Genomic prediction in insects: a case study on wing morphology traits in the jewel wasp Nasonia vitripennis

Biological control is a sustainable strategy to combat agricultural pests. Yet, legislation increasingly restricts importing nonnative biocontrol agents. Thus, selective breeding of biocontrol traits is suggested to enhance performance of existing biocontrol agents. Genomic prediction, where genomic data are used to estimate the genetic merit of an individual for specific traits, is an alternative to exploit genetic variation for the improvement of native biocontrol agents. This study aims to establish a proof of principle for genomic prediction in insect biocontrol agents, using wing morphology traits in the model parasitoid Nasonia vitripennis Walker (Pteromalidae). We performed genomic prediction using a genomic best linear unbiased prediction (GBLUP) model, using 1,230 individuals with 8,639 SNPs generated by genotyping-by-sequencing (GBS). We used individuals from 2 generations from the outbred HVRx population, 717 individuals from generation 169 (G169) and 513 individuals from generation 172 (G172). To assess genomic prediction accuracy, we used across generation validation (forward validation for G172 from G169 and backward validation for G169 from G172) and also 5-fold cross-validation. For size-related traits, including tibia length, wing length, wing width, and second moment area, the accuracy of genomic prediction was close to 0 in both across generation validations but much higher in 5-fold cross-validation (ranging from 0.54 to 0.68). For the shape-related trait wing aspect ratio, a high accuracy was found for all 3 validation strategies, with 0.47 for across generation forward validation (AGFV), 0.65 for across generation backward validation (AGBV), and 0.54 for 5-fold cross-validation. Overall, genomic selection in insect biocontrol agents with a relative small effective population size seems promising. However, factors such as the biology of insects, phenotyping techniques, and large-scale genotyping costs still challenge the application of genomic selection to biocontrol agents.