Genome-wide association study and genomic prediction of resistance to stripe rust in current Central and Northern European winter wheat germplasm

Genetic Dissection of Triple Rust Resistance (Leaf, Yellow, and Stem Rust) in Kenyan Wheat Cultivar, "Kasuku"

Climate change is driving the spread of transboundary wheat diseases, necessitating the development of resilient wheat varieties for sustainable agriculture. Wheat rusts, including leaf rust (LR), yellow rust (YR), and stem rust (SR), remain among the most economically significant diseases, causing substantial yield losses worldwide. Enhancing genetic diversity by identifying and deploying rust resistance genes is crucial for durable resistance in wheat breeding programs. This study aimed to identify quantitative trait loci (QTL) associated with rust resistance in the CIMMYT wheat line Kasuku, released in Kenya in 2018. A recombinant inbred line (RIL) population (181 lines) derived from Kasuku (triple rust-resistant) and Apav#1 (triple rust-susceptible) was evaluated under artificial LR and YR epidemics in Mexico and YR and SR in Kenya. QTL mapping using genotyping-by-sequencing (DArTSeq) and phenotypic data identified four major loci: QLrYrSr.cim-1BL (Lr46/Yr29/Sr58) on 1BL, conferring resistance to LR, YR, and SR; QLrYr.cim-2AS (Yr17/Lr37) on 2AS, providing LR and YR resistance; QLrYr.cim-3AL on 3AL; and QLrYrSr.cim-6AL on 6AL, representing novel loci associated with multiple rust resistances. Additionally, minor QTL were also identified: for LR (QLr.cim-2DS on 2DS, QLr.cim-6DS on 6DS), for YR (QYrKen.cim-3DS on 3DS, QYrKen.cim-6BS on 6BS), and for SR (QSr.cim-2BS on 2BS, QSr.cim-5AL on 5AL, QSr.cim-6AS on 6AS). RILs carrying these QTL combinations exhibited significant reductions in rust severity. Flanking markers for these loci are being used to develop Kompetitive Allele-Specific PCR (KASP) markers for fine mapping and marker-assisted selection (MAS). These findings contribute to the strategic deployment of rust resistance genes in wheat breeding programs, facilitating durable resistance to multiple rust pathogens.

A large-scale multi-environment study dissecting adult-plant resistance haplotypes for stripe rust resistance in Australian wheat breeding populations

KEY MESSAGE

Genetic variation in stripe rust resistance exists in Australian wheat breeding populations and is environmentally influenced. Stacking multiple resistance haplotypes or using whole-genome approaches will improve resistance stability and environmental specificity. Wheat stripe rust (Puccinia striiformis) is a fungal disease responsible for substantial yield losses globally. To maintain crop productivity in future climates, the identification of genetics offering durable resistance across diverse growing conditions is crucial. To stay one-step ahead of the pathogen, Australian wheat breeders are actively selecting for adult-plant resistance (APR), which is considered more durable than seedling resistance. However, deploying resistance that is stable or effective across environments and years is challenging as expression of underling APR loci often interacts with environmental conditions. To explore the underlying genetics and interactions with the environment for stripe rust resistance, we employ haplotype-based mapping using the local GEBV approach in elite wheat breeding populations. Our multi-environment trial analyses comprising 35,986 inbred lines evaluated across 10 environments revealed significant genotype-by-environment interactions for stripe rust. A total of 32 haploblocks associated with stripe rust resistance were identified, where 23 were unique to a specific environment and nine were associated with stable resistance across environments. Population structure analysis revealed commercial or advanced breeding lines carried desirable resistance haplotypes, highlighting the opportunity to continue to harness and optimise resistance haplotypes already present within elite backgrounds. Further, we demonstrate that in silico stacking of multiple resistance haplotypes through a whole-genome approach has the potential to substantially improve resistance levels. This represents the largest study to date exploring commercial wheat breeding populations for stripe rust resistance and highlights the breeding opportunities to improve stability of resistance across and within target environments.

Genome-wide association mapping for the identification of stripe rust resistance loci in US hard winter wheat

KEY MESSAGE

The GWAS and testing with Yr gene linked markers identified 109 loci including 40 novel loci for all-stage and adult plant stage resistance to stripe rust in 459 US contemporary hard winter wheat genotypes. Stripe rust is a destructive wheat disease, caused by Puccinia striiformis f. sp. tritici (Pst). To identify sources of stripe rust resistance in US contemporary hard winter wheat, a panel of 459 Great Plains wheat genotypes was evaluated at the seedling stage against five US Pst races and at the adult plant stage in field environments in Oklahoma, Kansas, and Washington. The results showed that 7-14% of the genotypes were resistant to Pst races at the seedling stage, whereas 32-78% of genotypes were resistant at the adult plant stage across field environments, indicating the presence of adult plant resistance. Sixteen genotypes displayed a broad spectrum of resistance to all five Pst races and across all field environments. The panel was further genotyped using 9858 single-nucleotide polymorphisms (SNPs) generated from multiplex restriction amplicon sequencing (MRASeq) and the functional DNA markers linked to the known stripe rust resistance (Yr) genes Yr5, Yr15, Yr17, Yr18, Yr29, Yr36, Yr40, Yr46, and QYr.tamu-2B. A genome-wide association study (GWAS) was performed using genotypic and phenotypic data, which identified 110 SNPs and the functional markers linked to Yr15 and Yr17 to be significantly associated with stripe rust response. In addition, Yr5, Yr15, Yr17, Yr18, Yr29, and QYr.tamu-2B were detected by their functional DNA markers in the panel. This study identified 40 novel loci associated with stripe rust resistance in genomic regions not previously characterized by known Yr genes. These findings offer significant opportunities to diversify and enhance stripe rust resistance in hard winter wheat.

Do different wheat ploidy levels respond differently against stripe rust infection: Interplay between reactive oxygen species (ROS) and the antioxidant defense system?

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) is the most damaging wheat disease, causing substantial losses in global wheat production and productivity. Our study aimed to unravel the complex reciprocity between reactive oxygen species and the antioxidant defense system as a source of resistance against stripe rust in diploid, tetraploid and hexaploid wheat genotypes. The significant genetic variability for stripe rust in the materials under study was evident as the genotypes showed contrasting responses during both the adult and seedling stages. Our thorough perspective on the biochemical responses of wheat genotypes to stripe rust infection revealed distinct patterns in oxidative damage, antioxidant enzymes and photosynthetic pigments. Principal component analysis revealed inverse correlations between antioxidants and ROS, underscoring their key function in maintaining the cellular redox balance and protecting plants against oxidative damage. Diploid (Ae. tauschii) wild wheat exhibited a better biochemical defense system and greater resistance to stripe rust than the tetraploid (T. durum) and hexaploid (Triticum aestivum) wheat genotypes. The antioxidant enzyme activity of durum wheat was moderate compared to diploid and hexaploid wheat genotypes. The hexaploid wheat genotypes exhibited increased ROS production, reduced antioxidant enzyme activity and decreased photosynthetic pigment levels. This study enhances understanding of the antioxidant defense system across different wheat ploidies facing stripe rust, serving as a valuable strategy for improving crop disease resistance. This study validated the biochemical response of stripe rust-resistant and susceptible candidate genotypes, which will be used to develop genetic resources for discovering stripe rust resistance genes in wheat.

Broad-spectrum resistance to fungal foliar diseases in wheat: recent efforts and achievements

Wheat (Triticum spp.) is one of the most important cereal crops in the world. Several diseases affect wheat production and can cause 20-80% yield loss annually. Out of these diseases, stripe rust, also known as yellow rust (Puccinia striiformis f. sp. tritici), stem rust (Puccinia graminis f. sp. tritici), leaf rust (Puccinia recondita), and powdery mildew (Blumeria graminis f. sp. tritici) are the most important fungal diseases that infect the foliar part of the plant. Many efforts were made to improve wheat resistance to these diseases. Due to the continuous advancement in sequencing methods and genomic tools, genome-wide association study has become available worldwide. This analysis enabled wheat breeders to detect genomic regions controlling the resistance in specific countries. In this review, molecular markers significantly associated with the resistance of the mentioned foliar diseases in the last five years were reviewed. Common markers that control broad-spectrum resistance in different countries were identified. Furthermore, common genes controlling the resistance of more than one of these foliar diseases were identified. The importance of these genes, their functional annotation, and the potential for gene enrichment are discussed. This review will be valuable to wheat breeders in producing genotypes with broad-spectrum resistance by applying genomic selection for the target common markers and associated genes.

Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing

Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype-phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties.

Leveraging trait and QTL covariates to improve genomic prediction of resistance to Fusarium head blight in Central European winter wheat

Fusarium head blight (FHB) is a devastating disease of wheat, causing yield losses, reduced grain quality, and mycotoxin contamination. Breeding can mitigate the severity of FHB epidemics, especially with genomics-assisted methods. The mechanisms underlying resistance to FHB in wheat have been extensively studied, including phenological traits and genome-wide markers associated with FHB severity. Here, we aimed to improve genomic prediction for FHB resistance across breeding programs by incorporating FHB-correlated traits and FHB-associated loci as model covariates. We combined phenotypic data on FHB severity, anthesis date, and plant height with genome-wide marker data from five Central European winter wheat breeding programs for genome-wide association studies (GWAS) and genomic prediction. Within all populations, FHB was correlated with anthesis date and/or plant height, and a marker linked to the semi-dwarfing locus Rht-D1 was detected with GWAS for FHB. Including the Rht-D1 marker, anthesis date, and/or plant height as covariates in genomic prediction modeling improved prediction accuracy not only within populations but also in cross-population scenarios.

Mapping rust resistance in European winter wheat: many QTLs for yellow rust resistance, but only a few well characterized genes for stem rust resistance

KEY MESSAGE

Stem rust resistance was mainly based on a few, already known resistance genes; for yellow rust resistance there was a combination of designated genes and minor QTLs. Yellow rust (YR) caused by Puccinia striiformis f. sp. tritici (Pst) and stem rust (SR) caused by Puccinia graminis f. sp. tritici (Pgt) are among the most damaging wheat diseases. Although, yellow rust has occurred regularly in Europe since the advent of the Warrior race in 2011, damaging stem rust epidemics are still unusual. We analyzed the resistance of seven segregating populations at the adult growth stage with the parents being selected for YR and SR resistances across three to six environments (location-year combinations) following inoculation with defined Pst and Pgt races. In total, 600 progenies were phenotyped and 563 were genotyped with a 25k SNP array. For SR resistance, three major resistance genes (Sr24, Sr31, Sr38/Yr17) were detected in different combinations. Additional QTLs provided much smaller effects except for a gene on chromosome 4B that explained much of the genetic variance. For YR resistance, ten loci with highly varying percentages of explained genetic variance (pG, 6-99%) were mapped. Our results imply that introgression of new SR resistances will be necessary for breeding future rust resistant cultivars, whereas YR resistance can be achieved by genomic selection of many of the detected QTLs.

Genome-wide association study identifies novel loci and candidate genes for rust resistance in wheat (Triticum aestivum L.)

BACKGROUND

Wheat rusts are important biotic stresses, development of rust resistant cultivars through molecular approaches is both economical and sustainable. Extensive phenotyping of large mapping populations under diverse production conditions and high-density genotyping would be the ideal strategy to identify major genomic regions for rust resistance in wheat. The genome-wide association study (GWAS) population of 280 genotypes was genotyped using a 35 K Axiom single nucleotide polymorphism (SNP) array and phenotyped at eight, 10, and, 10 environments, respectively for stem/black rust (SR), stripe/yellow rust (YR), and leaf/brown rust (LR).

RESULTS

Forty-one Bonferroni corrected marker-trait associations (MTAs) were identified, including 17 for SR and 24 for YR. Ten stable MTAs and their best combinations were also identified. For YR, AX-94990952 on 1A + AX-95203560 on 4A + AX-94723806 on 3D + AX-95172478 on 1A showed the best combination with an average co-efficient of infection (ACI) score of 1.36. Similarly, for SR, AX-94883961 on 7B + AX-94843704 on 1B and AX-94883961 on 7B + AX-94580041 on 3D + AX-94843704 on 1B showed the best combination with an ACI score of around 9.0. The genotype PBW827 have the best MTA combinations for both YR and SR resistance. In silico study identifies key prospective candidate genes that are located within MTA regions. Further, the expression analysis revealed that 18 transcripts were upregulated to the tune of more than 1.5 folds including 19.36 folds (TraesCS3D02G519600) and 7.23 folds (TraesCS2D02G038900) under stress conditions compared to the control conditions. Furthermore, highly expressed genes in silico under stress conditions were analyzed to find out the potential links to the rust phenotype, and all four genes were found to be associated with the rust phenotype.

CONCLUSION

The identified novel MTAs, particularly stable and highly expressed MTAs are valuable for further validation and subsequent application in wheat rust resistance breeding. The genotypes with favorable MTA combinations can be used as prospective donors to develop elite cultivars with YR and SR resistance.

Genomic selection in plant breeding: Key factors shaping two decades of progress

Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP-theoretically reaching one when using the Pearson's correlation as a metric-is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.

Genome-wide association study of resistance to anthracnose in pepper (Capsicum chinense) germplasm

BACKGROUND

Anthracnose is a fungal disease caused by Colletotrichum spp. that has a significant impact on worldwide pepper production. Colletotrichum scovillei is the most common pathogenic anthracnose-causing species in the Republic of Korea.

RESULTS

The resistances of 197 pepper (Capsicum chinense) accessions deposited in Korea's National Agrobiodiversity Center were evaluated for their response against the virulent pathogens Colletotrichum acutatum isolate 'KSCa-1' and C. scovillei isolate 'Hana') in the field and in vitro methods for three consecutive years (2018 to 2020). The severity of the disease was recorded and compared between inoculation methods. Six phenotypically resistant pepper accessions were selected based on three years of disease data. All of the selected resistant pepper accessions outperformed the control resistant pepper in terms of resistance (PI 594,137). A genome-wide association study (GWAS) was carried out to identify single nucleotide polymorphisms (SNPs) associated with anthracnose resistance. An association analysis was performed using 53,518 SNPs and the disease score of the 2020 field and in vitro experiment results. Both field and in vitro experiments revealed 25 and 32 significantly associated SNPs, respectively. These SNPs were found on all chromosomes except Ch06 and Ch07 in the field experiment, whereas in the in vitro experiment they were found on all chromosomes except Ch04 and Ch11.

CONCLUSION

In this study, six resistant C. chinense accessions were selected. Additionally, in this study, significantly associated SNPs were found in a gene that codes for a protein kinase receptor, such as serine/threonine-protein kinase, and other genes that are known to be involved in disease resistance. This may strengthen the role of these genes in the development of anthracnose resistance in Capsicum spp. As a result, the SNPs discovered to be strongly linked in this study can be used to identify a potential marker for selecting pepper material resistant to anthracnose, which will assist in the development of resistant varieties.

Slow stripe rusting in Chinese wheat Jimai 44 conferred by Yr29 in combination with a major QTL on chromosome arm 6AL

YrJ44, a more effective slow rusting gene than Yr29, was localized to a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479 on chromosome 6AL. "Slow rusting" (SR) is a type of adult plant resistance (APR) that can provide non-specific durable resistance to stripe rust in wheat. Chinese elite wheat cultivar Jimai 44 (JM44) has maintained SR to stripe rust in China since its release despite exposure to a changing and variable pathogen population. An F2:6 population comprising 295 recombinant inbred lines (RILs) derived from a cross between JM44 and susceptible cultivar Jimai 229 (JM229) was used in genetic analysis of the SR. The RILs and parental lines were evaluated for stripe rust response in five field environments and genotyped using the Affymetrix Wheat55K SNP array and 13 allele-specific quantitative PCR-based (AQP) markers. Two stable QTL on chromosome arms 1BL and 6AL were identified by inclusive composite interval mapping. The 1BL QTL was probably the pleiotropic gene Lr46/Yr29/Sr58. QYr.nwafu-6AL (hereafter named YrJ44), mapped in a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479, was more effective than Yr29 in reducing disease severity and relative area under the disease progress curve (rAUDPC). RILs harboring both YrJ44 and Yr29 displayed levels of SR equal to the resistant parent JM44. The AQP markers linked with YrJ44 were polymorphic and significantly correlated with stripe rust resistance in a panel of 1,019 wheat cultivars and breeding lines. These results suggested that adequate SR resistance can be obtained by combining YrJ44 and Yr29 and the AQP markers can be used in breeding for durable stripe rust resistance.

A major yellow rust resistance QTL on chromosome 6A shows increased frequency in recent Norwegian spring wheat cultivars and breeding lines

KEY MESSAGE

A major yellow rust resistance QTL, QYr.nmbu.6A, contributed consistent adult plant resistance in field trials across Europe, China, Kenya and Mexico. Puccinia striiformis f. sp. tritici, causing wheat yellow rust (YR), is one of the most devastating biotrophic pathogens affecting global wheat yields. Owing to the recent epidemic of the PstS10 race group in Europe, yellow rust has become a reoccurring disease in Norway since 2014. As all stage resistances (ASR) (or seedling resistances) are usually easily overcome by pathogen evolution, deployment of durable adult plant resistance (APR) is crucial for yellow rust resistance breeding. In this study, we assessed a Nordic spring wheat association mapping panel (n = 301) for yellow rust field resistance in seventeen field trials from 2015 to 2021, including nine locations in six countries across four different continents. Nine consistent QTL were identified across continents by genome-wide association studies (GWAS). One robust QTL on the long arm of chromosome 6A, QYr.nmbu.6A, was consistently detected in nine out of the seventeen trials. Haplotype analysis of QYr.nmbu.6A confirmed significant QTL effects in all tested environments and the effect was also validated using an independent panel of new Norwegian breeding lines. Increased frequency of the resistant haplotype was found in new varieties and breeding lines in comparison to older varieties and landraces, implying that the resistance might have been selected for due to the recent changes in the yellow rust pathogen population in Europe.

Toward combining qualitative race-specific and quantitative race-nonspecific disease resistance by genomic selection

A novel genomic selection strategy offers the unique opportunity to develop qualitative race-specific resistant varieties that possess high levels of the more durable quantitative race-nonspecific resistance in their genetic background. Race-specific qualitative resistance genes (R-genes) are conferring complete resistance in many pathosystems, but are frequently overcome by new virulent pathogen races. Once the deployed R-genes are overcome, a wide variation of quantitative disease resistance (QDR) can be observed in a set of previously race-specific, i.e., completely resistant genotypes-a phenomenon known as "vertifolia effect." This race-nonspecific QDR is considered to be more durable in the long term, but provides merely a partial protection against pathogens. This simulation study aimed to detangle race-specific R-gene-mediated resistance of pending selection candidates and the QDR in their genetic background by employing different genomic selection strategies. True breeding values that reflected performance data for rust resistance in wheat were simulated, and used in a recurrent genomic selection based on several prediction models and training population designs. Using training populations that were devoid of race-specific R-genes was thereby pivotal for an efficient improvement of QDR in the long term. Marker-assisted preselection for the presence of R-genes followed by a genomic prediction for accumulating the many small to medium effect loci underlying QDR in the genetic background of race-specific resistant genotypes appeared furthermore to be a promising approach to select simultaneously for both types of resistance. The practical application of such a knowledge-driven genomic breeding strategy offers the opportunity to develop varieties with multiple layers of resistance, which have the potential to prevent intolerable crop losses under epidemic situations by displaying a high level of QDR even when race-specific R-genes have been overcome by evolving pathogen populations.

Wheat Omics: Advancements and Opportunities

Plant omics, which includes genomics, transcriptomics, metabolomics and proteomics, has played a remarkable role in the discovery of new genes and biomolecules that can be deployed for crop improvement. In wheat, great insights have been gleaned from the utilization of diverse omics approaches for both qualitative and quantitative traits. Especially, a combination of omics approaches has led to significant advances in gene discovery and pathway investigations and in deciphering the essential components of stress responses and yields. Recently, a Wheat Omics database has been developed for wheat which could be used by scientists for further accelerating functional genomics studies. In this review, we have discussed various omics technologies and platforms that have been used in wheat to enhance the understanding of the stress biology of the crop and the molecular mechanisms underlying stress tolerance.

Genetic Basis of Resistance to Warrior (-) Yellow Rust Race at the Seedling Stage in Current Central and Northern European Winter Wheat Germplasm

To evaluate genetic variability and seedling plant response to a dominating Warrior (-) race of yellow rust in Northern and Central European germplasm, we used a population of 229 winter wheat cultivars and breeding lines for a genome-wide association study (GWAS). A wide variation in yellow rust disease severity (based on infection types 1-9) was observed in this panel. Four breeding lines, TS049 (from Austria), TS111, TS185, and TS229 (from Germany), and one cultivar, TS158 (KWS Talent), from Germany were found to be resistant to Warrior (-) FS 53/20 and Warrior (-) G 23/19. The GWAS identified five significant SNPs associated with yellow rust on chromosomes 1B, 2A, 5B, and 7A for Warrior (-) FS 53/20, while one SNP on chromosome 5B was associated with disease for Warrior (-) G 23/19. For Warrior (-) FS 53/20, we discovered a new QTL for yellow rust resistance associated with the marker Kukri_c5357_323 on chromosome 1B. The resistant alleles G and T at the marker loci Kukri_c5357_323 on chromosome 1B and Excalibur_c17489_804 on chromosome 5B showed the largest effects (1.21 and 0.81, respectively) on the severity of Warrior (-) FS 53/20 and Warrior (-) G 23/19. Our results provide the basis for knowledge-based resistance breeding in the face of the enormous impact of the Warrior (-) race on wheat production in Europe.

Comparison of linear and semi-parametric models incorporating genomic, pedigree, and associated loci information for the prediction of resistance to stripe rust in an Austrian winter wheat breeding program

We used a historical dataset on stripe rust resistance across 11 years in an Austrian winter wheat breeding program to evaluate genomic and pedigree-based linear and semi-parametric prediction methods. Stripe rust (yellow rust) is an economically important foliar disease of wheat (Triticum aestivum L.) caused by the fungus Puccinia striiformis f. sp. tritici. Resistance to stripe rust is controlled by both qualitative (R-genes) and quantitative (small- to medium-effect quantitative trait loci, QTL) mechanisms. Genomic and pedigree-based prediction methods can accelerate selection for quantitative traits such as stripe rust resistance. Here we tested linear and semi-parametric models incorporating genomic, pedigree, and QTL information for cross-validated, forward, and pairwise prediction of adult plant resistance to stripe rust across 11 years (2008-2018) in an Austrian winter wheat breeding program. Semi-parametric genomic modeling had the greatest predictive ability and genetic variance overall, but differences between models were small. Including QTL as covariates improved predictive ability in some years where highly significant QTL had been detected via genome-wide association analysis. Predictive ability was moderate within years (cross-validated) but poor in cross-year frameworks.