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Sources of new genetic variability have been limited to existing germplasm in the past. Wheat has been studied extensively for various agronomic traits located throughout the genome. The large size of the chromosomes and the ability of its polyploid genome to tolerate the addition or loss of chromosomes facilitated rapid progress in the early study of wheat genetics using cytogenetic techniques. At the same time, its large genome size has limited the progress in genetic characterization studies focused on diploid species, with a small genome and genetic engineering procedures already developed. Today, the genetic transformation and gene editing procedures offer attractive alternatives to conventional techniques for breeding wheat because they allow one or more of the genes to be introduced or altered into an elite cultivar without affecting its genetic background. Recently, significant advances have been made in regenerating various plant tissues, providing the essential basis for regenerating transgenic plants. In addition, Agrobacterium-mediated, biolistic, and in planta particle bombardment (iPB) gene delivery procedures have been developed for wheat transformation and advanced transgenic wheat development. As a result, several useful genes are now available that have been transferred or would be helpful to be transferred to wheat in addition to the current traditional effort to improve trait values, such as resistance to abiotic and biotic factors, grain quality, and plant architecture. Furthermore, the in planta genome editing method will significantly contribute to the social implementation of genome-edited crops to innovate the breeding pipeline and leverage unique climate adaptations.

Anther extrusion (AE) is the most important male floral trait for hybrid wheat seed production. AE is a complex quantitative trait that is difficult to phenotype reliably in field experiments not only due to high genotype-by-environment effects but also due to the short expression window in the field condition. In this study, we conducted a genome-wide association scan (GWAS) and explored the possibility of applying genomic prediction (GP) for AE in the CIMMYT hybrid wheat breeding program. An elite set of male lines (n = 603) were phenotype for anther count (AC) and anther visual score (VS) across three field experiments in 2017–2019 and genotyped with the 20K Infinitum is elect SNP array. GWAS produced five marker trait associations with small effects. For GP, the main effects of lines (L), environment (E), genomic (G) and pedigree relationships (A), and their interaction effects with environments were used to develop seven statistical models of incremental complexity. The base model used only L and E, whereas the most complex model included L, E, G, A, and G × E and A × E. These models were evaluated in three cross-validation scenarios (CV0, CV1, and CV2). In cross-validation CV0, data from two environments were used to predict an untested environment; in random cross-validation CV1, the test set was never evaluated in any environment; and in CV2, the genotypes in the test set were evaluated in only a subset of environments. The prediction accuracies ranged from −0.03 to 0.74 for AC and −0.01 to 0.54 for VS across different models and CV schemes. For both traits, the highest prediction accuracies with low variance were observed in CV2, and inclusion of the interaction effects increased prediction accuracy for AC only. In CV0, the prediction accuracy was 0.73 and 0.45 for AC and VS, respectively, indicating the high reliability of across environment prediction. Genomic prediction appears to be a very reliable tool for AE in hybrid wheat breeding. Moreover, high prediction accuracy in CV0 demonstrates the possibility of implementing genomic selection across breeding cycles in related germplasm, aiding the rapid breeding cycle.

In this study, we used genotype × environment interactions (G×E) models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by environmental covariables. We use five genomic and pedigree models (M1–M5) under four cross-validation (CV) schemes: prediction of hybrids when the training set (i) includes hybrids of all males and females evaluated only in some environments (T2FM), (ii) excludes all progenies from a randomly selected male (T1M), (iii) includes all progenies from 20% randomly selected females in combination with all males (T1F), and (iv) includes one randomly selected male plus 40% randomly selected females that were crossed with it (T0FM). Models were tested on a total of 1888 wheat ( L.) hybrids including 18 males and 667 females in three consecutive years. For grain yield, the most complex model (M5) under T2FM had slightly higher prediction accuracy than the less complex model. For T1F, the prediction accuracy of hybrids for grain yield and other traits of the most complete model was 0.50 to 0.55. For T1M, Model M3 exhibited high prediction accuracies for flowering traits (0.71), whereas the more complex model (M5) demonstrated high accuracy for grain yield (0.5). For T0FM, the prediction accuracy for grain yield of Model M5 was 0.61. Including genomic and pedigree gave relatively high prediction accuracy even when both parents were untested. Results show that it is possible to predict unobserved hybrids when modeling genomic general combining ability (GCA) and specific combining ability (SCA) and their interactions with environments.

Wheat rusts continue to cause significant losses worldwide despite major efforts given to their genetic control. This is due to frequent evolution and selection of virulence in pathogen overcoming the deployed race-specific resistance genes. Although the life of effective race-specific resistance genes can be prolonged by using gene combinations, an alternative approach being implemented at CIMMYT is to deploy varieties that posses adult plant resistance (APR) based on combinations of minor, slow rusting genes. When present alone, the APR genes do not confer adequate resistance especially under high disease pressure; however, combinations of 4 or 5 minor genes usually result in “near-immunity” or a high level of resistance. Although only a few APR genes are catalogued, various APR QTLs are now known and could lead to further characterization of additional genes. Four characterized genes have pleiotropic effects in conferring partial APR to all 3 rusts and powdery mildew, thus simplifying the task of breeding wheat varieties that are resistant to multiple diseases. Significant progress was made recently in developing high-yielding wheat germplasm that possesses high levels of APR to all three rusts by implementing a Mexico-Kenya shuttle breeding scheme. Parents with APR to Ug99 were hybridized with high-yielding parents that had adequate to high levels of APR to leaf rust and yellow rust. Segregating populations and advanced lines from these crosses were selected under high rust pressures in Mexico (leaf rust and yellow rust) and Kenya (Ug99 stem rust and yellow rust) to identify high-yielding progenies that possess high to adequate APR to all three rusts. International distribution of these high-yielding wheats is underway through CIMMYT international yield trials and screening nurseries. It is expected that several wheat varieties with APR to three rusts will be released and grown in various countries in the near-future that will allow determining the durability of resistance.

Rusts, a fungal disease as old as its host plant wheat, an enemy as old as wheat, has caused havoc for over 8,000 years. As the rust pathogens can evolve into new virulent races which quickly defeat to qualitative or vertical the resistance that primarily rely on race specificity over time, adult plant resistance (APR) has often been found to be race non-specific and hence is considered have been proven to be a more to be a more reliable and durable strategy to combat this malady. Over decades sets of donor lines have been identified at International Maize and Wheat Improvement Center (CIMMYT) representing a wide range of APR sources in wheat. In this study, using nine donors and a common parent ‘PBW343’, a popular Green Revolution variety at CIMMYT, the nested association mapping (NAM) population of 1122 lines was constructed to understand the APR genetics underlying these founder lines. Thirty-four QTL were associated with APR to rusts, and 20 of 34 QTL had pleiotropic effects on SR, YR and LR resistance. Three chromosomal regions, associated with known APR genes (Sr58/Yr29/Lr46, Sr2/Yr30/Lr27, and Sr57/Yr18/Lr34), were also identified, 13 previously reported QTL regions were validated. Of the 18 QTL first detected in this study, 7 were pleiotropic QTL, distributing on chromosomes 3A, 3B, 6B, 3D, and 6D. The present investigation revealed the genetic relationship of historical APR donor lines, the novel knowledge on APR, as well as the new analytical methodologies to facilitate the applications of NAM design in crop genetics. Results shown in this study will aid the parental selection for hybridization in wheat breeding, and envision the future rust management breeding for addressing potential threat to wheat production and food security.