Multi-locus sequence typing of African swine fever viruses from endemic regions of Kenya and Eastern Uganda (2011–2013) reveals rapid B602L central variable region evolution

The central variable region (CVR) within the B602L gene of the African swine fever virus (ASFV) is highly polymorphic within the 23 ASFV genotypes defined by sequencing of the C-terminal end of the p72 locus. Sequencing the p54 gene further discriminates ASFV genotypes that are conserved at the p72 locus. Variation in the thymidine kinase locus is a novel additional tool for ASFV genotyping whose application for this purpose is described for the first time herein. We evaluated genetic variation at these four polymorphic loci in 39 ASFV isolates obtained from outbreaks in Kenya and a region of Eastern Uganda between 2011 and 2013. Analysis of the p72 and p54 loci revealed high genetic conservation among these isolates; all clustered within p72 genotype IX and were similar to isolates associated with earlier outbreaks in East Africa. The thymidine kinase gene of the Kenyan isolates in this study were distinct relative to Southern African isolates and synonymous substitutions were observed among viruses from central Kenya. Analysis of the CVR within the B602L gene revealed two previously unknown polymorphisms that were restricted to Western Kenya and Eastern Uganda. A novel variant was revealed within CVR subgroup XXIV and a novel CVR subgroup XXIVa that contains tetrameric repeat F which has previously only been associated with p72 genotype I, was also identified for the first time in East Africa. Phylogeographic analysis of isolates based on CVR polymorphisms revealed rapid evolution and dissemination of variants present within ASFV genotype IX in East Africa.Supplementary Fig. 1 Phylogenetic tree based on the C-terminal end of the p72 protein comparing the Kenyan and Eastern Uganda ASFV isolates collected in this study (●) between 2011 and 2013 with other African swine fever virus isolates belonging to ASFV genotypes IX and X. A total of 91 distinct taxa were used to infer a Minimum Evolution tree and the percentage of replicate trees in which the associated taxa clustered together in a bootstrap analysis (1000 replicates) are shown adjacent to the branches. The tree is drawn to scale; with branch lengths represented using the same units as the evolutionary distances used to infer the phylogenetic tree.Supplementary Fig. 2 Phylogenetic tree highlighting genetic conservation within the E183L gene within the Kenyan and Eastern Uganda ASFV isolates in comparison to reference nucleotide sequences obtained from GenBank.Supplementary Fig. 3 Amino acid sequences translated using SeqPublish highlighting synonymous substitutions within the thymidine kinase gene in the ASFV isolates obtained from Central Kenya.Supplementary Table 1 Summary of the data obtained from ASFV isolates selected for genotyping in this study and the respective GenBank accession numbers.The Australian aid (AusAID) and the Commonwealth Scientific and Industrial Research Organization (CSIRO) under the Special Africa Program.http://link.springer.com/journal/11262hj2018Mammal Research InstituteZoology and Entomolog

Enhanced discrimination of African swine fever virus isolates through nucleotide sequencing of the p54, p72, and pB602L (CVR) genes

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The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

The past 2 years, during which waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants swept the globe, have starkly highlighted health disparities across nations. Tegally et al. show how the coordinated efforts of talented African scientists have in a short time made great contributions to pandemic surveillance and data gathering. Their efforts and initiatives have provided early warning that has likely benefited wealthier countries more than their own. Genomic surveillance identified the emergence of the highly transmissible Beta and Omicron variants and now the appearance of Omicron sublineages in Africa. However, it is imperative that technology transfer for diagnostics and vaccines, as well the logistic wherewithal to produce and deploy them, match the data-gathering effort