ABSTRACT
The COVID-19 pandemic poses a great threat to human society. SARS-CoV-2 is mainly transmitted through social contact; however, it is highly debated whether cold-chain related transmission has occurred and can be identified in the epidemic areas of COVID-19. Here, we provide a new method and distinguish two transmission routes by detecting a lineage-specific reduction of SARS-CoV-2 mutation rate. After analyzing 1,610,125 SARS-CoV-2 genomic sequences, we find that two outbreaks in Xinfadi-Beijing and Auckland are cold-chain related and respectively caused by two mutation-dormant variants. A Dalian outbreak in July 2020 and a Yingkou outbreak ten months later are epidemiologically connected and derived from a cold-chain related variant. Mutation-dormant variants are detected during the spread of spike D614G variant and the Delta Variant of Concern. Cold-chain contaminations repeatedly caused by epidemiologically connected patients are also found and have resulted in infections. Moreover, the COVID-19 outbreak in Wuhan is likely to be cold-chain related. A systematic identification reveals that the frequency of cold-chain related transmission is in the order of magnitude of 0.1-10%. Our results indicate that that cold-chain related transmission is rare but happens globally.
Subject(s)
COVID-19ABSTRACT
The SARS-CoV-2 variant of concern B.1.1.7 has quickly spread. To identify its crucial mutations, we explored the B.1.1.7 associated mutations on an evolutionary tree by the Coronavirus GenBrowser and VENAS. We found that a non-coding deletion g.a28271-, at upstream of the nucleocapsid (N) gene, has triggered the high transmissibility of B.1.1.7. The deletion changes the core Kozak site of the N gene and may reduce the expression of N protein and increase that of ORF9b. The expression of ORF9b is also regulated by another mutation (g.gat28280cta) that mutates the core Kozak sites of the ORF9b gene. If both mutations back-mutate, the B.1.1.7 variant loses its high transmissibility. Moreover, the deletion may interact with ORF1a:p.SGF3675-, S:p.P681H, and S:p.T716I to increase the viral transmissibility. Overall, these results demonstrate the importance of the non-coding deletion and provide evolutionary insight into the crucial mutations of B.1.1.7.
ABSTRACT
COVID-19 has widely spread across the world, and much research is being conducted on the causative virus SARS-CoV-2. To help control the infection, we developed the Coronavirus GenBrowser (CGB) to monitor the pandemic. CGB allows visualization and analysis of the latest viral genomic data. Distributed genome alignments and an evolutionary tree built on the existing subtree are implemented for easy and frequent updates. The tree-based data are compressed at a ratio of 2,760:1, enabling fast access and analysis of SARS-CoV-2 variants. CGB can effectively detect adaptive evolution of specific alleles, such as D614G of the spike protein, in their early stage of spreading. By lineage tracing, the most recent common ancestor, dated in early March 2020, of nine strains collected from six different regions in three continents was found to cause the outbreak in Xinfadi, Beijing, China in June 2020. CGB also revealed that the first COVID-19 outbreak in Washington State was caused by multiple introductions of SARS-CoV-2. To encourage data sharing, CGB credits the person who first discovers any SARS-CoV-2 variant. As CGB is developed with eight different languages, it allows the general public in many regions of the world to easily access pre-analyzed results of more than 132,000 SARS-CoV-2 genomes. CGB is an efficient platform to monitor adaptive evolution and transmission of SARS-CoV-2.
Subject(s)
COVID-19ABSTRACT
Understanding the mutational and evolutionary dynamics of SARS-CoV-2 is essential for treating COVID-19 and the development of a vaccine. Here, we analyzed publicly available 15,818 assembled SARS-CoV-2 genome sequences, along with 2,350 raw sequence datasets sampled worldwide. We investigated the distribution of inter-host single nucleotide polymorphisms (inter-host SNPs) and intra-host single nucleotide variations (iSNVs). Mutations have been observed at 35.6% (10,649/29,903) of the bases in the genome. The substitution rate in some protein coding regions is higher than the average in SARS-CoV-2 viruses, and the high substitution rate in some regions might be driven to escape immune recognition by diversifying selection. Both recurrent mutations and human-to-human transmission are mechanisms that generate fitness advantageous mutations. Furthermore, the frequency of three mutations (S protein, F400L; ORF3a protein, T164I; and ORF1a protein, Q6383H) has gradual increased over time on lineages, which provides new clues for the early detection of fitness advantageous mutations. Our study provides theoretical support for vaccine development and the optimization of treatment for COVID-19. We call researchers to submit raw sequence data to public databases.