BEAGLE 3: Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics

Ctenophores and parahoxozoans independently evolved functionally diverse voltage-gated K+ channels

The ctenophore species Mnemiopsis leidyi is known to have a large set of voltage-gated K+ channels, but little is known about the functional diversity of these channels or their evolutionary history in other ctenophore species. Here, we searched the genomes of two additional ctenophore species, Beroe ovata and Hormiphora californensis, for voltage-gated K+ channels and functionally expressed a subset of M. leidyi channels. We found that the last common ancestor of these three disparate ctenophore lineages probably had at least 33 voltage-gated K+ channels. Two of these genes belong to the EAG family, and the remaining 31 belong to the Shaker family and form a single clade within the animal/choanoflagellate Shaker phylogeny. We additionally found evidence for 10 of these Shaker channels in a transcriptome of the early branching ctenophore lineage Euplokamis dunlapae, suggesting that the diversification of these channels was already underway early in ctenophore evolution. We functionally expressed 16 Mnemiopsis Shakers and found that they encode a diverse array of voltage-gated K+ conductances with functional orthologs for many classic Shaker family subtypes found in cnidarians and bilaterians. Analysis of Mnemiopsis transcriptome data show these 16 Shaker channels are expressed in a wide variety of cell types, including neurons, muscle, comb cells, and colloblasts. Ctenophores therefore appear to have independently evolved much of the voltage-gated K+ channel diversity that is shared between cnidarians and bilaterians.

Island geography drives evolution of rattan palms in tropical Asian rainforests

Distributed across two continents and thousands of islands, the Asian tropics are among the most species-rich areas on Earth. The origins of this diversity, however, remain poorly understood. Here, we reveal and classify contributions of individual tropical Asian regions to their overall diversity by leveraging species-level phylogenomic data and new fossils from the most species-rich Asian palm lineage, the rattans and relatives (Arecaceae, Calamoideae). Radiators (Borneo) generate and distribute diversity, incubators (Indochina, New Guinea, and Sulawesi) produce diversity in isolation, corridors (Java, Maluku, Sumatra, and the Thai-Malay Peninsula) connect neighboring regions, and accumulators (Australia, India, Palawan, and the Philippines) acquire diversity generated elsewhere. These contrasting contributions can be explained by differences in region size and isolation, elucidating how the unique island-dominated geography of the Asian tropics drives their outstanding biodiversity.

Cross-species and mammal-to-mammal transmission of clade 2.3.4.4b highly pathogenic avian influenza A/H5N1 with PB2 adaptations

Highly pathogenic H5N1 avian influenza viruses (HPAIV) belonging to lineage 2.3.4.4b emerged in Chile in December 2022, leading to mass mortality events in wild birds, poultry, and marine mammals and one human case. We detected HPAIV in 7,33% (714/9745) of cases between December 2022-April 2023 and sequenced 177 H5N1 virus genomes from poultry, marine mammals, a human, and wild birds spanning >3800 km of Chilean coastline. Chilean viruses were closely related to Peru's H5N1 outbreak, consistent with north-to-south spread down the Pacific coastline. One human virus and nine marine mammal viruses in Chile had the rare PB2 D701N mammalian-adaptation mutation and clustered phylogenetically despite being sampled 5 weeks and hundreds of kilometers apart. These viruses shared additional genetic signatures, including another mammalian PB2 adaptation (Q591K, n = 6), synonymous mutations, and minor variants. Several mutations were detected months later in sealions in the Atlantic coast, indicating that the pinniped outbreaks on the west and east coasts of South America are genetically linked. These data support sustained mammal-to-mammal transmission of HPAIV in marine mammals over thousands of kilometers of Chile's Pacific coastline, which subsequently continued through the Atlantic coastline.

Genomic surveillance and evolution of Getah virus

Getah virus (GETV), a member of the Alphaviruses, has spread widely and is expanding its host range worldwide, posing a serious threat to public health safety and the farming industry. However, genetic monitoring of GETV is inadequate, and its evolution and transmission remain unclear. This study employed reverse transcription-polymerase chain reaction to screen pig tissue samples for the presence of GETV. Subsequent steps included DNA sequencing, phylogenetic analysis, and selection pressure assessments to elucidate the evolutionary history and transmission patterns of the virus. A total of 1382 samples were examined, with a positivity rate of 4.12% (95% confidence interval: 3.07%-5.17%) from 2022 to 2023. Subsequently, seven GETV strains were isolated and identified. A phylogenetic tree was constructed, which showed that all seven strains belonged to Group III. Phylodynamic analysis revealed that GETV evolved rapidly. Additionally, eight amino acid sites within the GETV E2 protein were identified as being under positive selection. These data provide insight into the epidemiology and evolution of GETV.

Dispersal dynamics and introduction patterns of SARS-CoV-2 lineages in Iran

Understanding the dispersal patterns of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) lineages is crucial to public health decision-making, especially in countries with limited access to viral genomic sequencing. This study provides a comprehensive epidemiological and phylodynamic perspective on SARS-CoV-2 lineage dispersal in Iran from February 2020 to July 2022. We explored the genomic epidemiology of SARS-CoV-2 combining 1281 genome sequences with spatial data in a phylogeographic framework. Our analyses shed light on multiple international imports seeding subsequent waves and on domestic dispersal dynamics. Lineage B.4 was identified to have been circulating in Iran, 29 days (95% highest probability density interval: 21-47) before non-pharmaceutical interventions were implemented. The importation dynamics throughout subsequent waves were primarily driven from the country or region where the variant was first reported and gradually shifted to other regions. At the national level, Tehran was the main source of dissemination across the country. Our study highlights the crucial role of continuous genomic surveillance and international collaboration for future pandemic preparedness and efforts to control viral transmission.

Disruption of seasonal influenza circulation and evolution during the 2009 H1N1 and COVID-19 pandemics in Southeastern Asia

East, South, and Southeast Asia (together referred to as Southeastern Asia hereafter) have been recognized as critical areas fuelling the global circulation of seasonal influenza. However, the seasonal influenza migration network within Southeastern Asia remains unclear, including how pandemic-related disruptions altered this network. We leveraged genetic, epidemiological, and airline travel data between 2007-2023 to characterise the dispersal patterns of influenza A/H3N2 and B/Victoria viruses both out of and within Southeastern Asia, including during perturbations by the 2009 A/H1N1 and COVID-19 pandemics. During the COVID-19 pandemic, consistent autumn-winter movement waves from Southeastern Asia to temperate regions were interrupted for both subtype/lineages, however the A/H1N1 pandemic only disrupted A/H3N2 spread. We find a higher persistence of A/H3N2 than B/Victoria circulation in Southeastern Asia and identify distinct pandemic-related disruptions in A/H3N2 antigenic evolution between two pandemics, compared to interpandemic levels; similar patterns are observed in B/Victoria using genetic distance. The internal movement structure within Southeastern Asia markedly diverged during the COVID-19 pandemic season, and to a lesser extent, during the 2009 A/H1N1 pandemic season. Our findings provide insights into the heterogeneous impact of two distinct pandemic-related disruptions on influenza circulation, which can help anticipate the effects of future pandemics and potential mitigation strategies on influenza dynamics.

Learning the fitness dynamics of pathogens from phylogenies

The dynamics of the genetic diversity of pathogens, including the emergence of lineages with increased fitness, is a foundational concept of disease ecology with key public-health implications. However, the identification of such lineages and estimation of associated fitness remain challenging, and is rarely done outside densely sampled systems1,2. Here we present phylowave, a scalable approach that summarizes changes in population composition in phylogenetic trees, enabling the automatic detection of lineages based on shared fitness and evolutionary relationships. We use our approach on a broad set of viruses and bacteria (SARS-CoV-2, influenza A subtype H3N2, Bordetella pertussis and Mycobacterium tuberculosis), which include both well-studied and understudied threats to human health. We show that phylowave recovers the main known circulating lineages for each pathogen and that it can detect specific amino acid changes linked to fitness changes. Furthermore, phylowave identifies previously undetected lineages with increased fitness, including three co-circulating B. pertussis lineages. Inference using phylowave is robust to uneven and limited observations. This widely applicable approach provides an avenue to monitor evolution in real time to support public-health action and explore fundamental drivers of pathogen fitness.

Evolution of SARS-CoV-2 in white-tailed deer in Pennsylvania 2021-2024

SARS-CoV-2 continues to transmit and evolve in humans and animals. White-tailed deer (Odocoileus virginianus) have been previously identified as a zoonotic reservoir for SARS-CoV-2 with high rates of infection and probable spillback into humans. Here we report sampling 1,127 white-tailed deer (WTD) in Pennsylvania, and a genomic analysis of viral dynamics spanning 1,017 days between April 2021 and January 2024. To assess viral load and genotypes, RNA was isolated from retropharyngeal lymph nodes and analyzed using RT-qPCR and viral whole genome sequencing. Samples showed a 14.64% positivity rate by RT-qPCR. Analysis showed no association of SARS-CoV-2 prevalence with age, sex, or diagnosis with Chronic Wasting Disease. From the 165 SARS-CoV-2 positive WTD, we recovered 25 whole genome sequences and an additional 17 spike-targeted amplicon sequences. The viral variants identified included 17 Alpha, 11 Delta, and 14 Omicron. Alpha largely stopped circulating in humans around September 2021, but persisted in WTD as recently as March of 2023. Phylodynamic analysis of pooled genomic data from Pennsylvania documents at least 12 SARS-CoV-2 spillovers from humans into WTD, including a recent series of Omicron spillovers. Prevalence was higher in WTD in regions with crop coverage rather than forest, suggesting an association with proximity to humans. Analysis of seasonality showed increased prevalence in winter and spring. Multiple examples of recurrent mutations were identified associated with transmissions, suggesting WTD-specific evolutionary pressures. These data document ongoing infections in white-tailed deer, probable onward transmission in deer, and a remarkable rate of new spillovers from humans.

Human outbreaks of a novel reassortant Oropouche virus in the Brazilian Amazon region

The Brazilian western Amazon is experiencing its largest laboratory-confirmed Oropouche virus (OROV) outbreak, with more than 6,300 reported cases between 2022 and 2024. In this study, we sequenced and analyzed 382 OROV genomes from human samples collected in Amazonas, Acre, Rondônia and Roraima states, between August 2022 and February 2024, to uncover the origin and genetic evolution of OROV in the current outbreak. Genomic analyses revealed that the upsurge of OROV cases in the Brazilian Amazon coincides with spread of a novel reassortant lineage containing the M segment of viruses detected in the eastern Amazon region (2009-2018) and the L and S segments of viruses detected in Peru, Colombia and Ecuador (2008-2021). The novel reassortant likely emerged in the Amazonas state between 2010 and 2014 and spread through long-range dispersion events during the second half of the 2010s. Phylodynamics reconstructions showed that the current OROV spread was driven mainly by short-range (< 2 km) movements consistent with the flight range of vectors. Nevertheless, a substantial proportion (22%) of long-range (>10 km) OROV migrations were also detected, consistent with viral dispersion by humans. Our data provide a view of the unprecedented spread and evolution of OROV in the Brazilian western Amazon region.

Reticulate evolution: Detection and utility in the phylogenomics era

Phylogenomics has enriched our understanding that the Tree of Life can have network-like or reticulate structures among some taxa and genes. Two non-vertical modes of evolution - hybridization/introgression and horizontal gene transfer - deviate from a strictly bifurcating tree model, causing non-treelike patterns. However, these reticulate processes can produce similar patterns to incomplete lineage sorting or recombination, potentially leading to ambiguity. Here, we present a brief overview of a phylogenomic workflow for inferring organismal histories and compare methods for distinguishing modes of reticulate evolution. We discuss how the timing of coalescent events can help disentangle introgression from incomplete lineage sorting and how horizontal gene transfer events can help determine the relative timing of speciation events. In doing so, we identify pitfalls of certain methods and discuss how to extend their utility across the Tree of Life. Workflows, methods, and future directions discussed herein underscore the need to embrace reticulate evolutionary patterns for understanding the timing and rates of evolutionary events, providing a clearer view of life's history.

Comparative Evolutionary Epidemiology of SARS-CoV-2 Delta and Omicron Variants in Kuwait

Continuous surveillance is critical for early intervention against emerging novel SARS-CoV-2 variants. Therefore, we investigated and compared the variant-specific evolutionary epidemiology of all the Delta and Omicron sequences collected between 2021 and 2023 in Kuwait. We used Bayesian phylodynamic models to reconstruct, trace, and compare the two variants' demographics, phylogeographic, and host characteristics in shaping their evolutionary epidemiology. The Omicron had a higher evolutionary rate than the Delta. Both variants underwent periods of sequential growth and decline in their effective population sizes, likely linked to intervention measures and environmental and host characteristics. We found that the Delta strains were frequently introduced into Kuwait from East Asian countries between late 2020 and early 2021, while those of the Omicron strains were most likely from Africa and North America between late 2021 and early 2022. For both variants, our analyses revealed significant transmission routes from patients aged between 20 and 50 years on one side and other age groups, refuting the notion that children are superspreaders for the disease. In contrast, we found that sex has no significant role in the evolutionary history of both variants. We uncovered deeper variant-specific epidemiological insights using phylodynamic models and highlighted the need to integrate such models into current and future genomic surveillance programs.

Genomic analysis of the early COVID-19 pandemic in Haiti reveals Caribbean-specific variant dynamics

Pathogen sequencing during the COVID-19 pandemic has generated more whole genome sequencing data than for any other epidemic, allowing epidemiologists to monitor the transmission and evolution of SARS-CoV-2. However, large parts of the world are heavily underrepresented in sequencing efforts, including the Caribbean islands. We performed genome sequencing of SARS-CoV-2 from upper respiratory tract samples collected in Haiti during the spring of 2020. We used phylogenetic analysis to assess the pandemic dynamics in the Caribbean region and observed that the epidemic in Haiti was seeded by multiple introductions, primarily from the United States. We identified the emergence of a SARS-CoV-2 lineage (B.1.478) from Haiti that spread into North America, as well as evidence of the undocumented spread of SARS-CoV-2 within the Caribbean. We demonstrate that the genomic analysis of a relatively modest number of samples from a severely under-sampled region can provide new insight on a previously unobserved spread of a specific lineage, demonstrating the importance of geographically widespread genomic epidemiology.

Analyses of Xenorhabdus griffiniae genomes reveal two distinct sub-species that display intra-species variation due to prophages

BACKGROUND

Nematodes of the genus Steinernema and their Xenorhabdus bacterial symbionts are lethal entomopathogens that are useful in the biocontrol of insect pests, as sources of diverse natural products, and as research models for mutualism and parasitism. Xenorhabdus play a central role in all aspects of the Steinernema lifecycle, and a deeper understanding of their genomes therefore has the potential to spur advances in each of these applications.

RESULTS

Here, we report a comparative genomics analysis of Xenorhabdus griffiniae, including the symbiont of Steinernema hermaphroditum nematodes, for which genetic and genomic tools are being developed. We sequenced and assembled circularized genomes for three Xenorhabdus strains: HGB2511, ID10 and TH1. We then determined their relationships to other Xenorhabdus and delineated their species via phylogenomic analyses, concluding that HGB2511 and ID10 are Xenorhabdus griffiniae while TH1 is a novel species. These additions to the existing X. griffiniae landscape further allowed for the identification of two subspecies within the clade. Consistent with other Xenorhabdus, the analysed X. griffiniae genomes each encode a wide array of antimicrobials and virulence-related proteins. Comparative genomic analyses, including the creation of a pangenome, revealed that a large amount of the intraspecies variation in X. griffiniae is contained within the mobilome and attributable to prophage loci. In addition, CRISPR arrays, secondary metabolite potential and toxin genes all varied among strains within the X. griffiniae species.

CONCLUSIONS

Our findings suggest that phage-related genes drive the genomic diversity in closely related Xenorhabdus symbionts, and that these may underlie some of the traits most associated with the lifestyle and survival of entomopathogenic nematodes and their bacteria: virulence and competition. This study establishes a broad knowledge base for further exploration of not only the relationships between X. griffiniae species and their nematode hosts but also the molecular mechanisms that underlie their entomopathogenic lifestyle.

Whole-genome sequencing reveals genetic structure and adaptive genes in Nepalese buffalo breeds

BACKGROUND

Indigenous buffaloes, as the important livestock species contributing to economy of the country, are the lifeline of livelihood in Nepal. They are distributed across diverse geographical regions of the country and have adapted to various feeding, breeding, and management conditions. The larger group of these native buffalo breeds are present in narrow and stiff hilly terrains. Their dispersal indicates a possible environmental adaptation mechanism, which is crucial for the conservation of these breeds.

RESULTS

We utilized whole-genome sequencing (WGS) to investigate the genetic diversity, population structure, and selection signatures of Nepalese indigenous buffaloes. We compared 66 whole-genome sequences with 118 publicly available sequences from six river and five swamp buffalo breeds. Genomic diversity parameters indicated genetic variability level in the Nepalese buffaloes comparable to those of Indian breeds, and population genetic structure revealed distinct geography-mediated genetic differentiation among these breeds. We used locus-specific branch length analysis (LSBL) for genome-wide scan, which revealed a list of potentially selected genes in Lime and Parkote breeds that inhabit the hilly region. A gene ontology (GO) analysis discovered that many GO terms were associated with cardiac function regulation. Furthermore, complementary analyses of local selection signatures, tissue expression profiles, and haplotype differences identified candidate genes, including KCNE1, CSF1R, and PDGFRB, related to the regulation of cardiac and pulmonary functions.

CONCLUSIONS

This study is a comprehensive WGS-based genetic analysis of the native Nepalese buffalo breeds. Our study suggested that the Nepalese "hilly" buffaloes, especially the Lime and Parkote breeds, have undergone some characteristic genetic changes and evolved increased cardiac and pulmonary function for their adaptation to the steep hilly terrains of the country.

Epidemiological data of an influenza A/H5N1 outbreak in elephant seals in Argentina indicates mammal-to-mammal transmission

H5N1 high pathogenicity avian influenza virus has killed thousands of marine mammals in South America since 2022. Here we report epidemiological data and full genome characterization of clade 2.3.4.4b H5N1 HPAI viruses associated with a massive outbreak in southern elephant seals (Mirounga leonina) at Península Valdés, Argentina, in October 2023. We also report on H5N1 viruses in concurrently dead terns. Our genomic analysis shows that viruses from pinnipeds and terns in Argentina form a distinct clade with marine mammal viruses from Peru, Chile, Brazil and Uruguay. Additionally, these marine mammal clade viruses share an identical set of mammalian adaptation mutations which were also present in tern viruses. Our combined ecological and phylogenetic data support mammal-to-mammal transmission and occasional mammal-to-bird spillover and suggest multinational transmission of H5N1 viruses in mammals. We reflect that H5N1 viruses becoming more evolutionary flexible and adapting to mammals in new ways could have global consequences for wildlife, humans, and/or livestock.

COVID-19 pandemic interventions reshaped the global dispersal of seasonal influenza viruses

The global dynamics of seasonal influenza viruses inform the design of surveillance, intervention, and vaccination strategies. The COVID-19 pandemic provided a singular opportunity to evaluate how influenza circulation worldwide was perturbed by human behavioral changes. We combine molecular, epidemiological, and international travel data and find that the pandemic's onset led to a shift in the intensity and structure of international influenza lineage movement. During the pandemic, South Asia played an important role as a phylogenetic trunk location of influenza A viruses, whereas West Asia maintained the circulation of influenza B/Victoria. We explore drivers of influenza lineage dynamics across the pandemic period and reasons for the possible extinction of the B/Yamagata lineage. After a period of 3 years, the intensity of among-region influenza lineage movements returned to pre-pandemic levels, with the exception of B/Yamagata, after the recovery of global air traffic, highlighting the robustness of global lineage dispersal patterns to substantial perturbation.

From emergence to endemicity of highly pathogenic H5 avian influenza viruses in Taiwan

A/goose/Guangdong/1/96-like (GsGd) highly pathogenic avian influenza (HPAI) H5 viruses cause severe outbreaks in poultry when introduced. Since emergence in 1996, control measures in most countries have suppressed local GsGd transmission following introductions, making persistent transmission in domestic birds rare. However, geographical expansion of clade 2.3.4.4 sublineages has raised concern about establishment of endemic circulation, while mechanistic drivers leading to endemicity remain unknown. We reconstructed the evolutionary history of GsGd sublineage, clade 2.3.4.4c, in Taiwan using a time-heterogeneous rate phylogeographic model. During Taiwan's initial epidemic wave (January 2015 - August 2016), we inferred that localised outbreaks had multiple origins from rapid spread between counties/cities nationwide. Subsequently, outbreaks predominantly originated from a single county, Yunlin, where persistent transmission harbours the trunk viruses of the sublineage. Endemic hotspots determined by phylogeographic reconstruction largely predicted the locations of re-emerging outbreaks in Yunlin. The transition to endemicity involved a shift to chicken-dominant circulation, following the initial bidirectional spread between chicken and domestic waterfowl. Our results suggest that following their emergence in Taiwan, source-sink dynamics from a single county have maintained GsGd endemicity up until 2023, pointing to where control efforts should be targeted to eliminate the disease.

Untangling lineage introductions, persistence and transmission drivers of HP-PRRSV sublineage 8.7

Despite a rapid expansion of Porcine reproductive and respiratory syndrome virus (PRRSV) sublineage 8.7 over recent years, very little is known about the patterns of virus evolution, dispersal, and the factors influencing this dispersal. Relying on a national PRRSV surveillance project established over 20 years ago, we expand the available genomic data of sublineage 8.7 from China. We perform independent interlineage and intralineage recombination analyses for the entire study period, which showed a heterogeneous recombination pattern. A series of Bayesian phylogeographic analyses uncover the role of Guangdong as an important infection hub within Asia. The spatial spread of PRRSV is highly linked with a composite of human activities and the heterogeneous provincial distribution of the swine industry, largely propelled by the smaller-scale Chinese rural farming systems in the past years. We sequence all four available modified live vaccines (MLVs) and perform genomic analyses with publicly available data, of which our results suggest a key "leaky" period spanning 2011-2017 with two concurrent amino acid mutations in ORF1a 957 and ORF2 250. Overall, our study provides an in-depth overview of the evolution, transmission dynamics, and potential leaky status of HP-PRRS MLVs, providing critical insights into new MLV development.

Sustained human outbreak of a new MPXV clade I lineage in eastern Democratic Republic of the Congo

Outbreaks of monkeypox (mpox) have historically resulted from zoonotic spillover of clade I monkeypox virus (MPXV) in Central Africa and clade II MPXV in West Africa. In 2022, subclade IIb caused a global epidemic linked to transmission through sexual contact. Here we describe the epidemiological and genomic features of an mpox outbreak in a mining region in eastern Democratic Republic of the Congo, caused by clade I MPXV. Surveillance data collected between September 2023 and January 2024 identified 241 suspected cases. Genomic analysis demonstrates a distinct clade I lineage divergent from previously circulating strains in the Democratic Republic of the Congo. Of the 108 polymerase chain reaction-confirmed mpox cases, the median age of individuals was 22 years, 51.9% were female and 29% were sex workers, suggesting a potential role for sexual transmission. The predominance of APOBEC3-type mutations and the estimated emergence time around mid-September 2023 imply recent sustained human-to-human transmission.

Identification and characterization of new Siberian subtype of tick-borne encephalitis virus isolates revealed genetic variations of the Chinese strains

Tick-borne encephalitis virus (TBEV) is a pathogen that causes febrile infectious diseases and neurological damage to humans. TBEVs are prevalent from Europe to Far Eastern Asia, including Northeastern China. The understanding of TBEV phylogeny in China has been limited owing to insufficient genomic data on Chinese TBEV strains. Here, six TBEV strains were isolated from ticks collected in Inner Mongolia. The transmission electron microscopy revealed spherical particles with an enveloped structure of 50-60 nm in diameter. Phylogenetic analysis showed that, two strains were classified as the Siberian subtype, while the remaining four were identified as the Far Eastern subtype. Migration analyses based on TBEV ORF and envelope (E) protein sequences revealed that Chinese TBEV strains were migrated from Russia and/or Kazakhstan into China. Hulun Buir and Mudanjiang, the northeastern region of China, are considered hotspots with multiple import and export routes of Chinese TBEV strains. These results promote the understanding of TBEV genetic variations and phylogeny in China and suggest the importance of improving investigation of TBEV prevalence, which would instrumental for vaccine design strategies and better preparation for controlling TBEV infection in humans.

Bioinformatics Goes Viral: I. Databases, Phylogenetics and Phylodynamics Tools for Boosting Virus Research

Computer-aided analysis of proteins or nucleic acids seems like a matter of course nowadays; however, the history of Bioinformatics and Computational Biology is quite recent. The advent of high-throughput sequencing has led to the production of "big data", which has also affected the field of virology. The collaboration between the communities of bioinformaticians and virologists already started a few decades ago and it was strongly enhanced by the recent SARS-CoV-2 pandemics. In this article, which is the first in a series on how bioinformatics can enhance virus research, we show that highly useful information is retrievable from selected general and dedicated databases. Indeed, an enormous amount of information-both in terms of nucleotide/protein sequences and their annotation-is deposited in the general databases of international organisations participating in the International Nucleotide Sequence Database Collaboration (INSDC). However, more and more virus-specific databases have been established and are progressively enriched with the contents and features reported in this article. Since viruses are intracellular obligate parasites, a special focus is given to host-pathogen protein-protein interaction databases. Finally, we illustrate several phylogenetic and phylodynamic tools, combining information on algorithms and features with practical information on how to use them and case studies that validate their usefulness. Databases and tools for functional inference will be covered in the next article of this series: Bioinformatics goes viral: II. Sequence-based and structure-based functional analyses for boosting virus research.

Random-Effects Substitution Models for Phylogenetics via Scalable Gradient Approximations

Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time Markov chain models into a richer class of processes capable of capturing a wider variety of substitution dynamics. As these random-effects substitution models often require many more parameters than their usual counterparts, inference can be both statistically and computationally challenging. Thus, we also propose an efficient approach to compute an approximation to the gradient of the data likelihood with respect to all unknown substitution model parameters. We demonstrate that this approximate gradient enables scaling of sampling-based inference, namely Bayesian inference via Hamiltonian Monte Carlo, under random-effects substitution models across large trees and state-spaces. Applied to a dataset of 583 SARS-CoV-2 sequences, an HKY model with random-effects shows strong signals of nonreversibility in the substitution process, and posterior predictive model checks clearly show that it is a more adequate model than a reversible model. When analyzing the pattern of phylogeographic spread of 1441 influenza A virus (H3N2) sequences between 14 regions, a random-effects phylogeographic substitution model infers that air travel volume adequately predicts almost all dispersal rates. A random-effects state-dependent substitution model reveals no evidence for an effect of arboreality on the swimming mode in the tree frog subfamily Hylinae. Simulations reveal that random-effects substitution models can accommodate both negligible and radical departures from the underlying base substitution model. We show that our gradient-based inference approach is over an order of magnitude more time efficient than conventional approaches.

Cryptic transmission and novel introduction of Dengue 1 and 2 genotypes in Colombia

Dengue fever remains as a public health challenge in Colombia, standing as the most prevalent infectious disease in the country. The cyclic nature of dengue epidemics, occurring approximately every 3 years, is intricately linked to meteorological events like El Niño Southern Oscillation (ENSO). Therefore, the Colombian system faces challenges in genomic surveillance. This study aimed to evaluate local dengue virus (DENV) transmission and genetic diversity in four Colombian departments with heterogeneous incidence patterns (department is first-level territorial units in Colombia). For this study, we processed 266 serum samples to identify DENV. Subsequently, we obtained 118 genome sequences by sequencing DENV genomes from serum samples of 134 patients infected with DENV-1 and DENV-2 serotypes. The predominant serotype was DENV-2 (108/143), with the Asian-American (AA) genotype (91/118) being the most prevalent one. Phylogenetic analysis revealed concurrent circulation of two lineages of both DENV-2 AA and DENV-1 V, suggesting ongoing genetic exchange with sequences from Venezuela and Cuba. The continuous migration of Venezuelan citizens into Colombia can contribute to this exchange, emphasizing the need for strengthened prevention measures in border areas. Notably, the time to most recent common ancestor analysis identified cryptic transmission of DENV-2 AA since approximately 2015, leading to the recent epidemic. This challenges the notion that major outbreaks are solely triggered by recent virus introductions, emphasizing the importance of active genomic surveillance. The study also highlighted the contrasting selection pressures on DENV-1 V and DENV-2 AA, with the latter experiencing positive selection, possibly influencing its transmissibility. The presence of a cosmopolitan genotype in Colombia, previously reported in Brazil and Peru, raises concerns about transmission routes, emphasizing the necessity for thorough DENV evolution studies. Despite limitations, the study underscores genomic epidemiology's crucial role in early detection and comprehension of DENV genotypes, recommending the use of advanced sequencing techniques as an early warning system to help prevent and control dengue outbreaks in Colombia and worldwide.

Ecological Changes Exacerbating the Spread of Invasive Ticks has Driven the Dispersal of Severe Fever with Thrombocytopenia Syndrome Virus Throughout Southeast Asia

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne virus recognized by the World Health Organization as an emerging infectious disease of growing concern. Utilizing phylodynamic and phylogeographic methods, we have reconstructed the origin and transmission patterns of SFTSV lineages and the roles demographic, ecological, and climatic factors have played in shaping its emergence and spread throughout Asia. Environmental changes and fluctuations in tick populations, exacerbated by the widespread use of pesticides, have contributed significantly to its geographic expansion. The increased adaptability of Lineage L2 strains to the Haemaphysalis longicornis vector has facilitated the dispersal of SFTSV through Southeast Asia. Increased surveillance and proactive measures are needed to prevent further spread to Australia, Indonesia, and North America.

Bayesian Phylogenetic Analysis on Multi-Core Compute Architectures: Implementation and Evaluation of BEAGLE in RevBayes With MPI

Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets-with many taxa and/or many sites in the sequence alignment-or complex substitutions models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time. To address this bottleneck, we incorporated the high-performance phylogenetic library BEAGLE into RevBayes, which enables multi-threading on multi-core CPUs and GPUs, as well as hardware specific vectorized instructions for faster likelihood calculations. Our new implementation of RevBayes+BEAGLE retains the flexibility and dynamic nature that users expect from vanilla RevBayes. In addition, we implemented native parallelization within RevBayes without an external library using the message passing interface (MPI); RevBayes+MPI. We evaluated our new implementation of RevBayes+BEAGLE using multi-threading on CPUs and 2 different powerful GPUs (NVidia Titan V and NVIDIA A100) against our native implementation of RevBayes+MPI. We found good improvements in speedup when multiple cores were used, with up to 20-fold speedup when using multiple CPU cores and over 90-fold speedup when using multiple GPU cores. The improvement depended on the data type used, DNA or amino acids, and the size of the alignment, but less on the size of the tree. We additionally investigated the cost of rescaling partial likelihoods to avoid numerical underflow and showed that unnecessarily frequent and inefficient rescaling can increase runtimes up to 4-fold. Finally, we presented and compared a new approach to store partial likelihoods on branches instead of nodes that can speed up computations up to 1.7 times but comes at twice the memory requirements.

Levels of Airborne Sound And Substrate-borne Vibration Calling Are Negatively Related Across Neotropical False-leaf Katydids

Animals often signal in multiple sensory modalities to attract mates, but the level of signaling investment in each modality can differ dramatically between individuals and across species. When functionally overlapping signals are produced in different modalities, their relative use can be influenced by many factors, including differences in signal active space, energetic costs, and predation risk. Characterizing differences in total signal investment across time can shed light on these factors, but requires long focal recordings of signal production. Neotropical pseudophylline katydids produce mate advertisement signals as airborne sound and substrate-borne vibration. Airborne calls, produced via stridulation, are extremely short, high-frequency, and longer-range signals. Conversely, substrate-borne calls produced via abdominal tremulation are longer, low-frequency, relatively more energetically costly, and shorter-range signals. To examine patterns of stridulation and tremulation across species and test hypotheses about the drivers of signal use in each modality, we recorded multimodal signaling activity over 24 hours for males from 10 pseudophylline species from a single Panamanian community. We also collected data on demographic and morphological species characteristics, and acoustic features of airborne calls, such as bandwidth, peak frequency, and duration. Finally, we generated a molecular phylogeny for these species and used phylogenetic generalized least squares models to test for relationships between variables while controlling for evolutionary relationships. We found a negative relationship between sound and vibration calling, indicating that substrate-borne vibrational signaling may compensate for reduced airborne signaling in these species. Sound call bandwidth and the proportion of males collected at lights, a proxy for the amount of male movement, also explained a significant amount of variation in sound calling across species, indicating that the overall relationship between the two types of calling signals may be mediated by the specific characteristics of the signals as well as other species traits.

A broad survey of choanoflagellates revises the evolutionary history of the Shaker family of voltage-gated K+ channels in animals

The Shaker family of voltage-gated K+ channels has been thought of as an animal-specific ion channel family that diversified in concert with nervous systems. It comprises four functionally independent gene subfamilies (Kv1-4) that encode diverse neuronal K+ currents. Comparison of animal genomes predicts that only the Kv1 subfamily was present in the animal common ancestor. Here, we show that some choanoflagellates, the closest protozoan sister lineage to animals, also have Shaker family K+ channels. Choanoflagellate Shaker family channels are surprisingly most closely related to the animal Kv2-4 subfamilies which were believed to have evolved only after the divergence of ctenophores and sponges from cnidarians and bilaterians. Structural modeling predicts that the choanoflagellate channels share a T1 Zn2+ binding site with Kv2-4 channels that is absent in Kv1 channels. We functionally expressed three Shakers from Salpingoeca helianthica (SheliKvT1.1-3) in Xenopus oocytes. SheliKvT1.1-3 function only in two heteromultimeric combinations (SheliKvT1.1/1.2 and SheliKvT1.1/1.3) and encode fast N-type inactivating K+ channels with distinct voltage dependence that are most similar to the widespread animal Kv1-encoded A-type Shakers. Structural modeling of the T1 assembly domain supports a preference for heteromeric assembly in a 2:2 stoichiometry. These results push the origin of the Shaker family back into a common ancestor of metazoans and choanoflagellates. They also suggest that the animal common ancestor had at least two distinct molecular lineages of Shaker channels, a Kv1 subfamily lineage predicted from comparison of animal genomes and a Kv2-4 lineage predicted from comparison of animals and choanoflagellates.

GeCKO: user-friendly workflows for genotyping complex genomes using target enrichment capture. A use case on the large tetraploid durum wheat genome

BACKGROUND

Genotyping of individuals plays a pivotal role in various biological analyses, with technology choice influenced by multiple factors including genomic constraints, number of targeted loci and individuals, cost considerations, and the ease of sample preparation and data processing. Target enrichment capture of specific polymorphic regions has emerged as a flexible and cost-effective genomic reduction method for genotyping, especially adapted to the case of very large genomes. However, this approach necessitates complex bioinformatics treatment to extract genotyping data from raw reads. Existing workflows predominantly cater to phylogenetic inference, leaving a gap in user-friendly tools for genotyping analysis based on capture methods. In response to these challenges, we have developed GeCKO (Genotyping Complexity Knocked-Out). To assess the effectiveness of combining target enrichment capture with GeCKO, we conducted a case study on durum wheat domestication history, involving sequencing, processing, and analyzing variants in four relevant durum wheat groups.

RESULTS

GeCKO encompasses four distinct workflows, each designed for specific steps of genomic data processing: (i) read demultiplexing and trimming for data cleaning, (ii) read mapping to align sequences to a reference genome, (iii) variant calling to identify genetic variants, and (iv) variant filtering. Each workflow in GeCKO can be easily configured and is executable across diverse computational environments. The workflows generate comprehensive HTML reports including key summary statistics and illustrative graphs, ensuring traceable, reproducible results and facilitating straightforward quality assessment. A specific innovation within GeCKO is its 'targeted remapping' feature, specifically designed for efficient treatment of targeted enrichment capture data. This process consists of extracting reads mapped to the targeted regions, constructing a smaller sub-reference genome, and remapping the reads to this sub-reference, thereby enhancing the efficiency of subsequent steps.

CONCLUSIONS

The case study results showed the expected intra-group diversity and inter-group differentiation levels, confirming the method's effectiveness for genotyping and analyzing genetic diversity in species with complex genomes. GeCKO streamlined the data processing, significantly improving computational performance and efficiency. The targeted remapping enabled straightforward SNP calling in durum wheat, a task otherwise complicated by the species' large genome size. This illustrates its potential applications in various biological research contexts.

Dispersal history of SARS-CoV-2 variants Alpha, Delta, and Omicron (BA.1) in Spain

Different factors influence the spread of SARS-CoV-2, from the inherent transmission capabilities of the different variants to the control measurements put in place. Here we studied the introduction of the Alpha, Delta, and Omicron-BA.1 variants of concern (VOCs) into Spain. For this, we collected genomic data from the GISAID database and combined it with connectivity data from different countries with Spain to perform a phylodynamic Bayesian analysis of the introductions. Our findings reveal that the introductions of these VOCs predominantly originated from France, especially in the case of Alpha. As travel restrictions were eased during the Delta and Omicron-BA.1 waves, the number of introductions from distinct countries increased, with the United Kingdom and Germany becoming significant sources of the virus. The largest number of introductions detected corresponded to the Delta wave, which was associated with fewer restrictions and the summer period, when Spain receives a considerable number of tourists. This research underscores the importance of monitoring international travel patterns and implementing targeted public health measures to manage the spread of SARS-CoV-2.

Dispersal history of SARS-CoV-2 in Galicia, Spain

The dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron-BA.1 variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the United States became increasingly significant. The number of detected introductions varied from 96 and 101 for Alpha and Delta to 39 for Omicron-BA.1. Most of these introductions left a low number of descendants (<10), suggesting a limited impact on the evolution of the pandemic in Galicia. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Molecular epidemiology of recurrent zoonotic transmission of mpox virus in West Africa

Nigeria and Cameroon reported their first mpox cases in over three decades in 2017 and 2018 respectively. The outbreak in Nigeria is recognised as an ongoing human epidemic. However, owing to sparse surveillance and genomic data, it is not known whether the increase in cases in Cameroon is driven by zoonotic or sustained human transmission. Notably, the frequency of zoonotic transmission remains unknown in both Cameroon and Nigeria. To address these uncertainties, we investigated the zoonotic transmission dynamics of the mpox virus (MPXV) in Cameroon and Nigeria, with a particular focus on the border regions. We show that in these regions mpox cases are still driven by zoonotic transmission of a newly identified Clade IIb.1. We identify two distinct zoonotic lineages that circulate across the Nigeria-Cameroon border, with evidence of recent and historic cross border dissemination. Our findings support that the complex cross-border forest ecosystems likely hosts shared animal populations that drive cross-border viral spread, which is likely where extant Clade IIb originated. We identify that the closest zoonotic outgroup to the human epidemic circulated in southern Nigeria in October 2013. We also show that the zoonotic precursor lineage circulated in an animal population in southern Nigeria for more than 45 years. This supports findings that southern Nigeria was the origin of the human epidemic. Our study highlights the ongoing MPXV zoonotic transmission in Cameroon and Nigeria, underscoring the continuous risk of MPXV (re)emergence.

Genomic epidemiology uncovers the timing and origin of the emergence of mpox in humans

Five years before the 2022-2023 global mpox outbreak Nigeria reported its first cases in nearly 40 years, with the ongoing epidemic since driven by sustained human-to-human transmission. However, limited genomic data has left questions about the timing and origin of the mpox virus' (MPXV) emergence. Here we generated 112 MPXV genomes from Nigeria from 2021-2023. We identify the closest zoonotic outgroup to the human epidemic in southern Nigeria, and estimate that the lineage transmitting from human-to-human emerged around July 2014, circulating cryptically until detected in September 2017. The epidemic originated in Southern Nigeria, particularly Rivers State, which also acted as a persistent and dominant source of viral dissemination to other states. We show that APOBEC3 activity increased MPXV's evolutionary rate twenty-fold during human-to-human transmission. We also show how Delphy, a tool for near-real-time Bayesian phylogenetics, can aid rapid outbreak analytics. Our study sheds light on MPXV's establishment in West Africa before the 2022-2023 global outbreak and highlights the need for improved pathogen surveillance and response.

Sustained transmission over two decades of a previously unrecognised MPT64 negative Mycobacterium tuberculosis strain in Queensland, Australia: a whole genome sequencing study

Background

MPT64 is a key protein used for Mycobacterium tuberculosis (MTB) complex strain identification. We describe protracted transmission of an MPT64 negative MTB strain in Queensland, Australia, and explore genomic factors related to its successful spread.

Methods

All MPT64 negative strains identified between 2002 and 2022 by the Queensland Mycobacteria Reference Laboratory, and an additional 2 isolates from New South Wales (NSW), were whole genome sequenced. Bayesian modelling and phylogeographical analyses were used to assess their evolutionary history and transmission dynamics. Protein structural modelling to understand the putative functional effects of the mutated gene coding for MPT64 protein was performed.

Findings

Forty-three MPT64 negative isolates were sequenced, belonging to a single MTB cluster of Lineage 4.1.1.1 strains. Combined with a UK dataset of the same lineage, molecular dating estimated 1990 (95% HPD 1987-1993) as the likely time of strain introduction into Australia. Although the strain has spread over a wide geographic area and new cases linked to the cluster continue to arise, phylodynamic analysis suggest the outbreak peaked around 2003. All MPT64 negative strains had a frame shift mutation (delAT, p.Val216fs) within the MPT64 gene, which confers two major structural rearrangements at the C-terminus of the protein.

Interpretation

This study uncovered the origins of an MPT64 negative MTB outbreak in Australia, providing a richer understanding of its biology and transmission dynamics, as well as guidance for clinical diagnosis and public health action. The potential spread of MPT64 negative strains undermines the diagnostic utility of the MPT64 immunochromatographic test.

Funding

This study was funded from an operational budget provided to the Queensland Mycobacterium Reference Laboratory by Pathology Queensland, Queensland Department of Health.

Accurate, scalable, and fully automated inference of species trees from raw genome assemblies using ROADIES

Inference of species trees plays a crucial role in advancing our understanding of evolutionary relationships and has immense significance for diverse biological and medical applications. Extensive genome sequencing efforts are currently in progress across a broad spectrum of life forms, holding the potential to unravel the intricate branching patterns within the tree of life. However, estimating species trees starting from raw genome sequences is quite challenging, and the current cutting-edge methodologies require a series of error-prone steps that are neither entirely automated nor standardized. In this paper, we present ROADIES, a novel pipeline for species tree inference from raw genome assemblies that is fully automated, easy to use, scalable, free from reference bias, and provides flexibility to adjust the tradeoff between accuracy and runtime. The ROADIES pipeline eliminates the need to align whole genomes, choose a single reference species, or pre-select loci such as functional genes found using cumbersome annotation steps. Moreover, it leverages recent advances in phylogenetic inference to allow multi-copy genes, eliminating the need to detect orthology. Using the genomic datasets released from large-scale sequencing consortia across three diverse life forms (placental mammals, pomace flies, and birds), we show that ROADIES infers species trees that are comparable in quality with the state-of-the-art approaches but in a fraction of the time. By incorporating optimal approaches and automating all steps from assembled genomes to species and gene trees, ROADIES is poised to improve the accuracy, scalability, and reproducibility of phylogenomic analyses.

New Vibrio cholerae sequences from Eastern and Southern Africa alter our understanding of regional cholera transmission

Despite ongoing containment and vaccination efforts, cholera remains prevalent in many countries in sub-Saharan Africa. Part of the difficulty in containing cholera comes from our lack of understanding of how it circulates throughout the region. To better characterize regional transmission, we generated and analyzed 118 Vibrio cholerae genomes collected between 2007-2019 from five different countries in Southern and Eastern Africa. We showed that V. cholerae sequencing can be successful from a variety of sample types and filled in spatial and temporal gaps in our understanding of circulating lineages, including providing some of the first sequences from the 2018-2019 outbreaks in Uganda, Kenya, Tanzania, Zambia, and Malawi. Our results present a complex picture of cholera transmission in the region, with multiple lineages found to be co-circulating within several countries. We also find evidence that previously identified sporadic cases may be from larger, undersampled outbreaks, highlighting the need for careful examination of sampling biases and underscoring the need for continued and expanded cholera surveillance across the African continent.

Spatiotemporal genotype replacement of H5N8 avian influenza viruses contributed to H5N1 emergence in 2021/2022 panzootic

Since 2020, clade 2.3.4.4b highly pathogenic avian influenza H5N8 and H5N1 viruses have swept through continents, posing serious threats to the world. Through comprehensive analyses of epidemiological, genetic, and bird migration data, we found that the dominant genotype replacement of the H5N8 viruses in 2020 contributed to the H5N1 outbreak in the 2021/2022 wave. The 2020 outbreak of the H5N8 G1 genotype instead of the G0 genotype produced reassortment opportunities and led to the emergence of a new H5N1 virus with G1's HA and MP genes. Despite extensive reassortments in the 2021/2022 wave, the H5N1 virus retained the HA and MP genes, causing a significant outbreak in Europe and North America. Furtherly, through the wild bird migration flyways investigation, we found that the temporal-spatial coincidence between the outbreak of the H5N8 G1 virus and the bird autumn migration may have expanded the H5 viral spread, which may be one of the main drivers of the emergence of the 2020-2022 H5 panzootic.IMPORTANCESince 2020, highly pathogenic avian influenza (HPAI) H5 subtype variants of clade 2.3.4.4b have spread across continents, posing unprecedented threats globally. However, the factors promoting the genesis and spread of H5 HPAI viruses remain unclear. Here, we found that the spatiotemporal genotype replacement of H5N8 HPAI viruses contributed to the emergence of the H5N1 variant that caused the 2021/2022 panzootic, and the viral evolution in poultry of Egypt and surrounding area and autumn bird migration from the Russia-Kazakhstan region to Europe are important drivers of the emergence of the 2020-2022 H5 panzootic. These findings provide important targets for early warning and could help control the current and future HPAI epidemics.

Spatio-temporal spread and evolution of Lassa virus in West Africa

BACKGROUND

Lassa fever is a hemorrhagic disease caused by Lassa virus (LASV), which has been classified by the World Health Organization as one of the top infectious diseases requiring prioritized research. Previous studies have provided insights into the classification and geographic characteristics of LASV lineages. However, the factor of the distribution and evolution characteristics and phylodynamics of the virus was still limited.

METHODS

To enhance comprehensive understanding of LASV, we employed phylogenetic analysis, reassortment and recombination detection, and variation evaluation utilizing publicly available viral genome sequences.

RESULTS

The results showed the estimated the root of time of the most recent common ancestor (TMRCA) for large (L) segment was approximately 634 (95% HPD: [385879]), whereas the TMRCA for small (S) segment was around 1224 (95% HPD: [10301401]). LASV primarily spread from east to west in West Africa through two routes, and in route 2, the virus independently spread to surrounding countries through Liberia, resulting in a wider spread of LASV. From 1969 to 2018, the effective population size experienced two significant increased, indicating the enhanced genetic diversity of LASV. We also found the evolution rate of L segment was faster than S segment, further results showed zinc-binding protein had the fastest evolution rate. Reassortment events were detected in multiple lineages including sub-lineage IIg, while recombination events were observed within lineage V. Significant amino acid changes in the glycoprotein precursor of LASV were identified, demonstrating sequence diversity among lineages in LASV.

CONCLUSION

This study comprehensively elucidated the transmission and evolution of LASV in West Africa, providing detailed insights into reassortment events, recombination events, and amino acid variations.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.

Dispersal history of SARS-CoV-2 in Galicia, Spain

The dynamics of SARS-CoV-2 transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the USA became increasingly significant. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Genetic insights of H9N2 avian influenza viruses circulating in Mali and phylogeographic patterns in Northern and Western Africa

Avian influenza viruses (AIVs) of the H9N2 subtype have become widespread in Western Africa since their first detection in 2017 in Burkina Faso. However, the genetic characteristics and diffusion patterns of the H9N2 virus remain poorly understood in Western Africa, mainly due to limited surveillance activities. In addition, Mali, a country considered to play an important role in the epidemiology of AIVs in the region, lacks more comprehensive data on the genetic characteristics of these viruses, especially the H9N2 subtype. To better understand the genetic characteristics and spatio-temporal dynamics of H9N2 virus within this region, we carried out a comprehensive genetic characterization of H9N2 viruses collected through active surveillance in live bird markets in Mali between 2021 and 2022. We also performed a continuous phylogeographic analysis to unravel the dispersal history of H9N2 lineages between Northern and Western Africa. The identified Malian H9N2 virus belonged to the G1 lineage, similar to viruses circulating in both Western and Northern Africa, and possessed multiple molecular markers associated with an increased potential for zoonotic transmission and virulence. Notably, some Malian strains carried the R-S-N-R motif at their cleavage site, mainly observed in H9N2 strains in Asia. Our continuous phylogeographic analysis revealed a single and significant long-distance lineage dispersal event of the H9N2 virus to Western Africa, likely to have originated from Morocco in 2015, shaping the westward diffusion of the H9N2 virus. Our study highlights the need for long-term surveillance of H9N2 viruses in poultry populations in Western Africa, which is crucial for a better understanding of virus evolution and effective management against potential zoonotic AIV strain emergence.

Many-core algorithms for high-dimensional gradients on phylogenetic trees

MOTIVATION

Advancements in high-throughput genomic sequencing are delivering genomic pathogen data at an unprecedented rate, positioning statistical phylogenetics as a critical tool to monitor infectious diseases globally. This rapid growth spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters increase with the number of sequences N. HMC requires repeated calculation of the gradient of the data log-likelihood with respect to (wrt) all branch-length-specific (BLS) parameters that traditionally takes O(N2) operations using the standard pruning algorithm. A recent study proposes an approach to calculate this gradient in O(N), enabling researchers to take advantage of gradient-based samplers such as HMC. The CPU implementation of this approach makes the calculation of the gradient computationally tractable for nucleotide-based models but falls short in performance for larger state-space size models, such as Markov-modulated and codon models. Here, we describe novel massively parallel algorithms to calculate the gradient of the log-likelihood wrt all BLS parameters that take advantage of graphics processing units (GPUs) and result in many fold higher speedups over previous CPU implementations.

RESULTS

We benchmark these GPU algorithms on three computing systems using three evolutionary inference examples exploring complete genomes from 997 dengue viruses, 62 carnivore mitochondria and 49 yeasts, and observe a >128-fold speedup over the CPU implementation for codon-based models and >8-fold speedup for nucleotide-based models. As a practical demonstration, we also estimate the timing of the first introduction of West Nile virus into the continental Unites States under a codon model with a relaxed molecular clock from 104 full viral genomes, an inference task previously intractable.

AVAILABILITY AND IMPLEMENTATION

We provide an implementation of our GPU algorithms in BEAGLE v4.0.0 (https://github.com/beagle-dev/beagle-lib), an open-source library for statistical phylogenetics that enables parallel calculations on multi-core CPUs and GPUs. We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (https://github.com/beast-dev/beast-mcmc).

Comparative evolution of influenza A virus H1 and H3 head and stalk domains across host species

IMPORTANCE

For decades, researchers have studied the rapid evolution of influenza A viruses for vaccine design and as a useful model system for the study of host/parasite evolution. By performing an exhaustive analysis of hemagglutinin protein (HA) sequences from 49 lineages independently evolving in birds, swine, canines, equines, and humans over the last century, our work uncovers surprising features of HA evolution. In particular, the canine H3 stalk, unlike human H3 and H1 stalk domains, is not evolving slowly, suggesting that evolution in the stalk domain is not universally constrained across all host species. Therefore, a broader multi-host perspective on HA evolution may be useful during the evaluation and design of stalk-targeted vaccine candidates.

African bushpigs exhibit porous species boundaries and appeared in Madagascar concurrently with human arrival

Several African mammals exhibit a phylogeographic pattern where closely related taxa are split between West/Central and East/Southern Africa, but their evolutionary relationships and histories remain controversial. Bushpigs (Potamochoerus larvatus) and red river hogs (P. porcus) are recognised as separate species due to morphological distinctions, a perceived lack of interbreeding at contact, and putatively old divergence times, but historically, they were considered conspecific. Moreover, the presence of Malagasy bushpigs as the sole large terrestrial mammal shared with the African mainland raises intriguing questions about its origin and arrival in Madagascar. Analyses of 67 whole genomes revealed a genetic continuum between the two species, with putative signatures of historical gene flow, variable FST values, and a recent divergence time (<500,000 years). Thus, our study challenges key arguments for splitting Potamochoerus into two species and suggests their speciation might be incomplete. Our findings also indicate that Malagasy bushpigs diverged from southern African populations and underwent a limited bottleneck 1000-5000 years ago, concurrent with human arrival in Madagascar. These results shed light on the evolutionary history of an iconic and widespread African mammal and provide insight into the longstanding biogeographic puzzle surrounding the bushpig's presence in Madagascar.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Complete genome reconstruction of the global and European regional dispersal history of the lumpy skin disease virus

IMPORTANCE

Lumpy skin disease virus (LSDV) has a complex epidemiology involving multiple strains, recombination, and vaccination. Its DNA genome provides limited genetic variation to trace outbreaks in space and time. Sequencing of LSDV whole genomes has also been patchy at global and regional scales. Here, we provide the first fine-grained whole genome sequence sampling of a constrained LSDV outbreak (southeastern Europe, 2015-2017), which we analyze along with global publicly available genomes. We formally evaluate the past occurrence of recombination events as well as the temporal signal that is required for calibrating molecular clock models and subsequently conduct a time-calibrated spatially explicit phylogeographic reconstruction. Our study further illustrates the importance of accounting for recombination events before reconstructing global and regional dynamics of DNA viruses. More LSDV whole genomes from endemic areas are needed to obtain a comprehensive understanding of global LSDV dispersal dynamics.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Online tree expansion could help solve the problem of scalability in Bayesian phylogenetics

Bayesian phylogenetics is now facing a critical point. Over the last 20 years, Bayesian methods have reshaped phylogenetic inference and gained widespread popularity due to their high accuracy, the ability to quantify the uncertainty of inferences and the possibility of accommodating multiple aspects of evolutionary processes in the models that are used. Unfortunately, Bayesian methods are computationally expensive, and typical applications involve at most a few hundred sequences. This is problematic in the age of rapidly expanding genomic data and increasing scope of evolutionary analyses, forcing researchers to resort to less accurate but faster methods, such as maximum parsimony and maximum likelihood. Does this spell doom for Bayesian methods? Not necessarily. Here, we discuss some recently proposed approaches that could help scale up Bayesian analyses of evolutionary problems considerably. We focus on two particular aspects: online phylogenetics, where new data sequences are added to existing analyses, and alternatives to Markov chain Monte Carlo (MCMC) for scalable Bayesian inference. We identify 5 specific challenges and discuss how they might be overcome. We believe that online phylogenetic approaches and Sequential Monte Carlo hold great promise and could potentially speed up tree inference by orders of magnitude. We call for collaborative efforts to speed up the development of methods for real-time tree expansion through online phylogenetics.

Scalable Bayesian Divergence Time Estimation With Ratio Transformations

Divergence time estimation is crucial to provide temporal signals for dating biologically important events from species divergence to viral transmissions in space and time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic studies have analyzed hundreds to thousands of sequences. Such large-scale analyses challenge divergence time reconstruction by requiring inference on highly correlated internal node heights that often become computationally infeasible. To overcome this limitation, we explore a ratio transformation that maps the original $N-1$ internal node heights into a space of one height parameter and $N-2$ ratio parameters. To make the analyses scalable, we develop a collection of linear-time algorithms to compute the gradient and Jacobian-associated terms of the log-likelihood with respect to these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio transform in a Bayesian framework to learn the divergence times in 4 pathogenic viruses (West Nile virus, rabies virus, Lassa virus, and Ebola virus) and the coralline red algae. Our method both resolves a mixing issue in the West Nile virus example and improves inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well as for the algae example. Our method now also makes it computationally feasible to incorporate mixed-effects molecular clock models for the Ebola virus example, confirms the findings from the original study, and reveals clearer multimodal distributions of the divergence times of some clades of interest.

Epidemiology, genetic diversity, and evolutionary dynamics of Tembusu virus

Tembusu virus (TMUV) is an emerging pathogenic flavivirus associated with acute egg-drop and fatal encephalitis in domestic waterfowl. Since its initial identification in mosquitoes in 1955, TMUV has been confirmed to infect ducks, pigeons, sparrows, geese, and chickens, posing a significant threat to the poultry industry. Here, we sequenced two DTMUV strains isolated in 2019 and systematically investigated the possible origin, genetic relationships, evolutionary dynamics, and transmission patterns of TMUV based on complete virus genome sequences in the public database. We found that TMUV can be divided into four major clusters: TMUV, cluster 1, cluster 2, and cluster 3. Interestingly, we found that cluster 2.2 (within cluster 2) is the most commonly involved in interspecies transmission events, and subcluster 2.1.2 (within cluster 2.1) is currently the most prevalent cluster circulating in Asia. Notably, we also identified three positively selected sites in the E and NS1 proteins, which may be involved in virus replication, immune evasion, and host adaptation. Finally, phylogeographic analysis revealed that cluster dispersal originated in Southeast Asia and that short-distance transmission events have occurred frequently. Altogether, these data provide novel insights into the evolution and dispersal of TMUV, facilitating the development of rapid diagnostics, vaccines, and therapeutics against TMUV infection.