ConvMut: Exploration of Viral Convergent Mutations Along Phylogenies

Convergent evolution in protein antigens is common across pathogens, including SARS-CoV-2; the most likely reason is the need to evade the selective pressure exerted by previous infection- or vaccine-elicited immunity. There is a pressing need for automated analysis of convergent mutations. We developed ConvMut, a tool to identify patterns of recurrent mutations in SARS-CoV-2 evolution; we exploited the granular phylogeny-based lineage hierarchy developed by PANGO, allowing us to observe deltas, i.e., groups of mutations that are acquired with respect to the immediately upstream tree nodes. Deltas comprise amino acid substitutions, insertions, and deletions. ConvMut can perform individual protein analysis to identify the most common single mutations acquired independently in a given subtree. Lineages are then gathered into clusters according to user-selected sets of shared mutations. An interactive graph orders the evolutionary steps of clusters, details the acquired amino acid change for each sublineage, and allows us to trace the evolutionary path until a selected lineage. ConvMut also supports frequency analysis for a given nucleotide or amino acid changes at a given residue across a selected phylogenetic subtree. ConvMut facilitates the exploration of convergent evolutionary trends in SARS-CoV-2, providing insights that could support the development of broadly effective anti-Spike monoclonal antibodies and Spike-based vaccines.