Abstract
Genomic selection can increase the rate of genetic gain in crops through accumulation of positive alleles and reduce phenotyping costs by shortening the breeding cycle time. We performed genomic prediction for resistance to wheat rusts in tetraploid wheat accessions using three cross-validation with the objective of predicting: (1) rust resistance when individuals are not tested in all environments/locations, (2) the performance of lines across years, and (3) adult plant resistance (APR) of lines with bivariate models. The rationale for the latter is that seedling assays are faster and could increase prediction accuracy for APR. Predictions were derived from adult plant and seedling responses for leaf rust (Lr), stem rust (Sr) and stripe rust (Yr) in a panel of 391 accessions grown across multiple years and locations and genotyped using 16,483 single nucleotide polymorphisms. Different Bayesian models and genomic best linear unbiased prediction yielded similar accuracies for all traits. Site and year prediction accuracies for Lr and Yr ranged between 0.56–0.71 for Lr and 0.51–0.56 for Yr. While prediction accuracy for Sr was variable across different sites, accuracies for Yr were similar across different years and sites. The changes in accuracies can reflect higher genotype × environment (G × E) interactions due to climate or pathogenic variation. The use of seedling assays in genomic prediction was underscored by significant positive genetic correlations between all stage resistance (ASR) and APR (Lr: 0.45, Sr: 0.65, Yr: 0.50). Incorporating seedling phenotypes in the bivariate genomic approach increased prediction accuracy for all three rust diseases. Our work suggests that the underlying plant-host response to pathogens in the field and greenhouse screens is genetically correlated, but likely highly polygenic and therefore difficult to detect at the individual gene level. Overall, genomic prediction accuracies were in the range suitable for selection in early generations of the breeding cycle.
Highlights
Tetraploid wheat has played important role in common wheat evolution and human history and comprises 5% of total global wheat production [1]
Africa and Middle East were loosely clustered by the first PC, while accessions from the Europe showed no clear pattern of clustering
This study examined methods for genomic prediction of adult plant resistance (APR) and all stage resistance (ASR) for resistance to rust diseases in this tetraploid wheat panel
Summary
Tetraploid wheat has played important role in common wheat evolution and human history and comprises 5% of total global wheat production [1]. Tritici Westend.; Pst) pose a major threat to global production of durum wheat. These three rust diseases can cause substantial losses in yield and quality, the losses due to Sr can be up to 100%, where susceptible varieties are grown [3]. The most economic and environment-friendly approach to control wheat rust diseases is to pyramid two or more rust resistance genes in new cultivars [4]. Rust resistance has often been categorised as all stage resistance (ASR) and adult plant resistance (APR). ASR is controlled either by single or a few genes of large effects, whereas an acceptable level of APR is often controlled by a combination of multiple minor-effect resistances genes [5,6]
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