Contrasting epidemiology and population genetics of COVID-19 infections defined with 74 polymorphic loci in SARS-CoV-2 genomes sampled globally
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CC-BY-NC-ND-4.0
Abstract
SARS-CoV-2, the coronavirus causing COVID-19, has infected and killed several millions of people worldwide. Since the first COVID-19 outbreak in December 2019, SARS-CoV-2 has evolved with a few genetic variants associated with higher infectivity. We aimed to identify polymorphic loci in SARS-CoV-2 that can be used to define and monitor the viral epidemiology and population genetics in different geographical regions. Between December 2019 and September 2020, we sampled 5,959 SARS-CoV-2 genomes. More than 80% of the genomes sampled in Africa, Asia, Europe, North America, Oceania and South America were reportedly isolated from clinical infections in older patients, ≥ 20 years. We used the first indexed genome (NC_045512.2) as a reference and constructed multilocus genotypes (MLGs) for each sampled genome based on amino acids detected at 74 polymorphic loci located in ORF1ab, ORF3a, ORF8, matrix (M), nucleocapsid (N) and spike (S) genes. Eight of the 74 loci were informative in estimating the risk of carrying infections with mutant alleles among different age groups, gender and geographical regions. Four mutant alleles - ORF1ab L 4715 , S G 614 , and N K 203 and R 204 reached 90% prevalence globally, coinciding with peaks in transmission but not COVID-19 severity, from March to August 2020. During this period, the MLG genetic diversity was moderate in Asia, Oceania and North America; in contrast to Africa, Europe and South America, where lower genetic diversity and absence of linkage disequilibrium indicated clonal SARS-CoV-2 transmission. Despite close relatedness to Asian MLGs, MLGs in the global population were genetically differentiated by geographic region, suggesting structure in SARS-CoV-2 populations. Our findings demonstrate the utility of the 74 loci as a genetic tool to study and monitor SARS-CoV-2 transmission dynamics and evolution, which can inform future control interventions.
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- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
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License: CC-BY-NC-ND-4.0