RESUMO
Expression of mRNA is often regulated by the binding of a small RNA (miRNA, snoRNA, siRNA). While the pairing contribution to the net free energy is well parameterized and can be computed in O(N) time, the cost of removing pre-existing mRNA secondary structure has not received sufficient attention. Conventional methods for computing the unfolding free energy of a target mRNA are costly, scaling like the cube of the number of target bases O(N3). Here we introduce a model to describe the unfolding costs of the binding site, which features surprisingly big differences in the free energy parameters for the four bases. The model is implemented in our O(N) algorithm, BindOligoNet. Donor splice site prediction is more accurate when using our calculation of spliceosomal U1-snRNA to mRNA net binding free energy. Our base-dependent free energies also correlate with efficient ribosome docking near the start codon.
Assuntos
Iniciação Traducional da Cadeia Peptídica , Splicing de RNA , RNA Mensageiro , Algoritmos , Sítios de Ligação , Conformação de Ácido Nucleico , Nucleotídeos , RNA Mensageiro/biossíntese , RNA Mensageiro/química , RNA Nuclear Pequeno/química , Spliceossomos/química , TermodinâmicaRESUMO
There are many effective ways to represent a minimum free energy RNA secondary structure that make it easy to locate its helices and loops. It is a greater challenge to visualize the thermal average probabilities of all folds in a partition function sum; dot plot representations are often puzzling. Therefore, we introduce the RNAbows visualization tool for RNA base pair probabilities. RNAbows represent base pair probabilities with line thickness and shading, yielding intuitive diagrams. RNAbows aid in disentangling incompatible structures, allow comparisons between clusters of folds, highlight differences between wild-type and mutant folds, and are also rather beautiful.
