Analysis of RNA nearest neighbor parameters reveals interdependencies and quantifies the uncertainty in RNA secondary structure prediction.

Autor:	Zuber J; Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York 14642, USA., Cabral BJ; Computational Sciences, Moderna Therapeutics, Cambridge, Massachusetts 02141, USA., McFadyen I; Computational Sciences, Moderna Therapeutics, Cambridge, Massachusetts 02141, USA., Mauger DM; Computational Sciences, Moderna Therapeutics, Cambridge, Massachusetts 02141, USA., Mathews DH; Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York 14642, USA.; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York 14642, USA.
Jazyk:	angličtina
Zdroj:	RNA (New York, N.Y.) [RNA] 2018 Nov; Vol. 24 (11), pp. 1568-1582. Date of Electronic Publication: 2018 Aug 13.
DOI:	10.1261/rna.065102.117
Abstrakt:	RNA secondary structure prediction is often used to develop hypotheses about structure-function relationships for newly discovered RNA sequences, to identify unknown functional RNAs, and to design sequences. Secondary structure prediction methods typically use a thermodynamic model that estimates the free energy change of possible structures based on a set of nearest neighbor parameters. These parameters were derived from optical melting experiments of small model oligonucleotides. This work aims to better understand the precision of structure prediction. Here, the experimental errors in optical melting experiments were propagated to errors in the derived nearest neighbor parameter values and then to errors in RNA secondary structure prediction. To perform this analysis, the optical melting experimental values were systematically perturbed within the estimates of experimental error and alternative sets of nearest neighbor parameters were then derived from these error-bounded values. Secondary structure predictions using either the perturbed or reference parameter sets were then compared. This work demonstrated that the precision of RNA secondary structure prediction is more robust than suggested by previous work based on perturbation of the nearest neighbor parameters. This robustness is due to correlations between parameters. Additionally, this work identified weaknesses in the parameter derivation that makes accurate assessment of parameter uncertainty difficult. Considerations for experimental design are provided to mitigate these weaknesses are provided. (© 2018 Zuber et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu