Phylogenetic Network of Coronavirus: Visualization, Classification and Evolution

Yu-Chen Tai^1*, Geng-Ming Hu¹, Chi-Ming Chen¹

¹Physics, National Taiwan Normal University, Taiwan

* Presenter:Yu-Chen Tai, email:roger0075835817@gmail.com

Coronaviruses have exerted a profound impact on human economic development, underscoring their evolution is key to developing effective response strategies. In this study, we applied a distance-based Minimum Spanning Clustering (MSClustering) method to classify 311 infectious bronchitis virus(IBV) strains and 1,420 SARS-CoV-2 strains, and compared the results with existing classification systems. For IBV, the phylogenetic network revealed distinct clusters reflecting relationships among strains. Importantly, when integrated with recombination analysis, these network patterns unveiled a previously unrecognized role of migratory birds in IBV dissemination, highlighting potential transmission routes beyond established poultry trade pathways. Although statistical limitations may influence threshold estimation in smaller networks, the MSClustering method substantially accelerated computational efficiency—approximately 100,000 times faster than PhyML—thereby enabling comprehensive phylogenetic analyses of viral populations. To further extend the applicability of this method, we analyzed SARS-CoV-2, which has evolved over merely five years, aiming to gain valuable evolutionary insights.

Keywords: Phylogenetic network, Coronavirus, Clustering, Migratory birds