Enhanced radiation use efficiency and grain filling rate as the main drivers of grain yield genetic gains in the CIMMYT elite spring wheat yield trial

Common wheat (Triticum aestivum L.) is a major staple food crop, providing a fifth of food calories and proteins to the world's human population. Despite the impressive growth in global wheat production in recent decades, further increases in grain yield are required to meet future demands. Here we estimated genetic gain and genotype stability for grain yield (GY) and determined the trait associations that contributed uniquely or in combination to increased GY, through a retrospective analysis of top-performing genotypes selected from the elite spring wheat yield trial (ESWYT) evaluated internationally during a 14-year period (2003 to 2016). Fifty-six ESWYT genotypes and four checks were sown under optimally irrigated conditions in three phenotyping trials during three consecutive growing seasons (2018-2019 to 2020-2021) at Norman E. Borlaug Research Station, Ciudad Obregon, Mexico. The mean GY rose from 6.75 (24th ESWYT) to 7.87 t ha-1 (37th ESWYT), representing a cumulative increase of 1.12 t ha-1. The annual genetic gain for GY was estimated at 0.96% (65 kg ha-1 year-1) accompanied by a positive trend in genotype stability over time. The GY progress was mainly associated with increases in biomass (BM), grain filling rate (GFR), total radiation use efficiency (RUE_total), grain weight per spike (GWS), and reduction in days to heading (DTH), which together explained 95.5% of the GY variation. Regression lines over the years showed significant increases of 0.015 kg m-2 year-1 (p < 0.01), 0.074 g m-2 year-1 (p < 0.05), and 0.017 g MJ-1 year-1 (p < 0.001) for BM, GFR, and RUE_total, respectively. Grain weight per spike exhibited a positive but no significant trend (0.014 g year-1, p = 0.07), whereas a negative tendency for DTH was observed (- 0.43 days year-1, p < 0.001). Analysis of the top ten highest-yielding genotypes revealed differential GY-associated trait contributions, demonstrating that improved GY can be attained through different mechanisms and indicating that no single trait criterion is adopted by CIMMYT breeders for developing new superior lines. We conclude that CIMMYT's Bread Wheat Breeding Program has continued to deliver adapted and more productive wheat genotypes to National partners worldwide, mainly driven by enhancing RUE_total and GFR and that future yield increases could be achieved by intercrossing genetically diverse top performer genotypes.

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

MOTIVATION

Developing new crop varieties with superior performance is highly important to ensure robust and sustainable global food security. The speed of variety development is limited by long field cycles and advanced generation selections in plant breeding programs. While methods to predict yield from genotype or phenotype data have been proposed, improved performance and integrated models are needed.

RESULTS

We propose a machine learning model that leverages both genotype and phenotype measurements by fusing genetic variants with multiple data sources collected by unmanned aerial systems. We use a deep multiple instance learning framework with an attention mechanism that sheds light on the importance given to each input during prediction, enhancing interpretability. Our model reaches 0.754 ± 0.024 Pearson correlation coefficient when predicting yield in similar environmental conditions; a 34.8% improvement over the genotype-only linear baseline (0.559 ± 0.050). We further predict yield on new lines in an unseen environment using only genotypes, obtaining a prediction accuracy of 0.386 ± 0.010, a 13.5% improvement over the linear baseline. Our multi-modal deep learning architecture efficiently accounts for plant health and environment, distilling the genetic contribution and providing excellent predictions. Yield prediction algorithms leveraging phenotypic observations during training therefore promise to improve breeding programs, ultimately speeding up delivery of improved varieties.

AVAILABILITY AND IMPLEMENTATION

Available at https://github.com/BorgwardtLab/PheGeMIL (code) and https://doi.org/doi:10.5061/dryad.kprr4xh5p (data).

Mining Sources of Resistance to Durum Leaf Rust among Tetraploid Wheat Accessions from CIMMYT's Germplasm Bank

A collection of 482 tetraploid wheat accessions from the CIMMYT Germplasm Bank was screened in the greenhouse for resistance to leaf rust disease caused by the fungus Puccinia triticina E. The accessions were screened against two races CBG/BP and BBG/BP in the field at two locations: against race CBG/BP at the Norman E. Borlaug Experimental Station (CENEB) located in the Yaqui Valley in the northern state of Sonora in Mexico during the 2014-2015 growing season; and against race BBG/BP at CIMMYT headquarters in El Batan, Texcoco, in the state of Mexico in the summer of 2015. Among the accessions, 79 durum genotypes were identified, of which 68 continued demonstrating their resistance in the field (past the seedling stage) against the two leaf rust races. An additional set of 41 genotypes was susceptible at the seedling stage, but adult plant race-specific resistance was identified in the field. The 79 seedling-resistant genotypes were tested against 15 different leaf rust races at the seedling stage to measure the usefulness of their resistance in a breeding program. Among the 79 accessions tested, 35 were resistant to all races used in the tests. Two sample sources, CIMMYT (18/35) pre-breeding germplasm and Ethiopian landraces (17/35), showed seedling resistance to all races tested except for seven landraces from Ethiopia, which became susceptible to the Cirno race identified in 2017.

Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data

The success of genomic selection (GS) in breeding schemes relies on its ability to provide accurate predictions of unobserved lines at early stages. Multigeneration data provides opportunities to increase the training data size and thus, the likelihood of extracting useful information from ancestors to improve prediction accuracy. The genomic best linear unbiased predictions (GBLUPs) are performed by borrowing information through kinship relationships between individuals. Multigeneration data usually becomes heterogeneous with complex family relationship patterns that are increasingly entangled with each generation. Under these conditions, historical data may not be optimal for model training as the accuracy could be compromised. The sparse selection index (SSI) is a method for training set (TRN) optimization, in which training individuals provide predictions to some but not all predicted subjects. We added an additional trimming process to the original SSI (trimmed SSI) to remove less important training individuals for prediction. Using a large multigeneration (8 yr) wheat (Triticum aestivum L.) grain yield dataset (n = 68,836), we found increases in accuracy as more years are included in the TRN, with improvements of ∼0.05 in the GBLUP accuracy when using 5 yr of historical data relative to when using only 1 yr. The SSI method showed a small gain over the GBLUP accuracy but with an important reduction on the TRN size. These reduced TRNs were formed with a similar number of subjects from each training generation. Our results suggest that the SSI provides a more stable ranking of genotypes than the GBLUP as the TRN becomes larger.

Stripe rust and leaf rust resistance in CIMMYT wheat line "Mucuy" is conferred by combinations of race-specific and adult-plant resistance loci

Developing wheat varieties with durable resistance is a core objective of the International Maize and Wheat Improvement Center (CIMMYT) and many other breeding programs worldwide. The CIMMYT advanced wheat line "Mucuy" displayed high levels of resistance to stripe rust (YR) and leaf rust (LR) in field evaluations in Mexico and several other countries. To determine the genetic basis of YR and LR resistance, 138 F₅ recombinant inbred lines (RILs) derived from the cross of Apav#1× Mucuy were phenotyped for YR responses from 2015 to 2020 at field sites in India, Kenya, and Mexico, and LR in Mexico. Seedling phenotyping for YR and LR responses was conducted in the greenhouse in Mexico using the same predominant races as in field trials. Using 12,681 polymorphic molecular markers from the DArT, SNP, and SSR genotyping platforms, we constructed genetic linkage maps and QTL analyses that detected seven YR and four LR resistance loci. Among these, a co-located YR/LR resistance loci was identified as Yr29/Lr46, and a seedling stripe rust resistance gene YrMu was mapped on the 2AS/2NS translocation. This fragment also conferred moderate adult plant resistance (APR) under all Mexican field environments and in one season in Kenya. Field trial phenotyping with Lr37-virulent Puccinia triticina races indicated the presence of an APR QTL accounting for 18.3-25.5% of the LR severity variation, in addition to a novel YR resistance QTL, QYr.cim-3DS, derived from Mucuy. We developed breeder-friendly KASP and indel molecular markers respectively for Yr29/Lr46 and YrMu. The current study validated the presence of known genes and identified new resistance loci, a QTL combination effect, and flanking markers to facilitate accelerated breeding for genetically complex, durable rust resistance.

Dissecting the Genetic Architecture of Phenology Affecting Adaptation of Spring Bread Wheat Genotypes to the Major Wheat-Producing Zones in India

Spring bread wheat adaptation to diverse environments is supported by various traits such as phenology and plant architecture. A large-scale genome-wide association study (GWAS) was designed to investigate and dissect the genetic architecture of phenology affecting adaptation. It used 48 datasets from 4,680 spring wheat lines. For 8 years (2014-2021), these lines were evaluated for days to heading (DH) and maturity (DM) at three sites: Jabalpur, Ludhiana, and Samastipur (Pusa), which represent the three major Indian wheat-producing zones: the Central Zone (CZ), North-Western Plain Zone (NWPZ), and North-Eastern Plain Zone (NEPZ), respectively. Ludhiana had the highest mean DH of 103.8 days and DM of 148.6 days, whereas Jabalpur had the lowest mean DH of 77.7 days and DM of 121.6 days. We identified 119 markers significantly associated with DH and DM on chromosomes 5B (76), 2B (18), 7D (10), 4D (8), 5A (1), 6B (4), 7B (1), and 3D (1). Our results clearly indicated the importance of the photoperiod-associated gene (Ppd-B1) for adaptation to the NWPZ and the Vrn-B1 gene for adaptation to the NEPZ and CZ. A maximum variation of 21.1 and 14% was explained by markers 2B_56134146 and 5B_574145576 linked to the Ppd-B1 and Vrn-B1 genes, respectively, indicating their significant role in regulating DH and DM. The results provide important insights into the genomic regions associated with the two phenological traits that influence adaptation to the major wheat-producing zones in India.

Genome-Wide Association Mapping Identifies Key Genomic Regions for Grain Zinc and Iron Biofortification in Bread Wheat

Accelerating breeding efforts for developing biofortified bread wheat varieties necessitates understanding the genetic control of grain zinc concentration (GZnC) and grain iron concentration (GFeC). Hence, the major objective of this study was to perform genome-wide association mapping to identify consistently significant genotyping-by-sequencing markers associated with GZnC and GFeC using a large panel of 5,585 breeding lines from the International Maize and Wheat Improvement Center. These lines were grown between 2018 and 2021 in an optimally irrigated environment at Obregon, Mexico, while some of them were also grown in a water-limiting drought-stressed environment and a space-limiting small plot environment and evaluated for GZnC and GFeC. The lines showed a large and continuous variation for GZnC ranging from 27 to 74.5 ppm and GFeC ranging from 27 to 53.4 ppm. We performed 742,113 marker-traits association tests in 73 datasets and identified 141 markers consistently associated with GZnC and GFeC in three or more datasets, which were located on all wheat chromosomes except 3A and 7D. Among them, 29 markers were associated with both GZnC and GFeC, indicating a shared genetic basis for these micronutrients and the possibility of simultaneously improving both. In addition, several significant GZnC and GFeC associated markers were common across the irrigated, water-limiting drought-stressed, and space-limiting small plots environments, thereby indicating the feasibility of indirect selection for these micronutrients in either of these environments. Moreover, the many significant markers identified had minor effects on GZnC and GFeC, suggesting a quantitative genetic control of these traits. Our findings provide important insights into the complex genetic basis of GZnC and GFeC in bread wheat while implying limited prospects for marker-assisted selection and the need for using genomic selection.

Identification and Characterization of Resistance Loci to Wheat Leaf Rust and Stripe Rust in Afghan Landrace "KU3067"

Leaf rust and stripe rust are important wheat diseases worldwide causing significant losses where susceptible varieties are grown. Resistant cultivars offer long-term control and reduce the use of hazardous chemicals, which can be detrimental to both human health and the environment. Land races have been a valuable resource for mining new genes for various abiotic and biotic stresses including wheat rusts. Afghan wheat landrace "KU3067" displayed high seedling infection type (IT) for leaf rust and low IT for stripe rust; however, it displayed high levels of field resistance for both rusts when tested for multiple seasons against the Mexican rust isolates. This study focused on identifying loci-conferring seedling resistance to stripe rust, and also loci-conferring adult plant resistance (APR) against the Mexican races of leaf rust and stripe rust. A backcrossed inbred line (BIL) population advanced to the BC1F₅ generation derived from the cross of KU3067 and Apav (triple rust susceptible line) was used for both, inheritance and QTL mapping studies. The population and parents were genotyped with Diversity Arrays Technology-genotyping-by-sequencing (DArT-Seq) and phenotyped for leaf rust and stripe rust response at both seedling and adult plant stages during multiple seasons in Mexico with relevant pathotypes. Mapping results identified an all-stage resistance gene for stripe rust, temporarily designated as YrKU, on chromosome 7BL. In total, six QTL-conferring APR to leaf rust on 1AS, 2AL, 4DL, 6BL, 7AL, and 7BL, and four QTL for stripe rust resistance on 1BS, 2AL, 4DL, and 7BL were detected in the analyses. Among these, pleiotropic gene Lr67/Yr46 on 4DL with a significantly large effect is the first report in an Afghan landrace-conferring resistance to both leaf and stripe rusts. QLr.cim-7BL/YrKU showed pleiotropic resistance to both rusts and explained 7.5-17.2 and 12.6-19.3% of the phenotypic variance for leaf and stripe rusts, respectively. QYr.cim-1BS and QYr.cim-2AL detected in all stripe environments with phenotypic variance explained (PVE) 12.9-20.5 and 5.4-12.5%, and QLr.cim-6BL are likely to be new. These QTL and their closely linked markers will be useful for fine mapping and marker-assisted selection (MAS) in breeding for durable resistance to multiple rust diseases.

Adult plant stem rust resistance in durum wheat Glossy Huguenot: mapping, marker development and validation

Adult plant stem rust resistance locus, QSrGH.cs-2AL, was identified in durum wheat Glossy Huguenot and mendelised as Sr63. Markers closely linked with Sr63 were developed. An F₃ population from a Glossy Huguenot (GH)/Bansi cross used in a previous Australian study was advanced to F₆ for molecular mapping of adult plant stem rust resistance. Maturity differences among F₆ lines confounded assessments of stem rust response. GH was crossed with a stem rust susceptible F₆ recombinant inbred line (RIL), GHB14 (M14), with similar maturity and an F_6:7 population was developed through single seed descent method. F₇ and F₈ RILs were tested along with the parents at different locations. The F₆ individual plants and both parents were genotyped using the 90 K single nucleotide polymorphism (SNP) wheat array. Stem rust resistance QTL on the long arms of chromosomes 1B (QSrGH.cs-1BL) and 2A (QSrGH.cs-2AL) were detected. QSrGH.cs-1BL and QSrGH.cs-2AL were both contributed by GH and explained 22% and 18% adult plant stem rust response variation, respectively, among GH/M14 RIL population. RILs carrying combinations of these QTL reduced more than 14% stem rust severity compared to those that possessed QSrGH.cs-1BL and QSrGH.cs-2AL individually. QSrGH.cs1BL was demonstrated to be the same as Sr58/Lr46/Yr29/Pm39 through marker genotyping. Lines lacking QSrGH.cs-1BL were used to Mendelise QSrGH.cs-2AL. Based on genomic locations of previously catalogued stem rust resistance genes and the QSrGH.cs-2AL map, it appeared to represent a new APR locus and was permanently named Sr63. SNP markers associated with Sr63 were converted to kompetetive allele-specific PCR (KASP) assays and were validated on a set of durum cultivars.

Genome-Wide Association Mapping Indicates Quantitative Genetic Control of Spot Blotch Resistance in Bread Wheat and the Favorable Effects of Some Spot Blotch Loci on Grain Yield

Spot blotch caused by the fungus Bipolaris sorokiniana poses a serious threat to bread wheat production in warm and humid wheat-growing regions of the world. Hence, the major objective of this study was to identify consistent genotyping-by-sequencing (GBS) markers associated with spot blotch resistance using genome-wide association mapping on a large set of 6,736 advanced bread wheat breeding lines from the International Maize and Wheat Improvement Center. These lines were phenotyped as seven panels at Agua Fria, Mexico between the 2013-2014 and 2019-2020 crop cycles. We identified 214 significant spot blotch associated GBS markers in all the panels, among which only 96 were significant in more than one panel, indicating a strong environmental effect on the trait and highlights the need for multiple phenotypic evaluations to identify lines with stable spot blotch resistance. The 96 consistent GBS markers were on chromosomes 1A, 1B, 1D, 2A, 3B, 4A, 5B, 5D, 6B, 7A, 7B, and 7D, including markers possibly linked to the Lr46, Sb1, Sb2 and Sb3 genes. We also report the association of the 2NS translocation from Aegilops ventricosa with spot blotch resistance in some environments. Moreover, the spot blotch favorable alleles at the 2NS translocation and two markers on chromosome 3BS (3B_2280114 and 3B_5601689) were associated with increased grain yield evaluated at several environments in Mexico and India, implying that selection for favorable alleles at these loci could enable simultaneous improvement for high grain yield and spot blotch resistance. Furthermore, a significant relationship between the percentage of favorable alleles in the lines and their spot blotch response was observed, which taken together with the multiple minor effect loci identified to be associated with spot blotch in this study, indicate quantitative genetic control of resistance. Overall, the results presented here have extended our knowledge on the genetic basis of spot blotch resistance in bread wheat and further efforts to improve genetic resistance to the disease are needed for reducing current and future losses under climate change.

Molecular Characterization of Genomic Regions for Adult Plant Resistance to Stem Rust in a Spring Wheat Mapping Population

Adult plant resistance (APR) to wheat stem rust has been one of the approaches for resistance breeding since the evolution of the Ug99 race group and other races. This study was conducted to dissect and understand the genetic basis of APR to stem rust in spring wheat line 'Copio'. A total of 176 recombinant inbred lines (RILs) from the cross of susceptible parent 'Apav' with Copio were phenotyped for stem rust resistance in six environments. Composite interval mapping using 762 genotyping-by-sequencing markers identified 16 genomic regions conferring stem rust resistance. Assays with gene-linked molecular markers revealed that Copio carried known APR genes Sr2 and Lr46/Yr29/Sr58 in addition to the 2NS/2AS translocation that harbors race-specific genes Sr38, Lr37, and Yr17. Three quantitative trait loci (QTLs) were mapped on chromosomes 2B, two QTLs on chromosomes 3A, 3B, and 6A each, and one QTL on each of chromosomes 2A, 1B, 2D, 4B, 5D, 6D, and 7A. The QTL QSr.umn.5D is potentially a new resistance gene and contributed to quantitative resistance in Copio. The RILs with allelic combinations of Sr2, Sr38, and Sr58 had 27 to 39% less stem rust coefficient of infection in all field environments compared with RILs with none of these genes, and this gene combination was most effective in the U.S. environments. We conclude that Copio carries several genes that provide both race-specific and non-race-specific resistance to diverse races of stem rust fungus and can be used by breeding programs in pyramiding other effective genes to develop durable resistance in wheat.

Juvenile Heat Tolerance in Wheat for Attaining Higher Grain Yield by Shifting to Early Sowing in October in South Asia

Farmers in northwestern and central India have been exploring to sow their wheat much earlier (October) than normal (November) to sustain productivity by escaping terminal heat stress and to utilize the available soil moisture after the harvesting of rice crop. However, current popular varieties are poorly adapted to early sowing due to the exposure of juvenile plants to the warmer temperatures in the month of October and early November. Therefore, a study was undertaken to identify wheat genotypes suited to October sowing under warmer temperatures in India. A diverse collection of 3322 bread wheat varieties and elite lines was prepared in CIMMYT, Mexico, and planted in the 3rd week of October during the crop season 2012-2013 in six locations (Ludhiana, Karnal, New Delhi, Indore, Pune and Dharwad) spread over northwestern plains zone (NWPZ) and central and Peninsular zone (CZ and PZ; designated as CPZ) of India. Agronomic traits data from the seedling stage to maturity were recorded. Results indicated substantial diversity for yield and yield-associated traits, with some lines showing indications of higher yields under October sowing. Based on agronomic performance and disease resistance, the top 48 lines (and two local checks) were identified and planted in the next crop season (2013-2014) in a replicated trial in all six locations under October sowing (third week). High yielding lines that could tolerate higher temperature in October sowing were identified for both zones; however, performance for grain yield was more promising in the NWPZ. Hence, a new trial of 30 lines was planted only in NWPZ under October sowing. Lines showing significantly superior yield over the best check and the most popular cultivars in the zone were identified. The study suggested that agronomically superior wheat varieties with early heat tolerance can be obtained that can provide yield up to 8 t/ha by planting in the third to fourth week of October.

Identification of Two New Loci for Adult Plant Resistance to Leaf Rust and Stripe Rust in the Chinese Wheat Variety 'Neimai 836'

The characterization of leaf rust (caused by Puccinia triticina) and stripe rust (caused by Puccinia striiformis f. sp. tritici) resistance genes is the basis for breeding resistant wheat varieties and managing epidemics of these diseases in wheat. A cross between the susceptible wheat variety 'Apav#1' and resistant variety 'Neimai 836' was used to develop a mapping population containing 148 F₅ recombinant inbred lines (RILs). Leaf rust phenotyping was done in field trials at Ciudad Obregón, Mexico, in 2017 and 2018, and stripe rust data were generated at Toluca, Mexico, in 2017 and in Mianyang, Ezhou, and Gansu, China, in 2019. Inclusive complete interval mapping (ICIM) was used to create a genetic map and identify significant resistance quantitative trait loci (QTL) with 2,350 polymorphic markers from a 15K wheat single-nucleotide polymorphism (SNP) array and simple-sequence repeats (SSRs). The pleiotropic multipathogen resistance gene Lr46/Yr29 and four QTL were identified, including two new loci, QLr.hzau-3BL and QYr.hzau-5AL, which explained 3 to 16% of the phenotypic variation in resistance to leaf rust and 7 to 14% of that to stripe rust. The flanking SNP markers for the two loci were converted to Kompetitive Allele-Specific PCR (KASP) markers and used to genotype a collection of 153 wheat lines, indicating the Chinese origin of the loci. Our results suggest that Neimai 836, which has been used as a parent for many wheat varieties in China, could be a useful source of high-level resistance to both leaf rust and stripe rust.

Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines

Wheat grain yield (GY) improvement using genomic tools is important for achieving yield breakthroughs. To dissect the genetic architecture of wheat GY potential and stress-resilience, we have designed this large-scale genome-wide association study using 100 datasets, comprising 105,000 GY observations from 55,568 wheat lines evaluated between 2003 and 2019 by the International Maize and Wheat Improvement Center and national partners. We report 801 GY-associated genotyping-by-sequencing markers significant in more than one dataset and the highest number of them were on chromosomes 2A, 6B, 6A, 5B, 1B and 7B. We then used the linkage disequilibrium (LD) between the consistently significant markers to designate 214 GY-associated LD-blocks and observed that 84.5% of the 58 GY-associated LD-blocks in severe-drought, 100% of the 48 GY-associated LD-blocks in early-heat and 85.9% of the 71 GY-associated LD-blocks in late-heat, overlapped with the GY-associated LD-blocks in the irrigated-bed planting environment, substantiating that simultaneous improvement for GY potential and stress-resilience is feasible. Furthermore, we generated the GY-associated marker profiles and analyzed the GY favorable allele frequencies for a large panel of 73,142 wheat lines, resulting in 44.5 million datapoints. Overall, the extensive resources presented in this study provide great opportunities to accelerate breeding for high-yielding and stress-resilient wheat varieties.

Target Population of Environments for Wheat Breeding in India: Definition, Prediction and Genetic Gains

In this study, we defined the target population of environments (TPE) for wheat breeding in India, the largest wheat producer in South Asia, and estimated the correlated response to the selection and prediction ability of five selection environments (SEs) in Mexico. We also estimated grain yield (GY) gains in each TPE. Our analysis used meteorological, soil, and GY data from the international Elite Spring Wheat Yield Trials (ESWYT) distributed by the International Maize and Wheat Improvement Center (CIMMYT) from 2001 to 2016. We identified three TPEs: TPE 1, the optimally irrigated Northwestern Plain Zone; TPE 2, the optimally irrigated, heat-stressed North Eastern Plains Zone; and TPE 3, the drought-stressed Central-Peninsular Zone. The correlated response to selection ranged from 0.4 to 0.9 within each TPE. The highest prediction accuracies for GY per TPE were derived using models that included genotype-by-environment interaction and/or meteorological information and their interaction with the lines. The highest prediction accuracies for TPEs 1, 2, and 3 were 0.37, 0.46, and 0.51, respectively, and the respective GY gains were 118, 46, and 123 kg/ha/year. These results can help fine-tune the breeding of elite wheat germplasm with stable yields to reduce farmers' risk from year-to-year environmental variation in India's wheat lands, which cover 30 million ha, account for 100 million tons of grain or more each year, and provide food and livelihoods for hundreds of millions of farmers and consumers in South Asia.

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

Genomic Selection for Grain Yield in the CIMMYT Wheat Breeding Program-Status and Perspectives

Genomic breeding technologies offer new opportunities for grain yield (GY) improvement in common wheat. In this study, we have evaluated the potential of genomic selection (GS) in breeding for GY in wheat by modeling a large dataset of 48,562 GY observations from the International Maize and Wheat Improvement Center (CIMMYT), including 36 yield trials evaluated between 2012 and 2019 in Obregón, Sonora, Mexico. Our key objective was to determine the value that GS can add to the current three-stage yield testing strategy at CIMMYT, and we draw inferences from predictive modeling of GY using 420 different populations, environments, cycles, and model combinations. First, we evaluated the potential of genomic predictions for minimizing the number of replications and lines tested within a site and year and obtained mean prediction accuracies (PAs) of 0.56, 0.5, and 0.42 in Stages 1, 2, and 3 of yield testing, respectively. However, these PAs were similar to the mean pedigree-based PAs indicating that genomic relationships added no value to pedigree relationships in the yield testing stages, characterized by small family-sizes. Second, we evaluated genomic predictions for minimizing GY testing across stages/years in Obregón and observed mean PAs of 0.41, 0.31, and 0.37, respectively when GY in the full irrigation bed planting (FI BP), drought stress (DS), and late-sown heat stress environments were predicted across years using genotype × environment (G × E) interaction models. Third, we evaluated genomic predictions for minimizing the number of yield testing environments and observed that in Stage 2, the FI BP, full irrigation flat planting and early-sown heat stress environments (mean PA of 0.37 ± 0.12) and the reduced irrigation and DS environments (mean PA of 0.45 ± 0.07) had moderate predictabilities among them. However, in both predictions across years and environments, the PAs were inconsistent across years and the G × E models had no advantage over the baseline model with environment and line effects. Overall, our results provide excellent insights into the predictability of a quantitative trait like GY and will have important implications on the future design of GS for GY in wheat breeding programs globally.

Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields

Breeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitative genetics study using CIMMYT's yield trials evaluated in the SEs (2013-2014 to 2017-2018), the South Asia Bread Wheat Genomic Prediction Yield Trials (SABWGPYTs) evaluated in India, Pakistan, and Bangladesh (2014-2015 to 2017-2018), and the Elite Spring Wheat Yield Trials (ESWYTs) evaluated in several sites globally (2003-2004 to 2016-2017). First, we compared the narrow-sense heritabilities in the Obregon SEs and target sites and observed that the mean heritability in the SEs was 44.2 and 92.3% higher than the mean heritabilities in the SABWGPYT and ESWYT sites, respectively. Second, we observed significant genetic correlations between a SE in Obregon and all the five SABWGPYT sites and 65.1% of the ESWYT sites. Third, we observed high ratios of response to indirect selection in the SEs of Obregon with a mean of 0.80 ± 0.21 and 2.6 ± 5.4 in the SABWGPYT and ESWYT sites, respectively. Furthermore, our results also indicated that for all the SABWGPYT sites and 82% of the ESWYT sites, a response greater than 0.5 can be achieved by indirect selection for GY in Obregon. We also performed genomic prediction for GY in the target sites using the performance of the same lines in the SEs of Obregon and observed moderate mean prediction accuracies of 0.24 ± 0.08 and 0.28 ± 0.08 in the SABWGPYT and ESWYT sites, respectively using the genotype x environment (GxE) model. However, we observed similar accuracies using the baseline model with environment and line effects and no advantage of modeling GxE interactions. Overall, this study provides important insights into the suitability of the Obregon SEs in breeding for GY, while the variable genomic predictabilities of GY and the high year-to-year GY fluctuations reported, highlight the importance of multi-environment testing across time and space to stave off GxE induced uncertainties in varietal yields.

Adult Plant Slow Rusting Genes Confer High Levels of Resistance to Rusts in Bread Wheat Cultivars From Mexico

Rust diseases continuously threaten global wheat production: stem rust, leaf rust, and yellow rust caused by Puccinia graminis f. sp. tritici, Puccinia triticina, and Puccinia striiformis f. sp. tritici, respectively. Recent studies indicated that the average losses from all these three rusts reached up to 15.04 million tons per year, which is equivalent to an annual average loss of around US $2.9 billion per year. The major focus of Mexican and worldwide breeding programs is the release of rust resistant cultivars, as this is considered the best option for controlling rust diseases. In Mexico, the emphasis has been placed on genes that confer partial resistance in the adult plant stage and against a broad spectrum of rust races since the 1970s. In this study, a set of the first-generation tall varieties developed and released in the 1940s and 1950s, the first semi-dwarfs, and other releases in Mexico, all of which showed different levels of rust resistance have been phenotyped for the three rust diseases and genotyped. Results of the molecular marker detection indicated that Lr34, Lr46, Lr67, and Lr68 alone or in different gene combinations were present among the wheat cultivars. Flag leaf tip necrosis was present in all cultivars and most were positive for brown necrosis or Pseudo Black Chaff associated with the Sr2 stem rust resistance complex. The phenotypic responses to the different rust infections indicate the presence of additional slow rusting and race-specific resistance genes. The study reveals the association of the slow rusting genes with durable resistance to the three rusts including Ug99 in cultivars bred before the green revolution such as Frontera, Supremo 211, Chapingo 48, Yaqui 50, Kentana 52, Bajio 52, Bajio 53, Yaqui 53, Chapingo 53, Yaktana Tardio 54, and Mayo 54 and their descendants after intercrossing and recombination. These slow rusting genes are the backbone of the resistance in the current Mexican germplasm.

Genome-Wide Mapping of Adult Plant Resistance to Leaf Rust and Stripe Rust in CIMMYT Wheat Line Arableu#1

Leaf (brown) rust (LR) and stripe (yellow) rust (YR), caused by Puccinia triticina and P. striiformis f. sp. tritici, respectively, significantly reduce wheat production worldwide. Disease-resistant wheat varieties offer farmers one of the most effective ways to manage these diseases. The common wheat (Triticum aestivum L.) Arableu#1, developed by the International Maize and Wheat Improvement Center and released as Deka in Ethiopia, shows susceptibility to both LR and YR at the seedling stage but a high level of adult plant resistance (APR) to the diseases in the field. We used 142 F₅ recombinant inbred lines (RILs) derived from Apav#1 × Arableu#1 to identify quantitative trait loci (QTLs) for APR to LR and YR. A total of 4,298 genotyping-by-sequencing markers were used to construct a genetic linkage map. The study identified four LR resistance QTLs and six YR resistance QTLs in the population. Among these, QLr.cim-1BL.1/QYr.cim-1BL.1 was located in the same location as Lr46/Yr29, a known pleiotropic resistance gene. QLr.cim-1BL.2 and QYr.cim-1BL.2 were also located on wheat chromosome 1BL at 37 cM from Lr46/Yr29 and may represent a new segment for pleiotropic resistance to both rusts. QLr.cim-7BL is likely Lr68 given its association with the tightly linked molecular marker cs7BLNLRR. In addition, QLr.cim-3DS, QYr.cim-2AL, QYr.cim-4BL, QYr.cim-5AL, and QYr.cim-7DS are probably new resistance loci based on comparisons with published QTLs for resistance to LR and YR. Our results showed the diversity of minor resistance QTLs in Arableu#1 and their role in conferring near-immune levels of APR to both LR and YR, when combined with the pleiotropic APR gene Lr46/Yr29.

Grain yield genetic gains and changes in physiological related traits for CIMMYT's High Rainfall Wheat Screening Nursery tested across international environments

The effects of climate change together with the projected future demand represents a huge challenge for wheat production systems worldwide. Wheat breeding can contribute to global food security through the creation of genotypes exhibiting stress tolerance and higher yield potential. The objectives of our study were to (i) estimate the annual grain yield (GY) genetic gain of High Rainfall Wheat Yield Trials (HRWYT) grown from 2007 (15th HRWYT) to 2016 (24th HRWYT) across international environments, and (ii) determine the changes in physiological traits associated with GY genetic improvement. The GY genetic gains were estimated as genetic progress per se (GYP) and in terms of local checks (GYLC). In total, 239 international locations were classified into two groups: high- and low-rainfall environments based on climate variables and trial management practices. In the high-rainfall environment, the annual genetic gains for GYP and GYLC were 3.8 and 1.17 % (160 and 65.1 kg ha-1 yr-1), respectively. In the low-rainfall environment, the genetic gains were 0.93 and 0.73 % (40 and 33.1 kg ha-1 yr-1), for GYP and GYLC respectively. The GY of the lines included in each nursery showed a significant phenotypic correlation between high- and low-rainfall environments in all the examined years and several of the five best performing lines were common in both environments. The GY progress was mainly associated with increased grain weight (R2 = 0.35 p < 0.001), days to maturity (R2 = 0.20, p < 0.001) and grain filling period (R2 = 0.06, p < 0.05). These results indicate continuous GY genetic progress and yield stability in the HRWYT germplasm developed and distributed by CIMMYT.

Four Consistent Loci Confer Adult Plant Resistance to Leaf Rust in the Durum Wheat Lines Heller#1 and Dunkler

The durum wheat lines Heller#1 and Dunkler from the International Maize and Wheat Improvement Center Global Wheat Program showed moderate and stable adult plant resistance to leaf rust under high disease pressure over field environments in northwestern Mexico. Leaf rust phenotyping was performed on two recombinant inbred line (RIL) populations derived from crosses of Heller#1 and Dunkler with the susceptible parent Atred#2, conducted under artificially induced Puccinia triticina epidemics in 2013, 2014, 2015, and 2016. The Atred#2 × Heller#1 and Atred#2 × Dunkler populations were genotyped by single nucleotide polymorphism (SNP) platforms and diversity arrays technology markers, respectively. Four leaf rust resistance quantitative trait loci were detected simultaneously in the two RIL populations: Lr46, QLr.cim-2BC, QLr.cim-5BL, and QLr.cim-6BL based on phenotypic data across all four crop seasons. They explained 11.7 to 46.8%, 7.2 to 26.1%, 8.4 to 24.1%, and 12.4 to 28.5%, respectively, of the phenotypic variation for leaf rust resistance in Atred#2 × Heller#1 and 16.3 to 56.6%, 6.7 to 15.7%, 4.1 to 10.1%, and 5.1 to 20.2% of the variation in the Atred#2 × Dunkler population. Only the resistance allele of QLr.cim-2BC was from the susceptible parent Atred#2, and resistance alleles at other loci came from the resistant parents Heller#1 and Dunkler. The SNP markers closely linked to Lr46 and QLr.cim-2BC were converted to kompetitive allele specific PCR markers for use in marker-assisted selection to improve leaf rust resistance through crosses with Heller#1 and Dunkler sources.

High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage

Genomic selection (GS) models have been validated for many quantitative traits in wheat (Triticum aestivum L.) breeding. However, those models are mostly constrained within the same growing cycle and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield.

Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting grain yield (GY) in drought-stressed (DS) and late-sown heat-stressed (HS) environments of the International maize and wheat improvement center's elite yield trial nurseries. We observed that the average genomic prediction accuracies using fivefold cross-validations were 0.50 and 0.51 in the DS and HS environments, respectively. However, when a different nursery/year was used to predict another nursery/year, the average genomic prediction accuracies in the DS and HS environments decreased to 0.18 and 0.23, respectively. While genomic predictions clearly outperformed pedigree-based predictions across nurseries, they were similar to pedigree-based predictions within nurseries due to small family sizes. In populations with some full-sibs in the training population, the genomic and pedigree-based prediction accuracies were on average 0.27 and 0.35 higher than the accuracies in populations with only one progeny per cross, indicating the importance of genetic relatedness between the training and validation populations for good predictions. We also evaluated the item-based collaborative filtering approach for multivariate prediction of GY using the green normalized difference vegetation index from HTP. This approach proved to be the best strategy for across-nursery predictions, with average accuracies of 0.56 and 0.62 in the DS and HS environments, respectively. We conclude that GY is a challenging trait for across-year predictions, but GS and HTP can be integrated in increasing the size of populations screened and evaluating unphenotyped large nurseries for stress-resilience within years.

Two Main Stripe Rust Resistance Genes Identified in Synthetic-Derived Wheat Line Soru#1

Stripe rust is a major disease constraint of wheat production worldwide. Resistance to stripe rust was analyzed using 131 F₆ recombinant inbred lines (RILs) derived from a cross between synthetic derived wheat line Soru#1 and wheat cultivar Naxos. The phenotype was evaluated in Mexico and Norway at both seedling and adult plant stages. Linkage groups were constructed based on 90K single-nucleotide polymorphism (SNP), sequence-tagged site, and simple sequence repeat markers. Two major resistance loci conferred by Soru#1 were detected and located on chromosomes 1BL and 4DS. The 1BL quantitative trait loci explained 15.8 to 40.2 and 51.1% of the phenotypic variation at adult plant and seedling stages, respectively. This locus was identified as Yr24/Yr26 based on the flanking markers and infection types. Locus 4DS was flanked by molecular markers D_GB5Y7FA02JMPQ0_238 and BS00108770_51. It explained 8.4 to 27.8 and 5.5% of stripe rust variation at the adult plant and seedling stages, respectively. The 4DS locus may correspond to known resistance gene Yr28 based on the resistance source. All RILs that combine Yr24/Yr26 and Yr28 showed significantly reduced stripe rust severity in all four environments compared with the lines with only one of the genes. SNP marker BS00108770_51 was converted into a breeder-friendly kompetitive allele-specific polymerase chain reaction marker that will be useful to accelerate Yr28 deployment in wheat breeding programs.

Genetics of Greenbug Resistance in Synthetic Hexaploid Wheat Derived Germplasm

The greenbug, Schizaphis graminum Rondani, significantly reduces wheat, Triticum aestivum L., grain yields if not controlled. Host plant resistance (HPR) can protect yield, is environmentally friendly and easy to use. Our objectives were to: (1) identify genomic regions associated with S. graminum resistance in a recombinant inbred line (RIL) population derived from a cross of "Sokoll" (resistant) and "Weebill1" (moderately susceptible), (2) evaluate Sokoll derived breeding germplasm for resistance, and (3) conduct allelism tests between Sokoll and sources carrying resistance genes Gba, Gbb, and Gbd. Resistance was measured quantitatively and qualitatively using a SPAD meter and visual assessments, respectively. We identified a large effect resistance gene on chromosome arm 7DL of Sokoll, herein referred as GbSkl, which contributed up to 24% of the phenotypic variation. Other minor QTL on chromosomes 2B, 3A, and 7B were also identified. The QTL on 2B and 3A originated from Weebill1. Of the Sokoll derived germplasm, 13% displayed resistance. Allelism tests indicated that GbSkl could be allelic or tightly linked to the temporarily designated genes Gba, Gbb, and Gbd. Utility of SPAD to determine quantitative variation in resistance phenotyping is demonstrated and breeding efforts are underway to transfer the resistance from Sokoll to new CIMMYT elite germplasm.

Identification and Validation of a Common Stem Rust Resistance Locus in Two Bi-parental Populations

Races belonging to Ug99 lineage of stem rust fungus Puccinia graminis f. sp. tritici (Pgt) continue to pose a threat to wheat (Triticum aestivum L.) production in various African countries. Growing resistant varieties is the most economical and environmentally friendly control measure. Recombinant inbred line (RIL) populations from the crosses of susceptible parent 'Cacuke' with the resistant parents 'Huhwa' and 'Yaye' were phenotyped for resistance at the seedling stage to Pgt race TTKSK (Ug99) and in adult plants in field trials at Njoro, Kenya for two seasons in 2016. Using the Affymetrix Axiom breeders SNP array, two stem rust resistance genes, temporarily designated as SrH and SrY, were identified and mapped on chromosome arm 2BL through selective genotyping and bulked segregant analysis (BSA), respectively. Kompetitive allele specific polymorphism (KASP) markers and simple sequence repeat (SSR) markers were used to saturate chromosome arm 2BL in both RIL populations. SrH mapped between markers cim109 and cim114 at a distance of 0.9 cM proximal, and cim117 at 2.9 cM distal. SrY was flanked by markers cim109 and cim116 at 0.8 cM proximal, and IWB45932 at 1.9 cM distal. Two Ug99-effective stem rust resistance genes derived from bread wheat, Sr9h and Sr28, have been reported on chromosome arm 2BL. Infection types and map position in Huhwa and Yaye indicated that Sr28 was absent in both the parents. However, susceptible reactions produced by resistant lines from both populations against Sr9h-virulent race TTKSF+ confirmed the presence of a common resistance locus Sr9h in both lines. Test of allelism is required to establish genetic relationships between genes identified in present study and Sr9h. Marker cim117 linked to SrH was genotyped on set of wheat lines with Huhwa in the pedigree and is advised to be used for marker assisted selection for this gene, however, a combination of phenotypic and genotypic assays is desirable for both genes especially for selection of Sr9h in breeding programs.

Prospects and Challenges of Applied Genomic Selection-A New Paradigm in Breeding for Grain Yield in Bread Wheat

Genomic selection (GS) has been promising for increasing genetic gains in several species. Therefore, we evaluated the potential integration of GS for grain yield (GY) in bread wheat ( L.) in CIMMYT's elite yield trial nurseries. We observed that the genomic prediction accuracies within nurseries (0.44 and 0.35) were substantially higher than across-nursery accuracies (0.15 and 0.05) for GY evaluated in the bed and flat planting systems, respectively. The accuracies from using only a subset of 251 genotyping-by-sequencing markers were comparable to the accuracies using all 2038 markers. We also used the item-based collaborative filtering approach for incorporating other related traits in predicting GY and observed that it outperformed genomic predictions across nurseries, but was less predictive when trait correlations with GY were low. Furthermore, we compared GS and phenotypic selections (PS) and observed that at a selection intensity of 0.5, GS could select a maximum of 70.9 and 61.5% of the top lines and discard 71.5 and 60.5% of the poor lines selected or discarded by PS within and across nurseries, respectively. Comparisons of GS and pedigree-based predictions revealed that the advantage of GS over the pedigree was moderate in populations without full-sibs. However, GS was less advantageous for within-family selections in elite families with few full-sibs and minimal Mendelian sampling variance. Overall, our results demonstrate the importance of applying GS for GY at the appropriate stage of the breeding cycle, and we speculate that gains can be maximized if it is implemented in early-generation within-family selections.

Genetic analysis of resistance to stripe rust in durum wheat (Triticum turgidum L. var. durum)

Stripe rust, caused by the fungal pathogen Puccinia striiformis Westend. f. sp. tritici Eriks, is an important disease of bread wheat (Triticum aestivum L.) worldwide and there is an indication that it may also become a serious disease of durum wheat (T. turgidum L. var. durum). Therefore, we investigated the genetic architecture underlying resistance to stripe rust in adapted durum wheat germplasm. Wheat infection assays were conducted under controlled conditions in Canada and under field conditions in Mexico. Disease assessments were performed on a population of 155 doubled haploid (DH) lines derived from the cross of Kofa (susceptible) and W9262-260D3 (moderately resistant) and on a breeding panel that consisted of 92 diverse cultivars and breeding lines. Both populations were genotyped using the 90K single-nucleotide polymorphism (SNP) iSelect assay. In the DH population, QTL for stripe rust resistance were identified on chromosome 7B (LOD 6.87-11.47) and chromosome 5B (LOD 3.88-9.17). The QTL for stripe rust resistance on chromosome 7B was supported in the breeding panel. Both QTL were anchored to the genome sequence of wild emmer wheat, which identified gene candidates involved in disease resistance. Exome capture sequencing identified variation in the candidate genes between Kofa and W9262-260D3. These genetic insights will be useful in durum breeding to enhance resistance to stripe rust.

Genetic Gains for Grain Yield in CIMMYT's Semi-Arid Wheat Yield Trials Grown in Suboptimal Environments

Wheat (Triticum aestivum L.) is a major staple food crop grown worldwide on >220 million ha. Climate change is regarded to have severe effect on wheat yields, and unpredictable drought stress is one of the most important factors. Breeding can significantly contribute to the mitigation of climate change effects on production by developing drought-tolerant wheat germplasm. The objective of our study was to determine the annual genetic gain for grain yield (GY) of the internationally distributed Semi-Arid Wheat Yield Trials, grown during 2002-2003 to 2013-2014 and developed by the Bread Wheat Breeding program at the CIMMYT. We analyzed data from 740 locations across 66 countries, which were classified in low-yielding (LYE) and medium-yielding (MYE) environments according to a cluster analysis. The rate of GY increase (GYC) was estimated relative to four drought-tolerant wheat lines used as constant checks. Our results estimate that the rate of GYC in LYE was 1.8% (38.13 kg ha-1 yr-1), whereas in MYE, it was 1.41% (57.71 kg ha-1 yr-1). The increase in GYC across environments was 1.6% (48.06 kg ha-1 yr-1). The pedigrees of the highest yielding lines through the coefficient of parentage analysis indicated the utilization of three primary sources-'Pastor', 'Baviacora 92', and synthetic hexaploid derivatives-to develop drought-tolerant, high and stably performing wheat lines. We conclude that CIMMYT's wheat breeding program continues to deliver adapted germplasm for suboptimal conditions of diverse wheat growing regions worldwide.

Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheat reveals potential candidate genes

KEY MESSAGE

Genome-wide association mapping in conjunction with population sequencing map and Ensembl plants was used to identify markers/candidate genes linked to leaf rust, stripe rust and tan spot resistance in wheat. Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT's (International Maize and Wheat Improvement Center) International bread wheat screening nurseries, we used genome-wide association studies (GWAS) in conjunction with information from the population sequencing map and Ensembl plants. Wheat entries were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. Using a mixed linear model, we observed that seedling resistance to LR was associated with 12 markers on chromosomes 1DS, 2AS, 2BL, 3B, 4AL, 6AS and 6AL, and seedling resistance to TS was associated with 14 markers on chromosomes 1AS, 2AL, 2BL, 3AS, 3AL, 3B, 6AS and 6AL. Seedling and adult plant resistance (APR) to YR were associated with several markers at the distal end of chromosome 2AS. In addition, YR APR was also associated with markers on chromosomes 2DL, 3B and 7DS. The potential candidate genes for these diseases included several resistance genes, receptor-like serine/threonine-protein kinases and defense-related enzymes. However, extensive LD in wheat that decays at about 5 × 107 bps, poses a huge challenge for delineating candidate gene intervals and candidates should be further mapped, functionally characterized and validated. We also explored a segment on chromosome 2AS associated with multiple disease resistance and identified seventeen disease resistance linked genes. We conclude that identifying candidate genes linked to significant markers in GWAS is feasible in wheat, thus creating opportunities for accelerating molecular breeding.

Genetic Analysis of Resistance to Wheat Rusts

Leaf rust, stripe rust, and stem rust pose a significant threat to global wheat production. Growing rust resistant cultivars is the most efficient and environment friendly method to reduce yield losses. Genetic analysis is undertaken to identify genes and study their roles in conferring rust resistance in a given wheat background. This chapter summarizes the protocol for genetic analysis of rust resistance at both seedling and adult plant stages. Additionally, it examines statistical analysis and related software to characterize quantitative trait loci (QTL) linked with rust resistance.

Potential for re-emergence of wheat stem rust in the United Kingdom

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production.

Characterization of Leaf Rust and Stripe Rust Resistance in Spring Wheat 'Chilero'

Since 1984, the 'Chilero' spring wheat line developed by CIMMYT has proven to be highly resistant to leaf rust and stripe rust. Amid efforts to understand the basis of resistance of this line, a recombinant inbred line (RIL) population derived from a cross between Avocet and Chilero was studied. The parents and RILs were characterized in field trials for leaf rust and stripe rust in three locations in Mexico between 2012 and 2015 and genotyped with DArT-array, DArT-GBS, and SSR markers. A total of 6,168 polymorphic markers were used to construct genetic linkage maps. Inclusive composite interval mapping detected four colocated resistance loci to both rust diseases and two stripe rust resistant loci in the Avocet × Chilero population. Among these, the quantitative trait locus (QTL) on chromosome 1BL was identified as a pleotropic adult plant resistance gene Lr46/Yr29, whereas QLr.cim-5DS/QYr.cim-5DS was a newly discovered colocated resistance locus to both rust diseases in Chilero. Additionally, one new stripe rust resistance locus on chromosome 7BL was mapped in the current population. Avocet also contributed two minor colocated resistance QTLs situated on chromosomes 1DL and 4BS. The flanking SNP markers can be converted to breeder friendly Kompetitive Allele Specific PCR (KASP) markers for wheat breeding programs.

Quantitative trait loci for resistance to stripe rust of wheat revealed using global field nurseries and opportunities for stacking resistance genes

Quantitative trait loci controlling stripe rust resistance were identified in adapted Canadian spring wheat cultivars providing opportunity for breeders to stack loci using marker-assisted breeding. Stripe rust or yellow rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss., is a devastating disease of common wheat (Triticum aestivum L.) in many regions of the world. The objectives of this research were to identify and map quantitative trait loci (QTL) associated with stripe rust resistance in adapted Canadian spring wheat cultivars that are effective globally, and investigate opportunities for stacking resistance. Doubled haploid (DH) populations from the crosses Vesper/Lillian, Vesper/Stettler, Carberry/Vesper, Stettler/Red Fife and Carberry/AC Cadillac were phenotyped for stripe rust severity and infection response in field nurseries in Canada (Lethbridge and Swift Current), New Zealand (Lincoln), Mexico (Toluca) and Kenya (Njoro), and genotyped with SNP markers. Six QTL for stripe rust resistance in the population of Vesper/Lillian, five in Vesper/Stettler, seven in Stettler/Red Fife, four in Carberry/Vesper and nine in Carberry/AC Cadillac were identified. Lillian contributed stripe rust resistance QTL on chromosomes 4B, 5A, 6B and 7D, AC Cadillac on 2A, 2B, 3B and 5B, Carberry on 1A, 1B, 4A, 4B, 7A and 7D, Stettler on 1A, 2A, 3D, 4A, 5B and 6A, Red Fife on 2D, 3B and 4B, and Vesper on 1B, 2B and 7A. QTL on 1A, 1B, 2A, 2B, 3B, 4A, 4B, 5B, 7A and 7D were observed in multiple parents. The populations are compelling sources of recombination of many stripe rust resistance QTL for stacking disease resistance. Gene pyramiding should be possible with little chance of linkage drag of detrimental genes as the source parents were mostly adapted cultivars widely grown in Canada.

Characterization and Mapping of Leaf Rust and Stripe Rust Resistance Loci in Hexaploid Wheat Lines UC1110 and PI610750 under Mexican Environments

Growing resistant wheat varieties is a key method of minimizing the extent of yield losses caused by the globally important wheat leaf rust (LR) and stripe rust (YR) diseases. In this study, a population of 186 F8 recombinant inbred lines (RILs) derived from a cross between a synthetic wheat derivative (PI610750) and an adapted common wheat line (cv. "UC1110") were phenotyped for LR and YR response at both seedling and adult plant stages over multiple seasons. Using a genetic linkage map consisting of single sequence repeats and diversity arrays technology markers, in combination with inclusive composite interval mapping analysis, we detected a new LR adult plant resistance (APR) locus, QLr.cim-2DS, contributed by UC1110. One co-located resistance locus to both rusts, QLr.cim-3DC/QYr.cim-3DC, and the known seedling resistance gene Lr26 were also mapped. QLr.cim-2DS and QLr.cim-3DC showed a marginally significant interaction for LR resistance in the adult plant stage. In addition, two previously reported YR APR loci, QYr.ucw-3BS and Yr48, were found to exhibit stable performances in rust environments in both Mexico and the United States and showed a highly significant interaction in the field. Yr48 was also observed to confer intermediate seedling resistance against Mexican YR races, thus suggesting it should be re-classified as an all-stage resistance gene. We also identified 5 and 2 RILs that possessed all detected YR and LR resistance loci, respectively. With the closely linked molecular markers reported here, these RILs could be used as donors for multiple resistance loci to both rusts in wheat breeding programs.

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat

KEY MESSAGE

Genomic prediction for seedling and adult plant resistance to wheat rusts was compared to prediction using few markers as fixed effects in a least-squares approach and pedigree-based prediction. The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies for effective evaluation and exploitation of quantitative rust resistance. One promising approach that could accelerate gain from selection for rust resistance is 'genomic selection' which utilizes dense genome-wide markers to estimate the breeding values (BVs) for quantitative traits. Our objective was to compare three genomic prediction models including genomic best linear unbiased prediction (GBLUP), GBLUP A that was GBLUP with selected loci as fixed effects and reproducing kernel Hilbert spaces-markers (RKHS-M) with least-squares (LS) approach, RKHS-pedigree (RKHS-P), and RKHS markers and pedigree (RKHS-MP) to determine the BVs for seedling and/or adult plant resistance (APR) to leaf rust (LR), stem rust (SR), and stripe rust (YR). The 333 lines in the 45th IBWSN and the 313 lines in the 46th IBWSN were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. The mean prediction accuracies ranged from 0.31-0.74 for LR seedling, 0.12-0.56 for LR APR, 0.31-0.65 for SR APR, 0.70-0.78 for YR seedling, and 0.34-0.71 for YR APR. For most datasets, the RKHS-MP model gave the highest accuracies, while LS gave the lowest. GBLUP, GBLUP A, RKHS-M, and RKHS-P models gave similar accuracies. Using genome-wide marker-based models resulted in an average of 42% increase in accuracy over LS. We conclude that GS is a promising approach for improvement of quantitative rust resistance and can be implemented in the breeding pipeline.

Identification and Mapping of Adult Plant Resistance Loci to Leaf Rust and Stripe Rust in Common Wheat Cultivar Kundan

Leaf rust (LR) and stripe rust (YR) are important diseases of wheat worldwide. We used 148 recombinant inbred lines (RIL) from the cross of Avocet × Kundan for determining and mapping the genetic basis of adult plant resistance (APR) loci. The population was phenotyped LR and YR for three seasons in field trials conducted in Mexico and genotyped with the diversity arrays technology sequencing (DArT-Seq) and simple sequence repeat markers. The final genetic map was constructed using 2,937 polymorphic markers with an average distance of 1.29 centimorgans between markers. Inclusive composite interval mapping identified two co-located APR quantitative trait loci (QTL) for LR and YR, two LR QTL, and three YR QTL. The co-located resistance QTL on chromosome 1BL corresponded to the pleiotropic APR gene Lr46/Yr29. QLr.cim-2BL, QYr.cim-2AL, and QYr.cim-5AS could be identified as new resistance loci in this population. Lr46/Yr29 contributed 49.5 to 65.1 and 49.2 to 66.1% of LR and YR variations, respectively. The additive interaction between detected QTL showed that LR severities for RIL combining four QTL ranged between 5.3 and 25.8%, whereas the lowest YR severities were for RIL carrying QTL on chromosomes 1BL + 2AL + 6AL. The high-density DArT-Seq markers across chromosomes can be used in fine mapping of the targeted loci and development SNP markers.

Genetic Yield Gains In CIMMYT's International Elite Spring Wheat Yield Trials By Modeling The Genotype × Environment Interaction

We calculated the annual genetic gains for grain yield (GY) of wheat (Triticum aestivum L.) achieved over 8 yr of international Elite Spring Wheat Yield Trials (ESWYT), from 2006-2007 (27th ESWYT) to 2014-2015 (34th ESWYT). In total, 426 locations were classified within three main megaenvironments (MEs): ME1 (optimally irrigated environments), ME4 (drought-stressed environments), and ME5 (heat-stressed environments). By fitting a factor analytical structure for modeling the genotype × environment (G × E) interaction, we measured GY gains relative to the widely grown cultivar Attila (GYA) and to the local checks (GYLC). Genetic gains for GYA and GYLC across locations were 1.67 and 0.53% (90.1 and 28.7 kg ha^-1 yr^-1), respectively. In ME1, genetic gains were 1.63 and 0.72% (102.7 and 46.65 kg ha^-1 yr^-1) for GYA and GYLC, respectively. In ME4, genetic gains were 2.7 and 0.41% (88 and 15.45 kg ha^-1 yr^-1) for GYA and GYLC, respectively. In ME5, genetic gains were 0.31 and 1.0% (11.28 and 36.6 kg ha^-1 yr^-1) for GYA and GYLC, respectively. The high GYA in ME1 and ME4 can be partially attributed to yellow rust races that affect Attila. When G × E interactions were not modeled, genetic gains were lower. Analyses showed that CIMMYT's location at Ciudad Obregon, Mexico, is highly correlated with locations in other countries in ME1. Lines that were top performers in more than one ME and more than one country were identified. CIMMYT's breeding program continues to deliver improved and widely adapted germplasm for target environments.

Genetic analysis and mapping of adult plant resistance loci to leaf rust in durum wheat cultivar Bairds

New leaf rust adult plant resistance (APR) QTL QLr.cim - 6BL was mapped and confirmed the known pleotropic APR gene Lr46 effect on leaf rust in durum wheat line Bairds. CIMMYT-derived durum wheat line Bairds displays an adequate level of adult plant resistance (APR) to leaf rust in Mexican field environments. A recombinant inbred line (RIL) population developed from a cross of Bairds with susceptible parent Atred#1 was phenotyped for leaf rust response at Ciudad Obregon, Mexico, during 2013, 2014, 2015 and 2016 under artificially created epidemics of Puccinia triticina (Pt) race BBG/BP. The RIL population and its parents were genotyped with the 50 K diversity arrays technology (DArT) sequence system and simple sequence repeat (SSR) markers. A genetic map comprising 1150 markers was used to map the resistance loci. Four significant quantitative trait loci (QTLs) were detected on chromosomes 1BL, 2BC (centromere region), 5BL and 6BL. These QTLs, named Lr46, QLr.cim-2BC, QLr.cim-5BL and QLr.cim-6BL, respectively, explained 13.5-60.8%, 9.0-14.3%, 2.8-13.9%, and 11.6-29.4%, respectively, of leaf rust severity variation by the inclusive composite interval mapping method. All of these resistance loci were contributed by the resistant parent Bairds, except for QLr.cim-2BC, which came from susceptible parent Atred#1. Among these, the QTL on chromosome 1BL was the known pleiotropic APR gene Lr46, whereas QLr.cim-6BL, a consistently detected locus, should be a new leaf rust resistance locus in durum wheat. The mean leaf rust severity of RILs carrying all four QTLs ranged from 8.0 to 17.5%, whereas it ranged from 10.9 to 38.5% for three QTLs (Lr46 + 5BL + 6BL) derived from the resistant parent Bairds. Two RILs with four QTLs combinations can be used as sources of complex APR in durum wheat breeding.

Identification of Genomic Associations for Adult Plant Resistance in the Background of Popular South Asian Wheat Cultivar, PBW343

Rusts, a fungal disease as old as its host plant wheat, has caused havoc for over 8000 years. As the rust pathogens can evolve into new virulent races which quickly defeat the resistance that primarily rely on race specificity, adult plant resistance (APR) has often been found to be race non-specific and hence is considered 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, and 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.

Genome wide association mapping of stripe rust resistance in Afghan wheat landraces

Mining of new genetic resources is of paramount importance to combat the alarming spread of stripe rust disease and breakdown of major resistance genes in wheat. We conducted a genome wide association study on 352 un-utilized Afghan wheat landraces against stripe rust resistance in eight locations. High level of disease variation was observed among locations and a core-set of germplasm showed consistence performance. Linkage disequilibrium (LD) decayed rapidly (R²≈0.16 at 0cM) due to germplasm peerless diversity. The mixed linear model resulted in ten marker-trait associations (MTAs) across all environments representing five QTL. The extensively short LD blocks required us to repeat the analysis with less diverse subset of 220 landraces in which R² decayed below 0.2 at 0.3cM. The subset GWAS resulted in 36 MTAs clustered in nine QTL. The subset analysis validated three QTL previously detected in the full list analysis. Overall, the study revealed that stripe rust epidemics in the geographical origin of this germplasm through time have permitted for selecting novel resistance loci.

Disease Impact on Wheat Yield Potential and Prospects of Genetic Control

Wheat is grown worldwide in diverse geographical regions, environments, and production systems. Although many diseases and pests are known to reduce grain yield potential and quality, the three rusts and powdery mildew fungi have historically caused major crop losses and continue to remain economically important despite the widespread use of host resistance and fungicides. The evolution and fast spread of virulent and more aggressive race lineages of rust fungi have only worsened the situation. Fusarium head blight, leaf spotting diseases, and, more recently, wheat blast (in South America and Bangladesh) have become diseases of major importance in recent years largely because of intensive production systems, the expansion of conservation agriculture, undesirable crop rotations, or increased dependency on fungicides. High genetic diversity for race-specific and quantitative resistance is known for most diseases; their selection through phenotyping reinforced with molecular strategies offers great promise in achieving more durable resistance and enhancing global wheat productivity.

Grain yield, adaptation and progress in breeding for early-maturing and heat-tolerant wheat lines in South Asia

Maintaining wheat productivity under the increasing temperatures in South Asia is a challenge. We focused on developing early maturing wheat lines as an adaptive mechanism in regions suffering from terminal heat stress and those areas that require wheat adapted to shorter cycles under continual high temperature stress. We evaluated the grain yield performance of early-maturing heat-tolerant germplasm developed by CIMMYT, Mexico at diverse locations in South Asia from 2009 to 2014 and estimated the breeding progress for high-yielding and early-maturing heat-tolerant germplasm in South Asia. Each year the trial comprised of 28 new entries, one CIMMYT check (Baj) and a local check variety. Locations were classified by mega environment (ME); ME1 being the temperate irrigated locations with terminal high temperature stress, and ME5 as hot, sub-tropical, irrigated locations. Grain yield (GY), days to heading (DTH) and plant height (PH) were recorded at each location. Effect of temperature on GY was observed in both ME1 and ME5. Across years, mean minimum temperatures in ME1 and mean maximum temperatures in ME5 during grain filling had significant negative association with GY. The ME1 locations were cooler that those in ME5 in the 5 years of evaluations and had a 1-2 t/ha higher GY. A mean reduction of 20 days for DTH and 20 cm in PH was observed in ME5. Negative genetic correlations of -0.43 to -0.79 were observed between GY and DTH in South Asia during 2009-2014. Each year, we identified early-maturing germplasm with higher grain yield than the local checks. A positive trend was observed while estimating the breeding progress across five years for high-yielding early-maturing heat tolerant wheat compared to the local checks in South Asia. The results suggests the potential of the high-yielding early-maturing wheat lines developed at CIMMYT in improving wheat production and maintaining genetic gains in South Asia.

Genetic Analysis of Resistance to Leaf Rust and Yellow Rust in Spring Wheat Cultivar Kenya Kongoni

The Kenyan wheat (Triticum aestivum L.) 'Kenya Kongoni' exhibits high levels of adult plant resistance (APR) to leaf rust (LR) and yellow rust (YR). We determined the genomic regions associated with LR and YR resistance in a population of 148 recombinant inbred lines generated from a cross between 'Avocet-YrA' and Kenya Kongoni. Field experiments to characterize APR to LR and YR were conducted in four and two Mexican or Uruguayan environments, respectively. A linkage map was constructed with 438 diversity arrays technology and 16 simple-sequence repeat markers by JoinMap 4.1 software. Genetic analyses showed that resistance to both rusts was determined by four to five APR genes, including Lr46/Yr29 and Sr2/Lr27/Yr30. Quantitative trait loci (QTL) analysis indicated that pleiotropic APR loci QYLr.cim-1BL corresponding to Lr46/Yr29 and QYLr.cim-7BL that is a putative novel QTL accounted for 5 to 57% and 12 to 35% of the phenotypic variation for resistance to LR and YR, respectively. These loci, in combination with another three LR QTL and two YR QTL, respectively, conferred high levels of resistance to both LR and YR in wheat under Mexican and Uruguayan environments. Among other detected QTL, QLr.cim-1DS, QLr.cim-2BL, and QYLr.icm-7BL may be new loci for APR to both rusts in common wheat.

Genetic Gain from Phenotypic and Genomic Selection for Quantitative Resistance to Stem Rust of Wheat

Stem rust of wheat (Triticum aestivum L.) caused by Puccinia graminis f. sp. tritici Eriks. and E. Henn. is a globally important disease that can cause severe yield loss. Breeding for quantitative stem rust resistance (QSRR) is important for developing cultivars with durable resistance. Genomic selection (GS) could increase rates of genetic gain for quantitative traits, but few experiments comparing GS and phenotypic selection (PS) have been conducted. Our objectives were to (i) compare realized gain from GS based on markers only with that of PS for QSRR in spring wheat using equal selection intensities; (ii) determine if gains agree with theoretical expectations; and (iii) compare the impact of GS and PS on inbreeding, genetic variance, and correlated response for pseudo-black chaff (PBC), a correlated trait. Over 2 yr, two cycles of GS were performed in parallel with one cycle of PS, with each method replicated twice. For GS, markers were generated using genotyping-by-sequencing, the prediction model was initially trained using historical data, and the model was updated before the second GS cycle. Overall, GS and PS led to a 31 ± 11 and 42 ± 12% increase in QSRR and a 138 ± 22 and 180 ± 70% increase in PBC, respectively. Genetic gains were not significant but were in agreement with expectations. Per year, gains from GS and PS were equal, but GS led to significantly lower genetic variance. This shows that while GS and PS can lead to equal rates of short-term gains, GS can reduce genetic variance more rapidly. Further work to develop efficient GS implementation strategies in spring wheat is warranted.

Emergence and Spread of New Races of Wheat Stem Rust Fungus: Continued Threat to Food Security and Prospects of Genetic Control

Race Ug99 (TTKSK) of Puccinia graminis f. sp. tritici, detected in Uganda in 1998, has been recognized as a serious threat to food security because it possesses combined virulence to a large number of resistance genes found in current widely grown wheat (Triticum aestivum) varieties and germplasm, leading to its potential for rapid spread and evolution. Since its initial detection, variants of the Ug99 lineage of stem rust have been discovered in Eastern and Southern African countries, Yemen, Iran, and Egypt. To date, eight races belonging to the Ug99 lineage are known. Increased pathogen monitoring activities have led to the identification of other races in Africa and Asia with additional virulence to commercially important resistance genes. This has led to localized but severe stem rust epidemics becoming common once again in East Africa due to the breakdown of race-specific resistance gene SrTmp, which was deployed recently in the 'Digalu' and 'Robin' varieties in Ethiopia and Kenya, respectively. Enhanced research in the last decade under the umbrella of the Borlaug Global Rust Initiative has identified various race-specific resistance genes that can be utilized, preferably in combinations, to develop resistant varieties. Research and development of improved wheat germplasm with complex adult plant resistance (APR) based on multiple slow-rusting genes has also progressed. Once only the Sr2 gene was known to confer slow rusting APR; now, four more genes-Sr55, Sr56, Sr57, and Sr58-have been characterized and additional quantitative trait loci identified. Cloning of some rust resistance genes opens new perspectives on rust control in the future through the development of multiple resistance gene cassettes. However, at present, disease-surveillance-based chemical control, large-scale deployment of new varieties with multiple race-specific genes or adequate levels of APR, and reducing the cultivation of susceptible varieties in rust hot-spot areas remains the best stem rust management strategy.