Development of whole?genome prediction models to increase the rate of genetic gain in intermediate wheatgrass ( <i>Thinopyrum intermedium</i> ) breeding

The development of perennial grain crops is driven by the vision simultaneous food production and enhanced ecosystem services. Typically, like intermediate wheatgrass (IWG)[Thinopyrum intermedium (Host) Barkworth & D.R Dewey] have low seed yield other detrimental traits. Next-generation sequencing has made genomic selection (GS) a tractable viable breeding method. To investigate how an IWG program may use GS, we evaluated 3,658 genets over 2 yr for 46 traits to build training population. Six statistical models were used evaluate non-replicated data, model using autoregressive order 1 (AR1) spatial correction rows columns combined with relationship matrix provided highest estimates heritability. Genomic built from 18,357 single nucleotide polymorphism markers via genotyping-by-sequencing, 20-fold cross-validation showed high predictive ability all (r > .80). Predictive abilities improved increased population size marker numbers, even larger amounts missing data per marker. On basis these results, propose GS method that capable completing one cycle year compared minimum phenotypic selection. We estimate this approach can increase rate genetic gain up 2.6× above spike in IWG, allowing enable rapid domestication improvement crop. These methods should be transferable species similar long cycles or limited capacity replicated observations.