Doctor of Philosophy / Department of Plant Pathology / Jan E. Leach / Because it is predicted to be durable and broad spectrum, quantitative trait loci (QTL)-based resistance is an important option for rice disease control. However, manipulation of this type of resistance requires knowledge of the contributing genes. This study demonstrates the contribution of two of three defense response (DR) genes to QTL-governed resistance, and identifies a third gene that negatively regulates resistance. The contribution to QTL-governed resistance of one of nine rice OsPAL genes, which encode phenylalanine ammonia-lyase, was determined using reverse genetics. Mutant ospal4 contains a 750 bp deletion in OsPAL4 and was identified using a PCR-pooling strategy. OsPAL4 underlies a QTL on chromosome 2, and is located in cluster with three other OsPAL members. Rice lines mutated in OsPAL4 are more susceptible to a virulent strain of Xanthomonas oryzae pv. oryzae (Xoo) than lines with the wild type allele. RNAi suppression was used to evaluate the contributions of genes encoding oxalate oxidase-like proteins (OsOXL) and a 14-3-3 protein (GF14-e) to disease resistance. Silencing of 12 OsOXL genes clustered on chromosome 8, varied from suppression of a few gene members to silencing of all expressed family members. Screening of transgenic lines by challenge with Magnaporthe grisea (Mg), the rice blast pathogen, revealed that the more chromosome 8 OsOXL genes suppressed, the more susceptible the plants were to Mg. GF14-e co-localizes with a disease resistance QTL on chromosome 2. Specific suppression of GF14-e by RNAi silencing did not result in enhanced susceptibility to Mg. Instead, the lines exhibited spontaneous HR-type lesions. The presence of this lesion mimic phenotype correlated with enhanced resistance to a virulent strain of Xoo, suggesting that the GF14-e encoded 14-3-3 protein functions as a negative regulator of plant cell death and bacterial resistance in rice. This study supports the hypothesis that DR genes, such as OsOXL and OsPAL4 contribute to disease resistance governed by QTL. The role of GF14-e is less clear, however its down regulation may contribute to QTL-governed resistance. Thus, incorporation of regions harboring the effective DR gene alleles into rice will enhance broad spectrum and durable resistance.

Doctor of Philosophy / Department of Plant Pathology / Barbara S. Valent / The hemibiotrophic rice blast fungus Magnaporthe oryzae undergoes complex morphological development throughout its infection cycle. From 8-20 hours after a fungal spore lands on a leaf surface, the fungus differentiates a complex appressorium that punctures the host cuticle. By ~24 hours post inoculation (hpi), the fungus grows inside an epidermal cell as a primary hypha, and by 36 hpi the fungus has differentiated specialized biotrophic invasive hyphae (IH) that are filling the first-invaded cell and moving into neighbor cells. Throughout its life cycle, IH invade living rice cells although invaded cells appear dead when the fungus moves into the next cell. Biotrophic invasion must be mediated by fungal effectors, proteins that pathogens secrete inside live host cells to control them. However, little is known about blast effectors, and the low fungal biomass in early infection stages complicates identification of effector genes, as well as identification of rice genes controlled by effectors. The characterized AVR-Pita effector gene is specifically expressed in planta, but it was not clear how its gene expression pattern changed in different infection stages. We found that AVR-Pita is first expressed around the time of penetration. AVR-Pita is highly expressed in IH developing in asymptomatic tissue from 36 hpi to as late as 7 days post inoculation when lesions are maturing. Using inoculated rice sheaths, we successfully enriched for infected tissue RNA that contained ~20% IH RNA at 36 hpi. We compared IH gene expression to expression in mycelium from pure culture using a whole-genome M. oryzae oligoarray, and we compared infected rice gene expression to expression in mock-inoculated tissue using a rice oligoarray. Rice genes that were induced >50-fold during infection were enriched for genes involved in transferring information from sensors to cellular responses. Fungal genes that were induced >50-fold in IH included known effectors and many IH-specific genes encoding hypothetical secreted proteins that are candidate effectors. Gene knock-out analyses of three putative effector genes failed to show major effects on pathogenicity. Details of the blast interaction transcriptome will provide insights on the mechanisms of biotrophic plant disease.

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Master of Science / Department of Electrical and Computer Engineering / Karen A. Garrett / Caterina M. Scoglio / With rapid global movement of epidemics, research efforts to characterize dynamics of epidemics have gained much focus. Traditional epidemiological models have focused on only temporal components of epidemics. Development of spatio-temporal models proved to be a notable achievement in epidemiology. Network-based epidemiological models enable better handling of spatial and temporal components of an epidemic. Early network models considered a binary level of contact between infected entities, which is an idealistic approach. A realistic approach would use weighted edges which signify the level of interaction between the nodes where the edge-weights change over time as a function of environmental factors. Estimation of edge weights from observed time series is a relatively less explored area for network modeling. Dynamic networks make the problem more complicated as edge weights change over time. Estimation of parameters for models describing the edge weights as a function of variables that change in time has the potential to provide better general models. Soybean rust (caused by Phakopsora pachyrhizi) is an important disease globally and its occurrence in the US has been studied extensively since its introduction in 2004. Rust is a fungal disease which propagates as a result of the fungal spores being carried by the wind. In this thesis, a network network based model is proposed to predict the intensity of spread of the disease in space and time. This model uses the host abundance and wind data and the observed rust incidence time series to compute the edge-weights. Also, the edge-weights in the model change over time thus following a dynamic approach. In order to cut costs involved with the establishment and maintenance of infection monitoring sites, the effect of removal of monitoring nodes using various strategies has also been analyzed in this thesis. The model has been tested with observed soybean rust data from sentinel plot network from across the United States.

Doctor of Philosophy / Department of Plant Pathology / John P. Fellers / Harold Trick / In Kansas, wheat (Triticum aestivum L.) is severely affected by the biotrophic fungus Puccinia triticina (leaf rust). Although resistant varieties have been developed, the fungus tends to overcome new sources resistance very quickly. Plants have evolved a single gene (R genes) defense network that can recognize specific pathogen effectors (Avr), in a gene-for-gene manor. In rusts, effectors are secreted proteins responsible for inducing the uptake of nutrients and inhibit host defense responses. Identification of secreted proteins during the infection may help to understand the mode of infection of P. triticina. Little is known about molecular interactions in the pathosystem wheat-leaf rust and no Avr genes from cereal rusts have been cloned. In order to understand pathogenicity in leaf rust and generate new alternatives for disease control, the goal of this research is identify P. triticina secreted proteins from a collection of expressed genes during the infection, and to characterize putative Avr function for three candidates. From 432 EST’s derived from haustoria and infected plants, fifteen secreted proteins were identified and 10 were selected as potential avirulence candidates. Pt3 and Pt 51 are two P. triticina (Pt) candidates expressed specifically in the haustoria and encode small cysteine-rich secreted proteins. Eight candidates are expressed at early stages of infection, during spore germination and 6 days after inoculation. They are small-secreted proteins. None are repetitive elements or have nuclear localization signals. They also do not share a conserved motif with known filamentous fungus Avr proteins. Five candidates are novel proteins, two have similarity with predicted proteins, one is homologous with Hesp-379-like protein, one is homologous with superoxide dismutase, and one has a cell glucanase predicted function. Pt3, Pt12 and Pt27 were tested by transient expression experiments using co-bombardment with GUS into leaf rust resistant isogenic lines. Reduction in the expression of reporter gene GUS co-expressed with Pt27 indicates a potential avirulence factor for Lr26 in wheat.

Master of Science / Department of Plant Pathology / Bernd Friebe / Bikram S. Gill / Common, bread, or hexaploid wheat, Triticum aestivum L. (2n=6x=42, AABBDD), has several relatives in the Triticum/Aegilops complex of the Poaceae family in the Triticeae tribe, which are valuable sources for broadening genetic diversity and may provide genes for disease and pest resistance and general wheat improvement. Other wild relatives of wheat also may be exploited for wheat improvement, such as Haynaldia villosa (L.) Schur. (2n=2x=14, VV). It is a diploid species with resistance to powdery mildew, wheat curl mite colonization, cereal eyespot disease, rust diseases, and wheat spindle streak mosaic virus. H. villosa may harbor many other as yet unidentified traits for wheat improvement. The polyploid nature of bread wheat allows tolerance to genomic changes, because homoeologous chromosomes from other genomes compensate for missing wheat chromosomes. In this experiment, we crossed the disomic alien addition line DA4V (2n=6x=44) with a pair of H. villosa chromosomes added to the wheat chromosome complement with wheat monosomic for chromosome 4D (2n=41) to produce 4D/4V double monosomic plants. According to centric breakage-fusion mechanisms, univalents tend to break at their centromeres at meiotic metaphase I producing telocentric chromosomes with unstable or “sticky” ends that can fuse with the sticky ends of other newly formed telocentric chromosomes. This fusion results in Robertsonian whole-arm translocations that may be compensating if a short arm of one chromosome fuses with a long arm of another. Double monosomic plants were screened cytogenetically and further visualized by genomic in situ hybridization (GISH). Five transfers were identified, including T4DS.4VL and T4VS.4DL translocations, and a T4VS-W.W transfer of unknown wheat origin. These results were confirmed by GISH. The T4DS.4VL and T4VS.4DL translocations are genetically compensating and should be exploited in wheat improvement.

Master of Science / Department of Plant Pathology / Erick D. DeWolf / Stripe rust, caused by Puccinia striiformis f. sp. tritici, historically has been a minor problem in the Great Plains. However, Kansas had significant losses due to stripe rust in 2001, 2003, and 2005. Recent research on the population of P. striiformis suggests changes in the fungal population may have been responsible for these epidemics. The objectives of this research were to determine conditions that are favorable for the infection of P. striiformis f. sp. tritici isolates from the current population and develop models to predict infection events. Two week old potted seedlings were inoculated with an isolate of P. striiformis and exposed to ambient weather conditions for 16 hours. Results of this bioassay were used to develop logistic regression models of infection. Models using hours at relative humidity >87%, leaf wetness, and mean relative humidity predicted infection with 93%, 80%, and 76% accuracy. Future research will use these results to determine weather patterns that influence the probability of stripe rust epidemics and to facilitate the development of regional prediction models for stripe rust. Foliar diseases of wheat result in an average yield loss of 7.8% in Kansas. Although it is possible to reduce these losses with foliar fungicides, the yield increases resulting from these applications may not justify the additional costs. The objective of this research was to develop models that help producers identify factors associated with disease-related yield loss and the profitable use of foliar fungicides. Data were collected for two years at three locations in central Kansas to determine yield response to fungicide application on eight varieties with varying degrees of resistance. Logistic regression was used to model the probability of a yield response >4 bushels per acre based on disease resistance of a variety, historical disease risk, and in-season disease risk. The accuracy of the resulting prediction models ranged from 84% to 71%. A model combining in-season disease risk and variety resistance was most accurate. The prediction accuracy of the model was 79% when tested with an independent validation dataset. In the future, these models will serve as educational tools to help producers maximize profit and productivity.

Doctor of Philosophy / Department of Plant Pathology / Karen A. Garrett / Late blight of potato, caused by Phytophthora infestans, is a pernicious disease of potatoes worldwide. This disease causes yield losses as a result of foliar and tuber damage. Many models exist to predict late blight risk for control purposes with-in season but rely upon fine-scale weather data collected in hourly, or finer, increments. This is a major constraint when working with disease prediction models for areas of the world where hourly weather data is not available or is unreliable. Weather or climate summary datasets are often available as monthly summaries. These provide a partial solution to this problem with global data at large time-steps (e.g., monthly). Difficulties arise when attempting to use these forms of data in small temporal scale models. My first objective was to develop new approaches for application of disease forecast models to coarser resolution weather data sets. I created metamodels based on daily and monthly weather values which adapt an existing potato late blight model for use with these coarser forms of data using generalized additive models. The daily and monthly weather metamodels have R-squared values of 0.62 and 0.78 respectively. These new models were used to map global late blight risk under current and climate change scenarios resistant and susceptible varieties. Changes in global disease risk for locations where wild potato species are indigenous, and disease risk for countries where chronic malnutrition is a problem were evaluated. Under the climate change scenario selected for use, A1B, future global late blight severity decreases. The risk patterns do not show major changes, areas of high risk remain high relative to areas of low risk with rather slight increases or decreases relative to previous years. Areas of higher wild potato species richness experience slightly increased blight risk, while areas of lower species richness experience a slight decline in risk.

Doctor of Philosophy / Department of Plant Pathology / Frank F. White / Plants have evolved sophisticated mechanisms to protect against microbial invaders of which resistance (R) genes are an important component. R genes mediate specific recognition of pathogens possessing cognate avirulence (avr) gene products, which leads to the induction of plant defense responses and the arrest of pathogen ingress. In contrast to numerous examples of R gene–avr interactions, the susceptible interaction is less well examined. Recent studies on rice and wheat indicate that host resistance to pathogens also involves genetic variability in dominant traits for susceptibility. Xanthomonas oryzae pv.oryzae (Xoo) causes bacterial blight disease in rice, a serious threat in the major rice growing regions of Asia. The pathogenicity of Xoo depends on the translocation of a cocktail of effector proteins into rice cells by a type III secretion system. The family of transcription activator like (TAL) effectors is the one of the most intriguing due to their eukaryotic features and function as major virulence determinants. The specificity of TAL effectors is determined by the nearly identical repeat units at the center of each protein. The major virulence determinant of the strain PXO99A is PthXo1, which hijacks the transcription of the host susceptibility (S) gene Os8N3, an allele of recessive resistance gene xa13. The strains that overcome xa13-mediated resistance harbor alternate major TAL effectors including PthXo2, PthXo3 and AvrXa7. Alternate effectors do not induce Os8N3. This study identified the alternate S gene Os11N3, which is dependent on the effectors AvrXa7 and PthXo3. The effectors bind to specific elements in the proximal promoter regions of the respective S genes and act as transcriptional activators. Our results indicate that rice–Xoo interactions involve gene-for-gene susceptibility to bacterial blight in addition to gene-for-gene resistance.