Genomic Prediction of Single Crosses in the Early Stages of a Maize Hybrid Breeding Pipeline

Abstract

Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.

Keywords: GenPred; Genomic Selection; Shared Data Resources; general combining ability; genomic prediction; genotyping by sequencing; hybrid breeding; specific combining ability.

Figure 1

Crossing scheme between RILs or DHLs derived from three biparental families representing the SSS (y-axis) and NSS (x-axis) heterotic groups. Colored boxes indicate the presence while unfilled boxes indicate absence of a particular single cross. Bold lines delineate single-cross families.

Figure 2

Schematic visualization of T2, T1F, T1M, and T0 cross-validation scenarios. Each small square represents one single cross. Completely filled squares (T2) indicate that both male and female parents of a single cross contained in the validation set were tested, half-filled squares indicate either the female (T1F) or male parent (T1M) of single cross contained in the validation set was tested, and unfilled squares (T0) indicate that neither parent of a single cross contained in the validation set was tested.

Figure 3

Prediction accuracy for T2, T1F, T1M and T0 cross-validation scenarios for traits grain yield (GY), plant height (PH) and staygreen (SG) obtained using the four methods 1a (Parent GCA), 1b (Parent GCA plus single-cross SCA), 2a (Additive genetic covariance among single crosses) and 2b (Additive plus dominance covariance among single crosses) as evaluated with training set of 250 and leave-one-individual-out cross-validation.

Figure 4

Mean prediction accuracy and SE of methods 1a (orange) and 1b (blue) in predicting performance of novel single-cross families. Two cross-validation schemes were used: leave-one-family out (bottom panel) and leave-one-individual out (top panel). Traits analyzed were grain yield (GY), plant height (PH), and staygreen (SG). SEs were estimated using the bootstrap method.

Figure 5

Distribution of genomic predictions for grain yield (GY) for all 7866 possible single crosses between the 46 SSS inbred progenies and 171 NSS inbred progenies.

Figure 6

SEs of predicted GCA and SCA effects estimated using differing numbers of single crosses per parental inbred progeny.