The source of the Black Death in fourteenth-century central Eurasia.

The origin of the medieval Black Death pandemic (AD 1346-1353) has been a topic of continuous investigation because of the pandemic's extensive demographic impact and long-lasting consequences1,2. Until now, the most debated archaeological evidence potentially associated with the pandemic's initiation derives from cemeteries located near Lake Issyk-Kul of modern-day Kyrgyzstan1,3-9. These sites are thought to have housed victims of a fourteenth-century epidemic as tombstone inscriptions directly dated to 1338-1339 state 'pestilence' as the cause of death for the buried individuals9. Here we report ancient DNA data from seven individuals exhumed from two of these cemeteries, Kara-Djigach and Burana. Our synthesis of archaeological, historical and ancient genomic data shows a clear involvement of the plague bacterium Yersinia pestis in this epidemic event. Two reconstructed ancient Y. pestis genomes represent a single strain and are identified as the most recent common ancestor of a major diversification commonly associated with the pandemic's emergence, here dated to the first half of the fourteenth century. Comparisons with present-day diversity from Y. pestis reservoirs in the extended Tian Shan region support a local emergence of the recovered ancient strain. Through multiple lines of evidence, our data support an early fourteenth-century source of the second plague pandemic in central Eurasia.

Stone Age Yersinia pestis genomes shed light on the early evolution, diversity, and ecology of plague.

The bacterial pathogen Yersinia pestis gave rise to devastating outbreaks throughout human history, and ancient DNA evidence has shown it afflicted human populations as far back as the Neolithic. Y. pestis genomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to its emergence from a Yersinia pseudotuberculosis-like progenitor; however, the number of reconstructed LNBA genomes are too few to explore its diversity during this critical period of development. Here, we present 17 Y. pestis genomes dating to 5,000 to 2,500 y BP from a wide geographic expanse across Eurasia. This increased dataset enabled us to explore correlations between temporal, geographical, and genetic distance. Our results suggest a nonflea-adapted and potentially extinct single lineage that persisted over millennia without significant parallel diversification, accompanied by rapid dispersal across continents throughout this period, a trend not observed in other pathogens for which ancient genomes are available. A stepwise pattern of gene loss provides further clues on its early evolution and potential adaptation. We also discover the presence of the flea-adapted form of Y. pestis in Bronze Age Iberia, previously only identified in in the Caucasus and the Volga regions, suggesting a much wider geographic spread of this form of Y. pestis. Together, these data reveal the dynamic nature of plague's formative years in terms of its early evolution and ecology.

Paleomicrobiology: Diagnosis and Evolution of Ancient Pathogens.

The last century has witnessed progress in the study of ancient infectious disease from purely medical descriptions of past ailments to dynamic interpretations of past population health that draw upon multiple perspectives. The recent adoption of high-throughput DNA sequencing has led to an expanded understanding of pathogen presence, evolution, and ecology across the globe. This genomic revolution has led to the identification of disease-causing microbes in both expected and unexpected contexts, while also providing for the genomic characterization of ancient pathogens previously believed to be unattainable by available methods. In this review we explore the development of DNA-based ancient pathogen research, the specialized methods and tools that have emerged to authenticate and explore infectious disease of the past, and the unique challenges that persist in molecular paleopathology. We offer guidelines to mitigate the impact of these challenges, which will allow for more reliable interpretations of data in this rapidly evolving field of investigation.

Genome Structure, Life Cycle, and Taxonomy of Coronaviruses and the Evolution of SARS-CoV-2.

Coronaviruses have a broad host range and exhibit high zoonotic potential. In this chapter, we describe their genomic organization in terms of encoded proteins and provide an introduction to the peculiar discontinuous transcription mechanism. Further, we present evolutionary conserved genomic RNA secondary structure features, which are involved in the complex replication mechanism. With a focus on computational methods, we review the emergence of SARS-CoV-2 starting with the 2019 strains. In that context, we also discuss the debated hypothesis of whether SARS-CoV-2 was created in a laboratory. We focus on the molecular evolution and the epidemiological dynamics of this recently emerged pathogen and we explain how variants of concern are detected and characterised. COVID-19, the disease caused by SARS-CoV-2, can spread through different transmission routes and also depends on a number of risk factors. We describe how current computational models of viral epidemiology, or more specifically, phylodynamics, have facilitated and will continue to enable a better understanding of the epidemic dynamics of SARS-CoV-2.

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.

Reconstruction of the Genetic History and the Current Spread of HIV-1 Subtype A in Germany.

HIV-1 non-B infections have been increasing in Europe for several years. In Germany, subtype A belongs to the most abundant non-B subtypes showing an increasing prevalence of 8.3% among new infections in 2016. Here we trace the origin and examine the current spread of the German HIV-1 subtype A epidemic. Bayesian coalescence and birth-death analyses were performed with 180 German HIV-1 pol sequences and 528 related and publicly available sequences to reconstruct the population dynamics and fluctuations for each of the transmission groups. Our reconstructions indicate two distinct sources of the German subtype A epidemic, with an Eastern European and an Eastern African lineage both cocirculating in the country. A total of 13 German-origin clusters were identified; among these, 6 clusters showed recent activity. Introductions leading to further countrywide spread originated predominantly from Eastern Africa when introduced before 2005. Since 2005, however, spreading introductions have occurred exclusively within the Eastern European clade. Moreover, we observed changes in the main route of subtype A transmission. The beginning of the German epidemic (1985 to 1995) was dominated by heterosexual transmission of the Eastern African lineage. Since 2005, transmissions among German men who have sex with men (MSM) have been increasing and have been associated with the Eastern European lineage. Infections among people who inject drugs dominated between 1998 and 2005. Our findings on HIV-1 subtype A infections provide new insights into the spread of this virus and extend the understanding of the HIV epidemic in Germany.IMPORTANCE HIV-1 subtype A is the second most prevalent subtype worldwide, with a high prevalence in Eastern Africa and Eastern Europe. However, an increase of non-B infections, including subtype A infections, has been observed in Germany and other European countries. There has simultaneously been an increased flow of refugees into Europe and especially into Germany, raising the question of whether the surge in non-B infections resulted from this increased immigration or whether German transmission chains are mainly involved. This study is the first comprehensive subtype A study from a western European country analyzing in detail its phylogenetic origin, the impact of various transmission routes, and its current spread. The results and conclusions presented provide new and substantial insights for virologists, epidemiologists, and the general public health sector. In this regard, they should be useful to those authorities responsible for developing public health intervention strategies to combat the further spread of HIV/AIDS.

Phenotypic deficits in the HIV-1 envelope are associated with the maturation of a V2-directed broadly neutralizing antibody lineage.

Broadly neutralizing antibodies (bnAbs) to HIV-1 can evolve after years of an iterative process of virus escape and antibody adaptation that HIV-1 vaccine design seeks to mimic. To enable this, properties that render HIV-1 envelopes (Env) capable of eliciting bnAb responses need to be defined. Here, we followed the evolution of the V2 apex directed bnAb lineage VRC26 in the HIV-1 subtype C superinfected donor CAP256 to investigate the phenotypic changes of the virus populations circulating before and during the early phases of bnAb induction. Longitudinal viruses that evolved from the VRC26-resistant primary infecting (PI) virus, the VRC26-sensitive superinfecting (SU) virus and ensuing PI-SU recombinants revealed substantial phenotypic changes in Env, with a switch in Env properties coinciding with early resistance to VRC26. Decreased sensitivity of SU-like viruses to VRC26 was linked with reduced infectivity, altered entry kinetics and lower sensitivity to neutralization after CD4 attachment. VRC26 maintained neutralization activity against cell-associated CAP256 virus, indicating that escape through the cell-cell transmission route is not a dominant escape pathway. Reduced fitness of the early escape variants and sustained sensitivity in cell-cell transmission are both features that limit virus replication, thereby impeding rapid escape. This supports a scenario where VRC26 allowed only partial viral escape for a prolonged period, possibly increasing the time window for bnAb maturation. Collectively, our data highlight the phenotypic plasticity of the HIV-1 Env in evading bnAb pressure and the need to consider phenotypic traits when selecting and designing Env immunogens. Combinations of Env variants with differential phenotypic patterns and bnAb sensitivity, as we describe here for CAP256, may maximize the potential for inducing bnAb responses by vaccination.

Quantifying the fitness cost of HIV-1 drug resistance mutations through phylodynamics.

Drug resistant HIV is a major threat to the long-term efficacy of antiretroviral treatment. Around 10% of ART-naïve patients in Europe are infected with drug-resistant HIV type 1. Hence it is important to understand the dynamics of transmitted drug resistance evolution. Thanks to routinely performed drug resistance tests, HIV sequence data is increasingly available and can be used to reconstruct the phylogenetic relationship among viral lineages. In this study we employ a phylodynamic approach to quantify the fitness costs of major resistance mutations in the Swiss HIV cohort. The viral phylogeny reflects the transmission tree, which we model using stochastic birth-death-sampling processes with two types: hosts infected by a sensitive or resistant strain. This allows quantification of fitness cost as the ratio between transmission rates of hosts infected by drug resistant strains and transmission rates of hosts infected by drug sensitive strains. The resistance mutations 41L, 67N, 70R, 184V, 210W, 215D, 215S and 219Q (nRTI-related) and 103N, 108I, 138A, 181C, 190A (NNRTI-related) in the reverse trancriptase and the 90M mutation in the protease gene are included in this study. Among the considered resistance mutations, only the 90M mutation in the protease gene was found to have significantly higher fitness than the drug sensitive strains. The following mutations associated with resistance to reverse transcriptase inhibitors were found to be less fit than the sensitive strains: 67N, 70R, 184V, 219Q. The highest posterior density intervals of the transmission ratios for the remaining resistance mutations included in this study all included 1, suggesting that these mutations do not have a significant effect on viral transmissibility within the Swiss HIV cohort. These patterns are consistent with alternative measures of the fitness cost of resistance mutations. Overall, we have developed and validated a novel phylodynamic approach to estimate the transmission fitness cost of drug resistance mutations.

BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.

Tracing the Impact of Public Health Interventions on HIV-1 Transmission in Portugal Using Molecular Epidemiology.

BACKGROUND: Estimation of temporal changes in human immunodeficiency virus (HIV) transmission patterns can help to elucidate the impact of preventive strategies and public health policies. METHODS: Portuguese HIV-1 subtype B and G pol genetic sequences were appended to global reference data sets to identify country-specific transmission clades. Bayesian birth-death models were used to estimate subtype-specific effective reproductive numbers (Re). Discrete trait analysis (DTA) was used to quantify mixing among transmission groups. RESULTS: We identified 5 subtype B Portuguese clades (26-79 sequences) and a large monophyletic subtype G Portuguese clade (236 sequences). We estimated that major shifts in HIV-1 transmission occurred around 1999 (95% Bayesian credible interval [BCI], 1998-2000) and 2000 (95% BCI, 1998-2001) for subtypes B and G, respectively. For subtype B, Re dropped from 1.91 (95% BCI, 1.73-2.09) to 0.62 (95% BCI,.52-.72). For subtype G, Re decreased from 1.49 (95% BCI, 1.39-1.59) to 0.72 (95% BCI, .63-.8). The DTA suggests that people who inject drugs (PWID) and heterosexuals were the source of most (>80%) virus lineage transitions for subtypes G and B, respectively. CONCLUSIONS: The estimated declines in Re coincide with the introduction of highly active antiretroviral therapy and the scale-up of harm reduction for PWID. Inferred transmission events across transmission groups emphasize the importance of prevention efforts for bridging populations.

Taming the BEAST-A Community Teaching Material Resource for BEAST 2.

Phylogenetics and phylodynamics are central topics in modern evolutionary biology. Phylogenetic methods reconstruct the evolutionary relationships among organisms, whereas phylodynamic approaches reveal the underlying diversification processes that lead to the observed relationships. These two fields have many practical applications in disciplines as diverse as epidemiology, developmental biology, palaeontology, ecology, and linguistics. The combination of increasingly large genetic data sets and increases in computing power is facilitating the development of more sophisticated phylogenetic and phylodynamic methods. Big data sets allow us to answer complex questions. However, since the required analyses are highly specific to the particular data set and question, a black-box method is not sufficient anymore. Instead, biologists are required to be actively involved with modeling decisions during data analysis. The modular design of the Bayesian phylogenetic software package BEAST 2 enables, and in fact enforces, this involvement. At the same time, the modular design enables computational biology groups to develop new methods at a rapid rate. A thorough understanding of the models and algorithms used by inference software is a critical prerequisite for successful hypothesis formulation and assessment. In particular, there is a need for more readily available resources aimed at helping interested scientists equip themselves with the skills to confidently use cutting-edge phylogenetic analysis software. These resources will also benefit researchers who do not have access to similar courses or training at their home institutions. Here, we introduce the "Taming the Beast" (https://taming-the-beast.github.io/) resource, which was developed as part of a workshop series bearing the same name, to facilitate the usage of the Bayesian phylogenetic software package BEAST 2.

Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods' development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention.

Phylodynamics with Migration: A Computational Framework to Quantify Population Structure from Genomic Data.

When viruses spread, outbreaks can be spawned in previously unaffected regions. Depending on the time and mode of introduction, each regional outbreak can have its own epidemic dynamics. The migration and phylodynamic processes are often intertwined and need to be taken into account when analyzing temporally and spatially structured virus data. In this article, we present a fully probabilistic approach for the joint reconstruction of phylodynamic history in structured populations (such as geographic structure) based on a multitype birth-death process. This approach can be used to quantify the spread of a pathogen in a structured population. Changes in epidemic dynamics through time within subpopulations are incorporated through piecewise constant changes in transmission parameters.We analyze a global human influenza H3N2 virus data set from a geographically structured host population to demonstrate how seasonal dynamics can be inferred simultaneously with the phylogeny and migration process. Our results suggest that the main migration path among the northern, tropical, and southern region represented in the sample analyzed here is the one leading from the tropics to the northern region. Furthermore, the time-dependent transmission dynamics between and within two HIV risk groups, heterosexuals and injecting drug users, in the Latvian HIV epidemic are investigated. Our analyses confirm that the Latvian HIV epidemic peaking around 2001 was mainly driven by the injecting drug user risk group.

Phylodynamics of Enterovirus A71-Associated Hand, Foot, and Mouth Disease in Viet Nam.

UNLABELLED: Enterovirus A71 (EV-A71) is a major cause of hand, foot, and mouth disease (HFMD) and is particularly prevalent in parts of Southeast Asia, affecting thousands of children and infants each year. Revealing the evolutionary and epidemiological dynamics of EV-A71 through time and space is central to understanding its outbreak potential. We generated the full genome sequences of 200 EV-A71 strains sampled from various locations in Viet Nam between 2011 and 2013 and used these sequence data to determine the evolutionary history and phylodynamics of EV-A71 in Viet Nam, providing estimates of the effective reproduction number (Re) of the infection through time. In addition, we described the phylogeography of EV-A71 throughout Southeast Asia, documenting patterns of viral gene flow. Accordingly, our analysis reveals that a rapid genogroup switch from C4 to B5 likely took place during 2012 in Viet Nam. We show that the Re of subgenogroup C4 decreased during the time frame of sampling, whereas that of B5 increased and remained >1 at the end of 2013, corresponding to a rise in B5 prevalence. Our study reveals that the subgenogroup B5 virus that emerged into Viet Nam is closely related to variants that were responsible for large epidemics in Malaysia and Taiwan and therefore extends our knowledge regarding its associated area of endemicity. Subgenogroup B5 evidently has the potential to cause more widespread outbreaks across Southeast Asia. IMPORTANCE: EV-A71 is one of many viruses that cause HFMD, a common syndrome that largely affects infants and children. HFMD usually causes only mild illness with no long-term consequences. Occasionally, however, severe infection may arise, especially in very young children, causing neurological complications and even death. EV-A71 is highly contagious and is associated with the most severe HFMD cases, with large and frequent epidemics of the virus recorded worldwide. Although major advances have been made in the development of a potential EV-A71 vaccine, there is no current prevention and little is known about the patterns and dynamics of EV-A71 spread. In this study, we utilize full-length genome sequence data obtained from HFMD patients in Viet Nam, a geographical region where the disease has been endemic since 2003, to characterize the phylodynamics of this important emerging virus.

Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV).

Phylogenetic trees can be used to infer the processes that generated them. Here, we introduce a model, the bayesian birth-death skyline plot, which explicitly estimates the rate of transmission, recovery, and sampling and thus allows inference of the effective reproductive number directly from genetic data. Our method allows these parameters to vary through time in a piecewise fashion and is implemented within the BEAST2 software framework. The method is a powerful alternative to the existing coalescent skyline plot, providing insight into the differing roles of incidence and prevalence in an epidemic. We apply this method to data from the United Kingdom HIV-1 epidemic and Egyptian hepatitis C virus (HCV) epidemic. The analysis reveals temporal changes of the effective reproductive number that highlight the effect of past public health interventions.

How well can the exponential-growth coalescent approximate constant-rate birth-death population dynamics?

One of the central objectives in the field of phylodynamics is the quantification of population dynamic processes using genetic sequence data or in some cases phenotypic data. Phylodynamics has been successfully applied to many different processes, such as the spread of infectious diseases, within-host evolution of a pathogen, macroevolution and even language evolution. Phylodynamic analysis requires a probability distribution on phylogenetic trees spanned by the genetic data. Because such a probability distribution is not available for many common stochastic population dynamic processes, coalescent-based approximations assuming deterministic population size changes are widely employed. Key to many population dynamic models, in particular epidemiological models, is a period of exponential population growth during the initial phase. Here, we show that the coalescent does not well approximate stochastic exponential population growth, which is typically modelled by a birth-death process. We demonstrate that introducing demographic stochasticity into the population size function of the coalescent improves the approximation for values of R0 close to 1, but substantial differences remain for large R0. In addition, the computational advantage of using an approximation over exact models vanishes when introducing such demographic stochasticity. These results highlight that we need to increase efforts to develop phylodynamic tools that correctly account for the stochasticity of population dynamic models for inference.

Efficient Bayesian inference under the structured coalescent.

MOTIVATION: Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and subpopulation sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo (MCMC) sampling algorithms (samplers) capable of efficiently exploring the state space. RESULTS: In this article, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylogenetic trees in which lineages are associated with the distinct subpopulation in which they lie. The sampler includes a set of MCMC proposal functions that offer significant mixing improvements over a previously published method. Furthermore, its implementation as a BEAST 2 package ensures maximum flexibility with respect to model and prior specification. We demonstrate the usefulness of this new sampler by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly available hemagglutinin (HA) gene sequences under the structured coalescent. AVAILABILITY AND IMPLEMENTATION: The sampler has been implemented as a publicly available BEAST 2 package that is distributed under version 3 of the GNU General Public License at http://compevol.github.io/MultiTypeTree.

Influenza a virus migration and persistence in North American wild birds.

Wild birds have been implicated in the emergence of human and livestock influenza. The successful prediction of viral spread and disease emergence, as well as formulation of preparedness plans have been hampered by a critical lack of knowledge of viral movements between different host populations. The patterns of viral spread and subsequent risk posed by wild bird viruses therefore remain unpredictable. Here we analyze genomic data, including 287 newly sequenced avian influenza A virus (AIV) samples isolated over a 34-year period of continuous systematic surveillance of North American migratory birds. We use a Bayesian statistical framework to test hypotheses of viral migration, population structure and patterns of genetic reassortment. Our results reveal that despite the high prevalence of Charadriiformes infected in Delaware Bay this host population does not appear to significantly contribute to the North American AIV diversity sampled in Anseriformes. In contrast, influenza viruses sampled from Anseriformes in Alberta are representative of the AIV diversity circulating in North American Anseriformes. While AIV may be restricted to specific migratory flyways over short time frames, our large-scale analysis showed that the long-term persistence of AIV was independent of bird flyways with migration between populations throughout North America. Analysis of long-term surveillance data provides vital insights to develop appropriately informed predictive models critical for pandemic preparedness and livestock protection.

BEAST 2: a software platform for Bayesian evolutionary analysis.

We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.

Recombination-aware phylogenetic analysis sheds light on the evolutionary origin of SARS-CoV-2.

SARS-CoV-2 can infect human cells through the recognition of the human angiotensin-converting enzyme 2 receptor. This affinity is given by six amino acid residues located in the variable loop of the receptor binding domain (RBD) within the Spike protein. Genetic recombination involving bat and pangolin Sarbecoviruses, and natural selection have been proposed as possible explanations for the acquisition of the variable loop and these amino acid residues. In this study we employed Bayesian phylogenetics to jointly reconstruct the phylogeny of the RBD among human, bat and pangolin Sarbecoviruses and detect recombination events affecting this region of the genome. A recombination event involving RaTG13, the closest relative of SARS-CoV-2 that lacks five of the six residues, and an unsampled Sarbecovirus lineage was detected. This result suggests that the variable loop of the RBD didn't have a recombinant origin and the key amino acid residues were likely present in the common ancestor of SARS-CoV-2 and RaTG13, with the latter losing five of them probably as the result of recombination.