Biology subjects

Llovera, L.

Publications and source records attributed to Llovera, L..

11 recordsLinked to original sources

bioRxiv2026

Single-molecule m6A profiling reveals position-dependent mRNA regulation and non-canonical roles for Ythdf2 in early embryogenesis

The maternal-to-zygotic transition (MZT) requires coordinated clearance and deadenylation of maternally deposited mRNAs, yet the underlying molecular mechanisms remain poorly understood. N6-methyladenosine (m6A) has emerged as a key regulator of maternal mRNA fate, but prior studies have relied on population-averaged short-read methods that cannot resolve modification state, poly(A) tail length, or isoform identity on the same molecule. Here, we employ nanopore direct RNA sequencing on zebrafish embryos across MZT to resolve the interplay between m6A deposition, mRNA clearance, and poly(A) tail length dynamics at single-molecule resolution. We find that 78% of expressed maternal genes harbor m6A-modified isoforms, significantly exceeding prior bulk estimates. Within-isoform comparisons demonstrate that m6A promotes mRNA decay, with CDS m6A contributing more to maternal mRNA clearance than 3-UTR m6A. The positional context of m6A alone is sufficient to determine the temporal regulation of poly(A) tail lengths. CDS m6A constitutively suppresses tail length throughout MZT, while 3'-UTR m6A acquires shortening activity only after zygotic genome activation (ZGA). Transcriptomic analysis of ythdf2 knockout embryos reveals two unrecognized roles. Ythdf2 stabilizes m6A-marked maternal transcripts to set stoichiometry at MZT onset, and is also responsible for maintaining global poly(A) tail homeostasis prior to ZGA through an m6A-independent mechanism. Together, these findings define the single-molecule logic by which m6A modifications shape transcript fate during vertebrate MZT.

developmental biology↗

bioRxiv2026

AMaNITA: an end-to-end workflow for native tRNA nanopore sequencing data analysis

Transfer RNA (tRNA) molecules serve as essential adapters during protein translation. While direct RNA sequencing (DRS) via Oxford Nanopore Technologies has emerged as a powerful platform for systematic tRNAome profiling, we currently lack a simple and robust statistical framework for nanopore tRNA data analyses. Here, we address this gap by developing AMaNITA (Abundance, Modifications, and Nanopore Intensity Toolbox Application), an end-to-end bioinformatic workflow that enables simplified, robust, and scalable analyses of nanopore native tRNA sequencing datasets. AMaNITA streamlines the entire analytical trajectory: from upstream processing (basecalling, mapping, filtering, batch effect correction) to downstream assessment of differential tRNA abundance and modification stoichiometry. The workflow generates an interactive HTML report for data exploration and analysis, allowing the user to download the source data files and resulting plots. AMaNITA can be executed using Singularity from the command line, without requiring installation of dependencies.

bioinformatics↗

bioRxiv2026

Host tRNA modifications drive efficient translation of influenza A virus genome and impact host antiviral stress responses

Influenza A virus (IAV), as all other viruses, is completely dependent on the host translation machinery components, including host transfer RNAs (tRNAs), to effectively decode its genome. However, while the human genome is biased towards cytosine (C) and guanosine (G)-ending codons, the IAV genome is skewed towards adenine (A) and uridine (U)-ending codons. Nevertheless, translation of IAVs RNA genome is highly efficient. Here we show that host tRNA and tRNA epitranscriptome dynamics are important regulators of IAV RNA translation and host antiviral responses. We show that the levels of several tRNA modifications, including 5-methylcarboxymethyluridine (mcm5U34) and 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U34), and their cognate writers, vary over the course of IAV infection. Additionally, we demonstrate that a set of tRNAs are preferentially recruited to ribosomes upon IAV infection, in line with IAV codon usage requirements. We further show that loss of ELP3, the catalytic subunit of the elongator complex, which is involved in the catalysis of mcm5U34 and of mcm5s2U34, induces tRNA hypomodifications, impairs translation of codon biased IAV genes and triggers the integrated stress response (ISR), interfering with IAV propagation. Taken together, our results uncover the relevance of host tRNAs and their modifications for optimal expression of viral genomes and host antiviral responses, setting the tRNA epitranscriptome as a promising target for the development of host-based antiviral therapies.

molecular biology↗

bioRxiv2026

Selective profiling of translationally active tRNAs and their dynamics under stress

During translation, transfer RNAs (tRNAs) deliver specific amino acids to the ribosome in a coordinated manner with the sequence encoded by the mRNA. Despite their central role in protein synthesis, their precise contribution to the modulation of translation remains poorly understood, primarily due to lack of methods to characterise tRNA abundances and their modifications from actively translating ribosomes. Here we develop tRIBO-seq, a simple and robust nanopore-based method to selectively capture ribosome-associated native tRNA populations (ribo-tRNAs) from actively translating ribosomes, providing tRNA abundance, modification and fragmentation information from a single experiment. Using tRIBO-seq, we find that ribo-tRNAs, but often not total tRNAs, are significantly altered upon stress. Notably, we find that tRNAome alterations strongly vary depending on the stress type: while viral infection and leucine deprivation leads to changes in ribo-tRNA abundances, methionine starvation causes a dramatic loss of methyl-based tRNA modifications. By contrast, we find that arsenite exposure does not alter tRNA abundances nor modification patterns, but rather causes major fragmentation events in selected subsets of ribo-tRNAs. Altogether, tRIBO-seq offers a robust and reproducible approach to map the full tRNA landscape -capturing tRNA abundance, modification and fragmentation patterns-, across both total and actively translating tRNA populations, revealing the dynamics of the tRNAome with unprecedented resolution, in a single experiment.

molecular biology↗

bioRxiv2025

Systematic benchmarking of basecalling models for RNA modification detection with highly multiplexed nanopore sequencing

Nanopore direct RNA sequencing (DRS) holds promise for advancing our understanding of the epitranscriptome by detecting RNA modifications in native RNA molecules. Recently, Oxford Nanopore Technologies (ONT) has released basecalling models capable of detecting several RNA modifications. However, their accuracy, sensitivity and specificity, as well as cross-reactivity against other modification types, remains largely unexplored. Here, we systematically benchmark modification-aware models by evaluating their performance on a highly-multiplexed panel of synthetic molecules covering all possible sequence contexts, as well as on biological samples from a diverse set of species. We find that modification-aware models reliably detect diverse RNA modification types across a broad range of sequence contexts. However, they are prone to elevated false positive rates and exhibit notable cross-reactivity with other RNA modification types. We show that the use of modification-free controls allows significant, yet incomplete removal of false positives, thus constituting an essential control. Finally, we demonstrate that basecalling error patterns and alterations in current features can identify differentially modified sites, for modifications for which modification-aware models are absent. Overall, our results underscore the utility and accuracy of modification-aware basecalling models for RNA modification detection, while highlighting the importance of including diverse control samples to mitigate false positive rates.

bioinformatics↗

bioRxiv2024

SeqTagger, a rapid and accurate tool to demultiplex direct RNA nanopore sequencing datasets

Nanopore direct RNA sequencing (DRS) enables direct measurement of RNA molecules, including their native RNA modifications, without prior conversion to cDNA. However, commercial methods for molecular barcoding of multiple DRS samples are lacking, and community-driven efforts, such as DeePlexiCon, are not compatible with newer RNA chemistry flowcells and the latest-generation GPU cards. To overcome these limitations, we introduce SeqTagger, a rapid and robust method that can demultiplex direct RNA sequencing datasets with 99% precision and 95% recall. We demonstrate the applicability of SeqTagger in both RNA002/R9.4 and RNA004/RNA chemistries and show its robust performance both for long and short RNA libraries, including custom libraries that do not contain standard poly-(A) tails, such as Nano-tRNAseq libraries. Finally, we demonstrate that increasing the multiplexing up to 96 barcodes yields highly accurate demultiplexing models. SeqTagger can be executed in a standalone manner or through the MasterOfPores NextFlow workflow. The availability of an efficient and simple multiplexing strategy improves the cost-effectiveness of this technology and facilitates the analysis of low-input biological samples.

genomics↗

bioRxiv2024

Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures

Mammalian ribosomal RNA (rRNA) molecules are highly abundant RNAs, decorated with over 220 rRNA modifications. Previous works have shown that some rRNA modification types can be dynamically regulated; however, how and when the mammalian rRNA modification landscape is remodeled remains largely unexplored. Here, we employ direct RNA nanopore sequencing to chart the human and mouse rRNA epitranscriptome across tissues, developmental stages, cell types and disease. Our analyses reveal multiple rRNA sites that are differentially modified in a tissue- and/or developmental stage-specific manner, including previously unannotated modified sites. We demonstrate that rRNA modification patterns can be used for tissue and cell type identification, which we hereby term epitranscriptomic fingerprinting. We then explore rRNA modification patterns in normal-tumor matched samples from lung cancer patients, finding that epitranscriptomic fingerprinting accurately classifies clinical samples into normal and tumor groups from only 250 reads per sample, demonstrating the potential of rRNA modifications as diagnostic biomarkers.

molecular biology↗

bioRxiv2023

Enhanced detection of RNA modifications and mappability with high-accuracy nanopore RNA basecalling models

In recent years, nanopore direct RNA sequencing (DRS) has established itself as a valuable tool for studying the epitranscriptome, due to its ability to detect multiple modifications within the same full-length native RNA molecules. While RNA modifications can be identified in the form of systematic basecalling errors in DRS datasets, N6-methyladenosine (m6A) modifications produce relatively low errors compared to other RNA modifications, limiting the applicability of this approach to m6A sites that are modified at high stoichiometries. Here, we demonstrate that the use of alternative RNA basecalling models, trained with fully unmodified sequences, increases the error signal of m6A, leading to enhanced detection and improved sensitivity even at low stoichiometries. Moreover, we find that high-accuracy alternative RNA basecalling models can show up to 97% median basecalling accuracy, outperforming currently available RNA basecalling models, which show 91% median basecalling accuracy. Notably, the use of high-accuracy basecalling models is accompanied by a significant increase in the number of mapped reads -especially in shorter RNA fractions- and increased basecalling error signatures at pseudouridine ({Psi}) and N1-methylpseudouridine (m1{Psi}) modified sites. Overall, our work demonstrates that alternative RNA basecalling models can be used to improve the detection of RNA modifications, read mappability and basecalling accuracy in nanopore DRS datasets.

genomics↗

bioRxiv2023

De novo basecalling of m6A modifications at single molecule and single nucleotide resolution

RNA modifications hold pivotal roles in shaping the fate and function of RNA molecules. Although nanopore sequencing technologies have proven successful at transcriptome-wide detection of RNA modifications, current algorithms are limited to predicting modifications at a per-site level rather than within individual RNA molecules. Herein, we introduce m6ABasecaller, an innovative method enabling direct basecalling of m6A modifications from raw nanopore signals within individual RNA molecules. This approach facilitates de novo prediction of m6A modifications with precision down to the single nucleotide and single molecule levels, without the need of paired knockout or control conditions. Using the m6ABasecaller, we find that the median transcriptome-wide m6A modification stoichiometry is [~]10-15% in human, mouse and zebrafish. Furthermore, we show that m6A modifications affect polyA tail lengths, exhibit a propensity for co-occurrence within the same RNA molecules, and show relatively consistent stoichiometry levels across isoforms. We further validate the m6ABasecaller by treating mESC with increasing concentrations of STM2457, a METTL3 inhibitor as well as in inducible METTL3 knockout systems. Overall, this work demonstrates the feasibility de novo basecalling of m6A modifications, opening novel avenues for the application of nanopore sequencing to samples with limited RNA availability and for which control knockout conditions are unavailable, such as patient-derived samples.

molecular biology↗

bioRxiv2022

Y chromosome sequence and epigenomic reconstruction across human populations

Recent advances in long-read sequencing technologies have allowed the generation and curation of more complete genome assemblies, enabling the analysis of traditionally neglected chromosomes, such as the human Y chromosome (chrY). Native DNA was sequenced on a MinION Oxford Nanopore Technologies sequencing device to generate genome assemblies for 7 major chrY human haplogroups. We analyzed and compared the chrY enrichment of sequencing data obtained using two different selective sequencing approaches: adaptive sampling and flow cytometry chromosome sorting. We show that adaptive sampling can produce data to create assemblies comparable to chromosome sorting while being a less expensive and time-consuming technique. We also assessed haplogroup-specific structural variants, which would be otherwise difficult to study using short-read sequencing data only. Finally, we took advantage of this technology to detect and profile epigenetic modifications amongst the considered haplogroups. Altogether, we provide a framework to study complex genomic regions with a simple, fast, and affordable methodology that could be applied to larger population genomics datasets.

genomics↗

bioRxiv2021

Whole-genomes from the extinct Xerces Blue butterfly reveal low diversity and long-term population decline

The Xerces Blue (Glaucopsyche xerces) is considered to be the first butterfly to become extinct at global scale in historical times. It was notable for its chalky lavender wings with conspicuous white spots on the ventral wings. The last individuals were collected in their restricted habitat, in the dunes near the Presidio military base in San Francisco, in 1941. We sequenced the genomes of four 80 to 100-year-old Xerces Blue, and seven historical and one modern specimens of its closest relative, the Silvery Blue (G. lygdamus). We compared these to a novel annotated genome of the Green-Underside Blue (G. alexis). Phylogenetic relationships inferred from complete mitochondrial genomes indicate that Xerces Blue was a distinct species that diverged from the Silvery Blue lineage at least 850,000 years ago. Using nuclear genomes, both species experienced population growth during the Eemian interglacial period, but the Xerces Blue decreased to a very low effective population size subsequently, a trend opposite to that observed in the Silvery Blue. Runs of homozygosity and deleterious load in the Xerces Blue were significantly greater than in the Silvery Blue, suggesting a higher incidence of inbreeding. These signals of population decline observed in Xerces Blue could be used to identify and monitor other insects threatened by human activities, whose extinction patterns are still not well known.

evolutionary biology↗