One of the most destructive diseases of soybean is Phytophthora root and stem rot, caused by the oomycete pathogen Phytophthora sojae, which thrives in wet conditions and poorly drained soils. This disease can cause major damage to soybean yields resulting in economic losses. P. sojae has been successfully controlled by genetic resistance in soybean cultivars. Breeding for this resistance is critical to Ohio agriculture and business because of soybean’s importance as an export, animal feed, and industrial product. Current methods for breeding for resistance to P. sojae involve time-consuming disease assays requiring a relatively large number of seed. Alternatively, molecular markers can be efficiently applied to an earlier generation of a single plant from large numbers of breeding lines. In addition, molecular markers can be used for the combination of multiple resistance genes that will provide a full spectrum of resistance against virulent P. sojae strains. Designing these markers begin with the utilization of sequences similar to a class of known disease resistance genes, nucleotide binding site- leucine rich repeat (NBS-LRR)- encoding genes, that co-locate with the genes for resistance to P. sojae (Rps genes). Primers were designed in order to amplify the variable intron regions of these sequences. Polymerase chain reactions were conducted containing the designed primers and genomic DNA from twelve soybean lines which vary for their resistance phenotypes. The PCR products were sequenced and the results are currently being analyzed for correlation of sequence polymorphisms within the genetically linked NBS-LRR encoding genes to each resistance phenotype. Markers will be designed based on the sequence polymorphisms and will be assayed on a larger population of breeding lines that have been previously tested for resistance in order to determine if the markers are predictive of the Rps gene. The developed molecular markers will be implemented in the breeding program by testing F2 individuals and making selections based on these results.