Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize

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.

NIR-HSI as a tool to predict deoxynivalenol and fumonisins in maize kernels: a step forward in preventing mycotoxin contamination

BACKGROUND

Maize is frequently contaminated with deoxynivalenol (DON) and fumonisins B1 (FB1) and B2 (FB2). In the European Union, these mycotoxins are regulated in maize and maize-derived products. To comply with these regulations, industries require a fast, economic, safe, non-destructive and environmentally friendly analysis method.

RESULTS

In the present study, near-infrared hyperspectral imaging (NIR-HSI) was used to develop regression and classification models for DON, FB1 and FB2 in maize kernels. The best regression models presented the following root mean square error of cross validation and ratio of performance to deviation values: 0.848 mg kg-1 and 2.344 (DON), 3.714 mg kg-1 and 2.018 (FB1) and 2.104 mg kg-1 and 2.301 (FB2). Regarding classification, European Union legal limits for DON and FB1 + FB2 were selected as thresholds to classify maize kernels as acceptable or not. The sensitivity and specificity were 0.778 and 1 for the best DON classification model and 0.607 and 0.938 for the best FB1 + FB2 classification model.

CONCLUSION

NIR-HSI can help reduce DON and fumonisins contamination in the maize food and feed chain. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Food Safety Aspects of Breeding Maize to Multi-Resistance against the Major (Fusarium graminearum, F. verticillioides, Aspergillus flavus) and Minor Toxigenic Fungi (Fusarium spp.) as Well as to Toxin Accumulation, Trends, and Solutions-A Review

Maize is the crop which is most commonly exposed to toxigenic fungi that produce many toxins that are harmful to humans and animals alike. Preharvest grain yield loss, preharvest toxin contamination (at harvest), and storage loss are estimated to be between 220 and 265 million metric tons. In the past ten years, the preharvest mycotoxin damage was stable or increased mainly in aflatoxin and fumonisins. The presence of multiple toxins is characteristic. The few breeding programs concentrate on one of the three main toxigenic fungi. About 90% of the experiments except AFB1 rarely test toxin contamination. As disease resistance and resistance to toxin contamination often differ in regard to F. graminearum, F. verticillioides, and A. flavus and their toxins, it is not possible to make a food safety evaluation according to symptom severity alone. The inheritance of the resistance is polygenic, often mixed with epistatic and additive effects, but only a minor part of their phenotypic variation can be explained. All tests are made by a single inoculum (pure isolate or mixture). Genotype ranking differs between isolates and according to aggressiveness level; therefore, the reliability of such resistance data is often problematic. Silk channel inoculation often causes lower ear rot severity than we find in kernel resistance tests. These explain the slow progress and raise skepticism towards resistance breeding. On the other hand, during genetic research, several effective putative resistance genes were identified, and some overlapped with known QTLs. QTLs were identified as securing specific or general resistance to different toxicogenic species. Hybrids were identified with good disease and toxin resistance to the three toxigenic species. Resistance and toxin differences were often tenfold or higher, allowing for the introduction of the resistance and resistance to toxin accumulation tests in the variety testing and the evaluation of the food safety risks of the hybrids within 2-3 years. Beyond this, resistance breeding programs and genetic investigations (QTL-analyses, GWAM tests, etc.) can be improved. All other research may use it with success, where artificial inoculation is necessary. The multi-toxin data reveal more toxins than we can treat now. Their control is not solved. As limits for nonregulated toxins can be introduced, or the existing regulations can be made to be stricter, the research should start. We should mention that a higher resistance to F. verticillioides and A. flavus can be very useful to balance the detrimental effect of hotter and dryer seasons on aflatoxin and fumonisin contamination. This is a new aspect to secure food and feed safety under otherwise damaging climatic conditions. The more resistant hybrids are to the three main agents, the more likely we are to reduce the toxin losses mentioned by about 50% or higher.

Kernel Bioassay Evaluation of Maize Ear Rot and Genome-Wide Association Analysis for Identifying Genetic Loci Associated with Resistance to Fusarium graminearum Infection

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most destructive diseases in maize, which severely reduces yield and contaminates several potential mycotoxins in the grain. However, few efforts had been devoted to dissecting the genetic basis of maize GER resistance. In the present study, a genome-wide association study (GWAS) was conducted in a maize association panel consisting of 303 diverse inbred lines. The phenotypes of GER severity were evaluated using kernel bioassay across multiple time points in the laboratory. Then, three models, including the fixed and random model circulating probability unification model (FarmCPU), general linear model (GLM), and mixed linear model (MLM), were conducted simultaneously in GWAS to identify single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance. A total of four individual significant association SNPs with the phenotypic variation explained (PVE) ranging from 3.51 to 6.42% were obtained. Interestingly, the peak SNP (PUT-163a-71443302-3341) with the greatest PVE value, was co-localized in all models. Subsequently, 12 putative genes were captured from the peak SNP, and several of these genes were directly or indirectly involved in disease resistance. Overall, these findings contribute to understanding the complex plant-pathogen interactions in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the kernel bioassay that can be used for evaluating and selecting elite germplasm resources with GER resistance in maize.

Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Genome-Wide Association Study Discovers Novel Germplasm Resources and Genetic Loci with Resistance to Gibberella Ear Rot Caused by Fusarium graminearum

Gibberella ear rot (GER) in maize caused by Fusarium graminearum is one of the most devastating maize diseases reducing grain yield and quality worldwide. The genetic bases of maize GER resistance remain largely unknown. Using artificial inoculation across multiple environments, the GER severity of an association panel consisting of 316 diverse inbred lines was observed with wide phenotypic variation. In the association panel, a genome-wide association study using a general linear model identified 69 single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance at the threshold of 2.04 × 10-5, and the average phenotypic variation explained (PVE) of these SNPs was 5.09%. We also conducted a genome-wide association study analysis using a mixed linear model at a threshold of 1.0 × 10-4, and 16 significantly associated SNPs with an average PVE of 4.73% were detected. A combined general linear model and mixed linear model method obtained 10 co-localized significantly associated SNPs linked to GER resistance, including the most significant SNP (PZE-105079915) with the greatest PVE value, 9.07%, at bin 5.05 following 10 candidate genes. These findings are significant for the exploration of the complicated genetic variations in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the elite germplasm resources that can be used for breeding GER resistance in maize.

Breeding and Genomic Approaches towards Development of Fusarium Wilt Resistance in Chickpea

Chickpea is an important leguminous crop with potential to provide dietary proteins to both humans and animals. It also ameliorates soil nitrogen through biological nitrogen fixation. The crop is affected by an array of biotic and abiotic factors. Among different biotic stresses, a major fungal disease called Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (FOC), is responsible for low productivity in chickpea. To date, eight pathogenic races of FOC (race 0, 1A, and 1B/C, 2-6) have been reported worldwide. The development of resistant cultivars using different conventional breeding methods is very time consuming and depends upon the environment. Modern technologies can improve conventional methods to solve these major constraints. Understanding the molecular response of chickpea to Fusarium wilt can help to provide effective management strategies. The identification of molecular markers closely linked to genes/QTLs has provided great potential for chickpea improvement programs. Moreover, omics approaches, including transcriptomics, metabolomics, and proteomics give scientists a vast viewpoint of functional genomics. In this review, we will discuss the integration of all available strategies and provide comprehensive knowledge about chickpea plant defense against Fusarium wilt.

A Combination of QTL Mapping and GradedPool-Seq to Dissect Genetic Complexity for Gibberella Ear Rot Resistance in Maize Using an IBM Syn10 DH Population

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most devastating maize diseases that reduces grain yield and quality worldwide. Utilization of host genetic resistance has become one of the most suitable strategies to control GER. In this study, a set of 246 diverse inbred lines derived from the intermated B 73 × Mo 17 doubled haploid population (IBM Syn10 DH) were used to detect quantitative trait loci (QTL) associated with resistance to GER. Meanwhile, a GradedPool-Seq (GPS) approach was performed to identify genomic variations involved in GER resistance. Using artificial inoculation across multiple environments, GER severity of the population was observed with wide phenotypic variation. Based on the linkage mapping, a total of 14 resistant QTLs were detected, accounting for 5.11 to 14.87% of the phenotypic variation, respectively. In GPS analysis, five significant single nucleotide polymorphisms (SNPs) associated with GER resistance were identified. Combining QTL mapping and GPS analysis, a peak-value SNP on chromosome 4 from GPS was overlapped with the QTL qGER4.2, suggesting that the colocalized region could be the most possible target location conferring resistance to GER. Subsequently, seven candidate genes were identified within the peak SNP, linking them to GER resistance. These findings are useful for exploring the complicated genetic variations in maize GER resistance. The genomic regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the combined strategy that can be used for quantitative traits in plant species.

Toward combining qualitative race-specific and quantitative race-nonspecific disease resistance by genomic selection

A novel genomic selection strategy offers the unique opportunity to develop qualitative race-specific resistant varieties that possess high levels of the more durable quantitative race-nonspecific resistance in their genetic background. Race-specific qualitative resistance genes (R-genes) are conferring complete resistance in many pathosystems, but are frequently overcome by new virulent pathogen races. Once the deployed R-genes are overcome, a wide variation of quantitative disease resistance (QDR) can be observed in a set of previously race-specific, i.e., completely resistant genotypes-a phenomenon known as "vertifolia effect." This race-nonspecific QDR is considered to be more durable in the long term, but provides merely a partial protection against pathogens. This simulation study aimed to detangle race-specific R-gene-mediated resistance of pending selection candidates and the QDR in their genetic background by employing different genomic selection strategies. True breeding values that reflected performance data for rust resistance in wheat were simulated, and used in a recurrent genomic selection based on several prediction models and training population designs. Using training populations that were devoid of race-specific R-genes was thereby pivotal for an efficient improvement of QDR in the long term. Marker-assisted preselection for the presence of R-genes followed by a genomic prediction for accumulating the many small to medium effect loci underlying QDR in the genetic background of race-specific resistant genotypes appeared furthermore to be a promising approach to select simultaneously for both types of resistance. The practical application of such a knowledge-driven genomic breeding strategy offers the opportunity to develop varieties with multiple layers of resistance, which have the potential to prevent intolerable crop losses under epidemic situations by displaying a high level of QDR even when race-specific R-genes have been overcome by evolving pathogen populations.

Phenotypic variation and quantitative trait loci for resistance to southern anthracnose and clover rot in red clover

High variability for and candidate loci associated with resistance to southern anthracnose and clover rot in a worldwide collection of red clover provide a first basis for genomics-assisted breeding. Red clover (Trifolium pratense L.) is an important forage legume of temperate regions, particularly valued for its high yield potential and its high forage quality. Despite substantial breeding progress during the last decades, continuous improvement of cultivars is crucial to ensure yield stability in view of newly emerging diseases or changing climatic conditions. The high amount of genetic diversity present in red clover ecotypes, landraces, and cultivars provides an invaluable, but often unexploited resource for the improvement of key traits such as yield, quality, and resistance to biotic and abiotic stresses. A collection of 397 red clover accessions was genotyped using a pooled genotyping-by-sequencing approach with 200 plants per accession. Resistance to the two most pertinent diseases in red clover production, southern anthracnose caused by Colletotrichum trifolii, and clover rot caused by Sclerotinia trifoliorum, was assessed using spray inoculation. The mean survival rate for southern anthracnose was 22.9% and the mean resistance index for clover rot was 34.0%. Genome-wide association analysis revealed several loci significantly associated with resistance to southern anthracnose and clover rot. Most of these loci are in coding regions. One quantitative trait locus (QTL) on chromosome 1 explained 16.8% of the variation in resistance to southern anthracnose. For clover rot resistance we found eight QTL, explaining together 80.2% of the total phenotypic variation. The SNPs associated with these QTL provide a promising resource for marker-assisted selection in existing breeding programs, facilitating the development of novel cultivars with increased resistance against two devastating fungal diseases of red clover.

SNP-based bulk segregant analysis revealed disease resistance QTLs associated with northern corn leaf blight in maize

Maize (Zea mays L.) is the most important food security crop worldwide. Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, severely reduces production causing millions of dollars in losses worldwide. Therefore, this study aimed to identify significant QTLs associated with NCLB by utilizing next-generation sequencing-based bulked-segregant analysis (BSA). Parental lines GML71 (resistant) and Gui A10341 (susceptible) were used to develop segregating population F₂. Two bulks with 30 plants each were further selected from the segregating population for sequencing along with the parental lines. High throughput sequencing data was used for BSA. We identified 10 QTLs on Chr 1, Chr 2, Chr 3, and Chr 5 with 265 non-synonymous SNPs. Moreover, based on annotation information, we identified 27 candidate genes in the QTL regions. The candidate genes associated with disease resistance include AATP1, At4g24790, STICHEL-like 2, BI O 3-BIO1, ZAR1, SECA2, ABCG25, LECRK54, MKK7, MKK9, RLK902, and DEAD-box ATP-dependent RNA helicase. The annotation information suggested their involvement in disease resistance-related pathways, including protein phosphorylation, cytoplasmic vesicle, protein serine/threonine kinase activity, and ATP binding pathways. Our study provides a substantial addition to the available information regarding QTLs associated with NCLB, and further functional verification of identified candidate genes can broaden the scope of understanding the NCLB resistance mechanism in maize.

Trichoderma versus Fusarium-Inhibition of Pathogen Growth and Mycotoxin Biosynthesis

This study evaluated the ability of selected strains of Trichoderma viride, T. viridescens, and T. atroviride to inhibit mycelium growth and the biosynthesis of mycotoxins deoxynivalenol (DON), nivalenol (NIV), zearalenone (ZEN), α-(α-ZOL) and β-zearalenol (β-ZOL) by selected strains of Fusarium culmorum and F. cerealis. For this purpose, an in vitro experiment was carried out on solid substrates (PDA and rice). After 5 days of co-culture, it was found that all Trichoderma strains used in the experiment significantly inhibited the growth of Fusarium mycelium. Qualitative assessment of pathogen-antagonist interactions showed that Trichoderma colonized 75% to 100% of the medium surface (depending on the species and strain of the antagonist and the pathogen) and was also able to grow over the mycelium of the pathogen and sporulate. The rate of inhibition of Fusarium mycelium growth by Trichoderma ranged from approximately 24% to 66%. When Fusarium and Trichoderma were co-cultured on rice, Trichoderma strains were found to inhibit DON biosynthesis by about 73% to 98%, NIV by about 87% to 100%, and ZEN by about 12% to 100%, depending on the pathogen and antagonist strain. A glycosylated form of DON was detected in the co-culture of F. culmorum and Trichoderma, whereas it was absent in cultures of the pathogen alone, thus suggesting that Trichoderma is able to glycosylate DON. The results also suggest that a strain of T. viride is able to convert ZEN into its hydroxylated derivative, β-ZOL.

Recent Research on Fusarium Mycotoxins in Maize-A Review

Maize (Zea mays L.) is one of the most susceptible crops to pathogenic fungal infections, and in particular to the Fusarium species. Secondary metabolites of Fusarium spp.-mycotoxins are not only phytotoxic, but also harmful to humans and animals. They can cause acute or chronic diseases with various toxic effects. The European Union member states apply standards and legal regulations on the permissible levels of mycotoxins in food and feed. This review summarises the most recent knowledge on the occurrence of toxic secondary metabolites of Fusarium in maize, taking into account modified forms of mycotoxins, the progress in research related to the health effects of consuming food or feed contaminated with mycotoxins, and also the development of biological methods for limiting and/or eliminating the presence of the same in the food chain and in compound feed.

Meta-analysis and co-expression analysis revealed stable QTL and candidate genes conferring resistances to Fusarium and Gibberella ear rots while reducing mycotoxin contamination in maize

Fusarium (FER) and Gibberella ear rots (GER) are the two most devastating diseases of maize (Zea mays L.) which reduce yield and affect grain quality worldwide, especially by contamination with mycotoxins. Genetic improvement of host resistance to effectively tackle FER and GER diseases requires the identification of stable quantitative trait loci (QTL) to facilitate the application of genomics-assisted breeding for improving selection efficiency in breeding programs. We applied improved meta-analysis algorithms to re-analyze 224 QTL identified in 15 studies based on dense genome-wide single nucleotide polymorphisms (SNP) in order to identify meta-QTL (MQTL) and colocalized genomic loci for fumonisin (FUM) and deoxynivalenol (DON) accumulation, silk (SR) and kernel (KR) resistances of both FER and GER, kernel dry-down rate (KDD) and husk coverage (HC). A high-resolution genetic consensus map with 36,243 loci was constructed and enabled the projection of 164 of the 224 collected QTL. Candidate genes (CG) mining was performed within the most refined MQTL, and identified CG were cross-validated using publicly available transcriptomic data of maize under Fusarium graminearum infection. The meta-analysis revealed 40 MQTL, of which 29 were associated each with 2-5 FER- and/or GER-related traits. Twenty-eight of the 40 MQTL were common to both FER and GER resistances and 19 MQTL were common to silk and kernel resistances. Fourteen most refined MQTL on chromosomes 1, 2, 3, 4, 7 and 9 harbored a total of 2,272 CG. Cross-validation identified 59 of these CG as responsive to FER and/or GER diseases. MQTL ZmMQTL2.2, ZmMQTL9.2 and ZmMQTL9.4 harbored promising resistance genes, of which GRMZM2G011151 and GRMZM2G093092 were specific to the resistant line for both diseases and encoded "terpene synthase21 (tps21)" and "flavonoid O-methyltransferase2 (fomt2)", respectively. Our findings revealed stable refined MQTL harboring promising candidate genes for use in breeding programs for improving FER and GER resistances with reduced mycotoxin accumulation. These candidate genes can be transferred into elite cultivars by integrating refined MQTL into genomics-assisted backcross breeding strategies.

Powdery Mildew Resistance Genes in European Barley Cultivars Registered in the Czech Republic from 2016 to 2020

Barley is an important crop grown annually on about 55 Mha and intensively cultivated in Europe. In central and north-western Europe, spring and winter barley can be grown in similar environments which creates suitable conditions for the development of barley pathogens, including Blumeria graminis f. sp. hordei, the causal agent of powdery mildew. Apart from pesticide application, it can be controlled by inexpensive and environmentally-friendly genetic resistance. In this contribution, results of the resistance gene identification in 58 barley cultivars to powdery mildew are presented. In 56 of them their resistances were postulated and in two hybrid cultivars a recently developed method of gene identification was used. In total, 18 known resistance genes were found and several unknown genes were detected. In spring barley, a gene of durable resistance mlo is still predominant. MlVe found in winter SU Celly was the only new resistance gene recorded in barley cultivars registered in the Czech Republic in this time span. Since 2001 eight new genes of specific resistance have been identified in cultivars registered in the country and their response under field conditions is discussed, including the corresponding responses of the pathogen population due to directional selection. Different strategies for breeding spring and winter barley are recommended.

Back to the wild: mining maize (Zea mays L.) disease resistance using advanced breeding tools

Cultivated modern maize (Zea mays L.) originated through the continuous process of domestication from its wild progenitors. Today, maize is considered as the most important cereal crop which is extensively cultivated in all parts of the world. Maize shows remarkable genotypic and phenotypic diversity which makes it an ideal model species for crop genetic research. However, intensive breeding and artificial selection of desired agronomic traits greatly narrow down the genetic bases of maize. This reduction in genetic diversity among cultivated maize led to increase the chance of more attack of biotic stress as climate changes hampering the maize grain production globally. Maize germplasm requires to integrate both durable multiple-diseases and multiple insect-pathogen resistance through tapping the unexplored resources of maize landraces. Revisiting the landraces seed banks will provide effective opportunities to transfer the resistant genes into the modern cultivars. Here, we describe the maize domestication process and discuss the unique genes from wild progenitors which potentially can be utilized for disease resistant in maize. We also focus on the genetics and disease resistance mechanism of various genes against maize biotic stresses and then considered the different molecular breeding tools for gene transfer and advanced high resolution mapping for gene pyramiding in maize lines. At last, we provide an insight for targeting identified key genes through CRISPR/Cas9 genome editing system to enhance the maize resilience towards biotic stress.

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction

Conceived as a general introduction to the book, this chapter is a reminder of the core concepts of genetic mapping and molecular marker-based prediction. It provides an overview of the principles and the evolution of methods for mapping the variation of complex traits, and methods for QTL-based prediction of human disease risk and animal and plant breeding value. The principles of linkage-based and linkage disequilibrium-based QTL mapping methods are described in the context of the simplest, single-marker, methods. Methodological evolutions are analysed in relation with their ability to account for the complexity of the genotype-phenotype relations. Main characteristics of the genetic architecture of complex traits, drawn from QTL mapping works using large populations of unrelated individuals, are presented. Methods combining marker-QTL association data into polygenic risk score that captures part of an individual's susceptibility to complex diseases are reviewed. Principles of best linear mixed model-based prediction of breeding value in animal- and plant-breeding programs using phenotypic and pedigree data, are summarized and methods for moving from BLUP to marker-QTL BLUP are presented. Factors influencing the additional genetic progress achieved by using molecular data and rules for their optimization are discussed.

Powdery Mildew Resistance Phenotypes of Wheat Gene Bank Accessions

Powdery mildew (Blumeria graminis f. sp. tritici) is a common pathogen of bread wheat (Triticum aestivum L.), and genetic resistance is an effective and environmentally friendly method to reduce its adverse impact. The introgression of novel genes from wheat progenitors and related species can increase the diversity of disease resistance and accumulation of minor genes to improve the crop's resistance durability. To accomplish these two actions, host genotypes without major resistances should be preferably used. Therefore, the main aim of this study was to carry out seedling tests to detect such resistances in a set of wheat accessions from the Czech gene bank and to group the cultivars according to their phenotype. Ear progenies of 448 selected cultivars originating from 33 countries were inoculated with three isolates of the pathogen. Twenty-eight cultivars were heterogeneous, and 110 cultivars showed resistance to at least one isolate. Fifty-nine cultivars, mostly from Northwest Europe, were resistant to all three isolates were more than three times more frequently recorded in spring than in winter cultivars. Results will facilitate a rational and practical approach preferably using the set of cultivars without major resistances for both mentioned methods of breeding wheat cultivars resistant to powdery mildew.

Climate change will influence disease resistance breeding in wheat in Northwestern Europe

Wheat productivity is threatened by global climate change. In several parts of NW Europe it will get warmer and dryer during the main crop growing period. The resulting likely lower realized on-farm crop yields must be kept by breeding for resistance against already existing and emerging diseases among other measures. Multi-disease resistance will get especially crucial. In this review, we focus on disease resistance breeding approaches in wheat, especially related to rust diseases and Fusarium head blight, because simulation studies of potential future disease risk have shown that these diseases will be increasingly relevant in the future. The long-term changes in disease occurrence must inevitably lead to adjustments of future resistance breeding strategies, whereby stability and durability of disease resistance under heat and water stress will be important in the future. In general, it would be important to focus on non-temperature sensitive resistance genes/QTLs. To conclude, research on the effects of heat and drought stress on disease resistance reactions must be given special attention in the future.