PRFdb: a database of computationally predicted eukaryotic programmed -1 ribosomal frameshift signals.
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They are then filtered through multiple algorithms to identify potential -1 PRF signals as defined by a heptameric slippery site followed by an mRNA pseudoknot.The significance of each candidate -1 PRF signal is evaluated by comparing the predicted thermodynamic stability (DeltaG degrees ) of the native mRNA sequence against a distribution of DeltaG degrees values of a pool of randomized sequences derived from the original.The data have been compiled in a user-friendly, easily searchable relational database.
Affiliation: Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20854, USA. abelew@umd.edu
ABSTRACT
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Background: The Programmed Ribosomal Frameshift Database (PRFdb) provides an interface to help researchers identify potential programmed -1 ribosomal frameshift (-1 PRF) signals in eukaryotic genes or sequences of interest. Results: To identify putative -1 PRF signals, sequences are first imported from whole genomes or datasets, e.g. the yeast genome project and mammalian gene collection. They are then filtered through multiple algorithms to identify potential -1 PRF signals as defined by a heptameric slippery site followed by an mRNA pseudoknot. The significance of each candidate -1 PRF signal is evaluated by comparing the predicted thermodynamic stability (DeltaG degrees ) of the native mRNA sequence against a distribution of DeltaG degrees values of a pool of randomized sequences derived from the original. The data have been compiled in a user-friendly, easily searchable relational database. Conclusion: The PRFdB enables members of the research community to determine whether genes that they are investigating contain potential -1 PRF signals, and can be used as a metasource of information for cross referencing with other databases. It is available on the web at http://dinmanlab.umd.edu/prfdb. Related in: MedlinePlus |
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Figure 2: The distribution of Saccharomyces cerevisiae sequences. Computed minimum free energy is on the x-axis, z score is on the y-axis. Black lines denote the mean values and gray lines define sequence windows that are one and two standard deviations less than mean. Clicking on any region links to the closest -1 PRF signals with respect to MFE and z score. Mentions: 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 description 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 browsing for sequences containing statistically significant putative -1 PRF signals through a graphical representation of computed minimum free energies with respect to randomized z scores for all sequence windows. It is also possible 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. |
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Affiliation: Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20854, USA. abelew@umd.edu
Background: The Programmed Ribosomal Frameshift Database (PRFdb) provides an interface to help researchers identify potential programmed -1 ribosomal frameshift (-1 PRF) signals in eukaryotic genes or sequences of interest.
Results: To identify putative -1 PRF signals, sequences are first imported from whole genomes or datasets, e.g. the yeast genome project and mammalian gene collection. They are then filtered through multiple algorithms to identify potential -1 PRF signals as defined by a heptameric slippery site followed by an mRNA pseudoknot. The significance of each candidate -1 PRF signal is evaluated by comparing the predicted thermodynamic stability (DeltaG degrees ) of the native mRNA sequence against a distribution of DeltaG degrees values of a pool of randomized sequences derived from the original. The data have been compiled in a user-friendly, easily searchable relational database.
Conclusion: The PRFdB enables members of the research community to determine whether genes that they are investigating contain potential -1 PRF signals, and can be used as a metasource of information for cross referencing with other databases. It is available on the web at http://dinmanlab.umd.edu/prfdb.