Polo B, Bennett KL, Barasa S, Brenas J, Agumba S, Mwangangi J, Wachira L, Kitur S, Matoke-Muhia D, Mburu DM, Ramaita E, Juma EO, Mbogo C, Ochomo E, Clarkson CS, Miles A, Kamau L
BMC Genomics. 2025;26
BACKGROUND: Insecticide resistance in disease vectors poses a significant threat to the control of transmission globally. In Anopheles mosquitoes, resistance has jeopardized gains made in malaria control and led to the resurgence of cases. Although Anopheles arabiensis is a major malaria vector, little is known about its genetic diversity and insecticide resistance mechanisms across geographical space. There is an urgent need to incorporate genomics in resistance monitoring to allow preemptive detection of adaptive alleles. METHODS: We analyzed whole-genome data from 498 An. arabiensis specimens collected across five regions in Kenya. Population structure was assessed and both known and novel resistance mechanisms were investigated through SNP and CNV frequency analysis, genome-wide selection scans and haplotype clustering. RESULTS: Analyses of whole-genome data revealed geographical population structure between the northwestern region and central coastal Kenya, which was likely influenced by the Great Rift Valley. Distinct geographical differences in insecticide resistance profiles were observed across Kenya, reflecting differences in ecology, land use and selection pressure. For instance, in central Kenya, copy number variants at the Cyp6aa/p gene cluster and carboxylesterase genes associated with metabolic resistance to pyrethroids and organophosphates are fixed. In contrast, northwestern Kenya had mutations associated with both the target site and metabolic resistance to pyrethroids and DDT at high frequencies. Vgsc-L995F mutations occurred at frequencies of up to 44%, and duplications of Cyp9k1 occurred at frequencies of up to 66%. Genome-wide selection scans identified novel candidates under selection in central Kenya, including the Keap1 gene, which is involved in the regulation of multiple detoxification genes, likely due to high insecticide pressure in the region. CONCLUSION: Restricted gene flow coupled with heterogeneity in molecular insecticide resistance across Kenya suggests that localized control measures may be more effective in preventing the spread of insecticide resistance in An. arabiensis. This study highlights the importance of incorporating genomics in the routine monitoring of malaria vector populations to identify the emergence of new resistance signatures and their geographic distribution and spread.
