Genomic Prediction Within and Among Doubled-Haploid Libraries from Maize Landraces

Abstract

Thousands of maize landraces are stored in seed banks worldwide. Doubled-haploid libraries (DHL) produced from landraces harness their rich genetic diversity for future breeding. We investigated the prospects of genomic prediction (GP) for line per se performance in DHL from six European landraces and 53 elite flint (EF) lines by comparing four scenarios: GP within a single library (sL); GP between pairs of libraries (LwL); and GP among combined libraries, either including (cLi) or excluding (cLe) lines from the training set (TS) that belong to the same DHL as the prediction set. For scenario sL, with N = 50 lines in the TS, the prediction accuracy (ρ) among seven agronomic traits varied from -0.53 to 0.57 for the DHL and reached up to 0.74 for the EF lines. For LwL, ρ was close to zero for all DHL and traits. Whereas scenario cLi showed improved ρ values compared to sL, ρ for cLe remained at the low level observed for LwL. Forecasting ρ with deterministic equations yielded inflated values compared to empirical estimates of ρ for the DHL, but conserved the ranking. In conclusion, GP is promising within DHL, but large TS sizes (N > 100) are needed to achieve decent prediction accuracy because LD between QTL and markers is the primary source of information that can be exploited by GP. Since production of DHL from landraces is expensive, we recommend GP only for very large DHL produced from a few highly preselected landraces.

Keywords: GenPred; Genomic Prediction; doubled-haploid; maize landraces; shared data resources.