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Selective Sweep Analysis in the Genomes of the 91-R and 91-C Drosophila melanogaster Strains Reveals Few of the ‘Usual Suspects’ in Dichlorodiphenyltrichloroethane (DDT) Resistance

  • Laura D. Steele ,

    Affiliation Department of Entomology, University of Illinois, Urbana-Champaign, Illinois, United States of America

  • Brad Coates,

    Affiliation United States Department of Agriculture, Agricultural Research Service, Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, Iowa, United States of America

  • M. Carmen Valero,

    Affiliation Department of Entomology, University of Illinois, Urbana-Champaign, Illinois, United States of America

  • Weilin Sun,

    Affiliation Department of Entomology, University of Illinois, Urbana-Champaign, Illinois, United States of America

  • Keon Mook Seong,

    Affiliation Department of Entomology, University of Illinois, Urbana-Champaign, Illinois, United States of America

  • William M. Muir,

    Affiliation Department of Animal Sciences, Purdue University, West Lafayette, Indiana, United States of America

  • John M. Clark,

    Affiliation Department of Veterinary & Animal Science, University of Massachusetts, Amherst, Massachusetts, United States of America

  • Barry R. Pittendrigh

    Affiliation Department of Entomology, University of Illinois, Urbana-Champaign, Illinois, United States of America

Selective Sweep Analysis in the Genomes of the 91-R and 91-C Drosophila melanogaster Strains Reveals Few of the ‘Usual Suspects’ in Dichlorodiphenyltrichloroethane (DDT) Resistance

  • Laura D. Steele, 
  • Brad Coates, 
  • M. Carmen Valero, 
  • Weilin Sun, 
  • Keon Mook Seong, 
  • William M. Muir, 
  • John M. Clark, 
  • Barry R. Pittendrigh


Adaptation of insect phenotypes for survival after exposure to xenobiotics can result from selection at multiple loci with additive genetic effects. To the authors’ knowledge, no selective sweep analysis has been performed to identify such loci in highly dichlorodiphenyltrichloroethane (DDT) resistant insects. Here we compared a highly DDT resistant phenotype in the Drosophila melanogaster (Drosophila) 91-R strain to the DDT susceptible 91-C strain, both of common origin. Whole genome re-sequencing data from pools of individuals was generated separately for 91-R and 91-C, and mapped to the reference Drosophila genome assembly (v. 5.72). Thirteen major and three minor effect chromosome intervals with reduced nucleotide diversity (π) were identified only in the 91-R population. Estimates of Tajima's D (D) showed corresponding evidence of directional selection in these same genome regions of 91-R, however, no similar reductions in π or D estimates were detected in 91-C. An overabundance of non-synonymous proteins coding to synonymous changes were identified in putative open reading frames associated with 91-R. Except for NinaC and Cyp4g1, none of the identified genes were the ‘usual suspects’ previously observed to be associated with DDT resistance. Additionally, up-regulated ATP-binding cassette transporters have been previously associated with DDT resistance; however, here we identified a structurally altered MDR49 candidate resistance gene. The remaining fourteen genes have not previously been shown to be associated with DDT resistance. These results suggest hitherto unknown mechanisms of DDT resistance, most of which have been overlooked in previous transcriptional studies, with some genes having orthologs in mammals.


Dichlorodiphenyltrichloroethane (DDT) has gone from being a worldwide panacea of insect control and probably the most famous pesticide in modern history, to being a critical flashpoint of the modern environmental movement and becoming the most infamous pesticide of recent times. DDT was first used to control pest insect populations beginning in the 1940s, but instances of field resistance were observed among many species of insects, including Drosophila melanogaster (Drosophila) [1]. Subsequent deleterious side effects were observed in non-target mammalian and avian species, and were linked to the environmental persistence of this insecticide or its metabolites [25], ultimately leading to DDT being banned in most countries. However, DDT remains in industrial production due to its continued use for the control of mosquitoes that vector malaria; a niche where DDT is very effective [6].

DDT disrupts nervous system function in arthropods by affecting nerve cell plasma membrane permeability and causing paralysis [7]. Contrary to expectations, when selection pressures for DDT resistance were eliminated following bans on DDT use in many nations, the frequencies of resistance phenotypes remained high in many endemic pest insect populations. Persistence has been attributed to random genetic drift of alleles that have no fitness costs compared to susceptible counterparts [8]. Additionally, DDT resistance mechanisms can confer cross-resistance to pyrethroid [9, 10] and neonicotinoid insecticides [11], and may be a factor that contributes to maintenance of resistance alleles in the absence of a direct DDT selection [12].

The genetic basis of DDT resistance traits in the mosquito Anopheles gambiae involves the additive effects of two quantitative trait loci (QTL) [13]. Similarly, two QTL with major effects were mapped to the para sodium channel and the CCEunk7 esterase genes in Aedes aegypti, along with minor QTL that implicated the role of 20 other detoxification enzymes [14]. Additionally, a significant amount of research on DDT resistance in Drosophila has focused on metabolic resistance [11, 12, 1517].

DDT resistance in Drosophila is not a uniform phenotype, with varying levels of resistance observed across different Drosophila strains, and resistance can roughly be categorized into low-, medium- and high-level resistance [18]. Initial work on DDT by Crow [19] demonstrated the polygenic nature of DDT resistance, however, subsequent research singled out one low-level DDT resistant phenotype involving the Rst(2)DDT locus on chromosome two [20]. The chromosome region of Rst(2)DDT contains two cytochrome monooxygenease (P450) genes, Cyp6g1 and Cyp12d1, that are over expressed in at least some DDT resistant strains [18, 21]. Transcription of Cyp6g1 in DDT resistant Drosophila was up-regulated by an upstream insertion of the Accord transposon [22], and all subsequently described field resistant strains similarly show an over expression of Cyp6g1 due to this Accord insertion [12].

In contrast, DDT resistance among laboratory strains involves over expression of multiple P450 genes in addition to Cyp6g1 and Cyp12d1 [23, 24]. Specifically, the laboratory selected strain 91-R showed significant increases in expression of multiple cytochrome P450s and dozens of other genes. Furthermore, over expression of Cyp6g1 in transgenic Drosophila with a susceptible genetic background failed to reconstitute high levels of DDT resistance [25] and reinforced the hypothesis that DDT resistance may be a multilocus trait in this species [17, 26]. Indeed, a recent toxicokinetic analysis of 91-R revealed that oxidative P450s likely causes little direct metabolic resistance, but reduced cuticular penetration, increased reductive dechlorination, and enhanced excretion have been shown to play dominant roles [27].

With the advent of next generation sequencing (NGS) technologies, full-genome re-sequencing has become logistically feasible, and allows for ultra-fine resolution to map the genome location of mutations [28]. It is also a tool for genome-wide association studies (GWAS), population genomic [29] and phylogenomic studies [30]. GWAS using NGS-based re-sequencing approaches has been effectively applied to estimate genome variation within and between populations, and has identified genome regions that are associated with the expression of various traits [3133]. GWAS in Drosophila are feasible due to a high-quality genome sequence assembly, gene models and tools for genome-wide molecular analyses [5, 34, 35].

The laboratory selected DDT resistant and control strains 91-R and 91-C, respectively, represent lines that have a common origin, have been kept side-by-side in the laboratory, yet while 91-C received no DDT selection, 91-R received intense DDT selection pressure for over 50 years. Using these resource populations, whole genome re-sequencing data were generated from pools of individuals from the Drosophila strains 91-R and 91-C, and applied to detect chromosome regions putatively affected by prolonged DDT selection. To the authors’ knowledge, analysis across the entire insect genome to identify regions influenced by selective sweeps in highly DDT resistant insects has not been previously performed, although there has been a study focused on insecticide resistant blow flies (Lucilia cuprina) examining selective sweeps around an individual gene [36] and some additional studies looking at signatures of selection around transposable elements [37, 38]. We tested the hypothesis that the expected usual gene suspects for DDT resistance would be detected, as opposed to the alternative that resistance is polygenic with many other genes impacting resistance. Elucidating these genetic and biochemical mechanisms associated with pesticide resistance evolution might lead to improved pest management strategies. Equally important, such information has the potential to further our understanding of how DDT impacts biological processes that are evolutionarily conserved between insects and mammals.


Genome re-sequencing and data filtering

Read mapping with the Bowtie2 resulted in alignment of ≥ 98.5% of all 91-R and 91-C trimmed reads to the Drosophila reference genome release 5.7 resulted mean coverage depths of 63.6- and 62.0-X, respectively (S1 Table). The resulting mapping files were submitted to NCBI with an accession number SRP052046.

Detection of selective sweeps in 91-R by mapping Pool-seq data

Mean nucleotide diversity (π) and Tajima's D (D) estimates were made among major chromosome arms for mapped read data from strains 91-R and 91-C (Table 1). Both estimates were generally higher for 91-R compared to 91-C and were also ~10-fold lower on the X chromosome compared to autosomes (Table 1). The variation within sliding window estimates for π and D were also greater for 91-R compared to 91-C. Use of an arbitrary cutoff of a ≥ 100-fold reduction of π in a given 500-kb window compared to the mean π across the same chromosome resulted in the identification of 13 genome intervals in the 91-R genome (Fig 1A). Strong evidence for directional selection was not found on chromosomes X or 3L. Reduced nucleotide diversity was used as a proxy for the identification of genome regions, which potentially show the effects of a selective sweep, where the size of these 13 genome regions ranged from 0.1 to 0.9-Mbp (Table 2). A second tier cutoff of a ≥ 90- but < 100-fold reduction of π in a given 500-kb window was used to identify putative genome regions affected to a lesser degree following chronic DDT exposure in 91-R, and resulted in the identification of three additional genome intervals showing “minor” selective sweeps (Fig 1A). By comparison to estimates obtained across the genome of 91-C, the effects of random genetic drift, as opposed to directional selection, could possibly be accounted for on the 91-R genome. Decreases in the estimates of D along chromosome arms were also interpreted as being derived from the effects of directional selection in those corresponding genome regions. The calculated values of D along 500-kb windows of genomic sequence from 91-R indicated the effects of negative section were detected in 2L and 3R, and that these genome regions corresponded to those also predicted to show significant reductions in π described above. Similar to the estimates of π described above, there were no intervals on chromosomes X or 3L that showed significant reductions in estimates of D in the 91-R or 91-C genome. In contrast, the estimates of D did appear to mirror those of π along 2L, 2R and 3R in 91-R but not 91-C (Fig 1B).

Fig 1. Estimates of (A) nucleotide diversity (pi; π) and (B) Tajima's D (D) across the chromosome arms of Drosophila melanogaster from the DDT resistant 91-R strain (black line) and DDT susceptible 91-C strain (grey line).

Metrics obtained from 500-kb sliding windows with a step size of 100-kb. The genes identified to be associated with each of the major selection sweeps are as follows: (1) CG42329, (2) CG15394, (3) NinaC, (4) CG6453, (5) CG17568 and Ref(2)P, (6) RtGEF, (7) CG12050, CG8677, and Dtr, (8) CG31612, (9) Dscam1, (10) Sut1, (11) MDR49, (12) CG1041 and (13) CG31495. The genes identified to be associated with each of the minor selection sweeps are as follows: (A) Cyp4g1; (B) AlstR, Mnt and Fd3F; and (C) Kon.

Table 1. Mean nucleotide diversity (pi; π) and Tajima's D (D) among chromosome arms for DDT resistant 91-R and susceptible 91-C Drosophila melanogaster strains.

Table 2. Thirteen genomic intervals in Drosophila melanogaster strain 91-R (ID 1 to 13) with nucleotide diversity estimated reduced ≥ 100-fold compared to respective chromosome means, and indicate putative genome regions under directional selection for survival when exposed to DDT.

Identification and annotation of candidate genes in selective sweeps

The location of 67,835 91-R and 58,376 91-C single nucleotide polymorphisms (SNPs) were mapped to all gene-coding regions on chromosomes 2L, 2R and 3R (S2, S3 and S4 Tables). Mapping was not conducted on chromosomes X or 3L due to lack of selective sweeps detected on those chromosome regions. The genes in each nucleotide interval identified within selective sweeps from the 91-R genome were interrogated for further evidence of directional selection using excess of nucleotide mutations that cause amino acid changes. Specifically, the ratios of the rate non-synonymous to synonymous mutation (KA/KS) were calculated for gene in each selective sweep, and those with a KA/KS > 1 were considered candidates genes with evidence of DDT selection (S5 Table). Functional and mutant annotations for each gene were retrieved from using gene symbol in a keyword search and distribution of tissues in which transcripts for each gene have been previously identified were found in Derived protein sequences were obtained for all genes putatively involved in DDT resistance in 91-R (S6 Table), and when possible the functional domains were mapped with respect to the site of amino acid changes (S7 Table).


In the current study we used a whole genome approach to detect nucleotide signatures of directional selection in the 91-R population that resulted following chronic DDT exposure. Specifically, the effects of DDT selection on localized regions of the 91-R genome were measured by reductions in nucleotide diversity and corresponding estimates of directional selection using Tajima's D. The implication of individual genes in DDT resistance was obscured using this approach since genetic hitchhiking of flanking genes and genome regions occurs during selection due to limits on recombination to reduce the size of haplotype blocks [39, 40]. Thus, selective sweeps in 91-R have resulted in the near fixation of nucleotide sequence of the causal genetic factor(s) that are directly involved in the genes giving rise to this DDT resistant phenotype, as well as genes in proximity. It is important to note that some gene(s) located within some of the selective sweeps may appear associated with the resistant phenotype in 91-R, but may have been carried to fixation due to physical genetic linkage to gene(s) with major effect due to genetic hitchhiking.

Overall, genes within the 13 major (Fig 1 and S6 Table) and three minor effect regions (Fig 1 and S6 Table) identified in 91-R by selective sweeps do not correspond to the genes that have been previously associated with DDT resistance using gene expression analyses or identified in pesticide resistant Drosophila populations. The only exception is gene NinaC, which has predicted kinase activity related to sensory transduction/vision, and is over-expressed in DDT resistant strains [26]. Similarly, four of the genes located in genome regions of 91-R affected by selective sweeps, Dscam1, Dtr, RtGEF, and CG6453, have previously been implicated in synaptic development and/or function [4144]. Additionally, the candidate genes of 91-R affected by selective sweeps may also be involved in regulation of cellular growth (CG6453) [44], as well as genes that are involved in cellular communication and signal transduction cascades (S4 Table). Although implication of these mutant alleles in DDT resistance can be rationalized, additional functional studies are required to deduce individual roles as well as the effects of the non-synonymous changes in 91-R on subsequent protein function and resulting phenotype. Additionally, the nucleotide diversity (pi; π) and D in the sliding window figure indicated that the control (91-C) strain showed no evidence for reduced variation or coding sequences (CDS) selection, in that sliding windows are fairly uniform across the chromosome—with exception of certain regions likely representing those near centromeres.

The genes CG17568, ref(2)P, CG8677, and CG31612 located in selective sweeps five, seven and eight, respectively, contain Zn-finger DNA binding motifs, which could suggest the resultant proteins have potential roles as transcription factors. Since trans-regulatory control of transcription by soluble transcription factors often occurs at cis-promoter or enhancer elements by way of Zn-finger mediated protein-DNA interactions, mutations in transcription factors that affect DNA-protein or protein-protein interactions at the promoter or with enhancer elements can cause changes in expression at physically unlinked genes. Therefore, genes in an interconnected gene regulatory pathway may show a coordinated response to transcription factor mutations. It is conceivable (but speculative) that the mutant transcription factor alleles in 91-R might be involved in the gene regulatory networks which lead to up-regulation of the transcripts in 91-R described by Pedra et al. [17], a hypothesis that remains to be tested. In a broader context, the basal cause of apparent incongruent results obtained from gene expression and genetic mapping/phylogenomic studies may be rooted in the effect that genes in QTL intervals/selective sweeps have upon gene networks. This hypothesis might also suggest that system approaches may yield greater insight into the genetic and genomic basis of insecticide resistance traits.

In the three genome regions showing less major effects of selection at a ≥ 90-fold reduction in nucleotide diversity cutoff, (A, B and C in Fig 1 and S2 Table), the candidate genes were associated with the nervous system and only one was a P450, Cyp4g1. The Cyp4g1 protein is known to be associated with hydrocarbon production, converting long-chained aldehydes to long-chained hydrocarbons in oenocytes in the epidermis of Drosophila, that are then in turn transported to the waxy layer of the epicuticle [45]. Additionally, Strycharz et al. [27] recently demonstrated that 91-R had higher quantities of cuticular hydrocarbons, visible changes in the cuticle (via electron microscopy), and that reduced penetration is an important component of DDT resistance in 91-R. Although work by Waters et al. [46] suggested no difference in expression levels of Cyp4g1 between 91-C and 91-R, it is not currently known if differential expression of the Cyp4g1 protein might be localized near the cuticle of the insect or if structural changes in Cyp4g1 may play some role in resistance.

Although ATP-binding cassette (ABC) transporters have previously been associated with DDT resistance in Drosophila, the selective sweeps analysis has shed new light on an additional candidate DDT resistance gene known as MDR49. Strycharz et al. [27] previously compared the transcription levels of the ATP-binding cassette transporters MDR49, MDR50 and MDR65 and MRP1 in 91-R versus Canton-S strains. Interestingly, MDR50, MDR65 and MRP1 were over-expressed in 91-R whereas MDR49 was not. RNAi knockdown of MDR50, MDR65 and MRP1 in DDT resistant flies results in increased sensitivity to DDT, however, knockdown of MDR49 had no effect [47]. Such aforementioned experimental approaches would only detect the putative role of differential transcription in DDT resistance and not structural changes in the protein that may lead to DDT resistance. Thus, the amino changes that we observed in MDR49 that may play a role in DDT resistance, if any, remain to be determined.

The other genes co-occurring with selective sweeps included: Dscam1, NinaC, CG6453, CG17568, Ref(2)P, RtGEF, CG12050, CG8677, Dtr, CG31612, Sut1, CG1041, and CG31495. Several of these aforementioned genes located within the identified selective sweeps contain known or suspected orthologs in other animals, including mammals, which could be useful in further investigation to better understand their potential links to DDT resistance. For example, some of these genes show plausible linkages to phenotypic resistance to DDT, however, based on their roles in mammals in biological processes known to be impacted by DDT exposure. For example, Dscam1 is associated with psychomotor retardation, and DDT (or more specifically the DDE byproduct) has been linked with retarded psychomotor development in humans exposed in the first trimester [48, 49]. NinaC is a retinal specific gene that codes for two photoreceptor cell specific proteins in Drosophila [50, 51], and mutations in NinaC were shown to cause light- and age-dependent retinal degeneration in Drosophila [51]. In human studies, Kamel et al. [52] found a dose-response relationship between exposure to organochlorides, such as DDT, and the risk of retinal degeneration. Male sterility in Drosophila results when Ref(2)P gene expression is absent in the testes, which suggested that the Ref(2)P gene expression is required for successful reproduction [53]. Although a somewhat controversial topic in the literature, there have been studies indicating that environmental pollutants (such as DDT) have links to male infertility [54, 55] in both humans [54] and rats [55]. The role these genes may play in high level DDT resistance remains to be determined. Additionally, it remains to be determined if some of these evolutionarily conserved, between insects and mammals, candidate genes may also provide insights into the impact of DDT exposure in mammalian systems, as has been done previously using Drosophila and human diseases [5660].

Interestingly, we did not observe many of the genes typically associated with pesticide resistance [19, 6165, 6876]. Many initial publications reported that moderate to high level DDT resistance is thought to be polygenic with multiple genome regions contributing to this phenotype [19, 63, 64]. Previous researchers have identified loci on the second chromosome involved in DDT resistance [20, 65], whereas chromosomes X and three are thought to have some slight impact on the DDT resistance phenotype [64, 65]. The uniform reduction in estimates of π across the X-chromosome of 91-C and 91-C, were not surprising due to the effective 3/4 population size of the X-chromosome as compared to autosomes [66], which affects the rate at which chromosomal loci may become fixed by random genetic drift or influenced by selection [77]. The affects of random fixation by random genetic drift on the X-chromosome may also have been exacerbated by the relatively small number of individuals in 91-C and 91-R laboratory populations [67]. An increasing amount of research has focused on the single Rst(2)DDT locus [20, 6871], whereby over-transcription of the cytochrome P450 Cyp6g1 located within the Rst(2)DDT region was suggested to be both necessary and sufficient for DDT resistance [25]. Daborn et al. [25] essentially proposed that resistance to DDT was monogenic, at least in Drosophila strains with low-level DDT resistance. The Rst(2)DDT locus maps to the second chromosome between the genes cinnabar (cn; location 2R:3,670,302–3,672,711) and vestigial (vg; 2R:8,772,137–8,786,890) [11, 21, 72, 73]. Although our current dataset is not from a low-level resistant strain, this genome interval in 91-R where Cyp6g1 exists is located between, and not within, the 91-R selective sweeps labeled 9 and 10 (Fig 1). Interestingly Cyp6g1 is over-expressed in the 91-R strain [17, 21, 78]. Thus, our analysis suggests that Rst(2)DDT is not a major factor, or potentially even involved, in the DDT resistance phenotype in 91-R, and agrees with prior results which showed that DDT resistance could be maintained in Drosophila strains that did not show high Cyp6g1 transcript levels derived from at the Rst(2)DDT locus [74]. The current results are also in agreement with the conclusion by Strycharz et al. [27] that metabolic resistance, particularly P450-based resistance, plays a negligible role in the overall DDT resistance phenotype in 91-R. In addition to Cyp6g1, expression of Cyp12d1 was implicated in being differentially expressed in DDT-resistant fly strains [18] as were non-synonymous coding sequence mutations Cyp6a2 [75] and para [76]. However, none of these genes occurred in any of the selective sweeps identified in our current experiments.

DDT resistance, however, is not a single phenotype, but varies among strains from low- (e.g., Hikone-R), to moderate- (e.g., Wisconsin), to high-levels (e.g., 91-R) [18]. Based on microarray analysis, moderate- to high-level resistant phenotypes appeared to result from the effect of multiple differentially-regulated genes. Specifically, using microarray data, Pedra et al. [17] observed that numerous genes were over-transcribed in the 91-R strain including cytochrome P450s, glutahione S transferases, and a set of additional genes. Comparative analysis of microarray data from the Wisconsin and 91-R strains showed that multiple genes were differentially expressed, and that these genes were more numerous in the more highly resistant strain than the moderately resistant strain [17, 79]. A proteomic analysis also revealed that proteins associated with energy metabolism were differentially expressed in two DDT resistant as compared with a susceptible strain [26]. These combined observations suggest that at least moderate- to high-level DDT resistance may involve complex molecular interactions, and this might be consistent with a resistant phenotype that results from the effects of multiple genes. These results also suggest that several different genetic mechanisms may result in DDT resistant phenotypes, and that increasing levels of DDT resistance may be additive with an increasing number of genes involved, a hypothesis that remains to be tested. However, these results do not rule out the fact that low-level DDT resistant strains, taken directly from the field, may have fewer, i.e., monogenic, molecular mechanisms of resistance such as overly transcribed Cyp6g1 [78].

Certainly, the current data and analysis could be of potential importance to those insecticides where DDT resistance has been shown to confer cross-resistance to other types of insecticides, such as imidacloprid in Drosophila and pyrethroids in A. aegypti [11, 80]. Of greater practical importance, however, this general GWAS approach could be applied to other insect species currently being controlled by other pesticides, in order to understand the evolution of resistance in “real time” (i.e., follow field populations through generations of selection). A number of other insect genomes have been sequenced since the Drosophila genome was published in 2000 and has allowed for the study of insecticide resistance at the molecular level for a variety of species, such as in Anopheles gambiae [34, 81]. Although the 91-C and 91-R fly lines provide a unique system where selection has occurred for over half a century, there exist multiple Aedes aegypti laboratory strains, including strains selected for insecticide resistance to permethrin, where similar studies could be performed to identify structural mutations across the genome [82].

The discoveries of novel resistance mechanisms from such studies could help lead to new target genes and the development of novel control methods for these resistant species [83, 84]. This work also highlights that selection with DDT may result in the selection for novel mutations, potentially with some or many of these being associated with or directly involved in DDT resistance. Additional studies are required to validate the role of genes in each predicted selective sweep in DDT resistance by verifying the functional consequence of amino acid changes on protein structures and potential impact on the 91-R resistant phenotype. Of greatest importance, this study highlights the need for selective sweep analyses in pesticide resistant insect populations in order to identify potential candidate resistance traits. Further molecular examination of individual genes and a more detailed analysis of the specific effects of the structural changes within the insects are crucial to better understanding resistance, something beyond the scope of the current project.

Materials and Methods

Genome re-sequencing and data filtering

Dr. Ranjan Ganguly of the University of Tennessee-Knoxville provided the DDT resistant and susceptible Drosophila strains, respectively 91-R and 91-C [85]. For detailed description of fly line maintenance, re-sequencing, and data filtering, please see Steele et al. [86].

Detection of selective sweeps in 91R by mapping Pool-seq data

Estimates of nucleotide diversity.

A pooled sequencing approach (Pool-seq) was used to compare the nucleotide variance at all positions across the Drosophila strains 91-C and 91-R genomes, with the goal of identifying putative regions of reduced nucleotide diversity in 91-R that putatively correspond to regions affected by directional selection (selective sweeps) [87, 88]. To accomplish this, quality score trimmed reads from 91-R and 91-C libraries were aligned separately to the Drosophila genome assembly release 5.7 (file dmel-all-chromosomee-r5.7.fasta downloaded from using Bowtie2 with parameters-l 100-n 0.01-o 2-e 12-d 12 [89]. Bowtie2 output in SAM format was converted to a sorted BAM file and synchronized with the SamTools mpileup command [90]. The BAM files have been deposited at NCBI with accession number of SRP052046. Nucleotide diversity (π) estimates were calculated across the alignments for 91-C and 91-R data in 500-kb sliding windows with a step size of 100 kb using the Perl script from the PoPoolation Package [91] with a minimum coverage = 2, maximum coverage = 75, and minimum quality = 25. The maximum coverage was restricted to 2-times the mean read depth to reduce the incidence of SNP detection within repetitive DNAs. Windows where genome regions lacked any SNPs were reported as "na", and were counted as missing data such that gaps were present in the resulting plots. Regions of the genome with evidence of putative selective sweeps were identified using an arbitrary cutoff of a π 100-fold reduction of π within a window compared to the mean π across the same chromosome. Mapping data to the Y chromosome, mitochondrial genome and chromosome four were excluded from analyses.

Estimates of Tajima's D.

Tajima's D (D) estimates were independently obtained for alignments of 91-R and 91-C reads using the script from the PoPoolation Package [91] using parameters identical to those used to estimate π, except a uniform coverage of 30 was used to account for heterogeneous expectations of D since the measure is dependent upon the number of chromosomes (coverage depth). The D estimates provided by PoPoolation do not take into account the potential of multiple sampling, thus a negative bias is likely among resulting output but was expected to be equally represented across the genome such that general inferences of the effects of directional and balancing selection in genome regions could be made [92]. Resulting estimates of D for 91-R and 91-C were plotted along the lengths of each chromosome arm. Gene-by-gene estimates of D were also made using the script (measure = D), with the file Drosophila_melanogaster_BDGP5.72.gtf used to define gene coding intervals. Sampling of the data also used a uniform depth of 30 across each gene.

Identification and annotation of candidate genes in selective sweeps

Genes in genome intervals with reduced estimates of π and D were considered candidate DDT resistance genes, but the pools were narrowed using an N/π S cutoff > 1.0. Specifically, nucleotide diversity at synonymous (πS) and nonsynonymous codon positions (πN) was estimated for all genes in 91-C and 91-R alignment data using the Perl script (measure = pi), where gene coding positions were defined in the file Drosophila_melanogaster_BDGP5.72.gtf ( SNPs predicted with a minimum count of 4, minimum coverage of 8, and a maximum coverage of 75 for both 91-C and 91-R datasets. Gene coding regions that lacked synonymous and/or non-synonymous mutations were excluded from subsequent calculations of πN/ πS, and the ratio was used to predict genes with an excess of non-synonymous site mutation (πN/ πS > 1.0).

Instances in each putative selective sweep where alleles had become fixed in strain 91-R but remained variable in the 91-C genome were identified manually. Functional gene annotation data were retrieved for candidate genes from FlyBase ( using a keyword search gene symbol. Derived protein coding sequences were constructed using predicted non-synonymous mutation predictions made from 91-R and 91-C SNP data, and used as a query against the NCBI nr protein database using the blastp algorithm (hit cutoff set for E-values ≤ 10–20). Conserved functional protein domains were identified by searches against the Conserved Domain Database (CDD) [93], and used to annotate the derived proteins from candidate DDT resistance genes from 91-R. These variable amino acids positions in 91-R were plotted with respect to protein functional domains (when known).

Supporting Information

S1 Table. Mapping statistics for Drosophila melanogaster 91-R and 91-C specific read libraries to the reference genome release 5.7 using Bowtie2 [89].

All reads reported in millions.


S2 Table. Locations of those 67,835 91-R and 58,376 91-C single nucleotide polymorphisms (SNPs), located on chromosome 2L, mapped to all gene-coding regions on the chromosome.


S3 Table. Locations of those 67,835 91-R and 58,376 91-C single nucleotide polymorphisms (SNPs), located on chromosome 2R, mapped to all gene-coding regions on the chromosome.


S4 Table. Locations of those 67,835 91-R and 58,376 91-C single nucleotide polymorphisms (SNPs), located on chromosome 3R, mapped to all gene-coding regions on the chromosome.


S5 Table. Genes in the genome of the Drosophila melanogaster 91-R strain that are within regions putatively affected to a lesser extent by selective sweeps caused by fixation of DDT resistant traits (please see Fig 1).

Expression in adult head (hd), brain (br), malpigian tubules (mt), central nervous system (cns) and embryonic tissues (emb) are shown as indicated in These genome regions did not surpass the arbitrary cutoff of 100-fold reductions in nucleotide diversity, but did shown an estimated ≥90-fold decreases when compared to the average across respective chromosomes.


S6 Table. Genes in the genome of the Drosophila melanogaster 91-R strain that are within regions putatively affected by selective sweeps caused by fixation of DDT resistant traits (please see Fig 1).

Expression in adult head (hd), brain (br), malpigian tubules (mt), central nervous system (cns) and reproductive tissues (rt; testis and/or ovaries) are shown as indicated in


S7 Table. Non-synonymous nucleotide and associated amino acid changes in candidate genes identified within thirteen major genome regions in the 91-R Drosophila melanogaster strain showing influence of a selective sweep.



The authors wish to thank Dr. Ranjan Ganguly at the University of Tennessee-Knoxville for providing strains 91-R and 91-C material.

Author Contributions

Conceived and designed the experiments: LDS WS WMM BRP. Performed the experiments: LDS WS. Analyzed the data: LDS BC MCV KMS WMM JMC BRP. Contributed reagents/materials/analysis tools: LDS BC MCV WS KMS WMM JMC BRP. Wrote the paper: LDS BC MCV WS MKS WMM JMC BRP.


  1. 1. Busvine JR. DDT-resistance in Drosophila melanogaster. Bull World Health Organ. 1957;16(1): 206–208. pmid:20604010
  2. 2. Greenberg DS. Pesticides: white house advisory body issues report recommending steps to reduce hazard to public. Science. 1963;140(3569): 878–879. pmid:17810673
  3. 3. Jaga K, Dharmani C. Global surveillance of DDT and DDE levels in human tissues. Int J Occup Med Environ Health. 2003;16(1): 7–20. pmid:12705713
  4. 4. Conis E. Debating the health effects of DDT: Thomas Jukes, Charles Wurster, and the fate of an environmental pollutant. Public Health Rep. 2010;125(2): 337–342. pmid:20297762
  5. 5. Perry T, Batterham P, Daborn PJ. The biology of insecticidal activity and resistance. Insect Biochem Mol Biol. 2011;41(7): 411–422. pmid:21426939
  6. 6. Feachem RG, Sabot OJ. Global malaria control in the 21st century: A historic but fleeting opportunity. JAMA. 2007;297(20): 2281–2284. pmid:17519417
  7. 7. Barnola FV, Camejo G, Villegas R. Ionic channels and nerve membrane lipoproteins: DDT-nerve membrane interaction. Int J Neurosci. 1971;1(5): 309–316. pmid:5161766
  8. 8. McCart C, Buckling A, ffrench-Constant R. DDT resistance in flies carries no cost. Curr Biol. 2005;15(15): R587–9. pmid:16085476
  9. 9. Prasittisuk C, Busvine JR. DDT-resistant mosquito strains with cross-resistance to pyrethroids. Pest Manag Sci. 1977;8(5): 527–533.
  10. 10. Scott JG, Matsumura F. Characteristics of a DDT-induced case of cross-resistance to permethrin in Blattella germanica. Pest Biochem Physiol 1981;16(1): 21–27.
  11. 11. Daborn P, Boundy S, Yen J, Pittendrigh B, ffrench-Constant R. DDT resistance in Drosophila correlates with Cyp6g1 over-expression and confers cross-resistance to the neonicotinoid imidacloprid. Mol Genet Genomics. 2001;266(4): 556–563. pmid:11810226
  12. 12. Catania F, Kauer MO, Daborn PJ, Yen L, ffrench-Constant RH, Schlötterer C. World-wide survey of an Accord insertion and its association with DDT resistance in Drosophila melanogaster. Mol Ecol. 2004;13(8): 2491–2504. pmid:15245421
  13. 13. Ranson H, Jensen B, Wang X, Prapanthadara L, Hemingway J, Collins FH. Genetic mapping of two loci affecting DDT resistance in the malaria vector Anopheles gambiae. Insect Mol Biol. 2000;9(5): 499–507. pmid:11029668
  14. 14. Saavedra-Rodriguez K, Strode C, Suarez AF, Salas IF, Ranson H, Hemingway J, et al. Quantitative trait loci mapping of genome regions controlling permethrin resistance in the mosquito Aedes aegypti. Genetics. 2008;180(2): 1137–1152. pmid:18723882
  15. 15. Feyereisen R. Insect P450 enzymes. Annu Rev Entomol. 1999;44: 507–533. pmid:9990722
  16. 16. Feyereisen R. Insect cytochrome P450. In: Gilbert LI, Iatrou K, Gill SS, editors. Comprehensive Molecular Insect Science. Elsevier, Oxford; 2005. pp 1–77.
  17. 17. Pedra JH, McIntyre LM, Scharf ME, Pittendrigh BR. Genome-wide transcription profile of field- and laboratory-selected dichlorodiphenyltrichloroethane (DDT)-resistant Drosophila. Proc Natl Acad Sci U S A. 2004;101(18): 7034–7039. pmid:15118106
  18. 18. Festucci-Buselli RA, Carvalho-Dias AS, de Oliveira-Andrade M, Caixeta-Nunes C, Li H-M, Stuart JJ, et al. Expression of Cyp6g1 and Cyp12d1 in DDT resistant and susceptible strains of Drosophila melanogaster. Insect Mol Biol. 2005;14(1): 69–77. pmid:15663776
  19. 19. Crow JF. Analysis of a DDT-Resistant Strain of Drosophila. J Econ Entomol. 1954;47(3): 393–398.
  20. 20. Dapkus D. Genetic localization of DDT resistance in Drosophila melanogaster (Dipetera: Drosophilidae). J Econ Entomol. 1992;85(2): 340–347. pmid:1593009
  21. 21. Brandt A, Scharf M, Pedra JHF, Holmes G, Dean A, Kreitman M, et al. Differential expression and induction of two Drosophila cytochrome P450 genes near the Rst(2)DDT locus. Insect Mol Biol. 2002;11(4): 337–341. pmid:12144699
  22. 22. Schlenke TA, Begun DJ. Strong selective sweep associated with a transposon insertion in Drosophila simulans. Proc Natl Acad Sci U S A. 2004;101(6): 1626–1631. pmid:14745026
  23. 23. Le Goff G, Soundy S, Daborn PJ, Yen JL, Sofer L, Lind R, et al. Microarray analysis of cytochrome P450 mediated insecticide resistance in Drosophila. Insect Biochem Mol Biol. 2003;33(7): 701–708. pmid:12826097
  24. 24. Bergé JB, Feyereisen R, Amichot M. Cytochrome P450 monooxygenases and insecticide resistance in insects. Philos Trans R Soc Lond B Biol Sci. 1998;353(1376): 1701–1705. pmid:10021770
  25. 25. Daborn PJ, Yen JL, Bogwitz MR, Le Goff G, Feil E, Jeffers S, et al. A single p450 allele associated with insecticide resistance in Drosophila. Science. 2002;297(5590): 2253–2256. pmid:12351787
  26. 26. Pedra JH, Festucci-Buselli RA, Sun W, Muir WM, Scharf ME, Pittendrigh BR. Profiling of abundant proteins associated with dichlorodiphenyltrichloroethane resistance in Drosophila melanogaster. Proteomics. 2005;5(1): 258–269. pmid:15619295
  27. 27. Strycharz JP, Lao A, Li H, Qiu X, Lee SH, Sun W, et al. Resistance in the highly DDT-resistant 91-R strain of Drosophila melanogaster involves decreased penetration, increased metabolism, and direct excretion. Pest Biochem Physiol. 2013;107(2): 207–217.
  28. 28. Linheiro RS, Bergman CM. Whole genome resequencing reveals natural target site preferences of transposable elements in Drosophila melanogater. PLoS ONE. 2012;7(2): e30008. pmid:22347367
  29. 29. Sackton TB, Kulathinal RJ, Bergman CM, Quinlan AR, Dopman EB, Carneiro M, et al. Population genomic inference from sparse high-throughput sequencing of two populations of Drosophila melanogaster. Genome Biol Evol. 2009;1: 449–465. pmid:20333214
  30. 30. Yang Y, Hou Z-C, Qian Y-H, Kang H, Zeng Q-T. Increasing the data size to accurately reconstruct the phylogenetic relationships between nine subgroups of the Drosophila melanogaster species group (Drosophilidae, Diptera). Mol Phylogenet Evol. 2011;62(1): 214–223. pmid:21985965
  31. 31. Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, Flint-Garcia S, et al. Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat Genet. 2011;43(2): 159–162. pmid:21217756
  32. 32. Branca A, Paape TD, Zhou P, Briskine R, Farmer AD, Mudge J, et al. Whole genome nucleotide diversity, recombination, and linkage disequilibrium in the legume Medicago truncatula. Proc Natl Acad Sci U S A. 2012;108(42): E864–70. pmid:21949378
  33. 33. Bastide H, Betancourt A, Nolte V, Tobler R, Stöbe P, Futschik A, et al. A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster. PLoS Genet. 2013;9(6): e1003534. pmid:23754958
  34. 34. Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, Amanatides PG, et al. The genome sequence of Drosophila melanogaster. Science. 2000;287(5461): 2185–2195. pmid:10731132
  35. 35. Langley CH, Stevens K, Cardeno C, Lee YC, Schrider DR, Poll JE, et al. Genomic variation in natural populations of Drosophila melanogaster. Genetics. 2012;192: 533–98. pmid:22673804
  36. 36. Rose CJ, Chapman JR, Marshall SDG, Lee SF, Batterham P, Ross HA, et al. Selective Sweeps at the Organophosphorus Insecticide Resistance Locus, Rop-1, Have Affected Variation across and beyond the α-Esterase Gene Cluster in the Australian Sheep Blowfly, Lucilia cuprina. Mol Biol Evol. 2011;28(6): 1835–1846. pmid:21228400
  37. 37. Schlenke TA, Begun DJ. Strong selective sweep associated with a transposon insertion in Drosophila simulans. Proc Natl Acad Sci U S A. 2004;101(6): 1626–1631. pmid:14745026
  38. 38. Wilding CS, Smith I, Lynd A, Yawson AE, Weetman D, Paine MJI, et al. A cis-regulatory sequence driving metabolic insecticide resistance in mosquitoes: Functional characterization and signatures of selection. Insect Biochem Mol Biol. 2012;42(9): 699–707. pmid:22732326
  39. 39. Kojima K-I, Schaffer HE. Survival process of linked mutant genes. Evolution. 1967;21(3): 518–531.
  40. 40. Smith JM, Haigh J. The hitch-hiking effect of a favourable gene. Genet Res. 1974;23(1): 23–35. pmid:4407212
  41. 41. Parnas D, Haghighi AP, Fetter RD, Kim SW, Goodman CS. Regulation of postsynaptic structure and protein localization by the Rho-type guanine nucleotide exchange factor dPix. Neuron. 2001;32(3): 415–424. pmid:11709153
  42. 42. Gengs C, Leung H-T, Skingsley DR, Iovchev MI, Yin Z, Semenov EP, et al. The target of Drosophila photoreceptor synaptic transmission is a histamine-gated chloride channel encoded by ort (hclA). J Biol Chem. 2002;277(44): 42113–42120. pmid:12196539
  43. 43. Sawaya MR, Wojtowicz WM, Andre I, Qian B, Wu W, Baker D, et al. A double S shape provides the structural basis for the extraordinary binding specificity of Dscam isoforms. Cell. 2008;134(6): 1007–1018. pmid:18805093
  44. 44. Mummery-Widmer JL, Yamazaki M, Stoeger T, Novatchkova M, Bhalerao S, Chen D, et al. Genome-wide analysis of Notch signaling in Drosophila by transgenic RNAi. Nature. 2009;458(7241): 987–992. pmid:19363474
  45. 45. Qiu Y, Tittiger C, Wicker-Thomas C, Le Goff G, Young S, Wajnberg E, et al. An insect-specific P450 oxidative decarbonylase for cuticular hydrocarbon biosynthesis. Proc Natl Acad Sci U S A. 2012;109(37): 14858–14863. pmid:22927409
  46. 46. Waters LC, Zelhof AC, Shaw BJ, Ch’ang LY. Possible involvement of the long terminal repeat of transposable element 17.6 in regulating expression of an insecticide resistance-associated P450 gene in Drosophila. Proc Natl Acad Sci U S A. 1992;89(11): 4855–4859. pmid:1317576
  47. 47. Strycharz JP, Lee SH, Sun W, Pittendrigh BR, Clark JM. RNAi knockdown of ABC transporters causes decreased tolerance in highly DDT-resistant 91-R strain of Drosophila melanogaster. In: Picogram: Abstract Book. ACS/AGRO. 2010. 78(182): pp. 116.
  48. 48. Ribas-Fitó N, Torrent M, Carrizo D, Muños-Ortiz L, Júlvez J, Grimalt JO, et al. In Utero Exposure to Background Concentrations of DDT and Cognitive Functioning among Preschoolers. Am J Epidemiol. 2006;164: 955–962. pmid:16968864
  49. 49. Torres-Sánchez L, Rothenberg SJ, Schnaas L, Cebrian ME, Osorio E, Hernández MDC, et al. In Utero p,p’-DDE Exposure and Infant Neurodevelopment:A Perinatal Cohort in Mexico. Environ Health Perspect. 2007;115(3): 435–439. pmid:17431495
  50. 50. Montell C, Rubin GM. The Drosophila ninaC Locus Encodes Two Photoreceptor Cell Specific Proteins with Domains Homologous to Protein Kinases and the Myosin Heavy Chain Head. Cell. 1988;52: 757–772. pmid:2449973
  51. 51. Porter JA, Hicks JL, Williams DS, Montell C. Differential Localizations of and Requirements for the Two Drosophila ninaC Kinase/Myosins in Photoreceptor Cells. J Cell Biol. 1992;116(3): 683–693. pmid:1730774
  52. 52. Kamel F, Boyes WK, Gladen BC, Rowland AS, Alavanja MCR, Blair A, et al. Retinal Degeneration in Licensed Pesticide Applicators. Am J Ind Med. 2000;37: 618–628. pmid:10797505
  53. 53. Dezelee S, Bras F, Contamine D, Lopez-Ferber M, Segretain D, Teninges D. Molecular analysis of ref(2)P, a Drosophila gene implicated in sigma rhabdovirus multiplication and necessary for male fertility. The EMBO Journal. 1989;8(11): 3437–3446. pmid:2510997
  54. 54. Pant N, Kumar R, Mathur N, Srivastava SP, Saxena DK, Gujrati VR. Chlorinated pesticide concentration in semen of fertile and infertile men and correlation with sperm quality. Environ Toxicol Pharmacol. 2007;23: 135–139. pmid:21783749
  55. 55. Rhouma KB, Tébourbi O, Krichah R, Sakly M. Reproductive toxicity of DDT in adult male rats. Hum Exp Toxicol. 2001;20: 393–397. pmid:11727789
  56. 56. Blow NS, Salomon RN, Garrity K, Reveillaud I, Kopin A, Jackson FR, et al. Vibrio cholerae Infection of Drosophila melanogaster Mimics the Human Disease Cholera. PloS Pathogens. 2005;1(1): e8. pmid:16201020
  57. 57. Gonzalez C. Drosophila melanogaster: a model and a tool to investigate malignancy and identify new therapeutics. Nature Reviews. 2013;13:172–183. pmid:23388617
  58. 58. Jeibmann A, Paulus W. Drosophila melanogaster as a Model Organism of Brain Diseases. Int J Mol Sci. 2009;10: 407–440. pmid:19333415
  59. 59. Rea SL, Graham BH, Nakamaru-Ogiso E, Kar A, Falk MJ. Bacteria, Yeast, Worms, and Flies: Exploiting Simple Model Organisms to Investigate Human Mitochondrial Diseases. Developmental Disabilities Research Reviews. 2010;16: 200–218. pmid:20818735
  60. 60. Bier E. Drosophila, The Golden Bug, Emerges as a Tool for Human Genetics. Nature Reviews. 2005;6: 9–23. pmid:15688063
  61. 61. Labbé P, Berticat C, Berthomieu A, Unal S, Bernard C, Weill M, et al. Forty years of erratic insecticide resistance evolution in the mosquito Culex pipiens. PLoS Genet. 2007;3(11): e205. pmid:18020711
  62. 62. Hemingway J, Field L, Vontas J. An overview of insecticide resistance. Science. 2002;298(5591): 96–97. pmid:12364782
  63. 63. King JC. The genetics of resistance to DDT in Drosophila melanogaster. J Econ Entomol. 1954;47(3): 387–393.
  64. 64. Dapkus D, Merrell DJ. Chromosomal analysis of DDT-resistance in a long-term selected population of Drosophila melanogaster. Genetics. 1977;87(4): 685–697. pmid:414959
  65. 65. Shepanski MC, Kuhr RJ, Glover TJ. Resistance of Drosophila melanogaster to DDT. J Econ Entomol. 1977;70(5): 539–543. pmid:410854
  66. 66. Wright S. Evolution in Mendelian populations. Genetics. 1931;16(2): 97–159. pmid:17246615
  67. 67. Crow JF, Morton NE. Measurement of gene frequency drift in small populations. Evolution. 1955;9(2): 202–214.
  68. 68. Walters LC, Zelhof AC, Shaw BJ, Ch’ang LY. Possible involvement of the long terminal repeat of transposable element 17.6 in regulating expression of an insecticide resistance-associated P450 gene in Drosophila. Proc Natl Acad Sci U S A. 1992;89(11): 4855–4859. pmid:1317576
  69. 69. Delpuech JM, Aquadro CF, Roush RT. Noninvolvement of the long terminal repeat of transposable element 17.6 in insecticide resistant in Drosophila. Proc Natl Acad Sci U S A. 1993;90(12): 5643–5647. pmid:8390673
  70. 70. Maitra S, Dombrowski SM, Waters LC, Ganguly R. Three second chromosome-linked clustered Cyp6 genes show differential constitutive and barbital-induced expression in DDT-resistant and susceptible strains of Drosophila melanogaster. Gene. 1996;180(1–2): 165–171. pmid:8973368
  71. 71. Brun A, Cuany A, Le Mouel T, Berge J, Amichot M. Inducibility of the Drosophila melanogaster cytochrome P450 gene, CYP6A2, by phenobarbital in insecticide susceptible or resistant strains. Insect Biochem Mol Biol. 1996;26(7): 697–703. pmid:8995791
  72. 72. Hällström I, Blanck A. Genetic regulation of the cytochrome P-450 system in Drosophila melanogaster. I. Chromosomal determination of some cytochrome P-450-dependent reactions. Chem Biol Interact. 1985;56(2–3): 157–171. pmid:4075453
  73. 73. Hällström I. Genetic regulation of the cytochrome P-450 system in Drosophila melanogaster. II. Localization of some genes regulating cytochrome P-450 activity. Chem Biol Interact. 1985;56(2–3): 173–184. pmid:4075453
  74. 74. Kuruganti S, Lam V, Zhou X, Bennett G, Pittendrigh BR, Ganguly R. High expression of Cyp6g1, a cytochrome P450 gene, does not necessarily confer DDT resistance in Drosophila melanogaster. Gene. 2007;388(1–2): 43–53. pmid:17157448
  75. 75. Amichot M, Tarès S, Brun-Barale A, Arthaud L, Bride J-M, Bergé J-B. Point mutations associated with insecticide resistance in the Drosophila cytochrome P450 Cyp6a2 enable DDT metabolism. Eur J Biochem. 2004;271(7): 1250–1257. pmid:15030474
  76. 76. Pittendrigh B, Reenan R, ffrench-Constant RH, Ganetzky B. Point mutations in the Drosophila sodium channel gene para associated with resistance to DDT and pyrethroid insecticides. Mol Gen Genet. 1997;256(6): 602–610. pmid:9435785
  77. 77. Charlesworth B. The role of background selection in shaping patterns of molecular evolution and variation: evidence from variability on the Drosophila X chromosome. Genetics. 2012;191(1): 233–246. pmid:22377629
  78. 78. ffrench-Constant RH. The Molecular Genetics of Insecticide Resistance. Genetics. 2013;194: 807–815. pmid:23908373
  79. 79. Qiu X, Sun W, McDonnell CM, Li-Byarlay H, Steele LD, Wu J, et al. Genome-wide analysis of genes associated with moderate and high DDT resistance in Drosophila melanogaster. Pest Manag Sci. 2013;69(8): 930–937. pmid:23371854
  80. 80. Brengues C. Pyrethroid and DDT cross-resistance in Aedes aegypti is correlated with novel mutations in the voltage-gated sodium channel gene. Med Vet Entomol. 2003;17(1): 87–94. pmid:12680930
  81. 81. Holt RA, Subramanian GM, Halpern A, Sutton GG, Charlab R, Nusskern DR, et al. The genome sequence of the malaria mosquito Anopheles gambiae. Science. 2002;298(5591): 129–149. pmid:12364791
  82. 82. Deus KM, Saavedra-Rodriguez K, Butters MP, Black IV MP, Foy BD. The fffect of ivermectin in seven strains of Aedes aegypti (Diptera: Culicidae) including a genetically diverse laboratory strain and three permethrin resistant strains. J Med Entomol. 2012;49(2): 356–363. pmid:22493855
  83. 83. Weill M, Lutfalla G, Mogensen K, Chandre F, Berthomieu A, Berticat C, et al. Comparative genomics: Insecticide resistance in mosquito vectors. Nature. 2003;423(6936): 137–138. pmid:12736675
  84. 84. Stevenson BJ, Pignatelli P, Nikou D, Paine MJI. Pinpointing P450s associated with pyrethroid metabolism in the dengue vector, Aedes aegypti: Developing new tools to combat insecticide resistance. PLoS Negl Trop Dis. 2012;6(3): e1595. pmid:22479665
  85. 85. Merrell DJ, Underhill JC. Selection for DDT resistance in inbred, laboratory, and wild stocks of Drosophila melanogaster. J Econ Entomol. 1956;49(1): 300–306.
  86. 86. Steele LD, Muir WM, Seong KM, Valero MC, Rangesa M, Sun W, et al. Genome-Wide Sequencing and an Open Reading Frame Analysis of Dichlorodiphenyltrichloroethane (DDT) Susceptible (91-C) and Resistant (91-R) Drosophila melanogaster Laboratory Populations. PLoS ONE. 2014;9(6): e98584. pmid:24915415
  87. 87. Sham P, Bader JS, Craig I, O’Donovan M, Owen M. DNA pooling: A tool for large-scale association studies. Nat Rev Genetics. 2002;3: 862–871.
  88. 88. Kim SY, Li Y, Guo Y, Li R, Holmkvist J, Hansen T, et al. Design of association studies with pooled or un-pooled next-generation sequencing data. Genet Epidemiol. 2010;34: 479–491. pmid:20552648
  89. 89. Langmead B, Salzberg S. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9(4): 357–359. pmid:22388286
  90. 90. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics. 2009;25(16): 2078–2079. pmid:19505943
  91. 91. Kofler R, Orozco-terWengel P, De Maio N, Pandey RV, Nolte V, Futschik A, et al. PoPoolation: a toolbox for population genetic analysis of next generation sequencing data from pooled individuals. PLoS ONE. 2011;6(1): e15925. pmid:21253599
  92. 92. Nolte V, Pandey RV, Kofler R, Schlötterer C. Genome-wide patterns of natural variation reveal strong selective sweeps and ongoing natural conflict in Drosophila mauritiana. Genome Res. 2011;23(1): 99–110.
  93. 93. Marchler-Bauer A. CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res. 2011; issue): D225-9