dc.contributor.author | Kiiza, Ronald | |
dc.date.accessioned | 2024-11-22T15:23:30Z | |
dc.date.available | 2024-11-22T15:23:30Z | |
dc.date.issued | 2024-10 | |
dc.identifier.citation | Kiiza, R. (2024). Evidence of molecular adaptive evolution of SARS-CoV-2 in Uganda using whole genome sequences (Unpublished master's dissertation). Makerere University, Kampala, Uganda | en_US |
dc.identifier.uri | http://hdl.handle.net/10570/13755 | |
dc.description | A dissertation report submitted to the Directorate of Research and Graduate Training in partial fulfilment of the requirements for the award of Master of Science in Bioinformatics of Makerere University, Kampala | en_US |
dc.description.abstract | Background: Seasonal influenza and coronaviruses both exhibit continual adaptive evolution during endemic circulation in the human population. The rapid evolution of human pathogenic RNA viruses can undermine the efforts to control a given viral infection and its transmission. It is not well understood whether the SARS-CoV-2 viral population in Uganda is undergoing a similar evolution.
Objectives: We established the molecular evolutionary rate, identified conserved genomic regions under positive selection and as well confirmed the signature of positive selection by determining the rate of adaptive evolution of the SARS-CoV-2 in Uganda.
Methods: We used Ugandan SARS-CoV-2 secondary genomic data, publicly available online in the EpiCoV database within GISAID. We downloaded all the Ugandan complete genomic sequences, stratified them according to the year sequences were generated, and then randomly sampled from all sequence data generated by SARS-CoV-2 genomic surveillance studies in Uganda from 2020-2023. We used bioinformatics approaches including Multiple Sequence Alignment, Phylogenetic analysis, and positive selection analysis using the data monkey adaptive evolution server, and finally determined the rate of adaptive evolution using Python modules.
Results: One hundred and thirty-one full genome sequences (n =131) were considered for this study. Our analysis established a molecular evolutionary rate of 3.802*10-4 substitutions per site per year of SARS-CoV-2 in Uganda. Spike gene selection analysis using MEME and SLAC methods revealed dN/dS ratios of 1.64 and 1.56 respectively which were all above the ratio of 1. This was evidence of adaptive evolution acting within certain codons of the spike gene (p < 0.1). Our analysis also determined the adaptive evolutionary rate of the spike gene at 4.85*10-4 substitutions per codon per year.
Conclusion: Our research provided evidence of the adaptive evolution of SARS-CoV-2 in Uganda and most especially in the spike genomic region. This has important implications for the future virus’s transmission, vaccine efficacy, disease severity, and public health response. Continued surveillance, close monitoring of SARS-CoV-2 evolution, and collaboration with the global scientific community are essential. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | SARS-CoV-2 | en_US |
dc.subject | Uganda | en_US |
dc.subject | Molecular adaptive evolution | en_US |
dc.subject | Positive selection | en_US |
dc.subject | Spike gene. | en_US |
dc.title | Evidence of molecular adaptive evolution of SARS-CoV-2 in Uganda using whole genome sequences | en_US |
dc.type | Thesis | en_US |