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Inferring Geographic Spread of Flaviviruses Through Analysis of Hypervariable Genomic Regions
Jimena Sánchez-Nava1, Mario H Rodríguez1, Eduardo D Rodríguez-Aguilar1
1Centre for Research in Infectious Diseases, National Institute of Public Health, Av. Universidad 655, Cuernavaca 62100, Mexico.
None:
The Flaviviruses Dengue virus (DENV), West Nile virus (WNV), Zika virus (ZIKV), and Yellow Fever virus (YFV), are mosquito-borne viruses that represent a persistent challenge to global health due to the emergence and re-emergence of outbreaks of significant magnitudes. Their positive-sense RNA genome, about 11,000 nucleotides long, encodes structural and nonstructural proteins. These viruses evolve rapidly through mutations and genetic recombination, which can lead to more virulent and transmissible strains. Although whole-genome sequencing is ideal for studying their evolution and geographic spread, its cost is a limitation. We investigated the genetic variability of DENV, ZIKV, WNV, and YFV to identify genomic regions that accurately reflect the phylogeny of the complete coding sequence and evaluated the utility of these regions in reconstructing the geographic dispersal patterns of viral genotypes and lineages. Publicly available sequences from GenBank were examined to assess variability, reconstruct phylogenies, and identify the most informative genomic regions. Once representative regions were identified, they were used to infer the global phylogeographic structure of each virus. The virus depicted distinct variation patterns, but conserved regions of high and low variability were common to all. Highly variable regions of ~2700 nt offered greater resolution in phylogenetic trees, improving the definition of internal branches and statistical support for nodes. In some cases, combined multiple highly variable regions enhanced phylogenetic accuracy. Phylogeographic reconstruction consistently grouped sequences by genotype and geographic origin, with temporal structuring revealing evolutionarily distinct clusters that diverged over decades. These findings highlight the value of targeting genomic regions for phylogenetic and phylogeographic analysis, providing an efficient alternative for genomic surveillance.
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