Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel

In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance. HighlightsO_LIGlobal phylogenetic analysis reveals relationship between air travel and speed of dispersal of SARS-CoV-2 variants of concern (VOCs) C_LIO_LIOmicron VOC spread to 5x more countries within 100 days of its emergence compared to all other VOCs C_LIO_LIOnward transmission and dissemination of VOCs Delta and Omicron was primarily from secondary hubs rather than initial country of detection during a time of increased global air travel C_LIO_LIAnalysis highlights highly connected countries identified as major global and regional exporters of VOCs C_LI

Conserved recombination patterns across coronavirus subgenera

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 breakpoints 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 breakpoints 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 breakpoint hot-spot locations. We find that while the locations of recombination breakpoints 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 breakpoints most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination breakpoint distributions in coronavirus genomes sampled from nature.

A Novel and Expanding SARS-CoV-2 Variant, B.1.1.318, dominates infections in Mauritius

Mauritius, a small island in the Indian Ocean, has had a unique experience of the SARS-CoV-2 pandemic. In March 2020, Mauritius endured a small first wave and quickly implemented control measures which allowed elimination of local transmission of SARS-CoV-2. When borders to the island reopened, it was accompanied by mandatory quarantine and testing of incoming passengers to avoid reintroduction of the virus into the community. As variants of concern (VOCs) emerged elsewhere in the world, Mauritius began using genomic surveillance to keep track of quarantined cases of these variants. In March 2021, another local outbreak occurred, and sequencing was used to investigate this new wave of local infections. Here, we analyze 154 SARS-CoV-2 viral genomes from Mauritius, which represent 12% of all the infections seem in Mauritius, these were both from specimens of incoming passengers before March 2021 and those of cases during the second wave. Our findings indicate that despite the presence of known VOCs Beta (B.1.351) and Alpha (B.1.1.7) among quarantined passengers, the second wave of local SARS-CoV-2 infections in Mauritius was caused by a single introduction and dominant circulation of the B.1.1.318 virus. The B.1.1.318 variant is characterized by fourteen non-synonymous mutations in the S-gene, with five encoded amino acid substitutions (T95I, E484K, D614G, P681H, D796H) and one deletion (Y144del) in the Spike glycoprotein. This variant seems to be increasing in prevalence and it is now present in 34 countries. This study highlights that despite having stopped the introduction of more transmissible VOCs by travel quarantines, a single undetected introduction of a B.1.1.318 lineage virus was enough to initiate a large local outbreak in Mauritius and demonstrated the need for continuous genomic surveillance to fully inform public health decisions.

A novel variant of interest of SARS-CoV-2 with multiple spike mutations is identified from travel surveillance in Africa

At the end of 2020, the Network for Genomic Surveillance in South Africa (NGS-SA) detected a SARS-CoV-2 variant of concern (VOC) in South Africa (501Y.V2 or PANGO lineage B.1.351)1. 501Y.V2 is associated with increased transmissibility and resistance to neutralizing antibodies elicited by natural infection and vaccination2,3. 501Y.V2 has since spread to over 50 countries around the world and has contributed to a significant resurgence of the epidemic in southern Africa. In order to rapidly characterize the spread of this and other emerging VOCs and variants of interest (VOIs), NGS-SA partnered with the Africa Centres for Disease Control and Prevention and the African Society of Laboratory Medicine through the Africa Pathogen Genomics Initiative to strengthen SARS-CoV-2 genomic surveillance across the region.

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org.

Exploring the natural origins of SARS-CoV-2

The lack of an identifiable intermediate host species for the proximal animal ancestor of SARS-CoV-2, and the large geographical distance between Wuhan and where the closest evolutionary related coronaviruses circulating in horseshoe bats (Sarbecoviruses) have been identified, is fuelling speculation on the natural origins of SARS-CoV-2. We have comprehensively analysed phylogenetic relations between SARS-CoV-2, and the related bat and pangolin Sarbecoviruses sampled so far. Determining the likely recombination events reveals a highly reticulate evolutionary history within this group of coronaviruses. Clustering of the inferred recombination events is non-random with evidence that Spike, the main target for humoral immunity, is beside a recombination hotspot likely driving antigenic shift in the ancestry of bat Sarbecoviruses. Coupled with the geographic ranges of their hosts and the sampling locations, across southern China, and into Southeast Asia, we confirm horseshoe bats, Rhinolophus, are the likely SARS-CoV-2 progenitor reservoir species. By tracing the recombinant sequence patterns, we conclude that there has been relatively recent geographic movement and co-circulation of these viruses ancestors, extending across their bat host ranges in China and Southeast Asia over the last 100 years or so. We confirm that a direct proximal ancestor to SARS-CoV-2 is yet to be sampled, since the closest relative shared a common ancestor with SARS-CoV-2 approximately 40 years ago. Our analysis highlights the need for more wildlife sampling to (i) pinpoint the exact origins of SARS-CoV-2s animal progenitor, and (ii) survey the extent of the diversity in the related Sarbecoviruses phylogeny that present high risk for future spillover. HighlightsO_LIThe origin of SARS-CoV-2 can be traced to horseshoe bats, genus Rhinolophus, with ranges in both China and Southeast Asia. C_LIO_LIThe closest known relatives of SARS-CoV-2 exhibit frequent transmission among their Rhinolophus host species. C_LIO_LISarbecoviruses have undergone extensive recombination throughout their evolutionary history. C_LIO_LIAccounting for the mosaic patterns of these recombinants is important when inferring relatedness to SARS-CoV-2. C_LIO_LIBreakpoint patterns are consistent with recombination hotspots in the coronavirus genome, particularly upstream of the pike open reading frame with a coldspot in S1. C_LI

Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa

Continued uncontrolled transmission of the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in many parts of the world is creating the conditions for significant virus evolution. Here, we describe a new SARS-CoV-2 lineage (501Y.V2) characterised by eight lineage-defining mutations in the spike protein, including three at important residues in the receptor-binding domain (K417N, E484K and N501Y) that may have functional significance. This lineage emerged in South Africa after the first epidemic wave in a severely affected metropolitan area, Nelson Mandela Bay, located on the coast of the Eastern Cape Province. This lineage spread rapidly, becoming within weeks the dominant lineage in the Eastern Cape and Western Cape Provinces. Whilst the full significance of the mutations is yet to be determined, the genomic data, showing the rapid displacement of other lineages, suggest that this lineage may be associated with increased transmissibility.

Major new lineages of SARS-CoV-2 emerge and spread in South Africa during lockdown.

In March 2020, the first cases of COVID-19 were reported in South Africa. The epidemic spread very fast despite an early and extreme lockdown and infected over 600,000 people, by far the highest number of infections in an African country. To rapidly understand the spread of SARS-CoV-2 in South Africa, we formed the Network for Genomics Surveillance in South Africa (NGS-SA). Here, we analyze 1,365 high quality whole genomes and identify 16 new lineages of SARS-CoV-2. Most of these unique lineages have mutations that are found hardly anywhere else in the world. We also show that three lineages spread widely in South Africa and contributed to [~]42% of all of the infections in the country. This included the first identified C lineage of SARS-CoV-2, C.1, which has 16 mutations as compared with the original Wuhan sequence. C.1 was the most geographically widespread lineage in South Africa, causing infections in multiple provinces and in all of the eleven districts in KwaZulu-Natal (KZN), the most sampled province. Interestingly, the first South-African specific lineage, B.1.106, which was identified in April 2020, became extinct after nosocomial outbreaks were controlled. Our findings show that genomic surveillance can be implemented on a large scale in Africa to identify and control the spread of SARS-CoV-2.