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DOI 10.1016/j.meegid.2021.105068

Медицинская библиотека · Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021

Genome-wide population structure inferences of human coxsackievirus-A; insights the genotypes diversity and evolution.

Khan Hizbullah, Khan Asifullah

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Coxsackievirus-A (CV-A) is a causative agent of Hand Foot Mouth Disease (HFMD) worldwide. It belongs to the Human Enterovirus genus of the family Picornaviridae. The genomics data availability of CV-A samples, isolated from human host across different continental regions, provide an excellent opportunity to study its genetic composition, diversity, and evolutionary events. The complete genome sequences of 424 CV-A isolates were analyzed through a model-based population genetic approach implemented in the STRUCTURE program. Twelve genetically distinct sub-populations were identified for CV-A isolates with a marked Fst distinction of 0.76991 (P-value = 0.00000). Besides, genetically admixed strains were characterized in the G-Id, G-IIIb clusters constituted by the CV-A12 and CV-A6 enterovirus serotypes. The serotypes depicted inter/intra-genotype recombination and episodic positive selection signatures in the structural and non-structural protein-coding regions. The observed genetic composition of CV-A samples was also deduced by the phylogenetic tree analyses, where a uniform genetic structure was inferred for most of the CV-A genotypes. However, the CV-A6 serotype samples genetically stratified into three sub-populations that may lead to the emergence of new lineages in future. These informations may implicate in planning the effective strategies to combat the coxsackievirus-A-mediated infection.

Для цитирования: Khan Hizbullah, Khan Asifullah. Genome-wide population structure inferences of human coxsackievirus-A; insights the genotypes diversity and evolution.. Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases. 2021. DOI: 10.1016/j.meegid.2021.105068.

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