Genomic prediction in insects: a case study on wing morphology traits in the jewel wasp Nasonia vitripennis
Background: Biological control is a sustainable strategy to combat agricultural pests. Yet, due to legislation, importing non-native biocontrol agents is increasingly restricted. Thus, selective breeding of biocontrol traits of native species is suggested to enhance performance of existing biocontrol agents. Genomic prediction is a new alternative to exploit genetic variation for improving biocontrol efficacy. This study aims to establish proof-of-principle for genomic prediction in insect biocontrol agents, using wing morphology traits in the parasitoid Nasonia vitripennis Walker (Pteromalidae) as a model.Methods: We performed genomic prediction using a Genomic Best Linear Unbiased Prediction (GBLUP) model, using a total of 1,230 individuals with 8,639 SNPs generated by genotyping-by-sequencing (GBS). We used individuals from two generations from the outbred HVRx population, 717 individuals from generation G169 and 513 from generation G172. To assess genomic prediction accuracy, we used across-generation validation: forward validation for G172 from G169, backward in time validation for G169 from G172, and also 5-fold cross-validation, randomly using one fifth of the population as validiation and the others as training groups.Results: For size-related traits, including tibia length, wing length, width, and second moment wing area, the accuracy of genomic prediction was close to zero in both across-generation validations, but much higher in 5-fold cross-validation (ranging 0.54-0.68). For the shape-related trait wing aspect ratio, a high accuracy was found for all three validation strategies, with 0.47 for across-generation forward validation, 0.65 for across-generation backward validation, and 0.54 for 5-fold cross-validation.Conclusion: Promising accuracies were observed for all traits in 5-fold cross-validation, but not in the across-generation validations. Overall, applying genomic selection in insect biocontrol agents with a relative small effective population size seems promising. However, factors such as the biology of insects, the techniques of phenotyping, and costs of large-scale genotyping still challenge the application of genomic selection to biocontrol agents.