Rice blast disease is caused by the filamentous fungus Magnaporthe oryzae and is the most destructive disease of cultivated rice. It was the first plant pathogenic fungus to have its genome sequence published which opened up the opportunities to discern the principal genetic components that confer pathogenicity on the fungus. The availability of the genome sequence has also presented fresh challenges in terms of converting sequence data into meaningful biological information. Functional genomics studies involve the generation of genome-wide mutant collections and comprehensive screens with potential to identify novel pathogenicity determinants. In this study I utilized Agrobacterium tumefaciens mediated random insertional mutagenesis to study the infection mechanism of M. oryzae. A collection 10,200 M. oryzae T-DNA insertion mutants were generated as part of this study and pathogenicity was assayed by high-throughput disease screening. From the primary qualitative screening I obtained 200 mutants that were reduced or lacking in pathogenicity. Quantitative re-screening allowed selection of 71 T-DNA mutants, including 9 non-pathogenic and 63 reduced virulence mutants exhibiting at least a 50% reduction in disease symptoms. Finally, we selected 8 non-pathogenic mutants for detailed phenotypic and gene functional analysis. A novel approach was used to retrieve T-DNA tagged genes from mutants of interest. Next generation DNA sequencing (NGS) was used to retrieve T-DNA flanking sequences in a high-throughput manner. The efficiency of NGS to facilitate the high-throughput large scale insertional mutagenesis was therefore demonstrated. Out of 8 selected mutants, I identified three novel genes that putatively encode a transcription factor, a PH domain containing signalling protein and a MAP kinase. I also provided evidence that, MGG_05343 is a functional C6 zinc finger transcription factor involved in conidiogenesis. The PH domain containing protein MGG_12956 is involved in vegetative growth, condiogenesis and virulence. The novel kinase MGG_15325 is a S. cerevisiae IME2 homolog that belongs to the Ime2 class of non-classical MAP kinase subfamily. Intriguingly, M. oryzae IME2 seems to have an essential role in growth in planta because the mutant was able to penetrate and colonize plant tissue but failed to cause necrotic rice blast lesions. Identification of these novel genes will allow us greater insight into the processes required for condiogenesis, vegetative and invasive growth and a more integrated understanding of the post-penetration phases of plant tissue colonization. Interestingly, I identified two mutants tagged with T-DNA insertion in the autophagy genes ATG2 and ATG3, reaffirming the importance of infection-associated autophagy in plant infection by M. oryzae and we characterized the ATG3 gene. In addition, I generated a resource of 63 unidentified T-DNA mutants which can potentially lead to identification of more novel determinants of pathogenicity in rice blast disease.

Statistical analyses were used to develop predictive models of rice blast and to relate the favorability of environment to disease incidence and severity on different rice cultivars at five sites in Asia. The WINDOW PANE program was used to search for weather factors highly correlated with blast. Stepwise and r-square linear regression procedures were then applied to generate the predictive models at each site. Models developed at Icheon, South Korea included relative humidity and rainfall factors as the most important predictors of disease. Temperature, rainfall, wind speed, and relative humidity factors were components of models at Cavinti and the IRRI blast nursery in the Philippines. Rainfall, temperature, and solar radiation factors were important at Gunung Medan and Sitiung, Indonesia. Model validation was done to verify accuracy of models for predictions. Model predictions were also used to determine the effects on blast of sowing time, nitrogen amount, and increase in temperature. Limitations of the models are discussed. Path coefficient analysis was used to identify direct and indirect influences exerted by weather factors on blast. The largest direct influence on disease was exerted by humidity factors at Icheon; temperature, rainfall, and wind speed factors at Cavinti; temperature and humidity factors at IRRI; rainfall factors at Gunung Medan; and temperature factors at Sitiung. Although path coefficient values (Py) were estimated from the decomposition of correlation coefficients, factors that had a high correlation with disease parameters did not always give high Py. Multivariate analysis was used to determine the effects of sowing times on proneness of tropical rice to blast. Cluster analysis of 24 hypothetical sowing months at Cavinti, the IRRI blast nursery, and Sitiung sites revealed three blast proneness groups. Principal component analysis showed that IR50 cultivar would be susceptible at Cavinti at any time of the year. Sowing C22 cultivar at Cavinti in Group I and III months would make it prone to panicle and leaf blast, respectively. At the IRRI blast nursery, leaf and panicle infections on IR50 would be probable only in Group I and II months. This trend was also observed for C22 at Sitiung, although some months in Group III at this site had moderate to high degree of proneness to leaf blast. / Graduation date: 1994

Thesis (Ph. D.)--University of Wisconsin--Madison, 1984. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographies.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 91-101).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 62-71).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 78-88).

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京都大学 / 新制・課程博士 / 博士(農学) / 甲第24680号 / 農博第2563号 / 新制||農||1100(附属図書館) / 学位論文||R5||N5461(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 寺内 良平, 教授 髙野 義孝, 教授 吉田 健太郎 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

No description available.