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Recombination and Positive Selection Differentially Shaped the Diversity of Betacoronavirus Subgenera.

ABSTRACT: The Betacoronavirus genus of mammal-infecting viruses includes three subgenera (Sarbecovirus, Embecovirus, and Merbecovirus), in which most known human coronaviruses, including SARS-CoV-2, cluster. Coronaviruses are prone to host shifts, with recombination and positive selection possibly contributing to their high zoonotic potential. We analyzed the role of these two forces in the evolution of viruses belonging to the Betacoronavirus genus. The results showed that recombination has been pervasive during sarbecovirus evolution, and it is more widespread in this subgenus compared to the other two. In both sarbecoviruses and merbecoviruses, recombination hotspots are clearly observed. Conversely, positive selection was a less prominent force in sarbecoviruses compared to embecoviruses and merbecoviruses and targeted distinct genomic regions in the three subgenera, with S being the major target in sarbecoviruses alone. Overall, the results herein indicate that Betacoronavirus subgenera evolved along different trajectories, which might recapitulate their host preferences or reflect the origins of the presently available coronavirus sequences.

SUBMITTER: Forni D

PROVIDER: S-EPMC7698105 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Recombination and Positive Selection Differentially Shaped the Diversity of Betacoronavirus Subgenera.

Forni Diego D Cagliani Rachele R Sironi Manuela M

Viruses 20201116 11

The Betacoronavirus genus of mammal-infecting viruses includes three subgenera (Sarbecovirus, Embecovirus, and Merbecovirus), in which most known human coronaviruses, including SARS-CoV-2, cluster. Coronaviruses are prone to host shifts, with recombination and positive selection possibly contributing to their high zoonotic potential. We analyzed the role of these two forces in the evolution of viruses belonging to the Betacoronavirus genus. The results showed t ...[more]

PMID: 33207802

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Project description:Recombination contributes to the genetic diversity found in coronaviruses and is known to be a prominent mechanism whereby they evolve. It is apparent, both from controlled experiments and in genome sequences sampled from nature, that patterns of recombination in coronaviruses are non-random and that this is likely attributable to a combination of sequence features that favour the occurrence of recombination break points at specific genomic sites, and selection disfavouring the survival of recombinants within which favourable intra-genome interactions have been disrupted. Here we leverage available whole-genome sequence data for six coronavirus subgenera to identify specific patterns of recombination that are conserved between multiple subgenera and then identify the likely factors that underlie these conserved patterns. Specifically, we confirm the non-randomness of recombination break points across all six tested coronavirus subgenera, locate conserved recombination hot- and cold-spots, and determine that the locations of transcriptional regulatory sequences are likely major determinants of conserved recombination break-point hotspot locations. We find that while the locations of recombination break points are not uniformly associated with degrees of nucleotide sequence conservation, they display significant tendencies in multiple coronavirus subgenera to occur in low guanine-cytosine content genome regions, in non-coding regions, at the edges of genes, and at sites within the Spike gene that are predicted to be minimally disruptive of Spike protein folding. While it is apparent that sequence features such as transcriptional regulatory sequences are likely major determinants of where the template-switching events that yield recombination break points most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination break-point distributions in coronavirus genomes sampled from nature.

Project description:The genus Betacoronavirus, consisting of four main subgenera (Embecovirus, Merbecovirus, Nobecovirus, and Sarbecovirus), encompasses all clinically significant coronaviruses (CoVs), including SARS, MERS, and the SARS-CoV-2 virus responsible for current COVID-19 pandemic. Very few molecular characteristics are known that are specific for the genus Betacoronavirus or its different subgenera. In this study, our analyses of the sequences of four essential proteins of CoVs, viz., spike, nucleocapsid, envelope, and RNA-dependent RNA polymerase (RdRp), identified ten novel molecular signatures consisting of conserved signature indels (CSIs) in these proteins which are specific for the genus Betacoronavirus or its subgenera. Of these CSIs, two 14-aa-conserved deletions found within the heptad repeat motifs 1 and 2 of the spike protein are specific for all betacoronaviruses, except for their shared presence in the highly infectious avian coronavirus. Six additional CSIs present in the nucleocapsid protein and one CSI in the RdRp protein are distinctive characteristics of either the Merbecovirus, Nobecovirus, or Sarbecovirus subgenera. In addition, a 4-aa insert is present in the spike protein, which is uniquely shared by all viruses from the subgenera Merbecovirus, Nobecovirus, and Sarbecovirus, but absent in Embecovirus and all other genera of CoVs. This molecular signature provides evidence that viruses from the three subgenera sharing this CSI are more closely related to each other, and they evolved after the divergence of embecoviruses and other CoVs. As all CSIs specific for different groups of CoVs are flanked by conserved regions, their sequences provide novel means for identifying the above groups of CoVs and for developing novel diagnostic tests. Furthermore, our analyses of the structures of the spike and nucleocapsid proteins show that all identified CSIs are localized in the surface-exposed loops of these protein. It is postulated that these surface loops, through their interactions with other cellular proteins/ligands, play important roles in the biology/pathology of these viruses.

Project description:Populations of human cytomegalovirus (HCMV), a large DNA virus, are highly polymorphic in patient samples, which may allow for rapid evolution within human hosts. To understand HCMV evolution, longitudinally sampled genomic populations from the urine and plasma of 5 infants with symptomatic congenital HCMV infection were analyzed. Temporal and compartmental variability of viral populations were quantified using high throughput sequencing and population genetics approaches. HCMV populations were generally stable over time, with ~88% of SNPs displaying similar frequencies. However, samples collected from plasma and urine of the same patient at the same time were highly differentiated with approximately 1700 consensus sequence SNPs (1.2% of the genome) identified between compartments. This inter-compartment differentiation was comparable to the differentiation observed in unrelated hosts. Models of demography (i.e., changes in population size and structure) and positive selection were evaluated to explain the observed patterns of variation. Evidence for strong bottlenecks (>90% reduction in viral population size) was consistent among all patients. From the timing of the bottlenecks, we conclude that fetal infection occurred between 13-18 weeks gestational age in patients analyzed, while colonization of the urine compartment followed roughly 2 months later. The timing of these bottlenecks is consistent with the clinical histories of congenital HCMV infections. We next inferred that positive selection plays a small but measurable role in viral evolution within a single compartment. However, positive selection appears to be a strong and pervasive driver of evolution associated with compartmentalization, affecting ? 34 of the 167 open reading frames (~20%) of the genome. This work offers the most detailed map of HCMV in vivo evolution to date and provides evidence that viral populations can be stable or rapidly differentiate, depending on host environment. The application of population genetic methods to these data provides clinically useful information, such as the timing of infection and compartment colonization.

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Recombination and Positive Selection Differentially Shaped the Diversity of Betacoronavirus Subgenera.

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Recombination and Positive Selection Differentially Shaped the Diversity of <i>Betacoronavirus</i> Subgenera.

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