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PRFdb: a database of computationally predicted eukaryotic programmed -1 ribosomal frameshift signals.

Belew AT, Hepler NL, Jacobs JL, Dinman JD - BMC Genomics (2008)

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20854, USA. abelew@umd.edu

ABSTRACT

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.

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Related in: MedlinePlus

The detailed interface. This demonstrates that pknots was used to compute an MFE of -23.7 kcal/mol for the 100 bases following the AAAAAU slippery site at position 1653 of the EST2 gene. When randomized 100 times using Fisher-Yates shuffling, a mean MFE of -17.4 kcal/mol was computed for a normal distribution of correlation coefficient 0.9627. The MFE distribution of the randomized sequences is on the right; with the idealized normal distribution in red. The black vertical line marks the mean MFE of the randomized sequences, and the green vertical line marks the MFE of the native sequence. This secondary structure is significantly more stable than random (z score = -2.10). The predicted mRNA secondary structure of this sequence is shown below using both bracket notation, and using a Feynman diagram.
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Figure 3: The detailed interface. This demonstrates that pknots was used to compute an MFE of -23.7 kcal/mol for the 100 bases following the AAAAAU slippery site at position 1653 of the EST2 gene. When randomized 100 times using Fisher-Yates shuffling, a mean MFE of -17.4 kcal/mol was computed for a normal distribution of correlation coefficient 0.9627. The MFE distribution of the randomized sequences is on the right; with the idealized normal distribution in red. The black vertical line marks the mean MFE of the randomized sequences, and the green vertical line marks the MFE of the native sequence. This secondary structure is significantly more stable than random (z score = -2.10). The predicted mRNA secondary structure of this sequence is shown below using both bracket notation, and using a Feynman diagram.

Mentions: 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 prediction, multiple methods to view the secondary structure, and a comparison of the distribution of randomized sequences to the MFE of the folded sequence.


PRFdb: a database of computationally predicted eukaryotic programmed -1 ribosomal frameshift signals.

Belew AT, Hepler NL, Jacobs JL, Dinman JD - BMC Genomics (2008)

The detailed interface. This demonstrates that pknots was used to compute an MFE of -23.7 kcal/mol for the 100 bases following the AAAAAU slippery site at position 1653 of the EST2 gene. When randomized 100 times using Fisher-Yates shuffling, a mean MFE of -17.4 kcal/mol was computed for a normal distribution of correlation coefficient 0.9627. The MFE distribution of the randomized sequences is on the right; with the idealized normal distribution in red. The black vertical line marks the mean MFE of the randomized sequences, and the green vertical line marks the MFE of the native sequence. This secondary structure is significantly more stable than random (z score = -2.10). The predicted mRNA secondary structure of this sequence is shown below using both bracket notation, and using a Feynman diagram.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2483730&req=5

Figure 3: The detailed interface. This demonstrates that pknots was used to compute an MFE of -23.7 kcal/mol for the 100 bases following the AAAAAU slippery site at position 1653 of the EST2 gene. When randomized 100 times using Fisher-Yates shuffling, a mean MFE of -17.4 kcal/mol was computed for a normal distribution of correlation coefficient 0.9627. The MFE distribution of the randomized sequences is on the right; with the idealized normal distribution in red. The black vertical line marks the mean MFE of the randomized sequences, and the green vertical line marks the MFE of the native sequence. This secondary structure is significantly more stable than random (z score = -2.10). The predicted mRNA secondary structure of this sequence is shown below using both bracket notation, and using a Feynman diagram.
Mentions: 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 prediction, multiple methods to view the secondary structure, and a comparison of the distribution of randomized sequences to the MFE of the folded sequence.

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20854, USA. abelew@umd.edu

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus