COMBAI computational biology and artificial intelligence

SARS-CoV-2 Variant Evolution

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This website for "Evolutionary trajectory and origin of SARS-CoV-2 variant"
by Anyou Wang

Alignment-based approaches have identified qualitative variants of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), but they leave this virus’s evolutionary trajectory unsolved. Here this study employs an alignment-free approach combining Fréchet distance (Fr) and artificial recurrent neural network(RNN) to reveal evolutionary trajectory and origin of SARS-CoV-2 variant. SARS-CoV-2 variants undergo both vertical and horizontal deletions during their evolutionary trajectories to infect humans. Gradual vertical mutations help variants to increase their infection, but over-mutations reduce their infection potential. Horizontal mutations make variants gain diverse mutation markers, which dramatically increase virus infection capacity, leading to COVID-19 pandemic. Mink coronavirus variants mutate 56 genome features similar to SARS-CoV-2 wild type and they are the most likely origin of SARS-CoV-2. This origin trajectory follows the order: mink, cat, tiger, mouse, hamster, dog, lion, gorilla, leopard, bat, and pangolin. Therefore, mink-origin SARS-CoV-2 gradually deletes its genome to carry diverse mutations, causing COVID-19 pandemic.


Anyou Wang,Integrating Fréchet distance and AI reveals the evolutionary trajectory and origin of SARS-CoV-2 Anyou Wang, Rong Hai,Paul J Rider and Qianchuan He. Noncoding RNAs and deep learning neural network discriminate multi-cancer types.Cancers 2022, 14(2), 352. Wang, A. & Hai, R. FINET: Fast Inferring NETwork. BMC Res Notes 13, 521 (2020).