PhyGraFT: a network-based method for phylogenetic trait analysis

Abstract

With the determination of numerous viral and bacterial genome sequences, phylogeny-trait associations are now being studied. In these studies, phylogenetic trees were first reconstructed, and trait data were analyzed based on the reconstructed tree. However, in some cases, such as fast evolution sequences and gene-sharing network data, reconstructing the phylogenetic tree is challenging. In such cases, network-thinking, instead of tree-thinking, is gaining attention. Here, we propose a novel network-thinking approach, PhyGraFT, to analyze trait data from the network. We validated that PhyGraFT can find phylogenetic signals and associations of traits with the simulation dataset. We applied PhyGraFT for influenza type A and virome gene-sharing datasets. As a result, we identified several evolutionary structures and their associated traits. Our approach is expected to provide novel insights into network-thinking not only for typical phylogenetics but also for various biological data, such as antibody evolution.