Stable stem enabled Shannon entropies distinguish non-coding RNAs from random backgrounds

• Published in: BMC bioinformatics Vol. 13 Suppl 5; no. S5; p. S1
• Main Authors: Wang, Yingfeng, Manzour, Amir, Shareghi, Pooya, Shaw, Timothy I, Li, Ying-Wai, Malmberg, Russell L, Cai, Liming
• Format: Journal Article
• Language: English
• Published: England BioMed Central 12.04.2012; BioMed Central Ltd; BMC
• Subjects: Algorithms; Base Pairing; Bioinformatics; Dynamic programming; Entropy; Nucleic Acid Conformation; Probability; Ribonucleic acid; RNA; RNA Folding; RNA, Untranslated - chemistry; RNA, Untranslated - genetics; Studies
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/1471-2105-13-S5-S1

The computational identification of RNAs in genomic sequences requires the identification of signals of RNA sequences. Shannon base pairing entropy is an indicator for RNA secondary structure fold certainty in detection of structural, non-coding RNAs (ncRNAs). Under the Boltzmann ensemble of secondary structures, the probability of a base pair is estimated from its frequency across all the alternative equilibrium structures. However, such an entropy has yet to deliver the desired performance for distinguishing ncRNAs from random sequences. Developing novel methods to improve the entropy measure performance may result in more effective ncRNA gene finding based on structure detection. This paper shows that the measuring performance of base pairing entropy can be significantly improved with a constrained secondary structure ensemble in which only canonical base pairs are assumed to occur in energetically stable stems in a fold. This constraint actually reduces the space of the secondary structure and may lower the probabilities of base pairs unfavorable to the native fold. Indeed, base pairing entropies computed with this constrained model demonstrate substantially narrowed gaps of Z-scores between ncRNAs, as well as drastic increases in the Z-score for all 13 tested ncRNA sets, compared to shuffled sequences. These results suggest the viability of developing effective structure-based ncRNA gene finding methods by investigating secondary structure ensembles of ncRNAs.