer therapies, most advanced malignancies remain incurable. We demonstrate that PMR-116, a second-generation RiBi inhibitor, has robust therapeutic efficacy in preclinical models of cancer, offering great promise to treat a broad spectrum of human solid and haematologic malignancies, especially where MYC is a driver.

cancer biology↗

bioRxiv2024

High-Accuracy RNA Integrity Definition for Unbiased Transcriptome Comparisons with INDEGRA

RNA sample integrity variability introduces biases and obscures natural RNA degradation, posing a significant challenge in transcriptomics. To address this, we developed the Direct Transcriptome Integrity (DTI) measure, a universal and robust RNA integrity metric based on nanopore sequencing. By accurately modeling RNA fragmentation, DTI provides a reliable assessment of sample quality. Integrated into the INDEGRA package (freely available at https://github.com/Arnaroo/INDEGRA), we provide tools to correct false discoveries and enable precise differential expression and RNA degradation analyses, even for challenging sample types. INDEGRA software can be used to accurately measure RNA DTI stability metric, isolate biological component of RNA degradation from technical biases, compare biological RNA stability transcriptome-wide and suppress false degradation-induced differential gene expression hits to allow broad comparisons across samples of different quality DTI offers a straightforward and accurate method for assessing RNA degradation, characterizing both overall sample integrity and transcript-specific degradation rates using direct RNA sequencing (DRS) data. Calculated through INDEGRA, DTI reveals inter- and intra-transcript variability in degradation, while INDEGRA separates RNA degradation from mapping inaccuracies, and connects degradation profiles to RNA fragmentation rates. By leveraging INDEGRA, researchers can minimize false differential transcript abundance findings caused by variations in overall sample integrity, while preserving genuine transcript-specific differences in stability and degradation. INDEGRA supports integration with widely used differential transcript abundance tools like DESeq2, limma-voom, and edgeR, enabling seamless analysis pipelines. INDEGRA enhances the accuracy and reliability of RNA quantification in high-throughput data and simplifies comparisons across diverse transcriptomic datasets, including those derived from different tissues, species, or experimental protocols.

bioinformatics↗

bioRxiv2024

The conserved landscape of RNA modifications and transcript diversity across mammalian evolution

Gene expression programs underpin the development of shared phenotypes, yet the importance of transcript complexity in shaping mammalian evolution remains unclear. Here we present a comprehensive long-read direct RNA sequencing atlas of full-length transcripts and their m6A modifications across six tissues (hippocampus, frontal cortex, cerebellum, testes, skeletal muscle, and liver) in five mammals (human, mouse, rat, dog, and cow) and a non-mammalian out-group (chicken). Our analysis reveals that 29% of genes have multiple mammalian-conserved alternative transcripts, with 31% of these genes showing tissue-specific switching of the major transcript isoforms. We uncover extensive conservation of coordinated splicing events, primarily driven by tissue-specific mutually associated exon splicing, particularly in neural tissues and cytoskeletal genes. At the epitranscriptome level, we find that 14.2% of m6A RNA modifications are conserved across mammals, with 39% of analysed genes containing a conserved m6A RNA modification. Our work provides unprecedented insight into the evolution of transcript complexity and the epitranscriptome, highlighting their potential roles in shaping mammalian phenotypic diversity and providing a valuable resource for understanding post-transcriptional regulation across mammalian evolutionary time.

genomics↗

bioRxiv2024

An integrative RNA spliceosomic landscape of pancreatic neuroendocrine tumors unveils novel clinicomolecular associations

Alterations in alternative splicing are emerging as a novel hallmark in cancer biology, offering new insights. However, integrative analyses of splicing are still scarce, particularly in rare cancers such as pancreatic neuroendocrine tumors (PanNETs). These tumors are highly heterogeneous, complicating diagnosis and treatment. This study is the first to comprehensively investigate the RNA splicing landscape in PanNETs, identifying distinct spliceosomic profiles correlated with unique clinical and molecular characteristics. We analyzed RNA-seq data from 174 samples, identifying three distinct spliceosomic groups (SPN1, SPN2, SPN3) with unique clinical and molecular characteristics. SPN1 exhibited intermediate clinical features and specific splicing machinery profile, SPN2 was associated with frequent mutations in MEN1 and DAXX/ATRX genes, and SPN3 showed a prevalence of well-differentiated tumors with distinct splicing patterns. These groups were linked to different clinical outcomes and activated key biological processes like mTOR signaling and hormone secretion pathways. Our findings underscore the significant impact of RNA splicing on PanNET heterogeneity and suggest that detailed splicing profiles could serve as valuable tools for identifying novel biomarkers and therapeutic targets. This study provides crucial insights into PanNET molecular biology and paves the way for personalized therapies based on splicing features.

cancer biology↗

bioRxiv2023

Profiling age and body fluid DNA methylation markers using nanopore adaptive sampling

DNA methylation plays essential roles in regulating physiological processes, from tissue and organ development to gene expression and aging processes and has emerged as a widely used biomarker for the identification of body fluids and age prediction. Currently, methylation markers are targeted independently at specific CpG sites, as part of a multiplexed assay, rather than through a unified assay. Methylation detection is also dependent on divergent methodologies, ranging from enzyme digestion and affinity enrichment to bisulfite treatment, alongside various technologies for high-throughput profiling, including microarray and sequencing. In this pilot study, we test the simultaneous identification of age-associated and body fluid-specific methylation markers using a single technology, nanopore adaptive sampling. This innovative approach enables the profiling of multiple CpG marker sites across entire gene regions from a single sample without the need for specialized DNA preparation or additional biochemical treatments. Our study demonstrates that adaptive sampling achieves sufficient coverage in regions of interest to accurately determine the methylation status, shows a robust consistency with whole-genome bisulfite sequencing data, and corroborates known CpG markers of age and body fluids. Our work also resulted in the identification of new sites strongly correlated with age, suggesting new possible age methylation markers. This study lays the groundwork for the systematic development of nanopore-based methodologies in both age prediction and body fluid identification, highlighting the feasibility and potential of nanopore adaptive sampling while acknowledging the need for further validation and expansion in future research.

genomics↗

bioRxiv2022

Real-time biochemical-free targeted sequencing of RNA species with RISER

The heterogeneous composition of cellular transcriptomes poses a major challenge for detecting weakly expressed RNA classes, as they can be obscured by abundant RNAs. Although biochemical protocols can enrich or deplete specified RNAs, they are time-consuming, expensive and can compromise RNA integrity. Here we introduce RISER, a biochemical-free technology for the real-time enrichment or depletion of RNA classes. RISER performs selective rejection of molecules during direct RNA sequencing by identifying RNA classes directly from nanopore signals with deep learning and communicating with the sequencing hardware in real time. By targeting the dominant messenger and mitochondrial RNA classes for depletion, RISER reduced their respective read counts by more than 85%, resulting in an increase in sequencing depth of up to 93% for long non-coding RNAs. We also applied RISER for the depletion of globin mRNA in whole blood, achieving a decrease in globin reads by more than 90% as well as a significant increase in non-globin reads. Furthermore, using a GPU or a CPU, RISER is faster than GPU-accelerated basecalling and mapping. RISERs modular and retrainable software and intuitive command-line interface allow easy adaptation to other RNA classes. RISER is available at https://github.com/comprna/riser.

bioinformatics↗

bioRxiv2022

Language-Informed Basecalling Architecture for Nanopore Direct RNA Sequencing

Algorithms developed for basecalling Nanopore signals have primarily focused on DNA to date and utilise the raw signal as the only input. However, it is known that messenger RNA (mRNA), which dominates Nanopore direct RNA (dRNA) sequencing libraries, contains specific nucleotide patterns that are implicitly encoded in the Nanopore signals since RNA is always sequenced from the 3 to 5 direction. In this study we present an approach to exploit the sequence biases in mRNA as an additional input to dRNA basecalling. We developed a probabilistic model of mRNA language and propose a modified CTC beam search decoding algorithm to conditionally incorporate the language model during basecalling. Our findings demonstrate that inclusion of mRNA language is able to guide CTC beam search decoding towards the more probable nucleotide sequence. We also propose a time efficient approach to decoding variable length nanopore signals. This work provides the first demonstration of the potential for biological language to inform Nanopore basecalling. Code is available at: https://github.com/comprna/radian.

bioinformatics↗

bioRxiv2022

R2Dtool: Positional interpretation of RNA-centric information in the context of transcriptomic and genomic features

Long-read RNA sequencing enables the mapping of RNA modifications, structures, and protein-interaction sites at the resolution of individual transcript isoforms. To understand the functions of these RNA features, it is critical to analyze them in the context of transcriptomic and genomic annotations, such as open reading frames and splice junctions. To enable this, we have developed R2Dtool, a bioinformatics tool that integrates transcript-mapped information with transcript and genome annotations, allowing for the isoform-resolved analytics and graphical representation of RNA features in their genomic context. We illustrate R2Dtools capability to integrate and expedite RNA feature analysis using epitranscriptomics data. R2Dtool facilitates the comprehensive analysis and interpretation of alternative transcript isoforms. R2Dtool is freely available under the MIT license at: https://github.com/comprna/R2Dtool.

bioinformatics↗

bioRxiv2022

Identification of m6A and m5C RNA modifications at single-molecule resolution from Nanopore sequencing

The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUIs capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.

bioinformatics↗

bioRxiv2022

Diffusional variance-determined stochastic translation efficiency

Full-transcriptome methods have brought versatile power to protein biosynthesis research, but remain difficult to apply for the quantification of absolute protein synthesis rates. Here we propose and, using modified translation complex profiling, confirm co-localisation of ribosomes on messenger(m)RNA resulting from their diffusional dynamics. We demonstrate that these stochastically co-localised ribosomes are linked with the translation initiation rate and provide a robust variable to model and quantify specific protein output from mRNA.

molecular biology↗

bioRxiv2022

A comprehensive single-cell expression atlas of human AML leukemia-initiating cells unravels the contribution of HIF pathway and its therapeutic potential

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML), and is driven by rare therapy-resistant leukemia-initiating stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling keeps cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to AML-LSC function and chemoresistance and is a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we provide a comprehensive single-cell expression atlas (119,000 cells) of AML cells and AML-LSCs in paired diagnostic-relapse samples from risk-stratified patients with AML. The HIF/hypoxia pathway is attenuated in AML-LSCs compared with differentiated AML cells, but is enhanced when compared with healthy hematopoietic cells. Accordingly, chemical inhibition cooperates with standard-of-care chemotherapy to impair leukemogenesis, substantially eliminating AML-LSCs. These findings support the HIF pathway as a stem cell regulator in human AML, and reveal avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs.

cancer biology↗

bioRxiv2021

A convergent malignant phenotype in B-cell acute lymphoblastic leukemia involving the splicing factor SRRM1

A significant proportion of infant B-cell acute lymphoblastic leukemia (B-ALL) patients remains with a dismal prognosis due to yet undetermined mechanisms. We performed a comprehensive multicohort analysis of gene expression, gene fusions, and RNA splicing alterations to uncover molecular signatures potentially linked to the observed poor outcome. We identified 87 fusions with significant allele frequency across patients and shared functional impacts, suggesting common mechanisms across fusions. We further identified a gene expression signature that predicts high risk independently of the gene fusion background and includes the upregulation of the splicing factor SRRM1. Experiments in B-ALL cell lines provided further evidence for the role of SRRM1 on cell survival, proliferation, and invasion. Supplementary analysis revealed that SRRM1 potentially modulates splicing events associated with poor outcomes through protein-protein interactions with other splicing factors. Our findings reveal a potential convergent mechanism of aberrant RNA processing that sustains a malignant phenotype independently of the underlying gene fusion, and that could potentially complement current clinical strategies in infant B-ALL.

cancer biology↗