BMC Genomics 2008, 9:339 http://www.biomedcentral.com/1471-2164/9/339 [7]. As such, -1 PRF is hypothesized to add a novel modal- ity for regulation of gene expression at the post-transcrip- tional level. There are currently three databases serving the transla- tional recoding community. RECODE (please see Availa- bility and requirements for more information) is a browsable collection of all the published translational recoding signals [8,9]. RECODE's strength is as central repository of all empirically proven translational recoding signals. FSDB (please see Availability and requirements for more information) contains a compilation of a hand- ful of known and predicted viral, prokaryotic and eukary- otic -1 and +1 PRF signals, and also allows users to input their own sequences to search for frameshift signals using a program called FSFinder [10]. Although incomplete, this site provides tools not available through RECODE, in par- ticular it integration of PseudoViewer, a powerful graphics tool that simplifies visualization of H-type pseudoknots [11]. MLOGD (please see Availability and requirements for more information) is a suite of software that allows detection of new protein-coding sequences by identifying overlapping open reading frames [12]. While all three of these sites have their strengths, a common weakness it that they do not provide well catalogued, searchable data- bases of all potential recoding signals of any one kind. To fill this gap, we have created PRFdb as a database of pre- dicted -1 PRF signals in eukaryotic genomes. The methods used to search for predicted -1 PRF signals have been pre- viously described, and importantly, we have empirically demonstrated that a significant number of -1 PRF signals so identified actually promote significant levels of frameshifting [13]. The strength of the PRFdb is that it provides a tool for researchers outside of the translational recoding field to use to quickly search for and identify potential -1 PRF signals in genes in which they are inter- ested. Construction and content In the PRFdb, the predicted -1 PRF signals are represented by: 1) the genes in which they reside; 2) the identity and location of their slippery sites; 3) graphical representa- tions of their predicted secondary structures; 4) computa- tionally identified minimum free energies (MFE); and 5) the thermodynamic significance of these mRNA structures as compared to randomized variants. Currently com- pleted genomes in the PRFdb are Saccharomyces cerevisiae (88,683 sequences windows from 4,238 of 6,352 genes); Homo sapiens (24,104 sequence windows from 6826 of 17,891 genes); Mus musculus (19,313 windows from 6,053 of 15,620 genes); Rattus norvegicus (5924 sequence windows comprising 1982 of 5341 genes); Bos Taurus (10,690 windows from comprising 3349 of 9187 genes); Danio rerio (7640 sequence windows comprising 2618 of 6197 genes); and Xenopus tropicalis (9776 sequence win- dows comprising 2712 of 5126 genes). As of this writing, sequences from Xenopus laevis are being evaluated and entered into the database. The Arabidopsis thaliana genome is queued next in the pipeline. Researchers can access data in the PRFdb through four means: (i) Search (Figure 1) provides a way to query a gene of interest using the specific gene name or descrip- tion from the yeast genome project or mammalian gene collection. The search interface also provides a means to use BLAST to search for genes in the PRFdb similar to a query sequence. ii) Distribution (Figure 2) enables brows- ing for sequences containing statistically significant puta- tive -1 PRF signals through a graphical representation of computed minimum free energies with respect to rand- omized z scores for all sequence windows. It is also possi- ble to limit this distribution to sequences that are preceded by a specific slippery site. iii) Filter prints sequences from a given genome that meet specific criteria including: species, pseudoknotted sequence, sequences with a specific number of base pairs and/or MFE. iv) Download provides a format suitable for parsing all sequences of a given genome/sequence dataset. The search, distribution, and filter interfaces lead to a detailed description of individual putative PRF signals (Figure 3). This provides a summary of all data gathered for a given sequence including: background information on the gene and location of the -1 PRF signal, information regarding the program used to perform the MFE predic- tion, multiple methods to view the secondary structure, and a comparison of the distribution of randomized sequences to the MFE of the folded sequence. If a sequence of interest is not currently in the PRFdb, it can be imported via its NCBI accession number. Sequences added in this manner will be filtered within hours of import. Sequences imported into the PRFdb are also folded using sequential windows across the entire sequence in order to create a graphical minimum free energy 'landscape.' This enables users to submit longer or shorter sequence strings for computational folding, a par- ticularly useful feature e.g. for eliminating extraneous sequence that may not be involved in actual RNA folding. For example, the computational analysis of the 100 nucle- otide sequence downstream of the slippery site of the mouse Ma3 -1 PRF signal provided by the PRFdb predicts tandem stem loop structures. However, when only 55 nt of downstream sequence are provided, PRFdB predicts the empirically documented pseudoknot structure [14]. Sequences to be analyzed by the PRFdb are imported into the database, filtered using RNAMotif [15], folded with secondary structure prediction algorithms, randomized using one or more randomization methods, and refolded. Page 2 of 7 (page number not for citation purposes)