Sclerotinia stem rot is an economically important disease of canola (Brassica napus) and is caused by the fungal pathogen Sclerotinia sclerotiorum. This study evaluated the differential gene expression patterns of S. sclerotiorum during disease development on two canola lines differing in susceptibility to this pathogen. Sequencing of the mRNA libraries derived from inoculated petioles and mycelium grown on liquid medium generated approximately 164 million Illumina reads, including 95 million 75-bp-single reads, and 69 million 50-bp-paired end reads. Overall, 36% of the quality filter-passed reads were mapped to the S. sclerotiorum reference genome. On the susceptible line, 1301 and 1214 S. sclerotiorum genes were differentially expressed at early (8-16 hours post inoculation (hpi)) and late (24-48 hpi) infection stages, respectively, while on the resistant line, 1311 and 1335 genes were differentially expressed at these stages, respectively. Gene ontology (GO) categories associated with cell wall degradation, detoxification of host metabolites, peroxisome related activities like fatty acid ß-oxidation, glyoxylate cycle, oxidoreductase activity were significantly enriched in the up-regulated gene sets on both susceptible and resistant lines. Quantitative RT-PCR of six selected DEGs further validated the RNA-seq differential gene expression analysis. The regulation of effector genes involved in host defense suppression or evasion during the early infection stage, and the expression of effectors involved in host cell death in the late stage of infection provide supporting evidence for a two-phase infection model involving a brief biotrophic phase during early stages of infection. The findings from this study emphasize the role of peroxisome related pathways along with cell wall degradation and detoxification of host metabolites as the key mechanisms underlying pathogenesis of S. sclerotiorum on B. napus.

Diseases caused by the fungus Sclerotinia sclerotiorum are managed mainly through fungicide applications in canola and dry bean. Accurate estimation of the risk of disease development on these crops could help farmers make spraying decisions. Five machine learning (ML) models were evaluated in classification and regression modes for predicting disease establishment under different air temperatures and leaf wetness duration conditions. Model algorithms were trained and tested using 20-fold cross validation. Correspondence between predicted and observed values were measured using Cohen’s Kappa (classification) and Lin’s concordance coefficients (regression). The artificial neural network (ANN) algorithms had average accuracies ≥ 89% (classification) and R2 ≥ 88% (regression) on canola and dry bean and their correspondence agreements were ≥ 0.83, which is considered substantial to almost perfect. In contrast, logistic regression algorithms had accuracies of 88% for dry bean and 78% for canola; other models were similarly inconsistent. Implementation of ANN models in disease warning systems could help farmers with spraying decisions. At the same time, these models provide insights on temperature and leaf wetness requirements for development of S. sclerotiorum diseases in these crops. Results of this study show the potential of ML models as tools for epidemiological studies on other pathosystems.

Bolton, M. D., Rivera-Varas, V., del Rio Mendoza, L. E., Khan, M. F. R., and Secor, G. A. 2012. Efficacy of variable tetraconazole rates against Cercospora beticola isolates with differing in vitro sensitivities to DMI fungicides. Plant Dis. 96:1749-1756.Cercospora leaf spot (CLS) of sugar beet is caused by the fungus Cercospora beticola. CLS management practices include the application of the sterol demethylation inhibitor (DMI) fungicides tetraconazole, difenoconazole, and prothioconazole. Evaluating resistance to DMIs is a major focus for CLS fungicide resistance management. Isolates were collected in 1997 and 1998 (baseline sensitivity to tetraconazole, prothioconazole, or difenoconazole) and 2007 through 2010 from the major sugar-beet-growing regions of Minnesota and North Dakota and assessed for in vitro sensitivity to two or three DMI fungicides. Most (47%) isolates collected in 1997-98 exhibited 50% effective concentration (EC50) values for tetraconazole of <0.01 (Jg ml"', whereas no isolates could be found in this EC50 range in 2010. Since 2007, annual median and mean tetraconazole EC50 values have generally been increasing, and the frequency of isolates with EC50 values >0.11 lig ml-' increased from 2008 to 2010. In contrast, the frequency of isolates with EC50 values for prothioconazole of >1.0 ng mh' has been decreasing since 2007. Annual median difenoconazole EC50 values appears to be stable, although annual mean EC50 values generally have been increasing for this fungicide. Although EC50 values are important for gauging fungicide sensitivity trends, a rigorous comparison of the relationship between in vitro EC50 values and loss of fungicide efficacy in planta has not been conducted for C. beticola. To explore this, 12 isolates exhibiting a wide range of tetraconazole EC50 values were inoculated to sugar beet but no tetraconazole was applied. No relationship was found between isolate EC50 value and disease severity. To assess whether EC50 values are related to fungicide efficacy in planta, sugar beet plants were sprayed with various dilutions of Eminent, the commercial formulation of tetraconazole, and subsequently inoculated with isolates that exhibited very low, medium, or high tetraconazole EC50 values. The high EC50 isolate caused significantly more disease than isolates with medium or very low EC50 values at the field application rate and most reduced rates. Because in vitro sensitivity testing is typically carried out with the active ingredient of the commercial fungicide, we investigated whether loss of disease control was the same for tetraconazole as for the commercial product Eminent. The high EC50 isolate caused more disease on plants treated with tetraconazole than Eminent but disease severity was not different between plants inoculated with the very low EC50 isolate.Cercospora leaf spot (CLS), caused by the fungus Cercospora beticola (Sacc), is the most important foliar disease of sugar beet {Beta vulgaris L.) in North Dakota and Minnesota (39). The disease causes a reduction in root har...

The polyploid nature of canola (Brassica napus) represents a challenge for the accurate identification of single nucleotide polymorphisms (SNPs) and the detection of quantitative trait loci (QTL). In this study, combinations of eight phenotyping scoring systems and six SNP calling and filtering parameters were evaluated for their efficiency in detection of QTL associated with response to Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, in two doubled haploid (DH) canola mapping populations. Most QTL were detected in lesion length, relative areas under the disease progress curve (rAUDPC) for lesion length, and binomial-plant mortality data sets. Binomial data derived from lesion size were less efficient in QTL detection. Inclusion of additional phenotypic sets to the analysis increased the numbers of significant QTL by 2.3-fold; however, the continuous data sets were more efficient. Between two filtering parameters used to analyze genotyping by sequencing (GBS) data, imputation of missing data increased QTL detection in one population with a high level of missing data but not in the other. Inclusion of segregation-distorted SNPs increased QTL detection but did not impact their R2 values significantly. Twelve of the 16 detected QTL were on chromosomes A02 and C01, and the rest were on A07, A09, and C03. Marker A02-7594120, associated with a QTL on chromosome A02 was detected in both populations. Results of this study suggest the impact of genotypic variant calling and filtering parameters may be population dependent while deriving additional phenotyping scoring systems such as rAUDPC datasets and mortality binary may improve QTL detection efficiency.

North Dakota leads the United States in canola (Brassica napus L.) production (4). A canola field with a distinct patch of dead plants spreading over an area of approximately 0.4 ha was detected in Cavalier County, North Dakota, in early September 2013. Numerous spots within the patch had plant mortalities >80%. Dead plants pulled from the soil had roots with severe galling and clubbing. Clubbed roots were brittle and disintegrated easily when pressed between fingers. Root and soil samples collected at several locations within and outside the affected patch were pooled in separate groups. All plants collected in the patch were symptomatic but those collected outside were not. In the lab, total genomic DNA from three symptomatic and two healthy root samples was extracted using standard procedures and freehand slices were prepared for observation with a compound microscope. Also, DNA from pooled soil samples was extracted using FastDNA Spin Kit for Soil (MP Biomedicals, Solon, OH). Round resting structures ranging from 2.2 to 4.2 μm in diameter were observed by microscopic examination of symptomatic root tissues. These structures resembled those typically produced by Plasmodiophora brassicae Woronin. This initial identification was later confirmed through PCR analysis using the species specific primers TC1F/R and TC2F/R (1). PCR products of 548 bp (TC1F/R) and 519 bp (TC2F/R) were produced in the three symptomatic and two infested soil samples, confirming the presence of P. brassicae. PCR amplicons were not detected in healthy root and soil samples. Pathogenicity tests were conducted in greenhouse to fulfill Koch's postulates. Briefly, five square plastic pots (10 × 10 × 13 cm) were filled with a 10-cm layer of Sunshine Mix #1 potting mix (Fison Horticulture, Vancouver, BC, Canada) and then 1 g of ground root galls (approximately 5 × 105 resting spores) was spread evenly on its surface and covered with 2 cm of soilless mix. A similar number of pots were filled only with soilless mix and used as controls. All pots were planted with two seeds of canola cv. Westar and incubated in greenhouse conditions at 21°C and 16 h light daily. The experiment was conducted twice. Four weeks after planting, all plants in the inoculated pots had developed galls while plants in control pots were symptomless. Presence of P. brassicae resting spores in the newly developed galls was confirmed by microscopic observations and PCR. Based on the symptoms, morphology of resting spores, PCR reactions, and pathogenicity tests, we confirm the presence of P. brassicae on canola. While P. brassicae has been reported as widespread in North America (2), to our knowledge, this is the first report of clubroot on canola in North Dakota and the United States. Clubroot became the most important disease affecting canola production in central Alberta, Canada, within 5 years of its discovery in 2003 (3); since then, the disease has been detected in Saskatchewan and Manitoba (3), Canadian provinces that share borders with North Dakota. Considering the difficulties in management of clubroot, measures should be initiated to limit the spread of the disease before it could pose a threat to United States canola production. References: (1) T. Cao et al. Plant Dis. 91:80, 2007. (2) G. Dixon J. Plant Growth Regul. 28:194, 2009. (3) S. Strelkov and S. Hwang. Can. J. Plant Pathol. 36(S1):27, 2014. (4) USDA-NASS, Ag. Statistics No. 81, 2012.