Journal
GENOME BIOLOGY AND EVOLUTION
Volume 13, Issue 2, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/gbe/evab015
Keywords
COVID-19; SARS-CoV-2; SNP; iSNV; mutants
Categories
Funding
- National Key Research and Development Program [2019YFC1604600]
- National Natural Science Foundation of China [31200941, 31660713]
- Fundamental Research Funds for the Central Universities [106112016CDJXY290002]
- National Natural Science Foundation of HeBei province [19226631D]
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The study reports nine newly evolved SARS-CoV-2 single nucleotide polymorphism (SNP) alleles that underwent rapid changes in frequency within the initial four months. These mutations show potential effects on virus replication and disease severity in COVID-19 patients, providing important insights for future epidemiological surveys and disease control.
The novel coronavirus (SARS-CoV-2) has become a pandemic and is threatening human health globally. Here, we report nine newly evolved SARS-CoV-2 single nucleotide polymorphism (SNP) alleles those underwent a rapid increase (seven cases) or decrease (two cases) in their frequency for 30-80% in the initial four months, which are further confirmed by intrahost single nucleotide variation analysis using raw sequence data including 8,217 samples. The nine SNPs are mostly (8/9) located in the coding region and are mainly (6/9) nonsynonymous substitutions. The nine SNPs show a complete linkage in SNP pairs and belong to three different linkage groups, named LG_1 to LG_3. Analyses in population genetics show signatures of adaptive selection toward the mutants in LG_1, but no signal of selection for LG_2. Population genetic analysis results on LG_3 show geological differentiation. Analyses on geographic COVID-19 cases and published clinical data provide evidence that the mutants in LG_1 and LG_3 benefit virus replication and those in LG_1 have a positive correlation with the disease severity in COVID-19-infected patients. The mutants in LG_2 show a bias toward mildness of the disease based on available public clinical data. Our findings may be instructive for epidemiological surveys and disease control of COVID-19 in the future.
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