Table 1.
First and second degree statistics for 135 inbred lines and 1,604 hybrids derived from them for quality traits gluten content(%), kernel hardness (%), protein content (%), SDS value (ml), starch content (%), test weight (kg/hL), and 1000-kernel weight (g) determined in up to six environments.
Fig 1.
SNPs with additive effects contributing to 1000-kernel weight.
Heat-plots of (OF, top row) frequencies with which SNP markers were significantly associated with 1000-kernel weight in 100 cross-validation runs, (P, middle row) P-values of respective SNP markers that contributed significantly to the additive genetic variation of 1000-kernel weight, and (r², lower triangular section) linkage disequilibrium measured as squared Pearson’s correlation coefficients among SNP markers.
Fig 2.
Cross-validated accuracies of prediction in marker-assisted selection for seven wheat quality traits.
Varying degrees of relatedness between the estimation and test sets, with triangles indicating a T2 scenario with closest, round discs a T1 scenario with intermediate, and squares a T0 scenario with closest relatedness, and levels of significance, with P-values of 0.001, 0.001, 0.01, 0.05, 0.1, and applying Bonferroni-Holm correction for multiple testing, were used in genome-wide scans for marker-trait associations. Significant markers were then used to predict the performance of the individuals included in test sets. Numbers in brackets indicate the average number of significant marker-trait associations found based on 100 cross-validation runs. Red lines show corresponding non-cross-validated accuracies of prediction accuracies obtained based on the full data set.
Table 2.
Cross-validated accuracies of prediction of marker-assisted selection, genomic selection, mid-parent prediction and prediction based on general-combining ability effects.
Fig 3.
Cross-validated accuracies of prediction of genomic selection using RR-BLUP for seven quality traits in dependence on marker density (0.1-17k) for three cross-validation scenarios.
The dashed lines indicate accuracies of prediction observed with highest marker density as reference, blue, green, and red refer to T2, T1, and T0 scenarios with closest, intermediate, and lowest relatedness between estimation and test sets, respectively.
Fig 4.
Cross-validated accuracies of prediction of genomic selection using RR-BLUP for seven quality in dependence on the size and composition of estimation sets as well as the relatedness between estimation and test sets.
Estimation sets consisted of (A, top row) 10 male lines, a varying number of female lines, and 100 hybrids derived from them or (B, lower row) 10 male parents, 80 females, and varying numbers of hybrids derived from them. Triangles in red, round discs in green, and squares in blue represent T2, T1, and T0 scenarios with closest, intermediate, and lowest relatedness between estimation and test sets, respectively. Solid red, green, and blue lines indicate accuracies for of prediction for T2, T1, and T0 scenarios with estimation sets consisting of 10 male parents, 80 female parents, and 610 hybrids as reference.