Among the 30 non-synonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (i) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (ii) interactions of Spike with ACE2 receptors, and (iii) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any virus within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and, in combination with other mutations, adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron over all previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected.
Background. SARS-CoV-2 is a novel coronavirus that causes COVID-19 infection, with a closest known relative found in bats. For this virus, hundreds of genomes have been sequenced. This data provides insights into SARS-CoV-2 adaptations, determinants of pathogenicity and mutation patterns. A comparison between patterns of mutations that occurred before and after SARS-CoV-2 jumped to human hosts may reveal important evolutionary consequences of zoonotic transmission. Methods. We used publically available complete genomes of SARS-CoV-2 to calculate relative frequencies of single nucleotide variations. These frequencies were compared with relative substitutions frequencies between SARS-CoV-2 and related animal coronaviruses. A similar analysis was performed for human coronaviruses SARS-CoV and HKU1. Results. We found a 9-fold excess of G to U transversions among SARS-CoV-2 mutations over relative substitution frequencies between SARS-CoV-2 and a close relative coronavirus from bats (RaTG13). This suggests that mutation patterns of SARS-CoV-2 have changed after transmission to humans. The excess of G to U transversions was much smaller in a similar analysis for SARS-CoV and non-existent for HKU1. Remarkably, we did not find a similar excess of complementary C to A mutations in SARS-CoV-2. We discuss possible explanations for these observations.
Background. SARS-CoV-2 is a novel coronavirus that causes COVID-19 infection, with a closest known relative found in bats. For this virus, hundreds of genomes have been sequenced. This data provides insights into SARS-CoV-2 adaptations, determinants of pathogenicity and mutation patterns. A comparison between patterns of mutations that occurred before and after SARS-CoV-2 jumped to human hosts may reveal important evolutionary consequences of zoonotic transmission. Methods. We used publically available complete genomes of SARS-CoV-2 to calculate relative frequencies of single nucleotide variations. These frequencies were compared with relative substitutions frequencies between SARS-CoV-2 and related animal coronaviruses. A similar analysis was performed for human coronaviruses SARS-CoV and HKU1. Results. We found a 9-fold excess of G to U transversions among SARS-CoV-2 mutations over relative substitution frequencies between SARS-CoV-2 and a close relative coronavirus from bats (RaTG13). This suggests that mutation patterns of SARS-CoV-2 have changed after transmission to humans. The excess of G to U transversions was much smaller in a similar analysis for SARS-CoV and non-existent for HKU1. Remarkably, we did not find a similar excess of complementary C to A mutations in SARS-CoV-2. We discuss possible explanations for these observations.
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