The stripe rust disease caused by the by the highly specialized fungal pathogen Puccinia striiformis f.sp. tritici (PST) is an historical and continuing threat to wheat production worldwide. Biotrophic plant pathogens, such as PST, secrete effector proteins that enable infection of the host tissue by subverting the plant innate immune response. Despite the central role of effectors in plant diseases and the economic importance of wheat stripe rust, not a single PST effector has been identified yet. The limited progress in this area is in partly due to the limited genomic information for this pathogen. Using Illumina technology we sequenced (>50x coverage) and assembled about 88% of the genome of the recently isolated and highly virulent race PST-130 (PLoS ONE 6: e24230). We characterized the transposable elements present in the PST-130 genome and with a combination of ab initio gene prediction, comparative genomics using the available information on related organisms, and transcriptome sequencing, we annotated the genes present in the PST-130 genome. We designed and implemented a comprehensive bioinformatic pipeline to identify the putative effector repertoire of PST. The in silico analysis was combined with mRNA-seq data of PST-infected leaves and isolated haustoria. To increase the power of the effector prediction pipeline the genome sequencing efforts were extended to additional PST races with different degrees of virulence and geographic distributions. Based on the genetic variations of putative effectors among the sequenced races and their correlations with virulence profiles, a set of potential effectors was selected for functional validation.