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Background: In Brazil, malaria is concentrated in the Amazon Basin, where more than 99% of the annual cases are reported. The main goal of this study was to investigate the population structure and genetic association of the biting behavior of Nyssorhynchus (also known as Anopheles) darlingi, the major malaria vector in the Amazon region of Brazil, using low‑ coverage genomic sequencing data. Methods: Samples were collected in the municipality of Mâncio Lima, Acre state, Brazil between 2016 and 2017. Different approaches using genotype imputation and no gene imputation for data treatment and low‑ coverage sequencing genotyping were performed. After the samples were genotyped, population stratification analysis was performed. Results: Weak but statistically significant stratification signatures were identified between subpopulations sepa‑ rated by distances of approximately 2–3 km. Genome‑ wide association studies (GWAS) were performed to compare indoor/outdoor biting behavior and blood‑seeking at dusk/dawn. A statistically significant association was observed between biting behavior and single nucleotide polymorphism (SNP) markers adjacent to the gene associated with cytochrome P450 (CYP) 4H14, which is associated with insecticide resistance. A statistically significant association between blood‑seeking periodicity and SNP markers adjacent to genes associated with the circadian cycle was also observed. Conclusion: The data presented here suggest that low‑ coverage whole‑ genome sequencing with adequate pro‑ cessing is a powerful tool to genetically characterize vector populations at a microgeographic scale in malaria trans‑ mission areas, as well as for use in GWAS. Female mosquitoes entering houses to take a blood meal may be related to a specific CYP4H14 allele, and female timing of blood‑seeking is related to circadian rhythm genes. malaria report 2019 [1], there were 229 million malaria Background cases and an estimated 409,000 deaths related to malaria Malaria is the most impactful arthropod-borne disease in 2018, 94% of which were concentrated in Africa. In in developing countries. According to the WHO world addition to Africa, this disease affects other poor popula - tions in tropical and subtropical areas because environ- *Correspondence: p.ribolla@unesp.br 1 mental conditions are favorable for the development of Sao Paulo State University (UNESP), Botucatu 18618‑689, Brazil Full list of author information is available at the end of the article the vectors and dissemination of the causative agent [2]. © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Alvarez et al. Parasites & Vectors (2022) 15:106 Page 2 of 11 Brazil presents a high incidence of malaria, with the each method must be carefully adjusted as the reduction majority of the 194,000 cases registered in 2018 concen- in coverage inevitably amplifies the possibility of false trated in the Brazilian Amazon rainforest [3]. Nyssorhyn- positive detection. chus darlingi, the main malaria vector in Brazil, is highly In the present study, we used low-coverage sequencing susceptible to human Plasmodium and capable of trans- markers to investigate the population of Ny. darlingi col- mitting the parasite inside and outside houses, even when lected in Mâncio Lima, Acre state, Brazil. Genetic data at low density [4]. Preferred breeding sites for this species were correlated with information such as specimen col- are collections of clear, shallow water that are shaded, lection and location (larva or adult), adult capture time, with vegetation and a low salt concentration [5–7]. Nys- house-to-house capture location (intra- or peridomestic) sorhynchus darlingi is both anthropophilic and oppor- and distance of larvae capture sites from forest areas. tunistic [8, 9] and, as the natural environment becomes more modified, or deforested, local populations tend to Methods cohabit with humans, invading their homes, thereby Sample collection increasing the importance of this species as a vector [10]. Larval and adult samples were captured from three dif- In the Amazon rainforest, it is the anopheline vector that ferent collection points in the municipality of Mâncio most quickly and efficiently benefits from the changes Lima, Acre state (Fig. 1) during December 2016 and Feb- humans produce to the natural environment [10, 11]. ruary, May and September 2017. Adult anophelines were Recent studies support the hypothesis of a Ny. dar- collected by human landing catch, by authors DPA, SMK, lingi species complex, and the mosquitoes present in the PRM and PEMR during 12-h collections, from 18:00 to Amazon correspond to one of three lineages within this 06:00 hours, for 2 days at each collection point. There complex [12]. Moreover, microgeographic scale studies were two volunteers indoors and two outdoors, who with markers across the Ny. darlingi genome have dem- rotated locations to mitigate collector-specific bias. The onstrated genetic differentiation that could represent three collection points were located around three houses, phenotypic differences related to malaria transmission as depicted in Fig. 1. The three samples are: (i) sampling dynamics [13, 14]. site A, houses relatively distant from the city center and The rapid development of technologies involved main streets as well as from forested areas; (ii) sampling in whole-genome sequencing (WGS) has resulted in site B, houses located in close proximity to the city center, dramatic reductions in the per base sequencing cost. alongside paved streets and distant from forested areas; However, studies that require the sequencing of large and (iii) sampling site C, houses relatively distant from numbers of samples remain costly, possibly prohibitively city center and in close proximity to forested areas. Biting so in some laboratories. One low-cost strategy is geno- behavior was recorded and classified as indoor or peri - typing-by-sequencing for low-coverage WGS (L-WGS), domestic (outdoor). The approximate linear distances which is associated with imputation that provides suffi - between the collection points were: 1.96 km from A to cient genomic information to select markers accurately B, 3.39 km from A to C and 2.51 km from B to C. Larvae [15]. The accuracy of variant detection is low in genomes were also collected in the community of Salvador, Loreto, with low coverage depth and tends to have a high false Peru (sampling site D on Fig. 1), for long-range compari- positive rate, but this is attenuated when information sons (site D is approximately 432 km distant from site A). between samples is combined, providing good common variant identification power [15, 16]. The inference of Sample preparation and sequencing genotypes by imputation for both panel-based genotyp- For DNA extraction, heads and thoraces of mosquitoes ing and sequencing genotyping has been shown to be were separated from the rest of the body with a sterile accurate, allowing for the potential use of extreme low- scalpel. Each adult (head and thorax) and larva (whole coverage WGS (EXL-WGS) to discover variants at a body) were extracted individually using the Glass Fiber dramatic reduction in cost when compared to standard Plate DNA Extraction Kit (Canadian Center for DNA WGS [17, 18]. Barcoding, Guelph, ON, Canada) following the Center’s Li and collaborators [19] demonstrated that rare vari- recommendations. DNA quantification was performed ants in L-WGS samples are more challenging to detect by fluorometric quantitation using QuBit dsDNA HS because of the difficulty in distinguishing genuine rare Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA) alleles from sequencing errors. The number of variants according to the manufacturer’s recommendations. identified is higher when the proportion of polymor - DNA libraries were prepared using one fifth of the phisms among the sequenced individuals in the segre- total volume recommended for the Nextera XT Library gated population is higher. Since different approaches prep kit (Illumina Inc., San Diego, CA, USA) following can be conducted in EXL-WGS analysis, the sensitivity of the manufacturer’s recommendations. DNA samples A lvarez et al. Parasites & Vectors (2022) 15:106 Page 3 of 11 Fig. 1 Nyssorhynchus darlingi collection sites in Mâncio, Lima city, Acre State, Brazil and in the Salvador community on the Napo River, Iquitos city, Loreto, Peru. A–D represent the collection sites: A 7°37′12.9″S, 72°53′06.7″W; B 7°38′02.1"S, 72°52′26.5"W; C 7°39′05.3″S, 72°53′20.9″W; D 3°44′17.1″S 73°14′19.9″W. The schematic representation of respective sites shows the houses where adults were captured (red dots), all breeding sites analyzed within approximately 1 km of each house (blue), forest areas (green) and the main roads (black lines) Alvarez et al. Parasites & Vectors (2022) 15:106 Page 4 of 11 Fig. 2 Estimated LD decay. Black dashed vertical line represents the estimated distance (in kbp) for r ≤ 0.1. Black dashed horizontal line represents mean r = 0.1. Black error bars represent the mean standard error. Green dashed line describes the estimated LD decay (nonlinear regression). Abbreviations: LD linkage disequilibrium were multiplexed to a total of 60 samples per run and Alignments were performed with BWA software and the sequenced in the NextSeq500 (Illumina) platform in variant calling was performed with the SamTools soft- a 151-cycle single-read run. Sequence quality analy- ware package. A genotype panel was generated in VCF sis was performed using the FastQC [20] program, and 4.2 format. Single nucleotide polymorphisms (SNPs) reads were used if results from all analysis modules were were removed from the pre-imputation panel by mini- approved without errors. mum allele frequency (MAF) < 0.1, as were missing data (MD) > 0.5 using the LCVCFtools program [25]. Geno- Species identification types with sequencing depth (DP) < 5 or genotype qual- Sequencing data was aligned with the Ny. darlingi ity of phred quality score (GQ) < 20 were imputed with cytochrome oxidase subunit I (COI) reference sequence BEAGLE 4.1 software [26] using genotype normalized (available at https:// www. ncbi. nlm. nih. gov/ nucco re/ probability values (PL). After imputation, genotypes were KP193 458.1/) using Burrows-Wheeler Aligner (BWA) removed from the panel if the probability of the imputed software [21]. After alignment, the individual COI con- genotype (GP) < 0.95. Finally, SNPs were filtered by sensus sequences were generated using the SamTools [22] MAF > 0.1, MD < 0.3 and Hardy–Weinberg Equilibrium software package. The BLASTn tool [23] was used for (HWE) < 0.001. HWE was calculated within locations multi-species identification using the individual gener - (collection points) to test for existing Wahlund effect ated COI consensus sequence. Only the highest matching between groups. result from BLAST was used. Specimens were discarded if The unimputed genotypic data used in secondary e-value > 1e-100, identities < 200, and identity < 90%, and if analyses were generated by the same variant call work- the matching sequence was not identified as Ny. darlingi . flow described above, except for the imputation and post-imputation steps. VCF quality control was applied Variant calling and genotype imputation with LCVCFtools. Genotypes were removed if DP < 5 The Ny. darlingi reference genome available in the and GQ < 20 and SNPs were filtered for MAF > 0.1 and VectorBase database, version AdarC3 [24], was used. MD < 0.8 (at least 15 non-missing genotypes from each A lvarez et al. Parasites & Vectors (2022) 15:106 Page 5 of 11 Fig. 3 The left image shows the principal component analysis and k‑means clustering analysis. The right images show the optimal k for k ‑means analysis (top right) and SNP F histogram for the statistically significant microgeographic informative SNPs (bottom right). For the optimal k plot, ST the blue line with dots represents the TWSS for the k‑th value (left axis) and the red bars represent the difference (in percentage) between the TWSS for the k‑th value and (k ‑ 1)‑th value (right axis). Abbreviations: SNP, Single nucleotide; TWSS, total within sum of squares polymorphism strata). HWE analysis control was also applied within and GS are the probabilities that two randomly selected strata (HWE < 0.001), including samples from Peru. alleles in the population and between house-to-house groups, respectively, will be identical by state. Pairwise Marker selection F values were calculated using all pruned markers, and ST The linkage disequilibrium decay was estimated from the a permutation test (10,000 permutations) was performed r pairwise linkage disequilibrium for all markers, calcu- to verify the statistical significance of the genome-wide lated by the PLINK 1.9 program [27]. Linkage disequilib-average F and per SNP F values. The genome-wide ST ST rium averages (r ) were calculated by 500-bp windows for average F and per SNP F estimates were consid- ST ST 40 adjacent windows, for a total of 20 kb. The prediction ered significant when P ≤ 0.05 after false discovery rate of the linkage disequilibrium decay function Y was calcu- (FDR; Benjamini–Hochberg procedure) correction. lated according to the nonlinear model Principal component analysis (PCA) was performed Y = β + β + e where β , is the intercept value, using the PLINK 1.9 program [27] and k-means cluster- 0 1 res 0 Log(x) ing was performed using R (R Foundation for Statistical β is the coefficient for variable one over the logarithm of Computing, Vienna, Austria). Both analyses were per- the distance of the markers in base pairs and e is the res formed using only the statistically significant SNP for value of residual error. SNPs were selected by pruning, stratification. considering as window size that the average r value at that distance is approximately between 0.1 and 0.05. Genomewide associa ‑ tion study A genome-wide association study (GWAS) was per- Population stratification analysis formed using the Cochran-Mantel–Haenszel Test statis- Stratification signals were estimated by F according to ST tical model [29]. The test assumes a case control 2 × 2 × the mathematical model of Weir and Cockerham [28]. K for k strata under the null hypothesis H that MH ~ χ The F value was calculated using the PLINK 1.9 pro- ST GS−GT (Chi-square) with 1 degree of freedom. The MH value gram according to the model F = ., where GT ST 1−GT Alvarez et al. Parasites & Vectors (2022) 15:106 Page 6 of 11 Fig. 4 Results for the genome‑ wide association study on biting behavior (outdoor vs indoor) and blood‑seeking (dusk vs dawn). Dashed lines represent false discovery rate‑ corrected P‑ value threshold of 0.05. Highlighted colors represent the scaffolds containing significantly associated SNPs. Labels represent genes located < 10 kb apart from the significant SNPs a +b a +c k ( )( ) i i i i 1 Results a − − i=1 n 2 2 i can be calculated as χ = , A total of 436 samples were captured and sequenced, of MH (a +b ) a +c b +d c +d k ( )( )( ) i i i i i i i i i=1 3 2 n −n which 394 and 42 samples were from Mâncio Lima and i i th Salvador, respectively. Following species identification given that in any biallelic site (alleles A and B) for the k and genome alignment, 73 samples from Mâncio Lima stratum, a and c are equal to the total number of alleles A and three from Salvador were discarded due to minimum for the case and control, respectively. In the same way, b sequencing coverage threshold, low confidence BLAST and d are equal to the total number of alleles B for the result or non-darlingi BLAST result for species identifi - case and control, respectively. n is the total number of cation. The samples used in the population analysis are observed alleles for the kth stratum, where described in Table 1 and Additional file 1: Table A. n = a + b + c + d. The imputed genotypes panel from 321 Brazilian sam - Case and control categories were considered indoor ples (Table 1) resulted in 1,070,802 markers, about 8.16 and outdoor for biting behavior, and samples were col- SNPs/kbp and a genotyping rate of 83.6%. The non- lected between 06:00 and 22:00 hours (dusk); samples imputed genotype panel from 360 Brazilian and Peru- collected between 02:00 and 06:00 hours (dawn) were vian samples resulted in 330,885 markers (29.6% of the considered as blood seeking at dusk or dawn. Stratum imputed panel), around 2.41 SNPs/Kbp and a genotyping groups were determined by collection location (A, B and rate of 14.2%. The linkage disequilibrium decay was esti - C). Table 1 shows the number of samples collected within mated and the observed nonlinear function coefficients the studied categories. were approximately − 0.40 (P < 0.001) and 4.76 (P < 0.001) The FDR multiple test correction method was applied for β and β , respectively, with R approximately = 0.97. 0 1 to control for false positives, assuming statistical sig- At approximately 12.57 kbp away, the estimated aver- nificance when corrected P-value < 0.05. Manhattan Plot age linkage disequilibrium was 0.1 for the lower confi - images were generated by R scripting in RStudio [30, 31]. dence interval curve. For practical purposes, 14 kb was Adjacent genes up to 10 kb from FDR-significant SNPs adopted as the window size for the pruning process. Fig- were investigated using AdarC3 [30, 31] from the anno- ure 2 shows the observed average linkage disequilibrium tated Ny. darlingi genome available in the gff3 format in VectorBase. A lvarez et al. Parasites & Vectors (2022) 15:106 Page 7 of 11 Table 1 Nyssorhynchus darlingi samples identified with BLASTn clusters and locations was found to be not independent and COI (e‑ value < 1e‑100) (χ = 95.257, df = 4, P-value < 2.2e-16). a b Cochran-Mantel–Haenszel model genome-wide StageCollection points Location Count association tests were performed between mosquitoes Adult A Indoor 12 collected outdoors and indoors (Fg. 4-I; Table 3) and Outdoor 35 mosquitoes collected during dusk (06:00 to 10:00 PM) Adult B Indoor 7 and dawn (02:00 to 06:00 AM) (Fig. 4-II; Table 3). For the Outdoor 15 indoor and outdoor analysis, three different scaffolds had Adult C Indoor 40 significantly associated SNPs that present genes < 10 kb Outdoor 93 apart from the significant SNPs (cyp4H14, period and Larvae A BS 1 9 prp4). For the blood-seeking period, three scaffolds had BS 2 14 significantly associated SNPs, of which two present genes BS 3 10 < 10 kb apart from the significant SNPs (timeless-2 and BS 4 15 rdgC) (Fig. 4). Larvae B BS 1 4 BS 2 10 Discussion BS 3 11 Population stratification and diversity BS 4 13 Significant F values were observed between groups ST Larvae C BS 1 7 from different collection sites in both the analyses BS 2 13 (imputed and non-imputed data). Considering pairwise BS 3 8 comparisons of the groups from Brazil and the compari- BS 4 5 son between groups from Brazil and Peru, groups col- Larvae D BS 1 39 lected in Acre showed signs of stratification that were approximately 15-fold lower when compared to the Mâncio Lima samples were collected at collection sites A (7°37’12.9"S, 72°53’06.7"W ), B (7°38’02.1"S, 72°52’26.5"W ) and C (7°39’05.3"S, 72°53’20.9"W ). F values between the groups from Brazil and Loreto, ST Peruvian larvae samples were collected at collection site D (3°23’47.0"S, Peru. Although the Mâncio Lima groups showed signifi - 73°12’18.2"W ) cance in the permutation tests, the F values showed Adult females were collected indoor or outdoor on each collection point. ST Larvae were collected around four different breeding sites (BS; 1–4)) within and a relatively weak signal of stratification. Gélin and col - around each collection point laborators [32] evaluated stratification between popula - tions of Anopheles gambiae in Muheza, Tanzania using microsatellite markers from 172 mosquito samples (43, values as a function of distance. Marker selection was 27 and 102 from Mamboleo, Songa Kibaoni and Zeneth performed by pruning, resulting in 123,620 markers villages, respectively). The linear distances between the (about 0.91 SNPs/kbp) and a genotyping rate of 86.06%. studied locations ranged from 5 to 10 km. F values of Mean F values obtained by pairwise comparisons ST ST 0.001, 0.003 and 0.009 were observed at distances of 6.5, of geographically and behaviorally distinct groups are 9.2 and 3.5 km, respectively, but none of the results were described in Table 2, considering imputed after pruning significant in the permutation test. Our study presents (IMPUT) and non-imputed (RAW) data. All geographi- similar observed values regarding the magnitude of the cally distinct populations presented significant F values, ST stratification signal for short distances and, interestingly, and no behaviorally distinct ones had significant values. the stratification signal of our data is significant. Strati - For comparison, 39 larvae of Ny. darlingi collected from fication analysis detected convergent results between Salvador (Peru), an estimated 465 km from Mâncio Lima the imputed and non-imputed panels, indicating that (Brazil), were compared with all Brazilian mosquitoes, imputation does not generate significant bias in strati - resulting in significant F (0.0420; P-value < 0.0001) that ST fied populations. The groups collected for biting behav - was 15-fold greater than the highest F obtained when ST ior and blood-seeking period did not show significant groups within Mâncio Lima, about 2–3 km apart, were F values. The PCA and clustering analysis indicated an compared. The per SNP permutation analysis resulted ST optimal k-value of k = 3 because this value had the opti- in a subset of 34 microgeographic informative SNPs. mal TWSS difference when compared to k < 3; in addi - The results from the PCA and clustering analysis shown tion the TWSS difference reached a plateau when k > 3. in Fig. 3 indicate an optimal k value of k = 3. Clusters 1, The three main clusters indicate a high association with 2 and 3 contain 7, 18 and 70 samples from location A, the microgeographic structure, with samples from loca- 34, 11 and 15 samples from location B and 35, 83 and tion A mostly in the third cluster (73.7%), samples from 48 samples from location C. The relationship between Alvarez et al. Parasites & Vectors (2022) 15:106 Page 8 of 11 Table 2 Mean F values obtained in pairwise comparisons ST a a DatasetGroup IGroup II N Geno F p M ST VALUE ‑2 IMPUT (imputed after C B 123,620 188 (84.7) 0.0009 1.6 × 10 pruning data) ‑5 C A 123,620 220(84.6) 0.0012 1.7 × 10 ‑3 A B 123,620 130 (84.0) 0.0015 1.3 × 10 ‑2 Outdoor Indoor 123,620 170 (84.5) 0.0005 9.4 × 10 ‑1 Dusk Dawn 123,620 107 (84.5) 0.0005 1.2 × 10 ‑3 RAW (non‑imputed C B 15,629 92 (34.5) 0.0008 3.5 × 10 ‑2 data) C A 15,629 86 (33.2) 0.0005 3.8 × 10 ‑4 A B 15,629 50 (32.5) 0.0027 9.8 × 10 ‑1 Outdoor Indoor 15,629 67(33.5) 0.0001 3.1 × 10 ‑1 Dusk Dawn 15,629 43(33.5) 0.0001 3.4 × 10 ‑4 C D 154,813 51 (14.2) 0.0420 1.0 × 10 Bold values indicate statistically significant p values (p < 0.05) F , Fixation index; N , number of single nucleotide polymorphisms used; Geno, average of non-missing genotypes per marker (% of total markers) ST M A, B and C: Locations from Mâncio Lima, Acre at which samples were collected. D: sample location from Loreto, Peru location B mostly in the first cluster (56.7%) and samples insecticide resistance. The role of prp4 is not yet clear, from location C mostly in the second cluster (50%). Inter- but the results suggest the importance of further studies estingly, the mosquito population structure presented to disclose the relationship between prp4 and insecticide here seems to be similar with Plasmodium vivax popu- resistance. lation structure reported by Salla and collaborators [33], The results of our GWAS on blood-seeking at dusk or where the city contains clusters of genetically correlated dawn and on adjacent gene regions related to the three parasites. We suggest that mosquito population structure significantly associated SNPs highlight two genes and could contribute to parasite population structure. their biological roles. The SNP ADMH02000929:14,323 (FDR-corrected P-value < 0.05) is located < 1.5 kb down- Genomewide associa ‑ tion study stream from the retinal degeneration C protein (rdgC) Our investigation of the gene regions adjacent to the gene locus, and the SNP ADMH02001945:12,409 (FDR- four significant SNPs in the GWAS for biting behavior corrected P-value < 0.05) is located approximately 1 kb revealed some genes that should be highlighted, includ- downstream from the timeout/timeless-2 (tim2 or time- ing prp4 and CYP4H14 (CYP450 superfamily). Two SNPs out) gene locus. Rhodopsin phosphatase (rdgC) plays an (ADMH02000641:85,279 and ADMH02000641:86,788) important role in the dephosphorylation of rhodopsin were < 10 kbp apart from CYP4H14 (FDR-corrected Rh1, the most abundant photosensory protein in Dros- P-value < 0.05). CYP450 is a well-known superfamily ophila melanogaster. Rh1 is required for molecular syn- containing members that are important in determin- chronization with light and circadian rhythm behavior ing insecticide resistance in insects [34], including in [39]. The loss of the rdgC gene function is associated anophelines [35–37]. The relationship between the use with Rh1 hyperphosphorylation, leading to photore- of pyrethroid insecticides indoors at locations where the ceptor degeneration in the presence of light in D. mela- samples were collected and the presence of markers asso- nogaster adults [40]. Adewoye[41] described several ciated with CYP450 genes was evident, since individuals candidate genes associated with the circadian cycle in D. with higher degrees of insecticide resistance were found melanogaster, including rdgC. Timeout is a timeless gene to have a higher chance of survival in an environment (tim1) paralog, and both have been described as compo- where the insecticide was applied. Gao and collabora- nents of the circadian cycle in D. melanogaster. Timeout tors [38] studied the response to five different types of is mainly involved in the perception of luminosity and insecticides on Plutella xylostella based on transcriptome circadian photoreception in adults [42]. Considering that analysis to identify genes that responded to these treat- all of the analyzed samples in the GWAS analysis were ments. The tested insecticides were chlorantraniliprole, adult Ny. darlingi (from Brazil), the functional associa- cypermethrin, dinotefuran, indoxacarb and spinosad. tion of timeout with the light stimulus at the time that Differential expression of prp4 genes was detected, anophelines were collected is rather remarkable. Honnen indicating the functional importance of this gene in and collaborators [43] studied differentially expressed A lvarez et al. Parasites & Vectors (2022) 15:106 Page 9 of 11 Table 3 List of statistically significant markers (P < 0.05) and adjacent genes in genome‑ wide association study for biting behavior FDR and blood‑seeking at dusk or dawn Scaffold Position Reference Alternative List of adjacent genes P FDR allele allele Biting behavior –4 ADMH02000641 85279 C T FMRFamide receptor [81054:82517]; cytochrome P450 CYP4H14 [87272:89456]; 6.23 × 10 DNA‑ J [91017:92150] –2 ADMH02000641 86788 C A FMRFamide receptor [81054:82517]; cytochrome P450 CYP4H14 [87272:89456]; 1.03 × 10 DNA‑ J [91017:92150] –2 ADMH02001329 14688 T C period circadian protein [8167:14819]; 8‑ oxoguanine DNA glycosylase [6298:7671] 1.03 × 10 –2 ADMH02002006 31454 G C prp4 [28738:32685] 1.64 × 10 Blood-seeking at dusk or dawn –2 ADMH02000323 77474 G A – 3.37 × 10 –2 ADMH02001945 12409 G A timeout/timeless-2 [10017:14540]; transmembrane protein 53‑B [15487:16608]; thiore ‑ 3.37 × 10 doxin [809:2978]; ap endonuclease [17694:20540]; alkylated DNA repair protein alkB homolog [21608:22713] –2 ADMH02000929 14323 G A retinal degeneration C protein [15781:45295] 3.76 × 10 P , False discovery rate-corrected P-value (Benjamini–Hochberg procedure) FDR Adjacent genes located in a maximum range of 10 kb, 5 kb upstream and downstream, are described. Gene start and end positions are represented as follows: [start: end] bioinformatics. MVNA, DPA and PEMR analyzed the data. All authors actively genes in response to overnight artificial light treatment in contributed to the interpretation of the findings. PEMR, MVNA and DPA wrote, Culex pipiens and timeout was observed in males. JEC and DG revised the manuscript. All authors approved the final manuscript. Funding Conclusion This research was funded by TDR/WHO (201460655) to DG. GC‑E was sup ‑ The genetic association related to the behavior of females ported by NIH/Fogarty International Center Global Infectious Diseases Training entering houses seems to be selection mediated by the Program (D43 TW007120). MVNA was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aper‑ use of indoor insecticides. On the other hand, genetic feiçoamento de Pessoal de Nível Superior (CAPES) 2018/07406‑6. JMV received control of the blood-seeking period could be an ecologi- funding from the National Institutes of Health, USA, International Centers for cal adaptation to host availability. Taken together, the Excellence in Malaria Research (U19AI089681). data presented here suggest that L-WGS with adequate Availability of data and materials processing represents a powerful tool to genetically char- Data are available at NCBI with the following BIOSAMPLE numbers: acterize vector populations at a microgeographic scale SAMN17015725 to SAMN17016048 and SAMN21386746 to SAMN21386784 as described in the Additional file 1: Table A. in malaria transmission areas, as well as for GWAS to disclose behavioral processes, such as the findings that Declarations females entering the houses to take a blood meal might be related to a specific CYP4H14 allele and that female Ethics approval and consent to participate time of blood-seeking is related to circadian rhythm Ethical review and approval were waived for this study because only the pro‑ fessionally trained authors conducted the human landing catches and the use genes. of this method to collect anopheline mosquitoes was considered to be a risk management issue, not a human subjects issue. All normal safety precautions Supplementary Information were taken. The authors (DPA, SMK, PRM and PEMR) involved in the human landing catches were fully informed about the details of the procedures, The online version contains supplementary material available at https:// doi. potential risks and mitigation plans, and were subject to checks by medical org/ 10. 1186/ s13071‑ 022‑ 05219‑5. doctors for 2 weeks after the collection. Additional file 1: Table A. List of statistically significant taxonomy identi‑ Consent for publication fications using BLAST and COI gene sequence as target. Individual sample Not applicable. data can be accessed using the BioSample accession code on NCBI. Competing interests The authors declare that they have no competing interests. Acknowledgements Not applicable. Author details 1 2 Sao Paulo State University (UNESP), Botucatu 18618‑689, Brazil. Nucleo Authors’ contributions de Medicina Tropical, Universidade de Brasília, Brasília, Brazil. 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Published: Mar 28, 2022
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