Detecting Potentially Adaptive Mutations from the Parallel and Fixed Patterns in SARS‐CoV‐2 Evolution

Abstract

Early identification of adaptive mutations could provide timely help for the control and prevention of the COVID‐19 pandemic. The fast accumulation of SARS‐CoV‐2 sequencing data pro-vides important support, while also raising a great challenge for the recognition of adaptive muta-tions. Here, we proposed a computational strategy to detect potentially adaptive mutations from their fixed and parallel patterns in the phylogenetic trajectory. We found that the biological mean-ings of fixed substitution and parallel mutation are highly complementary, and can reasonably be integrated as a fixed and parallel (paraFix) mutation, to identify potentially adaptive mutations. Tracking the dynamic evolution of SARS‐CoV‐2, 37 sites in spike protein were identified as having experienced paraFix mutations. Interestingly, 70% (26/37) of them have already been experimentally confirmed as adaptive mutations. Moreover, most of the mutations could be inferred as paraFix mutations one month earlier than when they became regionally dominant. Overall, we believe that the concept of paraFix mutations will help researchers to identify potentially adaptive mutations quickly and accurately, which will provide invaluable clues for disease control and prevention.