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

Xueting Qiu; Justin Bahl

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/228692 doi: bioRxiv preprint 11 well for some purposes of observing the co-evolution of multiple proteins, however, it assumes 224 evolutionary processes act uniformly across one protein, which may not be the biological reality 225 due to distinctively functional domains on one protein. 226 When developing the new model in this study, the primary tasks are to efficiently capture 227 the information regarding HA protein structural and functional domains and to properly 228 incorporate this information into the evolutionary models. Therefore, how to partition on the 229 protein structure with genetic data is critical. One solution is to compare all possible partitioning 230 schemes for a given genetic sequence dataset to find the best partitioning strategy (3). However, (H1, H2, H5, H6, H8, H9, H11, H12, H13, H16, and H17) and Group 2 (H3, H4, H7, H10, H14 287 and H15) (25), respectively, it is probably amongst the most promising approaches to design a 288 universal influenza vaccine. 289 While this model has been developed with influenza in mind, there is potential to apply 290 this approach to other viruses. Proteins, such as the respiratory syncytial virus F and G protein or 291 the coronavirus spike protein that have multiple functional domains including immune 292 All rights reserved. No reuse allowed without permission.