Relatedness severely impacts accuracy of marker-assisted selection for disease resistance in hybrid wheat

Abstract

The accuracy of genomic selection depends on the relatedness between the members of the set in which marker effects are estimated based on evaluation data and the types for which performance is predicted. Here, we investigate the impact of relatedness on the performance of marker-assisted selection for fungal disease resistance in hybrid wheat. A large and diverse mapping population of 1739 elite European winter wheat inbred lines and hybrids was evaluated for powdery mildew, leaf rust and stripe rust resistance in multi-location field trials and fingerprinted with 9 k and 90 k SNP arrays. Comparison of the accuracies of prediction achieved with data sets from the two marker arrays revealed a crucial role for a sufficiently high marker density in genome-wide association mapping. Cross-validation studies using test sets with varying degrees of relationship to the corresponding estimation sets revealed that close relatedness leads to a substantial increase in the proportion of total genotypic variance explained by the identified QTL and consequently to an overoptimistic judgment of the precision of marker-assisted selection.

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.)

“…Our results are in accordance with these previous findings, as the marker-assisted selection approaches based on the three marker systems explained up to 78% of the phenotypic variation for the total population when a significance threshold of Po0.005 was applied. This number dropped in fivefold cross-validation ( Figure 5) as was expected from previous results (Guo et al, 2012;Miedaner et al, 2013;Zhao et al, 2013;Gowda et al, 2014;Würschum and Kraft, 2014). Nevertheless, the cross-validated accuracy of prediction of FHB resistance is still high and in most cases higher than using randomly sampled markers ( Figure 5), suggesting that genome-wide association mapping studies indeed have the potential to at least partially answer the two central questions on the genetic architecture of FHB resistance outlined above.…”

The potential of genomic‐assisted breeding to improve Fusarium head blight resistance in winter durum wheat

“…Marker‐assisted selection (MAS) based on the four strongest QTL yielded a predictive ability of 0.65 (Figure ), while genomic prediction (GP) taking into account all genome‐wide markers only marginally improved the predictive ability to 0.70. It must be noted here that the predictive ability of MAS also exploits relatedness between lines and not only QTL effects (Gowda et al., ), which might in part explain the high predictive ability of MAS. The predictive ability of phenotypic selection, being roughly estimated as the square root of the heritability, reached 0.92 and was thus by far the highest value in this comparison.…”

Genome–metabolite associations revealed low heritability, high genetic complexity, and causal relations for leaf metabolites in winter wheat (Triticum aestivum)

“…S1 at JXB online) as outlined in detail by Anscombe and Tukey (1963). The adjusted entry means were estimated for the genome-wide association study (GWAS) (Zhao et al , 2014). A one-step model was used to estimate the genetic variance components of lines and the variance of genotype × environment interactions.…”