Spatial and temporal signatures of genomic insecticide resistance in the Anopheles arabiensis mosquito malaria vector from Ethiopia

Spatial and temporal signatures of genomic insecticide resistance in the Anopheles arabiensis mosquito malaria vector from Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Spatial and temporal signatures of genomic insecticide resistance in the Anopheles arabiensis mosquito malaria vector from Ethiopia Araya Eukubay, Kelly L. Bennett, Habte Tekie, Anastasia Hernandez-Koutoucheva, and 5 more This is a preprint; it has not been peer reviewed by a journal.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-8686648/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Insecticide resistance in Anopheles mosquitoes threatens the effectiveness of key malaria control tools such as insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in Ethiopia. Genomic analysis is essential to model known and novel molecular markers of insecticide resistance for effective resistance management. This study investigated insecticide resistance genes using whole-genome sequencing in a major malaria vector, Anopheles arabiensis sampled across the whole regions of Ethiopia and found high geographic and temporal variability in genes associated with insecticide resistance. The Vgsc-L995F target-site substitution in the voltage-gated sodium channel gene was highly prevalent in northern Ethiopia but less common at other sites. Metabolic modes of resistance in western Ethiopia were indicated by the high frequencies of copy number variants observed at the cytochrome P450 cluster Cyp6aa/p and the carboxylesterase Coeae2-7g . Frequencies of genetic markers associated with molecular target sites and metabolic resistance were generally lower in the Central Rift Valley. However, copy number variants (CNVs) at Gste2 and Cyp9k1 were observed at high frequency. We observed seasonal shifts in both target-site and metabolic marker frequencies, including increasing frequencies of Vgsc-L995F and several cytochrome P450 variants during the major transmission season. These patterns were specific to each location. Findings indicate that molecular insecticide resistance arises from a complex interplay of factors, including malaria control interventions, agricultural practices, human behavior, and possibly vector behavior. Selection scans revealed signals of selection on chromosome 2L, centered on the Coejhe1-5e genes in Werkamba, northernmost Ethiopia. Additional signals were detected on chromosome 3L (~ 20 Mb), near genes that may regulate detoxification pathways, including those associated with the ubiquitin–proteasome system in Asossa, western Ethiopia. Findings highlight the importance of integrating genomic surveillance of resistance markers into entomological monitoring to strengthen insecticide resistance management. They also underscore the need to investigate lesser-known sources of adaptive change that may have significant consequences for vector control. Biological sciences/Genetics Biological sciences/Molecular biology Biological sciences/Zoology Anopheles arabiensis target site resistance metabolic resistance insecticide resistance malaria mosquito vector Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Insecticides have been crucial in preventing and controlling vector-borne diseases. However, the emergence and widespread distribution of insecticide resistance is jeopardizing their effective implementation 1 . For example, the rapid emergence of insecticide resistance in Anopheles mosquito vectors has contributed to the resurgence of malaria, accounting for about 19% of resurgence events according to a systematic review by Cohen et al. 2 . Within Africa, the intensity of insecticide resistance and its underlying molecular basis varies greatly between mosquito vectors, across geography and over time 3 , 4 . These variations are often influenced by the strength and type of insecticide applied in major malaria interventions such as insecticide-treated nets (ITNs) and indoor residual spraying (IRS) 5 – 7 . In addition, the distribution of insecticide resistance is also influenced by human behaviors, including personal insecticide use 8 , 9 , and environmental factors such as anthropogenic pollution 10 , 11 . Monitoring such variation in insecticide resistance is vital to the application of appropriate resistance management strategies 12 , 13 , but it is largely based on laboratory-intensive phenotype bioassays often coupled with assays of only a few known molecular markers 14 – 16 . Genomic surveillance provides a complementary or alternative approach, allowing for the rapid and efficient monitoring of known molecular markers but also the identification of novel variation under selection 17 – 20 . This approach is not yet routinely applied to Anopheles vectors in Sub-Saharan Africa 21 , 22 and information on the geographical and seasonal presence of insecticide resistance is often lacking, including within the East African country of Ethiopia. Resistance to insecticides in Anopheles mosquitoes primarily evolves through target-site insensitivity and changes to metabolic detoxification, although there is growing evidence that cuticular changes and behavioral adaptations also contribute 23 , 24 .Target-site resistance involves alterations in the genes that encode for the protein targets of insecticides. For example, amino acid substitutions in the voltage-gated sodium-channel ( Vgsc ) gene, like L995S or the linked substitutions L995F and N1570Y, confer resistance to pyrethroids and DDT 19 , 25 . Additionally, whole genome sequence analysis recently revealed another two linked substitutions, Vgsc -V402L and Vgsc -I1527T, which synergistically enhance An. coluzzii resistance to pyrethroids 17 , 19 , 26 . The primary mutations conferring resistance to dieldrin are the amino acid substitutions A296G and A296S in the gamma-aminobutyric (GABA) gene Rdl 27 , 28 . Furthermore, the substitution Ace1 -A280S (also known as G119S) in the acetylcholinesterase-1 ( Ace-1 ) gene is known to confer resistance to carbamates and organophosphates 29 , often co-occurring with gene duplications that mitigate its associated fitness cost 26 , 30 . Metabolic insecticide resistance mechanisms can arise from overproduction, repetition, or enhancement of detoxification enzyme genes, leading to the enzymatic breakdown or sequestering of insecticides 31 . Copy number variants (CNVs) in detoxification gene clusters, such as cytochrome P450s ( Cyp6aa/p , Cyp9k1 ) 18 , glutathione S-transferase ( Gste2 ) 32 , and carboxylesterases ( Coeae2g-6g , Coeae1f-2f ) 33 , 34 are key drivers of resistance to pyrethroids, organophosphates, and DDT. For example, studies of Anopheles across West and East Africa have revealed high frequencies of Cyp6aa/p and Coeae2-7g CNVs associated with deltamethrin and pirimiphos-methyl resistance 18 , 33 , 35 , 36 , while duplications of the Gste2 gene contribute to resistance to multiple classes of insecticides 26 , 35 , 37 . The wide range of insecticide resistance mechanisms present within Anopheles vectors highlights the dynamic nature of genomic adaptation to insecticide pressure, emphasizing that it requires regular whole-genome monitoring to inform vector control strategies. Anopheles arabiensis is the primary malaria vector in Ethiopia and has a wide geographical distribution across the country 38 . This vector is found across lowland, highland, irrigated, and non-irrigated settings 39 – 42 , where it uses a wide range of habitats, including clear sunlit waters in permanent and temporary streams, hoofprints, artificial dams, roadside puddles, borrow pits, and rain pools 39 , 43 – 45 . The vector exhibits opportunistic, anthropozoophilic biting behavior, occurring throughout the night 46 , 47 . Although An. arabiensis shows a preference for human hosts indoors, it has a stronger inclination toward bovine hosts outdoors 47 – 49 . Its resting behavior is predominantly exophilic, favoring outdoor sites such as cattle sheds, pit shelters, ground holes, and vegetation over indoor resting spots. Bioassays of insecticide resistance in An. arabiensis have shown high resistance phenotypes to pyrethroids such as deltamethrin and permethrin, organophosphates including malathion, and the organochlorine DDT, with the levels differing across Ethiopia 14 , 50 – 53 . However, within Ethiopia, the molecular basis of insecticide resistance has been primarily investigated using targeted molecular assays of Vgsc knockdown down resistance mutations 14 , 50 – 53 , and gene expression studies of metabolic markers including cytochrome P450s, glutathione S-transferases, and carboxylesterases confined to a single location in the central region of the country 54 , 55 . For the first time, we used whole-genome sequencing to explore the genomic landscape of the An. arabiensis malaria vector across the whole of Ethiopia. Moreover, we present the first comprehensive genomic analysis of this species over both the major and minor malaria transmission seasons and across multiple years. Using longitudinal data, we analysed both SNPs and CNVs to investigate the spatial pattern of known target-site and metabolic resistance markers in the Anopheles genome. We also applied genome-wide selection scans to identify novel markers with the potential to be under local selection pressure from insecticides. Methods Mosquito Sampling Mosquitoes were collected from fifteen sites (Fig. 1 ) across the northern, central Great Rift Valley, southern, southwestern, and western Ethiopia. The sites are malarious with different ecoepidemiology, where both the ITN and IRS malaria vector control have been implemented for decades. Malaria transmission in most regions of Ethiopia follows a biannual seasonal pattern, with a major peak from September to December after the main rainy season (June-September) and a minor peak from April to July following the short rainy season (March and May) 56 – 58 . Mosquitoes were sampled during both major (September-December) and minor (April-July) transmission seasons between 2020 and 2023. Anopheles mosquitoes were sampled from selected households using a CDC light trap, mouth aspiration, and prokopack aspiration, both from indoor and outdoor locations, following the standard procedures described 59 . The CDC light traps were installed from 18:00 pm to 6:00 am. Battery-assisted Prokopack and manual aspirations were of a 15-minute duration per household from 6:00 am to 8:00 am, targeting indoor walls, under furniture, and animal shelters. Larval collections were performed using a standard dipper. Larvae were reared to adults for morphological identification, and all mosquito samples were identified morphologically using the standard identification keys 60 before individual preservation in 0.3 mL volume of PCR plates using 150 µL of 80% ethanol. Whole genome sequencing and processing Mosquitoes were whole-genome sequenced as part of the Malaria Vector Genome Observatory following the Anopheles gambiae 1000 Genomes Project ( https://malariagen.github.io/vector-data/ag3/methods.html ) protocols. DNA of individual mosquito specimens was extracted using the Qiagen DNeasy Blood and Tissue kit (Qiagen Sciences, MD, USA) according to the manufacturer's protocol. DNA was fragmented using Covaris Adaptive Focused Acoustics, and paired-end multiplex libraries were prepared as per Illumina’s instructions. All mosquito specimens were sequenced using the Illumina HiSeq X platform. Bioinformatic analysis, including raw sequence processing, quality filtering, read alignment, and variant calling, was performed using pipelines designed by the Anopheles gambiae 1000 Genomes project ( https://malariagen.github.io/vector-data/ag3/methods.html ). Reads were aligned to the AgamP4 reference genome using BWA version 0.7.15 and single nucleotide polymorphism (SNP) data generated with GATK version 3.7.0. Samples with a median coverage less than 10x, with less than 50% genome coverage, or with a high contamination threshold (> 4.5%) were excluded. CNV calling was based on copy number state generated across windows of the genome using normalized coverage data and a Gaussian Hidden Markov Model (HMM) implemented in hmmlearn ( GitHub - hmmlearn/hmmlearn: Hidden Markov Models in Python, with scikit-learn like API ) as previously described by Lucas et al. (2019) 18 . CNV calls were filtered such that only those with a high likelihood > 1000 predicted by the HMM model were retained. To increase CNV prediction accuracy, individuals with a high coverage variance (> 0.35) were removed. Genotypes at biallelic SNPs that met site filtering criteria were phased into haplotypes using a combination of read-backed and statistical phasing methods using WhatsHap V1.0 61 and SHAPEIT V4.2 62 , respectively, following protocols of the Anopheles gambiae 1000 Genome Project https://malariagen.github.io/vector-data/ag3/methods.html ). Insecticide Resistance Frequencies for population cohorts organised by the location, year, and month of collection were calculated for non-synonymous amino acid substitutions using the transcript for genes associated with pyrethroid, DDT, and organophosphate resistance. These included the gene encoding for the voltage-gated sodium channel ( Vgsc ; AGAP004707), which is the target site for pyrethroids, the GABA-gated chloride channel (resistance to dieldrin) gene, which is the target site for dieldrin ( Rdl ; AGAP006028), the acetylcholinesterase gene ( Ace1 ; AGAP001356), which codes for the target of organophosphates and a glutathione S-transferase gene, for which substitutions confer resistance to DDT and permethrin ( Gste2 ; AGAP009194). To account for sequencing and alignment error, only substitutions at a frequency > 5% were considered. We also generated the frequencies of copy number variants (CNVs) present at greater than 5% for cytochrome P450 genes such as Cyp6aa/p ( AGAP002862-AGAP013128) 63 and Cyp9k1 (AGAP000818), Cyp9m1 (AGAP009363) 64 , Cyp6z2 (AGAP008218) 65 , the carboxylesterases Coeae1f/2f (AGAP006227-AGAP006228) 34 and Coeae2-7g (AGAP006723-AGAP006727) 33 , the acetylcholinesterase Ace1 (AGAP001356) 66 , and glutathione S-transferase Gste2 (AGAP009194) 26 , 30 . All the analyses were conducted in the malariagen_data Python package. A chi-square contingency test was applied to assess the statistical significance of regional patterns in either amino acid substitutions or CNV frequencies at known resistance markers using the SciPy Python package 67 . For statistical analysis, the study sites were categorized by regions according to their geographical proximity: Northern (Werkamba, Raya-Azebo, Harbu), Central (Melka-Werer, Metehara, Wonji, Koka, Batu, Edo Gojola), Southern (Dilla, Arbaminch), Southwestern (Asendabo), and Western (Agnuak, Asossa). Genome-wide selection scans A genome-wide selection scan (GWSS) was performed using Garud’s H12 homozygosity statistic 68 across windows of the genome to detect signals of recent positive selection using the malariagen_data Python package ( https://malariagen.github.io/vector-data/ag3/api.html ). A window size calibration was performed for each chromosome arm before H12 analysis to determine the distribution of H12 values below 0.1 for the 95th percentile. The analysis was restricted only to chromosomes two and three since the X chromosome in the An. arabiensis is highly divergent from the An. gambiae reference genome. Results Population sampling A total of 1272 An. gambiae s.l. collected from fifteen sites were whole-genome sequenced at an average median sequence coverage of 34X. Specimens were identified as An. arabiensis based on Ancestry Informative Markers (AIM) and Principal Components Analysis (PCA) with known taxa during the standard data processing protocols of the Anopheles gambiae 1000G Project ( https://malariagen.github.io/vector-data/ag3/api.html ). A total of 69,636,442 SNPs passing site quality filters were segregated in the dataset, of which 33,534,459 were biallelic (Table 1 ). Table 1 Summary of Anopheles arabiensis samples whole-genome sequences available for analysis. Region Sampling site Latitude Longitude Year Month Anopheles arabiensis (N) Gambella Agnuak 7.504 34.293 2023 July 25 November 27 B/Gumuz Asossa 10.062 34.539 2023 June 23 October 13 South Ethiopia Arbaminch 6.033 37.583 2023 May 49 November 49 Dilla 6.254 38.173 2023 May 19 October 42 Oromia Asendabo 7.462 37.152 2023 July 50 November 45 Edo Gojola 7.975 38.722 2020 September 85 Batu 7.933 38.717 2021 September 7 2021 October 150 2023 May 49 2023 October 49 Koka 8.411 39.021 2021 October 110 Sodere 8.404 39.388 2021 September 6 Wonji 8.376 39.311 2023 May 46 October 6 November 30 Metehara 8.551 39.522 2023 June 50 October 9 November 40 Amhara Harbu 10.562 39.465 2023 May 49 November 49 Tigray Raya-Azebo 12.667 39.75 2023 July 50 November 28 Werkamba 13.667 38.917 2023 November 17 Afar Melka-Werer 9.19 40.105 2023 June 50 October 50 Table S1 Frequency of Vgs c-L995F resistance allele in Anopheles arabiensis from Ethiopia by geographical regions. Statistical significance was determined using a chi-square test (df = 1). A p-value ≤ 0.05 was considered significant. Location χ 2 df p -value Northern Central 129.11 1 < 0.0001 Southern 65.80 1 < 0.0001 Southwestern 27.73 1 < 0.0001 Western 33.70 1 < 0.0001 Central Southern 1.68 1 0.1956 Southwestern 0.59 1 0.4435 Western 0.01 1 0.9301 Southern Southwestern 2.55 1 0.1106 Western 0.37 1 0.5451 Western Southwestern 0.41 1 0.5245 Table S2 Frequency of Cyp6aa/p, Coeae2-7g , Cyp9k1, Gste2 , and Cyp6z2 copy number variation (CNVs) in Anopheles arabiensis across geographical regions in Ethiopia. Statistical significance was determined using a chi-square test (df = 1). A p-value ≤ 0.05 was considered significant. Location Genes Cyp6aa/p Coeae2-7g Cyp9k1 Gste2 Cyp6z2 χ 2 p-value χ 2 p-value χ 2 p-value χ 2 p-value χ 2 p-value Northern Central 1.442 0.2298 0.666 0.4144 27.380 < 0.0001 1.298 0.2546 0.006 0.9375 Southern 8.693 0.0032 2.551 0.1102 1.051 0.3052 4.541 0.0331 0.000 1.0000 Southwestern 0.000 0.9914 0.621 0.4307 1.940 0.1637 0.000 1.0000 0.621 0.4307 Western 39.773 < 0.0000 0.611 0.4343 0.012 0.9113 33.795 < 0.0000 0.023 0.8791 Central Southern 32.352 < 0.0000 1.289 0.2562 36.386 < 0.0001 2.295 0.1298 0.000 1.0000 Southwestern 0.202 0.6531 0.085 0.7707 4.304 0.0380 0.242 0.6225 1.169 0.2797 Western 109.873 < 0.0000 3.289 0.0697 11.098 0.0009 42.437 < 0.0000 0.159 0.6904 Southern Southwestern 5.909 < 0.0151 0.021 0.8836 5.104 0.0239 1.931 0.1646 0.817 0.3660 Western 10.908 < 0.0010 5.302 0.0213 1.008 0.3153 12.088 0.0005 0.085 0.7713 Western Southwestern 25.734 < 0.0000 2.172 0.1406 0.800 0.3711 18.550 < 0.0000 0.031 0.8601 Table S3 Putative genes showing increased H12 values (peaks) in the Asossa Anopheles arabiensis cohorts. Gene ID Conting Start End Name Description AGAP011227 3L 19635709 19644016 NaN Tartan AGAP011229 3L 19810767 19826552 NaN Tartan AGAP011231 3L 19867709 19868872 NaN fibrinogen AGAP011242 3L 19935159 19978825 NaN E3 ubiquitin ligase SMURF1/2 AGAP011243 3L 19979246 19979846 NaN Ribonuclease H2 subunit AGAP011244 3L 19979876 19981896 NaN rRNA 2'-O-methyltransferase fibrillarin AGAP011245 3L 19982535 19983733 NaN chloride channel AGAP011246 3L 19984046 19985106 NaN origin recognition complex subunit 6 AGAP011247 3L 19986323 19995087 NaN Longitudinals lacking protein-like AGAP011249 3L 19999770 20002401 NaN pre-mRNA-splicing factor CWC26 AGAP011251 3L 20072720 20077159 NaN ubiquitin-like protein 5 AGAP011254 3L 20102345 20111903 Arl5 ADP-ribosylation factor-like protein 5 Table S4 List of sample sets and accession numbers of the sequence samples. Samples with multiple run accessions are given within their respective sample sets. Sample sets Accession number 1270-VO-MULTI-PAMGEN-VMF00162 ERR6045394-ERR6045422,ERR6045425-ERR6045453,ERR6045456-ERR6045484 1270-VO-MULTI-PAMGEN-VMF00162 ERR5987917-ERR5987948,ERR5987949-ERR5987980,ERR5987981-ERR5988012 1270-VO-MULTI-PAMGEN-VMF00162 ERR5967771-ERR5967798,ERR5967799-ERR5967826,ERR5967827-ERR5967854 1270-VO-MULTI-PAMGEN-VMF00218 ERR10419623-ERR10419646 1270-VO-MULTI-PAMGEN-VMF00218 ERR10419672-ERR10419694 1270-VO-MULTI-PAMGEN-VMF00218 ERR10490762-ERR10490785 1270-VO-MULTI-PAMGEN-VMF00218 ERR10490810-ERR10490977 1270-VO-MULTI-PAMGEN-VMF00218 ERR10970454-ERR10970494, ERR11041589-ERR11041629 1324-VO-ET-GOLASSA-VMF00257 ERR12262329-ERR12262396 1324-VO-ET-GOLASSA-VMF00257 ERR12314213-ERR12314278 1324-VO-ET-GOLASSA-VMF00257 ERR12325996-ERR12326278 1324-VO-ET-GOLASSA-VMF00257 ERR12547479-ERR12547495 and ERR12767674 1324-VO-ET-GOLASSA-VMF00275 ERR12871282-ERR12871307 1324-VO-ET-GOLASSA-VMF00275 ERR12948031-ERR12948246 1324-VO-ET-GOLASSA-VMF00275 ERR12983126-ERR12983194 1324-VO-ET-GOLASSA-VMF00275 ERR13101382-ERR13101590 1324-VO-ET-GOLASSA-VMF00275 ERR13146891-ERR13146976 Supplementary Figures Target-site insecticide resistance variants To investigate the presence of target site resistance, we calculated the frequencies of non-synonymous (amino acid altering) substitutions at the voltage-gated sodium channel ( Vgsc : gene id AGAP004707-RD), acetylcholinesterase ( Ace-1 : gene id AGAP001356-RA), and GABA-gated channel gene ( Rdl : gene id AGAP006028-RA). The Vgsc -L995F associated with knockdown resistance to pyrethroids 19 , 69 was detected at a high frequency in the Northern Ethiopia Tigray region, with a frequency between 38% and 94% (Fig. 2 ). Lower but appreciable frequencies of 13–19% were also detected in the south-central regions of Amhara and South Ethiopia, as well as the western regions of Gambella and Benshangul Gumuz. We used a chi-squared contingency test to explore whether there was a significant difference in the frequency of Vgsc -L995F across the different regions of Ethiopia. We found a significant difference in the Vgsc -L995F frequency in the northern region when compared to frequencies in the central, southern, southwestern, and western regions of Ethiopia (P < 0.05, Supplementary Table S1). All other comparisons were non-significant. In some locations, we also observed a marked difference in frequencies moving into the major transmission season, but these were location-specific. For example, in Agnuak in western Gambella and Dilla in South Ethiopia, frequencies of L955F increased by 11% and 14%, respectively. In contrast, frequencies in northern Raya-Azebo and Asendabo in the southwest decreased by 8%. Substitutions associated with insecticide resistance, including Ace1 -G280S and Rdl -A296S, were not observed at > 5% frequency in all the sites except in the southern Ethiopian, Dilla town where the frequency of A296S was 6%, similar to previous observations for An. arabiensis from East Africa 36 , 70 . Copy number variation at known metabolic insecticide resistance genes We calculated the proportion of individuals with any number of CNV amplifications for each gene across study sites and seasons. The proportion of individuals with at least one CNV amplification at the Cyp6aa/p gene cluster, associated with pyrethroids and organophosphate insecticides 18 , 26 , was particularly high (65%) at the western site of Gambella. Furthermore, a chi-squared contingency test revealed the western region to have higher frequencies of CNVs compared to other regions in Ethiopia (P 0.05, Supplementary Table 2) in cohorts from Northern Ethiopia (0–29%), the Central Ethiopian Great Rift Valley (6–12%), and southwestern Ethiopia (6–7%). Moderate and statistically different frequencies were observed in Southern Ethiopia (6–29%) (P < 0.05, Supplementary Table 2). Frequencies of amplifications at the carboxylesterase Coeae2-7g were also comparatively high in western Gambella, with a frequency of 26% compared to less than 13% at other sites (Fig. 3 ). However, a chi-squared contingency test revealed that the CNV frequencies at the Coeae2-7g gene cluster were not significantly different for most regional comparisons, although frequencies in the western region were significantly different from that of southern Ethiopia (P < 0.05, Supplementary Table 2). CNV frequencies at other cytochrome P450s previously associated with resistance, including Cyp9k1 and Cyp6z2 , were generally comparable across sites (Fig. 3 ). Cyp9k1 amplification was consistently high (21–65%) and, in general, statistically similar across northern, western, southern, and southwestern Ethiopia (P > 0.05, Supplementary Table 2). However, frequencies were significantly higher, reaching up to 78% in the Central Great Rift Valley (P 0.05, Supplementary Table 2). We observed that frequencies in both Cyp9k1 and Cyp6z2 showed a frequency increase during the major transmission season in certain locations only, revealing that there is variation in the seasonal dynamics of metabolic resistance markers. For example, Cyp9k1 amplifications reached 78% compared to a lower frequency of 54% during the minor transmission season in Afar (Melka-Werer). Furthermore, Cyp6z2 CNV frequencies reached 15% in Tigray (Raya-Azebo) compared to 0% during the minor transmission season. In contrast to observations for cytochrome P450s and carboxylesterases, frequencies of Gste2 amplifications associated with pyrethroid and organophosphate resistance (Mitchell et al., 2014) 32 were highest in An. arabiensis from the northern region (35–98%), southwestern Ethiopia (79–91%), southern Ethiopia (70–78%) and the Central Ethiopian Great Rift Valley sites (58–88%), which were statistically similar to one another for most comparisons (P > 0.05, Supplementary Table 2). Conversely, frequencies of Gste2 were significantly lower in the western Ethiopian sites of Gambella and Benishangul-Gumuz (23–35%) (Fig. 3 ). Interestingly, the known SNPs of Gste2 (L119V, I114T) associated with resistance to DDT and pyrethroids 32 , 71 were absent in An. arabiensis from Ethiopia. Genome-wide selection scans A genome-wide scan for recent selection was performed using the H12 statistic, to investigate the presence of known and novel selection signals 68 . We identified a novel signal of selection on chromosome 2L, spanning 22.27–22.33 Mb, which encompasses the genes Coejhe1-5e . This selection signal was restricted to the cohorts from Werkamba only (Fig. 4 ). We checked for CNV amplifications at these genes and found a moderate to high (33–70%) frequency at Coejhe3e in all cohorts but a particularly high frequency of 82% in Werkamba. Although we found a 0–17% CNV frequency at Coejhe4e across all cohorts, CNVs were absent in Werkamba. We did not observe CNVs at the Coejhe1 , 2 , and 5e genes (Supplementary Figure S1). Similarly, we identified a signal of selection close to the Vgsc gene in the Werkamba site only (Fig. 4 ), where we found a high frequency of the L995F substitution. H12 analysis also revealed a novel signal of selection centred on chromosome 3L spanning 19.9–20.3 Mb, which is approximately 400 kb. The sweep signal encompasses 12 protein-coding genes (Supplementary Table S3), including chloride channel, fibrinogen, E3 ubiquitin ligase SMURF1/2, ADP-ribosylation factor-like protein 5, and ubiquitin factor-like protein 5. Notably, these selective signatures were only found in the Asossa site in Western Ethiopia (Fig. 4 ), and they were absent in any of the other study locations. Similarly, we found a signal of positive selection on the 3R chromosome around 31.84 Mb, encompassing the Cyp9m1, Cyp9m2, Gstu3 , odorant-receptor, nuclear hormone receptor FTZ-F1 beta , and cellular retinaldehyde-binding protein genes, in Northern Ethiopian cohorts from Raya-Azebo and Harbu and in the Wonji site located in the Central Rift Valley (Supplementary Figure S2). We screened for CNVs amplification in this region and found low frequencies at Gstu3 ranging from 0–14% across all cohorts, including those without a selection signal. Furthermore, we did not find amplifications at the other genes (Supplementary Figure S1), suggesting that the minor peak we observed could result from other structural variants such as SNPs, insertions, or indels. We also observed a more pronounced selection signal in the 2R chromosome centered on the Cyp6aa/p gene cluster (Supplementary Figure S3) in all populations of An. arabiensis , despite low frequencies of CNVs in cohorts from the Central Ethiopian Great Rift Valley. The clear signal of selection in the absence of a high CNV frequency suggests that an amino acid substitution (Supplementary Figure S4) or another structural variant may drive selection at this cytochrome P450. In support of the variable frequencies of Gste2 amplifications we observed, a signal of selection was detected at the gene on 3R in An. arabiensis from the Central Ethiopian Great Rift Valley and northern Amhara region (Supplementary Figure S2), but not the western region. Only a weak signal was observed in the northern sites. We did not observe a difference in selection signals between the major and minor malaria transmission seasons. Discussion In this study, we used whole-genome sequence analysis of 1272 An. arabiensis from Ethiopia to investigate molecular insecticide resistance mechanisms. We found marked geographical and temporal heterogeneity in resistance profiles across Ethiopia, pointing to potential influences of environmental and behavioral factors that warrant further investigation. Alongside established resistance markers, analysis of whole genomes allowed the identification of novel selection signals, highlighting new candidates for drivers of insecticide resistance, suggesting the need for targeted and routine monitoring to inform vector control strategies. We found considerable geographical variation in the molecular markers of insecticide resistance across Ethiopia. The historical use of DDT-based IRS since the 1960s 72 , followed by the scale-up of pyrethroid-based LLINs since 2005 73 , has been similarly applied across all malarious areas in Ethiopia. Despite the uniform application of vector control strategies across the country, the observed geographical differences in resistance profile could be impacted by differences in agricultural pesticide runoff. For example, the high frequency of Vgsc -L995F and selection signal observed in northern Ethiopia is likely driven by the region's intensive agricultural use of pyrethroids (lambda-cyhalothrin) and persistent DDT applications in horticultural crops, compounded by historical DDT exposure 74 . The western Ethiopia lowland also supports intensive large- and small-scale farming, mainly cotton and sesame 75 , and uses broad-spectrum pesticides 76 – 78 , which could explain the observed higher frequencies of cytochrome P450 and carboxylesterase CNVs. We also observed a comparatively lower frequency of Gste2 CNVs in the western region may reflect differing insecticide selection pressure. Although Gste2 amplifications are strongly associated with DDT metabolism 71 , their current distribution is more likely shaped by fitness costs 79 , cross-resistance to pyrethroids 71 , 80 – 82 , and other ecological factors such as agricultural chemical exposure and oxidative stress environments 83 , 84 . Furthermore, the comparable frequency of Cyp6aa/p CNVs we observed in the northern, southwestern and central Great Rift Valley regions may be influenced by shared agricultural practices, as farmers in both regions cultivate vegetables and cereals and apply similar classes of pesticides 74 , 85 . Additionally, the implementation of comparable vector control interventions such as ITNs and IRS may contribute to uniform selection pressure. However, there are also differences in intervention coverage and the type of insecticides used at the different locations that may contribute to variation in resistance patterns. For example, in western Ethiopia, where malaria transmission is high and year-round 57 , IRS with carbamate, organophosphate, and neonicotinoid (clothianidin-based) insecticides has been implemented 41 , 86 , 87 , alternating every two years in addition to the standard LLINs intervention in selected villages. This approach may increase metabolic-based resistance frequency while reducing pyrethroid target-site resistance-conferring markers due to potential fitness costs 88 , 89 . Additionally, it is possible that Anopheles behavior contributes to differences in the frequency of insecticide resistance-conferring markers. For example, in the cooler highlands of northern Ethiopia, lower outdoor temperatures may drive higher indoor biting rates among vectors such as An. arabiensis 42 , 90 , potentially exposing An. arabiensis to greater selection pressure from pyrethroid-based indoor interventions such as ITNs. However, this hypothesis is not fully supported due to a lack of species-specific comparative studies determining An. arabiensis behavior across the sites. However, it highlights that we know little of how this behavioral trait contributes to selection for insecticide resistance. Finally, we expect geography itself to impact the presence of genomic markers of insecticide resistance. For example, although not fully supported by the statistical analysis, we observed lower frequencies of both Vgsc -L995F and cytochrome P450s in the Great Rift Valley compared to elsewhere, despite high frequencies of Cyp9k1 , indicating the presence of selection for pyrethroid resistance 26 , 91 , 92 . Therefore, additionally or alternatively, it may be that restricted gene flow between the Great Rift Valley and other Ethiopian An. arabiensis has historically limited the spread of adaptive variation across the country. For example, genetic differentiation between the northwestern highlands and the Great Rift Valley of Ethiopia has been previously observed based on measures of F ST using microsatellite markers (Nyanjom et al., 2003) 93 . The high mountains surrounding the central Rift Valley populations may restrict mosquito gene flow, as evidenced by prior studies 70 , 94 , underscoring the necessity for further investigation into population connectivity in An. arabiensis . We observed marked differences in genomic insecticide resistance markers across the minor and major transmission seasons, demonstrating for the first time the potential of genomic data to track localised selection pressure from insecticides across a fine temporal scale. We found that seasonal differences were location-specific, and we did not have multi-year comparisons across seasons for statistical confirmation. However, we found that resistance-conferring variants (L995F and Cyp6aa/p CNV) increased during the major malaria transmission (September to December) in western (Gambella) and southern (Dilla, Arbaminch) cohorts. The increase was potentially driven by intense insecticide pressure from agricultural runoff 78 and/or LLIN utilization favoring individuals carrying resistant alleles over susceptible alleles, since IRS was not applied at these locations in 2023. In contrast, in northern (Raya-Azebo) and southwestern (Asendabo) Ethiopia, resistance variants unexpectedly increased in cohorts collected in July, which is typically the onset of the major rainy season rather than during the peak transmission season (September-December). This increase is possibly driven by year-round irrigation, sustained breeding habitats, and high intervention (ITN) utilization 95 , thereby maintaining selection pressure even before the onset of major transmission. Additionally, it may be coupled with climate variability, such as erratic rainfall, that supports emerging mosquito populations exposed to residual agricultural pesticides 74 , 96 . Our genome-wide selection scan revealed a novel signal of selection on the 2L chromosome in cohorts from northern Ethiopia (Werkamba). This selective sweep was centered on a gene cluster encoding five carboxylesterases: Coejhe1e , Coejhe2e , Coejhe3e , Coejhe4e , and Coejhe5e . While the primary function of these genes is in juvenile hormone regulation, their involvement in insecticide resistance is increasingly recognized. Indeed, there is a growing body of evidence demonstrating that members of these clusters, particularly Coejhe2e , are found consistently upregulated in organophosphate- and pyrethroid-resistant An. arabiensis populations 64 , 97 , suggesting their potential involvement in the metabolic insecticide resistance mechanism. We also identified a small selection peak on the 3L chromosome arm around 19.9–20.3 Mb in cohorts from Asossa in western Ethiopia. This region encompasses genes like E3 ubiquitin ligase SMURF1/2, chloride channel, ADP-ribosylation factor-like protein 5 (Arl5), ubiquitin factor-like protein 5, and fibrinogen. While these genes themselves have not yet been directly linked to insecticide resistance in Anopheles species, related E3 ubiquitin-protein ligase classes (such as SMURF1/2 like genes) have been identified as hub genes in resistance to organophosphate and pyrethroids in An. arabiensis and An. gambiae from Kenya and Benin 99 . Moreover, studies in yeast and Drosophila suggest that Arl5 and ubiquitin factor-like protein 5 support resistance by regulating stress response 100 – 102 . The ubiquitin factor-like protein 5 regulates mRNA splicing to assure that detoxification or antioxidant genes are expressed correctly. The Arl5 helps proteins move around the cell to keep it stable when oxidative stress is present 101 , 102 . Furthermore, the chloride channel ortholog, pICln-like protein, is a conserved regulator of spliceosomal snRNP assembly and cellular volume control in Drosophila with potential implications for gene expression under stress or developmental conditions 103 . Variants that enhance the efficiency of splicing or stress response may amplify the production of detoxification enzymes 104 , 105 . It is unknown whether these genes perform analogous functions in An. arabiensis and contribute to increased insecticide resistance, but they highlight the need for further functional investigation. In addition, we detected a small peak on the 3R chromosome centered around the Cyp9m1, Cyp9m2 , and Gstu3 genes previously reported to be overexpressed in pyrethroid-resistant An. arabiensis and An. funestus 64 , 106 , 107 . This peak was identified particularly in northern sites (Raya-Azebo and Harbu) and the central Great Rift Valley site of Wonji, but not in other surveyed sites. Cyp9m1 and Cyp9m2 encode Cyp450s commonly associated with metabolic insecticide detoxifications, while Gstu3 belongs to the Gste class, implicated in conjugation-based detoxification of pyrethroid and DDT. Although these genes are functionally linked to resistance, we did not detect CNVs at the Cyp9m1 and Cyp9m2 loci, which are typical of cytochrome P450 metabolic resistance 26 , 33 , 34 . Although CNVs in Gstu3 were identified at a low frequency, this was true of all study sites including those where no selection peak was observed. Our findings indicate that structural variation at this locus might be widespread but not necessarily under strong directional selection. Besides, the selection signal also comprises other genes with a potential role in insecticide resistance, including odorant receptors, the nuclear hormone receptor FTZ-F1 beta , and cellular retinaldehyde-binding protein 108 , 109 . Odorant receptors, while primarily involved in olfactory signalling, may contribute to behavioral resistance by modulating host-seeking and avoidance of insecticide-treated surfaces 108 , 110 . FTZ-F1 beta, a nuclear hormone receptor, regulates cuticular protein expression and has been shown to confer pyrethroid resistance in Culex pipiens pallens by modulating cuticular permeability 109 . The role of other genes in the mosquitoes is not studied. The selection signal for all aforementioned genes was minimal, but the strength of the peak could be affected by sampling effort. Further longitudinal sampling is needed to monitor the persistence of selection and confirm its potential significance in insecticide resistance. However, findings demonstrate how genomic surveillance is instrumental in identifying novel selection signals 20 , 22 , 36 , 70 , enabling the detection of genetic adaptations for further study that may contribute to insecticide resistance. Conclusion This study presents the first whole-genome sequencing data for An. arabiensis from Ethiopia using trans-seasonal collections across the major and minor malaria transmission seasons and multiple years from sites representing the whole of Ethiopia. This novel effort reveals, for the first time, the importance of capturing both spatial and seasonal patterns in the genomic landscape of insecticide resistance to uncover the full extent of its variation. An understanding of fine-scale temporal dynamics is critical in offering further resolution for the tailoring of malaria vector control strategies at the right time and with targeted interventions. In particular, our findings highlight the complexity of insecticide resistance in An. arabiensis across Ethiopia, driven by spatially heterogeneous mechanisms hypothesized to be shaped by vector control pressures, agricultural pesticide runoff, and interactions between human and vector behavior. In the Tigray region of northern Ethiopia, a high prevalence of Vgsc- L995F is likely to reduce the efficacy of pyrethroid-based interventions, potentially elevating vector survival. Conversely, in the western region, elevated Cyp6aa/p CNV amplification and moderate L995F frequencies may undermine LLIN and IRS efficacy while possibly promoting cross-resistance to organophosphates. In the central Rift Valley, high amplification of Cyp9k1 and Gste2 may circumvent the efficacy of conventional ITNs and IRS despite lower Vgsc-L995F frequencies. Further study is required to directly link the agricultural use of pesticides and human and vector behavior to both geographical and temporal genomic resistance patterns, as well as resistance phenotypes. Such studies will be crucial to comprehensively recognise the complexity of the selection landscape and to inform evidence-based control strategies. Data availability The sequences of the samples identified in this study were submitted to the European Nucleotide Archive (ENA; accession numbers are given in Supplementary Table S4). Declarations Competing interests The authors declare that they have no competing interests. Funding The MalariaGEN Vector Observatory is supported by multiple institutes and funders. 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 and 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 Gates Foundation Grant no. INV-050277. Author Contribution AE and KLB conducted the data analysis, interpretation and wrote the manuscript. AE and FG conducted sample collection, processing, and data collection. HT facilitated field sample collection and assisted data interpretation. AHK and FG conducted data analysis. AM, DA, CCC and LG conceptualised and designed the study, interpreted the data and assisted in drafting the manuscript. All the authors revised the manuscript. Acknowledgement 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. Wellcome Sanger Institute: Paballo Chauke, Katherine Figueroa, Kevin Howe, Mara Lawniczak; Liverpool School of Tropical Medicine: Julia Jeans, Lee Hart, Jon Brenas, Victoria Simpson, Eric Lucas, Sanjay Nagi, Martin Donnelly; Broad Institute of Harvard and MIT: Jessica Way, George Grant; Pan-African Mosquito Control Association: Jane Mwangi, Edward Lukyamuzi, Sonia Barasa, Ibra Lujumba, Elijah Juma. 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An atlas of positive selection in the genomes of major malaria vectors. 07.16.664900 Preprint at (2025). https://doi.org/10.1101/2025.07.16.664900 (2025). Odhiambo, C. A. et al. Key gene modules and hub genes associated with pyrethroid and organophosphate resistance in Anopheles mosquitoes: a systems biology approach. BMC Genom. 25 , 1–16 (2024). Rosenwald, A. G. et al. ARL1 and membrane traffic in Saccharomyces cerevisiae. Yeast 19 , 1039–1056 (2002). Hofmann, I. & Munro, S. An N-terminally acetylated Arf-like GTPase is localised to lysosomes and affects their motility. J. Cell. Sci. 119 , 1494–1503 (2006). Wilkinson, C. R. M. et al. Ubiquitin-like Protein Hub1 Is Required for Pre-mRNA Splicing and Localization of an Essential Splicing Factor in Fission Yeast. Curr. Biol. 14 , 2283–2288 (2004). Methylosome subunit pICln. (icln) – Drosophila melanogaster (Fruit fly). UniProtKB – A1ZAW5. UniProt Consortium (2025). https://www.uniprot.org/uniprotkb/A1ZAW5/entry Wei, P. et al. Alternative splicing of a carboxyl/choline esterase gene enhances the fenpropathrin tolerance of Tetranychus cinnabarinus. Insect Sci. 30 , 1255–1266 (2023). Díaz-Terenti, B., Ruiz, J. L. & Gómez-Díaz, E. Alternative splicing and its regulation in the malaria vector Anopheles gambiae. Front Malar 2 , (2024). Sandeu, M. M., Mulamba, C., Weedall, G. D. & Wondji, C. S. A differential expression of pyrethroid resistance genes in the malaria vector Anopheles funestus across Uganda is associated with patterns of gene flow. PLoS ONE . 15 , 1–21 (2020). Kouamo, M. F. M. et al. Allelic variation in a cluster of epsilon glutathione S-transferase genes contributes to DDT and pyrethroid resistance in the major African malaria vector Anopheles funestus. BMC Genom. 26 , 452 (2025). Wang, Q., Shentu, X., Yu, X. & Liu, Y. Insect Odorant-Binding Proteins (OBPs) and Chemosensory Proteins (CSPs): Mechanisms and Research Perspectives in Mediating Insecticide Resistance. Biology 14 , 1452 (2025). Xu, Y. et al. Transcription factor FTZ-F1 regulates mosquito cuticular protein CPLCG5 conferring resistance to pyrethroids in Culex pipiens pallens. Parasit. Vectors . 13 , 514 (2020). He, Z. et al. Genome-wide identification and expression profiling of odorant receptor genes in the malaria vector Anopheles sinensis. Parasit. Vectors . 15 , 143 (2022). Supplementary & Tables. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTablesFigures.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Mar, 2026 Reviews received at journal 05 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers invited by journal 09 Feb, 2026 Editor invited by journal 02 Feb, 2026 Editor assigned by journal 25 Jan, 2026 Submission checks completed at journal 25 Jan, 2026 First submitted to journal 24 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8686648","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588767995,"identity":"4bae0872-e4ec-452e-8279-8cbee5a7ba46","order_by":0,"name":"Araya Eukubay","email":"data:image/png;base64,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","orcid":"","institution":"Ethiopian Public Health Institute","correspondingAuthor":true,"prefix":"","firstName":"Araya","middleName":"","lastName":"Eukubay","suffix":""},{"id":588767996,"identity":"02391b10-ec38-45cd-87a1-ac8d7f9a671b","order_by":1,"name":"Kelly L. Bennett","email":"","orcid":"","institution":"Liverpool School of Tropical Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kelly","middleName":"L.","lastName":"Bennett","suffix":""},{"id":588767997,"identity":"40e41a40-b254-4f0f-bb01-0f4d1596c445","order_by":2,"name":"Habte Tekie","email":"","orcid":"","institution":"Department of Zoological Sciences, Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Habte","middleName":"","lastName":"Tekie","suffix":""},{"id":588767998,"identity":"8344fb05-965c-4b26-8dfb-008ee066745a","order_by":3,"name":"Anastasia Hernandez-Koutoucheva","email":"","orcid":"","institution":"Liverpool School of Tropical Medicine","correspondingAuthor":false,"prefix":"","firstName":"Anastasia","middleName":"","lastName":"Hernandez-Koutoucheva","suffix":""},{"id":588768006,"identity":"afb4e063-3109-4749-8c3f-89c450c7e025","order_by":4,"name":"Fekadu Gemechu","email":"","orcid":"","institution":"Ethiopian Public Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Fekadu","middleName":"","lastName":"Gemechu","suffix":""},{"id":588768010,"identity":"b895cd85-8a9d-4531-a686-6e9523e0cbf0","order_by":5,"name":"Alistair Miles","email":"","orcid":"","institution":"Ellison Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Alistair","middleName":"","lastName":"Miles","suffix":""},{"id":588768018,"identity":"5a55307d-1720-41a1-8ce2-2d8cdc8d89f7","order_by":6,"name":"Deriba Abera","email":"","orcid":"","institution":"Aklilu Lemma Institute of Health Research, Center for Pathobiology, Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Deriba","middleName":"","lastName":"Abera","suffix":""},{"id":588768021,"identity":"1ed6c555-d6a2-4a88-b024-87b0e8855b9c","order_by":7,"name":"Chris S. Clarkson","email":"","orcid":"","institution":"Liverpool School of Tropical Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chris","middleName":"S.","lastName":"Clarkson","suffix":""},{"id":588768023,"identity":"c765fb44-6d18-43c9-afd1-054af455cf51","order_by":8,"name":"Lemu Golassa","email":"","orcid":"","institution":"Aklilu Lemma Institute of Health Research, Center for Pathobiology, Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Lemu","middleName":"","lastName":"Golassa","suffix":""}],"badges":[],"createdAt":"2026-01-24 12:23:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8686648/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8686648/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102440993,"identity":"7474b955-6f15-4a95-a060-d6a85a3b915d","added_by":"auto","created_at":"2026-02-11 16:53:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139850,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Mosquito Sampling Sites across Ethiopia.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/d6f8bf9c33e1b9f6a762a9e5.png"},{"id":102440994,"identity":"96e6bfd4-411b-44f9-bbbc-4fbae1d010bf","added_by":"auto","created_at":"2026-02-11 16:53:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178834,"visible":true,"origin":"","legend":"\u003cp\u003eAmino acid allele frequencies for the \u003cem\u003eVgsc\u003c/em\u003e (AGAP004707-RD), \u003cem\u003eRdl \u003c/em\u003e(AGAP006028-RA) and \u003cem\u003eAce-1\u003c/em\u003e (AGAP001356-RA) genes in \u003cem\u003eAnopheles arabiensis\u003c/em\u003e across different regions of Ethiopia by sampling year and malaria transmission season. The Y-axis represents the frequency of the amino acid variants, each defined by a specific amino acid change and its genomic position. \u003cstrong\u003eMaMTS: \u003c/strong\u003emajor malaria transmission season; \u003cstrong\u003eMiMTS\u003c/strong\u003e: minor malaria transmission season.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/d928679f6e1d9c644662aad6.png"},{"id":102440990,"identity":"2e334ea6-f0ab-4907-ac75-e08dad716cf2","added_by":"auto","created_at":"2026-02-11 16:53:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":170493,"visible":true,"origin":"","legend":"\u003cp\u003eCopy number variation (CNV) frequency of the\u003cem\u003e Anopheles arabiensis Cyp450,\u003c/em\u003e \u003cem\u003eCOE\u003c/em\u003es, and \u003cem\u003eGste2 \u003c/em\u003egene clusters in \u003cem\u003eAnopheles arabiensis \u003c/em\u003efrom locations in Ethiopia stratified by year and malaria transmission season. The Y-axis represents the frequency of CNV amplification (amp) for each gene cluster. For the \u003cem\u003eGste2\u003c/em\u003egene, CNV and single nucleotide polymorphisms (SNPs) are plotted together. \u003cstrong\u003eMaMTS\u003c/strong\u003e: major malaria transmission season; \u003cstrong\u003eMiMTS\u003c/strong\u003e: minor malaria transmission season.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/f161dd8b8d4351c3f6b74c32.png"},{"id":102440991,"identity":"273a321f-eec8-4ffb-a5be-52a3de2833b7","added_by":"auto","created_at":"2026-02-11 16:53:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":347265,"visible":true,"origin":"","legend":"\u003cp\u003eGenome-wide selection scan of the H12 homozygosity statistic across the 2L and 3L chromosomes. Peaks in H12 values are centered in the 2L on the \u003cem\u003eCoejhe1-5e\u003c/em\u003egene cluster, and 3L:19925013-20324411 region, which includes 12 protein-coding genes, indicating a putative selection of signals. The name, gene ID, and description of genes found under the sweep on 3L are provided in Supplementary Table S3. \u003cstrong\u003eMaMTS\u003c/strong\u003e: major malaria transmission season; \u003cstrong\u003eMiMTS\u003c/strong\u003e: minor malaria transmission season.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/40baa815db76b7a5dd2d3d31.png"},{"id":102746113,"identity":"cad755d8-1087-440d-a0cb-67d565d51614","added_by":"auto","created_at":"2026-02-16 08:55:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2278892,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/c1f7c835-8596-4e87-861b-ed6e031fd24d.pdf"},{"id":102440992,"identity":"a9dd7cde-100f-46ab-866e-93a1131020c1","added_by":"auto","created_at":"2026-02-11 16:53:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1429972,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-8686648/v1/a3ca4eaa2fdf50d7cb6d8ba4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Spatial and temporal signatures of genomic insecticide resistance in the Anopheles arabiensis mosquito malaria vector from Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInsecticides have been crucial in preventing and controlling vector-borne diseases. However, the emergence and widespread distribution of insecticide resistance is jeopardizing their effective implementation\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. For example, the rapid emergence of insecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e mosquito vectors has contributed to the resurgence of malaria, accounting for about 19% of resurgence events according to a systematic review by Cohen et al.\u003csup\u003e2\u003c/sup\u003e. Within Africa, the intensity of insecticide resistance and its underlying molecular basis varies greatly between mosquito vectors, across geography and over time\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These variations are often influenced by the strength and type of insecticide applied in major malaria interventions such as insecticide-treated nets (ITNs) and indoor residual spraying (IRS)\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In addition, the distribution of insecticide resistance is also influenced by human behaviors, including personal insecticide use\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, and environmental factors such as anthropogenic pollution\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Monitoring such variation in insecticide resistance is vital to the application of appropriate resistance management strategies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, but it is largely based on laboratory-intensive phenotype bioassays often coupled with assays of only a few known molecular markers\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Genomic surveillance provides a complementary or alternative approach, allowing for the rapid and efficient monitoring of known molecular markers but also the identification of novel variation under selection\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This approach is not yet routinely applied to \u003cem\u003eAnopheles\u003c/em\u003e vectors in Sub-Saharan Africa\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and information on the geographical and seasonal presence of insecticide resistance is often lacking, including within the East African country of Ethiopia.\u003c/p\u003e \u003cp\u003eResistance to insecticides in \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes primarily evolves through target-site insensitivity and changes to metabolic detoxification, although there is growing evidence that cuticular changes and behavioral adaptations also contribute \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.Target-site resistance involves alterations in the genes that encode for the protein targets of insecticides. For example, amino acid substitutions in the voltage-gated sodium-channel (\u003cem\u003eVgsc\u003c/em\u003e) gene, like L995S or the linked substitutions L995F and N1570Y, confer resistance to pyrethroids and DDT\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Additionally, whole genome sequence analysis recently revealed another two linked substitutions, \u003cem\u003eVgsc\u003c/em\u003e-V402L and \u003cem\u003eVgsc\u003c/em\u003e-I1527T, which synergistically enhance \u003cem\u003eAn. coluzzii\u003c/em\u003e resistance to pyrethroids\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The primary mutations conferring resistance to dieldrin are the amino acid substitutions A296G and A296S in the gamma-aminobutyric (GABA) gene \u003cem\u003eRdl\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Furthermore, the substitution \u003cem\u003eAce1\u003c/em\u003e-A280S (also known as G119S) in the acetylcholinesterase-1 (\u003cem\u003eAce-1\u003c/em\u003e) gene is known to confer resistance to carbamates and organophosphates \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, often co-occurring with gene duplications that mitigate its associated fitness cost\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Metabolic insecticide resistance mechanisms can arise from overproduction, repetition, or enhancement of detoxification enzyme genes, leading to the enzymatic breakdown or sequestering of insecticides\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Copy number variants (CNVs) in detoxification gene clusters, such as cytochrome P450s (\u003cem\u003eCyp6aa/p\u003c/em\u003e, \u003cem\u003eCyp9k1\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, glutathione S-transferase (\u003cem\u003eGste2\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, and carboxylesterases (\u003cem\u003eCoeae2g-6g\u003c/em\u003e, \u003cem\u003eCoeae1f-2f\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e are key drivers of resistance to pyrethroids, organophosphates, and DDT. For example, studies of \u003cem\u003eAnopheles\u003c/em\u003e across West and East Africa have revealed high frequencies of \u003cem\u003eCyp6aa/p\u003c/em\u003e and \u003cem\u003eCoeae2-7g\u003c/em\u003e CNVs associated with deltamethrin and pirimiphos-methyl resistance\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, while duplications of the \u003cem\u003eGste2\u003c/em\u003e gene contribute to resistance to multiple classes of insecticides\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The wide range of insecticide resistance mechanisms present within \u003cem\u003eAnopheles\u003c/em\u003e vectors highlights the dynamic nature of genomic adaptation to insecticide pressure, emphasizing that it requires regular whole-genome monitoring to inform vector control strategies.\u003c/p\u003e \u003cp\u003e \u003cem\u003eAnopheles arabiensis\u003c/em\u003e is the primary malaria vector in Ethiopia and has a wide geographical distribution across the country\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This vector is found across lowland, highland, irrigated, and non-irrigated settings\u003csup\u003e\u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, where it uses a wide range of habitats, including clear sunlit waters in permanent and temporary streams, hoofprints, artificial dams, roadside puddles, borrow pits, and rain pools\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The vector exhibits opportunistic, anthropozoophilic biting behavior, occurring throughout the night \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Although \u003cem\u003eAn. arabiensis\u003c/em\u003e shows a preference for human hosts indoors, it has a stronger inclination toward bovine hosts outdoors\u003csup\u003e\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Its resting behavior is predominantly exophilic, favoring outdoor sites such as cattle sheds, pit shelters, ground holes, and vegetation over indoor resting spots. Bioassays of insecticide resistance in \u003cem\u003eAn. arabiensis\u003c/em\u003e have shown high resistance phenotypes to pyrethroids such as deltamethrin and permethrin, organophosphates including malathion, and the organochlorine DDT, with the levels differing across Ethiopia\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. However, within Ethiopia, the molecular basis of insecticide resistance has been primarily investigated using targeted molecular assays of \u003cem\u003eVgsc\u003c/em\u003e knockdown down resistance mutations\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and gene expression studies of metabolic markers including cytochrome P450s, glutathione S-transferases, and carboxylesterases confined to a single location in the central region of the country\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor the first time, we used whole-genome sequencing to explore the genomic landscape of the \u003cem\u003eAn. arabiensis\u003c/em\u003e malaria vector across the whole of Ethiopia. Moreover, we present the first comprehensive genomic analysis of this species over both the major and minor malaria transmission seasons and across multiple years. Using longitudinal data, we analysed both SNPs and CNVs to investigate the spatial pattern of known target-site and metabolic resistance markers in the \u003cem\u003eAnopheles\u003c/em\u003e genome. We also applied genome-wide selection scans to identify novel markers with the potential to be under local selection pressure from insecticides.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMosquito Sampling\u003c/h2\u003e \u003cp\u003eMosquitoes were collected from fifteen sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) across the northern, central Great Rift Valley, southern, southwestern, and western Ethiopia. The sites are malarious with different ecoepidemiology, where both the ITN and IRS malaria vector control have been implemented for decades. Malaria transmission in most regions of Ethiopia follows a biannual seasonal pattern, with a major peak from September to December after the main rainy season (June-September) and a minor peak from April to July following the short rainy season (March and May)\u003csup\u003e\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Mosquitoes were sampled during both major (September-December) and minor (April-July) transmission seasons between 2020 and 2023. \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were sampled from selected households using a CDC light trap, mouth aspiration, and prokopack aspiration, both from indoor and outdoor locations, following the standard procedures described\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. The CDC light traps were installed from 18:00 pm to 6:00 am. Battery-assisted Prokopack and manual aspirations were of a 15-minute duration per household from 6:00 am to 8:00 am, targeting indoor walls, under furniture, and animal shelters. Larval collections were performed using a standard dipper. Larvae were reared to adults for morphological identification, and all mosquito samples were identified morphologically using the standard identification keys\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e before individual preservation in 0.3 mL volume of PCR plates using 150 \u0026micro;L of 80% ethanol.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWhole genome sequencing and processing\u003c/h3\u003e\n\u003cp\u003eMosquitoes were whole-genome sequenced as part of the Malaria Vector Genome Observatory following the \u003cem\u003eAnopheles gambiae\u003c/em\u003e 1000 Genomes Project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malariagen.github.io/vector-data/ag3/methods.html\u003c/span\u003e\u003cspan address=\"https://malariagen.github.io/vector-data/ag3/methods.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e protocols. DNA of individual mosquito specimens was extracted using the Qiagen DNeasy Blood and Tissue kit (Qiagen Sciences, MD, USA) according to the manufacturer's protocol. DNA was fragmented using Covaris Adaptive Focused Acoustics, and paired-end multiplex libraries were prepared as per Illumina\u0026rsquo;s instructions. All mosquito specimens were sequenced using the Illumina HiSeq X platform. Bioinformatic analysis, including raw sequence processing, quality filtering, read alignment, and variant calling, was performed using pipelines designed by the \u003cem\u003eAnopheles gambiae\u003c/em\u003e 1000 Genomes project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malariagen.github.io/vector-data/ag3/methods.html\u003c/span\u003e\u003cspan address=\"https://malariagen.github.io/vector-data/ag3/methods.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Reads were aligned to the AgamP4 reference genome using BWA version 0.7.15 and single nucleotide polymorphism (SNP) data generated with GATK version 3.7.0. Samples with a median coverage less than 10x, with less than 50% genome coverage, or with a high contamination threshold (\u0026gt;\u0026thinsp;4.5%) were excluded. CNV calling was based on copy number state generated across windows of the genome using normalized coverage data and a Gaussian Hidden Markov Model (HMM) implemented in hmmlearn (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eGitHub - hmmlearn/hmmlearn: Hidden Markov Models in Python, with scikit-learn like API\u003c/span\u003e) as previously described by Lucas et al. (2019)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. CNV calls were filtered such that only those with a high likelihood\u0026thinsp;\u0026gt;\u0026thinsp;1000 predicted by the HMM model were retained. To increase CNV prediction accuracy, individuals with a high coverage variance (\u0026gt;\u0026thinsp;0.35) were removed. Genotypes at biallelic SNPs that met site filtering criteria were phased into haplotypes using a combination of read-backed and statistical phasing methods using WhatsHap V1.0\u003csup\u003e61\u003c/sup\u003e and SHAPEIT V4.2\u003csup\u003e62\u003c/sup\u003e, respectively, following protocols of the \u003cem\u003eAnopheles gambiae\u003c/em\u003e 1000 Genome Project \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malariagen.github.io/vector-data/ag3/methods.html\u003c/span\u003e\u003cspan address=\"https://malariagen.github.io/vector-data/ag3/methods.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e\n\u003ch3\u003eInsecticide Resistance\u003c/h3\u003e\n\u003cp\u003eFrequencies for population cohorts organised by the location, year, and month of collection were calculated for non-synonymous amino acid substitutions using the transcript for genes associated with pyrethroid, DDT, and organophosphate resistance. These included the gene encoding for the voltage-gated sodium channel (\u003cem\u003eVgsc\u003c/em\u003e; AGAP004707), which is the target site for pyrethroids, the GABA-gated chloride channel (resistance to dieldrin) gene, which is the target site for dieldrin (\u003cem\u003eRdl\u003c/em\u003e; AGAP006028), the acetylcholinesterase gene (\u003cem\u003eAce1\u003c/em\u003e; AGAP001356), which codes for the target of organophosphates and a glutathione S-transferase gene, for which substitutions confer resistance to DDT and permethrin (\u003cem\u003eGste2\u003c/em\u003e; AGAP009194). To account for sequencing and alignment error, only substitutions at a frequency\u0026thinsp;\u0026gt;\u0026thinsp;5% were considered. We also generated the frequencies of copy number variants (CNVs) present at greater than 5% for cytochrome P450 genes such as \u003cem\u003eCyp6aa/p (\u003c/em\u003eAGAP002862-AGAP013128)\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eCyp9k1\u003c/em\u003e (AGAP000818), \u003cem\u003eCyp9m1\u003c/em\u003e (AGAP009363)\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eCyp6z2\u003c/em\u003e (AGAP008218)\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e, the carboxylesterases \u003cem\u003eCoeae1f/2f\u003c/em\u003e (AGAP006227-AGAP006228)\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eCoeae2-7g\u003c/em\u003e (AGAP006723-AGAP006727)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, the acetylcholinesterase \u003cem\u003eAce1\u003c/em\u003e (AGAP001356)\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, and glutathione S-transferase \u003cem\u003eGste2\u003c/em\u003e (AGAP009194)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. All the analyses were conducted in the malariagen_data Python package. A chi-square contingency test was applied to assess the statistical significance of regional patterns in either amino acid substitutions or CNV frequencies at known resistance markers using the SciPy Python package\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. For statistical analysis, the study sites were categorized by regions according to their geographical proximity: Northern (Werkamba, Raya-Azebo, Harbu), Central (Melka-Werer, Metehara, Wonji, Koka, Batu, Edo Gojola), Southern (Dilla, Arbaminch), Southwestern (Asendabo), and Western (Agnuak, Asossa).\u003c/p\u003e\n\u003ch3\u003eGenome-wide selection scans\u003c/h3\u003e\n\u003cp\u003eA genome-wide selection scan (GWSS) was performed using Garud\u0026rsquo;s H12 homozygosity statistic\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e across windows of the genome to detect signals of recent positive selection using the malariagen_data Python package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malariagen.github.io/vector-data/ag3/api.html\u003c/span\u003e\u003cspan address=\"https://malariagen.github.io/vector-data/ag3/api.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e A window size calibration was performed for each chromosome arm before H12 analysis to determine the distribution of H12 values below 0.1 for the 95th percentile. The analysis was restricted only to chromosomes two and three since the X chromosome in the \u003cem\u003eAn. arabiensis\u003c/em\u003e is highly divergent from the \u003cem\u003eAn. gambiae\u003c/em\u003e reference genome.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePopulation sampling\u003c/h2\u003e \u003cp\u003eA total of 1272 \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. collected from fifteen sites were whole-genome sequenced at an average median sequence coverage of 34X. Specimens were identified as \u003cem\u003eAn. arabiensis\u003c/em\u003e based on Ancestry Informative Markers (AIM) and Principal Components Analysis (PCA) with known taxa during the standard data processing protocols of the \u003cem\u003eAnopheles gambiae\u003c/em\u003e 1000G Project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malariagen.github.io/vector-data/ag3/api.html\u003c/span\u003e\u003cspan address=\"https://malariagen.github.io/vector-data/ag3/api.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e A total of 69,636,442 SNPs passing site quality filters were segregated in the dataset, of which 33,534,459 were biallelic (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of \u003cem\u003eAnopheles arabiensis\u003c/em\u003e samples whole-genome sequences available for analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampling site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMonth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAnopheles\u003c/p\u003e \u003cp\u003earabiensis (N)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGambella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAgnuak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e34.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJuly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB/Gumuz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAsossa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e34.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJune\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSouth Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArbaminch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e37.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDilla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e38.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"14\" rowspan=\"15\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAsendabo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e37.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJuly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEdo Gojola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBatu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e7.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e38.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKoka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSodere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWonji\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e8.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e39.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMetehara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e8.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e39.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJune\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHarbu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e39.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRaya-Azebo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e39.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJuly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWerkamba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAfar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMelka-Werer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e40.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJune\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of \u003cem\u003eVgs\u003c/em\u003ec-L995F resistance allele in \u003cem\u003eAnopheles arabiensis\u003c/em\u003e from Ethiopia by geographical regions. Statistical significance was determined using a chi-square test (df\u0026thinsp;=\u0026thinsp;1). A p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1956\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.9301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.5451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.5245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of \u003cem\u003eCyp6aa/p, Coeae2-7g\u003c/em\u003e, \u003cem\u003eCyp9k1, Gste2\u003c/em\u003e, and \u003cem\u003eCyp6z2\u003c/em\u003e copy number variation (CNVs) in \u003cem\u003eAnopheles arabiensis\u003c/em\u003e across geographical regions in Ethiopia. Statistical significance was determined using a chi-square test (df\u0026thinsp;=\u0026thinsp;1). A p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eGenes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCyp6aa/p\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCoeae2-7g\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCyp9k1\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eGste2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cem\u003eCyp6z2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.2546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.9375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.0331\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.4307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.9113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e33.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.8791\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.1298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.0380\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.6225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.2797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.0009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e42.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.6904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0151\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.0239\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.1646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.3660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0213\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.0005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.7713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouthwestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e18.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.8601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePutative genes showing increased H12 values (peaks) in the Asossa \u003cem\u003eAnopheles arabiensis\u003c/em\u003e cohorts.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStart\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011227\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19635709\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19644016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTartan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011229\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19810767\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19826552\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTartan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011231\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19867709\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19868872\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003efibrinogen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011242\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19935159\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19978825\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eE3 ubiquitin ligase SMURF1/2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011243\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19979246\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19979846\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRibonuclease H2 subunit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011244\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19979876\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19981896\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003erRNA 2'-O-methyltransferase fibrillarin\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011245\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19982535\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19983733\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003echloride channel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011246\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19984046\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19985106\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eorigin recognition complex subunit 6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011247\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19986323\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19995087\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLongitudinals lacking protein-like\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011249\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19999770\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20002401\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003epre-mRNA-splicing factor CWC26\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011251\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20072720\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20077159\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNaN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eubiquitin-like protein 5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGAP011254\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20102345\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20111903\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArl5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eADP-ribosylation factor-like protein 5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of sample sets and accession numbers of the sequence samples. Samples with multiple run accessions are given within their respective sample sets.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample sets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAccession number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR6045394-ERR6045422,ERR6045425-ERR6045453,ERR6045456-ERR6045484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR5987917-ERR5987948,ERR5987949-ERR5987980,ERR5987981-ERR5988012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR5967771-ERR5967798,ERR5967799-ERR5967826,ERR5967827-ERR5967854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR10419623-ERR10419646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR10419672-ERR10419694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR10490762-ERR10490785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR10490810-ERR10490977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1270-VO-MULTI-PAMGEN-VMF00218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR10970454-ERR10970494,\u003c/p\u003e \u003cp\u003eERR11041589-ERR11041629\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12262329-ERR12262396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12314213-ERR12314278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12325996-ERR12326278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12547479-ERR12547495 and ERR12767674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12871282-ERR12871307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12948031-ERR12948246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR12983126-ERR12983194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR13101382-ERR13101590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1324-VO-ET-GOLASSA-VMF00275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERR13146891-ERR13146976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eSupplementary Figures\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTarget-site insecticide resistance variants\u003c/h3\u003e\n\u003cp\u003eTo investigate the presence of target site resistance, we calculated the frequencies of non-synonymous (amino acid altering) substitutions at the voltage-gated sodium channel (\u003cem\u003eVgsc\u003c/em\u003e: gene id AGAP004707-RD), acetylcholinesterase (\u003cem\u003eAce-1\u003c/em\u003e: gene id AGAP001356-RA), and GABA-gated channel gene (\u003cem\u003eRdl\u003c/em\u003e: gene id AGAP006028-RA). The \u003cem\u003eVgsc\u003c/em\u003e-L995F associated with knockdown resistance to pyrethroids\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e was detected at a high frequency in the Northern Ethiopia Tigray region, with a frequency between 38% and 94% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Lower but appreciable frequencies of 13\u0026ndash;19% were also detected in the south-central regions of Amhara and South Ethiopia, as well as the western regions of Gambella and Benshangul Gumuz. We used a chi-squared contingency test to explore whether there was a significant difference in the frequency of \u003cem\u003eVgsc\u003c/em\u003e-L995F across the different regions of Ethiopia. We found a significant difference in the \u003cem\u003eVgsc\u003c/em\u003e-L995F frequency in the northern region when compared to frequencies in the central, southern, southwestern, and western regions of Ethiopia (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Supplementary Table S1). All other comparisons were non-significant. In some locations, we also observed a marked difference in frequencies moving into the major transmission season, but these were location-specific. For example, in Agnuak in western Gambella and Dilla in South Ethiopia, frequencies of L955F increased by 11% and 14%, respectively. In contrast, frequencies in northern Raya-Azebo and Asendabo in the southwest decreased by 8%. Substitutions associated with insecticide resistance, including \u003cem\u003eAce1\u003c/em\u003e-G280S and \u003cem\u003eRdl\u003c/em\u003e-A296S, were not observed at \u0026gt;\u0026thinsp;5% frequency in all the sites except in the southern Ethiopian, Dilla town where the frequency of A296S was 6%, similar to previous observations for \u003cem\u003eAn. arabiensis\u003c/em\u003e from East Africa\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eCopy number variation at known metabolic insecticide resistance genes\u003c/h3\u003e\n\u003cp\u003eWe calculated the proportion of individuals with any number of CNV amplifications for each gene across study sites and seasons. The proportion of individuals with at least one CNV amplification at the \u003cem\u003eCyp6aa/p\u003c/em\u003e gene cluster, associated with pyrethroids and organophosphate insecticides\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, was particularly high (65%) at the western site of Gambella. Furthermore, a chi-squared contingency test revealed the western region to have higher frequencies of CNVs compared to other regions in Ethiopia (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, CNV frequencies at \u003cem\u003eCyp6aa/p\u003c/em\u003e were moderate or low but statistically similar (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2) in cohorts from Northern Ethiopia (0\u0026ndash;29%), the Central Ethiopian Great Rift Valley (6\u0026ndash;12%), and southwestern Ethiopia (6\u0026ndash;7%). Moderate and statistically different frequencies were observed in Southern Ethiopia (6\u0026ndash;29%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2). Frequencies of amplifications at the carboxylesterase \u003cem\u003eCoeae2-7g\u003c/em\u003e were also comparatively high in western Gambella, with a frequency of 26% compared to less than 13% at other sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, a chi-squared contingency test revealed that the CNV frequencies at the \u003cem\u003eCoeae2-7g\u003c/em\u003e gene cluster were not significantly different for most regional comparisons, although frequencies in the western region were significantly different from that of southern Ethiopia (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2). CNV frequencies at other cytochrome P450s previously associated with resistance, including \u003cem\u003eCyp9k1\u003c/em\u003e and \u003cem\u003eCyp6z2\u003c/em\u003e, were generally comparable across sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). \u003cem\u003eCyp9k1\u003c/em\u003e amplification was consistently high (21\u0026ndash;65%) and, in general, statistically similar across northern, western, southern, and southwestern Ethiopia (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2). However, frequencies were significantly higher, reaching up to 78% in the Central Great Rift Valley (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2) The frequency of \u003cem\u003eCyp6z2\u003c/em\u003e CNVs remained low (0\u0026ndash;18%) and was not statistically different across the different regions of Ethiopia (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2). We observed that frequencies in both \u003cem\u003eCyp9k1\u003c/em\u003e and \u003cem\u003eCyp6z2\u003c/em\u003e showed a frequency increase during the major transmission season in certain locations only, revealing that there is variation in the seasonal dynamics of metabolic resistance markers. For example, \u003cem\u003eCyp9k1\u003c/em\u003e amplifications reached 78% compared to a lower frequency of 54% during the minor transmission season in Afar (Melka-Werer). Furthermore, \u003cem\u003eCyp6z2\u003c/em\u003e CNV frequencies reached 15% in Tigray (Raya-Azebo) compared to 0% during the minor transmission season.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast to observations for cytochrome P450s and carboxylesterases, frequencies of \u003cem\u003eGste2\u003c/em\u003e amplifications associated with pyrethroid and organophosphate resistance (Mitchell et al., 2014)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e were highest in \u003cem\u003eAn. arabiensis\u003c/em\u003e from the northern region (35\u0026ndash;98%), southwestern Ethiopia (79\u0026ndash;91%), southern Ethiopia (70\u0026ndash;78%) and the Central Ethiopian Great Rift Valley sites (58\u0026ndash;88%), which were statistically similar to one another for most comparisons (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Supplementary Table\u0026nbsp;2). Conversely, frequencies of \u003cem\u003eGste2\u003c/em\u003e were significantly lower in the western Ethiopian sites of Gambella and Benishangul-Gumuz (23\u0026ndash;35%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Interestingly, the known SNPs of \u003cem\u003eGste2\u003c/em\u003e (L119V, I114T) associated with resistance to DDT and pyrethroids\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e were absent in \u003cem\u003eAn. arabiensis\u003c/em\u003e from Ethiopia.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGenome-wide selection scans\u003c/h2\u003e \u003cp\u003eA genome-wide scan for recent selection was performed using the H12 statistic, to investigate the presence of known and novel selection signals\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. We identified a novel signal of selection on chromosome 2L, spanning 22.27\u0026ndash;22.33 Mb, which encompasses the genes \u003cem\u003eCoejhe1-5e\u003c/em\u003e. This selection signal was restricted to the cohorts from Werkamba only (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). We checked for CNV amplifications at these genes and found a moderate to high (33\u0026ndash;70%) frequency at \u003cem\u003eCoejhe3e\u003c/em\u003e in all cohorts but a particularly high frequency of 82% in Werkamba. Although we found a 0\u0026ndash;17% CNV frequency at \u003cem\u003eCoejhe4e\u003c/em\u003e across all cohorts, CNVs were absent in Werkamba. We did not observe CNVs at the \u003cem\u003eCoejhe1\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e, and \u003cem\u003e5e\u003c/em\u003e genes (Supplementary Figure S1). Similarly, we identified a signal of selection close to the \u003cem\u003eVgsc\u003c/em\u003e gene in the Werkamba site only (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), where we found a high frequency of the L995F substitution. H12 analysis also revealed a novel signal of selection centred on chromosome 3L spanning 19.9\u0026ndash;20.3 Mb, which is approximately 400 kb. The sweep signal encompasses 12 protein-coding genes (Supplementary Table S3), including chloride channel, fibrinogen, E3 ubiquitin ligase SMURF1/2, ADP-ribosylation factor-like protein 5, and ubiquitin factor-like protein 5. Notably, these selective signatures were only found in the Asossa site in Western Ethiopia (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), and they were absent in any of the other study locations. Similarly, we found a signal of positive selection on the 3R chromosome around 31.84 Mb, encompassing the \u003cem\u003eCyp9m1, Cyp9m2, Gstu3\u003c/em\u003e, odorant-receptor, nuclear hormone receptor \u003cem\u003eFTZ-F1 beta\u003c/em\u003e, and cellular retinaldehyde-binding protein genes, in Northern Ethiopian cohorts from Raya-Azebo and Harbu and in the Wonji site located in the Central Rift Valley (Supplementary Figure S2). We screened for CNVs amplification in this region and found low frequencies at \u003cem\u003eGstu3\u003c/em\u003e ranging from 0\u0026ndash;14% across all cohorts, including those without a selection signal. Furthermore, we did not find amplifications at the other genes (Supplementary Figure S1), suggesting that the minor peak we observed could result from other structural variants such as SNPs, insertions, or indels.\u003c/p\u003e \u003cp\u003eWe also observed a more pronounced selection signal in the 2R chromosome centered on the \u003cem\u003eCyp6aa/p\u003c/em\u003e gene cluster (Supplementary Figure S3) in all populations of \u003cem\u003eAn. arabiensis\u003c/em\u003e, despite low frequencies of CNVs in cohorts from the Central Ethiopian Great Rift Valley. The clear signal of selection in the absence of a high CNV frequency suggests that an amino acid substitution (Supplementary Figure S4) or another structural variant may drive selection at this cytochrome P450. In support of the variable frequencies of \u003cem\u003eGste2\u003c/em\u003e amplifications we observed, a signal of selection was detected at the gene on 3R in \u003cem\u003eAn. arabiensis\u003c/em\u003e from the Central Ethiopian Great Rift Valley and northern Amhara region (Supplementary Figure S2), but not the western region. Only a weak signal was observed in the northern sites. We did not observe a difference in selection signals between the major and minor malaria transmission seasons.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we used whole-genome sequence analysis of 1272 \u003cem\u003eAn. arabiensis\u003c/em\u003e from Ethiopia to investigate molecular insecticide resistance mechanisms. We found marked geographical and temporal heterogeneity in resistance profiles across Ethiopia, pointing to potential influences of environmental and behavioral factors that warrant further investigation. Alongside established resistance markers, analysis of whole genomes allowed the identification of novel selection signals, highlighting new candidates for drivers of insecticide resistance, suggesting the need for targeted and routine monitoring to inform vector control strategies.\u003c/p\u003e \u003cp\u003eWe found considerable geographical variation in the molecular markers of insecticide resistance across Ethiopia. The historical use of DDT-based IRS since the 1960s\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, followed by the scale-up of pyrethroid-based LLINs since 2005\u003csup\u003e73\u003c/sup\u003e, has been similarly applied across all malarious areas in Ethiopia. Despite the uniform application of vector control strategies across the country, the observed geographical differences in resistance profile could be impacted by differences in agricultural pesticide runoff. For example, the high frequency of \u003cem\u003eVgsc\u003c/em\u003e-L995F and selection signal observed in northern Ethiopia is likely driven by the region's intensive agricultural use of pyrethroids (lambda-cyhalothrin) and persistent DDT applications in horticultural crops, compounded by historical DDT exposure\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. The western Ethiopia lowland also supports intensive large- and small-scale farming, mainly cotton and sesame\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, and uses broad-spectrum pesticides\u003csup\u003e\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, which could explain the observed higher frequencies of cytochrome P450 and carboxylesterase CNVs.\u003c/p\u003e \u003cp\u003eWe also observed a comparatively lower frequency of \u003cem\u003eGste2\u003c/em\u003e CNVs in the western region may reflect differing insecticide selection pressure. Although \u003cem\u003eGste2\u003c/em\u003e amplifications are strongly associated with DDT metabolism\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, their current distribution is more likely shaped by fitness costs\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e, cross-resistance to pyrethroids\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e,\u003cspan additionalcitationids=\"CR81\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e, and other ecological factors such as agricultural chemical exposure and oxidative stress environments\u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e. Furthermore, the comparable frequency of \u003cem\u003eCyp6aa/p\u003c/em\u003e CNVs we observed in the northern, southwestern and central Great Rift Valley regions may be influenced by shared agricultural practices, as farmers in both regions cultivate vegetables and cereals and apply similar classes of pesticides\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. Additionally, the implementation of comparable vector control interventions such as ITNs and IRS may contribute to uniform selection pressure. However, there are also differences in intervention coverage and the type of insecticides used at the different locations that may contribute to variation in resistance patterns. For example, in western Ethiopia, where malaria transmission is high and year-round\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, IRS with carbamate, organophosphate, and neonicotinoid (clothianidin-based) insecticides has been implemented\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e,\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e, alternating every two years in addition to the standard LLINs intervention in selected villages. This approach may increase metabolic-based resistance frequency while reducing pyrethroid target-site resistance-conferring markers due to potential fitness costs\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e. Additionally, it is possible that \u003cem\u003eAnopheles\u003c/em\u003e behavior contributes to differences in the frequency of insecticide resistance-conferring markers. For example, in the cooler highlands of northern Ethiopia, lower outdoor temperatures may drive higher indoor biting rates among vectors such as \u003cem\u003eAn. arabiensis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e, potentially exposing \u003cem\u003eAn. arabiensis\u003c/em\u003e to greater selection pressure from pyrethroid-based indoor interventions such as ITNs. However, this hypothesis is not fully supported due to a lack of species-specific comparative studies determining \u003cem\u003eAn. arabiensis\u003c/em\u003e behavior across the sites. However, it highlights that we know little of how this behavioral trait contributes to selection for insecticide resistance. Finally, we expect geography itself to impact the presence of genomic markers of insecticide resistance. For example, although not fully supported by the statistical analysis, we observed lower frequencies of both \u003cem\u003eVgsc\u003c/em\u003e-L995F and cytochrome P450s in the Great Rift Valley compared to elsewhere, despite high frequencies of \u003cem\u003eCyp9k1\u003c/em\u003e, indicating the presence of selection for pyrethroid resistance\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e,\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e. Therefore, additionally or alternatively, it may be that restricted gene flow between the Great Rift Valley and other Ethiopian \u003cem\u003eAn. arabiensis\u003c/em\u003e has historically limited the spread of adaptive variation across the country. For example, genetic differentiation between the northwestern highlands and the Great Rift Valley of Ethiopia has been previously observed based on measures of F\u003csub\u003eST\u003c/sub\u003e using microsatellite markers (Nyanjom et al., 2003)\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e. The high mountains surrounding the central Rift Valley populations may restrict mosquito gene flow, as evidenced by prior studies\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e, underscoring the necessity for further investigation into population connectivity in \u003cem\u003eAn. arabiensis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eWe observed marked differences in genomic insecticide resistance markers across the minor and major transmission seasons, demonstrating for the first time the potential of genomic data to track localised selection pressure from insecticides across a fine temporal scale. We found that seasonal differences were location-specific, and we did not have multi-year comparisons across seasons for statistical confirmation. However, we found that resistance-conferring variants (L995F and \u003cem\u003eCyp6aa/p\u003c/em\u003e CNV) increased during the major malaria transmission (September to December) in western (Gambella) and southern (Dilla, Arbaminch) cohorts. The increase was potentially driven by intense insecticide pressure from agricultural runoff\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e and/or LLIN utilization favoring individuals carrying resistant alleles over susceptible alleles, since IRS was not applied at these locations in 2023. In contrast, in northern (Raya-Azebo) and southwestern (Asendabo) Ethiopia, resistance variants unexpectedly increased in cohorts collected in July, which is typically the onset of the major rainy season rather than during the peak transmission season (September-December). This increase is possibly driven by year-round irrigation, sustained breeding habitats, and high intervention (ITN) utilization\u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e, thereby maintaining selection pressure even before the onset of major transmission. Additionally, it may be coupled with climate variability, such as erratic rainfall, that supports emerging mosquito populations exposed to residual agricultural pesticides\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur genome-wide selection scan revealed a novel signal of selection on the 2L chromosome in cohorts from northern Ethiopia (Werkamba). This selective sweep was centered on a gene cluster encoding five carboxylesterases: \u003cem\u003eCoejhe1e\u003c/em\u003e, \u003cem\u003eCoejhe2e\u003c/em\u003e, \u003cem\u003eCoejhe3e\u003c/em\u003e, \u003cem\u003eCoejhe4e\u003c/em\u003e, and \u003cem\u003eCoejhe5e\u003c/em\u003e. While the primary function of these genes is in juvenile hormone regulation, their involvement in insecticide resistance is increasingly recognized. Indeed, there is a growing body of evidence demonstrating that members of these clusters, particularly \u003cem\u003eCoejhe2e\u003c/em\u003e, are found consistently upregulated in organophosphate- and pyrethroid-resistant \u003cem\u003eAn. arabiensis\u003c/em\u003e populations\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e, suggesting their potential involvement in the metabolic insecticide resistance mechanism. We also identified a small selection peak on the 3L chromosome arm around 19.9\u0026ndash;20.3 Mb in cohorts from Asossa in western Ethiopia. This region encompasses genes like E3 ubiquitin ligase SMURF1/2, chloride channel, ADP-ribosylation factor-like protein 5 (Arl5), ubiquitin factor-like protein 5, and fibrinogen. While these genes themselves have not yet been directly linked to insecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e species, related E3 ubiquitin-protein ligase classes (such as SMURF1/2 like genes) have been identified as hub genes in resistance to organophosphate and pyrethroids in \u003cem\u003eAn. arabiensis\u003c/em\u003e and \u003cem\u003eAn. gambiae\u003c/em\u003e from Kenya and Benin\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. Moreover, studies in yeast and \u003cem\u003eDrosophila\u003c/em\u003e suggest that Arl5 and ubiquitin factor-like protein 5 support resistance by regulating stress response\u003csup\u003e\u003cspan additionalcitationids=\"CR101\" citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. The ubiquitin factor-like protein 5 regulates mRNA splicing to assure that detoxification or antioxidant genes are expressed correctly. The Arl5 helps proteins move around the cell to keep it stable when oxidative stress is present\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e,\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. Furthermore, the chloride channel ortholog, pICln-like protein, is a conserved regulator of spliceosomal snRNP assembly and cellular volume control in \u003cem\u003eDrosophila\u003c/em\u003e with potential implications for gene expression under stress or developmental conditions\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e. Variants that enhance the efficiency of splicing or stress response may amplify the production of detoxification enzymes\u003csup\u003e\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e,\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e. It is unknown whether these genes perform analogous functions in \u003cem\u003eAn. arabiensis\u003c/em\u003e and contribute to increased insecticide resistance, but they highlight the need for further functional investigation. In addition, we detected a small peak on the 3R chromosome centered around the \u003cem\u003eCyp9m1, Cyp9m2\u003c/em\u003e, and \u003cem\u003eGstu3\u003c/em\u003e genes previously reported to be overexpressed in pyrethroid-resistant \u003cem\u003eAn. arabiensis\u003c/em\u003e and \u003cem\u003eAn. funestus\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e,\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u003c/sup\u003e. This peak was identified particularly in northern sites (Raya-Azebo and Harbu) and the central Great Rift Valley site of Wonji, but not in other surveyed sites. \u003cem\u003eCyp9m1\u003c/em\u003e and \u003cem\u003eCyp9m2\u003c/em\u003e encode Cyp450s commonly associated with metabolic insecticide detoxifications, while \u003cem\u003eGstu3\u003c/em\u003e belongs to the \u003cem\u003eGste\u003c/em\u003e class, implicated in conjugation-based detoxification of pyrethroid and DDT. Although these genes are functionally linked to resistance, we did not detect CNVs at the \u003cem\u003eCyp9m1\u003c/em\u003e and \u003cem\u003eCyp9m2\u003c/em\u003e loci, which are typical of cytochrome P450 metabolic resistance\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Although CNVs in \u003cem\u003eGstu3\u003c/em\u003e were identified at a low frequency, this was true of all study sites including those where no selection peak was observed. Our findings indicate that structural variation at this locus might be widespread but not necessarily under strong directional selection. Besides, the selection signal also comprises other genes with a potential role in insecticide resistance, including odorant receptors, the nuclear hormone receptor \u003cem\u003eFTZ-F1 beta\u003c/em\u003e, and cellular retinaldehyde-binding protein\u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e,\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. Odorant receptors, while primarily involved in olfactory signalling, may contribute to behavioral resistance by modulating host-seeking and avoidance of insecticide-treated surfaces\u003csup\u003e\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e,\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eFTZ-F1 beta, a\u003c/em\u003e nuclear hormone receptor, regulates cuticular protein expression and has been shown to confer pyrethroid resistance in \u003cem\u003eCulex pipiens pallens\u003c/em\u003e by modulating cuticular permeability\u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. The role of other genes in the mosquitoes is not studied. The selection signal for all aforementioned genes was minimal, but the strength of the peak could be affected by sampling effort. Further longitudinal sampling is needed to monitor the persistence of selection and confirm its potential significance in insecticide resistance. However, findings demonstrate how genomic surveillance is instrumental in identifying novel selection signals\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e, enabling the detection of genetic adaptations for further study that may contribute to insecticide resistance.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents the first whole-genome sequencing data for \u003cem\u003eAn. arabiensis\u003c/em\u003e from Ethiopia using trans-seasonal collections across the major and minor malaria transmission seasons and multiple years from sites representing the whole of Ethiopia. This novel effort reveals, for the first time, the importance of capturing both spatial and seasonal patterns in the genomic landscape of insecticide resistance to uncover the full extent of its variation. An understanding of fine-scale temporal dynamics is critical in offering further resolution for the tailoring of malaria vector control strategies at the right time and with targeted interventions. In particular, our findings highlight the complexity of insecticide resistance in \u003cem\u003eAn. arabiensis\u003c/em\u003e across Ethiopia, driven by spatially heterogeneous mechanisms hypothesized to be shaped by vector control pressures, agricultural pesticide runoff, and interactions between human and vector behavior. In the Tigray region of northern Ethiopia, a high prevalence of \u003cem\u003eVgsc-\u003c/em\u003eL995F is likely to reduce the efficacy of pyrethroid-based interventions, potentially elevating vector survival. Conversely, in the western region, elevated \u003cem\u003eCyp6aa/p\u003c/em\u003e CNV amplification and moderate L995F frequencies may undermine LLIN and IRS efficacy while possibly promoting cross-resistance to organophosphates. In the central Rift Valley, high amplification of \u003cem\u003eCyp9k1\u003c/em\u003e and \u003cem\u003eGste2\u003c/em\u003e may circumvent the efficacy of conventional ITNs and IRS despite lower \u003cem\u003eVgsc-L995F\u003c/em\u003e frequencies. Further study is required to directly link the agricultural use of pesticides and human and vector behavior to both geographical and temporal genomic resistance patterns, as well as resistance phenotypes. Such studies will be crucial to comprehensively recognise the complexity of the selection landscape and to inform evidence-based control strategies.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe sequences of the samples identified in this study were submitted to the European Nucleotide Archive (ENA; accession numbers are given in Supplementary Table S4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe MalariaGEN Vector Observatory is supported by multiple institutes and funders. The Wellcome Sanger Institute\u0026rsquo;s participation was supported by funding from Wellcome (220540/Z/20/A, 'Wellcome Sanger Institute Quinquennial Review 2021\u0026ndash;2026') and the Gates Foundation (INV-001927 and INV-068808). The Liverpool School of Tropical Medicine's participation was supported by and 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 Gates Foundation Grant no. INV-050277.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAE and KLB conducted the data analysis, interpretation and wrote the manuscript. AE and FG conducted sample collection, processing, and data collection. HT facilitated field sample collection and assisted data interpretation. AHK and FG conducted data analysis. AM, DA, CCC and LG conceptualised and designed the study, interpreted the data and assisted in drafting the manuscript. All the authors revised the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis 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. Wellcome Sanger Institute: Paballo Chauke, Katherine Figueroa, Kevin Howe, Mara Lawniczak; Liverpool School of Tropical Medicine: Julia Jeans, Lee Hart, Jon Brenas, Victoria Simpson, Eric Lucas, Sanjay Nagi, Martin Donnelly; Broad Institute of Harvard and MIT: Jessica Way, George Grant; Pan-African Mosquito Control Association: Jane Mwangi, Edward Lukyamuzi, Sonia Barasa, Ibra Lujumba, Elijah Juma. The authors would like to thank the staff of the Wellcome Sanger Genomic Surveillance unit and the Wellcome Sanger Institute Sample Logistics, Sequencing and Informatics facilities for their contributions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe sequences of the samples identified in this study were submitted to the European Nucleotide Archive (ENA; accession numbers are given in Supplementary Table S4).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVan Den Berg, H. et al. Recent trends in global insecticide use for disease vector control and potential implications for resistance management. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 23867 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen, J. M. et al. 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Vectors\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e, 143 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary \u0026amp; Tables.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anopheles arabiensis, target site resistance, metabolic resistance, insecticide resistance, malaria mosquito vector","lastPublishedDoi":"10.21203/rs.3.rs-8686648/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8686648/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInsecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes threatens the effectiveness of key malaria control tools such as insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in Ethiopia. Genomic analysis is essential to model known and novel\u003c/p\u003e \u003cp\u003emolecular markers of insecticide resistance for effective resistance management. This study investigated insecticide resistance genes using whole-genome sequencing in a major malaria vector, \u003cem\u003eAnopheles arabiensis\u003c/em\u003e sampled across the whole regions of Ethiopia and found high geographic and temporal variability in genes associated with insecticide resistance. The Vgsc-L995F target-site substitution in the voltage-gated sodium channel gene was highly prevalent in northern Ethiopia but less common at other sites. Metabolic modes of resistance in western Ethiopia were indicated by the high frequencies of copy number variants observed at the cytochrome P450 cluster \u003cem\u003eCyp6aa/p\u003c/em\u003e and the carboxylesterase \u003cem\u003eCoeae2-7g\u003c/em\u003e. Frequencies of genetic markers associated with molecular target sites and metabolic resistance were generally lower in the Central Rift Valley. However, copy number variants (CNVs) at \u003cem\u003eGste2\u003c/em\u003e and \u003cem\u003eCyp9k1\u003c/em\u003e were observed at high frequency. We observed seasonal shifts in both target-site and metabolic marker frequencies, including increasing frequencies of \u003cem\u003eVgsc-L995F\u003c/em\u003e and several cytochrome P450 variants during the major transmission season. These patterns were specific to each location. Findings indicate that molecular insecticide resistance arises from a complex interplay of factors, including malaria control interventions, agricultural practices, human behavior, and possibly vector behavior. Selection scans revealed signals of selection on chromosome 2L, centered on the \u003cem\u003eCoejhe1-5e\u003c/em\u003e genes in Werkamba, northernmost Ethiopia. Additional signals were detected on chromosome 3L (~\u0026thinsp;20 Mb), near genes that may regulate detoxification pathways, including those associated with the ubiquitin\u0026ndash;proteasome system in Asossa, western Ethiopia. Findings highlight the importance of integrating genomic surveillance of resistance markers into entomological monitoring to strengthen insecticide resistance management. They also underscore the need to investigate lesser-known sources of adaptive change that may have significant consequences for vector control.\u003c/p\u003e","manuscriptTitle":"Spatial and temporal signatures of genomic insecticide resistance in the Anopheles arabiensis mosquito malaria vector from Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 16:52:57","doi":"10.21203/rs.3.rs-8686648/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-23T08:30:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-05T11:24:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T05:36:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74470171928012631846308803146202059283","date":"2026-02-11T15:19:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118094262471255202680770450647433940689","date":"2026-02-09T18:13:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230076631050107530438414388892494206529","date":"2026-02-09T08:39:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T08:14:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-02T12:04:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-26T04:42:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-26T04:42:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-01-24T12:06:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1fc0970b-cd55-4b4b-b50b-2f1c061275ab","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62637104,"name":"Biological sciences/Genetics"},{"id":62637105,"name":"Biological sciences/Molecular biology"},{"id":62637106,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-04-29T11:25:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 16:52:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8686648","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8686648","identity":"rs-8686648","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}