The potential of genome-wide prediction to support parental selection, evaluated with data from a commercial barley breeding program

Abstract

Parental selection marks the beginning and contributes significantly to the success of every breeding endeavor. The value of a cross is reflected in the potential of its progeny population. Breeders invest money, time, and space into the evaluation of progeny to select the best performing genotypes as candidates for variety development. Several proposals to support parental selection by genomics have been made, mostly based on theoretical assumptions or simulation studies. While most of them claim to provide the solution to the problem of parental selection, only few consider practical hurdles connected to their implementation or are solely based on simulations. In this study, we tested the potential of genomic prediction for predicting progeny mean, variance and usefulness criterion in an applied breeding population for winter barley. For three traits with genetic architectures at varying levels of complexity, ear emergence, plant height, and grain yield, progeny mean, variance, and usefulness criterion were predicted and validated in scenarios resembling situations in which the described tools shall be used in plant breeding. We showed that the identification of superior crosses remains a challenging task and suppose that the success for the prediction of the usefulness criterion depends highly on the complexity of the underlying trait.