A Novel Rubi-Like Virus in the Pacific Electric Ray (Tetronarce californica) Reveals the Complex Evolutionary History of the Matonaviridae

Rubella virus (RuV) is the causative agent of rubella ("German measles") and remains a global health concern. Until recently, RuV was the only known member of the genus Rubivirus and the only virus species classified within the Matonaviridae family of positive-sense RNA viruses. Recently, two new rubella-like matonaviruses, Rustrela virus and Ruhugu virus, have been identified in several mammalian species, along with more divergent viruses in fish and reptiles. To screen for the presence of additional novel rubella-like viruses, we mined published transcriptome data using genome sequences from Rubella, Rustrela, and Ruhugu viruses as baits. From this, we identified a novel rubella-like virus in a transcriptome of Tetronarce californica-order Torpediniformes (Pacific electric ray)-that is more closely related to mammalian Rustrela virus than to the divergent fish matonavirus and indicative of a complex pattern of cross-species virus transmission. Analysis of host reads confirmed that the sample analysed was indeed from a Pacific electric ray, and two other viruses identified in this animal, from the Arenaviridae and Reoviridae, grouped with other fish viruses. These findings indicate that the evolutionary history of the Matonaviridae is more complex than previously thought and highlights the vast number of viruses that remain undiscovered.

Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 during Border Quarantine and Air Travel, New Zealand (Aotearoa)

The strategy in New Zealand (Aotearoa) to eliminate coronavirus disease requires that international arrivals undergo managed isolation and quarantine and mandatory testing for severe acute respiratory syndrome coronavirus 2. Combining genomic and epidemiologic data, we investigated the origin of an acute case of coronavirus disease identified in the community after the patient had spent 14 days in managed isolation and quarantine and had 2 negative test results. By combining genomic sequence analysis and epidemiologic investigations, we identified a multibranched chain of transmission of this virus, including on international and domestic flights, as well as a probable case of aerosol transmission without direct person-to-person contact. These findings show the power of integrating genomic and epidemiologic data to inform outbreak investigations.

Virome composition in marine fish revealed by meta-transcriptomics

Revealing the determinants of virome composition is central to placing disease emergence in a broader evolutionary context. Fish are the most species-rich group of vertebrates and so provide an ideal model system to study the factors that shape virome compositions and their evolution. We characterized the viromes of nineteen wild-caught species of marine fish using total RNA sequencing (meta-transcriptomics) combined with analyses of sequence and protein structural homology to identify divergent viruses that often evade characterization. From this, we identified twenty-five new vertebrate-associated viruses and a further twenty-two viruses likely associated with fish diet or their microbiomes. The vertebrate-associated viruses identified here included the first fish virus in the Matonaviridae (single-strand, negative-sense RNA virus). Other viruses fell within the Astroviridae, Picornaviridae, Arenaviridae, Reoviridae, Hepadnaviridae, Paramyxoviridae, Rhabdoviridae, Hantaviridae, Filoviridae, and Flaviviridae, and were sometimes phylogenetically distinct from known fish viruses. We also show how key metrics of virome composition-viral richness, abundance, and diversity-can be analysed along with host ecological and biological factors as a means to understand virus ecology. Accordingly, these data suggest that that the vertebrate-associated viromes of the fish sampled here are predominantly shaped by the phylogenetic history (i.e. taxonomic order) of their hosts, along with several biological factors including water temperature, habitat depth, community diversity and swimming behaviour. No such correlations were found for viruses associated with porifera, molluscs, arthropods, fungi, and algae, that are unlikely to replicate in fish hosts. Overall, these data indicate that fish harbour particularly large and complex viromes and the vast majority of fish viromes are undescribed.

Genomic Evidence of In-Flight Transmission of SARS-CoV-2 Despite Predeparture Testing

Since the first wave of coronavirus disease in March 2020, citizens and permanent residents returning to New Zealand have been required to undergo managed isolation and quarantine (MIQ) for 14 days and mandatory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of October 20, 2020, of 62,698 arrivals, testing of persons in MIQ had identified 215 cases of SARS-CoV-2 infection. Among 86 passengers on a flight from Dubai, United Arab Emirates, that arrived in New Zealand on September 29, test results were positive for 7 persons in MIQ. These passengers originated from 5 different countries before a layover in Dubai; 5 had negative predeparture SARS-CoV-2 test results. To assess possible points of infection, we analyzed information about their journeys, disease progression, and virus genomic data. All 7 SARS-CoV-2 genomes were genetically identical, except for a single mutation in 1 sample. Despite predeparture testing, multiple instances of in-flight SARS-CoV-2 transmission are likely.

Subtype-specific differences in transmission cluster dynamics of HIV-1 B and CRF01_AE in New South Wales, Australia

INTRODUCTION

The human immunodeficiency virus 1 (HIV-1) pandemic is characterized by numerous distinct sub-epidemics (clusters) that continually fuel local transmission. The aims of this study were to identify active growing clusters, to understand which factors most influence the transmission dynamics, how these vary between different subtypes and how this information might contribute to effective public health responses.

METHODS

We used HIV-1 genomic sequence data linked to demographic factors that accounted for approximately 70% of all new HIV-1 notifications in New South Wales (NSW). We assessed differences in transmission cluster dynamics between subtype B and circulating recombinant form 01_AE (CRF01_AE). Separate phylogenetic trees were estimated using 2919 subtype B and 473 CRF01_AE sequences sampled between 2004 and 2018 in combination with global sequence data and NSW-specific clades were classified as clusters, pairs or singletons. Significant differences in demographics between subtypes were assessed with Chi-Square statistics.

RESULTS

We identified 104 subtype B and 11 CRF01_AE growing clusters containing a maximum of 29 and 11 sequences for subtype B and CRF01_AE respectively. We observed a > 2-fold increase in the number of NSW-specific CRF01_AE clades over time. Subtype B clusters were associated with individuals reporting men who have sex with men (MSM) as their transmission risk factor, being born in Australia, and being diagnosed during the early stage of infection (p < 0.01). CRF01_AE infections clusters were associated with infections among individuals diagnosed during the early stage of infection (p < 0.05) and CRF01_AE singletons were more likely to be from infections among individuals reporting heterosexual transmission (p < 0.05). We found six subtype B clusters with an above-average growth rate (>1.5 sequences / 6-months) and which consisted of a majority of infections among MSM. We also found four active growing CRF01_AE clusters containing only infections among MSM. Finally, we found 47 subtype B and seven CRF01_AE clusters that contained a large gap in time (>1 year) between infections and may be indicative of intermediate transmissions via undiagnosed individuals.

CONCLUSIONS

The large number of active and growing clusters among MSM are the driving force of the ongoing epidemic in NSW for subtype B and CRF01_AE.

Metagenomic sequencing reveals a lack of virus exchange between native and invasive freshwater fish across the Murray-Darling Basin, Australia

Biological invasions are among the biggest threats to freshwater biodiversity. This is increasingly relevant in the Murray-Darling Basin, Australia, particularly since the introduction of the common carp (Cyprinus carpio). This invasive species now occupies up to ninety per cent of fish biomass, with hugely detrimental impacts on native fauna and flora. To address the ongoing impacts of carp, cyprinid herpesvirus 3 (CyHV-3) has been proposed as a potentially effective biological control agent. Crucially, however, it is unknown whether CyHV-3 and other cyprinid herpesviruses already exist in the Murray-Darling. Further, little is known about those viruses that naturally occur in wild freshwater fauna, and the frequency with which these viruses jump species boundaries. To document the evolution and diversity of freshwater fish viromes and better understand the ecological context to the proposed introduction of CyHV-3, we performed a meta-transcriptomic viral survey of invasive and native fish across the Murray-Darling Basin, covering over 2,200 km of the river system. Across a total of thirty-six RNA libraries representing ten species, we failed to detect CyHV-3 nor any closely related viruses. Rather, meta-transcriptomic analysis identified eighteen vertebrate-associated viruses that could be assigned to the Arenaviridae, Astroviridae, Bornaviridae, Caliciviridae, Coronaviridae, Chuviridae, Flaviviridae, Hantaviridae, Hepeviridae, Paramyxoviridae, Picornaviridae, Poxviridae, Reoviridae and Rhabdoviridae families, and a further twenty-seven that were deemed to be associated with non-vertebrate hosts. Notably, we revealed a marked lack of viruses that are shared among invasive and native fish sampled here, suggesting that there is little virus transmission from common carp to native fish species, despite co-existing for over fifty years. Overall, this study provides the first data on the viruses naturally circulating in a major river system and supports the notion that fish harbour a large diversity of viruses with often deep evolutionary histories.

Red fox viromes in urban and rural landscapes

The Red fox (Vulpes vulpes) has established large populations in Australia’s urban and rural areas since its introduction following European settlement. The cryptic and highly adaptable nature of foxes allows them to invade cities and live among humans whilst remaining largely unnoticed. Urban living and access to anthropogenic food resources also influence fox ecology. Urban foxes grow larger, live at higher densities, and are more social than their rural counterparts. These ecological changes in urban red foxes are likely to impact the pathogens that they harbour, and foxes could pose a disease risk to humans and other species that share these urban spaces. To investigate this possibility, we used a meta-transcriptomic approach to characterise the virome of urban and rural foxes across the Greater Sydney region in Australia. Urban and rural foxes differed significantly in virome composition, with rural foxes harbouring a greater abundance of viruses compared to their urban counterparts. We identified ten potentially novel vertebrate-associated viruses in both urban and rural foxes, some of which are related to viruses associated with disease in domestic species and humans. These included members of the Astroviridae, Picobirnaviridae, Hepeviridae, and Picornaviridae as well as rabbit haemorrhagic disease virus-2. This study sheds light on the viruses carried by urban and rural foxes and emphasises the need for greater genomic surveillance of foxes and other invasive species at the human–wildlife interface.

The phylogenomics of evolving virus virulence

How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.

High diversity and rapid spatial turnover of integron gene cassettes in soil

Integrons are genetic elements that promote rapid adaptation in bacteria by capturing exogenous, mobile gene cassettes. Recently, a subset of gene cassettes has facilitated the global spread of antibiotic resistance. However, outside clinical settings, very little is known about their diversity and spatial ecology. To address this question, we sequenced integron gene cassettes from soils sampled across Australia and Antarctica. We recovered 44 970 open reading frames that encoded 27 215 unique proteins, representing an order of magnitude more cassettes than previous sequencing efforts. We found that cassettes have extremely high local richness, significantly greater than previously predicted, with estimates ranging from 4000 to 18 000 unique cassettes per 0.3 g of soil. We show that cassettes have a heterogeneous distribution across space, and that they exhibit rapid turnover with distance. Similarity between samples drops to between 0.1% and 10% at distances of as little as 100 m. Together, these data provide key insights into the ecology and size of the gene cassette metagenome.

Evolutionary Virology at 40

RNA viruses are diverse, abundant, and rapidly evolving. Genetic data have been generated from virus populations since the late 1970s and used to understand their evolution, emergence, and spread, culminating in the generation and analysis of many thousands of viral genome sequences. Despite this wealth of data, evolutionary genetics has played a surprisingly small role in our understanding of virus evolution. Instead, studies of RNA virus evolution have been dominated by two very different perspectives, the experimental and the comparative, that have largely been conducted independently and sometimes antagonistically. Here, we review the insights that these two approaches have provided over the last 40 years. We show that experimental approaches using in vitro and in vivo laboratory models are largely focused on short-term intrahost evolutionary mechanisms, and may not always be relevant to natural systems. In contrast, the comparative approach relies on the phylogenetic analysis of natural virus populations, usually considering data collected over multiple cycles of virus-host transmission, but is divorced from the causative evolutionary processes. To truly understand RNA virus evolution it is necessary to meld experimental and comparative approaches within a single evolutionary genetic framework, and to link viral evolution at the intrahost scale with that which occurs over both epidemiological and geological timescales. We suggest that the impetus for this new synthesis may come from methodological advances in next-generation sequencing and metagenomics.

Hidden diversity and evolution of viruses in market fish

Aquaculture is the fastest growing industry worldwide. Aquatic diseases have had enormous economic and environmental impacts in the recent past and the emergence of new aquatic pathogens, particularly viruses, poses a continuous threat. Nevertheless, little is known about the diversity, abundance and evolution of fish viruses. We used a meta-transcriptomic approach to help determine the virome of seemingly healthy fish sold at a market in Sydney, Australia. Specifically, by identifying and quantifying virus transcripts we aimed to determine (i) the abundance of viruses in market fish, (ii) test a key component of epidemiological theory that large and dense host populations harbour a greater number of viruses compared to their more solitary counterparts and (iii) reveal the relative roles of virus–host co-divergence and cross-species transmission in the evolution of fish viruses. The species studied comprised both shoaling fish—eastern sea garfish (Hyporhamphus australis) and Australasian snapper (Chrysophrys auratus)—and more solitary fish—eastern red scorpionfish (Scorpaena jacksoniensis) and largetooth flounder (Pseudorhombus arsius). Our analysis identified twelve potentially novel viruses, eight of which were likely vertebrate-associated across four viral families and that exhibited frequent cross-species transmission. Notably, the most solitary of the fish species studied, the largetooth flounder, harboured the least number of viruses while eastern sea garfish, a densely shoaling fish, had the highest number of viruses. These results support the emerging view that fish harbour a large and largely uncharacterised virome.

Inferring demographic parameters in bacterial genomic data using Bayesian and hybrid phylogenetic methods

Background

Recent developments in sequencing technologies make it possible to obtain genome sequences from a large number of isolates in a very short time. Bayesian phylogenetic approaches can take advantage of these data by simultaneously inferring the phylogenetic tree, evolutionary timescale, and demographic parameters (such as population growth rates), while naturally integrating uncertainty in all parameters. Despite their desirable properties, Bayesian approaches can be computationally intensive, hindering their use for outbreak investigations involving genome data for a large numbers of pathogen isolates. An alternative to using full Bayesian inference is to use a hybrid approach, where the phylogenetic tree and evolutionary timescale are estimated first using maximum likelihood. Under this hybrid approach, demographic parameters are inferred from estimated trees instead of the sequence data, using maximum likelihood, Bayesian inference, or approximate Bayesian computation. This can vastly reduce the computational burden, but has the disadvantage of ignoring the uncertainty in the phylogenetic tree and evolutionary timescale.

Results

We compared the performance of a fully Bayesian and a hybrid method by analysing six whole-genome SNP data sets from a range of bacteria and simulations. The estimates from the two methods were very similar, suggesting that the hybrid method is a valid alternative for very large datasets. However, we also found that congruence between these methods is contingent on the presence of strong temporal structure in the data (i.e. clocklike behaviour), which is typically verified using a date-randomisation test in a Bayesian framework. To reduce the computational burden of this Bayesian test we implemented a date-randomisation test using a rapid maximum likelihood method, which has similar performance to its Bayesian counterpart.

Conclusions

Hybrid approaches can produce reliable inferences of evolutionary timescales and phylodynamic parameters in a fraction of the time required for fully Bayesian analyses. As such, they are a valuable alternative in outbreak studies involving a large number of isolates.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1210-5) contains supplementary material, which is available to authorized users.

Predicting virus emergence amid evolutionary noise

The study of virus disease emergence, whether it can be predicted and how it might be prevented, has become a major research topic in biomedicine. Here we show that efforts to predict disease emergence commonly conflate fundamentally different evolutionary and epidemiological time scales, and are likely to fail because of the enormous number of unsampled viruses that could conceivably emerge in humans. Although we know much about the patterns and processes of virus evolution on evolutionary time scales as depicted in family-scale phylogenetic trees, these data have little predictive power to reveal the short-term microevolutionary processes that underpin cross-species transmission and emergence. Truly understanding disease emergence therefore requires a new mechanistic and integrated view of the factors that allow or prevent viruses spreading in novel hosts. We present such a view, suggesting that both ecological and genetic aspects of virus emergence can be placed within a simple population genetic framework, which in turn highlights the importance of host population size and density in determining whether emergence will be successful. Despite this framework, we conclude that a more practical solution to preventing and containing the successful emergence of new diseases entails ongoing virological surveillance at the human–animal interface and regions of ecological disturbance.

Virological Sampling of Inaccessible Wildlife with Drones

There is growing interest in characterizing the viromes of diverse mammalian species, particularly in the context of disease emergence. However, little is known about virome diversity in aquatic mammals, in part due to difficulties in sampling. We characterized the virome of the exhaled breath (or blow) of the Eastern Australian humpback whale (Megaptera novaeangliae). To achieve an unbiased survey of virome diversity, a meta-transcriptomic analysis was performed on 19 pooled whale blow samples collected via a purpose-built Unmanned Aerial Vehicle (UAV, or drone) approximately 3 km off the coast of Sydney, Australia during the 2017 winter annual northward migration from Antarctica to northern Australia. To our knowledge, this is the first time that UAVs have been used to sample viruses. Despite the relatively small number of animals surveyed in this initial study, we identified six novel virus species from five viral families. This work demonstrates the potential of UAVs in studies of virus disease, diversity, and evolution.

A comparison of methods for estimating substitution rates from ancient DNA sequence data

Background

Phylogenetic analysis of DNA from modern and ancient samples allows the reconstruction of important demographic and evolutionary processes. A critical component of these analyses is the estimation of evolutionary rates, which can be calibrated using information about the ages of the samples. However, the reliability of these rate estimates can be negatively affected by among-lineage rate variation and non-random sampling. Using a simulation study, we compared the performance of three phylogenetic methods for inferring evolutionary rates from time-structured data sets: regression of root-to-tip distances, least-squares dating, and Bayesian inference. We also applied these three methods to time-structured mitogenomic data sets from six vertebrate species.

Results

Our results from 12 simulation scenarios show that the three methods produce reliable estimates when the substitution rate is high, rate variation is low, and samples of similar ages are not all grouped together in the tree (i.e., low phylo-temporal clustering). The interaction of these factors is particularly important for least-squares dating and Bayesian estimation of evolutionary rates. The three estimation methods produced consistent estimates of rates across most of the six mitogenomic data sets, with sequence data from horses being an exception.

Conclusions

We recommend that phylogenetic studies of ancient DNA sequences should use multiple methods of inference and test for the presence of temporal signal, among-lineage rate variation, and phylo-temporal clustering in the data.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1192-3) contains supplementary material, which is available to authorized users.

Correction: Continental synchronicity of human influenza virus epidemics despite climactic variation

[This corrects the article DOI: 10.1371/journal.ppat.1006780.].

Continental synchronicity of human influenza virus epidemics despite climatic variation

The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007-2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus.

Pathogen population bottlenecks and adaptive landscapes: overcoming the barriers to disease emergence

Emerging diseases are a major challenge to public health. Revealing the evolutionary processes that allow novel pathogens to adapt to new hosts, also the potential barriers to host adaptation, is central to understanding the drivers of disease emergence. In particular, it is unclear how the genetics and ecology of pathogens interact to shape the likelihood of successful cross-species transmission. To better understand the determinants of host adaptation and emergence, we modelled key aspects of pathogen evolutionary dynamics at both intra- and inter-host scales, using parameter values similar to those observed in influenza virus. We considered the possibility of acquiring the necessary host adaptive mutations both before ('off-the-shelf' emergence) and after ('tailor-made' emergence) a virus is transmitted from a donor to a new recipient species. Under both scenarios, population bottlenecks at inter-host transmission act as a major barrier to host adaptation, greatly limiting the number of adaptive mutations that are able to cross the species barrier. In addition, virus emergence is hindered if the fitness valley between the donor and recipient hosts is either too steep or too shallow. Overall, our results reveal where in evolutionary parameter space a virus could adapt to and become transmissible in a new species.

Predicting virus emergence amid evolutionary noise

The study of virus disease emergence, whether it can be predicted and how it might be prevented, has become a major research topic in biomedicine. Here we show that efforts to predict disease emergence commonly conflate fundamentally different evolutionary and epidemiological time scales, and are likely to fail because of the enormous number of unsampled viruses that could conceivably emerge in humans. Although we know much about the patterns and processes of virus evolution on evolutionary time scales as depicted in family-scale phylogenetic trees, these data have little predictive power to reveal the short-term microevolutionary processes that underpin cross-species transmission and emergence. Truly understanding disease emergence therefore requires a new mechanistic and integrated view of the factors that allow or prevent viruses spreading in novel hosts. We present such a view, suggesting that both ecological and genetic aspects of virus emergence can be placed within a simple population genetic framework, which in turn highlights the importance of host population size and density in determining whether emergence will be successful. Despite this framework, we conclude that a more practical solution to preventing and containing the successful emergence of new diseases entails ongoing virological surveillance at the human-animal interface and regions of ecological disturbance.

Comparative analysis estimates the relative frequencies of co-divergence and cross-species transmission within viral families

The cross-species transmission of viruses from one host species to another is responsible for the majority of emerging infections. However, it is unclear whether some virus families have a greater propensity to jump host species than others. If related viruses have an evolutionary history of co-divergence with their hosts there should be evidence of topological similarities between the virus and host phylogenetic trees, whereas host jumping generates incongruent tree topologies. By analyzing co-phylogenetic processes in 19 virus families and their eukaryotic hosts we provide a quantitative and comparative estimate of the relative frequency of virus-host co-divergence versus cross-species transmission among virus families. Notably, our analysis reveals that cross-species transmission is a near universal feature of the viruses analyzed here, with virus-host co-divergence occurring less frequently and always on a subset of viruses. Despite the overall high topological incongruence among virus and host phylogenies, the Hepadnaviridae, Polyomaviridae, Poxviridae, Papillomaviridae and Adenoviridae, all of which possess double-stranded DNA genomes, exhibited more frequent co-divergence than the other virus families studied here. At the other extreme, the virus and host trees for all the RNA viruses studied here, particularly the Rhabdoviridae and the Picornaviridae, displayed high levels of topological incongruence, indicative of frequent host switching. Overall, we show that cross-species transmission plays a major role in virus evolution, with all the virus families studied here having the potential to jump host species, and that increased sampling will likely reveal more instances of host jumping.

Estimating evolutionary rates using time-structured data: a general comparison of phylogenetic methods

MOTIVATION

In rapidly evolving pathogens, including viruses and some bacteria, genetic change can accumulate over short time-frames. Accordingly, their sampling times can be used to calibrate molecular clocks, allowing estimation of evolutionary rates. Methods for estimating rates from time-structured data vary in how they treat phylogenetic uncertainty and rate variation among lineages. We compiled 81 virus data sets and estimated nucleotide substitution rates using root-to-tip regression, least-squares dating and Bayesian inference.

RESULTS

Although estimates from these three methods were often congruent, this largely relied on the choice of clock model. In particular, relaxed-clock models tended to produce higher rate estimates than methods that assume constant rates. Discrepancies in rate estimates were also associated with high among-lineage rate variation, and phylogenetic and temporal clustering. These results provide insights into the factors that affect the reliability of rate estimates from time-structured sequence data, emphasizing the importance of clock-model testing.

CONTACT

sduchene@unimelb.edu.au or garzonsebastian@hotmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Cross-validation to select Bayesian hierarchical models in phylogenetics

Background

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance.

Results

We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models.

Conclusions

Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0688-y) contains supplementary material, which is available to authorized users.

A generic assay for whole-genome amplification and deep sequencing of enterovirus A71

Enterovirus A71 (EV-A71) has emerged as the most important cause of large outbreaks of severe and sometimes fatal hand, foot and mouth disease (HFMD) across the Asia-Pacific region. EV-A71 outbreaks have been associated with (sub)genogroup switches, sometimes accompanied by recombination events. Understanding EV-A71 population dynamics is therefore essential for understanding this emerging infection, and may provide pivotal information for vaccine development. Despite the public health burden of EV-A71, relatively few EV-A71 complete-genome sequences are available for analysis and from limited geographical localities. The availability of an efficient procedure for whole-genome sequencing would stimulate effort to generate more viral sequence data. Herein, we report for the first time the development of a next-generation sequencing based protocol for whole-genome sequencing of EV-A71 directly from clinical specimens. We were able to sequence viruses of subgenogroup C4 and B5, while RNA from culture materials of diverse EV-A71 subgenogroups belonging to both genogroup B and C was successfully amplified. The nature of intra-host genetic diversity was explored in 22 clinical samples, revealing 107 positions carrying minor variants (ranging from 0 to 15 variants per sample). Our analysis of EV-A71 strains sampled in 2013 showed that they all belonged to subgenogroup B5, representing the first report of this subgenogroup in Vietnam. In conclusion, we have successfully developed a high-throughput next-generation sequencing-based assay for whole-genome sequencing of EV-A71 from clinical samples.