key: cord-0995201-5fkk80bi
authors: Zhang, Jingsong; Zhang, Yang; Kang, Junyan; Chen, Shuiye; He, Yongqun; Han, Benhao; Liu, Mofang; Lu, Lina; Li, Li; Yi, Zhigang; Chen, Luonan
title: Potential transmission chains of variant B.1.1.7 and co-mutations of SARS-CoV-2
date: 2021-04-20
journal: bioRxiv
DOI: 10.1101/2021.04.16.440141
sha: 29d53391fc089f860a4bb19dbfec37ff826c4ad2
doc_id: 995201
cord_uid: 5fkk80bi

The presence of SARS-CoV-2 mutants, including the emerging variant B.1.1.7, has raised great concerns in terms of pathogenesis, transmission, and immune escape. Characterizing SARS-CoV-2 mutations, evolution, and effects on infectivity and pathogenicity is crucial to the design of antibody therapies and surveillance strategies. Here we analyzed 454,443 SARS-CoV-2 spike genes/proteins and 14,427 whole-genome sequences. We demonstrated that the early variant B.1.1.7 may not have evolved spontaneously in the United Kingdom or within human populations. Our extensive analyses suggested that Canidae, Mustelidae or Felidae, especially the Canidae family (for example, dog) could be a possible host of the direct progenitor of variant B.1.1.7. An alternative hypothesis is that the variant was simply yet to be sampled. Notably, the SARS-CoV-2 whole genome represents a large number of potential co-mutations with very strong statistical significances (p value<E– 44). In addition, we used an experimental SARS-CoV-2 reporter replicon system to introduce the dominant co-mutations NSP12_c14408t, 5’UTR_c241t, and NSP3_c3037t into the viral genome, and to monitor the effect of the mutations on viral replication. Our experimental results demonstrated that the co-mutations significantly attenuated the viral replication. The study provides valuable clues for discovering the transmission chains of variant B.1.1.7 and understanding the evolutionary process of SARS-CoV-2.

isolated globally (Fig. S1 ), including 8,898 and 815 samples isolated from the U.S. (Fig. S2 ) 126 and Australia (Fig. S3 ). Therefore, these mutations shown in Fig. S4a were selected and 127 clustered into co-occurrences, which we called potential co-mutation patterns. From the 128 landscape of the mutation rates (Fig. S4a) , 25 nucleotide sites were clearly clustered into 7 several potential co-mutation patterns. Among these patterns, there was one consisting of 130 the top 4 high-frequency mutations (i.e., 5'UTR_c241t, NSP3_c3037t, NSP12_c14408t, and 131 S_a23403g), which converged into a dominant potential co-mutation pattern. Such 132 co-occurrence lineage has been found in almost all sequenced samples of SARS-CoV-2.

Within this co-occurrence pattern, mutation S_ a23403g resulted in the amino acid change 134 (D614G) that apparently enhances viral infectivity 6,35 , albeit debate exists 16 we found that the top 14 high-frequency mutations formed five common co-occurrence 138 patterns.

To assess the above co-occurrence patterns, we analyzed the correlations and statistical (Fig. 4a) . The NSP3_c3037t mutation is synonymous. The NSP12_c14408t mutation is 154 nonsynonymous with an amino acid change of a conserved amino acid P323 in the viral 155 RNA-dependent RNA polymerase (Fig. 4b) . We introduced the NSP12_c14408t mutation or 

Pattern Analysis and Machine Intelligence 20, 522-532 (1998). of mutations shows that eight clusters all denote the statistical significance level: ***p value < E-44. c 433 to k show the transitions of the high-frequency mutations. The sky-blue represents the rate per day of 434 initial residue in population and the golden the rate per day of substitution/mutant. These mutation 435 transitions provide further evidence that the above mutations potentially form co-mutation patterns. 436 

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