Zika virus (ZIKV) is a mosquito-borne virus belonging to the same family, Flaviviridae, as dengue, West-Nile and yellow fever viruses. The rapid spread of ZIKV infections in the Americas caused a public health emergency of international concern due to its linkage to a dramatic increase in cases of microcephaly. Although the overall number of ZIKV-related cases has declined sharply after 2016, the virus might still be circulating unnoticed in several regions. This may potentially give rise to future epidemics among the more than 2 billion people who worldwide inhabit regions at risk for ZIKV transmission. Our objective was to characterize ZIKV genome-wide diversity and phylodynamics, to identify genomic footprints of differentiation patterns and to propose a dynamic classification system that reflects its divergence levels. We analyzed a curated dataset of 505 publicly available sequences spanning the full-length coding region of ZIKV, sampled across its geographical span. We applied a combination of methods based on phylogenetics, clustering and evolutionary dynamics analyses. This integrated approach enabled us to identify the genetic subgroups within the two main genotypes, i.e., “African” and “Asian”. In this process we identified the most relevant mutations and investigated the most likely dispersion routes and explored the evolutionary processes involved. We found evidence of strong purifying selection, widespread across the genome, and of a few sites under positive selection. In our analyses, we did not find any evidence of recombination. Based on the identified genetic groups, we proposed a nomenclature that avoids geographical references and is flexible to accommodate future lineages. This classification, combined with the information on the identified mutations, will be a helpful tool for studies that involve ZIKV genomic variation and its association with pathogenicity, as well as to provide a reference for the study of future outbreaks of ZIKV.
Funding: European Union’s Horizon 2020 research and innovation program ZIKAlliance (Agreement No 734548); Fundação para a Ciência e Tecnologia (FCT), Portugal (GHTM-UID/04413/2020; contrato-programa 1567 –CEECINST/00102/2018); Fonds Wetenschappelijk Onderzoek (1S31916N; #1242021N; " G0E1420N, G098321N); Fonds de la Recherche Scientifique (FNRS, Belgium). KU Leuven/Internal Funds KU Leuven (C14/18/094)