Molecular clustering of clinical malaria infections based on AMA 1 gene in Rwanda: implications on Artemisinin resistance and potential vaccine development

Abstract

Background: Malaria caused by Plasmodium falciparum remains a major challenge in Rwanda, where genetic variability and emerging resistance threaten control strategies. This study examined molecular clustering of clinical P. falciparum infections based on the AMA1 gene and explored their association with PfK13 mutations and geographic distribution. Methods: A cross-sectional study analyzed 29 P. falciparum-positive isolates from Huye and Kirehe districts. Genomic DNA was sequenced targeting AMA1 and PfK13. Sequence data underwent quality control, SNP calling, and annotation. Genetic clustering was assessed using phylogenetic trees, haplotype networks, and principal component analysis (PCA). Neutrality tests (Tajima’s D, Fu & Li’s D) evaluated evolutionary pressures. Associations between AMA1 clusters and PfK13 mutations were investigated across regions. Results: AMA1 showed high polymorphism with 2,494 segregating sites and a Tajima’s D of +1.158, consistent with balancing selection. PCA and phylogenetic analyses revealed distinct haplotype clusters, indicating sub-structuring. PfK13 displayed limited variation (Tajima’s D = –0.071), reflecting nearneutral evolution. The R561H mutation, linked to artemisinin resistance, appeared only in Kirehe and co-occurred with specific AMA1 haplotypes, suggesting localized clustering of resistant lineages. Conclusion: Findings demonstrate molecular clustering of P. falciparum based on AMA1 diversity, with important implications for vaccine development and resistance monitoring. Integrating molecular and geographic data can enhance early detection of resistance hotspots and guide targeted interventions. Keywords: Plasmodium falciparum, AMA1, PfK13, artemisinin resistance, molecular clustering, Rwanda, haplotype diversity, vaccine development