Multiple Origins of kdr-type Resistance in the House Fly, Musca domestica

Abstract

Insecticide resistance is a model phenotype that can be used to investigate evolutionary processes underlying the spread of alleles across a global landscape, while offering valuable insights into solving the problems that resistant pests present to human health and agriculture. Pyrethroids are one of the most widely used classes of insecticides world-wide and they exert their toxic effects through interactions with the voltage-sensitive sodium channel (Vssc). Specific mutations in Vssc (kdr, kdr-his and super-kdr) are known to cause resistance to pyrethroid insecticides in house flies. In order to determine the number of evolutionary origins of kdr, kdr-his and super-kdr, we sequenced a region of Vssc from house flies collected in the USA, Turkey and China. Our phylogenetic analysis of Vssc unequivocally supports the hypothesis of multiple independent origins of kdr, super-kdr and kdr-his on an unprecedented geographic scale. The implications of these evolutionary processes on pest management are discussed.

About the Authors:

Frank D. Rinkevich

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Shannon M. Hedtke

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Cheryl A. Leichter

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Sarah A. Harris

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Cathy Su

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Seán G. Brady

Affiliation: Department of Entomology, National Museum of Natural History, Smithsonian Institution, Washington, D. C., United States of America

Vatan Taskin

Affiliation: Department of Biology, Faculty of Science, Muğla Sitki Kocman University, Muğla, Turkey

Xinghui Qiu

Affiliation: State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

Jeffrey G. Scott

* E-mail: [email protected]

Affiliation: Department of Entomology, Comstock Hall, Cornell University, Ithaca, New York, United States of America

Introduction

Insecticide resistance presents a useful phenotypic trait for studies of evolution because the selective agent is known, the force of selection is strong, and the mutations conferring resistance have often been identified. In addition, the evolution of resistance constrains our abilities to control pest species, resulting in significant economic and health problems. In naïve (i.e., susceptible) populations resistance alleles are rare, with a frequency of 10−2 to 10−13 [1], [2]. If the resistance allele is completely recessive, then the resistant phenotype will be even rarer. Following insecticide treatment, the frequency of resistance alleles depends on the strength of selection for resistance, the fitness cost of resistance alleles in the absence of insecticide, the initial frequency of resistance alleles, and the likelihood of gene flow among populations [1], [3], [4]. Information about the maintenance and spread of these alleles can improve predictive power for the evolutionary outcome of a particular insecticide regime.

Our understanding of the factors affecting the evolutionary outcome of insecticide use has been greatly enhanced by the development of molecular tools. In particular, sequencing the genes that confer resistance allows us to investigate whether resistance to a specific insecticide or group of insecticides has single or multiple evolutionary origins. In most cases, insecticide resistance appears to have had multiple, independent evolutionary origins that occur in separate geographic regions [5]–[9], although there are a significant number of cases in which resistance appears to have evolved once and then dispersed across the globe [10]–[16].

A major mechanism of resistance to pyrethroids, a commonly used class of insecticides, is target-site insensitivity conferred by mutations in the voltage-sensitive sodium channel gene (Vssc) [17]. The first mutation in Vssc found to confer pyrethroid resistance (L1014F) is known as kdr [18], [19]. In house flies, two other mutations have been identified: L1014H (kdr-his) and M918T+L1014F (super-kdr). Heterologous expression studies have shown that all three mutations (kdr, kdr-his and super-kdr) result in a sodium channel that is resistant to the effects of pyrethroid insecticides [17], [20]–[24]. For the sake of simplicity, herein we will refer to these as kdr-type mutations.

The sequence of the intron that is three base pairs (bp) downstream of the L1014F/H mutation is highly variable in house flies and several other insects. Phylogenetic analyses of Vssc haplotypes (including the intron) in house flies suggested multiple evolutionary origins of kdr-his and that super-kdr was sequentially derived from kdr [5]. In the green peach aphid, Myzus persicae, a similar analysis indicated multiple independent origins of kdr and super-kdr, with super-kdr again being derived from kdr [6]. Multiple origins of pyrethroid resistance have also been found via phylogenetic analysis in Bemisia tabaci (silverleaf whitefly), although the mutations conferring resistance differ (L925I and T925V) [7].

In this study, we extensively sampled house fly populations across the USA, Turkey and China. Our phylogenetic analysis of Vssc unequivocally supports the hypothesis of multiple independent origins of kdr, super-kdr and kdr-his on an unprecedented geographic scale. In light of our results, we discuss the implications for pest management of selection for and against resistant phenotypes, gene flow among populations, and allelic dominance.

Materials and Methods

House Fly Collections

House flies were collected using sweep nets in and around dairy barns at nine locations in the United States (Alachua County FL, Wake County NC, Chemung County NY, Riley County KS, Riverside County CA, Ramsey County MN, Gallatin County MT, Lancaster County NE and Dona Ana County NM). Adult flies were reared for a generation and pupae were mailed to Cornell University. Adult flies of each sex were stored in 70% ethanol at −80°C until used for genotyping. Flies were collected from 15 sites in Turkey and five provinces in China as previously described [14], [15] (Table S1).

Vssc Sequencing

We isolated gDNA from adult female flies collected in the USA as previously described [5]. To assess resistance to pyrethroids, we amplified two fragments of the voltage-sensitive sodium channel (Vssc): a 350-bp fragment that included the 1014 codon for evaluating kdr and the associated adjacent intron, and a 1.5 kb fragment that included the 918 codon for evaluating super-kdr [5]. Sequencing of samples collected in the USA was performed at the Cornell Biotechnology Resource Center. Samples collected from Turkey and China were sequenced as previously described [14], [15].

Electropherograms were inspected and homozygous sequences were compared to previously described haplotypes [5]. Novel haplotypes were named based on the allele present (defined by the deduced amino acids at positions 918 and 1014 of Vssc) and then numbered in the order they were discovered. For example, haplotypes that were M918+F1014 were named kdr1-5. Those that were M918+H1014 or T918+F1014 were named kdr-his1-4, or superkdr1-3, respectively. Haplotypes that were M918+L1014 (susceptible) were named v1-85. PCR products of the kdr region from samples with ambiguous sequences that did not match described haplotypes were cloned into pGEM-T Easy (Promega, Madison WI) and screened and sequenced as previously described [5].

Phylogenetic Analysis

We used intron+exon sequence from the ∼350 bp region adjacent to the kdr mutation to build a phylogenetic tree of sequenced alleles. Sequences were aligned by eye using Mesquite v.2.75 [25]. As there was some uncertainty in the alignment, two matrices were analyzed: one which contained the full matrix (“full”), and another for which all ambiguous cites were excluded (“strict”). Alignments were run in jModelTest v.0.1.1 [26] to determine the best fit model of sequence evolution under the Bayesian Information Criterion. Trees were scored using a branch-length optimization using PhyML [27] as distributed with jModelTest. The maximum-likelihood estimate for each alignment was determined using GARLI v.2.0 for Windows [28], using the best-fit model of sequence evolution, with twenty replicates (search reps = 20). Bootstrap support for each bipartition was determined using GARLI, with only two search replicates for each of 100 bootstrap replicates.

Parametric Bootstrapping

To assess whether the maximum-likelihood estimate, in which resistant alleles are found throughout the tree, has a statistically significantly higher likelihood than a tree in which there was a single origin of resistance, we used parametric bootstrapping [29]. We performed a phylogenetic analysis on our data, constraining the search to trees in which resistant alleles form a monophyletic grouping (using GARLI [28], with models as above). The statistical distribution of differences in log-likelihood scores under the single origin hypothesis was assessed using simulations on the constrained tree. Simulations were performed using Mesquite [25] with the model parameters estimated by GARLI to produce one hundred replicate data sets. GARLI was once again used to score the best tree and the best constrained tree for each simulated replicate; this generates a distribution of likelihood scores expected if the single-origin hypothesis were correct. We then determined where our observed value fell within this distribution.

Results

Haplotypes

We sampled 336 flies from the USA, 73 from Turkey and 46 from China. We identified 103 novel haplotypes, which brings the total number of haplotypes described to more than 120. Some haplotypes contained the same intron sequences and varied only in the coding region of the gene (Table 1). For example, kdr2, super-kdr1, kdr-his4 and v39 all had identical intron sequences, but varied at the codons for amino acids 918 and/or 1014 (Table 1, column B). This was also true for the following pairs of haplotypes: kdr1 and super-kdr3, kdr4 and v40, kdr5 and v85, kdr-his1 and v54, kdr-his2 and v41, kdr3 and superkdr2, and kdr-his3 and v42 (Table 1).

[Figure omitted. See PDF.]

Table 1. Vssc haplotypes found in house fly populations that share the same intron sequence.

https://doi.org/10.1371/journal.pone.0052761.t001

Phylogenetic Analyses

The maximum-likelihood estimate for the full alignment is presented in Figure 1. Analysis of the strict alignment, which eliminated potentially ambiguous sites, resulted in a tree with lower resolution. However, in both trees, there are three independent clades containing kdr-his alleles, at least two independent clades containing kdr alleles and at least two independent clades containing super-kdr alleles, suggesting independent gains or losses of resistance.

[Figure omitted. See PDF.]

Figure 1. Maximum-likelihood phylogeny of Vssc alleles/haplotypes in house flies.

Tree is unrooted, and is shown here with a mid-point root for visualization only. Susceptible haplotypes are represented by v+number. Numbers at nodes represent the bootstrap values (%); only bootstrap values greater than 50% are shown.

https://doi.org/10.1371/journal.pone.0052761.g001

Parametric Bootstrapping

The log-likelihood value of the best tree was −1330.985567, while the log-likelihood of the best tree in which resistant alleles are constrained to a single origin was −1524.707019. The difference in likelihood score, 193.72, falls outside of the distribution of values expected if there were a single origin, and is significant with a p<0.01.

Discussion

Our analyses strongly support multiple origins of all three Vssc alleles: kdr, kdr-his and super-kdr. Our statistical tests reject the hypothesis of a single origin of resistance to pyrethroids in house flies with strong support (p<0.01). If we make the reasonable assumption that susceptibility is the ancestral condition (since resistance is selected against in the absence of insecticide and is rare in populations not exposed to pyrethroids), then there have been at least two independent origins of kdr. Our data further support multiple origins of kdr-his, and a sequential progression of super-kdr from kdr (as in [6]). Although the evolution of super-kdr from kdr has been found in M. domestica and M. persicae [5], [6], [30], the M981T mutation has been found without the L1014F mutation in Aphis gossypii [31] and Tetranychus evansi [32].

Several kdr haplotypes have identical intron sequences to susceptible haplotypes (kdr4 and v40; kdr5 and v85), suggesting a single mutational step has recently led from a susceptible to a resistant phenotype. A similar pattern of intron identity between susceptible and resistant phenotypes was observed in Rdl, which confers resistance to cyclodienes in the red flour beetle, Tribolium castaneum [33]. In fact, the ability to find intron haplotypes that have L, F, or H1014 in 6 clusters confirms a thorough sampling effort. In all cases, each super-kdr intron haplotype is paired with an identical kdr haplotype (Table 1), suggesting that super-kdr (M918T+L1014F) likely evolved from an individual house fly with kdr (L1014F).

In some cases resistant alleles appear to have evolved once and rapidly spread across a large geographic area [11]. However, in house flies we observe multiple origins of kdr-type resistance alleles. Although house flies are capable of dispersing over large geographic areas [34], [35], the genetic structure (based on mitochondrial loci and microsatellites) indicates strong among-population differentiation [36], [37]. The multiple origins of kdr-type resistance and the limited geographic distribution of each resistance allele are consistent with independent mutational events in different geographic locations coupled with restricted gene flow and/or a geographic selection mosaic, in which alleles from different populations are selected against.

A geographic mosaic, with limited or rare dispersal coupled with heterogeneous local selection pressures, is suggested by the distribution of Vssc haplotypes across the globe (Table S2). House flies are reasonably mobile, being able to fly several km per day. If gene flow drives the distribution of haplotypes, we would expect to detect fewer alleles associated with resistance and greater homogeneity among populations. Instead, our results are consistent with genetically structured populations, as found in previous work [36], [37]. Several resistant alleles have a global distribution (kdr1, kdr2, kdr-his4), but most are restricted to a particular country. For example, kdr-his2 was detected in the USA only, while kdr-his5 is restricted to Turkey. Even in the cases where kdr-his haplotypes are shared between countries, there are usually very few locations where they are shared, as in the case of kdr-his4 seen from 10 locations in Turkey, but only from California in the USA. Similarly, susceptible haplotypes v41 through v103 were found in only a single country. All super-kdr haplotypes were only found in one location (USA). It is probable that super-kdr exists in house fly populations in China because it has been detected in a field-collected strain that was selected with deltamethrin [38], but it would appear to be rare [14]. This geographic distribution of resistance haplotypes observed in this study supports multiple, independent origins of resistant Vssc alleles.

When attempting to determine the number of origins of a resistance allele, adequate sampling size from a broad geographic range is critical. Previous work on house flies incorrectly concluded there was a single origin of kdr [5], likely because there were only two kdr haplotypes identified. Our current study, using larger numbers of flies that were sampled from a much wider geographic area, clearly shows that kdr has multiple evolutionary origins. Thus, it is important that studies on the evolutionary origins of resistance have a robust number of locations and number of individuals that are sampled.

Based on the cases reported to date, can we identify factors that have led to the multiple origins of resistance in some cases but single origins in others? Clearly the introduction and maintenance of resistant alleles within a population can be affected by multiple factors: the mutation rate from susceptible to resistant alleles (higher frequencies would make multiple origins more likely), the intensity of selection for and against those alleles, and the relative mobility (including movement facilitated by humans) of the pest. Review of the origins of resistance across pest species (Table 2) suggests an important fourth factor: whether the resistance is inherited as a dominant or recessive trait. In all cases where resistance is a recessive trait, there have been multiple origins of resistance. For a fully recessive mutation, resistance is only phenotypically manifest in a homozygote (assuming a diploid organism and an autosomal trait). Such a homozygous resistant individual that dispersed to a new population lacking resistant alleles would produce only heterozygous offspring, with no resistance (assuming fully recessive resistance). In contrast, the arrival of an individual with a dominant resistance mutation would provide resistance to at least half of their offspring (assuming an autosomal locus and diploid organism). If the new population is exposed to pesticide, the mutation can rapidly spread, effectively overcoming the need for the mutation to arise independently in that population. However, the number of cases for which we are able to understand the processes involved in determining the outcome of single or multiple evolutionary origins is limited (Table 2). It would be valuable to determine the number of evolutionary origins for other cases of insecticide resistance, to evaluate the potential connection between the dominance of the alleles underlying these traits and the origin and spread of resistance.

[Figure omitted. See PDF.]

Table 2. Resistance mechanisms, patterns of inheritance, evolutionary origins and prevalence of mutations conferring insecticide resistance.

https://doi.org/10.1371/journal.pone.0052761.t002

A confounding factor in understanding the evolution of insecticide resistance is the relative fitness costs of different alleles in the absence of selection. For example, the relative resistance conferred to most pyrethroid insecticides is super-kdr>kdr>kdr-his [5], [39]. However, even in populations where selection pressure is high and resistant individuals predominate, super-kdr is rare, and in one population kdr-his is the most prevalent allele even though super-kdr is also present [40]. This may also be the case in China where super-kdr was found in a field-collected strain that was selected in the laboratory with deltamethrin [38], even though in another study super-kdr was not detected in field-collected flies and kdr-his was the most common allele [14]. Studies in house flies, aphids and mosquitoes have demonstrated a fitness cost for kdr in the absence of insecticide [41]–[43], but the relative fitness costs of susceptible, kdr, kdr-his and super-kdr individuals are not well understood. Therefore, an important next step is to further quantify these fitness costs, which will in turn enhance our ability to make predictions about the equilibrium frequency of resistance under alternative pest management strategies.

In conclusion, we have identified a large number of Vssc haplotypes that, when subject to phylogenetic analysis, confirms multiple evolutionary origins of kdr-type resistance. This study highlights the genetic plasticity that underlies the manifestation of insecticide resistance and has significance for the synthesis of insecticide resistance management strategies. The capacity for convergent evolution of Vssc mutations represents a challenge for successful pest management. In particular, the mechanism of resistance and likelihood of gene flow among populations changes our expectations for the maintenance of resistant phenotypes across a species’ global range–and thus, the effects of the selection regime imposed by a particular pesticide application strategy.

Supporting Information

[Figure omitted. See PDF.]

Table S1.

Locations where house flies were collected.

https://doi.org/10.1371/journal.pone.0052761.s001

(PDF)

Table S2.

Intron haplotypes, GenBank Accession numbers and locations where each haplotype was observed.

https://doi.org/10.1371/journal.pone.0052761.s002

(PDF)

Acknowledgments

We thank C. Geden, A. Gerry, D. Taylor, R. Byford, W. Watson, R. Moon, G. Johnson, D. Boxler and L. Zureck for providing some of the flies used in this study.

Author Contributions

Conceived and designed the experiments: FDR JGS. Performed the experiments: FDR CAL SAH CS. Analyzed the data: FDR SMH CAL SAH CS JGS SGB. Contributed reagents/materials/analysis tools: VT XQ. Wrote the paper: FDR SMH CAL SAH CS SGB VT XQ JGS.

Citation: Rinkevich FD, Hedtke SM, Leichter CA, Harris SA, Su C, Brady SG, et al. (2012) Multiple Origins of kdr-type Resistance in the House Fly, Musca domestica. PLoS ONE 7(12): e52761. https://doi.org/10.1371/journal.pone.0052761

References

1. Georghiou GP, Taylor CE (1977) Genetic and biological influences in the evolution of insecticide resistance. J Econ Entomol 70: 319–323.

2. Whitten MJ, McKenzie JA (1981) The Genetic Basis for Pesticide Resistance. Proc 3rd Aust Conf Grassland Invert Ecol Adelaide, South Aust Gov Print 1–16.

3. ffrench-Constant RH, Daborn PJ, Le Goff G (2004) The genetics and genomics of insecticide resistance. Trends in Genetics 20: 165–170.

4. Caprio MA, Tabashnik BE (1992) Gene flow accelerates location adaptation among finite populations: simulating the evolution of insecticide resistance. J Econ Entomol 85: 611–620.

5. Rinkevich FD, Zhang L, Hamm RL, Brady SG, Lazzaro BP, et al. (2006) Frequencies of the pyrethroid resistance alleles of Vssc1 and CYP6D1 in house flies from the eastern United States. Insect Mol Biol 15: 157–167.

6. Anstead JA, Williamson MS, Denholm I (2005) Evidence for multiple origins of identical insecticide resistance mutations in the aphid Myzus persicae. Insect Biochem Molec Biol 35: 249–256.

7. Alon M, Benting J, Lueke B, Ponge T, Alon F, et al. (2006) Multiple origins of pyrethroid resistance in sympatric biotypes of Bemisia tabaci (Hemiptera: Aleyrodidae). Insect Biochem Molec Biol 36: 71–79.

8. Anthony NM, Brown JK, Markham PG, ffrench-Constant RH (1995) Molecular analysis of cyclodiene resistance-associated mutation among populations of the sweetpotato whitefly Bemisia tabaci. Pestic Biochem Physiol 51: 220–228.

9. Newcomb RD, Gleeson DM, Yong CG, Russell RJ, Oakeshott JG (2005) Multiple mutations and gene duplications conferring organophosphorus insecticide resistance have been selected at the Rop-1 locus of the sheep blowfly, Lucilia cuprina. J Mol Evol 60: 207–220.

10. Daborn PJ, Yen JL, Bogwitz MR, LeGoff G, Feil E, et al. (2002) A single P450 allele associated with insecticide resistance in Drosophila. Science 297: 2253–2256.

11. Raymond M, Callaghan A, Fort P, Pasteur N (1991) Worldwide migration of amplified insecticide resistance genes in mosquitoes. Nature 350: 151–153.

12. Field LM, Javed N, Stribley MF, Devonshire AL (1994) The peach-potato aphid Myzus persicae and the tobacco aphid Myzus nicotianae have the same esterase-based mechanisms of insecticide resistance. Insect Mol Biol 3: 143–148.

13. Seifert J, Scott JG (2002) The CYP6D1v1 allele is associated with pyrethroid resistance in the house fly, Musca domestica. Pestic Biochem Physiol 72: 40–44.

14. Wang Q, Li M, Pan J, Di M, Liu Q, et al. (2012) Diversity and frequencies of genetic mutations involved in insecticide resistance in field populations of the house fly (Musca domestica L.) from China. Pestic Biochem Physiol 102: 153–159.

15. Taskin V, Baskurt S, Dogac E, Taskin BG (2011) Frequencies of pyrethroid resistance-associated mutations of Vssc1 and CYP6D1 in field populations of Musca domestica L. in Turkey. J Vector Ecol 36: 239–247.

16. ffrench-Constant RH, Rocheleau TA, Steichen JC, Chalmers AE (1993) A point mutation in a Drosophila GABA receptor confers insecticide resistance. Nature 363: 449–451.

17. Dong K (2007) Insect sodium channels and insecticide resistance. Invert Neurosci 7: 17–30.

18. Milani R, Travaglino A (1957) Ricerche genetiche sulla resistenza al DDT in Musca domestica concatenazione del gene kdr (knockdown-resistance) con due mutanti morfologigi. Rivista Di Parassitologia 18: 199–202.

19. Williamson MS, Denholm I, Bell CA, Devonshire AL (1993) Knockdown resistance (kdr) to DDT and pyrethroid insecticides maps to a sodium channel gene locus in the housefly (Musca domestica). Molec Gen Genet 240: 17–22.

20. Park Y, Taylor MFJ (1997) A novel mutation L1014H in sodium channel gene hscp associated with pyrethroid resistance for Heliothis virescens (Lepidoptera: Noctuididae). Insect Biochem Molec Biol 27: 9–13.

21. Dong K, Valles SM, Scharf ME, Zeichner B, Bennett GW (1998) The knockdown resistance (kdr) mutations in pyrethroid-resistant German cockroaches. Pestic Biochem Physiol 60: 195–204.

22. Tan J, Liu Z, Wang R, Huang ZY, Chen AC, et al. (2005) Identification of amino acid residues in the insect sodium channel critical for pyrethroid binding. Mol Pharmacol 67: 513–522.

23. Dong K (1997) A single amino acid change in the para sodium channel protein is associated with knockdown-resistance (kdr) to pyrethroid insecticides in German cockroach. Insect Biochem Mol Biol 27: 93–100.

24. Knipple DC, Doyle KE, Marsella-Herrick PA, Soderlund DM (1994) Tight genetic linkage between the kdr insecticide resistance trait and a voltage-sensitive sodium channel gene in the house fly. Proc Natl Acad Sci U S A 91: 2483–2487.

25. Maddison WP, Maddison DR Mesquite: A modular system for evolutionary analysis. http://mesquiteproject.org. Accessed 2012 Nov 25.

26. Posada D (2008) jModelTest: Phylogenetic model averaging. Mol Biol Evol 25: 1253–1256.

27. Guindon S, Gascuel O (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52: 696–704.

28. Zwickl DJ (2006) Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion, PhD Dissertation, The University of Texas at Austin.

29. Hillis DM, Mable BK, Larson A, Davis SK, Zimmer EA (1996) Nucleic Acids IV: Sequencing and Cloning. In: Hillis DM, Mable BK, Moritz C, editors. Molecular Systematics. Sunderland, MA: Sinauer. 321–381.

30. Williamson M, Martinez-Torres D, Hick C, Devonshire A (1996) Identification of mutations in the housefly para-type sodium channel gene associated with knockdown resistance (kdr) to pyrethroid insecticides. Molec Gen Genet 252: 51–60.

31. Marshall KL, Moran C, Chen Y, Herron GA (2012) Detection of kdr pyrethroid resistance in the cotton aphid, Aphis gossypii (Hemiptera: Aphididae), using a PCR-RFLP assay. J Pestic Sci 37.

32. Nyoni B, Gorman K, Mzilahowa T, Williamson MS, Navajas M, et al. (2011) Pyrethroid resistance in the tomato red spider mite, Tetranychus evansi, is associated with mutation of the para-type sodium channel. Pest Man Sci 67: 891–897.

33. Andreev D, Kreitman M, Phillips TW, Beeman RW, ffrench-Constant RH (1999) Multiple origins of cyclodiene insecticide resistance in Tribolium castaneum (Coleoptera: Tenebrionidae). J Mol Evol 48: 615–624.

34. Schoof HF (1959) How far do flies fly and what effect does flight pattern have on their control? Pest Control 27: 16–24.

35. Keiding J (1986) The house fly – biology and control. World Health Organization (WHO), Vector Biology and Control Division WHO/VBC/86.937.

36. Marquez JG, Krafsur ES (2002) Gene flow among geographically diverse housefly populations (Musca domestica L.): a worldwide survey of mitochondrial diversity. J Heredity 93: 254–259.

37. Krafsur E, Cummings M, Endsley M, Marquez J, Nason J (2005) Geographic differentiation in the house fly estimated by microsatellite and mitochondrial variation. J Heredity 96: 502–512.

38. Qiu X, Li M, Luo H, Fu T (2007) Molecular analysis of resistance in a deltamethrin-resistant strain of Musca domestica from China. Pestic Biochem Physiol 89: 146–150.

39. Farnham AW, Murray AWA, Sawicki RM, Denholm I, White JC (1987) Characterization of the structure-activity relationship of kdr and two variants of super-kdr to pyrethroids in the housefly (Musca domestica L.). Pestic Sci 19: 209–220.

40. Rinkevich FD, Hamm RL, Geden CJ, Scott JG (2007) Dynamics of insecticide resistance alleles in two different climates over an entire field season. Insect Biochem Mol Biol 37: 550–558.

41. Foster SP, Woodcock CM, Williamson MS, Devonshire AL, Denholm I, et al. (1999) Reduced alarm response by peach-potato aphids, Myzus persicae (Hemiptera: Aphididae), with knock-down resistance to insecticides (kdr) may impose a fitness cost through increased vulnerability to natural enemies. Bull Entomol Res 89: 133–138.

42. Foster SP, Young S, Williamson MS, Duce I, Denholm I, et al. (2003) Analogous pleiotropic effects of insecticide resistance genotypes in peach-potato aphids and houseflies. Heredity 91: 98–106.

43. Berticat C, Bonnet J, Duchon S, Agnew P, Weill M, et al. (2008) Costs and benefits of multiple resistance to insecticides for Culex quinquefasciatus mosquitoes. BMC Evol Biol 8: 104.

44. Pinto J, Lynd A, Vicente JL, Santolamazza F, Randle NP, et al. (2007) Multiple origins of knockdown resistance mutations in the Afrotropical mosquito vector Anopheles gambiae. PLoS ONE 2: e1243.

45. ffrench-Constant RH, Anthony NM, Andreev D, Aronstein K (1996) Single Versus Multiple Origins of Insecticide Resistance: Inferences from the Cyclodiene Resistance Gene Rdl. In: Brown TM, editor. Molecular Genetics and Evolution of Pesticide Resistance. 645 ed. Washington, D.C.: American Chemical Society. 106–116.

46. Boykin LM, Armstrong KF, De Barro P (2012) Species delimitation and global biosecurity. Evol Bioinform 8: 1–37.