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bioRxiv2024

Rtt107 cooperates with Rad55 or Slx4 to maintain genome stability in Saccharomyces cerevisiae

A range of genome maintenance factors respond to endogenous and exogenous DNA damage to prevent mutations and cell death. The scaffold protein, Rtt107, is important for the growth of cells exposed to DNA-damaging agents in the budding yeast Saccharomyces cerevisiae. Rtt107 binds to a diverse array of partner proteins, such as Slx4, and responds to DNA damage by localizing to phosphorylated histone H2A. Rad55-Rad57, a heterodimer involved in DNA repair, also binds to Rtt107, but the function of the Rtt107-Rad55-Rad57 complex remains unclear. In addition to their sensitivity to DNA-damaging agents, rtt107{Delta} mutants exhibit spontaneous genome instability phenotypes, including spontaneous loss of heterozygosity (LOH) caused by crossovers and other genetic events. However, the binding partners with which Rtt107 interacts to prevent spontaneous genome instability have yet to be elucidated. Here, we showed that Rtt107 acts in the same pathway as Rad55 to limit LOH, specifically by preventing crossover events. A rad55-S404A phosphorylation site mutation largely disrupted the interaction between Rtt107 and Rad55-Rad57, resulting in increased LOH and crossover rates, consistent with the contribution of Rtt107-Rad55-Rad57 interaction to genome stability. Strikingly, an rtt107-K887M mutation that reduces Rtt107 recruitment to H2A did not result in an LOH phenotype, suggesting that the role of Rtt107 in preventing LOH is distinct from its function as an H2A-binding scaffold. Rtt107 did not function primarily in the same pathway as Rad55 to limit recombination at the sensitive ribosomal DNA (rDNA) locus, but instead acted with Slx4 to maintain rDNA stability, suggesting that interactions of Rtt107 with different partners prevented distinct types of instability. Taken together, our observations suggested that Rtt107 limits spontaneous LOH and crossover events in part by binding to Rad55 in a manner dependent on Rad55-S404. Author SummaryNumerous proteins are involved in the repair of damaged DNA and prevention of genome instability in cells, which would otherwise result in persistent changes to DNA. Genome maintenance pathways are evolutionarily conserved, and the budding yeast, Saccharomyces cerevisiae, is a powerful model organism for investigating the maintenance of genome integrity. Rtt107 is a scaffold protein expressed in yeast, containing conserved protein domains that are important for the function of genome maintenance proteins. Although the functions of Rtt107 in cells treated with DNA-damaging agents have been characterized in some detail, it remains unclear how Rtt107 prevents spontaneous genome instability in cells growing under normal conditions. Here, we found that Rtt107 prevents specific types of spontaneous genome instability and acts in the same pathway as the DNA repair protein, Rad55, to which it binds. Mutation of a possible Rtt107 binding site on Rad55 showed that Rtt107 indeed limited genome instability in part by binding to Rad55. Strikingly, Rtt107 also showed Rad55-independent roles in preventing ribosomal DNA (rDNA) instability, and in this context Rtt107 cooperated in part with its binding partner Slx4. Taken together, our results revealed the pathways by which the evolutionarily conserved protein Rtt107 limits spontaneous genome instability.

genetics↗

bioRxiv2024

Atypical landscape of transposable elements in the large genome of Aedes aegypti

Transposable elements (TEs) contribute significantly to variation in genome size among eukaryotic species, but the factors influencing TE accumulation and diversification are only partially understood. Most of our current knowledge about TE organization, dynamics and evolution derives from investigations in model organisms with a relatively small genome size such as Drosophila melanogaster or Arabidopsis thaliana. Whether the observed patterns hold true in larger genomes remains to be determined. The Diptera order is an ideal taxon to address this question, because it includes a forty-year model of TE biology (D. melanogaster) as well as mosquito species with significantly larger genomes. Here, we use a comparative genomics approach to characterize the genomic forces that have shaped the TE content of the Aedes aegypti genome (1.3 Gb) relative to the Anopheles coluzzii genome (300 Mb) and the D. melanogaster genome (180 Mb). Leveraging a newly developed high-quality TE library for Ae. aegypti, our results reveal a contrasted pattern of TE organization in Ae. aegypti compared to An. coluzzii and D. melanogaster. Our analyses suggest that the substantial TE fraction observed in the Ae. aegypti genome reflect both a high rate of TE transposition and a low rate of TE elimination. Together, our results indicate that TE organization and evolutionary dynamics in the large genome of Ae. aegypti are distinct from those of other dipterans with smaller genomes.

evolutionary biology↗

bioRxiv2024

Expanding the Triangle of U: The genome assembly of Hirschfeldia incana provides insights into chromosomal evolution, phylogenomics and high photosynthesis-related traits

The Brassiceae tribe encompasses many economically important crops and exhibits high intraspecific and interspecific phenotypic variation. After a shared whole-genome triplication (WGT) event (Br-, [~]15.9 million years ago), different lineages and species underwent differential chromosomal rearrangements (diploidization) leading to diverse patterns of gene retention and loss (fractionation). Lineage diversification and genomic changes contributed to an array of divergence in morphology, biochemistry, and physiology underlying photosynthesis-related traits. The C3 species Hirschfeldia incana is studied as it displays high photosynthetic rates under high-light conditions. We present an improved chromosome-level genome assembly for H. incana (Nijmegen, v2.0) using nanopore and chromosome conformation capture (Hi-C) technologies, with 409Mb in size and an N50 of 52Mb (a 10x improvement over the previously published scaffold-level v1.0 assembly). The updated assembly and annotation allowed to investigate the WGT history of H. incana in a comparative phylogenomic framework from the Brassiceae ancestral genomic blocks and related diploidized crops. Hirschfeldia incana (x=7) shares extensive genome collinearity with Raphanus sativus (x=9). These two species share some commonalities with Brassica rapa and B. oleracea (A genome, x=10 and C genome, x=9, respectively) and other similarities with B. nigra (B genome, x=8). Phylogenetic analysis revealed that H. incana and R. sativus form a monophyletic clade in between the Brassica A/C and B genomes. We postulate that H. incana and R. sativus genomes are results of reciprocal hybridization combinations of the Brassica A/C and B genome types. Our results might explain the discrepancy observed in published studies regarding phylogenetic placement of H. incana and R. sativus in relation to the "Triangle of U" species. Expression analysis of WGT retained gene copies revealed sub-genome expression divergence, likely due to neo- or sub-functionalization. Finally, we highlighted genes associated with physio-biochemical-anatomical adaptive changes observed in H. incana which likely facilitate its high-photosynthesis traits under high light.

plant biology↗

bioRxiv2024

Influenza A defective viral genomes and non-infectious particles are in-creased by host PI3K inhibition via anti-cancer drug alpelisib

RNA viruses produce abundant defective viral genomes during replication, setting the stage for interactions between viral genomes that alter the course of pathogenesis. Harnessing these interactions to develop antivirals has become a recent goal of intense research focus. Despite decades of research, the mechanisms that regulate the production and interactions of Influenza A defective viral genomes are still unclear. The role of the host is essentially unexplored; specifically, it remains unknown whether host metabolism can influence the formation of defective viral genomes and the particles that house them. To address this question, we manipulated host cell anabolic signaling activity and monitored the production of defective viral genomes and particles by A/H1N1 and A/H3N2 strains, using a combination of single-cell immunofluorescence quantification, third-generation long-read sequencing, and the cluster-forming assay, a method we developed to titer defective and fully-infectious particles simultaneously. Here we show that alpelisib (Piqray), a highly selective inhibitor of mammalian Class 1a phosphoinositide-3 kinase (PI3K) receptors, significantly changed the proportion of defective particles and viral genomes (specifically deletion-containing viral genomes) in a strain-specific manner, under conditions that minimize multiple cycles of replication. Alpelisib pre-treatment of cells led to an increase in defective particles in the A/H3N2 strain, while the A/H1N1 strain showed a decrease in total viral particles. In the same infections, we found that defective viral genomes of polymerase and antigenic segments increased in the A/H1N1 strain, while the total particles decreased suggesting defective interference. We also found that the average deletion size in polymerase complex viral genomes increased in both the A/H3N2 and A/H1N1 strains. The A/H1N1 strain, additionally showed a dose-dependent increase in total number of defective viral genomes. In sum, we provide evidence that host cell metabolism can increase the production of defective viral genomes and particles at an early stage of infection, shifting the makeup of the infection and potential interactions among virions. Given that Influenza A defective viral genomes can inhibit pathogenesis, our study presents a new line of investigation into metabolic states associated with less severe flu infection and the potential induction of these states with metabolic drugs.

microbiology↗

bioRxiv2024

Influenza A defective viral genome production is altered by metabolites, metabolic signaling molecules, and cyanobacteria extracts

RNA virus infections are composed of a diverse mix of viral genomes that arise from low fidelity in replication within cells. The interactions between "defective" and full-length viral genomes have been shown to shape pathogenesis, leading to intense research into employing these to develop novel antivirals. In particular, Influenza A defective viral genomes (DVGs) have been associated with milder clinical outcomes. Yet, the full potential of DVGs as broad-spectrum antivirals remains untapped due to the unknown mechanisms of their de novo production. Much of the research into the factors affecting defective viral genome production has focused on the virus, while the role of the host has been neglected. We recently showed that altering host cell metabolism away from pro-growth pathways using alpelisib increased the production of Influenza A defective viral genomes. To uncover other drugs that could induce infections to create more DVGs, we subjected active influenza infections of the two circulating human subtypes (A/H1N1 & A/H3N2) to a screen of metabolites, metabolic signaling molecules, and cyanobacteria-derived biologics, after which we quantified the defective viral genomes (specifically deletion-containing viral genomes, DelVGs) and total viral genomes using third generation long-read sequencing. Here we show that metabolites and signaling molecules of host cell central carbon metabolism can significantly alter DelVG production early in Influenza A infection. Adenosine, emerged as a potent inducer of defective viral genomes, significantly amplifying DelVG production across both subtypes. Insulin had similar effects, albeit subtype-specific, predominantly enhancing polymerase segment DVGs in TX12 infections. Tricarboxylic Acid (TCA) cycle inhibitors 4-octyl itaconate and UK5099, along with the purine analog favipiravir, increased total viral genome production across subtypes. Cyanobacterial extracts primarily affected DVG and total viral genome production in TX12, with a specific, almost complete shutdown of influenza antigenic segments. These results underscore the influence of host metabolic pathways on DVG production and suggest new avenues for antiviral intervention, including PI3K-AKT and Ras-MAPK signaling pathways, TCA cycle metabolism, purine-pyrimidine metabolism, polymerase inhibition, and cyanotherapeutic approaches. More broadly, our findings suggest that the social interactions observed between defective and full-length viral genomes, depend not only on the viral actors, but can be altered by the stage provided by the host. Our study advances our fundamental understanding of DVG production mechanisms and highlights the potential of targeting host metabolism to develop broad-spectrum influenza therapeutics.

microbiology↗

bioRxiv2024

ANASFV: a workflow for ASFV whole genome sequencing, assembly, and evaluation

African Swine Fever Virus (ASFV) poses an ongoing threat with widespread outbreaks affecting both domestic and wild pig populations globally. Effective management of ASFV outbreaks necessitates a deep understanding of its genetic diversity and evolutionary dynamics. Despite the advantages of nanopore sequencing for genome analysis, its application to ASFV genomes encounters specific challenges, such as high host DNA contamination that reduces viral genome coverage and an inherently higher error rate producing small insertions and deletions (indels). Another notable issue is the lack of standardized methods for assessing the quality of ASFV genomes. Furthermore, an increasing number of recombinant isolates of genotype I and II, have been observed, further complicating the task of phylogenetic analysis. To overcome these obstacles, we developed the ANASFV (analysis of an ASFV) pipeline. The pipeline is used to solve four tasks: In the first task, the pipeline introduces an amplicon sequencing approach that significantly improves genomic coverage, enabling reliable genome assembly. The pipeline also introduce reference-aided polishing techniques to correct small indels caused by nanopore sequencing errors. Moving on to the second task, a genome quality assessment system was established to evaluate the completeness and accuracy of the assembled genomes. For the third task, a method to rapidly analyze whether an isolate is a recombinant between genotype I and II, as well as to determine the pattern of recombination, based on gene similarity. Lastly, a comprehensive phylogenetic analysis based on coding sequences (CDS) was conducted, allowing us to generate a refined phylogenetic tree that includes all known ASFV genomes. The ANASFV pipeline will facilitate ASFV full genome sequencing using the nanopore platform. The pipeline will also support robust downstream bioinformatic analyses to assess genome integrity and conduct detailed phylogenetic studies based on whole-genome data.

genetics↗

bioRxiv2024

Evolutionary dynamics of genome structure and content among closely related bacteria

Bacterial genomes primarily diversify via gain, loss, and rearrangement of genetic material in their flexible accessory genome. Yet the dynamics of accessory genome evolution are very poorly understood, in contrast to the core genome where diversification is readily described by mutations and homologous recombination. Here, we tackle this problem for the case of very closely related genomes. We comprehensively describe genome evolution within n=222 genomes of E. coli ST131, which likely shared a common ancestor around one hundred years ago. After removing putative recombinant diversity, the total length of the phylogeny is 6000 core genome mutations. Within this diversity, we find 22 modifications to core genome synteny and estimate around 2000 structural changes within the accessory genome, i.e. one structural change for every 3 core genome mutations. 63% of loci with structural diversity could be resolved into individual gain and loss events with ten-fold more gains than losses, demonstrating a dominance of gains due to insertion sequences and prophage integration. Our results suggest the majority of synteny changes and insertions in bacterial genomes are likely deleterious and only persist for a short time before being removed by purifying selection.

evolutionary biology↗

bioRxiv2024

Novel Amplicons based Method for Near-Full-Length Genome (NFLG) Sequencing of HIV-1 Group M Recombinant Forms

Over the years the spread of HIV-1 across the globe resulted in the creation of multiple subtypes and new recombinant forms (RFs). While the pol gene region of the HIV-1 genome is used for resistance mutations analysis and initial detection of RFs, whole genome sequencing analysis is required to determine recombination events across the viral genome. Here, we present a novel robust near-full length genome (NFLG) sequencing approach for the sequencing of HIV-1 genomes, out of clinical whole blood samples. This method has been successfully tested for various HIV-1 subtypes and RFs. The method is based on an in-house developed set of 32 pan-genotypic primer pairs, divided into two pools, each containing 16 primer pairs covering the entire HIV-1 genome. Two parallel multiplex PCR reactions were used to generate 32 overlapping DNA fragments spanning the HIV-1 genome. Nextera XT protocol was used to obtain barcoded DNA libraries, which were sequenced with the Illumina Miseq platform using a V3 kit. A consensus sequence was determined for each sample and was used to define recombination events across the genome. For this aim, a combined analysis of several computational tools including HIV BLAST, phylogenetic analysis, RIP, SimPlot++ and jpHMM were employed. Overall, plasma samples from 33 patients suspected to carry RFs and 2 different, known pure subtypes controls, were included in this study. Genome coverage varied between RFs, while the gag and pol genes were nearly fully covered, the highly variable env gene region was not. Yet, these NFLG analyses enabled the identification of recombination events genome wide. In summary, we describe a methodology for HIV-1 NFLG sequencing, which is based on partially overlapping, multiple PCR fragments, spanning the HIV-1 genome. Additionally, this newly refined method was compared to HIV-1 NFLG results of PCR-free metagenomic sequencing and proved to obtain greater coverage of the HXB2 reference genome. Yet, further testing and validation on a larger cohort is required. Still, this method enables sequencing of 20 different patient samples in a single MiSeq sequencing run and was used for the characterization of different HIV-1 RFs and pure subtypes circulating in Israel.

molecular biology↗

bioRxiv2024

PneumoBrowse 2: An integrated visual platform for curated genome annotation and multiomics data analysis of Streptococcus pneumoniae

Streptococcus pneumoniae is an opportunistic human pathogen responsible for high morbidity and mortality rates. Extensive genome sequencing revealed its large pangenome, serotype diversity, and provided insight into genome dynamics. However, functional genome analysis has lagged behind, as that requires detailed and time-consuming manual curation of genome annotations, and integration of genomic and phenotypic data. To remedy this, PneumoBrowse was presented in 2018; a user-friendly interactive online platform, which provided the detailed annotation of the S. pneumoniae D39V genome, alongside transcriptomic data. Since 2018, many new studies on S. pneumoniae genome biology and protein functioning have been performed. Here, we present PneumoBrowse 2 (https://veeninglab.com/pneumobrowse), fully rebuilt in JBrowse 2. We updated annotations for transcribed and transcriptional regulatory features in the D39V genome. We added genome-wide data tracks for high-resolution chromosome conformation capture (Hi-C) data, chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq), ribosome profiling, CRISPRi-seq gene essentiality data and more. Additionally, we included 18 phylogenetically diverse S. pneumoniae genomes and their annotations. By providing easy access to diverse high-quality genome annotations, and links to other databases (including UniProt and AlphaFold), PneumoBrowse 2 will further accelerate research and development into preventive and treatment strategies, through increased understanding of the pneumococcal genome. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/606308v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1a38ce5org.highwire.dtl.DTLVardef@773428org.highwire.dtl.DTLVardef@1368aorg.highwire.dtl.DTLVardef@1a39f0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

In silico generation of synthetic cancer genomes using generative AI

Cancer originates from alterations in the genome, and understanding how these changes lead to disease is crucial for achieving the goals of precision oncology. Connecting genomic alterations to health outcomes requires extensive computational analysis using accurate algorithms. Over the years, these algorithms have become increasingly sophisticated, but a severe shortage of open access gold-standard datasets presents a fundamental challenge. Since genomic data is considered personal health information, only an extremely limited number of deeply sequenced legacy cancer genomes can be shared and redistributed. As a result, tool benchmarking is often conducted on the same small set of genomes sequenced with older technologies and uncertain ground truths. This is a major obstacle to the development of improved analytic tools. To address this issue, we have developed OncoGAN, a novel generative AI tool that uses a combination of generative adversarial networks and tabular variational autoencoders to generate realistic but entirely synthetic cancer genomes based on training sets derived from large-scale genomic projects. Our results demonstrate that this approach accurately reproduces the scale, distribution, and characteristics of somatic point mutations, copy number alterations and structural variants across multiple common cancer types, while protecting donors privacy information. OncoGAN accurately recapitulates tumor type-specific mutational signatures as well as the positional distribution of somatic mutations. To evaluate the fidelity of the simulations, we tested the synthetic genomes using DeepTumour, a software capable of identifying tumor types based on mutational patterns, and demonstrated a high level of concordance between the synthetic genome tumor type and DeepTumours prediction of the type. We also showed that augmenting real donor data with OncoGAN-generated synthetic data could be used to train a more accurate version of DeepTumour. This tool will allow the generation of an extensive and realistic set of training and testing cancer genomes whose ground truth is known exactly. This advance provides computational biologists with the ability to develop realistic cancer genome benchmarking sets and make them available to the research community for the testing, development and enhancement of cancer genome analysis tools.

bioinformatics↗

bioRxiv2024

Chromosome-scale genome assembly and linkage map for Silene uniflora reveal the recombination landscape in a rapidly evolving plant species

The genus Silene is an important model system for fields as diverse as sex chromosome evolution, speciation and disease ecology. However, genomic resources remain scarce in the genus. Here, we present a chromosome-scale genome assembly for S. uniflora, a hermaphroditic/gynodioecious species which is an important model for rapid adaptation to anthropogenic disturbance and the role of phenotypic plasticity in adaptive evolution. Using a combination of long-read and Hi-C sequencing technologies, we generated a 1,268 Mb genome assembly with a scaffold N50 of 40.72 Mb and 682 Mb assembled into 12 chromosomes. We annotated the genome using evidence from transcriptome and protein mapping in combination with ab initio gene prediction, resulting in 41,603 protein-coding genes and a BUSCO completeness score of 91%. We also present a linkage map which we used to validate the genome assembly and estimate local recombination rate across the genome. Comparison to the only two other Silene species with chromosome-scale genome assemblies reveals widespread genome rearrangements in the genus, suggesting Silene may be a promising study system for the role of genome rearrangement in evolution, particularly in the evolution of sex chromosomes and adaptation. Significance statementPlant species in the genus Silene (campions) are important study organisms in multiple areas of ecology and evolution. Sea campion (Silene uniflora) is an important model for investigations into rapid adaptation, phenotypic plasticity and parallel evolution. However, only two species have high-quality genome assemblies available, hampering studies of their genetics and evolution. We present a high-quality genome assembly, genetic map and gene annotation for sea campion. These will be important genomic resources for future studies of sea campion, other species in the genus Silene and the family Caryophyllaceae more generally.

evolutionary biology↗

bioRxiv2025

Ensemble-based genomic prediction for maize flowering time reveals novel insights into trait genetic architecture and improves prediction for breeding applications

While various genomic prediction models have been evaluated for their potential to accelerate genetic gain for multiple traits, no individual genomic prediction model has outperformed all others across all applications. As an alternative approach, ensembles of multiple individual genomic prediction models can be applied to utilise the complementary strengths of individual prediction models and offset the prediction errors of each. We used the EasiGP (Ensemble AnalySis with Interpretable Genomic Prediction) pipeline to investigate the performance of an ensemble approach, targeting flowering-time traits measured in two maize nested association mapping datasets. For both datasets, the ensemble-based prediction approach achieved higher prediction accuracy and lower prediction error across the flowering-time traits compared to each individual model. Multiple genomic regions known to contain key flowering-time related genes were repeatedly included as features across individual genomic prediction models, indicating the models successfully captured SNPs as features that are associated with genomic regions known to contain flowering-time genes. Although repeatability was high for some genomic regions, estimated marker effects varied across many genomic regions, suggesting that the models might also have captured different aspects of the genetic variation underlying the traits. The ensemble combination of the diverse views likely contributed to the improvement of prediction performance by the ensemble-based approach over the individual prediction models. Ensemble-based prediction can be applied to overcome limitations observed in the continuous exploration for the best individual genomic prediction models that can consistently achieve the highest prediction performance, thereby potentially contributing to improved prediction accuracy for applications in crop breeding. Article summaryThis study targets researchers interested in the performance of genomic prediction models. To demonstrate potential advantages of an ensemble of diverse individual genomic prediction models, we investigated the prediction of key flowering-time traits (days to anthesis and anthesis to silking interval) in two maize datasets. The ensemble approach consistently improved the prediction performance. The improvement was attributed to the offset of prediction errors by combining multiple different dimensions of trait genetic variation. Ensembles can lead to higher selection accuracy of desirable individuals for applications in crop breeding.

bioinformatics↗

bioRxiv2025

Nanopore long-read only genome assembly of clinical Enterobacterales isolates is complete and accurate

Whole bacterial genome sequence reconstruction using Oxford Nanopore Technologies ("Nanopore") long-read only sequencing may offer a lower-cost, higher-throughput alternative for pathogen surveillance to hybrid assembly with recent improvements in Nanopore sequencing accuracy. We evaluated the accuracy, including plasmid reconstruction, of Nanopore long-read only genome assemblies of Enterobacterales. We sequenced 92 genomes from clinical Enterobacterales isolates, collected in England under a national surveillance program, with long-read Nanopore (R10.4.1, Dorado v5.0.0 super-high-accuracy basecalled) and short-read Illumina (NovaSeq) sequencing approaches. Genomes were assembled using three long-read only (Flye; Hybracter long; Autocycler), and three hybrid assemblers (Hybracter hybrid; Unicycler normal; bold). Three polishing modalities (Medaka v2 with subsampled or un-subsampled long-reads; Polypolish + Pypolca with short-reads) were investigated. Autocycler circularised the most chromosomes (87/92 [95%]). Plasmid sequence reconstruction was comparable between all assemblers except Flye, all recovering 90-96% of plasmids, although the ground truth was uncertain. Flye performed worse than other assemblers on almost all metrics. Autocycler + Medaka (un-subsampled long-reads) was the most accurate long-read only assembler/polisher combination, comparable to hybrid assemblies (median 0 [IQR:0-0] SNPs and 0 [IQR:0-1] indels per genome; quality value/Q score, 100 [IQR: 64-100]), with only 4/92 genome sequences having >10 SNPs/indels. Medaka polishing with un-subsampled long-reads resulted in small improvements in indels but not SNPs for both Flye and Autocycler assemblies. Seven-locus MLST, antimicrobial resistance, virulence, and stress gene annotation was equivalent across assembler/polisher combinations. Nanopore long-read only bacterial genome assembly with Autocycler combined with Medaka polishing (using un-subsampled reads) is similarly accurate and possibly more complete than hybrid assemblies, representing a viable alternative for incorporating high-quality genomic data, including plasmids, into Enterobacterales surveillance. Data SummaryNanopore long-reads and Illumina short-reads from the 92 Enterobacterales isolates from this study have been uploaded to ENA (BioProject accession: PRJEB93885). Code for the Nextflow assembly pipeline, downstream analysis scripts, and R statistical analysis scripts are available on GitHub (https://github.com/oxfordmmm/NEKSUS_ont_hybrid_assembly_comparison). The following supplementary data tables are available on FigShare (https://figshare.com/account/home#/projects/253775): O_LIENA Sample accessions and sample metadata (accessions_and_metadata.csv) C_LIO_LISeqkit stats summaries of the Illumina and Nanopore reads (raw_qc_sup.cav) C_LIO_LISummary of assembly contig features (contigs_summary_sup_cleaned.csv) C_LIO_LIPairwise mash distances between contigs (mash_cleaned.csv) C_LIO_LIPlasmids matching across different assemblers compared to the Hybracter (hybrid) and manually-curated reference sets (plasmids_match_hybracter_mash.csv; plasmids_match_manual_mash.csv, respectively) C_LIO_LISeven-locus multi-locus sequence type annotation (mlst_cleaned.csv) C_LIO_LICheckM2 summaries of assemblies (checkm2_cleaned.csv) C_LIO_LINucleotide-level accuracy of assemblies (SNP, Indels, and Quality value compared to short-read mapping; assembly_nucleotide_accuracy_cleaned.csv) C_LIO_LIBakta annotation (bakta_by_contig_cleaned.csv) C_LIO_LIAMRFinderPlus annotations of contigs (amrfinder_plus_cleaned.csv) C_LIO_LIMOB-suite annotation summaries of contigs (mobsuite_cleaned.csv) C_LI Impact StatementNanopore long-reads have historically been too error-prone to use alone for accurate bacterial genome assembly, necessitating additional Illumina short-reads to achieve structurally complete and accurate hybrid genome assemblies for public health surveillance. This increases cost and complexity. Previous studies have shown that recent improvements in Nanopore chemistry (R10.4.1 flowcell) and basecalling (super-high accuracy) allow high-quality long-read only assemblies on a small number of laboratory reference strains. This is the first evaluation, to our knowledge, to assess Nanopore long-read only genome assembly compared with hybrid assembly on a large number of clinical isolates. In addition, this is the first large-scale evaluation of the recently released automated consensus long-read assembly tool, Autocycler. We show that Autocycler long-read only assemblies are more structurally complete for chromosomal sequences, while reconstructing a similar number of plasmids to other long-read and hybrid assemblers. Most long-read polished, Autocycler-assembled genome sequences have 0 errors (median: 0 SNPs/indels) relative to a short-read polished (hybrid) Autocycler assemblies, enabling accurate annotation of key genes.

bioinformatics↗

bioRxiv2025

Evolutionary Variation of Poxvirus Genome Architecture

Poxviruses (PXV) are large double-stranded DNA viruses (dsDNA) that infect and cause disease in a wide variety of hosts, including humans.. They are studied as models to understand host-specific disease and they have a wide variety of applications in biotechnology, including vaccines, oncolytic virotherapy, and immunotherapy. Despite a nearly fourfold variation in genome sizes across the Poxviridae family, the basic genome architectural features driving their evolution remain poorly understood. In this study of the summated poxvirus genome sequence database, we report that while only a weak negative correlation exist between viral coding densities and genome sizes, we detected a strong positive correlation between the number of assigned open reading frames (ORF) and genome sizes. We observe an inflection point at a genome size of 229 kb, above or below with the percentage of genes encoding secreted proteins increasing with genome size, and the percentage of predicted cytoplasmic proteins decreasing with genome size. Additionally, we observed a weak positive correlation between the potential of transcript overlap that would be expected to generate dsRNA and genome size. Unexpectedly, we observed a significant positive correlation between coding density and GC-content in mpox virus isolates (R2 = 0.799). Further analysis illustrated a rise in both GC-content and coding density of mpox isolates between 2022 and 2024. Codon usage bias was observed to be clustered by virus families, with tryptophan being the least utilized amino acid across all poxviruses. Protein distribution analysis revealed a right-skewed distribution of poxviral predicted ORFs, with the 150 - 250 amino acid cohort containing the highest number of viral proteins. Finally, we observe a significant positive correlation between ITR sizes and duplicate gene clusters (R2 = 0.679). Together, these architectural findings outline the constraints and adaptive pathways governing poxviral evolution and biology. ImportanceThis study establishes a family genome design rulebook for poxviruses and illustrates how these rules might be linked with their biology and evolution. We demonstrate that genome growth is accompanied by a modest increase in noncoding DNA and an increase in extracellular proteome investment. We further demonstrate that ITR expansions correlate with duplicate gene clusters, rather than genome size, indicating that ITRs serve as hubs of innovation. Our results provide a standard for generating hypotheses and experiments with poxviruses. This work also introduces matrices for within-family viral comparisons.

microbiology↗

bioRxiv2025

Genotype-phenotype modeling of light ecotypes in Prochlorococcusreveals genomic signatures of ecotypic divergence

Prochlorococcus species are the most abundant marine photosynthetic bacteria. Despite broadly shared phenotypic traits and marine habitats, they exhibit remarkable genomic diversity. We ask what genomic signatures underlie its ecotypic divergence into high- and low-light adapted lineages, and whether these signatures can still be recovered from incomplete assemblies. From [~]1,000 publicly available Prochlorococcus genomes, we focused on those with information on their light adaptation ecotype (high-light/low-light), phylogenetic clades, and depth of isolation. Across these divisions, we calculated average nucleotide identity and constructed pangenomes to assess cyanobacterial core genes vs. those that separate ecotypes. Despite scant conservation, we observe a sharp taxon separation by light ecotypes. Classical machine learning models trained to predict ecotype achieve near-perfect binary classification accuracy even when predicting on partial genomes (Matthews Correlation Coefficient = 0.86 - 1.00), while regression models trained to predict the depth of isolation performed poorly, with high root mean square error values (37.6 - 42.0m). For ecotype prediction, we analyzed top gene features across model runs and classes; these features included photosynthesis-associated genes and pathways, as well as many novel markers of unknown function. When separating ecotypes further by previously described phylogenetic clades, genomic content and composition show even clearer separation among clades, supporting the taxonomic breadth of the Prochlorococcus collective. These results emphasize the genomic specialization underlying ecotypic divergence and support the utility of ML approaches for cyanobacterial ecotype prediction from metagenomic data. Expanded sampling will yield novel clade-specific biology. All data, models, and results are available on GitHub: https://github.com/JRaviLab/cyano_adaptation. ImportanceProchlorococcus are common aquatic cyanobacteria that can derive energy from light. They can be classified into high-/low-light ecotypes depending on how they use light. Prochlorococcus have small genomes compared to other bacteria, but the gene sets they carry are also remarkably flexible, which may help them survive and adapt to their harsh oceanic environment. We studied hundreds of Prochlorococcus genomes from around the world in an effort to predict ecotypes from partial genome sequences. We used comparative genomics, machine learning, and other statistical methods to identify genomic features associated with ecotypes. These statistical approaches predicted ecotypes accurately, reliably, and according to large differences in gene content and genome structure. Our results support that Prochlorococcus can be divided into different species or genera based on clades, and provide many gene targets for further research to understand cyanobacterial circadian rhythms or improve their bioengineering potential as chassis organisms.

bioinformatics↗

bioRxiv2018

RNAs as proximity labeling media for identifying nuclear speckle positions relative to the genome

Nuclear speckles are interchromatin structures enriched in RNA splicing factors. Determining their relative positions with respect to the folded nuclear genome could provide critical information on co-and post-transcriptional regulation of gene expression. However, it remains challenging to identify which parts of the nuclear genome are in proximity to nuclear speckles, due to physical separation between nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNAs, 7SK and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA, nuclear speckle associated RNA), may extend to sufficient proximity to the nuclear genome. Leveraging a transcriptome-genome interaction assay (MARGI), we identified nsaRNA-interacting genomic sequences, which exhibited clustering patterns (nsaPeaks) in the genome, suggesting existence of relatively stable interaction sites for nsaRNAs in nuclear genome. Posttranscriptional pre-mRNAs, which are known to be clustered to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Furthermore, CDK9 proteins that localize to the vicinity of nuclear speckles produced ChIP-seq peaks that overlapped with nsaPeaks. Our combined DNA FISH and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs locate in sufficient proximity to nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles.

bioinformatics↗

bioRxiv2018

Homogenization of sub-genome secretome gene expression patterns in the allodiploid fungus Verticillium longisporum

Hybridization is an important evolutionary mechanism that can enable organisms to adapt to environmental challenges. It has previously been shown that the fungal allodiploid species Verticillium longisporum, causal agent of Verticillium stem striping in rape seed, has originated from at least three independent hybridization events between two haploid Verticillium species. To reveal the impact of genome duplication as a consequence of the hybridization, we studied the genome and transcriptome dynamics upon two independent V. longisporum hybridization events, represented by the hybrid lineages "A1/D1" and "A1/D3". We show that the V. longisporum genomes are characterized by extensive chromosomal rearrangements, including between parental chromosomal sets. V. longisporum hybrids display signs of evolutionary dynamics that are typically associated with the aftermath of allodiploidization, such as haploidization and a more relaxed gene evolution. Expression patterns of the two sub-genomes within the two hybrid lineages are more similar than those of the shared A1 parent between the two lineages, showing that expression patterns of the parental genomes homogenized within a lineage. However, as genes that display differential parental expression in planta do not typically display the same pattern in vitro, we conclude that sub-genome-specific responses occur in both lineages. Overall, our study uncovers the genomic and transcriptomic plasticity during evolution of the filamentous fungal hybrid V. longisporum and illustrate its adaptive potential. ImportanceVerticillium is a genus of plant-associated fungi that include a handful of plant pathogens that collectively affect a wide range of hosts. On several occasions, haploid Verticillium species hybridized into the stable allodiploid species Verticillium longisporum, which is, in contrast to haploid Verticillium species, a Brassicaceae specialist. Here, we studied the evolutionary genome and transcriptome dynamics of V. longisporum and the impact of the hybridization. V. longisporum genomes display a mosaic structure due do genomic rearrangements between the parental chromosome sets. Similar to other allopolyploid hybrids, V. longisporum displays an ongoing loss of heterozygosity and a more relaxed gene evolution. Also, differential parental gene expression is observed, with an enrichment for genes that encode secreted proteins. Intriguingly, the majority of these genes displays sub-genome-specific responses under differential growth conditions. In conclusion, hybridization has incited the genomic and transcriptomic plasticity that enables adaptation to environmental changes in a parental allele-specific fashion.

microbiology↗

bioRxiv2018

Definitive demonstration by synthesis of genome annotation completeness

Bacteriophage oX174 was the first DNA genome to be sequenced. The genome is well studied by classical methods and is known to encode 11 essential genes. At least 23 closely-related Bullavirinae genome sequences are now available. We identified 315 potential open reading frames (ORFs) within the genome via bioinformatic analysis, and a subset of 82 highly-conserved ORFs that have no known gene products or functions. Using genome scale design and synthesis we made a mutant genome in which all 11 essential genes are simultaneously disrupted, leaving intact only the 82 conserved-but-cryptic ORFs. The resulting genome is not viable, as expected. Cell-free gene expression followed by mass spectrometry revealed only a single peptide expressed from both the cryptic-ORF and wild-type genomes, suggesting a potential new gene. A second synthetic genome in which 71 conserved cryptic ORFs were simultaneously disrupted is viable but with ~50% reduced fitness relative to the wild type. However, rather than finding any new genes, repeated evolutionary adaptation revealed a single point mutation modulating translation of gene H, a known essential gene, that fully suppressed the fitness defect. Taken together, we conclude that the annotation of ORFs for the oX174 genome is formally complete. Sequencing and bioinformatics followed by synthesis-enabled reverse genomics, proteomics, and evolutionary adaptation can definitely establish the sufficiency and completeness of natural genome annotations.

synthetic biology↗