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Wheat stem rust disease caused by Puccinia graminis f. sp. tritici (Pgt) is a global threat to wheat production. Fast evolving populations of Pgt limit the efficacy of plant genetic resistance and constrain disease management strategies. Understanding molecular mechanisms that lead to rust infection and disease susceptibility could deliver novel strategies to deploy crop resistance through genetic loss of disease susceptibility. We used comparative transcriptome-based and orthology-guided approaches to characterize gene expression changes associated with Pgt infection in susceptible and resistant Triticum aestivum genotypes as well as the non-host Brachypodium distachyon. We targeted our analysis to genes with differential expression in T. aestivum and genes suppressed or not affected in B. distachyon and report several processes potentially linked to susceptibility to Pgt, such as cell death suppression and impairment of photosynthesis. We complemented our approach with a gene co-expression network analysis to identify wheat targets to deliver resistance to Pgt through removal or modification of putative susceptibility genes.

Rusts of the genus Puccinia are wheat pathogens. Stem (black; Sr), leaf (brown; Lr), and stripe (yellow; Yr) rust, caused by Puccinia graminis f. sp. tritici (Pgt), Puccinia triticina (Pt), and Puccinia striiformis f. sp. tritici (Pst), can occur singularly or in mixed infections and pose a threat to wheat production globally in terms of the wide dispersal of their urediniospores. The development of durable resistant cultivars is the most sustainable method for controlling them. Many resistance genes have been identified, characterized, genetically mapped, and cloned; several quantitative trait loci (QTLs) for resistance have also been described. However, few studies have considered resistance to all three rust pathogens in a given germplasm. A genome-wide association study (GWAS) was carried out to identify loci associated with resistance to the three rusts in a collection of 230 inbred lines of tetraploid wheat (128 of which were Triticum turgidum ssp. durum) genotyped with SNPs. The wheat panel was phenotyped in the field and subjected to growth chamber experiments across different countries (USA, Mexico, Morocco, Italy, and Spain); then, a mixed linear model (MLM) GWAS was performed. In total, 9, 34, and 5 QTLs were identified in the A and B genomes for resistance to Pgt, Pt, and Pst, respectively, at both the seedling and adult plant stages. Only one QTL on chromosome 4A was found to be effective against all three rusts at the seedling stage. Six QTLs conferring resistance to two rust species at the adult plant stage were mapped: three on chromosome 1B and one each on 5B, 7A, and 7B. Fifteen QTLs conferring seedling resistance to two rusts were mapped: five on chromosome 2B, three on 7B, two each on 5B and 6A, and one each on 1B, 2A, and 7A. Most of the QTLs identified were specific for a single rust species or race of a species. Candidate genes were identified within the confidence intervals of a QTL conferring resistance against at least two rust species by using the annotations of the durum (cv. ‘Svevo’) and wild emmer wheat (‘Zavitan’) reference genomes. The 22 identified loci conferring resistance to two or three rust species may be useful for breeding new and potentially durable resistant wheat cultivars [ABSTRACT FROM AUTHOR]

Control of stem rust, caused by Puccinia graminis f.sp. tritici, a highly destructive fungal disease of wheat, faces continuous challenges from emergence of new virulent races across wheat-growing continents. Using combinations of broad-spectrum resistance genes could impart durable stem rust resistance. This study attempted transfer of Sr59 resistance gene from line TA5094 (developed through CSph1bM-induced T2DS·2RL Robertsonian translocation conferring broad-spectrum resistance). Poor agronomic performance of line TA5094 necessitates Sr59 transfer to adapted genetic backgrounds and utility evaluations for wheat improvement. Based on combined stem rust seedling and molecular analyses, 2070 BC1F1 and 1230 BC2F1 plants were derived from backcrossing BAJ#1, KACHU#1, and REEDLING#1 with TA5094. Genotyping-by-sequencing (GBS) results revealed the physical positions of 15,116 SNPs on chromosome 2R. The adapted genotypes used for backcrossing were found not to possess broad-spectrum resistance to selected stem rust races, whereas Sr59-containing line TA5094 showed resistance to all races tested. Stem rust seedling assays combined with kompetitive allele-specific PCR (KASP) marker analysis successfully selected and generated the BC2F2 population, which contained the Sr59 gene, as confirmed by GBS. Early-generation data from backcrossing suggested deviations from the 3:1 segregation, suggesting that multiple genes may contribute to Sr59 resistance reactions. Using GBS marker data (40,584 SNPs in wheat chromosomes) to transfer the recurrent parent background to later-generation populations resulted in average genome recovery of 71.2% in BAJ#1*2/TA5094, 69.8% in KACHU#1*2/TA5094, and 70.5% in REEDLING#1*2/TA5094 populations. GBS data verified stable Sr59 introgression in BC2F2 populations, as evidenced by presence of the Ph1 locus and absence of the 50,936,209 bp deletion in CSph1bM. Combining phenotypic selections, stem rust seedling assays, KASP markers, and GBS data substantially accelerated transfer of broad-spectrum resistance into adapted genotypes. Thus, this study demonstrated that the Sr59 resistance gene can be introduced into elite genetic backgrounds to mitigate stem rust-related yield losses. [ABSTRACT FROM AUTHOR]

The rust diseases, including leaf rust caused by Puccinia triticina (Pt), stem rust caused by P. graminis f. sp. tritici (Pgt), and stripe rust caused by P. striiformis f. sp. tritici (Pst), are major limiting factors in wheat production worldwide. Identification of novel sources of rust resistance genes is key to developing cultivars resistant to rapidly evolving pathogen populations. Aegilops longissima is a diploid wild grass native to the Levant and closely related to the modern bread wheat D subgenome. To explore resistance genes in the species, we evaluated a large panel of Ae. longissima for resistance to several races of Pt, Pgt, and Pst, and conducted a genome-wide association study (GWAS) to map rust resistance loci in the species. A panel of 404 Ae. longissima accessions, mostly collected from Israel, were screened for seedling-stage resistance to four races of Pt, four races of Pgt, and three races of Pst. Out of the 404 accessions screened, two were found that were resistant to all 11 races of the three rust pathogens screened. The percentage of all accessions screened that were resistant to a given rust pathogen race ranged from 18.5% to 99.7%. Genotyping-by-sequencing (GBS) was performed on 381 accessions of the Ae. longissima panel, wherein 125,343 single nucleotide polymorphisms (SNPs) were obtained after alignment to the Ae. longissima reference genome assembly and quality control filtering. Genetic diversity analysis revealed the presence of two distinct subpopulations, which followed a geographic pattern of a northern and a southern subpopulation. Association mapping was performed in the genotyped portion of the collection (n = 381) and in each subpopulation (n = 204 and 174) independently via a single-locus mixed-linear model, and two multi-locus models, FarmCPU, and BLINK. A large number (195) of markers were significantly associated with resistance to at least one of 10 rust pathogen races evaluated, nine of which are key candidate markers for further investigation due to their detection via multiple models and/or their association with resistance to more than one pathogen race. The novel resistance loci identified will provide additional diversity available for use in wheat breeding. [ABSTRACT FROM AUTHOR]

Genetic manipulation of whole‐plant transpiration rate (TR) response to increasing atmospheric vapor pressure deficit (VPD) is a promising approach for crop adaptation to various drought regimes under current and future climates. Genotypes with a non‐linear TR response to VPD are expected to achieve yield gains under terminal drought, thanks to a water conservation strategy, while those with a linear response exhibit a consumptive strategy that is more adequate for well‐watered or transient‐drought environments. In wheat, previous efforts indicated that TR has a genetic basis under naturally fluctuating conditions, but because TR is responsive to variation in temperature, photosynthetically active radiation, and evaporative demand, the genetic basis of its response VPD per se has never been isolated. To address this, we developed a controlled‐environment gravimetric phenotyping approach where we imposed VPD regimes independent from other confounding environmental variables. We screened three nested association mapping populations totaling 150 lines, three times over a 3‐year period. The resulting dataset, based on phenotyping nearly 1400 plants, enabled constructing 63‐point response curves for each genotype, which were subjected to a genome‐wide association study. The analysis revealed a hotspot for TR response to VPD on chromosome 5A, with SNPs explaining up to 17% of the phenotypic variance. The key SNPs were found in haploblocks that are enriched in membrane‐associated genes, consistent with the hypothesized physiological determinants of the trait. These results indicate a promising potential for identifying new alleles and designing next‐gen wheat cultivars that are better adapted to current and future drought regimes. [ABSTRACT FROM AUTHOR]

Wheat stem rust disease caused by Puccinia graminis f. sp. tritici (Pgt) is a global threat to wheat production. Fast evolving populations of Pgt limit the efficacy of plant genetic resistance and constrain disease management strategies. Understanding molecular mechanisms that lead to rust infection and disease susceptibility could deliver novel strategies to deploy crop resistance through genetic loss of disease susceptibility. We used comparative transcriptome-based and orthology-guided approaches to characterize gene expression changes associated with Pgt infection in susceptible and resistant Triticum aestivum genotypes as well as the non-host Brachypodium distachyon. We targeted our analysis to genes with differential expression in T. aestivum and genes suppressed or not affected in B. distachyon and report several processes potentially linked to susceptibility to Pgt , such as cell death suppression and impairment of photosynthesis. We complemented our approach with a gene co-expression network analysis to identify wheat targets to deliver resistance to Pgt through removal or modification of putative susceptibility genes. [ABSTRACT FROM AUTHOR]

Improving grain protein content and flour quality is an important goal for wheat (Triticum aestivum L.) breeding programs. Identification of genomic regions and markers associated with quality traits can help enrich wheat breeding germplasm with favorable alleles. This study was carried out to identify genetic loci controlling bread‐making quality traits in a nested association mapping population of 230 lines. Lines were evaluated for grain protein content and three gluten aggregation traits from the Brabender GlutoPeak instrument: peak maximum time (PMT), maximum torque (MT), and aggregation energy (AE). The strongest positive correlation was observed between AE and MT (r =.87), whereas the strongest negative correlation was between PMT and MT (r = −.46). We identified 25 quantitative trait loci (QTL) associated with these traits on 14 chromosomes, of which three QTL were common between MT and AE. Quantitative trait loci explaining the largest variations were observed for grain protein content and AE, with QTL that explained 13% of the observed variation for each trait. Nearly 62% of the discovered QTL were of medium effect, as the median percentage of observed phenotypic variation explained by the detected QTL was 7% (range of 4–13%). Based on QTL analysis and marker screening results, the populations discussed in this study are segregating for the known alleles of the high‐molecular‐weight glutenin gene Glu‐D1. As some lines have better phenotypic performance relative to the elite common parent RB07, crossing these lines with elite breeding lines can help increase the frequency of alleles contributing to improve flour quality traits. [ABSTRACT FROM AUTHOR]

In the last 20 years, stem rust caused by the fungus Puccinia graminis f. sp. tritici (Pgt), has re‐emerged as a major threat to wheat and barley production in Africa and Europe. In contrast to wheat with 60 designated stem rust (Sr) resistance genes, barley's genetic variation for stem rust resistance is very narrow with only ten resistance genes genetically identified. Of these, only one complex locus consisting of three genes is effective against TTKSK, a widely virulent Pgt race of the Ug99 tribe which emerged in Uganda in 1999 and has since spread to much of East Africa and parts of the Middle East. The objective of this study was to assess the functionality, in barley, of cloned wheat Sr genes effective against race TTKSK. Sr22, Sr33, Sr35 and Sr45 were transformed into barley cv. Golden Promise using Agrobacterium‐mediated transformation. All four genes were found to confer effective stem rust resistance. The barley transgenics remained susceptible to the barley leaf rust pathogen Puccinia hordei, indicating that the resistance conferred by these wheat Sr genes was specific for Pgt. Furthermore, these transgenic plants did not display significant adverse agronomic effects in the absence of disease. Cloned Sr genes from wheat are therefore a potential source of resistance against wheat stem rust in barley. [ABSTRACT FROM AUTHOR]

Wheat stem rust caused by the fungus Puccinia graminis f. sp. tritici (Pgt), is regaining prominence due to the recent emergence of virulent isolates and epidemics in Africa, Europe and Central Asia. The development and deployment of wheat cultivars with multiple stem rust resistance (Sr) genes stacked together will provide durable resistance. However, certain disease resistance genes can suppress each other or fail in particular genetic backgrounds. Therefore, the function of each Sr gene must be confirmed after incorporation into an Sr -gene stack. This is difficult when using pathogen disease assays due to epistasis from recognition of multiple avirulence (Avr) effectors. Heterologous delivery of single Avr effectors can circumvent this limitation, but this strategy is currently limited by the paucity of cloned Pgt Avrs. To accelerate Avr gene cloning, we outline a procedure to develop a mutant population of Pgt spores and select for gain-of-virulence mutants. We used ethyl methanesulphonate (EMS) to mutagenize urediniospores and create a library of > 10,000 independent mutant isolates that were combined into 16 bulks of ~658 pustules each. We sequenced random mutants and determined the average mutation density to be 1 single nucleotide variant (SNV) per 258 kb. From this, we calculated that a minimum of three independently derived gain-of-virulence mutants is required to identify a given Avr gene. We inoculated the mutant library onto plants containing Sr43 , Sr44 , or Sr45 and obtained 9, 4, and 14 mutants with virulence toward Sr43 , Sr44 , or Sr45 , respectively. However, only mutants identified on Sr43 and Sr45 maintained their virulence when reinolculated onto the lines from which they were identified. We further characterized 8 mutants with virulence toward Sr43. These also maintained their virulence profile on the stem rust international differential set containing 20 Sr genes, indicating that they were most likely not accidental contaminants. In conclusion, our method allows selecting for virulent mutants toward targeted resistance (R) genes. The development of a mutant library from as little as 320 mg spores creates a resource that enables screening against several R genes without the need for multiple rounds of spore multiplication and mutagenesis. [ABSTRACT FROM AUTHOR]

Sharon goatgrass (Aegilops sharonensis Eig) is a useful source of genes for wheat (Triticum aestivum L.) improvement, but little is known about its genetic diversity in Israel. We analyzed genetic diversity and population structure of 106Ae. sharonensis accessions. Twenty-one microsatellites revealed a high level of diversity that was comparable to Triticeae species with larger geographic distribution. The genetic structure of Ae. sharonensis is characterized by high diversity within location and by a short distance (15 km) similarity between populations. Accessions from the Sharon Plain exhibited the highest level of diversity. Because the Sharon Plain is located in the center of geographic distribution of the species and includes the three most genetically diverse sites, it may be the center of diversity of Ae. sharonensis. A wide range of variation was observed in the 11 morphological traits evaluated, and the regional effect on the phenotypic variability was higher than the one observed for genetic diversity. Considerable variability was found in response to leaf rust and stem rust among regions, as a very low frequency of resistance was found for both diseases in the northern regions of Israel. The diversity pattern found in populations of Ae. sharonensis indicate that, to optimize the capture of the greatest diversity, collection and utilization programs should include multiple individuals from as many sites as possible. [ABSTRACT FROM AUTHOR]

In many regions of the world, wheat is vulnerable to severe yield and quality losses from the fungus disease of Fusarium head blight (FHB). The development of resistant cultivars is one means of ameliorating the devastating effects of this disease, but the breeding process requires the evaluation of hundreds of lines each year for reaction to the disease. These field evaluations are laborious, expensive, time-consuming, and are prone to rater error. A phenotyping cart that can quickly capture images of the spikes of wheat lines and their level of FHB infection would greatly benefit wheat breeding programs. In this study, mask region convolutional neural network (Mask-RCNN) allowed for reliable identification of the symptom location and the disease severity of wheat spikes. Within a wheat line planted in the field, color images of individual wheat spikes and their corresponding diseased areas were labeled and segmented into sub-images. Images with annotated spikes and sub-images of individual spikes with labeled diseased areas were used as ground truth data to train Mask-RCNN models for automatic image segmentation of wheat spikes and FHB diseased areas, respectively. The feature pyramid network (FPN) based on ResNet-101 network was used as the backbone of Mask-RCNN for constructing the feature pyramid and extracting features. After generating mask images of wheat spikes from full-size images, Mask-RCNN was performed to predict diseased areas on each individual spike. This protocol enabled the rapid recognition of wheat spikes and diseased areas with the detection rates of 77.76% and 98.81%, respectively. The prediction accuracy of 77.19% was achieved by calculating the ratio of the wheat FHB severity value of prediction over ground truth. This study demonstrates the feasibility of rapidly determining levels of FHB in wheat spikes, which will greatly facilitate the breeding of resistant cultivars. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a devastating disease of wheat worldwide. In addition to reducing the yield of the crop, the causal pathogens also produce mycotoxins that can contaminate the grain. The development of resistant wheat varieties is one of the best ways to reduce the impact of FHB. To develop such varieties, breeders must expose germplasm lines to the pathogen in the field and assess the disease reaction. Phenotyping breeding materials for resistance to FHB is time-consuming, labor-intensive, and expensive when using conventional protocols. To develop a reliable and cost-effective high throughput phenotyping system for assessing FHB in the field, we focused on developing a method for processing color images of wheat spikes to accurately detect diseased areas using deep learning and image processing techniques. Color images of wheat spikes at the milk stage were collected in a shadow condition and processed to construct datasets, which were used to retrain a deep convolutional neural network model using transfer learning. Testing results showed that the model detected spikes very accurately in the images since the coefficient of determination for the number of spikes tallied by manual count and the model was 0.80. The model was assessed, and the mean average precision for the testing dataset was 0.9201. On the basis of the results for spike detection, a new color feature was applied to obtain the gray image of each spike and a modified region-growing algorithm was implemented to segment and detect the diseased areas of each spike. Results showed that the region growing algorithm performed better than the K-means and Otsu's method in segmenting diseased areas. We demonstrated that deep learning techniques enable accurate detection of FHB in wheat based on color image analysis, and the proposed method can effectively detect spikes and diseased areas, which improves the efficiency of the FHB assessment in the field. [ABSTRACT FROM AUTHOR]

Stem rust [causal organism: Puccinia graminis f. sp. tritici (Pgt)], stripe rust [Puccinia striiformis f. sp. tritici (Pst)], and leaf rust [Puccinia triticina (Pt)] are important fungal diseases of wheat in Central Asia and worldwide. Therefore, identification of seedling and adult plant resistance (APR) genes is of major importance for the national wheat breeding program in many countries. The objectives of this study were to identify genes that confer seedling and APR resistances in widely grown wheat cultivars, landraces and advanced lines from Tajikistan. A total of 41 wheat accessions were inoculated with eleven races of Pgt, twelve races of Pst and nine races of Pt for postulation of Sr (stem rust), Yr (yellow or stripe rust), and Lr Lr (leaf rust) resistance genes at the seedling stage. In addition, all of the accessions were tested in field trials for the response to stem rust and stripe rust. Genes for seedling stem rust resistance (i.e. Sr5, Sr6, Sr11, Sr31, and Sr38), stripe rust resistance (Yr9, Yr17, and Y27), and leaf rust resistance (Lr16 and Lr26) were postulated in the Tajik wheat. The presence of the pleiotropic APR genes Sr2/Yr30/Lr27 (associated with pseudo-black chaff phenotype) and Lr34/Yr18/Sr57 (associated with leaf tip necrosis phenotype), and also Lr37 were assessed in the field and confirmed with linked molecular markers. In most of the wheat accessions, resistance genes could not be postulated because their infection types did not match the avirulence or virulence profile of the Pgt, Pst and Pt races tested. Six, seven, and nine accessions were identified that likely possess new genes for resistance to stem rust, stripe rust, and leaf rust, respectively, which have not been described previously. The research demonstrates the presence of effective seedling resistance and APR genes in widely grown wheat accessions that could facilitate further rust resistance breeding in the national wheat breeding program in Tajikistan. [ABSTRACT FROM AUTHOR]