1. The RNA Ontology RNAO Colin Batchelor Neocles Leontis May 2009 Eckart, Colin and Jane In Cambridge

2. 2 RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RNAO, PrO) Molecular Function (GO) Molecular Process (GO) OBO Foundry http://obofoundry.org Smith et al. Nature Biotechnology 2008

3. Relationship of RNAO and neighboring ontologies ChEBI (Chemical Entities of Biological Interest) Sequence Ontology Gene Ontology ChEBI Sequence Ontology RNAO Relations Ontology Basic Formal Ontology

4. RnaO and OBO Commitment to common upper ontology (BFO) Commitment to dividing responsibilities between ontologies: ChEBI for molecular parts (and relations?) SO for sequences GO for RNA function Leaving RnaO to concentrate on RNA…

5. Aim “… to create a common, dynamic, controlled vocabulary (the RO), pertaining to RNA function and based on RNA sequences, secondary and three-dimensional structures. Thus, the central objective of the ROC is to identify all RNA features, interactions and motifs mentioned in the literature or appearing in databases, to agree upon a definition for them and to write that definition down in a structured manner. This is very timely as knowledge about RNA accumulates and progresses rapidly. The purposes for creating the RO are therefore (1) to integrate sequence and structural databases and (2) to create powerful software tools that bring advanced computational methods to the bench scientist.”

6. RNAO Working Group meeting in Cambridge, UK, January 2009 Presentations on: RNAO in OWL (Colin Batchelor) Conformations (Jane Richardson) reasoning (Chris Mungall) formal ontology (Thomas Bittner) SO (Karen Eilbeck) ChEBI (Kirill Degtyarenko) alignment and phylogeny (Rob Knight) Rfam (Alex Bateman) 2D to 3D structure (Alain Laederach)

7. Existing neighbouring ontologies Sequence Ontology (5 base pair terms, 3 pseudoknots, 2 stem loops, 10 motif terms) ChEBI (4 RNA terms) Gene Ontology (functions performed by ncRNAs)

8. RNAO v1.0 Implemented in OWL (easier to write complicated logical definitions in Protégé than in OBOEdit but less powerful than FOL and names and really not suitable for human-readable definitions and synonyms) >100 classes >20 relationships

9. Simple use cases Classify base pairs according to the Leontis-Westhof scheme (easy) Identify motifs in 3d structures (hard going on impossible) (Vaguer, but really the most important) Provide bridge between different representations

10. Base pair classification (1) First attempt: use relations to express pairing, bonding and so forth (Dumontierian approach) Base pairing: pairsWith, pairsWithWW, pairsWithCWW Backbone bonding: fivePrimeTo, threePrimeTo, etc.

11. Base pair classification (2) Then (OWL Manchester syntax) Family1BasePair = hasPart some Nucleobase and (pairsWithCWW some Nucleobase) (this works and classifies base pairings satisfactorily within the LW scheme)

13. Drawbacks OWL cannot handle motifs–they require a larger subset of first-order logic But RNA experts differ on definitions of motifs anyway! RNAO.owl hides the interactions behind a large set of relations Relations are hard to maintain in Protégé/OWL

14. Next steps Integrate with real RNA data (NDB, FR3D) Collect RNA motif definitions Formalize what we are actually hiding behind the relations –(WC edge, etc. are parts of nucleotides and have a topological relation to other edges) –Base pairs are parts of RNA molecules –Base–base, base–phosphate and stacking interactions should be treated in the same way as we handle covalent bonds