Bayesian phylodynamic inference on the temporal evolution and global transmission of SARS-CoV-2

Comprehensive phylogeographic and phylodynamic analyses of global Senecavirus A

Senecavirus A (SVA) is a member of the genus Senecavirus in the family Picornaviridae that infects pigs and shows symptoms similar to foot and mouth diseases and other vesicular diseases. It is difficult to prevent, thus, causing tremendous economic loss to the pig industry. However, the global transmission routes of SVA and its natural origins remain unclear. In this study, we processed representative SVA sequences from the GenBank database along with 10 newly isolated SVA strains from the field samples collected from our lab to explore the origins, population characteristics, and transmission patterns of SVA. The SVA strains were firstly systematically divided into eight clades including Clade I–VII and Clade Ancestor based on the maximum likelihood phylogenetic inference. Phylogeographic and phylodynamics analysis within the Bayesian statistical framework revealed that SVA originated in the United States in the 1980s and afterward spread to different countries and regions. Our analysis of viral transmission routes also revealed its historical spread from the United States and the risk of the global virus prevalence. Overall, our study provided a comprehensive assessment of the phylogenetic characteristics, origins, history, and geographical evolution of SVA on a global scale, unlocking insights into developing efficient disease management strategies.

Exploring the dynamic variations of viral genomes via a novel genetic network

Exploring the dynamic variations of viral genomes utilizing with a phylogenetic analysis is vital to control the pandemic and stop its waves. Genetic network can be applied to depict the complicated evolution relationships of viral genomes. However, current phylogenetic methods cannot handle the cases with deletions effectively. Therefore, the k-mer natural vector is employed to characterize the compositions and distribution features of k-mers occurring in a viral genome, and construct a one-to-one relationship between a viral genome and its k-mer natural vector. Utilizing the k-mer natural vector, we proposed a novel genetic network to investigate the variations of viral genomes in transmission among humans. With the assistance of genetic network, we identified the super-spreaders that were responsible for the pandemic outbreaks all over the world and chose the parental strains to evaluate the effectiveness of diagnostics, therapeutics, and vaccines. The obtaining results fully demonstrated that our genetic network can truly describe the relationships of viral genomes, effectively simulate virus spread tendency, and trace the transmission routes precisely. In addition, this work indicated that the k-mer natural vector has the ability to capture established hotspots of diversities existing in the viral genomes and understand how genomic contents change over time.

Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10-3 (1.292 × 10-3 to 1.613 × 10-3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

Phylogenomics reveals multiple introductions and early spread of SARS-CoV-2 into Peru

Peru has become one of the countries with the highest mortality rates from the current coronavirus disease 2019 (COVID‐19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). To investigate early transmission events and the genomic diversity of SARS‐CoV‐2 isolates circulating in Peru in the early COVID‐19 pandemic, we analyzed 3472 viral genomes, of which 149 were from Peru. Phylogenomic analysis revealed multiple and independent introductions of the virus likely from Europe and Asia and a high diversity of genetic lineages circulating in Peru. In addition, we found evidence for community‐driven transmission of SARS‐CoV‐2 as suggested by clusters of related viruses found in patients living in different regions of Peru.

This is the first snapshot of the sources of epidemic transmission and genomic diversity of SARS‐CoV‐2 lineages circulating in Peru during the early COVID‐19 pandemic. Phylogenomic analysis revealed multiple and independent introductions of the virus likely from Europe and Asia, and high diversity of genetic lineages circulating in Peru with predominance of the G614G variant (S gene,n= 136/149). We found evidence that early spread of the virus in Lima City was sustained by community transmission.

Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We investigate several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, whereas methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. These results suggest that phylogenetic evidence alone is unlikely to identify the origin of the SARS-CoV-2 virus and we caution against strong inferences regarding the early spread of the virus based solely on such evidence.

Challenges in estimating virus divergence times in short epidemic timescales with special reference to the evolution of SARS-CoV-2 pandemic

The estimation of evolutionary parameters provides essential information for designing public health policies. In short time intervals, however, nucleotide substitutions are ineffective to record all complexities of virus population dynamics. In this sense, the current SARS-CoV-2 pandemic poses a challenge for evolutionary analysis. We used computer simulation to evolve populations in scenarios of varying temporal intervals to evaluate the impact of the age of an epidemic on estimates of time and geography. Before estimating virus timescales, the shape of tree topologies can be used as a proxy to assess the effectiveness of the virus phylogeny in providing accurate estimates of evolutionary parameters. In short timescales, estimates have larger uncertainty. We compared the predictions from simulations with empirical data. The tree shape of SARS-CoV-2 was closer to shorter timescales scenarios, which yielded parametric estimates with larger uncertainty, suggesting that estimates from these datasets should be evaluated cautiously. To increase the accuracy of the estimates of virus transmission times between populations, the uncertainties associated with the age estimates of both the crown and stem nodes should be communicated. We place the age of the common ancestor of the current SARS-CoV-2 pandemic in late September 2019, corroborating an earlier emergence of the virus.

Population Genomics Insights into the First Wave of COVID-19

Full-genome-sequence computational analyses of the SARS-coronavirus (CoV)-2 genomes allow us to understand the evolutionary events and adaptability mechanisms. We used population genetics analyses on human SARS-CoV-2 genomes available on 2 April 2020 to infer the mutation rate and plausible recombination events between the Betacoronavirus genomes in nonhuman hosts that may have contributed to the evolution of SARS-CoV-2. Furthermore, we localized the targets of recent and strong, positive selection during the first pandemic wave. The genomic regions that appear to be under positive selection are largely co-localized with regions in which recombination from nonhuman hosts took place. Our results suggest that the pangolin coronavirus genome may have contributed to the SARS-CoV-2 genome by recombination with the bat coronavirus genome. However, we find evidence for additional recombination events that involve coronavirus genomes from other hosts, i.e., hedgehogs and sparrows. We further infer that recombination may have recently occurred within human hosts. Finally, we estimate the parameters of a demographic scenario involving an exponential growth of the size of the SARS-CoV-2 populations that have infected European, Asian, and Northern American cohorts, and we demonstrate that a rapid exponential growth in population size from the first wave can support the observed polymorphism patterns in SARS-CoV-2 genomes.

Decoding Covid-19 with the SARS-CoV-2 Genome

Purpose of Review

SARS-CoV-2, the recently emerged coronavirus (CoV) that is responsible for the current global pandemic Covid-19, first appeared in late 2019 in Wuhan, China. Here, we summarise details of the SARS-CoV-2 genome to assist understanding of the emergence, evolution and diagnosis of this deadly new virus.

Recent Findings

Based on high similarities in the genome sequences, the virus is thought to have arisen from SARS-like CoVs in bats but the lack of an intermediate species containing a CoV with even greater similarity has so far eluded discovery. The critical determinant of the SARS-CoV-2 genome is the spike (S) gene encoding the viral structural protein that interacts with the host cell entry receptor ACE2. The S protein is sufficiently adapted to bind human ACE2 much more readily than SARS-CoV, the most closely related human CoV.

Summary

Although the SARS-CoV-2 genome is undergoing subtle evolution in humans through mutation that may enhance transmission, there is limited evidence for attenuation that might weaken the virus. It is also still unclear as to the events that led to the virus’ emergence from bats. Importantly, current diagnosis requires specific recognition and amplification of the SARS-CoV-2 RNA genome by qPCR, despite these ongoing viral genome changes. Alternative diagnostic procedures relying on immunoassay are becoming more prevalent.

Genetic variations among SARS-CoV-2 strains isolated in China

The rapid spread of COVID-19, which has led to a global pandemic, has placed public health systems under severe pressure. Identifying variations in SARS-CoV-2 strains from different regions is a key factor for understanding the pathogenic mechanisms, aid in diagnosis, prevention and therapy of this disease. The present study is an analytical descriptive study aimed to determine genetic variations among SARS-CoV-2 strains isolated in China. Sixty six complete genome sequences of the virus were retrieved from NCBI, the sequence of original Wuhan strain accession number NC 045512 was used as the reference sequence. Each genome sequence was blasted against the original Wuhan strain; the analysis was done using NCBI Nucleo-blast. The collected sequences showed 10 different variants. One hundred and thirty four mutations were identified among the variants of SARS-CoV-2 in this study; most of them 52.2% (70/134) were missense point mutation, majority of the mutations 65.7% (88/134) occurred in the open reading frame a/b (ORFab), few mutations occurred in the structural viral genome, each of spike (S) gene and nucleocapsid (N) gene showed 4 mutations; 2 silent point mutations and 2 missense point mutations occurred in each gene whereas membrane (M) gene showed silent point mutation and no mutation observed in the envelope E gene. The remarkable observation in this study showed by Yunnan variant accession number MT226610 which exhibited high incidence of mutations, it displayed 28 different point mutations; only 3(10.7%) of them were silent mutations while the rest were missense mutations. Our analysis showed several mutations including spike S gene and membrane M gene which may be responsible for a change in the structures of target proteins.

Substitutions in Spike and Nucleocapsid proteins of SARS-CoV-2 circulating in South America

SARS-CoV-2 is a new member of the genus Betacoronavirus, responsible for the COVID-19 pandemic. The virus crossed the species barrier and established in the human population taking advantage of the spike protein high affinity for the ACE receptor to infect the lower respiratory tract. The Nucleocapsid (N) and Spike (S) are highly immunogenic structural proteins and most commercial COVID-19 diagnostic assays target these proteins. In an unpredictable epidemic, it is essential to know about their genetic variability. The objective of this study was to describe the substitution frequency of the S and N proteins of SARS-CoV-2 in South America. A total of 504 amino acid and nucleotide sequences of the S and N proteins of SARS-CoV-2 from seven South American countries (Argentina, Brazil, Chile, Ecuador, Peru, Uruguay, and Colombia), reported as of June 3, and corresponding to samples collected between March and April 2020, were compared through substitution matrices using the Muscle algorithm. Forty-three sequences from 13 Colombian departments were obtained in this study using the Oxford Nanopore and Illumina MiSeq technologies, following the amplicon-based ARTIC network protocol. The substitutions D614G in S and R203K/G204R in N were the most frequent in South America, observed in 83% and 34% of the sequences respectively. Strikingly, genomes with the conserved position D614 were almost completely replaced by genomes with the G614 substitution between March to April 2020. A similar replacement pattern was observed with R203K/G204R although more marked in Chile, Argentina and Brazil, suggesting similar introduction history and/or control strategies of SARS-CoV-2 in these countries. It is necessary to continue with the genomic surveillance of S and N proteins during the SARS-CoV-2 pandemic as this information can be useful for developing vaccines, therapeutics and diagnostic tests.

Molecular analysis of several in-house rRT-PCR protocols for SARS-CoV-2 detection in the context of genetic variability of the virus in Colombia

The COVID-19 pandemic caused by SARS-CoV-2 is a public health problem unprecedented in the recent history of humanity. Different in-house real-time RT-PCR (rRT-PCR) methods for SARS-CoV-2 diagnosis and the appearance of genomes with mutations in primer regions have been reported. Hence, whole-genome data from locally-circulating SARS-CoV-2 strains contribute to the knowledge of its global variability and the development and fine tuning of diagnostic protocols. To describe the genetic variability of Colombian SARS-CoV-2 genomes in hybridization regions of oligonucleotides of the main in-house methods for SARS-CoV-2 detection, RNA samples with confirmed SARS-CoV-2 molecular diagnosis were processed through next-generation sequencing. Primers/probes sequences from 13 target regions for SARS-CoV-2 detection suggested by 7 institutions and consolidated by WHO during the early stage of the pandemic were aligned with Muscle tool to assess the genetic variability potentially affecting their performance. Finally, the corresponding codon positions at the 3' end of each primer, the open reading frame inspection was identified for each gene/protein product. Complete SARS-CoV-2 genomes were obtained from 30 COVID-19 cases, representative of the current epidemiology in the country. Mismatches between at least one Colombian sequence and five oligonucleotides targeting the RdRP and N genes were observed. The 3' end of 4 primers aligned to the third codon position, showed high risk of nucleotide substitution and potential mismatches at this critical position. Genetic variability was detected in Colombian SARS-CoV-2 sequences in some of the primer/probe regions for in-house rRT-PCR diagnostic tests available at WHO COVID-19 technical guidelines; its impact on the performance and rates of false-negative results should be experimentally evaluated. The genomic surveillance of SARS-CoV-2 is highly recommended for the early identification of mutations in critical regions and to issue recommendations on specific diagnostic tests to ensure the coverage of locally-circulating genetic variants.

Identification of the nucleotide substitutions in 62 SARS-CoV-2 sequences from Turkey

A previously unknown coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been shown to cause coronavirus disease 2019 (COVID-19) pandemic. The first case of COVID-19 in Turkey has been declared in March 11th, 2020 and from there on, more than 150,000 people in the country have been diagnosed with the disease. In this study, 62 viral sequences from Turkey, which have been uploaded to GISAID database, were analyzed by means of their nucleotide substitutions in comparison to the reference SARS-CoV-2 genome from Wuhan. Our results indicate that the viral isolates from Turkey harbor some common mutations with the viral strains from Europe, Oceania, North America and Asia. When the mutations were evaluated, C3037T, C14408T and A23403G were found to be the most common nucleotide substitutions among the viral isolates in Turkey, which are mostly seen as linked mutations and are part of a haplotype observed high in Europe.