Genomic analysis reveals the emergence of molecular insecticide resistance in the malaria vector, Anopheles gambiae, from Western Ethiopia

Genomic analysis reveals the emergence of molecular insecticide resistance in the malaria vector, Anopheles gambiae, from Western Ethiopia | Research Square Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genomic analysis reveals the emergence of molecular insecticide resistance in the malaria vector, Anopheles gambiae, from Western Ethiopia Fekadu Gemechu, Kelly L. Bennett, Sisay Dugassa, Anastasia Hernandez-Koutoucheva, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8867942/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Aug, 2026 Read the published version in Parasites & Vectors → Version 1 posted 9 You are reading this latest preprint version Abstract Background Insecticide resistance poses a significant challenge to malaria control, driven by diverse molecular mechanisms, whose distribution remains poorly characterized in Ethiopia. This study presents the first results using whole-genome sequence data of Anopheles gambiae from Ethiopia, confirming its presence in the western region of the country and expanding its known geographical distribution. Methods Analysis of single-nucleotide polymorphisms and copy number variants focused on key target site insecticide resistance genes, including the voltage-gated sodium channel ( Vgsc ), acetylcholinesterase-1 ( Ace-1 ), the gamma-aminobutyric acid ( GABA )-gated chloride channel ( Rdl ) gene, as well as metabolic resistance loci such as cytochrome P450s ( Cyp6m2, Cyp6aa/p , Cyp9k1 ) and carboxylesterases ( Coeae2f , Coeae2–6g ). Results Genomic analysis revealed high frequencies of Vgsc - L995F (kdr-west) mutations, alongside amplifications at Cyp6aa/p , Cyp9k1 , and Gste2 . Notably, frequencies of Vgsc and Gste2 variants exhibited differences on a local scale, while Vgsc and Cyp9k1 variant frequencies also fluctuated seasonally. Findings highlight the need for site-specific monitoring on a fine temporal scale. Furthermore, genome-wide selection scans using phased haplotypes identified emerging signals of selection at loci with a potential link to insecticide resistance, including a signal spanning 2L:33,039,186–34,168,017, which expands the catalogue of candidate loci for functional validation. Conclusions Together, the results suggest that An . gambiae populations may be largely refractory to pyrethroids and moderately resistant to organophosphate (OPs) insecticides in western Ethiopia. Findings necessitate a better understanding of the An. gambiae geographical distribution in Ethiopia, accompanied by resistance-informed malaria control interventions targeting the vector. Anopheles gambiae sensu stricto target site insecticide resistance metabolic insecticide resistance selection scans Ethiopia whole-genome sequencing malaria vector Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background From a global perspective, insecticide resistance poses a significant challenge to malaria control [ 1 – 2 ], and a range of molecular mechanisms mediates it. Major mechanisms of insecticide resistance include target-site resistance, in which modification of the target site occurs through changes in the structure of the insect’s proteins, and metabolic resistance, in which increased enzyme production and/or efficiency enhance the detoxification of insecticides [ 3 ]. Furthermore, insecticide resistance can be promoted by reduced cuticle penetration or changes in behavior, such as avoiding areas treated with insecticides or through alterations in feeding habits [ 4 – 6 ]. Due to their importance in guiding malaria control, the insecticide resistance phenotypes of its major vectors, Anopheles mosquitoes, are routinely tracked using bioassays, often without identifying their underlying genomic determinants [ 3 , 5 ]. ecently, however, there have been calls to increase the use of molecular assays to determine the genomic mechanism of resistance, to guide effective use of interventions, and to track the impact of their implementation [ 7 – 8 ]. Even so, because molecular assays typically focus on a few known genomic variants, other novel markers rising in frequency and under selection pressure from insecticides can be missed [ 9 – 10 ]. This is particularly true because Anopheles mosquitoes rapidly evolve novel mechanisms of defense [ 11 – 12 ]. The use of whole-genome sequencing offers the advantage of identifying novel genes under positive selection, potentially linked to insecticide resistance [ 13 – 14 ]. Such an approach can bridge the existing gaps in prioritizing genes for validation studies or identifying markers for longitudinal tracking [ 12 , 14 ]. Within Anopheles mosquitoes, the major genes involved in target site resistance are the voltage-gated sodium channel ( Vgsc) , acetylcholinesterase ( Ace-1 ), and gamma-aminobutyric acid ( GABA )-gated chloride channel ( Rdl ). These genes are associated with resistance to pyrethroids and DDT [ 16 – 17 ], organophosphates [ 18 – 20 ], and carbamates [ 21 – 23 ], respectively. In addition, metabolic insecticide resistance is frequently driven by copy number variants (CNVs), particularly at cytochrome P450 genes such as the Cyp6aa / p [ 24 – 25 ], or Cyp6m2-z1 gene clusters, Cyp9k1 [ 23 ] carboxylesterases such as Coeae2f [ 25 , 27 – 28 ], Coeae2-7g [ 22 ] as well as the glutathione S-transferase Gste2 [ 18 , 29 ]. These gene variants often emerge due to selective pressures from insecticide-based interventions, such as indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) [ 19 , 30 , 31 ]. Despite the increasing emergence of resistance, insecticide-based tools remain the primary method for malaria control interventions, including in Ethiopia [ 30 ]. In Ethiopia, major malaria vectors are members of the Anopheles gambiae species complex, including Anopheles arabiensis , Anopheles quadriannulatus , and the Anopheles funestus species group [ 32 , 35 ]. Additionally, another major malaria vector in Africa, Anopheles gambiae s.s. , has been reported from the Meskan and Sodo districts of the Gurage zone, south-central Ethiopia [ 34 ]. Since members of the Anopheles gambiae are morphologically indistinguishable [ 36 , 40 ], they were molecularly identified based on species-specific single-nucleotide polymorphism (SNPs) in the intergenic spacer region (IGS) using polymerase chain reaction (PCR) (38). Furthermore, PCR-based approaches have limited resolution and sensitivity, and may be subject to primer failure or misidentification due to genome polymorphism [ 40 – 41 , 44 ]. However, An. gambiae is present in other neighboring East African countries, including Kenya [ 42 ] and Sudan [ 43 ], while Ethiopia harbors a suitable habitat for An. gambiae [ 44 ], including wet-humid climatic conditions typical of its distribution [ 48 – 49 ]. Studies from nearby East Africa have shown that An. gambiae has evolved insecticide resistance, including target site resistance through the L995F and L995S substitutions at Vgsc and the G119S substitution at Ace-1 [ 50 – 51 ], as well as metabolic resistance due to copy number variations (CNVs) at cytochrome P450 loci, including Cyp6m2 , Cyp6aa1 , and Cyp9k1 [ 26 , 52 – 53 ]. Additionally, elevated expression and gene amplification of carboxylesterases have been implicated in insecticide resistance, particularly at major loci such as Coeae2f and Coeae6o , which play a role in detoxifying OPs and pyrethroid resistance [ 25 , 27 ]. However, since Anopheles gambiae has not yet been confirmed in Ethiopia, there has been no report of insecticide resistance or its molecular markers in the country. An understanding of its distribution and the extent of insecticide resistance would aid effective intervention against a recent malaria resurgence in the country [ 32 , 52 – 53 , 56 ]. Our study presents the first confirmation of Anopheles gambiae presence in Ethiopia using whole-genome sequencing. We determined the presence and frequency of known insecticide resistance markers based on single-nucleotide polymorphism (SNP) and copy number variant (CNV) data. To access recent adaptive changes, we performed a genome-wide selection scan (GWSS) using phased haplotypes to investigate evidence of novel markers under selection from insecticides. Materials and Methods T he study areas Anopheles mosquitoes were collected from the border region of western Ethiopia, including sites in Gambella and Benishangul-Gumuz, in the districts of Agnuak and Kurmuk, respectively (Figure 1). The areas were characterized by a mixed ecological setting, including seasonally flooded lowlands, riverine and swampy habitats, irrigated agricultural fields, and peridomestic environments near human dwellings. Such habitat diversity supports year-round mosquito breeding and contributes to persistent malaria transmission [57-58]. Collections were performed 2023, during both the major and minor malaria transmission seasons in Ethiopia. The major transmission season typically occurs from September to December, following the main rainy season (June - September), when extensive rainfall creates abundant mosquito breeding habitats. The minor transmission season spans April to June, following a short rainy season (February to April). Mosquito collections Both adult and immature mosquitoes reared to adulthood were collected and identified as Anopheles gambiae s.l. using a morphological key [56]. Adults were collected using a standard Prokopack aspirator or manual CDC aspiration from both indoor and outdoor areas of residential areas. CDC light traps were also deployed to collect host-seeking adult mosquitoes [57]. Immature mosquitoes were collected using CDC dippers from a variety of breeding habitats, including sunlit puddles, rain-filled hoofprints, irrigation channels, and temporary pools near human dwellings, which were intensively searched and sampled during each surveillance round. Individual mosquitoes were preserved in absolute ethanol in PCR plates for DNA extraction and subsequent sequencing. DNA was extracted from individual mosquitoes using the Qiagen DNeasy Blood and Tissue Kit (Qiagen Sciences, MD, USA), following the manufacturer’s protocol. Whole genome sequencing Mosquitoes were prepared for whole-genome sequencing according to the guidelines of the Anopheles gambiae 1000 Genomes Project [58], which involved generating paired-end multiplex libraries using the Illumina protocol. However, instead of nebulization, genomic DNA was fragmented using Covaris Adaptive Focused Acoustics. Multiplexes comprised 12 tagged individuals of mosquitoes, and 150 bp paired-end reads were generated using an Illumina NovaSeq sequencer. Sequencing alignment and variant processing Sequencing reads were aligned to the AgamP4 reference genome using BWA-mem (Burrows-Wheeler Aligner) [60-61, 65]. Single-nucleotide polymorphism (SNP) data were generated using GATK version 3.7.0 [63] according to the protocols of the Anopheles gambiae 1000 Genomes Project(The Anopheles gambiae 1000 Genomes Consortium, 2020). Samples with a median coverage less than 10X, with less than 50% genome coverage, or with a high contamination threshold (>4.5%) were excluded from further analysis. Biallelic SNPs passing site filters were phased into haplotypes using a combination of read-backed phasing with WhatsHap V1.0 [68-69] and statistical phasing with SHAPEIT V4.2 [66]. Copy number variants (CNVs) were called following the procedures described in Lucas et al . (2019) using a Gaussian Hidden Markov Model (HMM) to calculate the copy number for each sample across windows of the genome using normalized coverage data. CNV calls were filtered for those with a high likelihood > 1000 predicted by the HMM model. To increase CNV prediction accuracy, individuals with high coverage variance (>0.35) were excluded. Full specifications for the alignment and variant processing pipelines are accessible in the MalariaGen/pipelines GitHub repository [67]. Results Taxonomic Structure Analysis We sought to investigate taxonomic status using a coordinated panel of ancestry-informative markers (AIMs) to assign individuals to their respective sister species. The AIMs encompassed a set of SNPs highly differentiated between species that can be used to differentiate An. arabiensis , An. gambiae and An. coluzzii [68] . First, a total of 2,612 AIM variants were employed to determine the taxonomic status of An. gambiae / An. coluzzii from the closely related and morphologically identical species Anopheles arabiensis . Analysis revealed that all samples had an AIM profile typical of either Anopheles gambiae or An. coluzzii (Figure S1- a). Sequentially, a total of 700 AIM variants were then used to distinguish An. gambiae from its sister species An. coluzzii . It was further confirmed that all samples had an AIM profile characteristic of An. gambiae (Figure S1-bottom). Since the AIMs used in analysis are based on a limited number of genomic markers from individuals representing a restricted geographical distribution [69], we sought to confirm taxon classification using both principal component analysis (PCA) and neighbor-joining trees (NJT).  To validate taxon assignments, we analysed our samples together with  Kenyan Anopheles gambiae s.l. samples from the MalariaGEN Vector Observatory dataset [14, 52, 74-75]. Samples represented known closely related and morphologically indistinct taxa from East Africa, including An. gambiae , An. arabiensis , An. coluzzii and the Pwani molecular form [72]. The PCA and NJT revealed five distinct groups representing individuals of An . arabiensis , An. coluzzii , Pwani molecular form , and two groups of An. gambiae . The two groups of An. gambiae include samples from coastal Kilifi in Kenya and the inland populations of Busia and Turkana in Kenya, reflecting the restricted gene flow previously observed between coastal and inland populations in East Africa [49](Figure 2). All Ethiopian An . gambiae s.l. clustered with inland East African An. gambiae, confirming their taxonomic status. Target site resistance Genes coding for insecticide targets, including pyrethroids, organophosphates, and organochlorines, were analyzed for the presence of associated single-nucleotide polymorphisms (SNPs) [77 - 78] and copy number variants (CNVs) within population cohorts of Anopheles gambiae s.s [79-80] from western Ethiopia. The voltage-gated sodium channel ( Vgsc ) gene, the acetylcholinesterase-1 enzyme ( Ace-1 ), and the gamma-aminobutyric acid ( GABA )-gated chloride channel gene ( Rdl ) were investigated. High frequencies of Vgsc -L995F, known to confer pyrethroid resistance in Anopheles gambiae and Anopheles arabiensis [77 - 78], were found in all cohorts from Western Ethiopia, but were higher in  Benishangul-Gumuz (79-81%) than in Gambella (66-77%).  Furthermore, a slight increase in frequencies was observed in both cohorts moving from the minor (June and July) to the major malaria transmission season (October and November) (Figure 3). Another substitution associated with pyrethroid resistance [77-78], Vgsc -L995S (kdr-east), was observed at moderate frequencies (19-34%) in all cohorts. Between the two survey time points, the frequency of Vgsc-L995S decreased while Vgsc-L995F increased in both Benishangul-Gumuz and Gambella (Figure 3). Metabolic Resistance We investigated metabolic gene clusters associated with Anopheles insecticide resistance, including glutathione-S-transferases ( Gste2 ) [26], the cytochrome P450 gene clusters ( Cyp6aa/p, Cyp6m2 and Cyp9k1 ) [76] and the carboxylesterase gene clusters (Coeae2f and Coeae2-7g ) [27, 81]. For each gene, we evaluated the frequency of individuals with at least one copy number variant (CNV) (Figure 4). Amino acid substitution frequencies were also analyzed for Gste2 since the L119V substitution has been functionally validated to confer permethrin (pyrethroid class) target-site resistance [76]. Although we did not observe the Gste2 -L119V substitution in An. gambiae from Ethiopia, we found CNV amplifications which were higher in Benishangul-Gumuz (20-31%) compared to Gambella (0-13%). Amplification frequencies were also higher in both locations during the major malaria transmission season in June and July (Figure 4). CNV amplifications at Cyp6aa1 were fixed across all cohorts. CNVs at Cyp9k1 were present at a high frequency (50-67%) and increased during the major malaria transmission season in both locations. This increase was only 3% in Gambella, but more pronounced in Benishangul-Gumuz with a 16% increase. Amplifications were present at the Coeae2-7 g gene cluster at a 14% frequency, but this was only observed in Gambella in July, suggesting its presence may be temporary. We did not observe CNVs at the Coeae2f locus for all cohorts (Figure 4). Selection scans To detect signals of recent positive selection across the genomes, we calculated Garud’s H12 [78] statistic in 1,000-2,500 base pair windows across all chromosome arms. One prominent selection peak spanned the region 2L:33,767,545–34,391,778, similarly observed under selection in Kenya and previously associated with mosquito survival on exposure to insecticides and PBO nets [83-84]. The region encompasses a variety of genes, including acetyl-CoA synthetase (AGAP006569), U DP-glucose 6-dehydrogenase ( AGAP006532 ), and outer segment 1 ( Oseg1 , AGAP006535 ) (Table S1). We also observed a selection peak in all cohorts at the Vgsc on 2L (Figure 5), the Cyp6aa/p gene cluster on 2R, and Gste2 on 3R, as well as an indistinct peak at Cyp9k1 on the X chromosome (Figure S2), which concurs with our findings of either substitutions or CNVs associated with insecticide resistance at these loci. Discussion Our taxonomic analysis of whole-genome sequences of Anopheles gambiae s.l mosquitoes confirms the presence of Anopheles gambiae s.s. in Ethiopia, consistent with earlier reports. We have revealed that An . gambiae sensu stricto is found in western Ethiopia, where it was previously unreported. Our findings raise an important question about whether its presence explains the year-round malaria burden in West Ethiopia and categorizes the region as a stable malaria transmission setting [ 85 – 86 ]. Our findings underscore the importance of revisiting the geographical distribution of malaria vectors in Ethiopia, where numerous studies have investigated Anopheles populations, but only one reported An. gambiae s.s. in south-central Ethiopia based on a traditional molecular assay [ 34 ]. In addition, we have revealed that An. gambiae in Ethiopia have evidence of emerging molecular insecticide resistance mechanisms under selection, similar to those reported from elsewhere in East Africa [ 52 , 87 ]. An. gambiae in western Ethiopia carried several metabolic resistance markers, with CNV frequencies similar to those in Benishangul-Gumuz and Gambella. For example, we observed amplifications at the Cyp6aa / p locus at a very high frequency in our samples from western Ethiopia. Consistent with previous reports from East African An. gambiae populations [ 52 , 22 ], these amplifications included the Cyp6aa1 locus. Duplication of Cyp6aa1 has been widely and increasingly documented as strongly associated with metabolic resistance to pyrethroids and other insecticides [ 22 , 80 , 88 – 90 ]. Our findings provide additional empirical evidence that Cyp6aa1 CNV amplifications are widespread in East Africa. Furthermore, amplification frequencies for Cyp9k1 , associated with enhanced metabolic detoxification of pyrethroids [ 91 – 92 ], were generally similar across sites, although the frequency was lower in the Benishangul-Gumuz cohort from June. Together, findings suggest a similar selective pressure impacting these loci across western Ethiopia, linked to insecticide exposure across the region. In support of this notion, both regions implement similar vector control interventions, including LLINs and IRS, which use both pyrethroids and carbamates [ 91 , 93 , 95 ]. Additionally, the two sampling sites are approximately 500 km apart, and recent genomic studies have reported extensive gene flow among An. gambiae populations across large geographical distances, including ecological zones and national borders [ 96 – 97 ], An. gambiae 1000 Genomes Consortium 2017). Therefore, it is likely that gene flow and the exchange of adaptive alleles occur between the two locations in western Ethiopia, although this requires further study on the population structure and connectivity of An. gambiae across the country. Although we observed some similarities, the frequency of metabolic resistance loci such as Gste and the target site resistance gene Vgsc differed on a localized scale. For example, we observed that Gste2 amplifications were notably higher in Benishangul-Gumuz compared to Gambella, suggesting a differential selection pressure or different evolutionary trajectory for this locus. Although both regions implement similar malaria control strategies, the widespread use of agrochemicals in agricultural communities may contribute to localized environmental exposure [ 95 ]. Increasingly, studies on the geographical distribution of insecticide resistance markers have cited agricultural chemical use as a potential influencing factor [ 96 ]. Although information on local insecticide and pesticide use in Ethiopia is generally lacking, a recent environmental assessment by the Ethiopian Environmental Protection Authority (EEPA) further highlights escalating land degradation and vegetation stress in Benishangul-Gumuz, driven in part by slash-and-burn agriculture and chemical inputs, which may contribute to off-target selection pressure on Anopheles populations [ 97 ]. Although we found that the Vgsc - L995F substitution impacting the target site of pyrethroids was detected at high frequencies in both sites, we found that frequencies were also slightly elevated in Benishangul-Gumuz. However, this difference was minor, and confirmation requires further longitudinal sampling across multiple years since both sites are expected to receive sustained pyrethroid pressure resulting from their widespread use in vector control [ 99 , 101 , 103 ]. We observed seasonal shifts in allele frequencies at key pyrethroid resistance loci, including Vgsc - L995F and Cyp9k1 . Vgsc - L995F showed a slight increase across the minor (June-July) and major (October-November) transmission seasons in all cohorts, in contrast to Vgsc - L995S , which showed a slight decrease. This observation is consistent with previous reports indicating that Vgsc - L995F and Vgsc - L995S are typically found on distinct haplotypes and have different fitness effects, which appear context-dependent [ 101 ]. While Vgsc - L995F has been associated with enhanced survival under insecticide pressure, it may also incur fitness costs in the absence of insecticides, potentially influencing its frequency in natural populations [ 58 , 101 – 102 ]. Although we have limited temporal resolution, our findings suggest that Vgsc - L995F tends to increase in frequency relative to Vgsc -L995S in wild populations during the major malaria transmission season, when insecticide use for malaria control is expected to be higher [ 104 – 105 ], while appearing less prevalent during the minor transmission season, possibly reflecting an associated fitness cost. Along with shifts in insecticide use for malaria control, the higher frequencies of both Vgsc - L995F and Cyp9k1 amplifications during the major transmission season could result from increased use of OP and pyrethroid-based agrochemicals applied during the major agricultural season, which coincides with the peak malaria transmission period (September to November) [ 95 ]. During this time, irrigated and flood-prone agricultural zones expand following the major rainy season, increasing the likelihood of mosquito larval exposure to sub-lethal doses of pesticides. Additionally, vector control interventions, such as IRS and ITNs, are typically scaled up during this period to curb transmission ([ 103 – 104 ]. Consistent with this seasonal intensification of chemical exposure, we observed a notable increase in Gste2 amplification frequencies linked to DDT, organophosphate, and pyrethroid resistance [ 26 , 99 , 105 – 106 ] during the major transmission season in western Ethiopia. Interestingly, we further observed a 19% increase in Gste2 - T154S , a substitution implicated in the detoxification of pyrethroids [ 71 ], although this was restricted to Benishangul-Gumuz. However, to date, this variant has not been functionally validated for its role in insecticide resistance, and its phenotypic impact remains uncertain. This temporal and regional difference raises the hypothesis that localized selection pressure may be acting on Gste2 - T154S , potentially driven by pyrethroid exposure. We observed an H12 selection scan peak at the genomic region spanning 2L:34,158, 499 − 34, 168, 017 centered on acetyl-CoA synthetase ( AGAP006569 ), a metabolic gene implicated in energy regulation and detoxification [ 107 ]. Our detection of a strong selection signature at both sampled locations for this locus aligns with transcriptomic and genomic surveillance by Nagi et al . (2025), who identified ( AGAP006569 ) as part of a broader group of metabolic genes potentially under selection in An. gambiae , particularly in populations from Kenya exposed to mixed agrochemical and public health insecticides. Furthermore, this gene’s upregulation has been linked to enhanced survival under pressure from pyrethroids and organophosphates [ 72 , 108 ], suggesting it as a candidate for functional validation. Other nearby genes like UDP-glucose 6-dehydrogenase ( AGAP006532 ) and outer segment 1 ( Oseg1 , AGAP006535 ) were previously identified under a selection peak in Kenyan populations at position 2L: 33.9-33.97 Mb and also potentially have a potential indirect role in insecticide resistance through cuticular modifications or sensory adaptation [ 24 , 72 ]. However, these genes did not fall under the peak we observed. Together with these studies, our findings indicate that selection on the 2L region is impacting An. gambiae across the wider East African region, emphasizing its growing significance as a locus of concern for vector control efforts. Conclusion This study presents the first whole-genome sequencing-based characterization of Anopheles gambiae in western Ethiopia, enabling high-resolution analysis of species identity and molecular insecticide resistance architecture, generating insights that can inform malaria control in the region. The confirmed presence of An. gambiae s.s. , a species with high vectoral capacity across East Africa, raises important concerns about its potential role in sustaining transmission, particularly in ecologically permissive zones of Ethiopia, where its distribution has been poorly characterized. To better characterise its presence in Ethiopia, the entomological surveillance of An. gambiae should be incorporated into routine regional monitoring. Our finding that An. gambiae s.s. in Ethiopia have a high frequency of both Vgsc-L995F target site and metabolic resistance-associated variants, including copy number amplifications at Cypaa/p, Cyp9k1 , and Gste2 , suggesting that populations may be largely refractory to pyrethroids and potentially moderately resistant to OPs, the cornerstone insecticides of current vector control programs. This resistance profile threatens the efficacy of both indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs), necessitating the development of species-specific and resistance-informed intervention strategies. The suggestion of seasonal fluctuations in An. gambiae molecular insecticide resistance marker frequencies underscore the critical importance of temporally resolved monitoring. Importantly, this study identifies a newly emerging signal of selection across multiple loci spanning the region 2L:34,158, 499 − 34, 168, 017. Our findings highlight its importance as an emerging signal of selection in East Africa and underscore the value of population genomics for detecting adaptive changes beyond canonical markers. Such insights provide a foundation for prioritizing loci in molecular assays and emphasize the need for functional validation to assess their operational impact on insecticide efficacy. Abbreviations ACE-1 - A cetylcholinesterase -1 CNV – Copy Number Variants Cyp450s – Cytochrome P450 monooxygenase system ENA - European Nucleotide Archive GABA - gamma-aminobutyric acid Gste – Glutathione S-transferase epsilon class genes GWSS - genome-wide selection scan IRS - indoor residual spraying LLINs - long-lasting insecticidal nets Rdl – Resistance to dieldrin SNP – Single Nucleotide Polymorphisms Vgsc – Voltage-gated Sodium Channel Declarations Data availability The sequences of the samples identified in this study were submitted to the European Nucleotide Archive (ENA; accession numbers in Table S2). Author contributions FG and KLB conducted the data analysis, interpretation, and wrote the manuscript. FG and AE conducted sample collection, processing, and data collection. SD facilitated sample collection, processing, and data collection. AHK, AE, and DA participated in data analysis. AM, CSC, and LG conceptualized and designed the study, interpreted the data, and assisted in drafting the manuscript. Ethics approval and consent to participate Mosquito collections were conducted with the informed consent of householders at each site. All sampling locations were non-protected areas, and the field work didn’t involve any direct human participation, endangered or protected species. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The MalariaGEN Vector Observatory has received support from multiple institutes and funding organizations. The Wellcome Sanger Institute’s participation was supported by funding from Wellcome (220540/Z/20/A, 'Wellcome Sanger Institute Quinquennial Review 2021-2026') and the Gates Foundation (INV-001927 and INV-068808). The Liverpool School of Tropical Medicine's participation was supported by the Gates Foundation (INV-068808), the National Institute of Allergy and Infectious Diseases ([NIAID] R01-AI116811), with additional support from the Medical Research Council (MR/P02520X/1). The latter grant is a UK-funded award and is part of the EDCTP2 programme supported by the European Union. Lemu Golassa of Addis Ababa University was funded by the Bill and Melinda Gates Foundation Grant No. INV-050277. Acknowledgements This study was supported by the MalariaGEN Vector Observatory, which is an international collaboration working to build capacity for malaria vector genomic research and surveillance, and involves contributions by the following institutions and teams. 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