Abstract
Backgroud Hantaan virus (HTNV), as one of the pathogenic hantaviruses of HFRS, has raised serious concerns in Eurasia. China and its neighbors, especially Russia and South Korea, are seriously suffered HTNV infections. Recent studies reported genetic diversity and phylogenetic features of HTNV in different parts of China, but the analyses from the holistic perspective are rare.
Methodology and Principal Findings To better understand HTNV genetic diversity and dynamics, we analyzed all available complete sequences derived from the S and M segments with bio-informatic tools. Our study revealed 11 phylogroups and sequences showed obvious geographic clustering. We found 42 significant amino acid variants sites and 18 of them located in immune epitopes. Nine recombination events and seven reassortment isolates were deteced in our study. Sequences from Guizhou were highly genetic divergent, characterized by the emergence of multiple lineages, recombination and reassortment events. We found that HTNV probably emerged in Zhejiang about 1,000 years ago and the population size expanded from 1980s to 1990s. Bayesian stochastic search variable selection analysis revealed that Heilongjiang, Shaanxi and Guizhou played important roles in HTNV evolution and migration.
Conclusions/Significance These findings reveal the original and evolution features of HTNV which might assist in understanding Hantavirus epidemics and would be useful for disease prevention and control.
Author summary Hemorrhagic Fever with Renal Syndrome (HFRS) and Hantavirus Pulmonary Syndrome (HPS) are endemic zoonotic infectious diseases caused by hantaviruses that belong to the Family Bunyaviridae. Hantaviruses have gained worldwide attention as etiological agents of emerging zoonotic diseases, with fatality rates ranging from <10% up to 60%. However, our knowledge about the emergence and evolution of HTNV is limited. To get more information about HTNV genetic diversity and phylogenetic features in holistic perspective, we investigated the genetic diversity and spatial distribution of HTNV using all available whole genomic sequences of S and M segments. We also gain insights into the genetic diversity and spatial-temporal dynamics of HTNV. These data can augment traditional approach to infectious disease surveillance and control.