Tai-Jung Li, Kuan-Fu Chen, Andrew Pekosz, Yu-Nong. Visualizing and Deciphering Influenza A(H1N1) pdm09 Reassortment in the 2019-2023 Seasons. Virus Evolution, veaf070
Influenza A viruses remain a persistent public health concern due to their extensive genomic diversity and seasonality. Among the mechanisms driving their evolution, reassortment plays a pivotal role by facilitating the exchange of gene segments between co-infecting viruses, leading to novel viral genotypes. This mechanism contributes to pandemic strains, such as the 2009 H1N1 pandemic (H1N1pdm), and affects seasonal influenza by introducing genetic changes with potential impacts on viral traits and clinical outcomes. Comprehensive reassortment analysis is therefore critical for better understanding the mechanisms underlying influenza virus evolution and their potential impact on public health. A new visualization tool, Crossing lines Annotating with Tanglegrams on Trees (CatTrees), was designed to enhance the presentation of reassortment events in multiple phylogenetic trees. To facilitate this workflow, we developed the Virus Data Analysis Toolkit (VIDA), a modular Python toolkit that automates and standardizes viral sequence preprocessing and downstream analyses. This integrated approach was successfully applied to whole genomes of influenza A(H1N1)pdm from 2019 to 2023. Notably, a novel group named reassortment 6B.1A.5a.1 (in short, re6B.1A.5a.1 or re5a.1) emerged during the 2020–2021 season and became dominant in the Netherlands, France, Togo, South Africa, and Kenya in 2021–2022, eventually replacing the original clade 6B.1A.5a.1 in the 2022–2023 season. Three reassortment patterns were observed, where clade 6B.1A.5a.1 reassorted with clades 6B.1A.5a and 6B.1A.5a.2. These patterns shed light on the ongoing evolution of influenza viruses.
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