James W. Brown

Associate Professor & Undergraduate Coordinator
Department of Microbiology, NC State University

Pace Symposium, Oct 25,26, 2007, Boulder, CO

The need for an RNA alignment ontology

James Brown, Fabrice Jossinet, Rym Kachouri, Franz Lang, Neocles Leontis, Gerhard Steger, Jesse Stombaugh, and Eric Westhof.
Department of Microbiology, North Carolina State University, Raleigh, NC, USA 27695-7615

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 homologues in genomic sequences. We would like to address here some ontological issues related to RNA structural sequence alignments. Multiple sequence alignments are usually shown as two-dimensional matrices, with rows representing individual sequences and columns identifying structurally similar (presumably homologous) residues from different sequences. In accommodating the rapidly growing number of new sequences that are becoming available through high-throughput genomic sequencing, traditional two-dimensional alignments rapidly become unmanageable due to vertical and horizontal expansion. In parallel with large-scale sequencing efforts, progress in structural biology is contributing detailed secondary structures, and atomic-resolution 3D structures of representative molecules of important families of biological molecules. Structural data increase tremendously in value when associated with corresponding multiple sequence alignments. The resolution of alignments in turn increases when 3D data is utilized to establish structural similarity. Solving the expansion and data integration problems requires explicitly stating the fundamental meaning of each portion of the alignment. In short, what is required is an ontology of RNA alignments. The purpose of this ontology is two-fold: first to enable the development of new representations of RNA data and software tools to resolve the expansion problems with current RNA sequence alignments; second, to facilitate the integration of sequence data with secondary and 3D structural as well as other experimental information to create more accurate alignments.

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