Evaluation of Stagonospora Nodorum Blotch Severity and Parastagonospora nodorum Population Structure and Genetic Diversity Across Multiple Locations and Wheat Varieties in Virginia

Parastagonospora nodorum is a necrotrophic pathogen that causes Stagonospora nodorum blotch (SNB) in wheat. Wheat varieties grown in Virginia vary in susceptibility to SNB, and the severity of SNB varies across locations and years. However, the impacts of wheat genetic backgrounds and environments on SNB severity and the structure of P. nodorum populations in the region have not been well studied. Thus, a population genetic study was conducted utilizing P. nodorum isolates collected from different wheat varieties and locations in Virginia. A total of 320 isolates were collected at seven locations over 2 years from five wheat varieties. Isolates were genotyped using multilocus simple sequence repeat markers, and necrotrophic effector (NE) and mating type genes were amplified using gene-specific primers. Wheat varieties varied in susceptibility to SNB, but site-specific environmental conditions were the primary drivers of disease severity. Fungal populations were genetically diverse, but no genetic subdivision was observed among locations or varieties. The ratio of the two mating type idiomorphs was not significantly different from 1:1, consistent with the P. nodorum population undergoing sexual reproduction. Three major NE genes were detected within the P. nodorum population, but not with equal frequency. However, NE gene profiles were similar for groups of isolates originating from different varieties, suggesting that wheat genetic backgrounds do not differentially select for NEs. There was no evidence of population structure among P. nodorum populations in Virginia and, thus, no support for wheat genetic backgrounds shaping these populations. Finally, although varieties only exhibited moderate resistance to SNB, current levels of resistance are likely to be durable over time and remain a useful tool for integrated management of SNB in the region. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Occurrence of Quinone Outside Inhibitor Resistance in Virginia Populations of Parastagonospora nodorum Infecting Wheat

Stagonospora nodorum blotch (SNB) of wheat, caused by Parastagonospora nodorum, is managed using cultural practices, resistant varieties, and foliar fungicides. Frequent fungicide use can select for fungicide resistance, making certain chemistries less effective; this may in part explain the increasing severity of SNB in the mid-Atlantic United States. Quinone outside inhibitor (QoI) resistance has been documented for a diversity of fungi, but it has not been reported for P. nodorum in the United States. The objectives of this study were (i) to evaluate QoI sensitivity of P. nodorum from Virginia wheat fields, (ii) to screen P. nodorum for QoI target site mutations in the cytochrome b gene, and (iii) to develop a molecular assay to detect target site mutations associated with QoI resistance. Sensitivity of 16 isolates to pyraclostrobin and azoxystrobin was evaluated with radial growth assays, and the cytochrome b gene was sequenced. One isolate was insensitive to both fungicides and had the G143A mutation in the cytochrome b gene. For azoxystrobin, 10 isolates without target site mutations had reduced sensitivity. Additional isolates (n = 58) were sequenced. A total of seven isolates had the G143A mutation and also had reduced sensitivity to pyraclostrobin and azoxystrobin compared with a sensitive control isolate without the mutation. A pyrosequencing assay targeting G143A was developed as a rapid method to screen P. nodorum for the QoI resistance-conferring mutation. To our knowledge, this is the first report of QoI-resistant P. nodorum in the United States. Overall resistance frequency was low, but resistance management practices are needed to maintain the efficacy of fungicides for SNB control.

Mining and genomic characterization of resistance to tan spot, Stagonospora nodorum blotch (SNB), and Fusarium head blight in Watkins core collection of wheat landraces

BACKGROUND

In the late 1920s, A. E. Watkins collected about 7000 landrace cultivars (LCs) of bread wheat (Triticum aestivum L.) from 32 different countries around the world. Among which 826 LCs remain viable and could be a valuable source of superior/favorable alleles to enhance disease resistance in wheat. In the present study, a core set of 121 LCs, which captures the majority of the genetic diversity of Watkins collection, was evaluated for identifying novel sources of resistance against tan spot, Stagonospora nodorum blotch (SNB), and Fusarium Head Blight (FHB).

RESULTS

A diverse response was observed in 121 LCs for all three diseases. The majority of LCs were moderately susceptible to susceptible to tan spot Ptr race 1 (84%) and FHB (96%) whereas a large number of LCs were resistant or moderately resistant against tan spot Ptr race 5 (95%) and SNB (54%). Thirteen LCs were identified in this study could be a valuable source for multiple resistance to tan spot Ptr races 1 and 5, and SNB, and another five LCs could be a potential source for FHB resistance. GWAS analysis was carried out using disease phenotyping score and 8807 SNPs data of 118 LCs, which identified 30 significant marker-trait associations (MTAs) with -log10 (p-value) > 3.0. Ten, five, and five genomic regions were found to be associated with resistance to tan spot Ptr race 1, race 5, and SNB, respectively in this study. In addition to Tsn1, several novel genomic regions Q.Ts1.sdsu-4BS and Q.Ts1.sdsu-5BS (tan spot Ptr race 1) and Q.Ts5.sdsu-1BL, Q.Ts5.sdsu-2DL, Q.Ts5.sdsu-3AL, and Q.Ts5.sdsu-6BL (tan spot Ptr race 5) were also identified. Our results indicate that these putative genomic regions contain several genes that play an important role in plant defense mechanisms.

CONCLUSION

Our results suggest the existence of valuable resistant alleles against leaf spot diseases in Watkins LCs. The single-nucleotide polymorphism (SNP) markers linked to the quantitative trait loci (QTLs) for tan spot and SNB resistance along with LCs harboring multiple disease resistance could be useful for future wheat breeding.

High-density SNP mapping reveals closely linked QTL for resistance to Stagonospora nodorum blotch (SNB) in flag leaf and glume of hexaploid wheat

The genetic control of adult plant resistance to Stagonospora nodorum blotch (SNB) is complex, consisting of genes with minor effects interacting in an additive manner. Earlier studies detected quantitative trait loci (QTL) for flag leaf resistance in successive years on chromosomes 1B, 2A, 2D, and 5B using SSR- and DArT-based genetic maps of progeny from the crosses EGA Blanco/Millewa, 6HRWSN125/WAWHT2074, and P92201D5/P91193D1. Similarly, QTL for glume resistance detected in successive years and multiple environments were identified on chromosomes 2D and 4B from genetic maps of P92201D5/P91193D1 and 6HRWSN125/WAWHT2074, respectively. The SSR- and DArT-based genetic maps had an average distance of 6.5, 7.8, and 9.7 cM between marker loci for populations EGA/Millewa, P92201D5/P91193D1, and 6HRWSN125/WAWHT2074, respectively. This study used single nucleotide polymorphism (SNP) markers from the iSelect Infinium 90K genotyping array to fine-map genomic regions harbouring QTL for flag leaf and glume SNB resistance, reducing the average distance between markers to 2.9, 3.3, and 3.4 cM for populations P92201D5/P91193D1, EGA/Millewa, and 6HRWSN125/WAWHT2074, respectively. Increasing the marker density of the genetic maps with SNPs did not identify any new QTL for SNB resistance but discriminated previously identified co-located QTL into separate but closely linked QTL.

Mutations in the CYP51 gene reduce DMI sensitivity in Parastagonospora nodorum populations in Europe and China

BACKGROUND

Sterol demethylation inhibitors (DMIs) have been widely used to manage agronomically important fungal diseases in wheat, but reports of DMI-resistant pathogens continue to mount. Parastagonospora nodorum shows a wide range of sensitivity to DMIs, but until now no molecular mechanisms have been identified to explain these differences. The aim of this study was to correlate the DMI sensitivity of a global collection of P. nodorum isolates with mutations in the CYP51 gene that encodes the target of DMI fungicides.

RESULTS

Two non-synonymous mutations connected to DMI resistance in other plant pathogenic fungi were detected for the first time in the CYP51 gene of P. nodorum. The two mutations occurred at amino acid position 144, which is homologous to position 137 in other pathogens. The Y144F mutation was detected in China, Denmark, Sweden and Switzerland while the Y144H mutation was found in China and Switzerland. Both mutations were correlated with significantly reduced sensitivity to the DMI fungicide propiconazole.

CONCLUSION

CYP51 mutations conferred reduced sensitivity against DMIs in field populations of P. nodorum originating from China, Denmark, Sweden and Switzerland. © 2016 Society of Chemical Industry.

Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models

Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR) and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF), in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors) collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early assessment of the risk of SNB, facilitating sound disease management decisions prior to planting of wheat.

Relationship between leaf stages and epistasis for resistance to Stagonospora nodorum in durum wheat

Ten varieties and eight generations (2F1, 2F2, 2B1 and 2B2) of durum wheat derived from two crosses were evaluated for resistance to natural infection by Stagonospora nodorum blotch (SNB) at the 2-3 and 6-7 leaf stages at two sites over two years. There were significant differences in the incidence of SNB between leaf stages in most of the wheat varieties, with resistance being most evident at the 6-7 leaf stage. Separate analyses of the mean values for each generation showed that the genetic mechanism of defense against the pathogen depended upon the leaf stage. At the 2-3 leaf stage, only additive and dominance effects were implicated in the control of SNB for the two crosses at the two sites and for the two replications. For the 6-7 leaf stage, inheritance was more complicated and an epistatic effect was involved. Narrow-sense heritability values (range: 0.63-0.67) were consistent between crosses and leaf stages. These findings indicate a lack of resistance to SNB at the 2-3 leaf stage whereas resistance was observed at the 6-7 leaf stage and involved the genetic mechanisms of plant defense such as epistasis.