Time dependence of evolutionary metrics during the 2009 pandemic influenza virus outbreak

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

An atlas of continuous adaptive evolution in endemic human viruses

Through antigenic evolution, viruses such as seasonal influenza evade recognition by neutralizing antibodies. This means that a person with antibodies well tuned to an initial infection will not be protected against the same virus years later and that vaccine-mediated protection will decay. To expand our understanding of which endemic human viruses evolve in this fashion, we assess adaptive evolution across the genome of 28 endemic viruses spanning a wide range of viral families and transmission modes. Surface proteins consistently show the highest rates of adaptation, and ten viruses in this panel are estimated to undergo antigenic evolution to selectively fix mutations that enable the escape of prior immunity. Thus, antibody evasion is not an uncommon evolutionary strategy among human viruses, and monitoring this evolution will inform future vaccine efforts. Additionally, by comparing overall amino acid substitution rates, we show that SARS-CoV-2 is accumulating protein-coding changes at substantially faster rates than endemic viruses.

The Influenza B Virus Victoria and Yamagata Lineages Display Distinct Cell Tropism and Infection-Induced Host Gene Expression in Human Nasal Epithelial Cell Cultures

Understanding Influenza B virus infections is of critical importance in our efforts to control severe influenza and influenza-related diseases. Until 2020, two genetic lineages of influenza B virus-Yamagata and Victoria-circulated in the population. These lineages are antigenically distinct, but the differences in virus replication or the induction of host cell responses after infection have not been carefully studied. Recent IBV clinical isolates of both lineages were obtained from influenza surveillance efforts of the Johns Hopkins Center of Excellence in Influenza Research and Response and characterized in vitro. B/Victoria and B/Yamagata clinical isolates were recognized less efficiently by serum from influenza-vaccinated individuals in comparison to the vaccine strains. B/Victoria lineages formed smaller plaques on MDCK cells compared to B/Yamagata, but infectious virus production in primary human nasal epithelial cell (hNEC) cultures showed no differences. While ciliated epithelial cells were the dominant cell type infected by both lineages, B/Victoria lineages had a slight preference for MUC5AC-positive cells, and B/Yamagata lineages infected more basal cells. Finally, while both lineages induced a strong interferon response 48 h after infection of hNEC cultures, the B/Victoria lineages showed a much stronger induction of interferon-related signaling pathways compared to B/Yamagata. This demonstrates that the two influenza B virus lineages differ not only in their antigenic structure but also in their ability to induce host innate immune responses.

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Contributions of adaptation and purifying selection to SARS-CoV-2 evolution

Continued evolution and adaptation of SARS-CoV-2 has led to more transmissible and immune-evasive variants with profound impacts on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate the rates of evolution for synonymous and non-synonymous changes separately for evolution within clades-well-defined monophyletic groups with gradual evolution-and for the pandemic overall. The rate of synonymous mutation is found to be around 6 changes per year. Synonymous rates within variants vary little from variant to variant and are compatible with the overall rate of 7 changes per year (or [Formula: see text] per year and codon). In contrast, the rate at which variants accumulate amino acid changes (non-synonymous mutations) was initially around 12-16 changes per year, but in 2021 and 2022 it dropped to 6-9 changes per year. The overall rate of non-synonymous evolution, that is across variants, is estimated to be about 26 amino acid changes per year (or [Formula: see text] per year and codon). This strong acceleration of the overall rate compared to within clade evolution indicates that the evolutionary process that gave rise to the different variants is qualitatively different from that in typical transmission chains and likely dominated by adaptive evolution. I further quantify the spectrum of mutations and purifying selection in different SARS-CoV-2 proteins and show that the massive global sampling of SARS-CoV-2 is sufficient to estimate site-specific fitness costs across the entire genome. Many accessory proteins evolve under limited evolutionary constraints with little short-term purifying selection. About half of the mutations in other proteins are strongly deleterious.

Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza

High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.

Molecular archeology of human viruses

The evolution of human-virus associations is usually reconstructed from contemporary patterns of genomic diversity. An intriguing, though still rarely implemented, alternative is to search for the genetic material of viruses in archeological and medical archive specimens to document evolution as it happened. In this chapter, we present lessons from ancient DNA research and incorporate insights from virology to explore the potential range of applications and likely limitations of archeovirological approaches. We also highlight the numerous questions archeovirology will hopefully allow us to tackle in the near future, and the main expected roadblocks to these avenues of research.

Genomic epidemiology of the first epidemic wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Palestine

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the COVID-19 pandemic, continues to cause a significant public-health burden and disruption globally. Genomic epidemiology approaches point to most countries in the world having experienced many independent introductions of SARS-CoV-2 during the early stages of the pandemic. However, this situation may change with local lockdown policies and restrictions on travel, leading to the emergence of more geographically structured viral populations and lineages transmitting locally. Here, we report the first SARS-CoV-2 genomes from Palestine sampled from early March 2020, when the first cases were observed, through to August of 2020. SARS-CoV-2 genomes from Palestine fall across the diversity of the global phylogeny, consistent with at least nine independent introductions into the region. We identify one locally predominant lineage in circulation represented by 50 Palestinian SARS-CoV-2, grouping with genomes generated from Israel and the UK. We estimate the age of introduction of this lineage to 05/02/2020 (16/01/2020-19/02/2020), suggesting SARS-CoV-2 was already in circulation in Palestine predating its first detection in Bethlehem in early March. Our work highlights the value of ongoing genomic surveillance and monitoring to reconstruct the epidemiology of COVID-19 at both local and global scales.

Analysis of selection in protein-coding sequences accounting for common biases

The evolution of protein-coding genes is usually driven by selective processes, which favor some evolutionary trajectories over others, optimizing the subsequent protein stability and activity. The analysis of selection in this type of genetic data is broadly performed with the metric nonsynonymous/synonymous substitution rate ratio (dN/dS). However, most of the well-established methodologies to estimate this metric make crucial assumptions, such as lack of recombination or invariable codon frequencies along genes, which can bias the estimation. Here, we review the most relevant biases in the dN/dS estimation and provide a detailed guide to estimate this metric using state-of-the-art procedures that account for such biases, along with illustrative practical examples and recommendations. We also discuss the traditional interpretation of the estimated dN/dS emphasizing the importance of considering complementary biological information such as the role of the observed substitutions on the stability and function of proteins. This review is oriented to help evolutionary biologists that aim to accurately estimate selection in protein-coding sequences.

Ancient Bacterial Genomes Reveal a High Diversity of Treponema pallidum Strains in Early Modern Europe

Syphilis is a globally re-emerging disease, which has marked European history with a devastating epidemic at the end of the 15^th century. Together with non-venereal treponemal diseases, like bejel and yaws, which are found today in subtropical and tropical regions, it currently poses a substantial health threat worldwide. The origins and spread of treponemal diseases remain unresolved, including syphilis' potential introduction into Europe from the Americas. Here, we present the first genetic data from archaeological human remains reflecting a high diversity of Treponema pallidum in early modern Europe. Our study demonstrates that a variety of strains related to both venereal syphilis and yaws-causing T. pallidum subspecies were already present in Northern Europe in the early modern period. We also discovered a previously unknown T. pallidum lineage recovered as a sister group to yaws- and bejel-causing lineages. These findings imply a more complex pattern of geographical distribution and etiology of early treponemal epidemics than previously understood.

Phylogenetic Inference of H3N2 Canine Influenza A Outbreak in Ontario, Canada in 2018

The first Canadian H3N2 canine influenza A outbreak involving an Asian-origin H3N2 canine influenza virus (CIV) began in southwestern Ontario, Canada, in late December 2017. More H3N2 CIV cases were identified in central and eastern Ontario between March and October 2018. Based on epidemiological investigation, 5 clusters were identified (C1, C2, C3a, C3b, and C4); however, the origin of infection has only been revealed for epidemiological cluster C1. Here, we use phylogenetic analyses to unravel the links of virus transmission between the 5 epidemiological clusters and the origin of infection for all epidemiological clusters. Our results demonstrate that the Canadian H3N2 CIV sequences were grouped into four distinct phylogenetic clusters with minimal genetic diversity between these clusters. Large scale phylogenetic analysis of H3N2 CIV from around the globe showed that the Canadian CIVs formed a distinct new clade along with CIVs that have been circulating in the USA since 2017-2018 and in China since 2017. This clade shares a common ancestor of Asian origin. This study concludes that the H3N2 CIV outbreak in Ontario was driven by multiple introductions of South Korean/Chinese-origin H3N2 CIVs over 10 months.

Substantial Antigenic Drift in the Hemagglutinin Protein of Swine Influenza A Viruses

The degree of antigenic drift in swine influenza A viruses (swIAV) has historically been regarded as minimal compared to that of human influenza A virus strains. However, as surveillance activities on swIAV have increased, more isolates have been characterized, revealing a high level of genetic and antigenic differences even within the same swIAV lineage. The objective of this study was to investigate the level of genetic drift in one enzootically infected swine herd over one year. Nasal swabs were collected monthly from sows (n = 4) and piglets (n = 40) in the farrowing unit, and from weaners (n = 20) in the nursery. Virus from 1-4 animals were sequenced per month. Analyses of the sequences revealed that the hemagglutinin (HA) gene was the main target for genetic drift with a substitution rate of 7.6 × 10-3 substitutions/site/year and evidence of positive selection. The majority of the mutations occurred in the globular head of the HA protein and in antigenic sites. The phylogenetic tree of the HA sequences displayed a pectinate typology, where only a single lineage persists and forms the ancestor for subsequent lineages. This was most likely caused by repeated selection of a single immune-escape variant, which subsequently became the founder of the next wave of infections.

Bovine Astrovirus Surveillance in Uruguay Reveals High Detection Rate of a Novel Mamastrovirus Species

Viral infections affecting cattle lead to economic losses to the livestock industry worldwide, but little is known about the circulation, pathogenicity and genetic diversity of enteric bovine astrovirus (BoAstV) in America. The aim of this work was to describe the prevalence and genetic diversity of enteric BoAstV in dairy cattle in Uruguay. A total of 457 fecal and 43 intestinal contents from dairy calves were collected between July 2015 and May 2017 and tested by RT-PCR, followed by sequencing and phylogenetic analyses of the polymerase and capsid regions. Twenty-six percent (128/500) of the samples were positive. Three different species within the Mamastrovirus genus were identified, including Mamastrovirus 28, Mamastrovirus 33 (3 samples each) and an unclassified Mamastrovirus species (19 samples). The unclassified species was characterized as a novel Mamastrovirus species. BoAstV circulates in Uruguayan dairy cattle with a high genetic diversity. The eventual clinicopathological significance of enteric BoAstV infection in cattle needs further investigation.

The range of sampling times affects Zika virus evolutionary rates and divergence times

The rate of evolution of viral genomes is a fundamental parameter for understanding the origin and spread of epidemics. For instance, molecular dating is one of the many practical outcomes of evolutionary rate estimation. In this sense, the rate of evolution of ZIKV merits attention, because it has been shown to be higher than the average rate reported for other flaviviruses. It has been hypothesized that the higher rate of ZIKV evolution is due to a bias related to the analysis of sequences collected within a short time range, which would increase the chance of sampling slightly deleterious nucleotide polymorphisms. To investigate this hypothesis, we assembled datasets with different ranges of sampling times and also decomposed the ZIKV evolutionary rate into synonymous and non-synonymous rates. Our results demonstrated that the rate of ZIKV evolution is time dependent and that the observed increase in short-term rates is largely accounted for by a higher non-synonymous rate, suggesting the presence of slightly deleterious variants not yet eliminated by purifying selection. On the other hand, we show that synonymous rates were less impacted by the range of sampling times, generating timescales with reduced uncertainty. We conclude that, for inferring the ZIKV timescale and reconstructing the history of epidemics, synonymous changes are the most appropriate substitution type to be examined. We were able to obtain ZIKV divergence times that were time independent and exhibited greater precision than previous estimates. This observation should also hold for other serially sampled fast-evolving pathogens with evidence of time dependence of evolutionary rates.

H1N1 seasonal influenza virus evolutionary rate changed over time

It was previously shown that the seasonal H1N1 influenza virus antigenic drift occurred at a slower rate than the seasonal H3N2 virus during the first decade of the 21th century. It was hypothesized that the slower antigenic evolution led to a decrease in average ages of infection, which in turn resulted in lower level of global viral circulation. It is unclear what caused the difference between the two viruses, but a plausible explanation may be related to the fact that the H1N1 virus had been in human population for much longer than the H3N2 virus. This would suggest that H1N1 antigenic drift in an earlier period may have been different from a more recent period. To test this hypothesis, we analyzed seasonal H1N1 influenza sequences during various time periods. In comparison to more recent H1N1 virus, the older H1N1 virus during the first half of the 20th century showed evidences of higher nonsynnonymous/synonymous ration (dN/dS) in its hemagglutinin (HA) gene. We compared amino acid sequence changes in the HA epitopes for each outbreak season and found that there were less changes in later years. Amino acid sequence diversity in the epitopes as measured by sequence entropy became smaller for each passing decade. These suggest that there might be some limit to the antigenic drift. The longer an influenza virus has drifted in human population, the less flexibility it may become. With less flexibility to adapt and escape the host immunity, the virus may have to rely more on younger naïve population.

The substitution rate of HIV-1 subtypes: a genomic approach

HIV-1M causes most infections in the AIDS pandemic. Its genetic diversity is defined by nine pure subtypes and more than sixty recombinant forms. We have performed a comparative analysis of the evolutionary rate of five pure subtypes (A1, B, C, D, and G) and two circulating recombinant forms (CRF01_AE and CRF02 AG) using data obtained from nearly complete genome coding sequences. Times to the most recent common ancestor (tMRCA) and substitution rates of these HIV genomes, and their genomic partitions, were estimated by Bayesian coalescent analyses. Genomic substitution rate estimates were compared between the HIV-1 datasets analyzed by means of randomization tests. Significant differences in the rate of evolution were found between subtypes, with subtypes C and A1 and CRF01_AE displaying the highest rates. On the other hand, CRF02_AG and subtype D were the slowest evolving types. Using a different molecular clock model for each genomic partition led to more precise tMRCA estimates than when linking the same clock along the HIV genome. Overall, the earliest tMRCA corresponded to subtype A1 (median = 1941, 95% HPD = 1943-55), whereas the most recent tMRCA corresponded to subtype G and CRF01_AE subset 3 (median = 1971, 95% HPD = 1967-75 and median = 1972, 95% HPD = 1970-75, respectively). These results suggest that both biological and epidemiological differences among HIV-1M subtypes are reflected in their evolutionary dynamics. The estimates obtained for tMRCAs and substitution rates provide information that can be used as prior distributions in future Bayesian coalescent analyses of specific HIV-1 subtypes/CRFs and genes.

The Evolutionary History and Spatiotemporal Dynamics of the NC Lineage of Citrus Tristeza Virus

Citrus tristeza virus (CTV) is a major pathogen affecting citrus trees worldwide. However, few studies have focused on CTV's evolutionary history and geographic behavior. CTV is locally dispersed by an aphid vector and long distance dispersion due to transportation of contaminated material. With the aim to delve deeper into the CTV-NC (New Clade) genotype evolution, we estimated an evolution rate of 1.19 × 10^-3 subs/site/year and the most common recent ancestor in 1977. Furthermore, the place of origin of the genotype was in the United States, and a great expansion of the population was observed in Uruguay. This expansion phase could be a consequence of the increment in the number of naïve citrus trees in Uruguayan orchards encompassing citrus industry growth in the past years.

A Comparison of One-Rate and Two-Rate Inference Frameworks for Site-Specific dN/dS Estimation

Two broad paradigms exist for inferring [Formula: see text] the ratio of nonsynonymous to synonymous substitution rates, from coding sequences: (i) a one-rate approach, where [Formula: see text] is represented with a single parameter, or (ii) a two-rate approach, where [Formula: see text] and [Formula: see text] are estimated separately. The performances of these two approaches have been well studied in the specific context of proper model specification, i.e., when the inference model matches the simulation model. By contrast, the relative performances of one-rate vs. two-rate parameterizations when applied to data generated according to a different mechanism remain unclear. Here, we compare the relative merits of one-rate and two-rate approaches in the specific context of model misspecification by simulating alignments with mutation-selection models rather than with [Formula: see text]-based models. We find that one-rate frameworks generally infer more accurate [Formula: see text] point estimates, even when [Formula: see text] varies among sites. In other words, modeling [Formula: see text] variation may substantially reduce accuracy of [Formula: see text] point estimates. These results appear to depend on the selective constraint operating at a given site. For sites under strong purifying selection ([Formula: see text]), one-rate and two-rate models show comparable performances. However, one-rate models significantly outperform two-rate models for sites under moderate-to-weak purifying selection. We attribute this distinction to the fact that, for these more quickly evolving sites, a given substitution is more likely to be nonsynonymous than synonymous. The data will therefore be relatively enriched for nonsynonymous changes, and modeling [Formula: see text] contributes excessive noise to [Formula: see text] estimates. We additionally find that high levels of divergence among sequences, rather than the number of sequences in the alignment, are more critical for obtaining precise point estimates.

The utility of protein structure as a predictor of site-wise dN/dS varies widely among HIV-1 proteins

Protein structure acts as a general constraint on the evolution of viral proteins. One widely recognized structural constraint explaining evolutionary variation among sites is the relative solvent accessibility (RSA) of residues in the folded protein. In influenza virus, the distance from functional sites has been found to explain an additional portion of the evolutionary variation in the external antigenic proteins. However, to what extent RSA and distance from a reference site in the protein can be used more generally to explain protein adaptation in other viruses and in the different proteins of any given virus remains an open question. To address this question, we have carried out an analysis of the distribution and structural predictors of site-wise dN/dS in HIV-1. Our results indicate that the distribution of dN/dS in HIV follows a smooth gamma distribution, with no special enrichment or depletion of sites with dN/dS at or above one. The variation in dN/dS can be partially explained by RSA and distance from a reference site in the protein, but these structural constraints do not act uniformly among the different HIV-1 proteins. Structural constraints are highly predictive in just one of the three enzymes and one of three structural proteins in HIV-1. For these two proteins, the protease enzyme and the gp120 structural protein, structure explains between 30 and 40% of the variation in dN/dS. Finally, for the gp120 protein of the receptor-binding complex, we also find that glycosylation sites explain just 2% of the variation in dN/dS and do not explain gp120 evolution independently of either RSA or distance from the apical surface.

Bayesian coalescent inference reveals high evolutionary rates and diversification of Zika virus populations

Zika virus (ZIKV) is a member of the family Flaviviridae. In 2015, ZIKV triggered an epidemic in Brazil and spread across Latin America. By May of 2016, the World Health Organization warns over spread of ZIKV beyond this region. Detailed studies on the mode of evolution of ZIKV strains are extremely important for our understanding of the emergence and spread of ZIKV populations. In order to gain insight into these matters, a Bayesian coalescent Markov Chain Monte Carlo analysis of complete genome sequences of recently isolated ZIKV strains was performed. The results of these studies revealed a mean rate of evolution of 1.20 × 10(-3) nucleotide substitutions per site per year (s/s/y) for ZIKV strains enrolled in this study. Several variants isolated in China are grouped together with all strains isolated in Latin America. Another genetic group composed exclusively by Chinese strains were also observed, suggesting the co-circulation of different genetic lineages in China. These findings indicate a high level of diversification of ZIKV populations. Strains isolated from microcephaly cases do not share amino acid substitutions, suggesting that other factors besides viral genetic differences may play a role for the proposed pathogenesis caused by ZIKV infection. J. Med. Virol. 88:1672-1676, 2016. © 2016 Wiley Periodicals, Inc.

Zika virus in the Americas: Early epidemiological and genetic findings

Brazil has experienced an unprecedented epidemic of Zika virus (ZIKV), with ~30,000 cases reported to date. ZIKV was first detected in Brazil in May 2015, and cases of microcephaly potentially associated with ZIKV infection were identified in November 2015. We performed next-generation sequencing to generate seven Brazilian ZIKV genomes sampled from four self-limited cases, one blood donor, one fatal adult case, and one newborn with microcephaly and congenital malformations. Results of phylogenetic and molecular clock analyses show a single introduction of ZIKV into the Americas, which we estimated to have occurred between May and December 2013, more than 12 months before the detection of ZIKV in Brazil. The estimated date of origin coincides with an increase in air passengers to Brazil from ZIKV-endemic areas, as well as with reported outbreaks in the Pacific Islands. ZIKV genomes from Brazil are phylogenetically interspersed with those from other South American and Caribbean countries. Mapping mutations onto existing structural models revealed the context of viral amino acid changes present in the outbreak lineage; however, no shared amino acid changes were found among the three currently available virus genomes from microcephaly cases. Municipality-level incidence data indicate that reports of suspected microcephaly in Brazil best correlate with ZIKV incidence around week 17 of pregnancy, although this correlation does not demonstrate causation. Our genetic description and analysis of ZIKV isolates in Brazil provide a baseline for future studies of the evolution and molecular epidemiology of this emerging virus in the Americas.

Causes of evolutionary rate variation among protein sites

It has long been recognized that certain sites within a protein, such as sites in the protein core or catalytic residues in enzymes, are evolutionarily more conserved than other sites. However, our understanding of rate variation among sites remains surprisingly limited. Recent progress to address this includes the development of a wide array of reliable methods to estimate site-specific substitution rates from sequence alignments. In addition, several molecular traits have been identified that correlate with site-specific mutation rates, and novel mechanistic biophysical models have been proposed to explain the observed correlations. Nonetheless, current models explain, at best, approximately 60% of the observed variance, highlighting the limitations of current methods and models and the need for new research directions.