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).

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

KEY MESSAGE: 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 F6:7 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.

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.

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.

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.

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.

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.

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.

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.

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

KEY MESSAGE: 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.

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.

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

KEY MESSAGE: 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.

A high density GBS map of bread wheat and its application for dissecting complex disease resistance traits.

BACKGROUND: Genotyping-by-sequencing (GBS) is a high-throughput genotyping approach that is starting to be used in several crop species, including bread wheat. Anchoring GBS tags on chromosomes is an important step towards utilizing them for wheat genetic improvement. Here we use genetic linkage mapping to construct a consensus map containing 28644 GBS markers. RESULTS: Three RIL populations, PBW343 × Kingbird, PBW343 × Kenya Swara and PBW343 × Muu, which share a common parent, were used to minimize the impact of potential structural genomic variation on consensus-map quality. The consensus map comprised 3757 unique positions, and the average marker distance was 0.88 cM, obtained by calculating the average distance between two adjacent unique positions. Significant variation of segregation distortion was observed across the three populations. The consensus map was validated by comparing positions of known rust resistance genes, and comparing them to wheat reference genome sequences recently published by the International Wheat Genome Sequencing Consortium, Rye and Ae. tauschii genomes. Three well-characterized rust resistance genes (Sr58/Lr46/Yr29, Sr2/Yr30/Lr27, and Sr57/Lr34/Yr18) and 15 published QTLs for wheat rusts were validated with high resolution. Fifty-two per cent of GBS tags on the consensus map were successfully aligned through BLAST to the right chromosomes on the wheat reference genome sequence. CONCLUSION: The consensus map should provide a useful basis for analyzing genome-wide variation of complex traits. The identified genes can then be explored as genetic markers to be used in genomic applications in wheat breeding.

Identification and characterization of pleiotropic and co-located resistance loci to leaf rust and stripe rust in bread wheat cultivar Sujata.

KEY MESSAGE: Two new co-located resistance loci, QLr.cim - 1AS/QYr.cim - 1AS and QLr.cim - 7BL/YrSuj , in combination with Lr46 / Yr29 and Lr67/Yr46 , and a new leaf rust resistance quantitative trait loci, conferred high resistance to rusts in adult plant stage. The tall Indian bread wheat cultivar Sujata displays high and low infection types to leaf rust and stripe rust, respectively, at the seedling stage in greenhouse tests. It was also highly resistant to both rusts at adult plant stage in field trials in Mexico. The genetic basis of this resistance was investigated in a population of 148 F5 recombinant inbred lines (RILs) derived from the cross Avocet × Sujata. The parents and RIL population were characterized in field trials for resistance to leaf rust during 2011 at El Batán, and 2012 and 2013 at Ciudad Obregón, Mexico, and for stripe rust during 2011 and 2012 at Toluca, Mexico; they were also characterized three times for stripe rust at seedling stage in the greenhouse. The RILs were genotyped with diversity arrays technology and simple sequence repeat markers. The final genetic map was constructed with 673 polymorphic markers. Inclusive composite interval mapping analysis detected two new significant co-located resistance loci, QLr.cim-1AS/QYr.cim-1AS and QLr.cim-7BL/YrSuj, on chromosomes 1AS and 7BL, respectively. The chromosomal position of QLr.cim-7BL overlapped with the seedling stripe rust resistance gene, temporarily designated as YrSuj. Two previously reported pleiotropic adult plant resistance genes, Lr46/Yr29 and Lr67/Yr46, and a new leaf rust resistance quantitative trait loci derived from Avocet were also mapped in the population. The two new co-located resistance loci are expected to contribute to breeding durable rust resistance in wheat. Closely linked molecular markers can be used to transfer all four resistance loci simultaneously to modern wheat varieties.

Multi-environment multi-QTL association mapping identifies disease resistance QTL in barley germplasm from Latin America.

KEY MESSAGE: Multi-environment multi-QTL mixed models were used in a GWAS context to identify QTL for disease resistance. The use of mega-environments aided the interpretation of environment-specific and general QTL. Diseases represent a major constraint for barley (Hordeum vulgare L.) production in Latin America. Spot blotch (caused by Cochliobolus sativus), stripe rust (caused by Puccinia striiformis f.sp. hordei) and leaf rust (caused by Puccinia hordei) are three of the most important diseases that affect the crop in the region. Since fungicide application is not an economically or environmentally sound solution, the development of durably resistant varieties is a priority for breeding programs. Therefore, new resistance sources are needed. The objective of this work was to detect genomic regions associated with field level plant resistance to spot blotch, stripe rust, and leaf rust in Latin American germplasm. Disease severities measured in multi-environment trials across the Americas and 1,096 SNPs in a population of 360 genotypes were used to identify genomic regions associated with disease resistance. Optimized experimental design and spatial modeling were used in each trial to estimate genotypic means. Genome-Wide Association Mapping (GWAS) in each environment was used to detect Quantitative Trait Loci (QTL). All significant environment-specific QTL were subsequently included in a multi-environment-multi-QTL (MEMQ) model. Geographical origin and inflorescence type were the main determinants of population structure. Spot blotch severity was low to intermediate while leaf and stripe rust severity was high in all environments. Mega-environments were defined by locations for spot blotch and leaf rust. Significant marker-trait associations for spot blotch (9 QTL), leaf (6 QTL) and stripe rust (7 QTL) and both global and environment-specific QTL were detected that will be useful for future breeding efforts.

Molecular Mapping and Validation of SrND643: A New Wheat Gene for Resistance to the Stem Rust Pathogen Ug99 Race Group.

This study reports the identification of a new gene conferring resistance to the Ug99 lineage of races of Puccinia graminis f. sp. tritici in wheat (Triticum aestivum L.). Because the virulent races of stem rust pathogen continue to pose a serious threat in global wheat production, identification and molecular characterization of new resistance genes remains of utmost important to enhance resistance diversity and durability in wheat germplasm. Advanced wheat breeding line 'ND643/2*Weebill1' carries a stem rust resistance gene, temporarily designated as SrND643, effective against the Ug99 group of P. graminis f. sp. tritici races at both seedling and adult growth stages. This study was conducted to map the chromosomal location of SrND643 and identify closely linked molecular markers to allow its selection in breeding populations. In total, 123 recombinant inbred lines, developed by crossing ND643/2*Weebill1 with susceptible line 'Cacuke', were evaluated for stem rust response in field nurseries at Njoro, Kenya, during two growing seasons in 2010, and were genotyped with DNA markers, including Diversity Arrays Technology, simple sequence repeats (SSR), and single-nucleotide polymorphisms. Linkage mapping tagged SrND643 at the distal end of chromosome 4AL, showing close association with SSR markers Xgwm350 (0.5 centimorgans [cM]), Xwmc219 (4.1 cM), and Xwmc776 (2.9 cM). The race specificity of SrND643 is different from that of Sr7a and Sr7b, indicating that the resistance is conferred by a gene at a new locus or by a new allele of Sr7. The flanking markers Xgwm350 and Xwmc219 were predictive of the presence of SrND643 in advanced germplasm, thus validating the map location and their use in marker-assisted selection.

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.