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Evidence from the evolutionary analysis of nucleotide sequences for a recombinant history of SARS-CoV.

ABSTRACT: The origins and evolutionary history of the Severe Acute Respiratory Syndrome (SARS) coronavirus (SARS-CoV) remain an issue of uncertainty and debate. Based on evolutionary analyses of coronavirus DNA sequences, encompassing an approximately 13kb stretch of the SARS-TOR2 genome, we provide evidence that SARS-CoV has a recombinant history with lineages of types I and III coronavirus. We identified a minimum of five recombinant regions ranging from 83 to 863bp in length and including the polymerase, nsp9, nsp10, and nsp14. Our results are consistent with a hypothesis of viral host jumping events, concomitant with the reassortment of bird and mammalian coronaviruses, a scenario analogous to earlier outbreaks of influenzae.

SUBMITTER: Stanhope MJ

PROVIDER: S-EPMC7128439 | biostudies-literature | 2004 Mar

REPOSITORIES: biostudies-literature

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Evidence from the evolutionary analysis of nucleotide sequences for a recombinant history of SARS-CoV.

Stanhope Michael J MJ Brown James R JR Amrine-Madsen Heather H

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 20040301 1

The origins and evolutionary history of the Severe Acute Respiratory Syndrome (SARS) coronavirus (SARS-CoV) remain an issue of uncertainty and debate. Based on evolutionary analyses of coronavirus DNA sequences, encompassing an approximately 13kb stretch of the SARS-TOR2 genome, we provide evidence that SARS-CoV has a recombinant history with lineages of types I and III coronavirus. We identified a minimum of five recombinant regions ranging from 83 to 863bp in length and including the polymeras ...[more]

PMID: 15019585

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Project description:BackgroundSince the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses.MethodsUsing a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence.ResultsWe show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant.ConclusionsOur multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

Project description:Background & objectivesSeveral phylogenetic classification systems have been devised to trace the viral lineages of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, inconsistency in the nomenclature limits uniformity in its epidemiological understanding. This study provides an integration of existing classifications and describes evolutionary trends of the SARS-CoV-2 strains circulating in India.MethodsThe whole genomes of 330 SARS-CoV-2 samples were sequenced using next-generation sequencing (NGS). Phylogenetic and sequence analysis of a total of 3014 Indian SARS-CoV-2 sequences from 20 different States/Union Territories (January to September 2020) from the Global Initiative on Sharing All Influenza Data (GISAID) database was performed to observe the clustering of Nextstrain and Phylogenetic Assignment of Named Global Outbreak LINeages (Pangolin) lineages with the GISAID clades. The identification of mutational sites under selection pressure was performed using Mixed Effects Model of Evolution and Single-Likelihood Ancestor Counting methods available in the Datamonkey server.ResultsTemporal data of the Indian SARS-CoV-2 genomes revealed that except for Uttarakhand, West Bengal and Haryana that showed the circulation of GISAID clade O even after July 2020, the rest of the States showed a complete switch to GR/GH clades. Pangolin lineages B.1.1.8 and B.1.113 identified within GR and GH clades, respectively, were noted to be indigenous evolutions. Sites identified to be under positive selection pressure within these clades were found to occur majorly in the non-structural proteins coded by ORF1a and ORF1b.Interpretation & conclusionsThis study interpreted the geographical and temporal dominance of SARS-CoV-2 strains in India over a period of nine months based on the GISAID classification. An integration of the GISAID, Nextstrain and Pangolin classifications is also provided. The emergence of new lineages B.1.1.8 and B.1.113 was indicative of host-specific evolution of the SARS-CoV-2 strains in India. The hotspot mutations such as those driven by positive selection need to be further characterized.

Project description:BackgroundRooted phylogenetic networks are used to display complex evolutionary history involving so-called reticulation events, such as genetic recombination. Various methods have been developed to construct such networks, using for example a multiple sequence alignment or multiple phylogenetic trees as input data. Coronaviruses are known to recombine frequently, but rooted phylogenetic networks have not yet been used extensively to describe their evolutionary history. Here, we created a workflow to compare the evolutionary history of SARS-CoV-2 with other SARS-like viruses using several rooted phylogenetic network inference algorithms. This workflow includes filtering noise from sets of phylogenetic trees by contracting edges based on branch length and bootstrap support, followed by resolution of multifurcations. We explored the running times of the network inference algorithms, the impact of filtering on the properties of the produced networks, and attempted to derive biological insights regarding the evolution of SARS-CoV-2 from them.ResultsThe network inference algorithms are capable of constructing rooted phylogenetic networks for coronavirus data, although running-time limitations require restricting such datasets to a relatively small number of taxa. Filtering generally reduces the number of reticulations in the produced networks and increases their temporal consistency. Taxon bat-SL-CoVZC45 emerges as a major and structural source of discordance in the dataset. The tested algorithms often indicate that SARS-CoV-2/RaTG13 is a tree-like clade, with possibly some reticulate activity further back in their history. A smaller number of constructed networks posit SARS-CoV-2 as a possible recombinant, although this might be a methodological artefact arising from the interaction of bat-SL-CoVZC45 discordance and the optimization criteria used.ConclusionOur results demonstrate that as part of a wider workflow and with careful attention paid to running time, rooted phylogenetic network algorithms are capable of producing plausible networks from coronavirus data. These networks partly corroborate existing theories about SARS-CoV-2, and partly produce new avenues for exploration regarding the location and significance of reticulate activity within the wider group of SARS-like viruses. Our workflow may serve as a model for pipelines in which phylogenetic network algorithms can be used to analyse different datasets and test different hypotheses.

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Evidence from the evolutionary analysis of nucleotide sequences for a recombinant history of SARS-CoV.

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Evidence from the evolutionary analysis of nucleotide sequences for a recombinant history of SARS-CoV.

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