Müller NF, Stolz U, Dudas G, Stadler T, Vaughan TG. Bayesian Inference of Reassortment Networks Reveals Fitness Benefits of Reassortment in Human Influenza Viruses. Proc Natl Acad Sci U S A. 2020;201918304
Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.
See Also:
Latest articles in those days:
- The evolution, complexity, and diversity of swine influenza viruses in China: A hidden public health threat 1 days ago
- MHC class II proteins mediate sialic acid independent entry of human and avian H2N2 influenza A viruses 1 days ago
- Histopathologic Features and Viral Antigen Distribution of H5N1 Highly Pathogenic Avian Influenza Virus Clade 2.3.4.4b from the 2022–2023 Outbreak in Iowa Wild Birds 1 days ago
- Detection and characterization of H5N1 HPAIV in environmental samples from a dairy farm 1 days ago
- Genomic Characterization of Highly Pathogenic Avian Influenza A H5N1 Virus Newly Emerged in Dairy Cattle 1 days ago
[Go Top] [Close Window]