Molecular genetics of leaf rust resistance in wheat and barley

Optimizing dsRNA sequences for RNAi in pest control and research with the dsRIP web platform

BACKGROUND

RNA interference (RNAi) is a tool for studying gene function and has emerged as a promising eco-friendly alternative to chemical pesticides. RNAi relies on delivering double-stranded RNA (dsRNA), which is processed into small interfering RNA (siRNA) to silence genes. However, so far, knowledge and tools for optimizing the dsRNA sequences for maximum efficacy are based on human data, which might not be optimal for insect pest control.

RESULTS

Here, we systematically tested different siRNA sequences in the red flour beetle Tribolium castaneum to identify sequence features that correlated with high efficacy using pest control as a study case. Thermodynamic asymmetry, the absence of secondary structures, and adenine at the 10th position in antisense siRNA were most predictive of insecticidal efficacy. Interestingly, we also found that, in contrast to results from human data, high, rather than low, GC content from the 9th to 14th nucleotides of antisense was associated with high efficacy. Consideration of these features for the design of insecticidal dsRNAs targeting essential genes in three insect species improved the efficacy of the treatment. The improvement was associated with a higher ratio of the antisense, rather than sense, siRNA strand bound to the RNA-induced silencing complex. Finally, we developed a web platform named dsRIP, which offers tools for optimizing dsRNA sequences, identifying effective target genes in pests, and minimizing risk to non-target species.

CONCLUSIONS

The identified sequence features and the dsRIP web platform allow optimizing dsRNA sequences for application of RNAi for pest control and research.

Abundant Genetic Diversity Harbored by Traditional Naked Barley Varieties on Tibetan Plateau: Implications in Their Effective Conservation and Utilization

Naked barley (Hordeum vulgare var. nudum) is a staple food crop, contributing significantly to global food security. Understanding genetic diversity will facilitate its effective conservation and utilization. To determine genetic diversity and its distribution within and among varieties, we characterized 30 naked barley varieties from Tibet, representing the traditional, modern, and germplasm-resources-bank gene pools, by analyzing SSR molecular fingerprints. The results demonstrate abundant genetic diversity in Tibetan naked barley varieties, particularly those in the traditional gene pool that holds much more private (unique) alleles. Principal coordinates and STRUCTURE analyses indicate substantial deviation of the modern varieties from the traditional and germplasm-resources-bank varieties. A considerable amount of seed mixture is detected in the modern varieties, suggesting the practices of using mixed seeds in modern-variety cultivation. Cluster analyses further indicate the narrow genetic background of the modern varieties, likely due to the limited number of traditional/germplasm-resources-bank varieties applied in breeding. Relationships between increases in genetic diversity and sample sizes within naked barley varieties highlight the importance of effective sampling strategies for field collections. The findings from this study have important implications for the sustainable utilization and effective conservation of different types of naked barley germplasm, both in Tibet and in other regions around the world.

A single NLR gene confers resistance to leaf and stripe rust in wheat

Nucleotide-binding leucine-rich repeat (NLR) disease resistance genes typically confer resistance against races of a single pathogen. Here, we report that Yr87/Lr85, an NLR gene from Aegilops sharonensis and Aegilops longissima, confers resistance against both P. striiformis tritici (Pst) and Puccinia triticina (Pt) that cause stripe and leaf rust, respectively. Yr87/Lr85 confers resistance against Pst and Pt in wheat introgression as well as transgenic lines. Comparative analysis of Yr87/Lr85 and the cloned Triticeae NLR disease resistance genes shows that Yr87/Lr85 contains two distinct LRR domains and that the gene is only found in Ae. sharonensis and Ae. longissima. Allele mining and phylogenetic analysis indicate multiple events of Yr87/Lr85 gene flow between the two species and presence/absence variation explaining the majority of resistance to wheat leaf rust in both species. The confinement of Yr87/Lr85 to Ae. sharonensis and Ae. longissima and the resistance in wheat against Pst and Pt highlight the potential of these species as valuable sources of disease resistance genes for wheat improvement.

Puccinia triticina avirulence protein AvrLr21 directly interacts with wheat resistance protein Lr21 to activate wheat immune response

Wheat leaf rust, caused by Puccinia triticina (Pt), remains a constant threat to wheat production worldwide. Deployment of race-specific leaf rust (Lr) resistance genes in wheat provides effective protection against leaf rust, but often leads to selective pressures that drive the rapid emergence of new virulent Pt isolates in nature. However, the molecular mechanisms underlying the evasion of Lr-delivered resistance by leaf rust remain largely unknown. Here, we identify an avirulence gene AvrLr21 in Pt that triggers Lr21-dependent immune responses. BSMV (Barley stripe mosaic virus)-mediated host-induced gene silencing assay shows that silencing AvrLr21 compromises Lr21-mediated immunity. AvrLr21 interacts directly with Lr21 protein to induce a hypersensitive response in tobacco leaves. The evolved Lr21-breaking Pt isolates can suppress Lr21-mediated immunity. Our data provide a basis for studying the molecular determinants in Pt-wheat incompatible interaction and monitoring natural Pt populations to prioritize the deployment of Lr resistance genes in the field.

Exploring the Frontier of Wheat Rust Resistance: Latest Approaches, Mechanisms, and Novel Insights

Wheat rusts, including leaf, stripe, and stem rust, have been a threat to global food security due to their devastating impact on wheat yields. In recent years, significant strides have been made in understanding wheat rusts, focusing on disease spread mechanisms, the discovery of new host resistance genes, and the molecular basis of rust pathogenesis. This review summarizes the latest approaches and studies in wheat rust research that provide a comprehensive understanding of disease mechanisms and new insights into control strategies. Recent advances in genetic resistance using modern genomics techniques, as well as molecular mechanisms of rust pathogenesis and host resistance, are discussed. In addition, innovative management strategies, including the use of fungicides and biological control agents, are reviewed, highlighting their role in combating wheat rust. This review also emphasizes the impact of climate change on rust epidemiology and underscores the importance of developing resistant wheat varieties along with adaptive management practices. Finally, gaps in knowledge are identified and suggestions for future research are made. This review aims to inform researchers, agronomists, and policy makers, and to contribute to the development of more effective and sustainable wheat rust control strategies.

Uncovering the Mechanisms: The Role of Biotrophic Fungi in Activating or Suppressing Plant Defense Responses

This paper discusses the mechanisms by which fungi manipulate plant physiology and suppress plant defense responses by producing effectors that can target various host proteins. Effector-triggered immunity and effector-triggered susceptibility are pivotal elements in the complex molecular dialogue underlying plant-pathogen interactions. Pathogen-produced effector molecules possess the ability to mimic pathogen-associated molecular patterns or hinder the binding of pattern recognition receptors. Effectors can directly target nucleotide-binding domain, leucine-rich repeat receptors, or manipulate downstream signaling components to suppress plant defense. Interactions between these effectors and receptor-like kinases in host plants are critical in this process. Biotrophic fungi adeptly exploit the signaling networks of key plant hormones, including salicylic acid, jasmonic acid, abscisic acid, and ethylene, to establish a compatible interaction with their plant hosts. Overall, the paper highlights the importance of understanding the complex interplay between plant defense mechanisms and fungal effectors to develop effective strategies for plant disease management.

EfficientRMT-Net-An Efficient ResNet-50 and Vision Transformers Approach for Classifying Potato Plant Leaf Diseases

The primary objective of this study is to develop an advanced, automated system for the early detection and classification of leaf diseases in potato plants, which are among the most cultivated vegetable crops worldwide. These diseases, notably early and late blight caused by Alternaria solani and Phytophthora infestans, significantly impact the quantity and quality of global potato production. We hypothesize that the integration of Vision Transformer (ViT) and ResNet-50 architectures in a new model, named EfficientRMT-Net, can effectively and accurately identify various potato leaf diseases. This approach aims to overcome the limitations of traditional methods, which are often labor-intensive, time-consuming, and prone to inaccuracies due to the unpredictability of disease presentation. EfficientRMT-Net leverages the CNN model for distinct feature extraction and employs depth-wise convolution (DWC) to reduce computational demands. A stage block structure is also incorporated to improve scalability and sensitive area detection, enhancing transferability across different datasets. The classification tasks are performed using a global average pooling layer and a fully connected layer. The model was trained, validated, and tested on custom datasets specifically curated for potato leaf disease detection. EfficientRMT-Net's performance was compared with other deep learning and transfer learning techniques to establish its efficacy. Preliminary results show that EfficientRMT-Net achieves an accuracy of 97.65% on a general image dataset and 99.12% on a specialized Potato leaf image dataset, outperforming existing methods. The model demonstrates a high level of proficiency in correctly classifying and identifying potato leaf diseases, even in cases of distorted samples. The EfficientRMT-Net model provides an efficient and accurate solution for classifying potato plant leaf diseases, potentially enabling farmers to enhance crop yield while optimizing resource utilization. This study confirms our hypothesis, showcasing the effectiveness of combining ViT and ResNet-50 architectures in addressing complex agricultural challenges.

A pathogen-induced putative NAC transcription factor mediates leaf rust resistance in barley

Leaf rust, caused by Puccinia hordei, is one of the most widespread and damaging foliar diseases affecting barley. The barley leaf rust resistance locus Rph7 has been shown to have unusually high sequence and haplotype divergence. In this study, we isolate the Rph7 gene using a fine mapping and RNA-Seq approach that is confirmed by mutational analysis and transgenic complementation. Rph7 is a pathogen-induced, non-canonical resistance gene encoding a protein that is distinct from other known plant disease resistance proteins in the Triticeae. Structural analysis using an AlphaFold2 protein model suggests that Rph7 encodes a putative NAC transcription factor with a zinc-finger BED domain with structural similarity to the N-terminal DNA-binding domain of the NAC transcription factor (ANAC019) from Arabidopsis. A global gene expression analysis suggests Rph7 mediates the activation and strength of the basal defence response. The isolation of Rph7 highlights the diversification of resistance mechanisms available for engineering disease control in crops.

Genetic mapping of the wheat leaf rust resistance gene Lr19 and development of translocation lines to break its linkage with yellow pigment

KEY MESSAGE

The leaf rust resistance gene Lr19, which is present on the long arm of chromosome 7E1 in Thinopyrum ponticum, was mapped within a 0.3-cM genetic interval, and translocation lines were developed to break its linkage with yellow pigmentation The leaf rust resistance locus Lr19, which was transferred to wheat (Triticum aestivum) from its relative Thinopyrum ponticum in 1966, still confers broad resistance to most known races of the leaf rust pathogen Puccinia triticina (Pt) worldwide. However, this gene has not previously been fine-mapped, and its tight linkage with a gene causing yellow pigmentation has limited its application in bread wheat breeding. In this study, we genetically mapped Lr19 using a bi-parental population from a cross of two wheat-Th. ponticum substitution lines, the Lr19-carrying line 7E1(7D) and the leaf rust-susceptible line 7E2(7D). Genetic analysis of the F2 population and the F2:3 families showed that Lr19 was a single dominant gene. Genetic markers allowed the gene to be mapped within a 0.3-cM interval on the long arm of Th. ponticum chromosome 7E1, flanked by markers XsdauK3734 and XsdauK2839. To reduce the size of the Th. ponticum chromosome segment carrying Lr19, the Chinese Spring Ph1b mutant was employed to promote recombination between the homoeologous chromosomes of the wheat chromosome 7D and the Th. ponticum chromosome 7E1. Two translocation lines with short Th. ponticum chromosome fragments carrying Lr19 were identified using the genetic markers closely linked to Lr19. Both translocation lines were resistant to 16 Pt races collected throughout China. Importantly, the linkage between Lr19 and yellow pigment content was broken in one of the lines. Thus, the Lr19 linked markers and translocation lines developed in this study are valuable resources in marker-assisted selection as part of common wheat breeding programs.

Phenotyping and Identification of Molecular Markers Associated with Leaf Rust Resistance in the Wheat Germplasm from Kazakhstan, CIMMYT and ICARDA

Leaf rust (LR) is the most widespread disease of common wheat worldwide. In order to evaluate leaf rust resistance, 70 uncharacterized wheat cultivars and promising lines with unknown leaf rust resistance genes (Lr genes) were exposed to Kazakhstani Puccinia triticina (Pt) races at the seedling stage. Field tests were performed to characterize leaf rust responses at the adult plant growth stage in the 2020-2021 and 2021-2022 cropping seasons. The wheat collection showed phenotypic diversity when tested with two virulent races of Pt. Thirteen wheat genotypes (18.6%) showed high resistance at both seedling and adult plant stages. In most cases, breeding material originating from international nurseries showed higher resistance to LR. Nine Lr genes, viz. Lr9, Lr10, Lr19, Lr26, Lr28, Lr34, Lr37, Lr46, and Lr68, either singly or in combination, were identified in 47 genotypes. Known Lr genes were not detected in the remaining 23 genotypes. The most commonly identified resistance genes were Lr37 (17 cultivars), Lr34 (16 cultivars), and Lr46 (10 cultivars), while Lr19, Lr68, Lr26, and Lr28 were the least frequent. Four Lr genes were identified in Keremet and Hisorok, followed by three Lr genes in Aliya, Rasad, Reke, Mataj, Egana and Almaly/Obri. The molecular screening revealed twenty-nine carriers of a single Lr gene, ten carriers of two genes, six carriers of three genes, and two carriers of four genes. Most of these accessions showed a high and moderate level of APR (Adult plant resistance) and may be utilized for the incorporation of Lr genes in well-adapted wheat cultivars. The most effective combination was Lr37, Lr34, and Lr68, the carriers of which were characterized by a low disease susceptibility index. The obtained results will facilitate breeding programs for wheat resistance in Kazakhstan.

Simplifying Barley Leaf Rust Research: An Easy and Reproducible Infection Protocol for Puccinia hordei on a Small Laboratory Scale

Barley (Hordeum vulgare) is one of the most important agricultural crops in the world, but pathogen infections regularly limit its annual yield. A major threat is the infection with the biotrophic leaf rust fungus, Puccinia hordei. Rust fungi have a complex life cycle, and existing resistances can be easily overcome. To address this problem, it is crucial to develop barley varieties with improved and durable resistance mechanisms. An essential step towards this goal is a simple and reproducible infection protocol to evaluate potential resistance phenotypes in the lab. However, available protocols sometimes lack detailed procedure or equipment information, use spore application methods that are not suitable for uniform spore dispersion, or require special mineral oils or engineered fluids. In addition, they are often optimized for pathogen-dedicated greenhouses or phytochambers, which may not be available to every research institute. Here, we describe an easy and user-friendly procedure to infect barley with Puccinia hordei on a small laboratory scale. This procedure utilizes inexpensive and simple tools to evenly split and apply spores to barley leaves. The treated plants are incubated in affordable and small phytocabinets. Our protocol enables a quick and reproducible infection of barley with leaf rust, a method that can easily be transferred to other rust fungi, including stripe rust, or to other plant species. Key features Step-by-step infection protocol established for barley cv. Golden Promise, the gold standard genotype for genetic transformation Plant age-independent protocol Precise spore application by using inexpensive pipe cleaners for uniform symptom formation and increased reproducibility No specialized equipment needed Includes simple spore harvesting method Protocol is applicable to other biotrophic pathogens (stripe rust or powdery mildew) and other plants (e.g., wheat) Protocol is also applicable for a detached leaf assay Graphical overview.

Expression Profiling of the Slow Rusting Resistance Genes Lr34/Yr18 and Lr67/Yr46 in Common Wheat (Triticum aestivum L.) and Associated miRNAs Patterns

The main efforts in common wheat (Triticum aestivum L.) breeding focus on yield, grain quality, and resistance to biotic and abiotic stresses. One of the major threats affecting global wheat cultivation and causing significant crop production losses are rust diseases, including leaf rust caused by a biotrophic fungus Puccinia triticina Eriks. Genetically determined resistance to leaf rust has been characterized in young plants (seedling resistance) as well as in plants at the adult plant stage. At the seedling stage, resistance is controlled vertically by major R genes, conferring a race-specific response that is highly effective but usually short-lived due to the rapid evolution of potentially virulent fungi. In mature plants, horizontal adult plant resistance (APR) was described, which provides long-term protection against multiple races of pathogens. A better understanding of molecular mechanisms underlying the function of APR genes would enable the development of new strategies for resistance breeding in wheat. Therefore, in the present study we focused on early transcriptomic responses of two major wheat APR genes, Lr34 and Lr67, and three complementary miRNAs, tae-miR9653b, tae-miR9773 and tae-miR9677b, to inoculation with P. triticina. Plant material consisted of five wheat reference varieties, Artigas, NP846, Glenlea, Lerma Rojo and TX89D6435, containing the Lr34/Yr18 and Lr67/Yr46 resistance genes. Biotic stress was induced by inoculation with fungal spores under controlled conditions in a phytotron. Plant material consisted of leaf tissue sampled before inoculation as well as 6, 12, 24 and 48 h postinoculation (hpi). The APR gene expression was quantified using real-time PCR with two reference genes, whereas miRNA was quantified using droplet digital PCR. This paper describes the resistance response of APR genes to inoculation with races of leaf rust-causing fungi that occur in central Europe. The study revealed high variability of expression profiles between varieties and time-points, with the prevalence of downregulation for APR genes and upregulation for miRNAs during the development of an early defense response. Nevertheless, despite the downregulation initially observed, the expression of Lr34 and Lr67 genes in studied cultivars was significantly higher than in a control line carrying wild (susceptible) alleles.

Advances in the Mining of Disease Resistance Genes from Aegilops tauschii and the Utilization in Wheat

Aegilops tauschii is one of the malignant weeds that affect wheat production and is also the wild species ancestor of the D genome of hexaploid wheat (Triticum aestivum, AABBDD). It contains many disease resistance genes that have been lost in the long-term evolution of wheat and is an important genetic resource for the mining and utilization of wheat disease resistance genes. In recent years, the genome sequence of Aegilops tauschii has been preliminarily completed, which has laid a good foundation for the further exploration of wheat disease resistance genes in Aegilops tauschii. There are many studies on disease resistance genes in Aegilops tauschii; in order to provide better help for the disease resistance breeding of wheat, this paper analyzes and reviews the relationship between Aegilops tauschii and wheat, the research progress of Aegilops tauschii, the discovery of disease resistance genes from Aegilops tauschii, and the application of disease resistance genes from Aegilops tauschii to modern wheat breeding, providing a reference for the further exploration and utilization of Aegilops tauschii in wheat disease resistance breeding.

A robust deep learning approach for tomato plant leaf disease localization and classification

Tomato plants' disease detection and classification at the earliest stage can save the farmers from expensive crop sprays and can assist in increasing the food quantity. Although, extensive work has been presented by the researcher for the tomato plant disease classification, however, the timely localization and identification of various tomato leaf diseases is a complex job as a consequence of the huge similarity among the healthy and affected portion of plant leaves. Furthermore, the low contrast information between the background and foreground of the suspected sample has further complicated the plant leaf disease detection process. To deal with the aforementioned challenges, we have presented a robust deep learning (DL)-based approach namely ResNet-34-based Faster-RCNN for tomato plant leaf disease classification. The proposed method includes three basic steps. Firstly, we generate the annotations of the suspected images to specify the region of interest (RoI). In the next step, we have introduced ResNet-34 along with Convolutional Block Attention Module (CBAM) as a feature extractor module of Faster-RCNN to extract the deep key points. Finally, the calculated features are utilized for the Faster-RCNN model training to locate and categorize the numerous tomato plant leaf anomalies. We tested the presented work on an accessible standard database, the PlantVillage Kaggle dataset. More specifically, we have obtained the mAP and accuracy values of 0.981, and 99.97% respectively along with the test time of 0.23 s. Both qualitative and quantitative results confirm that the presented solution is robust to the detection of plant leaf disease and can replace the manual systems. Moreover, the proposed method shows a low-cost solution to tomato leaf disease classification which is robust to several image transformations like the variations in the size, color, and orientation of the leaf diseased portion. Furthermore, the framework can locate the affected plant leaves under the occurrence of blurring, noise, chrominance, and brightness variations. We have confirmed through the reported results that our approach is robust to several tomato leaf diseases classification under the varying image capturing conditions. In the future, we plan to extend our approach to apply it to other parts of plants as well.

DCNet: DenseNet-77-based CornerNet model for the tomato plant leaf disease detection and classification

Early recognition of tomato plant leaf diseases is mandatory to improve the food yield and save agriculturalists from costly spray procedures. The correct and timely identification of several tomato plant leaf diseases is a complicated task as the healthy and affected areas of plant leaves are highly similar. Moreover, the incidence of light variation, color, and brightness changes, and the occurrence of blurring and noise on the images further increase the complexity of the detection process. In this article, we have presented a robust approach for tackling the existing issues of tomato plant leaf disease detection and classification by using deep learning. We have proposed a novel approach, namely the DenseNet-77-based CornerNet model, for the localization and classification of the tomato plant leaf abnormalities. Specifically, we have used the DenseNet-77 as the backbone network of the CornerNet. This assists in the computing of the more nominative set of image features from the suspected samples that are later categorized into 10 classes by the one-stage detector of the CornerNet model. We have evaluated the proposed solution on a standard dataset, named PlantVillage, which is challenging in nature as it contains samples with immense brightness alterations, color variations, and leaf images with different dimensions and shapes. We have attained an average accuracy of 99.98% over the employed dataset. We have conducted several experiments to assure the effectiveness of our approach for the timely recognition of the tomato plant leaf diseases that can assist the agriculturalist to replace the manual systems.

The genetic basis and interaction of genes conferring resistance to Puccinia hordei in an ICARDA barley breeding line GID 5779743

Leaf rust of barley causes significant losses in crops of susceptible cultivars. Deploying host resistance is the most cost-effective and eco-sustainable strategy to protect the harvest. However, most known leaf rust resistance genes have been overcome by the pathogen due to the pathogen's evolution and adaptation. The discovery of novel sources of genetic resistance is vital to keep fighting against pathogen evolution. In this study, we investigated the genetic basis of resistance in barley breeding line GID 5779743 (GID) from ICARDA, found to carry high levels of seedling resistance to prevalent Australian pathotypes of Puccinia hordei. Multipathotype tests, genotyping, and marker-trait associations revealed that the resistance in GID is conferred by two independent genes. The first gene, Rph3, was detected using a linked CAPS marker and QTL analysis. The second gene was detected by QTL analysis and mapped to the same location as that of the Rph5 locus on the telomeric region of chromosome 3HS. The segregating ratio in F2 (conforming to 9 resistant: 7 susceptible genetic ratio; p > 0.8) and F3 (1 resistant: 8 segregating: 7 susceptible; p > 0.19) generations of the GID × Gus population, when challenged with pathotype 5477 P- (virulent on Rph3 and Rph5) suggested the interaction of two genes in a complementary fashion. This study demonstrated that Rph3 interacts with Rph5 or an additional locus closely linked to Rph5 (tentatively designated RphGID) in GID to produce an incompatible response when challenged with a pathotype virulent on Rph3+Rph5.

Genotyping by Sequencing Advancements in Barley

Barley is considered an ideal crop to study cereal genetics due to its close relationship with wheat and diploid ancestral genome. It plays a crucial role in reducing risks to global food security posed by climate change. Genetic variations in the traits of interest in crops are vital for their improvement. DNA markers have been widely used to estimate these variations in populations. With the advancements in next-generation sequencing, breeders could access different types of genetic variations within different lines, with single-nucleotide polymorphisms (SNPs) being the most common type. However, genotyping barley with whole genome sequencing (WGS) is challenged by the higher cost and computational demand caused by the large genome size (5.5GB) and a high proportion of repetitive sequences (80%). Genotyping-by-sequencing (GBS) protocols based on restriction enzymes and target enrichment allow a cost-effective SNP discovery by reducing the genome complexity. In general, GBS has opened up new horizons for plant breeding and genetics. Though considered a reliable alternative to WGS, GBS also presents various computational difficulties, but GBS-specific pipelines are designed to overcome these challenges. Moreover, a robust design for GBS can facilitate the imputation to the WGS level of crops with high linkage disequilibrium. The complete exploitation of GBS advancements will pave the way to a better understanding of crop genetics and offer opportunities for the successful improvement of barley and its close relatives.

Phenotypic characterization of the Hordeum bulbosum derived leaf rust resistance genes Rph22 and Rph26 in barley

Aims

Two introgression lines (ILs), 182Q20 and 200A12, which had chromosomal segments introgressed from Hordeum bulbosum in H. vulgare backgrounds, were identified to show seedling resistance against Puccinia hordei, possibly attributed to two resistance genes, Rph22 and Rph26, respectively. This study characterized the phenotypic responses of the two genes against P. hordei over different plant development stages.

Methods and Results

Using visual and fungal biomass assessments, responses of ILs 182Q20, 200A12 and four other barley cultivars against P. hordei were determined at seedling, tillering, stem elongation and booting stages. Plants carrying either Rph22 or Rph26 were found to confer gradually increasing resistance over the course of different development stages, with partial resistant phenotypes (i.e. prolonged rust latency periods, reduced uredinia numbers but with susceptible infection types) observed at seedling stage and adult plant resistance (APR) at booting stage. A definitive switch between the two types of resistance occurred at tillering stage.

Conclusions

Rph22 and Rph26 derived from H. bulbosum were well characterized and had typical APR phenotypes against P. hordei.

Significance and Impact of the Study

This study provides important insights on the effectiveness and expression of Rph22 and Rph26 against P. hordei during plant development and underpins future barley breeding programmes using non‐host as a genetic resource for leaf rust management.

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Comparative Transcriptome Analysis Reveals the Gene Expression and Regulatory Characteristics of Broad-Spectrum Immunity to Leaf Rust in a Wheat-Agropyron cristatum 2P Addition Line

Wheat leaf rust (caused by Puccinia triticina Erikss.) is among the major diseases of common wheat. The lack of resistance genes to leaf rust has limited the development of wheat cultivars. Wheat-Agropyron cristatum (A. cristatum) 2P addition line II-9-3 has been shown to provide broad-spectrum immunity to leaf rust. To identify the specific A. cristatum resistance genes and related regulatory pathways in II-9-3, we conducted a comparative transcriptome analysis of inoculated and uninoculated leaves of the resistant addition line II-9-3 and the susceptible cultivar Fukuhokomugi (Fukuho). The results showed that there were 66 A. cristatum differentially expressed genes (DEGs) and 1389 wheat DEGs in II-9-3 during P. triticina infection. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and gene set enrichment analysis (GSEA) revealed that the DEGs of II-9-3 were associated with plant-pathogen interaction, MAPK signaling pathway-plant, plant hormone signal transduction, glutathione metabolism, and phenylpropanoid biosynthesis. Furthermore, many defense-related A. cristatum genes, such as two NLR genes, seven receptor kinase-encoding genes, and four transcription factor-encoding genes, were identified. Our results indicated that the key step of resistance to leaf rust involves, firstly, the gene expression of chromosome 2P upstream of the immune pathway and, secondly, the effect of chromosome 2P on the co-expression of wheat genes in II-9-3. The disease resistance regulatory pathways and related genes in the addition line II-9-3 thus could play a critical role in the effective utilization of innovative resources for leaf rust resistance in wheat breeding.

Artificial Intelligence-Based Drone System for Multiclass Plant Disease Detection Using an Improved Efficient Convolutional Neural Network

The role of agricultural development is very important in the economy of a country. However, the occurrence of several plant diseases is a major hindrance to the growth rate and quality of crops. The exact determination and categorization of crop leaf diseases is a complex and time-required activity due to the occurrence of low contrast information in the input samples. Moreover, the alterations in the size, location, structure of crop diseased portion, and existence of noise and blurriness effect in the input images further complicate the classification task. To solve the problems of existing techniques, a robust drone-based deep learning approach is proposed. More specifically, we have introduced an improved EfficientNetV2-B4 with additional added dense layers at the end of the architecture. The customized EfficientNetV2-B4 calculates the deep key points and classifies them in their related classes by utilizing an end-to-end training architecture. For performance evaluation, a standard dataset, namely, the PlantVillage Kaggle along with the samples captured using a drone is used which is complicated in the aspect of varying image samples with diverse image capturing conditions. We attained the average precision, recall, and accuracy values of 99.63, 99.93, and 99.99%, respectively. The obtained results confirm the robustness of our approach in comparison to other recent techniques and also show less time complexity.

The barley leaf rust resistance gene Rph3 encodes a predicted membrane protein and is induced upon infection by avirulent pathotypes of Puccinia hordei

Leaf rust, caused by Puccinia hordei, is an economically significant disease of barley, but only a few major resistance genes to P. hordei (Rph) have been cloned. In this study, gene Rph3 was isolated by positional cloning and confirmed by mutational analysis and transgenic complementation. The Rph3 gene, which originated from wild barley and was first introgressed into cultivated Egyptian germplasm, encodes a unique predicted transmembrane resistance protein that differs from all known plant disease resistance proteins at the amino acid sequence level. Genetic profiles of diverse accessions indicated limited genetic diversity in Rph3 in domesticated germplasm, and higher diversity in wild barley from the Eastern Mediterranean region. The Rph3 gene was expressed only in interactions with Rph3-avirulent P. hordei isolates, a phenomenon also observed for transcription activator-like effector-dependent genes known as executors conferring resistance to Xanthomonas spp. Like known transmembrane executors such as Bs3 and Xa7, heterologous expression of Rph3 in N. benthamiana induced a cell death response. The isolation of Rph3 highlights convergent evolutionary processes in diverse plant-pathogen interaction systems, where similar defence mechanisms evolved independently in monocots and dicots.

Leaf rust is an economically significant disease of barley. Here the authors describe cloning of the barley Rph3 leaf rust resistance gene and reveal it encodes a predicted transmembrane protein that is expressed upon infection by Rph3-avirulent Puccinia hordei isolates.

An Update on Resistance Genes and Their Use in the Development of Leaf Rust Resistant Cultivars in Wheat

Wheat is one of the most important cereal crops in the world. The production and productivity of wheat is adversely affected by several diseases including leaf rust, which can cause yield losses, sometimes approaching >50%. In the present mini-review, we provide updated information on (i) all Lr genes including those derived from alien sources and 14 other novel resistance genes; (ii) a list of QTLs identified using interval mapping and MTAs identified using GWAS (particular those reported recently i.e., after 2018) and their association with known Lr genes; (iii) introgression/pyramiding of individual Lr genes in commercial/prominent cultivars from 18 different countries including India. Challenges and future perspectives of breeding for leaf rust resistance are also provided at the end of this mini-review. We believe that the information in this review will prove useful for wheat geneticists/breeders, not only in the development of leaf rust-resistant wheat cultivars, but also in the study of molecular mechanism of leaf rust resistance in wheat.

The barley HvSTP13GR mutant triggers resistance against biotrophic fungi

High-yielding and stress-resistant crops are essential to ensure future food supply. Barley is an important crop to feed livestock and to produce malt, but the annual yield is threatened by pathogen infections. Pathogens can trigger an altered sugar partitioning in the host plant, which possibly leads to an advantage for the pathogen. Hampering these processes represents a promising strategy to potentially increase resistance. We analysed the response of the barley monosaccharide transporter HvSTP13 towards biotic stress and its potential use for plant protection. The expression of HvSTP13 increased on bacterial and fungal pathogen-associated molecular pattern (PAMP) application, suggesting a PAMP-triggered signalling that converged on the transcriptional induction of the gene. Promoter studies indicate a region that is probably targeted by transcription factors downstream of PAMP-triggered immunity pathways. We confirmed that the nonfunctional HvSTP13GR variant confers resistance against an economically relevant biotrophic rust fungus in barley. Our experimental setup provides basal prerequisites to further decode the role of HvSTP13 in response to biological stress. Moreover, in line with other studies, our experiments indicate that the alteration of sugar partitioning pathways, in a host-pathogen interaction, is a promising approach to achieve broad and durable resistance in plants.

A novel deep learning method for detection and classification of plant diseases

The agricultural production rate plays a pivotal role in the economic development of a country. However, plant diseases are the most significant impediment to the production and quality of food. The identification of plant diseases at an early stage is crucial for global health and wellbeing. The traditional diagnosis process involves visual assessment of an individual plant by a pathologist through on-site visits. However, manual examination for crop diseases is restricted because of less accuracy and the small accessibility of human resources. To tackle such issues, there is a demand to design automated approaches capable of efficiently detecting and categorizing numerous plant diseases. Precise identification and classification of plant diseases is a tedious job due because of the occurrence of low-intensity information in the image background and foreground, the huge color resemblance in the healthy and diseased plant areas, the occurrence of noise in the samples, and changes in the position, chrominance, structure, and size of plant leaves. To tackle the above-mentioned problems, we have introduced a robust plant disease classification system by introducing a Custom CenterNet framework with DenseNet-77 as a base network. The presented method follows three steps. In the first step, annotations are developed to get the region of interest. Secondly, an improved CenterNet is introduced in which DenseNet-77 is proposed for deep keypoints extraction. Finally, the one-stage detector CenterNet is used to detect and categorize several plant diseases. To conduct the performance analysis, we have used the PlantVillage Kaggle database, which is the standard dataset for plant diseases and challenges in terms of intensity variations, color changes, and differences found in the shapes and sizes of leaves. Both the qualitative and quantitative analysis confirms that the presented method is more proficient and reliable to identify and classify plant diseases than other latest approaches.

Analysis of NIA and GSNOR family genes and nitric oxide homeostasis in response to wheat-leaf rust interaction

Nitric oxide (NO) modulates plant response to biotic and abiotic stresses by S-nitrosylation-mediated protein post-translational modification. Nitrate reductase (NR) and S-nitrosoglutathione reductase (GSNOR) enzymes are essential for NO synthesis and the maintenance of Nitric oxide/S-nitroso glutathione (NO/GSNO) homeostasis, respectively. S-nitrosoglutathione, formed by the S-nitrosylation reaction of NO with glutathione, plays a significant physiological role as the mobile reservoir of NO. The genome-wide analysis identified nine NR (NIA) and three GSNOR genes in the wheat genome. Phylogenic analysis revealed that the nine NIA genes +were clustered into four groups and the 3 GSNORs into two groups. qRT-PCR expression profiling of NIAs and GSNORs was done in Chinese spring (CS), a leaf rust susceptible wheat line showing compatible interaction, and Transfer (TR), leaf rust-resistant wheat line showing incompatible interaction, post-inoculation with leaf rust pathotype 77-5 (121-R-63). All the NIA genes showed upregulation during incompatible interaction in comparison with the compatible reaction. The GSNOR genes showed a variable pattern of expression: the TaGSNOR1 showed little change, whereas TaGSNOR2 showed higher expression during the incompatible response. TaGSNOR3 showed a rise of expression both in compatible and incompatible reactions. Before inoculation and after 72 h of pathogen inoculation, NO localization was studied in both compatible and incompatible reactions. The S-nitrosothiol accumulation, NR, and glutathione reductase activity showed a consistent increase in the incompatible interactions. The results demonstrate that both NR and GSNOR plays significant role in defence against the leaf rust pathogen in wheat by modulating NO homeostasis or signalling.

Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat

Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs often explained only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1574 hybrids and characterized with 626 245 high-quality SNPs. In total, 2408 and 1 139 828 significant associations were detected in the mapping population by using SNP-based and FH-based GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, Lr22a and Lr34-B, while FH-based GWAS detected associations not only on these genes but also on two additional genes, Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, the use of detected associations from SNP-based and FH-based GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-based GWAS is not only more powerful for detecting associations, but also improves the accuracy of marker-assisted selection compared with the SNP-based approach.

Diversity of winter common wheat varieties for resistance to leaf rust created in the V. M. Remeslo myronivka institute of wheat

The results of the investigations of resistance winter common wheat varieties to leaf rust are given. The high resistance to the pathogen manifest varieties that contain resistance genes: Lr9, Lr19, Lr37, Lr42 + Lr24, Lr43 (Lr21 + Lr39) + Lr24, Lr9 + Lr26, Lr10 + Lr24 are ascertained. The genes Lr13, Lr34, Lr37 in combination with other resistance genes provides long-term protection to leaf rust wheat. Winter wheat varieties, created at the V. M. Remeslo Myronivka Institute of Wheat, contain resistance genes Lr23, Lr24, Lr26, Lr34. The varieties Vesta, Snizhana, Demetra are protected by the resistance genes Lr26 + Lr34, variety Zolotokolosa– Lr24 + Lr34, Ekonomka – Lr3 + Lr26, Myronivska storichna – Lr3 + Lr23 + Lr10 + Lr26. The allele Lr34 (+) is contained in varieties: Kryzhynka, Vesta, Snizhana, Volodarka, Demetra, Vdiachna, Pamiati Remesla, Sviatkova, Podolianka, Berehynia myronivska, MIP Dniprianka, and Balada myronivska.  Sustainability is an important element of an integrated system of plant protection against many diseases, and to ensure increased yields it is necessary to create and distribute sustainable varieties that will be an environmentally promising way to develop the agro-industrial complex of Ukraine.

The donor properties of resources resistance against the exciter of wheat rust wheat

A collection of soft winter wheat specimens investigated on the artificial infectious background of the leaf rust pathogen and selected resistance among them. The genetics of resistance sign in varieties and specimens were determined by hybridological analysis of F2: Lovrin 32, KM 1485-6-8, VR 89 Bo 22, Beres, Tobarzo, 0-74-8-2, MIKM 1851-80, 4347-4, NS 326-99, 5517 A-5-5 Yr, Florida 302, VR 87 Bo 15, Matyo, NS 1308, 200-830, Polka, NS 2630/1, NS 18-30, HBE 0140-119, HBE 208-120, HBE 0303 156, HBE 0425-156, Tx91v4511, Tx92v4511, Plyska, Zernogradskaya 31, Volshebnitsa, Myronivska 40, Myronivska ostysta, Myronivska 28, Estet, Volynska napivintensivna, Kyivska 8, Expromt, Mironivska 29, Remeslivna, Garant, Selyanka, Erythrospermum 15761, Erythrospermum 12557, Erythrospermum 12735, Vympel odeskyiy during 1990–2018. The gene non-identity of the investigated donors was determined. In a variety of VR 89 Bo 22, 2 resistance genes, one of them Lr19, was investigated. The results of investigations of the composition of the leaf rust pathogen population by a series of isogenic lines and varieties of carriers of known effective resistance genes are presented. The high resistance against the leaf rust pathogen in the forest-steppe of Ukraine provide the genes Lr9, Lr19, Lr37, Lr42 + Lr24, Lr43 (Lr21 + Lr39) + Lr24, Lr9 + Lr26, Lr10 + Lr24.

Application of Genomics Tools in Wheat Breeding to Attain Durable Rust Resistance

Wheat is an important source of dietary protein and calories for the majority of the world's population. It is one of the largest grown cereal in the world occupying over 215 M ha. Wheat production globally is challenged by biotic stresses such as pests and diseases. Of the 50 diseases of wheat that are of economic importance, the three rust diseases are the most ubiquitous causing significant yield losses in the majority of wheat production environments. Under severe epidemics they can lead to food insecurity threats amid the continuous evolution of new races of the pathogens, shifts in population dynamics and their virulence patterns, thereby rendering several effective resistance genes deployed in wheat breeding programs vulnerable. This emphasizes the need to identify, characterize, and deploy effective rust-resistant genes from diverse sources into pre-breeding lines and future wheat varieties. The use of genetic resistance has been marked as eco-friendly and to curb the further evolution of rust pathogens. Deployment of multiple rust resistance genes including major and minor genes in wheat lines could enhance the durability of resistance thereby reducing pathogen evolution. Advances in next-generation sequencing (NGS) platforms and associated bioinformatics tools have revolutionized wheat genomics. The sequence alignment of the wheat genome is the most important landmark which will enable genomics to identify marker-trait associations, candidate genes and enhanced breeding values in genomic selection (GS) studies. High throughput genotyping platforms have demonstrated their role in the estimation of genetic diversity, construction of the high-density genetic maps, dissecting polygenic traits, and better understanding their interactions through GWAS (genome-wide association studies) and QTL mapping, and isolation of R genes. Application of breeder's friendly KASP assays in the wheat breeding program has expedited the identification and pyramiding of rust resistance alleles/genes in elite lines. The present review covers the evolutionary trends of the rust pathogen and contemporary wheat varieties, and how these research strategies galvanized to control the wheat killer genus Puccinia. It will also highlight the outcome and research impact of cost-effective NGS technologies and cloning of rust resistance genes amid the public availability of common and tetraploid wheat reference genomes.

Fusarium Head Blight and Rust Diseases in Soft Red Winter Wheat in the Southeast United States: State of the Art, Challenges and Future Perspective for Breeding

Among the biotic constraints to wheat (Triticum aestivum L.) production, fusarium head blight (FHB), caused by Fusarium graminearum, leaf rust (LR), caused by Puccinia triticina, and stripe rust (SR) caused by Puccinia striiformis are problematic fungal diseases worldwide. Each can significantly reduce grain yield while FHB causes additional food and feed safety concerns due to mycotoxin contamination of grain. Genetic resistance is the most effective and sustainable approach for managing wheat diseases. In the past 20 years, over 500 quantitative trait loci (QTLs) conferring small to moderate effects for the different FHB resistance types have been reported in wheat. Similarly, 79 Lr-genes and more than 200 QTLs and 82 Yr-genes and 140 QTLs have been reported for seedling and adult plant LR and SR resistance, respectively. Most QTLs conferring rust resistance are race-specific generally conforming to a classical gene-for-gene interaction while resistance to FHB exhibits complex polygenic inheritance with several genetic loci contributing to one resistance type. Identification and deployment of additional genes/QTLs associated with FHB and rust resistance can expedite wheat breeding through marker-assisted and/or genomic selection to combine small-effect QTL in the gene pool. LR disease has been present in the southeast United States for decades while SR and FHB have become increasingly problematic in the past 20 years, with FHB arguably due to increased corn acreage in the region. Currently, QTLs on chromosome 1B from Jamestown, 1A, 1B, 2A, 2B, 2D, 4A, 5A, and 6A from W14, Ning7840, Ernie, Bess, Massey, NC-Neuse, and Truman, and 3B (Fhb1) from Sumai 3 for FHB resistance, Lr9, Lr10, Lr18, Lr24, Lr37, LrA2K, and Lr2K38 genes for LR resistance, and Yr17 and YrR61 for SR resistance have been extensively deployed in southeast wheat breeding programs. This review aims to disclose the current status of FHB, LR, and SR diseases, summarize the genetics of resistance and breeding efforts for the deployment of FHB and rust resistance QTL on soft red winter wheat cultivars, and present breeding strategies to achieve sustainable management of these diseases in the southeast US.

Molecular identification of slow rusting resistance Lr46/Yr29 gene locus in selected triticale (× Triticosecale Wittmack) cultivars

Recently, leaf rust and yellow rust caused by the fungi Puccinia triticina Erikss. and P. striiformis Westend f. sp. tritici Eriks and Henn are diseases of increasing threat in triticale (× Triticosecale Wittmack, AABBRR, 2n = 6x = 42) growing areas. The use of genetic resistance is considered the most economical, effective and environmentally friendly method to control the disease and minimize the use of fungicides. Currently, breeding programs mainly relied on race-specific Lr and Yr genes (R), but new races of the rust fungi frequently defeat resistance. There is a small group of genes that causes partial type of resistance (PR) that are characterized by a slow epidemic build up despite a high infection type. In wheat slow rusting resistance genes displayed longer latent periods, low infection frequencies, smaller pustule size and less spore production. Slow rusting Lr46/Yr29 gene, located on chromosome 1B, is being exploited in many wheat breeding programs. So far, there is no information about slow rusting genes in triticale. This paper showed significant differences between the results of identification of wheat molecular markers Xwmc44 and csLV46G22 associated with Lr46/Yr29 in twenty triticale cultivars, which were characterized by high levels of field resistance to leaf and yellow rust. The csLV46G22res marker has been identified in the following cultivars: Kasyno, Mamut and Puzon. Belcanto and Kasyno showed the highest resistance levels in three-year (2016–2018), leaf and yellow rust severity tests under post-registration variety testing program (PDO). Leaf tip necrosis, a phenotypic trait associated with Lr34/Yr18 and Lr46/Yr29 was observed, among others, to Belcanto and Kasyno, which showed the highest resistance for leaf rust and yellow rust. Kasyno could be considered to have Lr46/Yr29 and can be used as a source of slow rust resistance in breeding and importantly as a component of gene pyramiding in triticale.