Accuracy of genomic selection for grain yield and agronomic traits in soft red winter wheat.

BACKGROUND: Genomic selection has the potential to increase genetic gains by using molecular markers as predictors of breeding values of individuals. This study evaluated the accuracy of predictions for grain yield, heading date, plant height, and yield components in soft red winter wheat under different prediction scenarios. Response to selection for grain yield was also compared across different selection strategies- phenotypic, marker-based, genomic, combination of phenotypic and genomic, and random selections. RESULTS: Genomic selection was implemented through a ridge regression best linear unbiased prediction model in two scenarios- cross-validations and independent predictions. Accuracy for cross-validations was assessed using a diverse panel under different marker number, training population size, relatedness between training and validation populations, and inclusion of fixed effect in the model. The population in the first scenario was then trained and used to predict grain yield of biparental populations for independent validations. Using subsets of significant markers from association mapping increased accuracy by 64-70% for grain yield but resulted in lower accuracy for traits with high heritability such as plant height. Increasing size of training population resulted in an increase in accuracy, with maximum values reached when ~ 60% of the lines were used as a training panel. Predictions using related subpopulations also resulted in higher accuracies. Inclusion of major growth habit genes as fixed effect in the model caused increase in grain yield accuracy under a cross-validation procedure. Independent predictions resulted in accuracy ranging between - 0.14 and 0.43, dependent on the grouping of site-year data for the training and validation populations. Genomic selection was "superior" to marker-based selection in terms of response to selection for yield. Supplementing phenotypic with genomic selection resulted in approximately 10% gain in response compared to using phenotypic selection alone. CONCLUSIONS: Our results showed the effects of different factors on accuracy for yield and agronomic traits. Among the factors studied, training population size and relatedness between training and validation population had the greatest impact on accuracy. Ultimately, combining phenotypic with genomic selection would be relevant for accelerating genetic gains for yield in winter wheat.

Race-Specific Adult-Plant Resistance in Winter Wheat to Stripe Rust and Characterization of Pathogen Virulence Patterns.

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is an important disease of wheat in the Great Plains and southeastern United States. Growing resistant cultivars is the preferred means for managing stripe rust, but new virulence in the pathogen population overcomes some of the resistance. The objectives of this study were to characterize the stripe rust resistance in contemporary soft and hard red winter wheat cultivars, to characterize the virulence of P. striiformis f. sp. tritici isolates based on the resistances found in the cultivars, and to determine wheat breeders' perceptions on the importance and methods for achieving stripe rust resistance. Seedlings of cultivars were susceptible to recent isolates, indicating they lacked effective all-stage resistance. However, adult-plants were resistant or susceptible depending on the isolate, indicating they had race-specific adult-plant resistance. Using isolates collected from 1990 to 2013, six major virulence patterns were identified on adult plants of twelve cultivars that were selected as adult-plant differentials. Race-specific adult-plant resistance appears to be the only effective type of resistance protecting wheat from stripe rust in eastern United States. Among wheat breeders, the importance of incorporating stripe rust resistance into cultivars ranged from high to low depending on the frequency of epidemics in their region, and most sources of stripe rust resistance were either unknown or already overcome by virulence in the pathogen population. Breeders with a high priority for stripe rust resistance made most of their selections based on adult-plant reactions in the field, whereas breeders with a low priority for resistance based selections on molecular markers for major all-stage resistance genes.

Elucidation of the genetic architecture of water absorption capacity in hard winter wheat through genome wide association study.

Water absorption capacity (WAC) influences various aspects of bread making, such as loaf volume, bread yield, and shelf life. Despite its importance in the baking process and end-product quality, its genetic determinants are less explored. To address this limitation, a genome-wide association study was conducted on 337 hard wheat (Triticum aestivum L.) genotypes evaluated over 5 years in multi-environmental trials. Phenotyping was done using the solvent retention capacity (SRC) test with water (SRC-water), sucrose (SRC-sucrose), lactic acid (SRC-lactic acid), and sodium carbonate (SRC-carbonate) as solvents. Individuals were genotyped using genotyping-by-sequencing to detect single nucleotide polymorphisms across the wheat genome. To detect the genomic regions that underline the SRCs and gluten performance index (GPI), a genome-wide association study was performed using six multi-locus models using the mrMLM package in R. Adjusted means for SRC-water ranged from 54.1% to 66.5%, while SRC-carbonate exhibited a narrow range from 84.9% to 93.9%. Moderate to high genomic heritability values were observed for SRCs and GPI, ranging from h2 = 0.61 to 0.88. The genome-wide association study identified a total of 42 quantitative trait nucleotides (QTNs), of which five explained over 10% of the phenotypic variation (R2 ≥ 10%). Most of the QTNs were detected on chromosomes 1A, 1B, 3B, and 5B. Few QTNs, such as S1A_5190318, S1B_3282665, S4D_472908721, and S7A_37433960, were located near gliadin, glutenin starch synthesis, and galactosyltransferase genes. Overall, these results show WAC to be under polygenic genetic control, with genes involved in the synthesis of key flour components influencing overall water absorption.

QTL mapping of a high protein digestibility trait in Sorghum bicolor.

Compared with other cereal grains, Sorghum bicolor shows lower protein digestibility. The low digestibility is thought to result from disulfide cross linking in the beta- and gamma-kafirins. In contrast, the single recessive high digestibility/high lysine content (HD) mutation which confers greater grain digestibility exists in sorghum that is thought to result from reduced accumulation of gamma-kafirin that allows greater access to the high digestible alpha-kafarin fraction. In an effort to both clearly define the molecular basis for the HD trait and develop tools to improve the introgression of this difficult-to-screen trait, this study focuses on mapping the QTLs linked to this trait. While the HD trait has been defined as a single recessive gene, our results uncovered that two major QTLs on chromosome 1 are associated with protein digestibility-one QTL (locus 1 from the HD parent) unfavorably affects digestibility and one QTL (locus 2 from the HD parent) only 20 cM away favorably affects digestibility. A contrast analysis between genotypic groups at these two loci shows that a higher level of protein digestibility may be obtained when this linkage in repulsion is broken and favorable alleles are allowed to recombine.