Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Multiple recombination events between two cytochrome P450 loci contribute to global pyrethroid resistance in Helicoverpa armigera

  • Thomas K. Walsh ,

    Contributed equally to this work with: Thomas K. Walsh, Nicole Joussen

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organisation, Acton, Australian Capital Territory, Australia

  • Nicole Joussen ,

    Contributed equally to this work with: Thomas K. Walsh, Nicole Joussen

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Writing – original draft

    Affiliation Department of Entomology, Max Planck Institute for Chemical Ecology, Jena, Germany

  • Kai Tian,

    Roles Investigation, Resources

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

  • Angela McGaughran,

    Roles Formal analysis, Investigation, Resources, Writing – review & editing

    Affiliations Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organisation, Acton, Australian Capital Territory, Australia, School of BioSciences, University of Melbourne, Melbourne, Victoria, Australia

  • Craig J. Anderson,

    Roles Formal analysis, Investigation, Resources

    Affiliations Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organisation, Acton, Australian Capital Territory, Australia, Biological and Environmental Sciences, University of Stirling, Stirling, United Kingdom

  • Xinghui Qiu,

    Roles Data curation, Funding acquisition, Investigation, Project administration, Resources, Supervision

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

  • Seung-Joon Ahn,

    Roles Investigation, Resources

    Current address: Department of Crop and Soil Science, Oregon State University, Corvallis, Oregon, United States of America

    Affiliation Horticultural and Herbal Crop Environment Division, National Institute of Horticultural and Herbal Science, Suwon, Korea

  • Lisa Bird,

    Roles Resources

    Affiliation Tamworth Agricultural Institute, New South Wales Department of Primary Industry, Calala, New South Wales, Australia

  • Nena Pavlidi,

    Roles Investigation, Resources

    Affiliation Department of Biology, University of Crete, Rethymno, Greece

  • John Vontas,

    Roles Investigation, Resources

    Affiliation Laboratory of Pesticide Science, Agricultural University of Athens, Athens, Greece

  • Jaeeun Ryu,

    Roles Investigation, Resources

    Affiliation Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organisation, Acton, Australian Capital Territory, Australia

  • Akhtar Rasool,

    Roles Investigation, Resources

    Current address: Centre for Animal Sciences and Fisheries, University of Swat, Odigram, Khyber Pakhtunkhwa, Pakistan

    Affiliation Insect Molecular Biology Laboratory, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan

  • Isabella Barony Macedo,

    Roles Investigation, Resources

    Affiliation Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

  • Wee Tek Tay,

    Roles Resources

    Affiliation Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organisation, Acton, Australian Capital Territory, Australia

  • Yongjun Zhang,

    Roles Investigation, Resources

    Affiliation Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China

  • Mary E. A. Whitehouse,

    Roles Resources

    Affiliation Australian Cotton Research Institute, Narrabri, New South Wales, Australia

  • Pierre Jean Silvie,

    Roles Resources

    Affiliation Agroécologie et intensification durable des cultures annuelles, Centre de coopération internationale en recherche agronomique pour le développement, Montpellier, France

  • Sharon Downes,

    Roles Resources

    Affiliation Australian Cotton Research Institute, Narrabri, New South Wales, Australia

  • Lori Nemec,

    Roles Resources

    Affiliation Australian Cotton Research Institute, Narrabri, New South Wales, Australia

  •  [ ... ],
  • David G. Heckel

    Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing

    Affiliation Department of Entomology, Max Planck Institute for Chemical Ecology, Jena, Germany

  • [ view all ]
  • [ view less ]

Multiple recombination events between two cytochrome P450 loci contribute to global pyrethroid resistance in Helicoverpa armigera

  • Thomas K. Walsh, 
  • Nicole Joussen, 
  • Kai Tian, 
  • Angela McGaughran, 
  • Craig J. Anderson, 
  • Xinghui Qiu, 
  • Seung-Joon Ahn, 
  • Lisa Bird, 
  • Nena Pavlidi, 
  • John Vontas


The cotton bollworm, Helicoverpa armigera (Hübner) is one of the most serious insect pest species to evolve resistance against many insecticides from different chemical classes. This species has evolved resistance to the pyrethroid insecticides across its native range and is becoming a truly global pest after establishing in South America and having been recently recorded in North America. A chimeric cytochrome P450 gene, CYP337B3, has been identified as a resistance mechanism for resistance to fenvalerate and cypermethrin. Here we show that this resistance mechanism is common around the world with at least eight different alleles. It is present in South America and has probably introgressed into its closely related native sibling species, Helicoverpa zea. The different alleles of CYP337B3 are likely to have arisen independently in different geographic locations from selection on existing diversity. The alleles found in Brazil are those most commonly found in Asia, suggesting a potential origin for the incursion of H. armigera into the Americas.


In agriculture, insecticides are commonly used to control insect pest species. However, pest management is hindered by the increasing level of insecticide resistance in various pest species worldwide. One of the most serious insect pest species to evolve resistance against many insecticides from different chemical classes is the Old World cotton bollworm, Helicoverpa armigera (Hübner). Its pest status is further strengthened by its highly polyphagous nature and extremely wide geographical distribution, with the latter due to its ability to migrate long distances [14]. Recent work confirmed a major incursion of H. armigera into Brazil, as well as Argentina, Uruguay and Paraguay and it has been detected in Puerto Rico and Florida [58].

Pyrethroid resistance of H. armigera was first reported in Australian populations in 1983, six years after the introduction of these insecticides [9]. Since then, pyrethroid resistance has been reported from various populations globally but, in most cases, the molecular resistance mechanism in H. armigera is yet to be determined. The two major pyrethroid resistance mechanisms common to other species are target site insensitivity, and metabolic resistance by cytochrome P450 monooxygenases (P450s) and carboxylesterases [10, 11]. Target site resistance against pyrethroids, also known as knockdown resistance (kdr), is based on one or more point mutations in the insect sodium channel protein, which is the target of pyrethroid insecticides. In H. armigera, two mutations (D1549V and E1553G) in the sodium channel protein have been described [12, 13]. In the case of metabolic resistance, 18 P450s have been identified as capable of metabolizing one or more pyrethroid insecticides after heterologous expression [11, 1419]. One of them is the chimeric CYP337B3, recently identified in Australian H. armigera and thought to have arisen through an unequal crossing-over between the parental genes, CYP337B1 and CYP337B2 [18].

Joussen et al. [18] demonstrated that, after heterologous expression, CYP337B3 is capable of metabolizing fenvalerate, a type II pyrethroid ester, to the nontoxic 4'-hydroxyfenvalerate. In contrast, the parental enzymes exhibit no detectable fenvalerate metabolism. CYP337B3 has been shown to confer 42-fold resistance towards fenvalerate in Australian H. armigera lines differing solely in the presence of CYP337B3 and its parental genes [18]. Similarly, a 49-fold resistance factor was reported by Forrester et al. [20] for an Australian field-collected population, indicating that metabolism of fenvalerate by CYP337B3 is the detoxification mechanism in vivo.

Recently, CYP337B3 was also identified in field-collected populations from Pakistan [21] and China [22], confirming its presence outside Australia. Sequence analysis revealed a distinct CYP337B3 allele (CYP337B3v2), in the Pakistani population and three distinct alleles in the Chinese populations (CYP337B3v2, CYP337B3v3, CYP337B3v4) that differ from the Australian allele (CYP337B3v1), by a number of synonymous and non-synonymous SNPs, in addition to variability of the intron sequence and size. This variation may result from different crossing-over positions during recombination of the CYP337B1 and CYP337B2 parental genes, with different alleles of CYP337B1 and CYP337B2 involved in the crossing-over. Such a pattern is indicative of independent origins of the various CYP337B3 alleles, however further work would be required to determine whether this is accurate across a wide geographic distribution of samples. Given the high frequency of this allele around the world, it is possible that the population of H. armigera now established in South America [5, 23, 24] may be carrying this allele and that the possession of CYP337B3 may confer a selective advantage over local species.

Previous studies with allozymes and mitochondrial DNA indicated that very little population structure among H. armigera populations, though more recent work using many thousand genomic markers has shown that the population of H. armigera in Australia can be differentiated from the rest of the world [25, 26]. This lack of structure makes the identification of the CYP337B3 chimeric origin difficult, as well as more generally hampering the identification of source populations in the case of incursions into the New World. However, examining patterns of distribution and diversity among recently selected genes can shed light on such processes. CYP337B3 is a strong candidate for having undergone rapid selection due to its role in pyrethroid resistance, which has a short (approximately 50 year) history across much of the globe [27].

Here, we use field-collected populations from 17 countries distributed through Africa, Asia, Oceania, Europe, and South America to first examine the evolutionary history of the chimeric CYP337B3 gene and the global spread in H. armigera. We use global allelic frequency data to show that CYP337B3 is commonly found around the world, with at least six likely independent unequal crossing-over events giving rise to the same resistance phenotype in different regions. We also confirm recent data showing evidence of hybridisation between invasive H. armigera from Brazil and the local Helicoverpa zea population, including the exchange of the CYP337B3 gene [26, 28]. Furthermore, we then use the different CYP337B3 alleles to shed light on the nature of selection of CYP337B3, finding evidence to support recent selection operating on standing variation as opposed to novel mutations arising as a result of pyrethroid application.

Materials and methods

Population samples

A total of 1063 insect samples were used in the current study, including several specimens collected and used in previous work [5, 25, 26, 28, 29]. H. armigera was collected from 17 countries, H. zea from two (Fig 1; S1 Table). All insect samples were collected from agricultural areas with the permission of the landholder or by trapping using species-specific pheromones. No collecting permits were required because both species are common agricultural pests. No endangered or protected species were used in this work. Samples were usually collected as larvae from wild and crop host plants, as adult moths via light/pheromone traps or as larvae after bioassay. For one set of samples from China (n = 240), larvae were collected from colonies derived from eight recently collected field samples (established with 20 to 50 individuals). Collection dates range from 2002 to 2013. Samples were preserved in ethanol (>95%), in RNAlater, or at -20°C prior to DNA extraction. DNA was extracted using the DNeasy Blood and Tissue Kit (Qiagen) or the Fast Tissue-to-PCR Kit (Fermentas, Thermo Scientific).

Fig 1. Collection localities.

H. armigera (n = 986) were sampled from 17 countries (black stars): Australia, New Zealand, China, Korea, India, Pakistan, Greece, Spain, France, Burkina Faso, Cameroon, Chad, Ghana, Madagascar, Senegal, Uganda, and Brazil. H. zea were sampled from Brazil (n = 43) and the United States of America (n = 16). Modified from public domain map from Natural Earth (

The species status of several preserved specimens was confirmed by mitochondrial gene (COI and Cytb) sequencing, either from previous work [5, 29] or, where new samples were available, by amplifying and sequencing the same regions (S2 Table). PCR amplification followed the protocols of Behere et al. [29] and Tay et al. [5]. PCR products were sequenced at Macrogen (Seoul, Korea) and the Biological Resources Facility (Australian National University, Canberra, Australia). Assembly of DNA trace sequences was performed using CLC Genomics Workbench version 8.0.

Screening for CYP337B3

Following species identification, samples were screened for the presence of CYP337B3 using the CYP337B2F and CYP337B1R primers described in Joussen et al. [18]. Heterozygote/homozygote status was determined through relevant band detection on 1.5–2% agarose gels containing 1% (w/v) of GelRed (Biotium) and visualised under UV light. Initial sequence was generated from these short fragments for a subset of samples following the PCR amplification protocol of Joussen et al. [18]. However, in order to generate more information, primers were designed to amplify the intron of the gene (S2 Table). In the chimeric CYP337B3 gene, CYP337B1 contributes the intron and several hundred base pairs of coding sequence depending on the allele, while CYP337B2 contributes much of the 5' end of the coding sequence. Thus, the CYP337B3 intron corresponds to the CYP337B1 intronic sequence. We also screened samples from Brazil (n = 181) and Australia (n = 97) for the reciprocal recombination event using CYP337B1F and CYP337B2R primers (S2 Table) but no products were detected with this primer combination.

Further amplification of full-length genes and transcripts was performed for selected individuals with representative alleles. PCR products and cloned fragments were sequenced at several institutes, including: Macrogen (Seoul, Korea), Biological Resources Facility (Australian National University, Canberra, Australia), UC Davis Genome Center (University of California, Davis, US), StarSEQ (Mainz, Germany), Bioneer Corporation (Daejeon, Korea) and the Department of Entomology at the Max Planck Institute for Chemical Ecology (Jena, Germany). Assembly and sequence analysis of the PCR products was done using CLC genomics workbench v8.0 and T-Coffee (

Resistance bioassays

To establish the role of CYP337B3 in pythrethroid resistance, fenvalerate field resistant and susceptible individuals were identified by bioassay of field-collected material. Fenvalerate (95.3%) was provided by Sumitomo Chemical (Sydney, Australia) and dissolved in analytical grade acetone to produce a diagnostic concentration (0.125 μg/μL). A 1 μL volume of the discriminating concentration was applied to the dorsal thorax of late 3rd/early 4th instar larvae within a weight range of 30-40mg using a 50 μL micro-syringe in a repeating dispenser (Hamilton Company, Reno, NV, USA). Bioassays were maintained for 7 d at 25°C with a 14:10 (L:D) h cycle. Relative humidity (RH) was not controlled. Dead and moribund larvae were collected and described as sensitive by using one or more of the following criteria: larvae unable to demonstrate coordinated movement when prodded; paralysis of prolegs; larvae very slow to right themselves (time exceeding 3 s). Larvae that were actively feeding and developing normally were described as resistant.

Population genetic analysis

The elimination of variation in regions linked to an adaptive allele on one or even a few haplotypes is referred to as a “selective sweep” [30]. This process will lead to low nucleotide diversity (π) across the region of the genome under selection as well as an excess of rare variants as highlighted by Tajima’s D [31]. This statistic identifies deviation from a neutral model of evolution, whereby a negative score signifies purifying selection or population expansion that one would expect following a selection event. To provide evidence that the CYP337B3 gene is under selection in H. armigera, we searched for genomic signals of a recent selection event using high-throughput sequencing data.

DNA samples from 12 Australian H. armigera homozygous for CYP337B3v1 were sequenced on an Illumina HiSeq. Briefly, Nextera libraries were produced following the manufacturer’s instructions and sequence was generated as 100 bp PE reads (Illumina HiSeq 2000, Biological Resources Facility, Australian National University, Canberra, Australia). Raw reads were aligned to the bacterial artificial chromosome (BAC) 33J17 (JQ995292.1) sequence using BBMAP v33.43 (, trimming reads when quality in at least 2 bases fell below Q10. We did not align reads to the reference H. armigera genome sequence, which contains only CYP337B1 and CYP337B2 but not CYP337B3 [32]. Only uniquely aligning reads were included in the analysis, to prevent spuriously inferring evolutionary processes occurring independently on each BAC. Outputted BAM files were sorted before duplicate reads were removed and files were annotated with read groups using Picard v1.138 ( The reference sequences were indexed using Samtools [33]. UnifiedGenotyper in GATK v3.3–0 [34] was used to estimate genotypes across all individuals simultaneously, implementing a heterozygosity value of 0.01. Genotypes annotated as “LowQual” were removed prior to subsequent analysis with VCFtools v0.1.12b [35], whereby π and Tajima’s D were calculated in sliding windows of 2500 bp that progressed by 1250 bp across biallelic sites of 33J17. Results were plotted in R v3.1.2 using ggplot2 v1.0.1 [36], while gene annotations were derived via tblastx [37] and visualised with CLC Genomics workbench v8.0.

To examine potential mechanisms underlying the origin of the CYP337B3 alleles, an intron dataset containing sequences for representative CYP337B1 and CYP337B3 individuals (since the chimeric CYP337B3 intron comes from the CYP337B1 parental gene; see above) was created. MAFFT ver. 7.182 [38] was used to align these sequences using the -linsi option. Subsequently, IQ-TREE ver. 1.3.0 [39] was used, first in the -m TESTNEWONLY mode to determine the appropriate nucleotide substitution model, and then in full mode to generate a maximum likelihood tree. Subsequently 10,000 bootstrap replicates were carried out, and the bootstrap values transferred from the consensus tree to corresponding nodes of the maximum likelihood tree.

BEAST ver. 2.3.0 [40] was used for the intron-only dataset to test whether the CYP337B3 allele is monophyletic in origin (i.e., has arisen once from a CYP337B1/CYP337B2 cross-over and subsequently diverged independently). Two analyses were performed–one, in which monophyletic taxon sets for each of the CYP337B1 and CYP337B3 introns was enforced, and the other in which no monophyly was assumed. In BEAST, all runs used the evolutionary model identified in IQ-TREE (HKY + G4), a constant population coalescent tree prior, and a chain length of 10 x 106. Other coalescent tree priors were also tested, but these did not quantitatively impact the results. BEAST results were examined in Tracer to confirm convergence and check ESS values (all exceeded 1,500). The likelihood of each analysis was then compared using Bayes Factors and the ACIM model, with 1,000 replicates, in Tracer ver. 1.6 [41].


A total of 1063 insect samples was collected from 18 countries around the world (Fig 1). The identification of H. armigera was initially based on morphological assessments by collectors and subsequently confirmed with the mitochondrial markers, cytochrome oxidase I and cytochrome b [29]. Any individuals not identified as H. armigera by mitochondrial DNA were excluded from subsequent analysis (H. armigera n = 999, H. zea n = 59, Chloridea (Heliothis) virescens n = 5).

A PCR assay using one primer from each of the two parental genes CYP337B1 and CYP337B2 was used to identify the presence of the chimeric CYP337B3 gene. CYP337B3 was extremely common in field collected H. armigera throughout its native range (Fig 2 and S1S5 Figs). From a total of 999 individuals tested, CYP337B3 was present in 969 (97%) and only 30 (3%) individuals were homozygous for CYP337B1 or CYP337B2. 878 individuals were CYP337B3 homozygotes (88%) and 91 were heterozygotes, meaning they carried one chromosome carrying CYP337B3 and the other chromosome with the two parental genes CYP337B1 and CYP337B2 (9%). In some countries, almost all individuals were at least heterozygous for the CYP337B3 gene, but homozygous CYP337B3 individuals were the most common everywhere. In India, Pakistan, Korea, China, and Australia, almost all individuals were homozygous for CYP337B3, while heterozygotes (CYP337B1, CYP337B2 and CYP337B3) at the CYP337B3 locus were more common in European and African samples (Fig 2 and S1S5 Figs).

Fig 2. The frequency of CYP337B genotypes in selected geographic regions.

For a more detailed breakdown see S1 Fig through S5 Fig.

The PCR product of CYP337B3 used in the screening PCR reaction [18] was sequenced from positive individuals (alleles n = 460) and a pattern of single nucleotide polymorphisms was identified. By comparing this short (355 bp) sequence between individuals, 6 alleles (CYP337B3v1-2, 5–8) were identified worldwide (Fig 3). An allele originally identified in an Australian (Toowoomba) strain [18] was found only in Australia in the current study, where it was the most common allele (v1: n = 91), and v2 the next most common allele (v2: n = 23). In Asian samples, v2 was the most common allele (n = 203) and two other rare alleles were identified (v7 and v8; n = 1 each) in addition to v3 and v4 identified by Han et al. [22]. Three alleles were found in Africa including two that were new (v2: n = 11, v5: n = 79, v6: n = 8). In the European samples, we identified an approximately 50:50 ratio of CYP337B3v2 and v5 (v2: n = 20; v5 n = 17). In addition, a proportion of samples from Australia (n = 11), Africa (n = 2), and Europe (n = 7) appeared from the sequencing traces to be heterozygous for different CYP337B3 alleles. Overall, the various CYP337B3 alleles appeared to show distinct patterns for each region, suggesting different alleles are present for pyrethroid resistance around the world.

Fig 3. Frequencies of the different alleles of CYP337B3 (B3vX) in different geographic regions.

Africa = Burkina Faso, Cameroon, Chad, Ghana, Madagascar, Senegal, Uganda; Australasia = Australia and New Zealand; Europe = Greece, France and Spain. n = the number of alleles sequenced, homozygotes and heterozygote alleles summed.

Sequencing of the entire coding sequences of all variants revealed a number of non-synonymous SNPs resulting in different predicted proteins when compared to CYP337B1v1: 3 in v2 [21], 3 in v5, 8 in v6, 9 in v7, and 11 in v8. All variants of the chimeric gene appear to show a similar pattern with slightly different cross over points between CYP337B1 and CYP337B2 during the formation of CYP337B3 and different intron sequences and sizes that derived from CYP337B1 determined by sequencing genomic DNA (Fig 4; S6 Fig; S3 Table). This suggests that multiple origins of the same functional phenotype from different genetic backgrounds define the development of this chimeric gene.

Fig 4. A schematic of the different crossing-over points and intron sizes observed in the chimeric CYP337B3 gene.

All of the 93 H. armigera individuals collected in Brazil were positive for CYP337B3, and all except one were homozygous. The majority of CYP337B3 alleles detected in Brazilian H. armigera were identical to CYP337B3v2, which is predominantly found in Asia. However, the single heterozygous individual was carrying an African allele (CYP337B3v5). This suggests that Asia may be the most likely source for the Brazilian incursion of H. armigera, however, other source populations are also possible, as is the occurrence of multiple incursions. As well as examining H. armigera, we also examined H. zea from Brazil (n = 59) and we were able to amplify CYP337B3 from one individual from Goias while from the others (n = 23) only CYP337B1 provided consistent results. DNA from the suspect individual (S1 Table) was re-extracted twice in a different laboratory, using new reagents (extraction kit, primers, PCR reagents) and PCR was performed for the CYP337B3 gene, intron and the mitochondrial marker COI. Extraction blanks were performed and were negative for both the COI sequence and the CYP337B3. Sequencing of both fragments from the three different extractions confirmed the presence of the CYP337B3v2 allele (as found in the Brazilian H. armigera) in an individual with a mitochondrial sequence from H. zea.

Bioassays for pyrethroid resistance on H. armigera from cotton growing areas in eastern Australia using the discriminating dose clearly showed a higher frequency of homozygotes for CYP337B3 in survivors (100% CYP337B3 homozygous; n = 26) than in dead or dying insects (9 CYP337B3 homozygotes, 2 heterozygotes and 1 homozygous CYP337B1/B2 individual; n = 12), although a subset of the dead or dying caterpillars was actually positive for CYP337B3. In addition to bioassayed individuals, samples were collected from crops in Kununurra, Ord River Irrigation Scheme, Western Australia seven days after a field application of fenvalerate on cotton. Survivors were found to possess CYP337B3, with a 100% homozygous frequency (n = 7). Insects collected from the same region on unsprayed crops (cotton, chickpea and chia) showed a lower frequency of CYP337B3 (2 homozygote CYP337B3, 1 heterozygote and 3 homozygote CYP337B1/B2 individuals; n = 6). Although these very small samples from field populations are insufficient for claims of statistical significance, they are consistent with the significant genotypic differences previously found in the Toowoomba laboratory population derived from Australia [18].

Using individuals from Australia that were homozygous for the CYP337B3v1 allele, high throughput sequencing data was aligned to the BAC clone 33J17 which was the original source of the CYP337B3v1 identification and originates from the Australian Toowoomba strain [18]. Of the 100,377 genotypes called across 33J17, 32,381 remained after “LowQual” SNPs were removed. Both π and Tajima’s D were variable, however values were decisively differentiated where CYP337B3 lies; nucleotide diversity reaches its lowest point at the CYP337B3 locus (0.00057) relative to the BAC-wide mean at 0.0179 (Fig 5; S4 Table). This is the expectation following a “hard” selective sweep, whereby adaptive alleles appear as a single haplotype before increasing in frequency [30]. Tajima’s D is also lowest across the region where CYP337B3 is located (-2.18) and points towards the process of purifying selection. It is worth noting that the BAC-wide mean value for Tajima’s D is -0.43; such a low negative value may signify that other evolutionary processes have also acted upon this region [42]. While this variability is likely a result of small sample sizes and relatively small sliding window values, the small size (~ 5 kbp) of the region around CYP337B3v1 may signify ongoing high recombination rates and gene flow [43, 44].

Fig 5. Selective sweep among Australian H. armigera homozygous for CYP337B3v1.

(a) Nucleotide diversity (π) and (b) Tajima’s D calculated across sliding windows of the 33J17 BAC (JQ995292.1), with the red dashed line showing the average value of π (0.0179). Locations of gene bodies are indicated between the plots, with those in red identified as potential reverse transcriptases and those in yellow as exons of CYP337B3v1.

To establish the potential mechanisms that underlie the creation of the chimeric gene and account for its global distribution, we sequenced the intron of CYP337B3. This region should contain more polymorphisms and allow a better diagnosis of the frequency of the different genotypes. As for the coding region data (above), we found a pattern of eight alleles in the intron data. Introns sequenced from B3v3, v4 and v8 are very similar and differ only by two SNPS whereas introns from B3v1, v2, v5, v6 and v7 show more significant differences in both length and sequence (Fig 4). Individuals that were homozygous for the CYP337B3 gene were predominantly homozygous at the allele level, but as in the coding region, heterozygotes were again observed in the sequence traces of a small number of samples from Africa, Australia and Europe. Cloning and sequencing of the heterozygous PCR products showed that, in Australia, v1/v2 (Australia/Asia) heterozygotes were present, while in Africa, there were heterozygotes of v2/v5 (Asia/Africa) and v5/v6 (both African). European heterozygotes possessed v2/v5 (Asia/Africa).

Phylogenetic relationships were inferred for the intronic region of a subset of representative CYP337B1 and CYP337B3 sequences. If the chimeric CYP337B3 were due to a single cross-over event followed by subsequent divergence of allelic variations, then the phylogenetic estimates should show a monophyletic clade with the CYP337B3 clade nested within the CYP337B1 clade. Our tests with BEAST indicated that this was not the case; specifically Bayes Factor (BF) analysis found overwhelming support for a paraphyletic origin of CYP337B3 (BF score for paraphyly vs. monophyly = 494.412, with BF > 10 indicating very strong evidence against the null model of monophyly). This does not rule out the possibility of some subsequent recombination between derived CYP337B3 alleles and either parent gene.

Fig 6 presents the results of the maximum likelihood phylogenetic analysis, which also suggests multiple origins of the various CYP337B3 alleles. Although bootstrap support values for some nodes of the tree are quite low, several well-supported relationships are present, and these are consistent with multiple geographic origins for the CYP337B3 alleles. For example, CYP337B3v1 (found only in Australia) is most closely related at the sequence level to a CYP337B1v1 allele from Australia. Furthermore there is a cluster of closely related but rare CYP337B3 alleles found in China (CYP337B3v3, v4, and v7) which could indicate local origins for those alleles. Thus, while some CYP337B3 alleles may be recently derived from local CYP337B1 alleles, the overall signal indicates that multiple unequal crossing-over events are responsible for the geographic distribution of chimeric CYP337B3 while gene flow as well as some intergenic recombination may also have played a role producing the current geographic distribution patterns of CYP337B3 alleles.

Fig 6. Maximum likelihood phylogeny of CYP337B1 and CYP337B3 alleles.

The maximum likelihood tree was generated in IQ-TREE with the HKY+G4 model of sequence evolution, using representative CYP337B1 and CYP337B3 intron sequences. Bootstrap values from 10,000 replicates are given on tree nodes. The eight CYP337B3 alleles are indicated with labels (v1:v8), different CYP337B1 alleles are indicated by B1- followed by an allele ID and the country of origin. Sequences and related NCBI identifiers can be found in S3 Table and S1 File.

We performed an additional calculation to determine the molecular rate that would be required to produce the measured CYP337B3 allelic diversity if it had all arisen in the last ~50 years. Even using the rapidly evolving mitochondrial divergence rate of 1.5–2.5% divergence per million years as a baseline [45], we found that a 1000-fold increase in this rate would be required to place all CYP337B3 divergence events inside a 50-year time window. This rate is so high, it suggests that rather than recently arising through de novo mutation in response to pyrethroid applications and then spreading around the world, cytochrome P450-mediated pyrethroid resistance is most likely the result of selection acting over the last 50 years on existing genetic variation present in the populations at low frequency.


Helicoverpa armigera is one of the world’s most destructive pests and has developed resistance to numerous pesticides over the years [27]. Globally, pyrethroids are one of the most commonly used insecticides and resistance occurred rapidly at a global scale after the first use of pyrethroid insecticides in the late 1970s [27]. A number of mechanisms have been proposed for this resistance, including target site insensitivity [27, 46, 47], and metabolism by carboxylesterases [48, 49] and P450s [5056]. Recent work suggests that a chimeric gene, CYP337B3, may play an important role in cytochrome P450-mediated pyrethroid resistance and we set out to examine the frequency of this gene worldwide [18, 21].

We detected the chimeric CYP337B3 gene in every population examined and found a total of eight allelic variants of CYP337B3 globally. Of the eight global alleles identified, one was found only in Australia (CYP337B3v1), one was dominant across Asia (India, Pakistan, China, Korea), and Brazil (CYP337B3v2), four were rare and uniquely found in China (CYP337B3v3, v4, v7 and v8) and two were predominantly African (CYP337B3v5, v6). European samples showed a mixture of alleles (CYP337B3v2, v5). CYP337B3v2 was the most widespread allele, identified on every continent examined but was present at the highest frequencies in Asia and Brazil.

One issue in using CYP337B3 as a population marker is that diversity in CYP337B3 is not new diversity, but rather a re-shuffling of diversity already present in the parental CYP337B1 and CYP337B2 genes. However, the presence of multiple alleles at the CYP337B3 locus suggests that this chimeric gene has formed independently several times over the evolutionary history of the locus. In the overall patterns, we found that three alleles, v1, v2 and v5, together account for ~98% of all detected CYP337B3 alleles. The geographic distribution of these common alleles may suggest older recombination events in Australia, Asia, and Africa producing the common alleles and potentially more recent additional events in Asia and Africa producing the rare alleles. The alternative explanation that a single event has occurred, and then been distributed globally by migration and subjected to subsequent local recombination, is much less likely as it is not supported by the phylogeny or the molecular rate analysis. Indeed, our phylogenetic analysis found strong support for a paraphyletic origin of CYP337B3 rather than the alternative of a single unequal cross-over event followed by subsequent allelic divergence. In addition, our calculations suggest that a 1000-fold increase in a commonly accepted baseline divergence rate (1.5–2.5% divergence per million years) would be required to place all CYP337B3 divergence events inside a 50-year time window [45]. Taken together, the allele frequencies and phylogenetic analysis suggest that, rather than recently arising through de novo mutations in response to pyrethroid application, cytochrome P450-mediated pyrethroid resistance is most likely the result of recent selection acting on existing genetic variation maintained in the population at low frequency. Our selective sweep analysis supports this scenario, with patterns of estimated π and Tajima’s D across the 33J17 BAC indicating that the CYP337B3 locus has undergone recent selection, at least in Australia and with regard to CYP337B3v1. Recent work confirms that this can also be shown for the other alleles [26]. Further work will reveal how the diversity in this one region compares to the rest of the genome.

There are a number of examples in the literature where the same insecticide resistance mechanisms have developed independently in different locations. In particular pyrethroid resistance (perhaps because of the short period between the introduction and the development of resistance) associated with identical point mutations in the voltage-gated sodium channel has developed in different haplotypes with different geographical origins in mosquitoes and houseflies [57, 58]. In the sheep blowfly, the same mutations in an esterase gene conferring organophosphate resistance were identified in very different haplotypes [59].

Although further work incorporating whole genome scale markers will be necessary to determine the origin of H. armigera in the New World and global patterns of movement in this species [26, 28], we gain insight into some of these processes here. The vast majority of the Brazilian insects examined possessed the allele CYP337B3v2 found predominantly in Asia. However, we also detected the CYP337B3v2 allele in other regions of the world, and so it is possible that the Brazilian populations of H. armigera could have come from localities where the CYP337B3v2 allele also exists. For example, the closest native population of H. armigera to the New World is in West Africa and it is possible that the New World H. armigera are the result of a similar incursion from West Africa. However, only Asia has close to the same proportion of CYP337B3v2 alleles. A recent survey [8] showed that the pattern of mitochondrial markers in H. armigera populations collected from southern Brazil, Argentina, Uruguay and Paraguay is very different from H. armigera populations from central and northern regions of Brazil, suggesting multiple incursions of this global pest into the New World [60]. It would be interesting to examine the CYP337B3 locus in these individuals to see if they share the same pattern as found in Brazil.

Recently, evidence for other pyrethroid detoxicative mechanisms in addition to CYP337B3 has been found in China [22], and our own data showed some mortality in CYP337B3- homozygous individuals. This might suggest that possession of the CYP337B3 is not enough for resistance alone and other mechanisms related to expression or other genes may exist. However, as the resistance based on CYP337B3 is metabolic, it is not unusual that a high dose of insecticide will kill even homozygous individuals, for example if the enzyme is not abundant enough to decrease the amount of insecticide at its target site beneath the toxic threshold. Furthermore, we clearly see evidence of conservation of the CYP337B3 alleles at this locus across the globe and we would not expect the observed level of conservation in the absence of selection, particularly in the non-coding regions. Indeed, when we examined individuals from Australia we found evidence of a selective sweep around the gene, indicating maintenance of the allele at this locus. Throughout its native range, phenotypic pyrethroid resistance is very common in H. armigera and it is of course possible that other or additive resistance mechanisms are at work in populations around the world.

The arrival of H. armigera in the New World represents a significant expansion of its geographc range. It remains to be seen how large the problem H. armigera will become but, clearly, arriving with a resistance gene already in place would provide H. armigera a selective advantage over local susceptible populations of pests such as H. zea and Chloridea (Heliothis) virescens. One further complication is that H. zea has been shown to interbreed with H. armigera in the laboratory to produce viable offspring [6163] and there is evidence of hybridisation in Brazil using genome wide markers [28]. In the current study, we applied the same PCR reaction conditions to individuals identified as H. zea from Brazil and we able to amplify CYP337B3v2 from one individual. Clearly this one result is not enough to suggest that hybridisation is widespread between the two species but the detection of a presumably highly selectable gene indicates that this is something that should be considered a risk. While it is unclear what risk hybrids may pose, it is certain that an exchange of resistance and host association genes could lead to significant problems in control. The fact that the presence of the chimeric resistance gene CYP337B3 can be ascertained by a simple screening PCR enables the rapid determination of susceptible vs. pyrethroid-resistant populations, which could lead to improved pest management strategies and the detection of hybrid individuals in the field.

This work highlights a case of resistance alleles in H. armigera evolving on a local scale in a global context and provides an example of a species invading new continents, already able to overcome some of the control measures deployed for other species. We also show that resistance genes can arise locally and then mix on a global scale as a result of either natural movement or human-mediated transport. The implications for H. armigera and potentially H. zea as species are unclear but what is not in doubt is that the pesticide resistance selection pressure on H. armigera, in terms of numbers exposed, has dramatically increased with this incursion. This is true not just for conventional pesticide resistance but also for transgenic insecticidal traits. Transgenic cotton and especially corn and soybean which express Bt toxins are grown over a far larger area in the New World and the management of Bt and conventional pesticide resistance should be a priority.

Ultimately, we grow the same crops around the world, control pests using the same chemistries, and transport commodities through global trade routes, so it is not a surprise that we are developing global, well-adapted pests. Our paper not only sets the scene for further work in this area but also highlights the value of considering biosecurity threats in terms of both the actual pest as well as its resistance profile (both phenotype and genotype).

Supporting information

S1 Fig. The frequency of CYP337B3 on the Asian Sub-continent by region.

Northern, Central and Southern represent general geographic regions of India.


S2 Fig. The frequency of CYP337B3 in selected African countries.

Homozygous and heterozygous frequencies are shown.


S3 Fig. The frequency of CYP337B3 in China and Korea.

*Larvae from lab colonies derived from each field collection (20–50 individuals) and maintained at a population size of 300–500 adults per generation without exposure to any insecticide for 3–5 generations.


S4 Fig. The frequency of CYP337B3 in Australia and New Zealand.

Homozygous and heterozygous frequencies are shown.


S5 Fig. The frequency of CYP337B3 in Europe.

Homozygous and heterozygous frequencies are shown.


S6 Fig. Alignment of the crossover points for the various CYP337B3 alleles.

CYP337B1 is in red, CYP337B2 is green and the boxed sequence represents crossover point for each CYP337B3 allele.


S1 Table. Collection sites of H. armigera and H. zea from 18 different countries.


S3 Table. Sequence identifiers, gene names, origin and NCBI numbers used for the maximum likelihood estimate of phylogenetic relationships.


S4 Table. Sequencing and alignment statistics for the 12 individuals used to demonstrate the selective sweep around CYP337B3v1.


S1 File. Intron sequence data used for the maximum likelihood estimate of phylogenetic relationships.



We thank George Mironidis (IMBB-FORTH, Greece), Athanase Badolo (University of Ouagadougou), Juil Kim (National Institute of Horticultural and Herbal Science, Korea), and Muhammad Ashfaq (National Institute for Biotechnology and Genetic Engineering, Pakistan; now: Biodiversity Institute of Ontario, Canada) for sampling and providing insects for this study from Greece, Burkina Faso, Korea, and Pakistan, respectively; Hae Kyung Kwon (National Institute of Horticultural and Herbal Science; Korea) for technical assistance; and Domenica Schnabelrauch (MPI for Chemical Ecology, Germany) for sequencing. In Brazil, we thank Miguel Soria and Cecelia Czepak for the collection of specimens. In Northern Australia, we also thank Penny Goldsmith from Ord Co.


  1. 1. Feng HQ, Wu KM, Ni YX, Cheng DF, Guo YY. Return migration of Helicoverpa armigera (Lepidoptera: Noctuidae) during autumn in northern China. Bull Entomol Res. 2005;95(4):361–70. pmid:16048684.
  2. 2. Feng HQ, Wu KM, Ni YX, Cheng DF, Guo YY. High-altitude windborne transport of Helicoverpa armigera (Lepidoptera: Noctuidae) in mid-summer in northern China. J Insect Behav. 2005;18(3):335–49. WOS:000228854200005.
  3. 3. Pogue MG. A new synonym of Helicoverpa zea (Boddie) and differentiation of adult males of H. zea and H. armigera (Hübner) (Lepidoptera: Noctuidae: Heliothinae). Ann Entomol Soc Am. 2004;97(6):1222–6. WOS:000225335000011.
  4. 4. Venette RC DE, Zaspel Z, Heisler H, Larson M. Mini risk assessment, Old World bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae): Cooperative Agricultural Pest Survey, Animal and Plant Health Inspection Service, US Department of Agriculture; 2003. Available from:
  5. 5. Tay WT, Soria MF, Walsh T, Thomazoni D, Silvie P, Behere GT, et al. A Brave New World for an Old World Pest: Helicoverpa armigera (Lepidoptera: Noctuidae) in Brazil. PLoS ONE. 2013;8(11):art. e80134. WOS:000327308500116. pmid:24260345
  6. 6. Czepak C AK, Vivan LM, Guimaraes HO, Carvalhais T. Primeiro registro de ocorrência de Helicoverpa armigera (Hübner) Lepidoptera: Noctuidae) no Brasil. Pesquisa Agropecuâria Tropical 2013;43:110–3.
  7. 7. Hayden J, Brambila J. Florida Department of Agriculture and Consumer Services Division of Plant Industry; 2015 [03/12/2015]. Available from:
  8. 8. Arnemann J, James W, Walsh T, Guedes J, Smagghe G, Castiglioni E, et al. Mitochondrial DNA COI characterization of Helicoverpa armigera (Lepidoptera: Noctuidae) from Paraguay and Uruguay. Gen Mol Res. 2016;15:art. UNSP 15028292.
  9. 9. Gunning RV, Easton CS, Greenup LR, Edge VE. Pyrethroid Resistance in Heliothis armigera (Hübner) (Lepidoptera, Noctuidae) in Australia. J Econ Entomol. 1984;77(5):1283–7. WOS:A1984TQ93100045.
  10. 10. Heckel DG. Molecular genetics of insecticide resistance in Lepidoptera. In: MR Goldsmith, F Marec, editors. Molecular Biology and Genetics of the Lepidoptera. Boca Raton: CRC Press; 2010. p. 239–69.
  11. 11. Li XC, Schuler MA, Berenbaum MR. Molecular mechanisms of metabolic resistance to synthetic and natural xenobiotics. Annu Rev Entomol. 2007;52:231–53. WOS:000243653800013. pmid:16925478
  12. 12. Head DJ, McCaffery AR, Callaghan A. Novel mutations in the para-homologous sodium channel gene associated with phenotypic expression of nerve insensitivity resistance to pyrethroids in Heliothine lepidoptera. Insect Mol Biol. 1998;7(2):191–6. WOS:000072510700009. pmid:9535164
  13. 13. Dong K, Du YZ, Rinkevich F, Nomura Y, Xu P, Wang LX, et al. Molecular biology of insect sodium channels and pyrethroid resistance. Insect Biochem Mol Biol. 2014;50:1–17. WOS:000337780300001. pmid:24704279
  14. 14. Feyereisen R. Insect CYP genes and P450 enzymes. In: Gilbert LI, editor. Insect Molecular Biology and Biochemistry. London: Elsevier; 2012. p. 236–316.
  15. 15. Duangkaew P, Pethuan S, Kaewpa D, Boonsuepsakul S, Sarapusit S, Rongnoparut P. Characterization of Mosquito CYP6P7 and CYP6AA3: Differences in Substrate Preference and Kinetic Properties. Arch Insect Biochem Physiol. 2011;76(4):236–48. WOS:000288543400005. pmid:21308761
  16. 16. Mao WF, Schuler MA, Berenbaum MR. CYP9Q-mediated detoxification of acaricides in the honey bee (Apis mellifera). Proc Natl Acad Sci USA. 2011;108(31):12657–62. WOS:000293385700030. pmid:21775671
  17. 17. Feyereisen R. Arthropod CYPomes illustrate the tempo and mode in P450 evolution. Biochim Biophys Acta. 2011;1814(1):19–28. WOS:000285277900005. pmid:20601227
  18. 18. Joussen N, Agnolet S, Lorenz S, Schöne SE, Ellinger R, Schneider B, et al. Resistance of Australian Helicoverpa armigera to fenvalerate is due to the chimeric P450 enzyme CYP337B3. Proc Natl Acad Sci USA. 2012;109(38):15206–11. WOS:000309211000035. pmid:22949643
  19. 19. 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. WOS:000302132100036. pmid:22479665
  20. 20. Forrester NW, Cahill M, Bird LJ, Layland JK. Management of Pyrethroid and Endosulfan Resistance in Helicoverpa armigera (Lepidoptera, Noctuidae) in Australia. Bull Entomol Res. 1993:R1–132. WOS:A1993MK61800001.
  21. 21. Rasool A, Joussen N, Lorenz S, Ellinger R, Schneider B, Khan SA, et al. An independent occurrence of the chimeric P450 enzyme CYP337B3 of Helicoverpa armigera confers cypermethrin resistance in Pakistan. Insect Biochem Mol Biol. 2014;53:54–65. WOS:000342889600006. pmid:25064010
  22. 22. Han YC, Yu WT, Zhang WQ, Yang YH, Walsh T, Oakeshott JG, et al. Variation in P450-mediated fenvalerate resistance levels is not correlated with CYP337B3 genotype in Chinese populations of Helicoverpa armigera. Pestic Biochem Physiol. 2015;121:129–35. WOS:000356109700017. pmid:26047121
  23. 23. Leite NA, Alves-Pereira A, Correa AS, Zucchi MI, Omoto C. Demographics and Genetic Variability of the New World Bollworm (Helicoverpa zea) and the Old World Bollworm (Helicoverpa armigera) in Brazil. PLoS ONE. 2014;9(11):art. e113286. WOS:000345533200091. pmid:25409452
  24. 24. Mastrangelo T, Paulo DF, Bergamo LW, Morais EGF, Silva M, Bezerra-Silva G, et al. Detection and Genetic Diversity of a Heliothine Invader (Lepidoptera: Noctuidae) From North and Northeast of Brazil. J Econ Entomol. 2014;107(3):970–80. WOS:000337174300012. pmid:25026655
  25. 25. Behere GT, Tay WT, Russell DA, Kranthi KR, Batterham P. Population Genetic Structure of the Cotton Bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) in India as Inferred from EPIC-PCR DNA Markers. PLoS ONE. 2013;8(1):e53448. WOS:000314705800045. pmid:23326431
  26. 26. Anderson C, Tay, WT., McGaughran, A., Gordon, K., Walsh,TK. Population structure and gene flow in the global pest, Helicoverpa armigera. Mol Ecol. 2017;25:5296–311.
  27. 27. McCaffery AR. Resistance to insecticides in heliothine Lepidoptera: a global view. Philos Trans R Soc Lond, Ser B: Biol Sci. 1998;353(1376):1735–50. WOS:000076756200010.
  28. 28. Anderson CJ, Oakeshott JG, Tay WT, Gordon K, Zwick A, Walsh TK. Hybridization and gene flow in the mega-pest lineage of moth, Helicoverpa. Proc Natl Acad Sci USA. 2018.
  29. 29. Behere GT, Tay WT, Russell DA, Heckel DG, Appleton BR, Kranthi KR, et al. Mitochondrial DNA analysis of field populations of Helicoverpa armigera (Lepidoptera: Noctuidae) and of its relationship to H. zea. BMC Evol Biol. 2007;7:art. 117. WOS:000248497200001.
  30. 30. Olson-Manning CF, Wagner MR, Mitchell-Olds T. Adaptive evolution: evaluating empirical support for theoretical predictions. Nat Rev Genet. 2012;13(12):867–77. WOS:000311212500009. pmid:23154809
  31. 31. Tennessen JA, O'Connor TD, Bamshad MJ, Akey JM. The promise and limitations of population exomics for human evolution studies. Genome Biology. 2011;12(9):art. 127. WOS:000298926900015.
  32. 32. Pearce S, Clarke D, East P, Elfikh S, Gordon K, Jermiin L, et al. Genomic innovations, transcriptional plasticity and gene loss underlying the evolution and divergence of two highly polyphagous and invasive Helicoverpa pest species. BMC Biol. 2017;15:art. 63.
  33. 33. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. WOS:000268808600014. pmid:19505943
  34. 34. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–303. WOS:000281520400015. pmid:20644199
  35. 35. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27(15):2156–8. WOS:000292778700023. pmid:21653522
  36. 36. Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer; 2009. 212 p.
  37. 37. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic Local Alignment Search Tool. J Mol Biol. 1990;215(3):403–10. WOS:A1990ED16700008. pmid:2231712
  38. 38. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol Biol Evol. 2013;30(4):772–80. WOS:000317002300004. pmid:23329690
  39. 39. Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. Mol Biol Evol. 2015;32(1):268–74. WOS:000350050200025. pmid:25371430
  40. 40. Bouckaert R, Heled J, Kuhnert D, Vaughan T, Wu CH, Xie D, et al. BEAST 2: A Software Platform for Bayesian Evolutionary Analysis. PLoS Comp Biol. 2014;10(4):e1003537. WOS:000336507500022.
  41. 41. Rambaut A, Suchard, M.A., Xie, D. & Drummond, A.J. Tracer v1.6 2014. Available from:
  42. 42. Hohenlohe PA, Phillips PC, Cresko WA. Using Population Genomics to Detect Selection in Natural Populations: Key Concepts and Methodological Considerations. Int J Plant Sci. 2010;171(9):1059–71. WOS:000284000800012. pmid:21218185
  43. 43. Nadeau NJ, Whibley A, Jones RT, Davey JW, Dasmahapatra KK, Baxter SW, et al. Genomic islands of divergence in hybridizing Heliconius butterflies identified by large-scale targeted sequencing. Philos Trans R Soc Lond, Ser B: Biol Sci. 2012;367(1587):343–53. WOS:000298659600002. pmid:22201164
  44. 44. Wood HM, Grahame JW, Humphray S, Rogers J, Butlin RK. Sequence differentiation in regions identified by a genome scan for local adaptation. Mol Ecol. 2008;17(13):3123–35. WOS:000256922000007. pmid:18510587
  45. 45. Brower AVZ. Rapid morphological radiation and convergence among races of the butterfly Heliconius erato inferred from patterns of mitochondrial DNA evolution. Proc Natl Acad Sci U S A. 1994;91(14):6491–5. PubMed Central PMCID: PMCPMC44228. pmid:8022810
  46. 46. Gunning RV, Easton CS, Balfe ME, Ferris IG. Pyrethroid Resistance Mechanisms in Australian Helicoverpa armigera. Pestic Sci. 1991;33(4):473–90. WOS:A1991GY50600009.
  47. 47. Gunning RV. Bioassay for detecting pyrethroid nerve insensitivity in Australian Helicoverpa armigera (Lepidoptera: Noctuidae). J Econ Entomol. 1996;89(4):816–9. WOS:A1996VA95000006.
  48. 48. Gunning RV, Moores GD, Devonshire AL. Esterases and esfenvalerate resistance in Australian Helicoverpa armigera (Hübner) Lepidoptera: Noctuidae. Pestic Biochem Physiol. 1996;54(1):12–23. WOS:A1996UG15700004.
  49. 49. Gunning RV, Moores GD, Devonshire AL. Esterase inhibitors synergise the toxicity of pyrethroids in Australian Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Pestic Biochem Physiol. 1999;63(1):50–62. WOS:000078849600005.
  50. 50. Pittendrigh B, Aronstein K, Zinkovsky E, Andreev O, Campbell B, Daly J, et al. Cytochrome P450 genes from Helicoverpa armigera: Expression in a pyrethroid-susceptible and -resistant strain. Insect Biochem Mol Biol. 1997;27(6):507–12. WOS:A1997XV97600004. pmid:9304792
  51. 51. Daly JC, Fisk JH. Inheritance of Metabolic Resistance to the Synthetic Pyrethroids in Australian Helicoverpa armigera (Lepidoptera, Noctuidae). Bull Entomol Res. 1992;82(1):5–12. WOS:A1992HR51200002.
  52. 52. Heckel DG, Gahan LJ, Daly JC, Trowell S. A genomic approach to understanding Heliothis and Helicoverpa resistance to chemical and biological insecticides. Philos Trans R Soc Lond, Ser B: Biol Sci. 1998;353(1376):1713–22. WOS:000076756200007.
  53. 53. Ranasinghe C, Hobbs AA. Induction of cytochrome P450 CYP6B7 and cytochrome b(5) mRNAs from Helicoverpa armigera (Hübner) by pyrethroid insecticides in organ culture. Insect Mol Biol. 1999;8(4):443–7. WOS:000084470900003. pmid:10620039
  54. 54. Ranasinghe C, Campbell B, Hobbs AA. Over-expression of cytochrome P450 CYP6B7 mRNA and pyrethroid resistance in Australian populations of Helicoverpa armigera (Hübner). Pestic Sci. 1998;54(3):195–202. WOS:000076844800002.
  55. 55. Wee CW, Lee SF, Robin C, Heckel DG. Identification of candidate genes for fenvalerate resistance in Helicoverpa armigera using cDNA-AFLP. Insect Mol Biol. 2008;17(4):351–60. WOS:000257709500003. pmid:18651917
  56. 56. Ranasinghe C, Hobbs AA. Isolation and characterisation of a cytochrome b5 cDNA clone from Helicoverpa armigera (Hübner): possible involvement of cytochrome b5 in cytochrome P450 CYP6B7 activity towards pyrethroids. Insect Biochem Mol Biol. 1999;29(2):145–51. WOS:000079394900007. pmid:10196737
  57. 57. Pinto J, Lynd A, Vicente JL, Santolamazza F, Randle NP, Gentile G, et al. Multiple Origins of Knockdown Resistance Mutations in the Afrotropical Mosquito Vector Anopheles gambiae. PLoS ONE. 2007;2(11):e1243. WOS:000207459300024. pmid:18043750
  58. 58. Rinkevich FD, Hedtke SM, Leichter CA, Harris SA, Su C, Brady SG, et al. Multiple Origins of kdr-type Resistance in the House Fly, Musca domestica. PLoS ONE. 2012;7(12):e52761. WOS:000313051500058. pmid:23285178
  59. 59. Newcomb RD, Gleeson DM, Yong CG, Russell RJ, Oakeshott JG. 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. 2005;60(2):207–20. WOS:000227070100007. pmid:15785849
  60. 60. Arnemann J. Molecular tools to identify and study invasive pests in Brazil. PhD Thesis. Ghent, Belgium: Ghent University; 2015.
  61. 61. Hardwick DF. The corn earworm complex. Memoirs of the Entomological Society of Canada. 1965;40:1–247.
  62. 62. Laster ML, Hardee DD. Intermating Compatibility between North American Helicoverpa zea and Heliothis armigera (Lepidoptera, Noctuidae) from Russia. J Econ Entomol. 1995;88(1):77–80. WOS:A1995QF56400012.
  63. 63. Laster ML, Sheng CF. Search for Hybrid Sterility for Helicoverpa zea in Crosses between the North American Heliothis zea and Helicoverpa armigera (Lepidoptera, Noctuidae) from China. J Econ Entomol. 1995;88(5):1288–91. WOS:A1995RY81000032.