Biology subjects

Chiara, M.

Publications and source records attributed to Chiara, M..

12 recordsLinked to original sources

bioRxiv2025

Distinctive viral genome signatures are linked to repeated mammalian spillovers of H5N1 in North America

Highly pathogenic avian influenza H5N1 rarely infects mammals. In 2024-2025, however, genotypes B3.13 and D1.1 caused two independent spillovers into U.S. dairy cattle. By analysing 26,930 complete H5N1 genomes from global surveillance, we identified 73 major viral groups, most of which show continent-specific distribution in Europe, Asia, Africa, and North America. North American viruses exhibit higher genetic diversity in specific viral segments, including variants potentially associated with mammalian adaptation. Both dairy-cattle-associated B3.13 and D1.1 genotypes originate from the same geographic macro-area, suggesting a possible regional hotspot where avian-mammalian interfaces may facilitate viral adaptation. Our findings place the U.S. outbreaks in a global framework and indicate that North American H5N1 may be predisposed to cross-species transmission. TeaserComparative genomics and geographic analyses delineate distinctive genomic features of H5N1 genotypes associated with U.S. dairy cattle spillover.

evolutionary biology↗

bioRxiv2025

Multi-scale early warning system for influenza A spillovers

Spillovers of Influenza A viruses into farmed animals and humans have the potential to trigger epidemics or even global pandemics. We introduce FluWarning, a highly efficient and elegant computational method based on anomaly detection of codon bias and dinucleotide composition for early flagging of divergent viral HA segments. Applied to H1N1 specimens collected between 2008-2009, FluWarning accurately identifies the emergence of pdm09 - the virus that caused the 2009 flu pandemic; warnings precede the observed progression of the pandemic. Applied to H5N1 specimens collected between 2019 and 2025, FluWarning flagged the emergence of the B3.13 genotype, linked to a spillover event in dairy cows in the United States. In summary, FluWarning is an effective multi-scale warning system for IAVs, detecting spillovers with few available sequences. One-Sentence SummaryEarly detection of zoonoses using a few viral sequences is critical for the timely implementation of mitigation strategies.

bioinformatics↗

bioRxiv2024

Impact of mutations in the HEADING DATE 1 gene on transcription and cell wall composition of rice

Plants utilize environmental information to modify their developmental trajectories for optimal survival and reproduction. Over a century ago, day length (photoperiod) was identified as a major factor influencing developmental transitions, particularly the shift from vegetative to reproductive growth. In rice, exposure to day lengths shorter than a critical threshold accelerates flowering, while longer days inhibit this process. This response is mediated by HEADING DATE 1 (Hd1), a zinc finger transcription factor that is central in the photoperiodic flowering network. Hd1 acts as a repressor of flowering under long days but functions as a promoter of flowering under short days. However, the transcriptional organization of this dual function is still not fully understood. In this study, we utilized RNA-Seq to analyze the transcriptome of hd1 mutants under both long and short day conditions. We identified genes involved in the phenylpropanoid pathway that are deregulated under long days in the mutant. Quantitative profiling of cell wall components and abiotic stress assays suggest that Hd1 is involved in processes considered unrelated to flowering control. This indicates that day length perception and responses are intertwined with physiological processes beyond flowering.

plant biology↗

bioRxiv2023

Data-driven recombination detection in viral genomes

Recombination is a key molecular mechanism for the evolution and adaptation of viruses. The first recombinant SARS-CoV-2 genomes were recognized in 2021; as of today, more than ninety SARS-CoV-2 lineages are designated as recombinant. In the wake of the COVID-19 pandemic, several methods for detecting recombination in SARS-CoV-2 have been proposed; however, none could faithfully confirm manual analyses by experts in the field. We hereby present RecombinHunt, a novel, automated method for the identification of recombinant/mosaic genomes purely based on a data-driven approach. RecombinHunt compares favorably with other state-of-the-art methods and recognizes recombinant SARS-CoV-2 genomes (or lineages) with one or two breakpoints with high accuracy, within reduced turn-around times and small discrepancies with respect to the expert manually-curated standard nomenclature. Strikingly, applied to the complete collection of viral sequences from the recent monkeypox epidemic, RecombinHunt identifies recombinant viral genomes in high concordance with manually curated analyses by experts, suggesting that our approach is robust and can be applied to any epidemic/pandemic virus. In conclusion, RecombinHunt represents a breakthrough in the detection of recombinant viral lineages in pandemic/epidemic scenarios and could substantially improve/advance community-based approaches for the detection of recombinant viral genomes based on phylogenetic analyses.

bioinformatics↗

bioRxiv2021

Unsupervised classification of SARS-CoV-2 genomic sequences uncovers hidden genetic diversity and suggests an efficient strategy for genomic surveillance

Accurate and timely monitoring of emerging genomic diversity is crucial for limiting the spread of potentially more transmissible/pathogenic strains of SARS-CoV-2. At the time of writing, over 1.8M distinct viral genome sequences have been made publicly available, and a sophisticated nomenclature system based on phylogenetic evidence and expert manual curation has allowed the relatively rapid classification of emerging lineages of potential concern. Here, we propose a complementary approach that integrates fine-grained spatiotemporal estimates of allele frequency with unsupervised clustering of viral haplotypes, and demonstrate that multiple highly frequent genetic variants, arising within large and/or rapidly expanding SARS-CoV-2 lineages, have highly biased geographic distributions and are not adequately captured by current SARS-CoV-2 nomenclature standards. Our results advocate a partial revision of current methods used to track SARS-CoV-2 genomic diversity and highlight the importance of the application of strategies based on the systematic analysis and integration of regional data. Here we provide a complementary, completely automated and reproducible framework for the mapping of genetic diversity in time and across different geographic regions, and for the prioritization of virus variants of potential concern. We believe that the approach outlined in this study will contribute to relevant advances to current genomic surveillance methods.

genomics↗

bioRxiv2020

Complete vertebrate mitogenomes reveal widespread gene duplications and repeats

Modern sequencing technologies should make the assembly of the relatively small mitochondrial genomes an easy undertaking. However, few tools exist that address mitochondrial assembly directly. As part of the Vertebrate Genomes Project (VGP) we have developed mitoVGP, a fully automated pipeline for similarity-based identification of mitochondrial reads and de novo assembly of mitochondrial genomes that incorporates both long (>10 kbp, PacBio or Nanopore) and short (100-300 bp, Illumina) reads. Our pipeline led to successful complete mitogenome assemblies of 100 vertebrate species of the VGP. We have observed that tissue type and library size selection have considerable impact on mitogenome sequencing and assembly. Comparing our assemblies to purportedly complete reference mitogenomes based on short-read sequencing, we have identified errors, missing sequences, and incomplete genes in those references, particularly in repeat regions. Our assemblies have also identified novel gene region duplications, shedding new light on mitochondrial genome evolution and organization.

genomics↗

bioRxiv2020

Comparative genomic provides an operational classification system and reveals early emergence and spatio-temporal

Effective systems for the analysis of molecular data are of fundamental importance for real-time monitoring of the spread of infectious diseases and the study of pathogen evolution. While the Nextstrain and GISAID portals offer widely used systems for the classification of SARS-CoV-2 genomes, both present relevant limitations. Here we propose a highly reproducible method for the systematic classification of SARS-CoV-2 viral types. To demonstrate the validity of our approach, we conduct an extensive comparative genomic analysis of more than 20,000 SARS-CoV-2 genomes. Our classification system delineates 12 clusters and 4 super-clusters in SARS-CoV-2, with a highly biased spatio-temporal distribution worldwide, and provides important observations concerning the evolutionary processes associated with the emergence of novel viral types. Based on the estimates of SARS-CoV-2 evolutionary rate and genetic distances of genomes of the early pandemic phase, we infer that SARS-CoV-2 could have been circulating in humans since August-November 2019. The observed pattern of genomic variability is remarkably similar between all clusters and super-clusters, being UTRs and the s2m element, a highly conserved secondary structure element, the most variable genomic regions. While several polymorphic sites that are specific to one or more clusters were predicted to be under positive or negative selection, overall, our analyses also suggest that the emergence of novel genome types is unlikely to be driven by widespread convergent evolution and independent fixation of advantageous substitutions. While, in the absence of rigorous experimental validation, several questions concerning the evolutionary processes and the phenotypic characteristics (increased/decreased virulence) remain open, we believe that the approach outlined in this study can be of relevance for the tracking and functional characterization of different types of SARS-CoV-2 genomes.

genomics↗

bioRxiv2020

Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-Cov-2

Phylogenomic analysis of SARS-CoV-2 as available from publicly available repositories suggests the presence of 3 prevalent groups of viral episomes (super-clades), which are mostly associated with outbreaks in distinct geographic locations (China, USA and Europe). While levels of genomic variability between SARS-CoV-2 isolates are limited, to our knowledge, it is not clear whether the observed patterns of variability in viral super-clades reflect ongoing adaptation of SARS-CoV-2, or merely genetic drift and founder effects. Here, we analyze more than 1100 complete, high quality SARS-CoV-2 genome sequences, and provide evidence for the absence of distinct evolutionary patterns/signatures in the genomes of the currently known major clades of SARS-CoV-2. Our analyses suggest that the presence of distinct viral episomes at different geographic locations are consistent with founder effects, coupled with the rapid spread of this novel virus. We observe that while cross species adaptation of the virus is associated with hypervariability of specific protein coding regions (including the RDB domain of the spike protein), the more variable genomic regions between extant SARS-CoV-2 episomes correspond with the 3 and 5 UTRs, suggesting that at present viral protein coding genes should not be subjected to different adaptive evolutionary pressures in different viral strains. Although this study can not be conclusive, we believe that the evidence presented here is strongly consistent with the notion that the biased geographic distribution of SARS-CoV-2 isolates should not be associated with adaptive evolution of this novel pathogen.

genomics↗

bioRxiv2020

The drought-responsive ZmFDL1 gene regulates cuticle biosynthesis and cuticle-dependent leaf permeability

In higher plants, the outer surface of the aerial parts is covered by the cuticle, a complex lipid layer that constitutes a barrier against damages caused by environmental factors and provides protection against non-stomatal water loss. We show in this study that cuticle deposition, during the juvenile phase of in maize (Zea mays) plant development, and cuticle-dependent leaf permeability are controlled by the MYB transcription factor ZmMYB94/FUSED LEAVES1 (ZmFDL1). Biochemical analysis showed that in fdl1-1 mutant seedlings at the coleoptile stage both cutin and wax biosynthesis and deposition were altered. Among cutin compounds, {omega}-hydroxy fatty acids and polyhydroxy-fatty acids were specifically affected, while the reduction of epicuticular waxes, was mainly observed in primary long chain alcohols, and to a minor extent, long-chain wax esters. Transcriptome analysis allowed the identification of novel candidate genes involved in lipid metabolism and the assembly of a proposed pathway for cuticle biosynthesis in maize. Lack of ZmFDL1 affects the expression of genes located in different modules of the pathway and correspondence between gene transcriptional variations and biochemical defects have been highlighted. A decrease in cuticle-dependent leaf permeability was observed in maize seedlings exposed to drought as well as ABA treatment, which implies coordinated changes in the transcript levels of ZmFDL1 and associated genes. Overall, our results suggest that the response to water stress implies the activation of wax biosynthesis and the involvement of by both ZmFDL1 and ABA regulatory pathways. One-Sentence SummaryCuticle biosynthesis and cuticle-mediated drought-response during the juvenile phase of maize plant growth, are regulated by the MYB transcription factor fused leaves1 (ZmFDL1) and influenced by ABA.

plant biology↗

bioRxiv2020

VINYL: Variant prIoritizatioN bY survivaL analysis

MotivationClinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance, especially when large volumes of data - like those produced by modern sequencing technologies - are involved. ResultsIn this paper, we present VINYL, a highly accurate and fully automated system for the functional annotation and prioritization of genetic variants in large scale clinical studies. Extensive analyses of both real and simulated datasets suggest that VINYL show higher accuracy and sensitivity when compared to equivalent state of the art methods, allowing the rapid and systematic identification of potentially pathogenic variants in different experimental settings.

bioinformatics↗

bioRxiv2018

Laniakea: an open solution to provide Galaxy \"on-demand\" instances over heterogeneous cloud infrastructures.

BackgroundGalaxy is rapidly becoming the de facto standard among workflow managers for bioinformatics. A rich feature set, its overall flexibility, and a thriving community of enthusiastic users are among the main factors contributing to the popularity of Galaxy and Galaxy based applications. One of the main advantages of Galaxy consists in providing access to sophisticated analysis pipelines, e.g., involving numerous steps and large data sets, even to users lacking computer proficiency, while at the same time improving reproducibility and facilitating teamwork and data sharing among researchers. Although several Galaxy public services are currently available, these resources are often overloaded with a large number of jobs and offer little or no customization options to end users. Moreover, there are scenarios where a private Galaxy instance still constitutes a more viable alternative, including, but not limited to, heavy workloads, data privacy concerns or particular needs of customization. In such cases, a cloud-based virtual Galaxy instance can represent a solution that overcomes the typical burdens of managing the local hardware and software infrastructure needed to run and maintain a production-grade Galaxy service.\n\nResultsHere we present Laniakea, a robust and feature-rich software suite which can be deployed on any scientific or commercial Cloud infrastructure in order to provide a \"Galaxy on demand\" Platform as a Service (PaaS). Laying its foundations on the INDIGO-DataCloud middleware, which has been developed to accommodate the needs of a large number of scientific communities, Laniakea can be deployed and provisioned over multiple architectures by private or public e-infrastructures. The end user interacts with Laniakea through a front-end that allows a general setup of the Galaxy instance, then Laniakea takes charge of the deployment both of the virtual hardware and all the software components. At the end of the process the user has access to a private, production-grade, yet fully customizable, Galaxy virtual instance. Laniakeas supports the deployment of plain or cluster backed Galaxy instances, shared reference data volumes, encrypted data volumes and rapid development of novel Galaxy flavours, that is Galaxy configurations tailored for specific tasks. As a proof of concept, we provide a demo Laniakea instance hosted at an ELIXIR-IT Cloud facility.\n\nConclusionsThe migration of scientific computational services towards virtualization and e-infrastructures is one of the most visible trends of our times. Laniakea provides Cloud administrators with a ready-to-use software suite that enables them to offer Galaxy, a popular workflow manager for bioinformatics, as an on-demand PaaS to their users. We believe that Laniakea can concur in making the many advantages of using Galaxy more accessible to a broader user base by removing most of the burdens involved in running a private instance. Finally, Laniakeas design is sufficiently general and modular that could be easily adapted to support different services and platforms beyond Galaxy.

bioinformatics↗

bioRxiv2018

SMRT long-read sequencing and Direct Label and Stain optical maps allow the generation of a high-quality genome assembly for the European barn swallow (Hirundo rustica rustica)

BackgroundThe barn swallow (Hirundo rustica) is a migratory bird that has been the focus of a large number of ecological, behavioural and genetic studies. To facilitate further population genetics and genomic studies, here we present a reference genome assembly for the European subspecies (H. r. rustica).\n\nFindingsAs part of the Genome10K (G10K) effort on generating high quality vertebrate genomes, we have assembled a highly contiguous genome assembly using Single Molecule Real-Time (SMRT) DNA sequencing and several Bionano optical map technologies. We compared and integrated optical maps derived both from the Nick, Label, Repair and Stain and from the Direct Label and Stain (DLS) technologies. As proposed by Bionano, the DLS more than doubled the scaffold N50 with respect to the nickase. The dual enzyme hybrid scaffold led to a further marginal increase in scaffold N50 and an overall increase of confidence in the scaffolds. After removal of haplotigs, the final assembly is approximately 1.21 Gbp in size, with a scaffold N50 value of over 25.95 Mbp.\n\nConclusionsThis high-quality genome assembly represents a valuable resource for further studies of population genetics and genomics in the barn swallow, and for studies concerning the evolution of avian genomes. It also represents one of the very first genomes assembled by combining SMRT long-read sequencing with the new Bionano DLS technology for scaffolding. The quality of this assembly demonstrates the potential of this methodology to substantially increase the contiguity of genome assemblies.

genomics↗