Unbiased Local Sequencing Similarity Analysis for SARS-CoV-2 Worldwide

Abstract

There is an urgent public health need to better understand SARS-CoV-2/COVID-19, particularly how sequences of the viruses could lead to diverse severity of COVID-19 in different countries. However, because of its unknown ancestors and hosts, elucidating the genetic variations of the novel coronavirus, SARS-CoV-2, has been difficult. Without needing to know ancestors, we identified an uneven distribution of local genome similarities among the viruses categorized by geographic regions, and it was strongly correlated with infection severity. To ensure unbiased and origin-independent analyses, we used a pairwise comparison of local genome sequences of virus genomes by BLAST. We found a strong statistical correlation between dominance of the SARS-CoV-2 in distributions of uneven similarities and the severity of illness in terms of infection cases and deaths. Genomic annotation of the BLAST hits also showed that viruses from geographic regions with severe infections tended to have more dynamic genomic regions in the SARS-CoV-2 receptor binding domain (RBD) and receptor binding motif (RBM) of the spike protein (S protein). Dynamic domains in the S protein were also confirmed by a canyon region of mismatches coincident with RBM and RBD, without hits of alignments of 100% matching. Thus, our origin-independent analysis suggests that the dynamic and unstable SARS-CoV-2-RBD could be the main reason for diverse severity of COVID-19 infection.