Dominant point mutation in a tetraspanin gene associated with field-evolved resistance of cotton bollworm to transgenic Bt cotton

Lin Jin; Jing Wang; Fang Guan; Jianpeng Zhang; Shan Yu; Shaoyan Liu; Yuanyuan Xue; Lingli Li; Shuwen Wu; Xingliang Wang; Yihua Yang; Heba Abdelgaffar; Juan Luis Jurat-Fuentes; Bruce E. Tabashnik; Yidong Wu

doi:10.1073/pnas.1812138115

Edited by May R. Berenbaum, University of Illinois at Urbana–Champaign, Urbana, IL, and approved October 5, 2018 (received for review July 15, 2018)

Significance

Crops genetically engineered to produce insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) kill some major pests and reduce use of insecticide sprays. However, evolution of pest resistance to Bt proteins decreases these benefits. Better understanding of the genetic basis of resistance to Bt crops is urgently needed to address this problem. We discovered that a point mutation in the cotton bollworm, one of the world’s most voracious pests, confers dominantly inherited resistance to the Bt protein produced by transgenic cotton grown in China. This mutation increased 100-fold in frequency from 2006 to 2016 in China. Proactive tracking of this mutation may improve management of resistance and enhance sustainability of Bt cotton for millions of smallholder farmers in China.

Abstract

Extensive planting of crops genetically engineered to produce insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) has suppressed some major pests, reduced insecticide sprays, enhanced pest control by natural enemies, and increased grower profits. However, rapid evolution of resistance in pests is reducing these benefits. Better understanding of the genetic basis of resistance to Bt crops is urgently needed to monitor, delay, and counter pest resistance. We discovered that a point mutation in a previously unknown tetraspanin gene in the cotton bollworm (Helicoverpa armigera), a devastating global pest, confers dominant resistance to Cry1Ac, the sole Bt protein produced by transgenic cotton planted in China. We found the mutation using a genome-wide association study, followed by fine-scale genetic mapping and DNA sequence comparisons between resistant and susceptible strains. CRISPR/Cas9 knockout of the tetraspanin gene restored susceptibility to a resistant strain, whereas inserting the mutation conferred 125-fold resistance in a susceptible strain. DNA screening of moths captured from 23 field sites in six provinces of northern China revealed a 100-fold increase in the frequency of this mutation, from 0.001 in 2006 to 0.10 in 2016. The correspondence between the observed trajectory of the mutation and the trajectory predicted from simulation modeling shows that the dominance of the mutation accelerated adaptation. Proactive identification and tracking of the tetraspanin mutation demonstrate the potential for genomic analysis, gene editing, and molecular monitoring to improve management of resistance.

Genetically engineered crops that produce insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) have been planted globally on a cumulative total of over 930 million hectares since 1996 (1). The benefits of these transgenic Bt crops include pest suppression, reduced insecticide use, enhanced biological control, and increased farmer profits (2 ⇓⇓⇓⇓–7). However, increasingly rapid evolution of resistance to Bt crops by pests has eroded these benefits (8 ⇓–10). Better understanding of the genetic basis of resistance to Bt crops is urgently needed to monitor, delay, and counter pest resistance.

The most widely adopted strategy for delaying pest resistance to Bt crops entails “refuges” of non-Bt host plants that enable survival of susceptible insects to mate with resistant insects (8). Refuges are especially effective for delaying resistance that is inherited as a recessive trait, because the matings between rare homozygous resistant insects and relatively abundant homozygous susceptible insects from refuges produce heterozygous progeny that are killed by the Bt crop (11). Because such recessive resistance can be suppressed more readily, nonrecessive resistance is more likely to evolve in the field (8). Nonetheless, most research has focused on recessive resistance conferred by mutations that disrupt binding of Bt toxins in the larval midgut to receptors such as cadherin and ATP-binding cassette transporter proteins (12 ⇓⇓⇓⇓–17), whereas little is known about the genetic basis of dominant resistance. Moreover, previous efforts to achieve proactive molecular monitoring of Bt resistance have had limited success because the mutations that increase markedly in the field are usually identified after resistance has caused severe control failures (13, 14, 16).

Here, we report the discovery and proactive monitoring of a point mutation in a tetraspanin gene that confers dominant resistance to Bt toxin Cry1Ac in the cotton bollworm, Helicoverpa armigera. This lepidopteran is one of the world’s most devastating crop pests and has recently invaded the Americas (18, 19). We analyzed H. armigera from northern China, where Bt cotton producing Cry1Ac has been planted by millions of smallholder farmers since 1997 (20, 21). The percentage of H. armigera larvae resistant to Cry1Ac increased significantly there, from 0.93% in 2010 to 5.5% in 2013 (21). This has been categorized as an “early warning of resistance,” because the percentage of resistant individuals did not exceed 50% and reduced efficacy of Bt cotton in the field was not reported (8, 21).

Previous work showed the resistance to Cry1Ac in the AY2 strain of H. armigera from northern China was autosomal, dominant, and 1,200-fold relative to the susceptible strain SCD, based on the concentration of Cry1Ac killing 50% of larvae (LC₅₀) (20). The dominance parameter, h, which varies from 0 for completely recessive to 1 for completely dominant, was previously reported for AY2 as 1.0 based on larval survival at the diagnostic toxin concentration (1 μg of Cry1Ac per square centimeter of diet) (20). In this study, we calculated h as 0.79 (SI Appendix, Supplementary Methods), based on a more comprehensive approach using data from previous bioassays on Bt cotton for survival from neonate to adult, sex ratio, and fertile eggs per female (21).

Here, a genome-wide association study (GWAS) with 48 resistant larvae and 48 susceptible larvae from a mass backcross experiment using AY2 and SCD revealed a highly significant association with resistance to Cry1Ac for four of 2,097 single-nucleotide polymorphisms (SNPs), all from 10.48 to 11.15 Mbp on chromosome 10 (Fig. 1A and SI Appendix, Table S1). Next, we conducted fine-scale mapping using seven other SNPs from 10.58 to 11.01 Mbp on chromosome 10 and 363 larvae that were derived from three single-pair backcross families and survived exposure to the diagnostic toxin concentration (SI Appendix, Fig. S1B). The results demonstrate a highly significant association between resistance and each of these seven SNPs (P < 10⁻⁶⁰ for each SNP; Fig. 1B and SI Appendix, Table S2).

Fig. 1.

Identification of the mutation in HaTSPAN1 associated with dominant resistance to Cry1Ac in H. armigera. (A) GWAS based on 2,097 SNPs in the AY2 strain. The horizontal line shows the threshold for significant association (P < 5 × 10⁻⁸). The two most significant points have the same probability (10⁻¹¹) and nearly identical positions in chromosome 10 (SI Appendix, Table S1); they are shifted slightly apart so that both are visible. (B) SNP markers and HaTSPAN1 locus on HaChr10. (C) HaTSPAN1 protein with four transmembrane domains (TM1–TM4), two extracellular loops (EC1 and EC2), and the L31S mutation in TM1. (D) Amino acid sequence alignment of the TM1 domain of HaTSPAN1 in five strains of H. armigera [two with the wild-type (WT) sequence (the susceptible SCD strain and the SCD-r1 strain with recessive cadherin-based resistance) and three with the L31S mutation (MUT; AY2, SCD423, and QX7 with dominant resistance)] and homologous genes from nine other lepidopteran species from seven families: Helicoverpa zea (Noctuidae); Papilio machaon, Papilio polytes, Papilio xuthus (Papilionidae); Danaus plexippus (Nymphalidae); Pectinophora gossypiella (Gelechiidae); Amyelois transitella (Pyralidae); Plutella xylostella (Plutellidae); and Bombyx mori (Bombycidae).

We narrowed our search to the 17 of 21 genes between 10.62 and 10.87 Mbp on chromosome 10 that are expressed in the midgut of final instar larvae (SI Appendix, Table S3). We designed specific primers to amplify by PCR the complete ORF of these 17 genes from the cDNA of the resistant AY2 strain and the susceptible SCD strain. Comparison of the predicted amino acid sequences between the two strains identified a single amino acid substitution (L31S) in a tetraspanin gene of AY2, and no other mutations in the 17 genes that differed consistently between strains. We named this gene HaTSPAN1 (GenBank accession nos. MH514007 for SCD and MH514008 for AY2).

Tetraspanins are a family of proteins that are important in cell migration, signal transduction, and intracellular trafficking, as well as infection by diverse pathogens, including bacteria (22, 23). The full-length transcript of HaTSPAN1 from SCD encodes a protein of 304 amino acids with 63.4% identity to the 23-kDa integral membrane protein of Bombyx mori (GenBank accession no. XP_004933861). The predicted structure of the HaTSPAN1 protein includes characteristic features of tetraspanins: four transmembrane segments (TM1–TM4), one small and one large extracellular loop (EC1 and EC2, respectively), short intracellular amino and carboxyl tails, and the signature CCG motif (Fig. 1C).

The L31S substitution occurs in the third amino acid of TM1 (Fig. 1 C and D) and is encoded by DNA near the 3′-end of exon 1 (Fig. 2A). Comparison of cDNA sequences between AY2 and SCD indicates the L31S substitution is encoded by a single nucleotide substitution: T92C. Analysis of the 363 backcross progeny that survived exposure to the diagnostic concentration in the fine-scale mapping experiment (SI Appendix, Fig. S1B) confirmed a strong association between T92C and resistance (345 heterozygous for T92C, 18 homozygous for wild type; χ² = 298.6, df = 1, P = 5 × 10⁻⁶⁶). Survival of the 18 larvae that lacked the T92C mutation apparently was conferred by other mutations, nongenetic factors, or both.

Fig. 2.

CRISPR/Cas9 editing of HaTSPAN1. (A) Red arrows show positions of mutations introduced with CRISPR/Cas9. (B) Portion of the wild-type (WT) sequence and a single-stranded oligodeoxynucleotide (ssODN) used as donor DNA to introduce four single-base substitutions (red letters in boxes) in exon 1. The T92C mutation yields the L31S amino acid substitution. The other three substitutions are synonymous and serve as markers, including one in the PAM sequence (highlighted in green) that also prevents double cutting. The sgRNA target sequence is highlighted in yellow. (C) Chromatograms of direct sequencing of PCR products for determining genotype.

The leucine at position 31 predicted in wild-type HaTSPAN1 is conserved in this protein and homologous proteins from susceptible strains of 10 species representing seven families of Lepidoptera (SI Appendix, Fig. S2) and in the SCD-r1 strain of H. armigera, which has recessive resistance to Cry1Ac conferred by a cadherin mutation (Fig. 1D). Conversely, the T92C mutation yielding the L31S substitution occurs in AY2 and two other strains of H. armigera from northern China (SCD423 and QX7) that have dominant resistance to Cry1Ac (Fig. 1D). We detected the T92C mutation in all 36 larvae tested from SCD423 (23 homozygotes and 13 heterozygotes) and in all 28 larvae tested from QX7 (23 homozygotes and five heterozygotes).

The results from GWAS, fine-scale mapping, and sequence comparisons reported above show a strong association between T92C and resistance to Cry1Ac in several strains of H. armigera. However, like nearly all related previous work, they do not demonstrate causation. Here, we used gene editing with CRISPR/Cas9 to test the hypothesis that the T92C mutation in HaTSPAN1 causes resistance to Cry1Ac. First, we created knockout strain AY2-KO in which a 4-bp insertion in exon 4 (Fig. 2A) introduced a premature stop codon expected to produce a truncated, inactive HaTSPAN1 protein. Of 835 AY2 eggs injected with a single-guide RNA (sgRNA1; SI Appendix, Table S4) and Cas9 protein, 78% hatched and 66% of the neonates developed to adults (G₀). Reciprocal mass crosses between moths from G₀ and SCD produced the next generation (G₁). Among the 96 G₁ pupae genotyped with nondestructive exuviate-based PCR, 74% were heterozygous for indel mutations in HaTSPAN1. From these heterozygotes, five females and four males harboring the 4-bp insertion were pooled to generate the G₂ moths. Of the G₂ moths genotyped by exuviate-based PCR, 27 of 122 (22%) were homozygous for the 4-bp insertion. We pooled these 27 moths to establish the homozygous knockout strain AY2-KO. AY2-KO was as susceptible to Cry1Ac as the susceptible SCD strain (Fig. 3 and SI Appendix, Table S5), indicating the knockout of HaTSPAN1 eliminated resistance.

Fig. 3.

Responses to Cry1Ac by five strains of H. armigera. AY2, resistant; AY2-KO, AY2 with knockout of HaTSPAN1; SCD, susceptible; SCD423, resistance introgressed into SCD; SCD-KI, SCD with knock-in of the T92C mutation in HaTSPAN1. The resistance ratio is the LC₅₀ for a strain divided by the LC₅₀ for the SCD strain. The resistance ratio did not differ significantly between SCD (1) and AY2-KO (0.9). Details are provided in SI Appendix, Table S5.

Next, we used CRISPR/Cas9 to introduce the T92C mutation into SCD and create knock-in strain SCD-KI. Of 1,800 SCD eggs injected with sgRNA2, Cas9, and a single-stranded oligodeoxynucleotide, 26 hatched, and 17 of the neonates developed to adults. Reciprocal mass crosses between these G₀ adults and SCD produced G₁ larvae that had a survival rate of 1.9% (95 of 4,896) at the diagnostic concentration of Cry1Ac. The 95 survivors were reared to adults and mass-crossed to generate G₂ larvae that had a survival rate of 25% (581 of 2,304) at the diagnostic concentration. The 288 largest of these survivors (≥10 mg) were reared to pupation and nondestructively genotyped: 157 were homozygous for the T92C mutation, and the rest were heterozygous. The 157 homozygous mutant moths were mass-crossed to establish the SCD-KI strain. Relative to SCD, SCD-KI had 125-fold resistance to Cry1Ac (Fig. 3 and SI Appendix, Table S5), demonstrating that the T92C mutation can cause resistance to Cry1Ac. Survival at the diagnostic concentration was 81% (n = 48) for SCD-KI, 45% (n = 288) for the first generation (F₁) progeny from crosses between SCD-KI and SCD, and 0% for SCD (n = 48), which yields h = 0.56 for SCD-KI.

Relative to SCD-KI, resistance to Cry1Ac was higher and more dominant in AY2. At the diagnostic concentration, AY2 survival was 96% and h was 1.0 (20). Also, the LC₅₀ of Cry1Ac was ninefold greater for AY2 than SCD-KI (Fig. 3 and SI Appendix, Table S5). These results suggest that one or more factors other than the T92C mutation boosted dominance and resistance in AY2 relative to SCD-KI. However, AY2-KO had no resistance to Cry1Ac, indicating that CRISPR/Cas9 introduction of the mutation yielding a truncated HaTSPAN1 protein completely restored susceptibility. Considered together, these results imply that one or more factors in AY2 other than the T92C mutation can interact with that mutation to increase dominance and resistance, but such factors confer little or no resistance in the absence of the T92C mutation. One such factor could be the 2.7-fold increased transcription of HaTSPAN1 in AY2 relative to SCD (P < 10⁻¹⁹; SI Appendix, Table S3), which might increase resistance in combination with T92C but is not expected to confer resistance without T92C.

The AY2 strain had 10-fold cross-resistance to Bt toxin Cry2Ab (SI Appendix, Table S5), which does not share binding sites with Cry1Ac in H. armigera (24). AY2-KO was not significantly cross-resistant to Cry2Ab, indicating that the knockout of HaTSPAN1 restored susceptibility to Cry2Ab. However, SCD-KI also was not significantly cross-resistant to Cry2Ab. These results suggest that one or more factors in AY2 interact with the T92C mutation to cause cross-resistance to Cry2Ab, but they do not confer significant cross-resistance without the T92C mutation.

Unlike the markedly reduced binding of Cry1Ac in the SCD-r1 strain of H. armigera and many other strains with recessive resistance to Bt toxins (12), substantially reduced binding of Cry1Ac was not associated with the dominant resistance of AY2 (SI Appendix, Fig. S3). This supports the idea that the T92C mutation involves a gain of function, rather than a loss of function, and suggests interference with other steps in the toxic pathway (25).

To test the hypothesis that the T92C mutation in HaTSPAN1 contributes to resistance to Bt cotton in the field, we used two methods to track its frequency in ethanol-preserved H. armigera moths captured from 2006 to 2016 at 23 sites in six provinces of northern China (SI Appendix, Fig. S4). In the first of two screening methods, we tested moths in pools to enable efficient screening, using amplicon sequencing. We tested a total of 5,996 moths captured in seven different years (2006, 2010, and 2012–2016) by screening pools, with a mean of 102 moths per pool (SE = 8). In the second method, to check the effectiveness of screening pools, we used the more rigorous and labor-intensive approach of testing moths individually. The 2,259 moths tested individually were a subset of the moths captured during 2006, 2010, 2013, and 2016.

Consistent with the hypothesis that the T92C mutation contributes to resistance to Bt cotton in the field, both methods revealed a significant increase in the frequency of the T92C mutation from 2006 to 2016 (Mann–Whitney U test, P < 0.005 for each method). Based on screening pooled moths, the frequency of T92C increased 100-fold, from 0.001 [95% confidence interval (CI): 0.0–0.003] in 2006 to 0.10 (95% CI: 0.05–0.15) in 2016 (Fig. 4 and SI Appendix, Table S6). Based on screening moths individually, the frequency increased from 0.0 in 2006 (none detected, n = 454 moths) to 0.093 (95% CI: 0.06–0.12) in 2016 (SI Appendix, Table S7). For the 4 y that both methods were applied, the results are correlated between the two methods (r = 0.98, df = 2, P = 0.019; SI Appendix, Fig. S5), and no significant difference occurred between them in any year (Mann–Whitney U test, P > 0.6 for each year). Based on pooled moths, the percentage of populations evaluated that had at least one T92C mutation increased from 12% (one of eight) in 2006, to 50% (three of six) in 2010, to 88% (seven of eight) in 2016 (SI Appendix, Table S6).

Fig. 4.

Observed versus predicted frequency of the T92C mutation in H. armigera in northern China. The predicted values are from simulations of a population genetic model with dominance (h) set to hypothetical values of 0 (recessive) or 0.4 (intermediate dominance), or the empirically determined value of 0.79 (dominant). The observed values are means (with 95% CIs) based on DNA screening of pooled moths. For all simulations, the observed frequency for 2006 of 0.001 (95% CI: 0.0–0.003) was used as the initial frequency (i.e., for 2006; SI Appendix, Table S8).

To evaluate the importance of the dominance of the resistance conferred by the T92C mutation, we compared the observed trajectory of this mutation with the trajectories predicted by simulation modeling under three different assumptions: the empirically determined dominant resistance (h = 0.79) and hypothetical scenarios with either recessive inheritance of resistance (h = 0) or intermediate dominance (h = 0.4) (Fig. 4 and SI Appendix, Table S8). With dominant resistance, the predicted trajectory corresponded well with the observed trajectory, but with h = 0 or 0.4, the predicted frequency increased much more slowly than the observed frequency (Fig. 4). A sensitivity analysis varying assumptions about dominance and the fitness cost associated with resistance shows these results are robust (SI Appendix, Fig. S6), confirming the critical role of the dominance of the T92C mutation in accelerating the evolution of resistance. Moreover, among survivors of exposure to the diagnostic concentration of Cry1Ac, the percentage of individuals that were either heterozygous or homozygous for T92C increased from 44% in 2011 to 70% in 2016 (SI Appendix, Fig. S7). These data demonstrate a faster increase in frequency for T92C relative to the other mutations contributing to field-evolved resistance, including the recessive cadherin mutations (26).

Although the T92C frequency in H. armigera increased 100-fold to 0.10 in 2016, reduced efficacy of Bt cotton against this pest has not been reported yet in northern China. However, analysis of the observed T92C frequency data from 2012 to 2016 indicates that if the current trajectory continues, the T92C frequency in northern China will exceed 0.50 by 2023 (linear regression of log-transformed data: r² = 0.91, df = 3, P = 0.01). The tracking of T92C reported here may spur changes to delay resistance, while tracking it in the future could help to determine if such changes are effective. Options for slowing resistance include switching to transgenic cotton that augments Cry1Ac with one or two unrelated Bt toxins (Cry2Ab and Vip3Aa) or RNA interference (27, 28), increasing the abundance of non-Bt host plant refuges, and integrating diverse tactics for pest control (8, 29).

As far as we know, previous work has not reported interactions between Bt toxins and tetraspanins. Web of Science searches identified over 24,000 papers on Bt and over 5,000 on tetraspanins, but none on both. More work is needed to determine the function of wild-type HaTSPAN1, how the T92C mutation confers resistance, and if mutations in tetraspanin genes confer dominant resistance to Bt toxins in other insects. With resistance an urgent global threat to food security and human health (30), the results here demonstrate the potential for genomic analysis, gene editing, and molecular monitoring to facilitate more sustainable pest control.

Materials and Methods

Insect Strains.

We used seven strains of H. armigera: resistant strains AY2, QX7, SCD423, SCD-r1, and SCD-KI and susceptible strains SCD and AY2-KO. All strains were maintained as described previously, with larvae reared on an artificial diet and adults provided with 10% sugar solution (31). The two primary strains of H. armigera analyzed here are the previously described resistant strain AY2 and susceptible strain SCD. AY2 was started in 2011 by pairing a susceptible SCD female with a resistant male from Anyang in the Henan province of northern China (20). The descendants from this single-pair mating were selected with increasing concentrations of Cry1Ac (20). SCD was started with insects from Côte D’Ivoire (Ivory Coast) over 30 y ago and has been maintained in the laboratory without exposure to Bt toxins or other insecticides (32). In diet overlay bioassays with Cry1Ac, the LC₅₀ was 1,200-fold higher for AY2 than SCD and resistance at the diagnostic concentration was dominant (h = 1) (20).

We also analyzed three other previously described resistant strains: QX7 and SCD423 with dominant resistance and SCD-r1 with recessive resistance. In parallel with AY2, QX7 was started in 2011 by pairing a susceptible SCD female with a resistant male from Qiuxian in the Hebei province of northern China, followed by selection of subsequent generations with Cry1Ac (20). Resistance to Cry1Ac in QX7 was 460-fold relative to SCD and dominant (h = 1) (20). SCD423 originated from crosses between SCD and resistant strain AY423, which was established from an F₂ screen of a field population from Anyang in 2009 (26). Resistance to Cry1Ac in AY423 was 660-fold relative to SCD and dominant (h = 0.64) (26). The resistance to Cry1Ac in AY423 was introgressed into SCD by four crosses with SCD, followed by selection with Cry1Ac (26). Although the resistance to Cry1Ac was similar in SCD423 and AY423, SCD423 shares ca. 94% of its genetic background with SCD. The previously described SCD-r1 strain had 500-fold resistance to Cry1Ac caused by introgressing the recessive r1 cadherin allele (h = 0) into SCD (32).

Here, we created the susceptible AY2-KO strain and the resistant SCD-KI strain by CRISPR/Cas9-mediated editing. AY2-KO was created by knocking out HaTSPAN1 from AY2, and SCD-KI was created by knocking in the T92C mutation into SCD.

Bt Toxins and Bioassays.

For bioassays, we used activated Cry1Ac toxin purchased from Marianne Pusztai-Carey (Case Western Reserve University, Cleveland, OH) and Cry2Ab protoxin generously provided by the Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China. We used diet overlay bioassays as described previously (20). Toxin stock suspensions were diluted with a 0.01 M (pH 7.4) phosphate buffer solution (PBS). Liquid artificial diet (900 μL) was dispensed into each well (surface area = 2 cm²) of a 24-well plate. After the diet cooled and solidified, 100 μL of PBS containing the desired concentration of Cry1Ac or Cry2Ab was applied evenly to the diet surface in each well and allowed to dry. A single larva was placed in each well. Larvae were kept at 26 °C (±1°), 60% (±10%) relative humidity, and 16 h light: 8 h dark. We followed established protocols for each toxin (31). For Cry1Ac, we tested second instars that had been starved for 4 h and recorded mortality after 5 d. For Cry2Ab, we tested unfed neonates (24 h old) and recorded mortality after 7 d. At the end of the bioassays, larvae were scored as dead if they died or weighed less than 5 mg.

GWAS of Resistance to Cry1Ac in AY2.

Backcross.

We conducted a mass cross with 30 females from the resistant AY2 strain and 30 males from the susceptible SCD strain (SI Appendix, Fig. S1A). Crossing over occurs only in male Lepidoptera (33, 34), and resistance to Cry1Ac in AY2 is dominant (20). Accordingly, we generated backcross progeny (BC₁) by allowing mating between 30 females from SCD and 30 F₁ males from AY2 × SCD.

Phenotyping by bioassay.

To distinguish between susceptible and resistant individuals, 240 larvae from BC₁ were reared on diet treated with 0.25 μg of Cry1Ac per square centimeter of diet and 240 were reared on diet with 10-fold that concentration (SI Appendix, Fig. S1A). After 5 d, 53 live larvae exposed to the lower concentration that weighed <5 mg were scored as susceptible (BC₁-S), while 97 live larvae exposed to the higher concentration that weighed >10 mg were scored as resistant (BC₁-R). Larvae from each group were reared to fifth instars on untreated diet for DNA extraction.

DNA extraction.

We dissected 48 midguts from fifth instars from each group, washed them in ice-cold 0.15 M NaCl solution, and extracted DNA from each midgut by the phenol/chloroform method. Each sample was digested individually in 500 μL of DNA lysis buffer [100 mM Tris, 50 mM EDTA, 200 mM NaCl, 1% SDS (pH 8.0)] for 10 min at 56 °C. We purified DNA by extraction three times with phenol/chloroform (1:1 vol/vol), and then once with phenol. After centrifugation at 12,000 × g for 10 min, the supernatant was collected and DNA was precipitated using 50 μL of NH₄COOH (pH 7.5) and 800 μL of 100% ethanol. The DNA pellet was washed with 500 μL of 70% ethanol, resuspended in 80 μL of TE buffer [1 mM EDTA, 10 mM Tris (pH 8.0)], and stored at −20 °C.

Genotyping by sequencing.

DNA was digested by the Pstl restriction enzyme, which recognizes a 6-bp sequence (5′-CTGCAG-3′). Genomic DNA libraries were prepared for genotyping by sequencing by ligating the digested DNA to unique nucleotide barcode adapters for each individual and a common adapter for all individuals. Next, we pooled the DNA samples and conducted PCR amplification (35). Single-end sequencing (85-bp reads) of the 96-plex library per flow cell channel was performed on a Genome Analyzer II (Illumina, Inc.). We performed an initial quality check using FastQC (www.bioinformatics.babraham.ac.uk/projects/fastqc/). We used Process_Radtags built-in Stacks (36) for demultiplexing and cleaning of sequencing reads. We mapped high-quality reads to the H. armigera genome (37) using the Burrows–Wheeler Aligner (38) and called SNPs using the Genome Analysis Toolkit (39). We assigned 2,097 segregating SNPs to the 31 chromosomes of H. armigera.

Association between resistance and SNPs.

We performed GWAS using PLINK with stringent quality-control filters (40). We used individuals and SNPs that met three criteria: individuals with 50% of all called SNPs, loci that were present in 50% of individuals, and a minor allele frequency of >0.03. We analyzed 2,097 informative SNPs from 93 individuals to compare allele frequencies between BC₁-R and BC₁-S using PLINK. We obtained P values from Fisher’s exact test and produced a Manhattan plot of the results using the software package “qqman” (41).

Fine-Scale Mapping of Resistance.

For fine-scale mapping of resistance within H. armigera chromosome 10 (HaChr10), we conducted a second backcross (BC₂) (SI Appendix, Fig. S1B). As with BC₁ described above, we started with a mass cross between 30 females from AY2 and 30 males from SCD (SI Appendix, Fig. S1B). Backcross families (BC₂) were obtained by crossing F₁ (AY2 × SCD) males with SCD females in single pairs. The progeny from three single-pair BC₂ families were allowed to feed on diet that had the diagnostic toxin concentration (1 μg of Cry1Ac per square centimeter of diet). We named the group of 363 survivors BC₂-R. Total genomic DNA was extracted individually, as described above, from each of the 363 BC₂-R survivors and the parents of the three BC₂ families.

Based on the genome sequence data of H. armigera (37), we designed specific primers in the exons of functional genes spanning 10.58–11.01 Mbp on HaChr10. PCR amplification of the genomic DNA and sequencing were performed for each parent of the three BC₂ families. As informative markers, we used each of the seven SNPs that were heterozygous in the father (F₁ of AY2 × SCD) and homozygous in the mother (SCD). We compared the observed frequency of each of these markers with the expected 1:1 frequency if they segregated independent of resistance.

Larval Midgut RNA Abundance for 21 Genes from 10.62 to 10.87 Mbp on Chromosome 10.

We extracted total midgut RNA from final instars of SCD and AY2 using TRIzol (Invitrogen). Purified RNA was treated with DNase I to eliminate DNA contamination. From each strain, we obtained three replicates with 30 midguts per replicate.

The mRNA was isolated from total RNA with oligo (dT) magnetic beads, and fragmented to generate reads that covered the entire length of the transcripts using fragmentation buffer on a thermomixer. Subsequently, cDNA libraries (one library per sequencing sample) were constructed using classical Illumina protocols (42). Briefly, these cleaved mRNA fragments were primed randomly and subjected to the synthesis of the first-strand and second-strand cDNAs. Single-nucleotide A was added to obtain short fragments, the adapters were ligated to short fragments, and PCR was then performed. The quality of total RNA, mRNA, and cDNA libraries was checked with an Agilent 2100 Bioanalyzer instrument. The cDNA libraries were sequenced on an Illumina HiSeq 2000 platform.

The raw reads were cleaned by omitting adapter sequences, reads with more than 5% ambiguous bases N, and low-quality sequences with more than 15% of nucleotides with a Phred quality score of <20. The clean reads were assembled de novo using Trinity software (43). We used SOAPaligner software for short oligonucleotide alignment to remove sequences that were not covered by any sample reads. The assembled transcripts were processed through the TGICL Gene Indices clustering tools to eliminate sequence redundancy and further assemble sequences to generate effective unigenes (44). We assigned a gene ID to each of the 21 unigenes based on homology to the genome database of H. armigera (37) identified with Blastx software.

Sequencing Candidate Genes in the Region of Chromosome 10 Associated with Resistance.

Based on the gene sequences in the genome database of H. armigera (37), we designed specific primers in the 5′ and 3′ UTRs to amplify the complete ORF in AY2 and SCD of the 17 candidate genes that are expressed in the midguts of fifth instars and occur from 10.62 to 10.87 Mbp on chromosome 10. The PCR products were sequenced directly. The amino acid sequence was predicted from the complete ORF sequence and aligned between AY2 and SCD using DNAssist 2.2 software (https://dnassist.en.softonic.com/).

Predicted HaTSPAN1 Protein Structure.

We used the amino acid sequence of HaTSPAN1 to predict the protein’s structure, including TM helices using TMHMM Server v2.0 (www.cbs.dtu.dk/services/TMHMM/). The conserved domains were analyzed by Blastp to the Conserved Domain Database of NCBI (https://www.ncbi.nlm.nih.gov/cdd).

Detection of the T92C Mutation of HaTSPAN1.

We used the phenol/chloroform method described above to prepare genomic DNA from individual larvae (fourth or fifth instars) or moths from three strains (AY2, SCD423, and QX7) and from the 363 survivors of exposure to the diagnostic concentration in the fine-scale mapping experiment (SI Appendix, Fig. S1B). Specific primers TM1-F (forward) and TM1-R (reverse) (SI Appendix, Table S4) amplified a fragment of ∼500 bp containing exon 1 and partial intron 1 to detect the T92C mutation of HaTSPAN1. The PCR mixture (20 μL) consisted of 10 μL of 2× PrimeSTAR Max Premix (TaKaRa), 1 μL of genomic DNA, 1 μL of 10 μM forward primer (TM1-F), 1 μL of 10 μM reverse primer (TM1-R), and 7 μL of ddH₂O. The PCR conditions were as follows: 94 °C for 2 min followed by 35 cycles of 94 °C for 10 s, 55 °C for 30 s, and 72 °C for 1 min, followed by a final extension at 72 °C for 10 min. The PCR products of the expected size were directly sequenced with the forward primer TM1-F by TSINGKE.

HaTSPAN1 Amino Acid Sequence Alignment in H. armigera and Nine Other Species of Lepidoptera.

The sequence alignment in Fig. 1D shows the region of TM1 of the HaTSPAN1 protein containing the L31S mutation from five strains of H. armigera (mutant: AY2, QX7, and SCD423; wild type: SCD and SCD-r1) and homologs of HaTSPAN1 (with GenBank accession nos. MH514007 and MH514008) from Helicoverpa zea (NFMG01022088.1), Papilio machaon (XP_014368154.1), Papilio polytes (XP_013141160.1), Papilio xuthus (XP_013182388.1), Danaus plexippus (EHJ70576.1), Pectinophora gossypiella (JAT80322.1), Amyelois transitella (XP_013190067.1), Plutella xylostella (XP_011564311.1), and B. mori (XP_004933861).

Additional details of the methods for CRISPR/Cas9 editing of HaTSPAN1, binding of Cry1Ac, DNA screening of field-captured moths, and computer simulations are provided in SI Appendix, Supplementary Methods.

Acknowledgments

We thank Y. Carrière, G. Davidowitz, A. Mathias, L. Matzkin, and S. Morin for suggestions that improved the paper. This work was supported by the National Natural Science Foundation of China (Grant 31530060), the Ministry of Agriculture and Rural Affairs of China (Grant 2016ZX08012-004), the Agriculture and Food Research Initiative Program (Grant 2018-67013-27821), and the Biotechnology Risk Assessment Research Grant Program (Grant 2014-33522-22215) from the US Department of Agriculture National Institute of Food and Agriculture.

Footnotes

↵¹L.J. and J.W. contributed equally to this work.
↵²To whom correspondence should be addressed. Email: wyd{at}njau.edu.cn.

Author contributions: Y.Y. and Y.W. designed research; L.J., J.W., F.G., J.Z., S.Y., S.L., Y.X., L.L., H.A., and J.L.J.-F. performed research; S.W., X.W., and Y.Y. contributed new reagents/analytic tools; L.J., J.W., F.G., J.Z., B.E.T., and Y.W. analyzed data; B.E.T. conducted modeling; and L.J., J.W., B.E.T., and Y.W. wrote the paper.
Conflict of interest statement: B.E.T. is coauthor of a patent on modified Bacillus thuringiensis toxins, “Suppression of Resistance in Insects to Bacillus thuringiensis Cry Toxins, Using Toxins That Do Not Require the Cadherin Receptor” (patent nos. CA2690188A1, CN101730712A, EP2184293A2, EP2184293A4, EP2184293B1, WO2008150150A2, and WO2008150150A3). Amvac, Bayer CropScience, Dow AgroSciences, DuPont Pioneer, Monsanto, and Syngenta did not provide funding to support this work, but may be affected financially by publication of this paper and have funded other work by B.E.T.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1812138115/-/DCSupplemental.

Published under the PNAS license.

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1. Anderson CJ, et al.
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↵
1. Jin L, et al.
(2013) Dominant resistance to Bt cotton and minor cross-resistance to Bt toxin Cry2Ab in cotton bollworm from China. Evol Appl 6:1222–1235.
OpenUrl CrossRef PubMed
↵
1. Jin L, et al.
(2015) Large-scale test of the natural refuge strategy for delaying insect resistance to transgenic Bt crops. Nat Biotechnol 33:169–174.
OpenUrl PubMed
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1. Monk PN,
2. Partridge LJ
(2012) Tetraspanins: Gateways for infection. Infect Disord Drug Targets 12:4–17.
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1. Florin L,
2. Lang T
(2018) Tetraspanin assemblies in virus infection. Front Immunol 9:1140.
OpenUrl CrossRef
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1. Hernández-Rodríguez CS,
2. Van Vliet A,
3. Bautsoens N,
4. Van Rie J,
5. Ferré J
(2008) Specific binding of Bacillus thuringiensis Cry2A insecticidal proteins to a common site in the midgut of Helicoverpa species. Appl Environ Microbiol 74:7654–7659.
OpenUrl Abstract/FREE Full Text
↵
1. Pardo-López L,
2. Soberón M,
3. Bravo A
(2013) Bacillus thuringiensis insecticidal three-domain Cry toxins: Mode of action, insect resistance and consequences for crop protection. FEMS Microbiol Rev 37:3–22.
OpenUrl CrossRef PubMed
↵
1. Zhang H, et al.
(2012) Diverse genetic basis of field-evolved resistance to Bt cotton in cotton bollworm from China. Proc Natl Acad Sci USA 109:10275–10280.
OpenUrl Abstract/FREE Full Text
↵
1. Carrière Y,
2. Fabrick JA,
3. Tabashnik BE
(2016) Can pyramids and seed mixtures delay resistance to Bt crops? Trends Biotechnol 34:291–302.
OpenUrl CrossRef PubMed
↵
1. Ni M, et al.
(2017) Next-generation transgenic cotton: Pyramiding RNAi and Bt counters insect resistance. Plant Biotechnol J 15:1204–1213.
OpenUrl
↵
1. Tabashnik BE, et al.
(2010) Suppressing resistance to Bt cotton with sterile insect releases. Nat Biotechnol 28:1304–1307.
OpenUrl CrossRef PubMed
↵
1. Gould F,
2. Brown ZS,
3. Kuzma J
(2018) Wicked evolution: Can we address the sociobiological dilemma of pesticide resistance? Science 360:728–732.
OpenUrl Abstract/FREE Full Text
↵
1. Zhang H, et al.
(2011) Early warning of cotton bollworm resistance associated with intensive planting of Bt cotton in China. PLoS One 6:e22874.
OpenUrl CrossRef PubMed
↵
1. Yang YH, et al.
(2009) Introgression of a disrupted cadherin gene enables susceptible Helicoverpa armigera to obtain resistance to Bacillus thuringiensis toxin Cry1Ac. Bull Entomol Res 99:175–181.
OpenUrl CrossRef PubMed
↵
1. Traut W
(1997) A study of recombination, formation of chiasmata and synaptonemal complexes in female and male meiosis of Ephestia kuehniella (Lepidoptera). Genetica 47:135–142.
OpenUrl
↵
1. Heckel DG,
2. Gahan LJ,
3. Liu YB,
4. Tabashnik BE
(1999) Genetic mapping of resistance to Bacillus thuringiensis toxins in diamondback moth using biphasic linkage analysis. Proc Natl Acad Sci USA 96:8373–8377.
OpenUrl Abstract/FREE Full Text
↵
1. Elshire RJ, et al.
(2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6:e19379.
OpenUrl CrossRef PubMed
↵
1. Catchen JM,
2. Amores A,
3. Hohenlohe P,
4. Cresko W,
5. Postlethwait JH
(2011) Stacks: Building and genotyping loci de novo from short-read sequences. G3 (Bethesda) 1:171–182.
OpenUrl CrossRef
↵
1. Pearce SL, et al.
(2017) Genomic innovations, transcriptional plasticity and gene loss underlying the evolution and divergence of two highly polyphagous and invasive Helicoverpa pest species. BMC Biol 15:63.
OpenUrl
↵
1. Li H,
2. Durbin R
(2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760.
OpenUrl CrossRef PubMed
↵
1. McKenna A, et al.
(2010) The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303.
OpenUrl Abstract/FREE Full Text
↵
1. Purcell S, et al.
(2007) PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575.
OpenUrl CrossRef PubMed
↵
1. Turner SD
(May 14, 2014) qqman: An R package for visualizing GWAS results using Q-Q and Manhattan plots. bioRxiv:10.1101/005165.
↵
1. van Dijk EL,
2. Jaszczyszyn Y,
3. Thermes C
(2014) Library preparation methods for next-generation sequencing: Tone down the bias. Exp Cell Res 322:12–20.
OpenUrl CrossRef PubMed
↵
1. Grabherr MG, et al.
(2011) Trinity: Reconstructing a full-length transcriptome without a genome from RNA-seq data. Nat Biotechnol 29:644–652.
OpenUrl CrossRef PubMed
↵
1. Pertea G, et al.
(2003) TIGR Gene Indices clustering tools (TGICL): A software system for fast clustering of large EST datasets. Bioinformatics 19:651–652.
OpenUrl CrossRef PubMed

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Proceedings of the National Academy of Sciences: 115 (46)

Table of Contents

Submit

[1] ↵
James C
(2017) Global Status of Commercialized Biotech/GM Crops in 2017: Biotech Crop Adoption Surges as Economic Benefits Accumulate in 22 Years (International Service for the Acquisition of Agri-biotech Applications, Ithaca, NY), ISAAA Brief No. 53.

[2] James C

[3] ↵
Hutchison WD, et al.
(2010) Areawide suppression of European corn borer with Bt maize reaps savings to non-Bt maize growers. Science 330:222–225.
OpenUrl Abstract/FREE Full Text

[4] Hutchison WD, et al.

[5] ↵
Downes S,
Walsh T,
Tay WT
(2016) Bt resistance in Australian insect pest species. Curr Opin Insect Sci 15:78–83.
OpenUrl

[6] Downes S,

[7] Walsh T,

[8] Tay WT

[9] ↵
Dively GP, et al.
(2018) Regional pest suppression associated with widespread Bt maize adoption benefits vegetable growers. Proc Natl Acad Sci USA 115:3320–3325.
OpenUrl Abstract/FREE Full Text

[10] Dively GP, et al.

[11] ↵
Lu Y,
Wu K,
Jiang Y,
Guo Y,
Desneux N
(2012) Widespread adoption of Bt cotton and insecticide decrease promotes biocontrol services. Nature 487:362–365.
OpenUrl CrossRef PubMed

[12] Lu Y,

[13] Wu K,

[14] Jiang Y,

[15] Guo Y,

[16] Desneux N

[17] ↵
National Academies of Sciences, Engineering, and Medicine
(2016) Genetically Engineered Crops: Experiences and Prospects (National Academies Press, Washington, DC).

[18] National Academies of Sciences, Engineering, and Medicine

[19] ↵
Wu KM,
Lu YH,
Feng HQ,
Jiang YY,
Zhao JZ
(2008) Suppression of cotton bollworm in multiple crops in China in areas with Bt toxin-containing cotton. Science 321:1676–1678.
OpenUrl Abstract/FREE Full Text

[20] Wu KM,

[21] Lu YH,

[22] Feng HQ,

[23] Jiang YY,

[24] Zhao JZ

[25] ↵
Tabashnik BE,
Carrière Y
(2017) Surge in insect resistance to transgenic crops and prospects for sustainability. Nat Biotechnol 35:926–935.
OpenUrl CrossRef PubMed

[26] Tabashnik BE,

[27] Carrière Y

[28] ↵
Gassmann AJ, et al.
(2014) Field-evolved resistance by western corn rootworm to multiple Bacillus thuringiensis toxins in transgenic maize. Proc Natl Acad Sci USA 111:5141–5146.
OpenUrl Abstract/FREE Full Text

[29] Gassmann AJ, et al.

[30] ↵
Tabashnik BE
(2016) Tips for battling billion-dollar beetles. Science 354:552–553.
OpenUrl Abstract/FREE Full Text

[31] Tabashnik BE

[32] ↵
Gould F
(1998) Sustainability of transgenic insecticidal cultivars: Integrating pest genetics and ecology. Annu Rev Entomol 43:701–726.
OpenUrl CrossRef PubMed

[33] Gould F

[34] ↵
Wu Y
(2014) Detection and mechanisms of resistance evolved in insects to Cry toxins from Bacillus thuringiensis. Adv Insect Physiol 47:297–342.
OpenUrl CrossRef

[35] Wu Y

[36] ↵
Mathew LG, et al.
(2018) ABC transporter mis-splicing associated with resistance to Bt toxin Cry2Ab in laboratory- and field-selected pink bollworm. Sci Rep 8:13531.
OpenUrl

[37] Mathew LG, et al.

[38] ↵
Banerjee R, et al.
(2017) Mechanism and DNA-based detection of field-evolved resistance to transgenic Bt corn in fall armyworm (Spodoptera frugiperda). Sci Rep 7:10877.
OpenUrl CrossRef

[39] Banerjee R, et al.

[40] ↵
Walsh T,
James B,
Chakroun M,
Ferré J,
Downes S
(2018) Isolating, characterising and identifying a Cry1Ac resistance mutation in field populations of Helicoverpa punctigera. Sci Rep 8:2626.
OpenUrl

[41] Walsh T,

[42] James B,

[43] Chakroun M,

[44] Ferré J,

[45] Downes S

[46] ↵
Fabrick JA, et al.
(2014) Alternative splicing and highly variable cadherin transcripts associated with field-evolved resistance of pink bollworm to Bt cotton in India. PLoS One 9:e97900.
OpenUrl CrossRef PubMed

[47] Fabrick JA, et al.

[48] ↵
Peterson B,
Bezuidenhout CC,
Van den Berg J
(2017) An overview of mechanisms of Cry toxin resistance in lepidopteran insects. J Econ Entomol 110:362–377.
OpenUrl CrossRef

[49] Peterson B,

[50] Bezuidenhout CC,

[51] Van den Berg J

[52] ↵
Kriticos DJ, et al.
(2015) The potential distribution of invading Helicoverpa armigera in North America: Is it just a matter of time? PLoS One 10:e0119618, and erratum (2015) 10:e0133224.
OpenUrl

[53] Kriticos DJ, et al.

[54] ↵
Anderson CJ, et al.
(2018) Hybridization and gene flow in the mega-pest lineage of moth, Helicoverpa. Proc Natl Acad Sci USA 115:5034–5039.
OpenUrl Abstract/FREE Full Text

[55] Anderson CJ, et al.

[56] ↵
Jin L, et al.
(2013) Dominant resistance to Bt cotton and minor cross-resistance to Bt toxin Cry2Ab in cotton bollworm from China. Evol Appl 6:1222–1235.
OpenUrl CrossRef PubMed

[57] Jin L, et al.

[58] ↵
Jin L, et al.
(2015) Large-scale test of the natural refuge strategy for delaying insect resistance to transgenic Bt crops. Nat Biotechnol 33:169–174.
OpenUrl PubMed

[59] Jin L, et al.

[60] ↵
Monk PN,
Partridge LJ
(2012) Tetraspanins: Gateways for infection. Infect Disord Drug Targets 12:4–17.
OpenUrl CrossRef PubMed

[61] Monk PN,

[62] Partridge LJ

[63] ↵
Florin L,
Lang T
(2018) Tetraspanin assemblies in virus infection. Front Immunol 9:1140.
OpenUrl CrossRef

[64] Florin L,

[65] Lang T

[66] ↵
Hernández-Rodríguez CS,
Van Vliet A,
Bautsoens N,
Van Rie J,
Ferré J
(2008) Specific binding of Bacillus thuringiensis Cry2A insecticidal proteins to a common site in the midgut of Helicoverpa species. Appl Environ Microbiol 74:7654–7659.
OpenUrl Abstract/FREE Full Text

[67] Hernández-Rodríguez CS,

[68] Van Vliet A,

[69] Bautsoens N,

[70] Van Rie J,

[71] Ferré J

[72] ↵
Pardo-López L,
Soberón M,
Bravo A
(2013) Bacillus thuringiensis insecticidal three-domain Cry toxins: Mode of action, insect resistance and consequences for crop protection. FEMS Microbiol Rev 37:3–22.
OpenUrl CrossRef PubMed

[73] Pardo-López L,

[74] Soberón M,

[75] Bravo A

[76] ↵
Zhang H, et al.
(2012) Diverse genetic basis of field-evolved resistance to Bt cotton in cotton bollworm from China. Proc Natl Acad Sci USA 109:10275–10280.
OpenUrl Abstract/FREE Full Text

[77] Zhang H, et al.

[78] ↵
Carrière Y,
Fabrick JA,
Tabashnik BE
(2016) Can pyramids and seed mixtures delay resistance to Bt crops? Trends Biotechnol 34:291–302.
OpenUrl CrossRef PubMed

[79] Carrière Y,

[80] Fabrick JA,

[81] Tabashnik BE

[82] ↵
Ni M, et al.
(2017) Next-generation transgenic cotton: Pyramiding RNAi and Bt counters insect resistance. Plant Biotechnol J 15:1204–1213.
OpenUrl

[83] Ni M, et al.

[84] ↵
Tabashnik BE, et al.
(2010) Suppressing resistance to Bt cotton with sterile insect releases. Nat Biotechnol 28:1304–1307.
OpenUrl CrossRef PubMed

[85] Tabashnik BE, et al.

[86] ↵
Gould F,
Brown ZS,
Kuzma J
(2018) Wicked evolution: Can we address the sociobiological dilemma of pesticide resistance? Science 360:728–732.
OpenUrl Abstract/FREE Full Text

[87] Gould F,

[88] Brown ZS,

[89] Kuzma J

[90] ↵
Zhang H, et al.
(2011) Early warning of cotton bollworm resistance associated with intensive planting of Bt cotton in China. PLoS One 6:e22874.
OpenUrl CrossRef PubMed

[91] Zhang H, et al.

[92] ↵
Yang YH, et al.
(2009) Introgression of a disrupted cadherin gene enables susceptible Helicoverpa armigera to obtain resistance to Bacillus thuringiensis toxin Cry1Ac. Bull Entomol Res 99:175–181.
OpenUrl CrossRef PubMed

[93] Yang YH, et al.

[94] ↵
Traut W
(1997) A study of recombination, formation of chiasmata and synaptonemal complexes in female and male meiosis of Ephestia kuehniella (Lepidoptera). Genetica 47:135–142.
OpenUrl

[95] Traut W

[96] ↵
Heckel DG,
Gahan LJ,
Liu YB,
Tabashnik BE
(1999) Genetic mapping of resistance to Bacillus thuringiensis toxins in diamondback moth using biphasic linkage analysis. Proc Natl Acad Sci USA 96:8373–8377.
OpenUrl Abstract/FREE Full Text

[97] Heckel DG,

[98] Gahan LJ,

[99] Liu YB,

[100] Tabashnik BE

[101] ↵
Elshire RJ, et al.
(2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6:e19379.
OpenUrl CrossRef PubMed

[102] Elshire RJ, et al.

[103] ↵
Catchen JM,
Amores A,
Hohenlohe P,
Cresko W,
Postlethwait JH
(2011) Stacks: Building and genotyping loci de novo from short-read sequences. G3 (Bethesda) 1:171–182.
OpenUrl CrossRef

[104] Catchen JM,

[105] Amores A,

[106] Hohenlohe P,

[107] Cresko W,

[108] Postlethwait JH

[109] ↵
Pearce SL, et al.
(2017) Genomic innovations, transcriptional plasticity and gene loss underlying the evolution and divergence of two highly polyphagous and invasive Helicoverpa pest species. BMC Biol 15:63.
OpenUrl

[110] Pearce SL, et al.

[111] ↵
Li H,
Durbin R
(2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760.
OpenUrl CrossRef PubMed

[112] Li H,

[113] Durbin R

[114] ↵
McKenna A, et al.
(2010) The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303.
OpenUrl Abstract/FREE Full Text

[115] McKenna A, et al.

[116] ↵
Purcell S, et al.
(2007) PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575.
OpenUrl CrossRef PubMed

[117] Purcell S, et al.

[118] ↵
Turner SD
(May 14, 2014) qqman: An R package for visualizing GWAS results using Q-Q and Manhattan plots. bioRxiv:10.1101/005165.

[119] Turner SD

[120] ↵
van Dijk EL,
Jaszczyszyn Y,
Thermes C
(2014) Library preparation methods for next-generation sequencing: Tone down the bias. Exp Cell Res 322:12–20.
OpenUrl CrossRef PubMed

[121] van Dijk EL,

[122] Jaszczyszyn Y,

[123] Thermes C

[124] ↵
Grabherr MG, et al.
(2011) Trinity: Reconstructing a full-length transcriptome without a genome from RNA-seq data. Nat Biotechnol 29:644–652.
OpenUrl CrossRef PubMed

[125] Grabherr MG, et al.

[126] ↵
Pertea G, et al.
(2003) TIGR Gene Indices clustering tools (TGICL): A software system for fast clustering of large EST datasets. Bioinformatics 19:651–652.
OpenUrl CrossRef PubMed

[127] Pertea G, et al.

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Dominant point mutation in a tetraspanin gene associated with field-evolved resistance of cotton bollworm to transgenic Bt cotton

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Abstract