BMC Genomics 2006, 7:245 http://www.biomedcentral.com/1471-2164/7/245 between at least two species. This number represents a remarkably large, diverse reservoir of markers that is potentially useful for diversity and population studies. With far fewer primers, an acceptable level of polymor- phism has been found in previous studies of different organisms, where the primers are used to amplify a DNA region that has undergone SSR expansion in one lineage but not in related ones [8,54,60]. The transferability results might suggest that the organization of oomycete genomes shows marked variations. However, a more plausible explanation could be that the evolutionary dis- tance between the selected taxa is greater than in other sys- tems or organisms in which SSRs have been shown to be transferable (e.g. plants). Experimental validation of these hypothetically transferable SSRs and their polymorphism is on-going. This will verify the potential effectiveness of this in silico tool for finding transferable molecular mark- ers for evaluating intra- and inter-specific diversity, instead of spending resources to validate them. Evolutionary forces keep pathogen lineages and their hosts in an arms race, as each evolves new strategies for attack and defense [61]. The success of this arms race over time depends on the mechanisms by which pathogenicity factors evolve. Microsatellite mutation rates, ranging from 10-6 to 10-2 per generation, are higher than base substitu- tion rates [10], and it is thus reasonable to assume that their presence in pathogenicity factors may contribute to variability in the relevant sequences [62]. In this study, we surveyed SSR abundance and distribution in putative pathogenicity factor sequences. The results were com- pared with SSR abundance and distribution in ribosomal and housekeeping sequences, which are presumed to be less variable because their fundamental functions in the organism are conserved. However, our results did not show higher SSR abundance in the pathogenicity factors. Differences from reference sequences (ribosomal and housekeeping) were not statistically significant (P > 0.05). This suggests that SSRs probably do not make a clear con- tribution to functional changes in pathogenicity factors, which allow P. infestans, P. sojae and P. ramorum to cause disease, but our study does not rule out the possibility that SSR polymorphisms may be present in pathogenicity genes. Conclusion Databases for P. sojae, P. infestans and P. ramorum were inexpensive sources of SSRs. In silico investigation of SSRs is a significant step towards understanding the biological functions and nature of these important portions of the DNA. SSR markers are potentially useful tools for identi- fying Phytophthora species and for assessing genetic varia- tion among populations. Evaluation of intraspecific genetic variation in Phytophthora concomitant with equiv- alent studies of host genetic variation could allow the rela- tionships between host genotype variability, Phytophthora genotype and the selection pressures acting between them to be established. An important direct application of this study is as a resource for future population research. Methods Sources of ESTs and annotated transcript sequences EST sequences from P. infestans (81974) were down- loaded from the Phytophthora Functional Genomics Database [31]. The annotated transcript sequences availa- ble for P. sojae (19276) and P. ramorum (16066) were downloaded from the Department of Energy's Joint Genome Institute [32]. These redundant ESTs and tran- script sequence sets were obtained in FASTA format. In addition, we downloaded 136, 318, and 171 sequences corresponding to putative or validated pathogenicity fac- tors from P. infestans (National Center for Biotechnology Information [63]), P. sojae (Virginia Bioinformatics Insti- tute [64]) and P. ramorum (DOE Joint Genome Institute [32]). From the same databases, ribosomal and house- keeping gene sequences were obtained for each of the organisms studied. Masking and assembly of the ESTs sequences from P. infestans UniVec build # 3.2 was obtained from the NCBI web site FTP directory [65] and the latest repetitions database Rep- Base [33] EST were masked using the cross-match utility. PHRAP version 0.990329 was used to cluster the ESTs and to generate consensus sequences. Parameters phrap- miniscore 100 -minmatch 50 were used to generate con- sensus. The total consensus sequence count was 25965. Scanning of non-redundant EST and transcript sequences from P. infestans, P. sojae and P. ramorum for SSR survey Non-redundant EST and transcript sequences were scanned using a local version of the Microsatellite Identi- fication Tool (MISA) available from the Plant Genome Resources Center (PGRC) [66]. This program searches for both perfect and compound SSRs with 2 to 6 nucleotides in the basic repeat unit. It records repeat numbers and SSR locations inside the EST sequence and deposits these results in an output file. SSR redundancy was minimized by counting only a single match when there was more than one record for the same SSR locus. Minimum SSR length was determined by the number of repeats, which were (2/6) (3/4) (4/3) (5/3) (6/3); the first digit refers to the SSR repeat type and the second to the minimum number of repeat units (Table 1). For example, (2/6) means that a motif consisting of 2 bp and should have at least 6 repeats to be considered a microsatellite in our analysis. Pathogenicity factors, ribosomal genes and housekeeping genes were also scanned for SSRs using the same parameters (Table 6). Page 9 of 11 (page number not for citation purposes)