Phytophthora sojae, the causal organism of stem and root rot, and <i>Soybean mosaic virus</i> (SMV) cause two of the most highly destructive diseases of soybean (<i>Glycine max</i> L. Merr). <i>P. sojae</i> can be managed either through deployment of race-specific resistance or through quantitative resistance termed partial resistance. In the current study, partial resistance to <i>P. sojae</i> was mapped in an interspecific recombinant inbred line (RIL) population of <i>Glycine max</i> by <i>Glycine soja</i>. One major quantitative trait loci (QTL) on molecular linkage group (MLG)-J (chromosome 16) and two minor QTL on MLG-I (chromosome 20) and -G (chromosome 18) were mapped using conventional molecular markers. Additionally, partial resistance to <i>P. sojae</i> was mapped in the same RIL population using single feature polymorphism (SFP) markers that further fine mapped the <i>P. sojae</i> QTL and identified potential candidate genes contributing to resistance. In a separate study, race-specific resistance was characterized in PI96983 discovering a potentially new allele of <i>Rps4</i> on MLG-G. Finally, using the newly available whole-genome shotgun sequence of soybean, <i>Rsv4</i> conferring resistance to strains of SMV known in the US, was localized to an approximately 100 kb region of sequence on chromosome 2 (MLG-D1B). Newly designed PCR-based markers permit for efficient selection of <i>Rsv4</i> by breeding programs. Identified candidate genes for <i>Rsv4</i> are discussed. Genomic resources developed in all of these studies provide breeders the tools necessary for developing durable resistance to both SMV and <i>P. sojae</i>. / Ph. D.

This thesis involves the important crop plant soybean (Glycine max), and provides a rich information resource for breeders and geneticists working towards improving traits for pathogen resistance.Results reported here provide a systemic view at both the genetic and biochemical level, and were generated by data-mining gene expression data from soybean cultivars inoculated with plant pathogens and also recombinant inbred line (RIL) populations.The genome variability based on Single Feature Polymorphisms (SFPs) was measured for the first time in soybean, using a genetically diverse set of cultivated G. max lines and also a G. soja line. Additionally, a genetic map spanning all 20 soybean chromosomes groups were assembled in a large RIL population.The well studied metabolic pathways from the model plant Arabidopsis thaliana, were reconstructed in G. max based on sequence similarity comparison between the genomes of the two species. We performed algorithmic analysis of pathways in our set of soybean lines and RILs using the gene expression data, and acquired a systemic view of the metabolic response to pathogen infection in different genetic backgrounds.Significant differences in the patterns of pathway perturbation was observed in the different lines, and also between four different chromosomal regions that have been known to contain genetic elements contributing to pathogen resistance. / Ph. D.