RNA global alignment in the joint sequence–structure space using elastic shape analysis

Abstract

The functions of RNAs, like proteins, are determined by their structures, which, in turn, are determined by their sequences. Comparison/alignment of RNA molecules provides an effective means to predict their functions and understand their evolutionary relationships. For RNA sequence alignment, most methods developed for protein and DNA sequence alignment can be directly applied. RNA 3-dimensional structure alignment, on the other hand, tends to be more difficult than protein structure alignment due to the lack of regular secondary structures as observed in proteins. Most of the existing RNA 3D structure alignment methods use only the backbone geometry and ignore the sequence information. Using both the sequence and backbone geometry information in RNA alignment may not only produce more accurate classification, but also deepen our understanding of the sequence–structure–function relationship of RNA molecules. In this study, we developed a new RNA alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves with sequence information encoded on additional dimensions so that the alignment can be performed in the joint sequence–structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances of full structures can be defined and computed, and probability distributions on spaces of such structures can be constructed for a group of RNAs. Our method was further applied to predict functions of RNA molecules and showed superior performance compared with previous methods when tested on benchmark datasets. The programs are available at http://stat.fsu.edu/ ∼jinfeng/ESA.html.

Reverse Watson-Crick purine-purine base pairs — the Sharp-turn motif and other structural consequences in functional RNAs

“…Recent progress in RNA-based therapeutics 2 including RNA vaccination therapy 3 and successful application of RNA based technologies in plant 4 and animal agriculture 5 have highlighted the importance of developing an overall understanding of the sequence-structure-function relationships in RNA. Despite numerous scientific investigations exploring the sequence-structure [6][7][8][9] and structure-function [10][11][12] spaces for RNA, a comprehensive picture similar to those for protein or DNA is yet to evolve 1,13,14 . RNA achieves the remarkable structural complexity and fascinating functional diversity similar to proteins with only four different building blocks (nucleotides), instead of twenty physicochemically different amino acids as present in proteins.…”

RASS: a web server for RNA alignment in the joint sequence-structure space

“…The framework allows us to seamlessly incorporate sequence information into 3D structures in the computation of geodesic distances. The detailed description of the ESA method is given in (23) and (25). …”

“…With this option users can select a partial structure within a larger RNA molecule for comparison, which can be interesting either structurally or functionally. Since our method is a global alignment method, this option can be especially useful if a user wants to compare a partial structure based on some prior knowledge/information.Lambda: weight for the nucleotide sequence (23). The value of lambda needs to be greater or equal to zero.…”

“…Lambda: weight for the nucleotide sequence (23). The value of lambda needs to be greater or equal to zero.…”

“…In principle, structure alignment methods should utilize sequence information since such information is almost always available. Recently, we have developed a RNA structure alignment method (23,24) that aligns RNAs in the joint sequence-structure space using a framework based on elastic shape analysis (ESA) originally designed for protein structure comparison (25,26). We have shown that the method performed better than using either sequence or structure information alone.…”