JWB
James W. Brown

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

Abstract# 94, RNA 2009 (RNA Society), May 26-31, 2009, Madison, WI

The RNA Structure Alignment Ontology

James Brown1, Amanda Birmingham2, Paul Griffiths3, Fabrice Jossinet4, Rym Kachouri-Lafond4, Rob Knight5, Franz Lang6, Neocles Leontis7, Gerhard Steger8, Jesse Stombaugh7, Eric Westhof4

1NC State University, Raleigh, NC, USA, 2Therm Fisher Scientific, Lafayette, CO, USA, 3University of Sydney, Sydney, NSW, Australia, 4Universite de Strasbourg, Strasbourg, France, 5University of Colorado at Boulder, Boulder, CO, USA, 6Universite de Montreal, Montreal, Quebec, Canada, 7Bowling Green State University, Bowling Green, OH, USA, 8Heinrich-Heine-Universitat Dusseldorf, Dusseldorf, Germany

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 matrices, with rows representing individual sequences and columns identifying nucelotides 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 two-dimensional 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, and this in turn requires an RNA alignment ontology. The purpose of this ontology is two-fold: 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 3D structural information, as well as other experimental information, to create simultaneously more accurate and more exploitable RNA alignments. We conclude by discussing implementation issues.

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