The effect of the SnTox3-Snn3 interaction was documented for the first time under natural infection at the adult plant stage in the field. Co-segregating SNP markers were identified. Parastagonospora nodorum is a necrotrophic pathogen of wheat, causing Septoria nodorum blotch (SNB) affecting both the leaf and glume. P. nodorum is the major leaf blotch pathogen on spring wheat in Norway. Resistance to the disease is quantitative, but several host-specific interactions between necrotrophic effectors (NEs) and host sensitivity (Snn) genes have been identified, playing a major role at the seedling stage. However, the effect of these interactions in the field under natural infection has not been investigated. In the present study, we saturated the genetic map of the recombinant inbred (RI) population SHA3/CBRD × Naxos using the Illumina 90 K SNP chip. The population had previously been evaluated for segregation of SNB susceptibility in field trials. Here, we infiltrated the population with the purified NEs SnToxA, SnTox1 and SnTox3, and mapped the Snn3 locus on 5BS based on sensitivity segregation and SNP marker data. We also conducted inoculation and culture filtrate (CF) infiltration experiments on the population with four selected P. nodorum isolates from Norway and North America. Remapping of quantitative trait loci (QTL) for field resistance showed that the SnTox3-Snn3 interaction could explain 24% of the phenotypic variation in the field, and more than 51% of the variation in seedling inoculations. To our knowledge, this is the first time the effect of this interaction has been documented at the adult plant stage under natural infection in the field.
S eptoria nodorum leaf blotch caused by the necrotrophic ascomycete Parastagonospora nodorum is a major disease in many wheat growing areas such as Australia, the United States, and Norway (
The wheat (Triticum aestivum L.) disease Septoria nodorum blotch (SNB) is caused by the necrotrophic fungus Parastagonospora nodorum (Berk.) Quaedvlieg, Verkley & Crous and causes significant yield and quality losses in several wheat growing regions. The resistance mechanisms are quantitative and progress in resistance breeding has been slow. However, gene‐for‐gene interactions involving necrotrophic effectors (NEs) and sensitivity genes (Snn) are involved, providing hope for more effective breeding. Although the interactions are significant determinants of seedling SNB susceptibility, their role in adult plant leaf blotch resistance in the field is less understood. In this study, the frequency of SnTox genes was investigated in 62 P. nodorum isolates collected in Norway. A panel of Norwegian and international spring wheat lines and cultivars was screened under natural SNB infection in a mist‐irrigated field nursery across 7 yr. The lines were infiltrated in the greenhouse with the purified NEs SnToxA, SnTox1, and SnTox3, and the prevalence of corresponding sensitivity was investigated, as well as correlation between NE sensitivity and resistance level in the field. The frequencies of SnToxA, SnTox1, and SnTox3 in the isolates were 0.69, 0.53 and 0.76, respectively. Sensitivity to SnToxA, SnTox1, and SnTox3 was present in 45, 12, and 55% of the plant material. Sensitivity to SnToxA was associated with significantly higher disease severity in the field than insensitivity. This indicates that elimination of SnToxA sensitivity in the breeding material by effector infiltrations or marker‐assisted selection can be an effective way to increase field resistance to SNB.
This study demonstrates that the spectral quality of radiation sources applied with ultraviolet-B (UV-B; background radiation) affects the suppression of cucumber powdery mildew (Podosphaera xanthii) by UV-B. Suppression provided by daily UV-B exposure of 1 W/m2 for 10 min was greatest in the presence of red light or by a complete lack of background light, and powdery mildew suppression was least in the presence of ultraviolet-A (UV-A) or blue radiation compared with plants exposed only to 16 h of daily natural light supplemented with high-pressure sodium lamps that supply broad-spectrum radiation with peaks in the yellow-orange region. Exposure of powdery mildew-inoculated plants to supplemental red light without UV-B, beginning at the end of the daylight period, also reduced disease severity; however, supplemental blue light applied in the same fashion had no effect. Daily application of UV-B at 1 W/m2 beginning on the day of inoculation significantly reduced the severity of powdery mildew to 15% compared with 100% severity on control plants. Maximum suppression of powdery mildew was observed following 15 min of exposure to UV-B (1.1% severity compared with 100% severity on control plants) but exposure time had to be limited to 5 to 10 min to reduce phytotoxicity. There was no additional disease suppression when plants were exposed to UV-B beginning 2 days prior to inoculation compared with plants exposed to UV-B beginning on the day of inoculation. UV-B inhibited germination, infection, colony expansion, and sporulation of P. xanthii. The results suggest that efficacy of UV-B treatments, alone or in combination with red light, against P. xanthii can be enhanced by exposure of inoculated plants to these wavelengths of radiation during the night, thereby circumventing the counteracting effects of blue light and UV-A radiation. The effect of UV-B on powdery mildew seemed to be directly upon the pathogen, rather than induced resistance of the host. Night exposure of plants to 5 to 10 min of UV-B at 1 W/m2 and inexpensive, spectral-specific, light-emitting diodes may provide additional tools to suppress powdery mildews of diverse greenhouse crops.
Septoria nodorum blotch (SNB) is an important disease affecting wheat in many of its production areas around the world, and is caused by the ascomycete fungal pathogen Parastagonospora nodorum. Breeding for SNB resistance has been hampered by the polygenic and quantitative nature of the resistance, and the farmers often have to rely on fungicides to control the disease. In recent years, substantial progress has been made in understanding the P. nodorum–wheat pathosystem. Several host-specific interactions between necrotrophic effectors (NEs) and host sensitivity (Snn) genes have been identified and play major roles in SNB seedling resistance. Some of the NEs have been cloned and can be used to screen breeding material at the seedling stage. This chapter provides an overview of the molecular understanding of host–pathogen interactions, progress in understanding the genetics of host resistance and use of molecular markers and effector screening as promising tools in resistance breeding for this challenging disease.
The growing demand for food and feed crops in the world because of growing population and more extreme weather events requires high-yielding and resilient crops. Many agriculturally important traits are polygenic, controlled by multiple regulatory layers, and with a strong interaction with the environment. In this study, 120 F 2 families of perennial ryegrass (Lolium perenne L.) were grown across a water gradient in a semifield facility with subsoil irrigation. Genomic (single-nucleotide polymorphism [SNP]), transcriptomic (gene expression [GE]), and DNA methylomic (MET) data were integrated with feed quality trait data collected from control and drought sections in the semifield facility, providing a treatment effect. Deep root length (DRL) below 110 cm was assessed with convolutional neural network image analysis. Bayesian prediction models were used to partition phenotypic variance into its components and evaluated the proportion of phenotypic variance in all traits captured by different regulatory layers (SNP, GE, and MET). The spatial effects and effects of SNP, GE, MET, the interaction between GE and MET (GE × MET) and GE × treatment (GE Control and GE Drought ) interaction were investigated. Gene expression explained a substantial part of the genetic and spatial variance for all the investigated phenotypes, whereas MET explained residual variance not accounted for by SNPs or GE. For DRL, MET also contributed to explaining spatial variance. The study provides a statistically elegant analytical paradigm that integrates genomic, transcriptomic, and MET information to understand the regulatory mechanisms of polygenic effects for complex traits.
Patterns and level of cytosine methylation vary widely among plant species and are associated with genome size as well as the proportion of transposons and other repetitive elements in the genome. We explored epigenetic patterns and diversity in a representative proportion of the spring barley (Hordeum vulgare L.) genome across several commercial and historical cultivars. This study adapted a genotyping‐by‐sequencing (GBS) approach for the detection of methylated cytosines in genomic DNA. To analyze the data, we developed WellMeth, a complete pipeline for analysis of reduced representation bisulfite sequencing. WellMeth enabled quantification of context‐specific DNA methylation at the single‐base resolution as well as identification of differentially methylated sites (DMCs) and regions (DMRs). On average, DNA methylation levels were significantly higher than what is commonly observed in many plants species, reaching over 10‐fold higher levels than those in Arabidopsis thaliana (L.) Heynh. in the CHH methylation. Preferential methylation was observed within and at the edges of long‐terminal repeats (LTR) retrotransposons Gypsy and Copia. From a pairwise comparison of cultivars, numerous DMRs could be identified of which more than 5,000 were conserved within the analyzed set of barley cultivars. The subset of regions overlapping with genes showed enrichment in gene ontology (GO) categories associated with chromatin and cellular structure and organization. A significant correlation between genetic and epigenetic distances suggests that a considerable portion of methylated regions is under strict genetic control in barley. The data presented herein represents the first step in efforts toward a better understanding of genome‐level structural and functional aspects of methylation in barley.
Whole-genome multi-omics profiles contain valuable information for the characterization and prediction of complex traits in plants. In this study, we evaluate multi-omics models to predict four complex traits in barley (Hordeum vulgare); grain yield, thousand kernel weight, protein content, and nitrogen uptake. Genomic, transcriptomic, and DNA methylation data were obtained from 75 spring barley lines tested in the RadiMax semi-field phenomics facility under control and water-scarce treatment. By integrating multi-omics data at genomic, transcriptomic, and DNA methylation regulatory levels, a higher proportion of phenotypic variance was explained (0.72–0.91) than with genomic models alone (0.55–0.86). The correlation between predictions and phenotypes varied from 0.17–0.28 for control plants and 0.23–0.37 for water-scarce plants, and the increase in accuracy was significant for nitrogen uptake and protein content compared to models using genomic information alone. Adding transcriptomic and DNA methylation information to the prediction models explained more of the phenotypic variance attributed to the environment in grain yield and nitrogen uptake. It furthermore explained more of the non-additive genetic effects for thousand kernel weight and protein content. Our results show the feasibility of multi-omics prediction for complex traits in barley.
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