Structurally informed evolutionary models improve phylogenetic reconstruction for emerging, seasonal, and pandemic influenza viruses

摘要: Precise estimation of genetic substitution patterns is critical for accurate reconstruction pathogen phylogenies. Few studies viral evolution account mutational rate variation across a single gene. This especially true when considering segmented viruses where individual segments are short, encoding few proteins. However, the structural and functional partition these proteins could provide valuable information more inference evolution, due to intense immune selection pressure on different domains. In this study we developed evaluated structurally informed partitioning scheme combined with an approximate codon model that accounts among immunogenic head stalk domains surface protein hemagglutinin (HA) influenza viruses. We fit Bayes factor, using path-sampling (PS) stepping-stone sampling (SS) approaches calculate marginal likelihood estimation. compared 4 models - HKY85, SRD06 codon, HKY85 plus partitioning, pandemic H1N1/2009, seasonal H3N2, B-Yamagata Victoria lineages, two highly pathogenic avian A H5Nx H7N9. The factor tests showed performed better all datasets decisive support. Significantly faster nucleotide rates domain, domain was observed may insight derived universal vaccine design. summary, show integrating functionally conserved based structures targets allow significant improvement phylogenetic analysis providing important biological insights.