BMC Genomics 2006, 7:245 http://www.biomedcentral.com/1471-2164/7/245 Background Phytophthora spp. are notorious, world-wide pathogens because of their devastating effects on many crop species, that often result in significant economic losses. All mem- bers of the genus Phytophthora infect plants, although some exhibit a broad host range and others infect only a few species [1]. Among the most important species are P. infestans, P. sojae and the newly described species, P. ram- orum [2]. P. infestans affects several host plants from the Solanaceae family including potato, tomato and a number of tropical fruits economically important for pro- ducer countries [3,4]. Current losses in potato production worldwide reach $5 billion [5]. The soybean pathogen, P. sojae, causes root rot and damping off, and in the US alone has recently accounted for annual losses in the order of $1–2 million [1]. P. ramorum has only been described rel- atively recently, so that basic information about its biol- ogy and ecology is scant. This pathogen causes sudden oak death disease and is currently decimating trees and shrubs in the coastal oak forest in California, including keystone tanoak and coast live oak species, and might be expanding to other hosts such as redwoods and to other regions in North America [6]. Given the economic relevance of these pathogens, it is important to standardize high-throughput molecular methods for routinely characterizing Phytophthora popula- tions. Genomic and bioinformatics resources have grown exponentially in recent years, generating information more rapidly than current data-processing tools can han- dle. Thus, the generation of new tools and the application of existing ones for exploring databases constitute a prac- tical and inexpensive approach to elucidating biological systems. The application of bioinformatic tools to genomic databases that are already available for different species of Phytophthora could allow techniques for charac- terizing these pathogens to be developed rapidly. Two of the most informative databases available for Phy- tophthora are the EST (Expressed Sequence Tags) public databases and the Department of Energy's Joint Genome Institute (JGI) databases in which complete genomes, pre- dicted proteins and predicted transcripts are available for P. sojae and P. ramorum [7]. Transcript sequences consti- tute a rich and special source of informative molecular markers because they represent genes that are expressed in an organism. Coding sequences are generally more informative than anonymous markers because they allow for a more direct association between the molecular marker and the phenotype. Microsatellites or simple sequence repeats (SSRs) are molecular markers that con- sist of tandem repeats of one to six DNA base pairs. SSRs are highly versatile, PCR-based markers, usually associ- ated with a high frequency of length polymorphism [8]. They are choice markers given that they show fairly high mutation rates and are codominant [9,10]. They have been found in both coding and non-coding DNA sequences of all higher organisms analyzed [11,12]. In oomycetes, SSRs have had important applications such as diagnosis and determination of mating type [13], genetic structure and disease dynamics [14,15], and population genetics [16,17]. Apart from their application as molecu- lar markers, determining the abundance and density of SSRs in oomycetes may help understand whether these sequences have any functional and evolutionary signifi- cance [18]. An innovative marker system that has been developed links expressed sequence tags (ESTs) and SSRs [19,20]. These EST-SSRs have been applied successfully in studies of genetic variation, linkage mapping, gene tagging, evo- lution and sequencing of several plant genomes [21]. Although they are less polymorphic than genomic SSRs, EST-SSRs tend to be more conserved, at least in the plant species in which they have been studied [22]. This charac- teristic makes EST-SSRs readily transferable between related organisms [17,23-26]. Therefore, SSRs from tran- script sequences have considerable potential for compara- tive mapping studies, as well as for analyses of genetic diversity within the expressed portions of the genome in which they are located. Although Phytophthora EST and transcript databases are publicly available, no formal analysis of SSRs in these sequences has been reported. We used an in silico approach to analyze the frequency and distribution of SSRs in transcript sequences from the oomycetes Phytoph- thora infestans, P. sojae and P. ramorum. Previous studies on oomycete phylogeny have suggested that these three spe- cies are monophyletic and that P. sojae and P. ramorum are more closely related to each other than to P. infestans [27- 29]. We also surveyed the distribution and possible pat- terns of SSRs in selected sequences corresponding to genes previously associated with pathogenesis and virulence. In addition, we studied in silico the transferability of these SSR-based markers between species. We generated primer pairs, where possible, for all SSRs from these three organ- isms. A publicly available database was generated for Phy- tophthora microsatellites, including primers and SSR survey results [30]. This study will serve as reference for future comparative mapping studies and for the develop- ment of strategies that take advantage of DNA sequence analyses for cross-referencing genes between species and perhaps genera. Results Microsatellites: motif, length and frequency Consensus EST databases from P. infestans and annotated transcripts from P. sojae and P. ramorum, were scanned for the presence of microsatellites, defined as short tandem Page 2 of 11 (page number not for citation purposes)