Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya
Abstract 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 vec...
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2025-07-01
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| Online Access: | https://doi.org/10.1186/s12864-025-11788-3 |
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| author | Brian Polo Kelly L. Bennett Sonia Barasa Jon Brenas Silas Agumba Joseph Mwangangi Lucy Wachira Stanley Kitur Damaris Matoke-Muhia David M. Mburu Edith Ramaita Elijah O. Juma Charles Mbogo Eric Ochomo Chris S. Clarkson Alistair Miles Luna Kamau |
| author_facet | Brian Polo Kelly L. Bennett Sonia Barasa Jon Brenas Silas Agumba Joseph Mwangangi Lucy Wachira Stanley Kitur Damaris Matoke-Muhia David M. Mburu Edith Ramaita Elijah O. Juma Charles Mbogo Eric Ochomo Chris S. Clarkson Alistair Miles Luna Kamau |
| author_sort | Brian Polo |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-e69ab42cfe494b5ba9817b12a8492ccd |
| institution | Kabale University |
| issn | 1471-2164 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
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| series | BMC Genomics |
| spelling | doaj-art-e69ab42cfe494b5ba9817b12a8492ccd2025-08-20T03:37:19ZengBMCBMC Genomics1471-21642025-07-0126111410.1186/s12864-025-11788-3Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across KenyaBrian Polo0Kelly L. Bennett1Sonia Barasa2Jon Brenas3Silas Agumba4Joseph Mwangangi5Lucy Wachira6Stanley Kitur7Damaris Matoke-Muhia8David M. Mburu9Edith Ramaita10Elijah O. Juma11Charles Mbogo12Eric Ochomo13Chris S. Clarkson14Alistair Miles15Luna Kamau16Centre for Global Health Research (CGHR), Kenya Medical Research InstituteVector Genomic Surveillance Unit, Wellcome Trust Sanger InstitutePan-Africa Mosquito Control Association (PAMCA)Vector Genomic Surveillance Unit, Wellcome Trust Sanger InstituteCentre for Global Health Research (CGHR), Kenya Medical Research InstituteCentre for Geographic Medicine Research-Coast (CGMR-C), Kenya Medical Research InstituteCenter for Biotechnology Research and Development (CBRD), Kenya Medical Research instituteCenter for Biotechnology Research and Development (CBRD), Kenya Medical Research institutePan-Africa Mosquito Control Association (PAMCA)Pwani University Biosciences Research Centre (PUBReC)Ministry of Health - National Malaria Control Programme (NMCP)Pan-Africa Mosquito Control Association (PAMCA)Pan-Africa Mosquito Control Association (PAMCA)Centre for Global Health Research (CGHR), Kenya Medical Research InstituteVector Genomic Surveillance Unit, Wellcome Trust Sanger InstituteVector Genomic Surveillance Unit, Wellcome Trust Sanger InstituteCenter for Biotechnology Research and Development (CBRD), Kenya Medical Research instituteAbstract 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.https://doi.org/10.1186/s12864-025-11788-3Insecticide ResistanceAnopheles arabiensisPopulation GeneticsMalaria vectorKenya |
| spellingShingle | Brian Polo Kelly L. Bennett Sonia Barasa Jon Brenas Silas Agumba Joseph Mwangangi Lucy Wachira Stanley Kitur Damaris Matoke-Muhia David M. Mburu Edith Ramaita Elijah O. Juma Charles Mbogo Eric Ochomo Chris S. Clarkson Alistair Miles Luna Kamau Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya BMC Genomics Insecticide Resistance Anopheles arabiensis Population Genetics Malaria vector Kenya |
| title | Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya |
| title_full | Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya |
| title_fullStr | Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya |
| title_full_unstemmed | Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya |
| title_short | Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya |
| title_sort | genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in anopheles arabiensis across kenya |
| topic | Insecticide Resistance Anopheles arabiensis Population Genetics Malaria vector Kenya |
| url | https://doi.org/10.1186/s12864-025-11788-3 |
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