Genomic predictability of interconnected biparental maize populations

Abstract

Intense structuring of plant breeding populations challenges the design of the training set (TS) in genomic selection (GS). An important open question is how the TS should be constructed from multiple related or unrelated small biparental families to predict progeny from individual crosses. Here, we used a set of five interconnected maize (Zea mays L.) populations of doubled-haploid (DH) lines derived from four parents to systematically investigate how the composition of the TS affects the prediction accuracy for lines from individual crosses. A total of 635 DH lines genotyped with 16,741 polymorphic SNPs were evaluated for five traits including Gibberella ear rot severity and three kernel yield component traits. The populations showed a genomic similarity pattern, which reflects the crossing scheme with a clear separation of full sibs, half sibs, and unrelated groups. Prediction accuracies within full-sib families of DH lines followed closely theoretical expectations, accounting for the influence of sample size and heritability of the trait. Prediction accuracies declined by 42% if full-sib DH lines were replaced by half-sib DH lines, but statistically significantly better results could be achieved if half-sib DH lines were available from both instead of only one parent of the validation population. Once both parents of the validation population were represented in the TS, including more crosses with a constant TS size did not increase accuracies. Unrelated crosses showing opposite linkage phases with the validation population resulted in negative or reduced prediction accuracies, if used alone or in combination with related families, respectively. We suggest identifying and excluding such crosses from the TS. Moreover, the observed variability among populations and traits suggests that these uncertainties must be taken into account in models optimizing the allocation of resources in GS.

Keywords: Fusarium graminearum; G-BLUP; GenPred; shared data resources; whole-genome prediction.

Figure 1

Crossing scheme to obtain the five populations.

Figure 2

Heatmap showing IBS similarities (red, above diagonal) and genomic correlations (blue, below diagonal) among all genotypes. The numbers in the blocks refer to average IBS similarities within and between populations. Average genomic correlations in comparisons with linkage phase similarities can be found in Table S2. FS, full sibs; HS, half sibs; UR, unrelated.

Figure 3

(A–D) Prediction accuracies for within-population prediction using full sibs (1A). Shown are the average values for all traits obtained from 100 repetitions. The dashed lines indicate phenotypic accuracies calculated as the square root of the heritability.

Figure 4

(A and B) Observed vs. expected within-population prediction accuracy using full sibs (1A) averaged over (A) all populations except the smallest one (π_2,4) and (B) traits. The expected prediction accuracy was calculated using the formula suggested by Daetwyler et al. (2010), assuming an average genome size L = 16.34 M and effective number of loci M_e = 2N_eL. Effective population size (N_e) was calculated using the harmonic mean approximation for two generations.

Figure 5

(A–E) Prediction accuracies for individual validation populations (VP) depending on the composition of the training set (TS) and the total TS size. Shown are the mean values over all traits, repetitions, and possible combinations to construct the TS. The dashed lines indicates the TS size at which a model-based statistical comparison of TS compositions was performed. See Table 1 for details about the different TS compositions. Results for individual traits can be found in Figure S4, Figure S5, Figure S6, Figure S7, and Figure S8.