Population genomics of dengue virus serotype 4: insights into genetic structure and evolution
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The spread of dengue disease has become a global public health concern. Dengue is caused by dengue virus, which is a mosquito-borne arbovirus of the genus Flavivirus, family Flaviviridae. There are four dengue virus serotypes (1-4), each of which is known to trigger mild to severe disease. Dengue virus serotype 4 (DENV-4) has four genotypes and is increasingly being reported to be re-emerging in various parts of the world. Therefore, the population structure and factors shaping the evolution of DENV-4 strains across the world were studied using genome-based population genetic, phylogenetic and selection pressure analysis methods. The population genomics study helped to reveal the spatiotemporal structure of the DENV-4 population and its primary division into two spatially distinct clusters: American and Asian. These spatial clusters show further time-dependent subdivisions within genotypes I and II. Thus, the DENV-4 population is observed to be stratified into eight genetically distinct lineages, two of which are formed by American strains and six of which are formed by Asian strains. Episodic positive selection was observed in the structural (E) and non-structural (NS2A and NS3) genes, which appears to be responsible for diversification of Asian lineages in general and that of modern lineages of genotype I and II in particular. In summary, the global DENV-4 population is stratified into eight genetically distinct lineages, in a spatiotemporal manner with limited recombination. The significant role of adaptive evolution in causing diversification of DENV-4 lineages is discussed. The evolution of DENV-4 appears to be governed by interplay between spatiotemporal distribution, episodic positive selection and intra/inter-genotype recombination.
KeywordsMarkov Chain Monte Carlo Dengue Virus Envelope Gene Dengue Virus Serotypes Brazilian Strain
This work was supported by a Center of Excellence (CoE) grant from the Department of Biotechnology (DBT), Government of India, New Delhi. UKK acknowledges DBT CoE for financial assistance. VPW acknowledges DBT fellowship. SMK acknowledges the Bioinformatics Resources and Applications Facility (BRAF), C-DAC, Pune.
Compliance with ethical standards
This work was supported by a Center of Excellence (CoE) grant from the Department of Biotechnology (DBT), Government of India, New Delhi, India.
Conflict of interest
All authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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