Genomic prediction of single cross families of perennial ryegrass under two nitrogen managements

The performance of a single cross is determined by the additive effects of the parents and their interactions, which can be estimated through general combining ability (GCA) and specific combining ability (SCA). With genome‐wide marker information, it is possible to predict GCA for new parents and the genetic value of unrealized crosses. Several studies in crops such as maize ( Zea mays L.) and rice ( Oryza sativa L.) have demonstrated the potential of genomic prediction for single‐cross performance. However, no study to date has explored its relevance in perennial ryegrass ( Lolium perenne L.), an obligate allogamous species bred in genetically heterogeneous families. In this study, we estimated genetic parameters and evaluated genomic prediction models for dry matter yield and nutritive quality traits in F 2 family bulk. Data were obtained from a large partial diallel involving 104 parents from two genetically distinct subpopulations identified by admixture analysis. Families were evaluated across multiple environments under two nitrogen conditions. Genotyping‐by‐sequencing generated 42,145 high‐quality variants used to estimate genomic relationships. Variance component analyses revealed limited GCA and SCA interactions with environment and nitrogen management. Predictive abilities of parental models exceeded 0.60 and often 0.70 for most traits, whereas including nonadditive effects did not improve predictive ability. Genome‐wide association analyses identified six quantitative trait locus regions and 45 candidate genes within linkage disequilibrium intervals averaging 92 kb. Our results demonstrate that genomic prediction of single crosses in perennial ryegrass can achieve high accuracy, particularly when both parents are represented in the training population.