| Literature DB >> 29740041 |
Lex Flagel1, Young Wha Lee1, Humphrey Wanjugi1, Shilpa Swarup1, Alana Brown1, Jinling Wang2, Edward Kraft2,3, John Greenplate1, Jeni Simmons4, Nancy Adams4, Yanfei Wang1, Samuel Martinelli5, Jeffrey A Haas1, Anilkumar Gowda1, Graham Head6.
Abstract
The use of Bt proteins in crops has revolutionized insect pest management by offering effective season-long control. However, field-evolved resistance to Bt proteins threatens their utility and durability. A recent example is field-evolved resistance to Cry1Fa and Cry1A.105 in fall armyworm (Spodoptera frugiperda). This resistance has been detected in Puerto Rico, mainland USA, and Brazil. A S. frugiperda population with suspected resistance to Cry1Fa was sampled from a maize field in Puerto Rico and used to develop a resistant lab colony. The colony demonstrated resistance to Cry1Fa and partial cross-resistance to Cry1A.105 in diet bioassays. Using genetic crosses and proteomics, we show that this resistance is due to loss-of-function mutations in the ABCC2 gene. We characterize two novel mutant alleles from Puerto Rico. We also find that these alleles are absent in a broad screen of partially resistant Brazilian populations. These findings confirm that ABCC2 is a receptor for Cry1Fa and Cry1A.105 in S. frugiperda, and lay the groundwork for genetically enabled resistance management in this species, with the caution that there may be several distinct ABCC2 resistances alleles in nature.Entities:
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Year: 2018 PMID: 29740041 PMCID: PMC5940765 DOI: 10.1038/s41598-018-25491-9
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1The diagram shows the amino acid (top) and codon (bottom) identities for the Wild Type and R1 mutant alleles of SfABCC2. The R1 mutant has a 2 bp GC insertion (highlighted in red) in the 740th codon, which causes a premature stop codon to arise at codon 747.
Figure 2Schematic of representation of the SfABCC2 gene. The two-marker system (SNP and +GC) used to diagnose the three segregating haplotypes is presented on the structure of the SfABCC2 gene, along with the rubric used to identify each haplotype. This schematic applies to Family 1, however in Family 26 the S allele behaved dominantly, rather than codominantly, in R2S backgrounds, making it impossible to separate SS from R2S genotypes. The intron/exon structure of SfABCC2 is given, and the protein domains are color-coded and shown below their corresponding exons. The location of the R2 insert and splice disruption sites on exon 4 is also marked. Finally, three numbered magenta triangles mark the location of the putatively paralogous peptides detected in in the resistant individuals using LC-MS/MS. Their numbering is as follows 1) FFDTNPSGR, 2) SSLISALFR, and 3) SKISIIPQEPVLFSASLR.
SYTOX green fluorescence averages and standard deviations given in relative fluorescence units (RFU), for the wild type (WT) and R1 allele, and a GUS control.
| Toxin Core | Target Receptor | Average RFU | St. Dev. RFU | N |
|---|---|---|---|---|
| Cry1A.105 | WT | 14928 | 1352 | 3 |
| Cry1A.105 | R1 | 1225 | 98 | 3 |
| Cry1A.105 | GUS control | 493 | 108 | 3 |
| Cry1Fa | WT | 4283 | 550 | 3 |
| Cry1Fa | R1 | 260 | 44 | 3 |
| Cry1Fa | GUS control | 88 | 8 | 3 |
Increased SYTOX Green fluorescence is associated with greater cell death.
Proportion among eight individuals from the BenzonS and JuanaDiazR population that were positive for 31 peptides from the SfABCC2 protein.
| Annotated Sequence | Susceptible Proportion Pos. | Resistant Proportion Pos. |
|---|---|---|
| [R].MSQVSVGDVAGGK.[L] | 0.75 | 0 |
| [K].YSPDDPPVLK.[D] | 0.25 | 0 |
| [K].VSEGGTNFSMGQR.[Q] | 0.875 | 0 |
| [R].ALEQVELKESIPALDYK.[V] | 0.75 | 0 |
| [R].ALEQVELK.[E] | 0.625 | 0 |
| [K].MYAWEKPFQLVVK.[A] | 1 | 0 |
| [K].DMGAMDELLPR.[S] | 0.375 | 0 |
| [R].SKISIIPQEPVLFSASLR.[Y] | 1 | 0.125 |
| [R].ENILFGLEYNVAK.[Y] | 0.75 | 0 |
| [R].QSGSLKWDVLGR.[Y] | 0.25 | 0 |
| [R].AYEMSALR.[K] | 0.625 | 0 |
| [K].SSLISALFR.[L] | 0.75 | 0.875 |
| [R].YWFEEVAIAEREDRDPSLWK.[A] | 1 | 0 |
| [R].IKLMSEIINGIQVIK.[M] | 0.5 | 0 |
| [R].IQGFLLLDER.[S] | 0.75 | 0 |
| [K].TSLLQLLLR.[E] | 0.75 | 0 |
| [R].SDIQITPK.[V] | 0.375 | 0 |
| [K].LMSEIINGIQVIK.[M] | 0.625 | 0 |
| [R].LSDITGSIKIDGLDTQGIAK.[K] | 0.25 | 0 |
| [R].FFDTNPSGR.[V] | 0.875 | 0.5 |
| [R].DVEEDDLIVPSK.[K] | 0.75 | 0 |
| [K].IAASSLLFR.[K] | 0.625 | 0 |
| [K].ILIMDEATANVDPQTDALIQK.[T] | 0.125 | 0 |
| [K].DLNFAIK.[S] | 0.5 | 0 |
| [K].IDGLDTQGIAK.[K] | 0.5 | 0 |
| [R].GVSLSGGQR.[AX] | 0.625 | 0 |
| [R].ASENLHNTIYEK.[L] | 0.75 | 0 |
| [K].VNATWADLNDNKEMTLK.[N] | 0.25 | 0 |
| [R].ILFEVAK.[T] | 1 | 0 |
| [K].SDDEEGEEKVQVLEAEER.[Q] | 0.75 | 0 |
| [K].LVNLLSNDVAR.[F] | 0.25 | 0 |
Figure 3Mating scheme and expected genotype frequencies for Family 1 and 26, which had a heterozygous R1R2 resistant parent.
F2 genotype and phenotype results for family #1 (top panel) and #26 (bottom panel).
| Observed Genotype | Family 1 | |||
|---|---|---|---|---|
| Resistant Individuals | Susceptible Individuals | Expected Freq | Observed Freq | |
| R1R1 | 40 | 0 | 0.0625 | 0.0917 |
| R1R2 | 57 | 0 | 0.125 | 0.1307 |
| R2R2 | 24 | 0 | 0.0625 | 0.0550 |
| R1S | 5 | 125 | 0.25 | 0.2982 |
| R2S | 1 | 89 | 0.25 | 0.2064 |
| SS | 0 | 95 | 0.25 | 0.2179 |
| Total | 127 | 309 | ||
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| R1R1 | 34 | 0 | 0.0625 | 0.0658 |
| R1R2 | 61 | 2 | 0.125 | 0.1219 |
| R2R2 | 40 | 1 | 0.0625 | 0.0793 |
| R1S | 1 | 107 | 0.25 | 0.2089 |
| R2S | 0 | 0 | 0.25 | 0 |
| SS | 2 | 269 | 0.25 | 0.5242 |
| Total | 138 | 379 | ||
The genotype categories are listed on the rows, while phenotypic results are given in the second and third columns. The fourth and fifth columns list the Hardy-Weinberg expected genotype frequencies and the observed frequencies, respectively, for each genotype.
Geographic sampling of +GC allele. All Brazilian populations of S. frugiperda were subjected to Cry1A.105 assays and their survivorship is given. The column labled N gives the number of individuals genotyped.
| Country | Location (State) | Year |
| +GC Allele Freq. | % Survivorship (Cry1A.105) |
|---|---|---|---|---|---|
| Brazil | Campo Grande (MS) | 2016 | 10 | 0 | 57.5 |
| Brazil | Campo Verde (MT) | 2016 | 10 | 0 | 43.6 |
| Brazil | Casa Branca (SP) | 2016 | 10 | 0 | 7.8 |
| Brazil | Casa Branca (SP) | 2016 | 10 | 0 | 18.9 |
| Brazil | Ivatuba (PR) | 2016 | 10 | 0 | 15.0 |
| Brazil | Londrina (PR) | 2016 | 10 | 0 | 52.6 |
| Brazil | Não-me-Toque (RS) | 2016 | 10 | 0 | 4.0 |
| Brazil | Palotina (PR) | 2016 | 10 | 0 | 25.3 |
| Brazil | Ponta Grossa (PR) | 2016 | 10 | 0 | 31.2 |
| Brazil | Rio Verde (GO) | 2016 | 10 | 0 | 25.9 |
| Brazil | Santa Helena de Goiás (GO) | 2016 | 10 | 0 | 19.0 |
| Brazil | Santo Ângelo (RS) | 2016 | 10 | 0 | 56.3 |
| Brazil | Sapezal (MT) | 2016 | 4 | 0 | 46.0 |
| Brazil | Seara (SC) | 2016 | 10 | 0 | 0.0 |
| Brazil | Água Fria de Goiás (GO) | 2016 | 10 | 0 | 38.8 |
| USA | Benzon-JuanaDiazR (PR) | 2010 | 48 | 0.77 | NA |
| USA | Juana Diaz (PR) | 2015 | 177 | 0.88 | NA |
| USA | Isabella (PR) | 2015 | 49 | 0.48 | NA |
| USA | Unknown (PR)* | 2011 | 43 | 0.32 | NA |
*Samples provided by Fengneng Huang[4].