The RNA structure alignment ontology

Abstract

Multiple sequence alignments are powerful tools for understanding the structures, functions, and evolutionary histories of linear biological macromolecules (DNA, RNA, and proteins), and for finding homologs in sequence databases. We address several ontological issues related to RNA sequence alignments that are informed by structure. Multiple sequence alignments are usually shown as two-dimensional (2D) matrices, with rows representing individual sequences, and columns identifying nucleotides from different sequences that correspond structurally, functionally, and/or evolutionarily. However, the requirement that sequences and structures correspond nucleotide-by-nucleotide is unrealistic and hinders representation of important biological relationships. High-throughput sequencing efforts are also rapidly making 2D alignments unmanageable because of vertical and horizontal expansion as more sequences are added. Solving the shortcomings of traditional RNA sequence alignments requires explicit annotation of the meaning of each relationship within the alignment. We introduce the notion of ''correspondence,'' which is an equivalence relation between RNA elements in sets of sequences as the basis of an RNA alignment ontology. The purpose of this ontology is twofold: first, to enable the development of new representations of RNA data and of software tools that resolve the expansion problems with current RNA sequence alignments, and second, to facilitate the integration of sequence data with secondary and three-dimensional structural information, as well as other experimental information, to create simultaneously more accurate and more exploitable RNA alignments.

Nuclear and cytoplasmic localization of neural stem cell microRNAs

“…Second, it requires that in a certain alignment of two sequences; of the last eight bases of one, at least five should match consecutive bases within the last 10 bases of the other. By focusing alignment on the two ends of a mature miRNA, this approach is a simple application of the principle of correspondence, that is, general alignment of RNAs with focus on blocks of residues (Brown et al 2009). As described below, our experimental data imply that miRNAs having identical seeds and similar 39 regions tend to have either entirely nuclear dominance or entirely cytoplasmic dominance (Table 2).…”

Sharing and archiving nucleic acid structure mapping data

“…Our SNRNASM classification depends on several ontologies, including the Ontology of Biomedical Investigations (OBI) (Whetzel et al 2006), the Chemical Entities for Biomedical Investigations (CHEBI) (Degtyarenko et al 2008(Degtyarenko et al , 2009, the Protein Ontology (PRO) (Natale et al 2007(Natale et al , 2011, and the RNA Ontology (RNAO) (Leontis et al 2006;Brown et al 2009;Hoehndorf et al 2011). SNRNASM experiments are described as assays in OBI, with the input being the nucleic acid and the chemical or enzymatic probe, while the output is a measurement of reactivity.…”

“…This is particularly important if one of the goals of sharing data is to facilitate meta-analyses using automated tools. Ontologies are commonly used to define terms and the relations between them in a precise way (Noy et al 2003;Leontis et al 2006;Brown et al 2009). We therefore describe single nucleotide resolution nucleic acid structure mapping (SNRNASM) experiments in terms of an ontological framework.…”

“…Defining best practices for experimental annotation of data is a nuanced challenge (Griffiths-Jones et al 2005;Whetzel et al 2006;Brown et al 2009). On one hand, capturing as much detail as possible is ideal from a future analysis perspective.…”

“…Fields in which data standardization has allowed sharing among many researchers, including sequence data in GenBank Wheeler et al 2008) and structural data in the Protein Data Bank (Bernstein et al 1977), have benefited enormously from the ability of investigators to draw insights from the work of thousands of people dispersed across the globe (Cannone et al 2002;GriffithsJones et al 2003;Noy et al 2003;Zhang et al 2006;Elnitski et al 2007;Musen et al 2008;Brown et al 2009). At present, there is currently no standard database for archiving and sharing nucleic acid structure mapping data, despite the compelling opportunities to incorporate such data in studies with direct relevance to human health and to a wide range of scientific challenges (Russell and Herschlag 2001;Tullius 2002;Schroeder et al 2004;Takamoto et al 2004;Thirumalai and Hyeon 2005;Mortimer and Weeks 2007;Tijerina et al 2007;Shcherbakova and Brenowitz 2008;Woodson 2008;Deigan et al 2009).…”