Biocontrol is a strategy to reduce the population density of pests, such as insects, weeds and diseases, by using the natural enemies of the individuals causing those pests. Biocontrol is an appealing strategy in agriculture, because it holds the promise of controlling pests without the need for pesticides. Genetic selection of biocontrol populations may offer a solution to further improve the performance of natural enemies in practical biocontrol, in particular using the method of Genomic Prediction (GP). However, to our knowledge, the utility of GP has not yet been demonstrated for populations of natural enemies. Here we demonstrate proof-of-principle for the use of GP in a natural enemy population. We applied GP based on genotyping-by-sequencing (GBS) SNP data, using the parasitoid wasp Nasiona vitripennis as a model organism. A total of 1,230 individuals from two generations (G0 and G3) with genotypes for 8,639 SNPs were included in the analysis for wing aspect ratio (the ratio of wing length to width). Genomic best linear unbiased prediction (GBLUP) was applied to predict genomic breeding values (GEBVs). To assess the accuracy of GP, different cross-validation strategies were carried out: (1) across-generations validation; (2) 5-fold cross-validation within generations and combined dataset of G0 and G3. Accuracy was computed as the correlation between GEBVs and the observed phenotypes of individuals in the validation group divided by the square root of estimated heritability of validation group. The accuracy varied from 0.49 to 0.59 in across-generations validation, while higher variation in accuracy was observed in 5-fold cross-validation scenarios, ranging from 0.49 to 0.81. To conclude, our results indicate the potential of GP to predict breeding values in natural enemies.
|Name||Book of Abstracts|
|Publisher||Wageningen Academic Publishers|
|Conference||70th Annual Meeting of the European Federation of Animal Science|
|Period||25/08/19 → 31/08/19|