Data from: Detection of genetic incompatibilities in non-model systems using simple genetic markers: hybrid breakdown in the haplodiploid spider mite Tetranychus evansi

When two related species interbreed, their hybrid offspring frequently suffer from reduced fitness. The genetics of hybrid incompatibility are described by the Bateson–Dobzhansky–Muller (BDM) model, where fitness is reduced by epistatic interactions between alleles of heterospecific origin. Unfortunately, most empirical evidence for the BDM model comes from a few well-studied model organisms, restricting our genetic understanding of hybrid incompatibilities to limited taxa. These systems are predominantly diploid and incompatibility is often complete, which complicates the detection of recessive allelic interactions and excludes the possibility to study viable or intermediate stages. Here, we advocate research into non-model organisms with haploid or haplodiploid reproductive systems and incomplete hybrid incompatibility because (1) dominance is absent in haploids and (2) incomplete incompatibility allows comparing affected with unaffected individuals. We describe a novel two-locus statistic specifying the frequency of individuals for which two alleles co-occur. This approach to studying BDM incompatibilities requires genotypic characterization of hybrid individuals, but not genetic mapping or genome sequencing. To illustrate our approach, we investigated genetic causes for hybrid incompatibility between differentiated lineages of the haplodiploid spider mite Tetranychus evansi, and show that strong, but incomplete, hybrid breakdown occurs. In addition, by comparing the genotypes of viable hybrid males and inviable hybrid male eggs for eight microsatellite loci, we show that nuclear and cytonuclear BDM interactions constitute the basis of hybrid incompatibility in this species. Our approach opens up possibilities to study BDM interactions in non-model taxa, and may give further insight into the genetic mechanisms behind hybrid incompatibility.,Adjusted residual haplotype count R scriptThis R script shows how the regression of adjusted residual haplotype count on allele indicator was performedKnegt_etal_Adjusted_residuals.RDataset for regression of adjusted residual haplotype count against allele indicator - comparison viable I versus inviable IThis dataset was used for the regression of adjusted residual haplotype count against allele indicator, in the comparison of viable hybrids cytotype I versus inviable hybrids cytotype I. See the R script for details of the analysis.Knegt_etal_Adjusted_residuals1.csvDataset for regression of adjusted residual haplotype count against allele indicator - comparison viable II versus inviable IIThis dataset was used for the regression of adjusted residual haplotype count against allele indicator, in the comparison of viable hybrids cytotype II versus inviable hybrids cytotype II. See the R script for details of the analysis.Knegt_etal_Adjusted_residuals2.csvR script for the comparison of allele frequencies between hybrid groupsKnegt_etal_Allele_frequencies.RAllele frequencies - FisherDataset used for comparison of allele frequencies between hybrid groups: Fisher exact tests of independence. See R script for details.Knegt_etal_Allele_frequencies1.csvAllele frequencies - CMHDataset used for comparison of allele frequencies between hybrid groups: Cochran-Mantel-Haenszel tests. See R script for details.Knegt_etal_Allele_frequencies2.csvR script for analysis of F1 hatch rateKnegt_etal_F1_hatch_rate.RF1 hatch ratesKnegt_etal_F1_hatch_rate.csvR script for analysis of F1 ovipositionKnegt_etal_F1_oviposition.RF1 ovipositionKnegt_etal_F1_oviposition.csvR script for analysis of F1 sex ratioKnegt_etal_F1_sex_ratio.RF1 sex ratioKnegt_etal_F1_sex_ratio.csvR script for analysis of F2 hatch ratesKnegt_etal_F2_hatch_rate.RF2 hatch rateKnegt_etal_F2_hatch_rate.csvR script for analysis of parental ovipositionKnegt_etal_Parental_oviposition.RParental ovipositionKnegt_etal_Parental_oviposition.csvR script for CMH tests among hybrid groups using their haplotype counts as inputKnegt_etal_Haplotype_counts.RHaplotype countsKnegt_etal_Haplotype_counts1.csv,