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COFOLD: an RNA secondary structure prediction method that takes co-transcriptional folding into account.

Proctor JR, Meyer IM - Nucleic Acids Res. (2013)

Bottom Line: These aim to predict the most stable RNA structure.There exists by now ample experimental and theoretical evidence that the process of structure formation matters and that sequences in vivo fold while they are being transcribed.Here, we present a conceptually new method for predicting RNA secondary structure, called CoFold, that takes effects of co-transcriptional folding explicitly into account.

View Article: PubMed Central - PubMed

Affiliation: Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, BC, V6T 1Z4, Canada.

ABSTRACT
Existing state-of-the-art methods that take a single RNA sequence and predict the corresponding RNA secondary structure are thermodynamic methods. These aim to predict the most stable RNA structure. There exists by now ample experimental and theoretical evidence that the process of structure formation matters and that sequences in vivo fold while they are being transcribed. None of the thermodynamic methods, however, consider the process of structure formation. Here, we present a conceptually new method for predicting RNA secondary structure, called CoFold, that takes effects of co-transcriptional folding explicitly into account. Our method significantly improves the state-of-art in terms of prediction accuracy, especially for long sequences of >1000 nt in length.

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Relative free-energy differences of the predicted structures w.r.t. the MFE structures predicted by RNAfold. Summary of three distributions for the long data set showing the relative free-energy differences of the RNA structures predicted by RNAfold-A w.r.t. the MFE structures predicted by RNAfold for the same sequence (left), of the RNA structures predicted by CoFold w.r.t. the MFE structures predicted by RNAfold (middle) and of the RNA structures predicted by CoFold-A w.r.t the MFE structures predicted by RNAfold-A (right). The free energies of all structures are calculated using the Turner 1999 energy parameters. For each of the three distributions, the dark horizontal line indicates the average, the box indicates the first to the third quartile and the dotted lines indicate minimum and maximum values. Circles indicate outliers which are not included in the calculation of the average value.
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gkt174-F3: Relative free-energy differences of the predicted structures w.r.t. the MFE structures predicted by RNAfold. Summary of three distributions for the long data set showing the relative free-energy differences of the RNA structures predicted by RNAfold-A w.r.t. the MFE structures predicted by RNAfold for the same sequence (left), of the RNA structures predicted by CoFold w.r.t. the MFE structures predicted by RNAfold (middle) and of the RNA structures predicted by CoFold-A w.r.t the MFE structures predicted by RNAfold-A (right). The free energies of all structures are calculated using the Turner 1999 energy parameters. For each of the three distributions, the dark horizontal line indicates the average, the box indicates the first to the third quartile and the dotted lines indicate minimum and maximum values. Circles indicate outliers which are not included in the calculation of the average value.

Mentions: The structures predicted by CoFold for the long data set differ on average by 2% from the respective free energies of the corresponding structures predicted by RNAfold and the distribution of relative energy differences is comparatively tight (SD = 1.0%, min = 0.2%, max = 4.4%) (Figure 3, Supplementary Figure S4 and Supplementary Table S4). Combining CoFold and RNAfold with the Andronescu 2007 energy parameters significantly increases the average free-energy difference [5% (RNAfold-A), 7% (CoFold-A)], broadens the distributions [SD(RNAfold-A) = 1.9%, SD(CoFold-A) = 2.4%] and leads to higher maximum energy differences [max(RNAfold-A) = 11.1%, max(CoFold-A) = 13.1%]. For short and viral sequences, these differences are even more pronounced (Supplementary Table S4).Figure 3.


COFOLD: an RNA secondary structure prediction method that takes co-transcriptional folding into account.

Proctor JR, Meyer IM - Nucleic Acids Res. (2013)

Relative free-energy differences of the predicted structures w.r.t. the MFE structures predicted by RNAfold. Summary of three distributions for the long data set showing the relative free-energy differences of the RNA structures predicted by RNAfold-A w.r.t. the MFE structures predicted by RNAfold for the same sequence (left), of the RNA structures predicted by CoFold w.r.t. the MFE structures predicted by RNAfold (middle) and of the RNA structures predicted by CoFold-A w.r.t the MFE structures predicted by RNAfold-A (right). The free energies of all structures are calculated using the Turner 1999 energy parameters. For each of the three distributions, the dark horizontal line indicates the average, the box indicates the first to the third quartile and the dotted lines indicate minimum and maximum values. Circles indicate outliers which are not included in the calculation of the average value.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643587&req=5

gkt174-F3: Relative free-energy differences of the predicted structures w.r.t. the MFE structures predicted by RNAfold. Summary of three distributions for the long data set showing the relative free-energy differences of the RNA structures predicted by RNAfold-A w.r.t. the MFE structures predicted by RNAfold for the same sequence (left), of the RNA structures predicted by CoFold w.r.t. the MFE structures predicted by RNAfold (middle) and of the RNA structures predicted by CoFold-A w.r.t the MFE structures predicted by RNAfold-A (right). The free energies of all structures are calculated using the Turner 1999 energy parameters. For each of the three distributions, the dark horizontal line indicates the average, the box indicates the first to the third quartile and the dotted lines indicate minimum and maximum values. Circles indicate outliers which are not included in the calculation of the average value.
Mentions: The structures predicted by CoFold for the long data set differ on average by 2% from the respective free energies of the corresponding structures predicted by RNAfold and the distribution of relative energy differences is comparatively tight (SD = 1.0%, min = 0.2%, max = 4.4%) (Figure 3, Supplementary Figure S4 and Supplementary Table S4). Combining CoFold and RNAfold with the Andronescu 2007 energy parameters significantly increases the average free-energy difference [5% (RNAfold-A), 7% (CoFold-A)], broadens the distributions [SD(RNAfold-A) = 1.9%, SD(CoFold-A) = 2.4%] and leads to higher maximum energy differences [max(RNAfold-A) = 11.1%, max(CoFold-A) = 13.1%]. For short and viral sequences, these differences are even more pronounced (Supplementary Table S4).Figure 3.

Bottom Line: These aim to predict the most stable RNA structure.There exists by now ample experimental and theoretical evidence that the process of structure formation matters and that sequences in vivo fold while they are being transcribed.Here, we present a conceptually new method for predicting RNA secondary structure, called CoFold, that takes effects of co-transcriptional folding explicitly into account.

View Article: PubMed Central - PubMed

Affiliation: Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, BC, V6T 1Z4, Canada.

ABSTRACT
Existing state-of-the-art methods that take a single RNA sequence and predict the corresponding RNA secondary structure are thermodynamic methods. These aim to predict the most stable RNA structure. There exists by now ample experimental and theoretical evidence that the process of structure formation matters and that sequences in vivo fold while they are being transcribed. None of the thermodynamic methods, however, consider the process of structure formation. Here, we present a conceptually new method for predicting RNA secondary structure, called CoFold, that takes effects of co-transcriptional folding explicitly into account. Our method significantly improves the state-of-art in terms of prediction accuracy, especially for long sequences of >1000 nt in length.

Show MeSH