Using genomic selection to correct pedigree errors in kiwiberry breeding

In breeding programmes, accurate estimation of breeding values is crucial for selecting superior genotypes. Traditional methods rely on phenotypic observations and pedigree information to estimate variance components and heritability. However, pedigree errors can significantly affect the accuracy of these estimates, especially in long-lived perennial vines. This study evaluates the effect of pedigree errors on breeding value predictions in kiwiberry breeding and explores the benefits of using genomic selection. We applied Best Linear Unbiased Prediction (BLUP) to estimate breeding values for each genotype for a given trait. Four scenarios with varying degrees of alteration in pedigree-based relationship matrices were used to represent inaccurate relationships between genotypes. Pedigree-based breeding values were compared with genomic estimated breeding values for one vine-related and four fruit-related quantitative traits. The results showed that as the degree of altered population structure increased, the prediction accuracy of pedigree-based breeding values decreased. In contrast, genomic selection, which uses marker inheritance, maintained realised relationships between genotypes, making it a more robust method for predicting genetic merit. In kiwiberries, as in all species of the genus Actinidia, only female vines bear fruit. The genotypic merit of fruit-related traits in male genotypes can only be estimated indirectly. Marker-based predictions outperformed pedigree-based predictions, especially for genotypes without phenotypic observations, such as male siblings. This study reviewed the induced population structures and introduced genomic selection into the kiwiberry breeding programme. We demonstrated that genomic selection provides more accurate breeding values by capturing true genetic relationships and reducing the effects of misidentified relationships between individuals.