Genome-wide association analysis permits characterization of Stagonospora nodorum blotch (SNB) resistance in hard winter wheat

Stagonospora nodorum blotch (SNB) is an economically important wheat disease caused by the necrotrophic fungus Parastagonospora nodorum. SNB resistance in wheat is controlled by several quantitative trait loci (QTLs). Thus, identifying novel resistance/susceptibility QTLs is crucial for continuous improvement of the SNB resistance. Here, the hard winter wheat association mapping panel (HWWAMP) comprising accessions from breeding programs in the Great Plains region of the US, was evaluated for SNB resistance and necrotrophic effectors (NEs) sensitivity at the seedling stage. A genome-wide association study (GWAS) was performed to identify single‐nucleotide polymorphism (SNP) markers associated with SNB resistance and effectors sensitivity. We found seven significant associations for SNB resistance/susceptibility distributed over chromosomes 1B, 2AL, 2DS, 4AL, 5BL, 6BS, and 7AL. Two new QTLs for SNB resistance/susceptibility at the seedling stage were identified on chromosomes 6BS and 7AL, whereas five QTLs previously reported in diverse germplasms were validated. Allele stacking analysis at seven QTLs explained the additive and complex nature of SNB resistance. We identified accessions (‘Pioneer-2180’ and ‘Shocker’) with favorable alleles at five of the seven identified loci, exhibiting a high level of resistance against SNB. Further, GWAS for sensitivity to NEs uncovered significant associations for SnToxA and SnTox3, co-locating with previously identified host sensitivity genes (Tsn1 and Snn3). Candidate region analysis for SNB resistance revealed 35 genes of putative interest with plant defense response-related functions. The QTLs identified and validated in this study could be easily employed in breeding programs using the associated markers to enhance the SNB resistance in hard winter wheat.

Yield increases due to fungicide control of leaf blotch diseases in wheat and barley as a basis for IPM decision-making in the Nordic-Baltic region

Fungal plant diseases driven by weather factors are common in European wheat and barley crops. Among these, septoria tritici blotch (Zymoseptoria tritici), tan spot (Pyrenophora tritici-repentis), and stagonospora nodorum blotch (Parastagonospora nodorum) are common in the Nordic-Baltic region at variable incidence and severity both in spring and winter wheat fields. In spring barley, net blotch (Pyrenophora teres), scald (Rhynchosporium graminicola, syn. Rhynchosporium commune) and ramularia leaf spot (Ramularia collo-cygni) are common yield limiting foliar diseases. We analysed data from 449 field trials from 2007 to 2017 in wheat and barley crops in the Nordic-Baltic region and explored the differences in severity of leaf blotch diseases between countries and years, and the impact of the diseases on yield. In the experiments, septoria tritici blotch dominated in winter wheat in Denmark and southern Sweden; while in Lithuania, both septoria tritici blotch and tan spot were common. In spring wheat, stagonospora nodorum blotch dominated in Norway and tan spot in Finland. Net blotch and ramularia leaf blotch were the most severe barley diseases over large areas, while scald occurred more locally and had less yield impact in all countries. Leaf blotch diseases, with severity >50% at DC 73–77, caused an average yield loss of 1072 kg/ha in winter wheat and 1114 kg/ha in spring barley across all countries over 5 years. These data verify a large regional and yearly variation in disease severity, distribution and impact on yield, emphasizing the need to adapt fungicide applications to the actual need based on locally adapted risk assessment systems.

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.

A Model for Predicting Onset of Stagonospora nodorum Blotch in Winter Wheat Based on Preplanting and Weather Factors

Stagonospora nodorum blotch (SNB) caused by Parastagonospora nodorum is a serious disease of wheat worldwide. In the United States, the disease is prevalent on winter wheat in many eastern states, and its management relies mainly on fungicide application after flag leaf emergence. Although SNB can occur prior to flag leaf emergence, the relationship between the time of disease onset and yield has not been determined. Such a relationship is useful in identifying a threshold to facilitate prediction of disease onset in the field. Disease occurred in 390 of 435 disease cases that were recorded across 11 counties in North Carolina from 2012 to 2014. Using cases with disease occurrence, the effect of disease onset on yield was analyzed to identify a disease onset threshold that related time of disease onset to yield. Regression analysis showed that disease onset explained 32% of the variation in yield (P < 0.0001) and from this relationship, day of year (DOY) 102 was identified as the disease onset threshold. Below-average yield occurred in 87% of the disease cases when disease onset occurred before DOY 102 but in only 28% of those cases when onset occurred on or after DOY 102. Subsequently, binary logistic regression models were developed to predict the occurrence and onset of SNB using preplanting factors and cumulative daily infection values (cDIV) starting 1 to 3 weeks prior to DOY 102. Logistic regression showed that previous crop, latitude, and cDIV accumulated 2 weeks prior to DOY 102 (cDIV.2) were significant (P < 0.0001) predictors of disease occurrence, and wheat residue, latitude, longitude, and cDIV.2 were significant (P < 0.0001) predictors of disease onset. The disease onset model had a correct classification rate of 0.94 and specificity and sensitivity rates >0.90. Performance of the disease onset model based on the area under the receiver operating characteristic curve (AUC), κ, and the true skill statistic (TSS) was excellent, with prediction accuracy values >0.88. Similarly, internal validation of the disease onset model based on AUC, κ, and TSS indicated good performance, with accuracy values >0.88. This disease onset prediction model could serve as a useful decision support tool to guide fungicide applications to manage SNB in wheat.