How Population Structure Impacts Genomic Selection Accuracy in Cross-Validation: Implications for Practical Breeding.

Over the last two decades, the application of genomic selection has been extensively studied in various crop species, and it has become a common practice to report prediction accuracies using cross validation. However, genomic prediction accuracies obtained from random cross validation can be strongly inflated due to population or family structure, a characteristic shared by many breeding populations. An understanding of the effect of population and family structure on prediction accuracy is essential for the successful application of genomic selection in plant breeding programs. The objective of this study was to make this effect and its implications for practical breeding programs comprehensible for breeders and scientists with a limited background in quantitative genetics and genomic selection theory. We, therefore, compared genomic prediction accuracies obtained from different random cross validation approaches and within-family prediction in three different prediction scenarios. We used a highly structured population of 940

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Copyright © 2020 Werner, Gaynor, Gorjanc, Hickey, Kox, Abbadi, Leckband, Snowdon and Stahl.

Déclaration de conflit d'intérêts

AA and TK were employed by the company NPZ Innovation GmbH. GL was employed by the company German Seed Alliance GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.