bioRxivMicrobiologyPreprint
Multi-site co-mutations and 5'UTR CpG immunity escape drive the evolution of SARS-CoV-2
J. Zhang, J. Kang, M. Liu, B. Han, L. Li, Y. He, Z. Yi, L. Chen
Abstract
The SARS-CoV-2 infected cases and the caused mortalities have been surging since the COVID-19 pandemic. Viral mutations emerge during the virus circulating in the population, which is shaping the viral infectivity and pathogenicity. Here we extensively analyzed 6698 SARS-CoV-2 whole genome sequences with specific sample collection dates in NCBI database. We found that four mutations, i.e., 5UTR_c-241-t, NSP3_c-3037-t, NSP12_c-14408-t, and S_a-23403-g, became the dominant variants and each of them represented nearly 100% of all virus sequences since the middle May, 2020. Notably, we found that co-occurrence rates of three significant multi-site co-mutational patterns, i.e., (i) S_a-23403-g, NSP12_c-14408-t, 5UTR_c-241-t, NSP3_c-3037-t, and ORF3a_c-25563-t; (ii) ORF8_t-28144-c, NSP4_c-8782-t, NSP14_c-18060-t, NSP13_a-17858-g, and NSP13_c-17747-t; and (iii) N_g-28881-a, N_g-28882-a, and N_g-28883-c, reached 66%, 90%, and nearly 100% of recent sequences, respectively. Moreover, we found significant decrease of CpG dinucleotide at positions 241(c)-242(g) in the 5UTR during the evolution, which was verified as a potential target of human zinc finger antiviral protein (ZAP). The four dominant mutations, three significant multi-site co-mutations, and the potential escape mutation of ZAP-target in 5UTR region contribute to the rapid evolution of SARS-CoV-2 virus in the population, thus shaping the viral infectivity and pathogenicity. This study provides valuable clues and frameworks to dissect the viral replication and virus-host interactions for designing effective therapeutics. One Sentence SummaryFour dominant mutations, three significant multi-site co-mutations, and 5UTR CpG escape contribute to the rapid evolution of SARS-CoV-2 virus.
- organism: virus
- assay: whole-genome sequencing
- research focus: phylogenetics / evolution
- approach: statistical model
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