Keywan Hassani-Pak Plant Systems Biology meeting Edinburgh, March 2011

1. Creating an integrated Ondex knowledge base for comparative gene function analysis Keywan Hassani-Pak UK Plant Systems Biology Workshop 2011 keywan.hassani-pak@bbsrc.ac.uk

2. 2% of fully sequenced genomes are plant genomes Sequenced Plant and Crop Genomes phytozome.net Arabidopsis Rice ? Functional knowledge

3. Functional knowledge in plant and crop databases Source: Mochida et.al. “Genomics and bioinformatics resources for crop improvement.” (2010)

4. Ontologies – Bridging the gap across species and databases Major ontologies used in plant databases Gene Ontology (GO) Plant Ontology (PO) Gramene Trait Ontology (TO) Crop Ontology (CO) Functional annotations use terms from ontologies Annotations must haveevidence types, e.g. IMP, IEA Metrics exist to computesemantic similarity of terms

5. IEA Comparing functional annotations between orthologous genes Conserved Arabidopsis Rice IMP

6. A knowledge base of functional annotations in plants October 2010 Collected data from TAIR and Gramene Used Ondex to create a knowledgebase of functional gene annotations in plants Measured conservation and transferability of ontology terms

7. Conservation of Plant Ontology terms between Arabidopsis and rice Conserved ? NotConserved A function is conserved if genes from two species are annotated with the same term and are orthologous Conservation of ontology terms can be used as background knowledge for cross-species annotation transfer Conserved terms suited for automated annotation transfer Not conserved terms need further investigation Defoin-Platel M, Hassani-Pak K and Rawlings CJ (2011)

8. Cross-species annotation transfer Newly sequenced crop gene Arabidopsis Rice IMP

9. Bioenergy application case Linked References Arabidopsis, Rice etc. Poplar Willow Phenotypes Plant Hormones Physical map QTL Map Orthologous Genes Expression Patterns Pathways Cross-species annotation transfer List of candidate genes linked to biomass traits

10. Is Gene X a possible biomass candidate? IEA E-Value: 8.3E-17 MSA IGI IMP

11. Phenotypic information in literature Keyword: Shoot branching

12. Summary Study of gene function needs integration of multiple sources of information Cross-species knowledge is one (sometimes the only) source of information we have available Ontologies are essential for comparing annotations across species and databases Developed a procedure to measure transferability of Gene Ontology (GO) and Plant Ontology (PO) terms QTL analysis and candidate gene prediction using integrative and comparative approaches

13. Acknowledgements Rothamsted Chris Rawlings Jan Taubert Catherine Canevet KeywanHassani-Pak Andrea Splendiani Matthew Hindle Artem Lysenko Michael Defoin-Platel Angela Karp Steve Hanley Kim Hammond-Kosack Martin Urban Manchester Robert Stevens Carole Goble Pedro Mendes Paul Dobson Paul Fisher David Withers Georgina Moulton Katy Wolstenholme NaCTem Sophia Ananiadou Gina-Anne Levow RaheelNawaz Newcastle Neil Wipat Phil Lord Darren Wilkinson Jochen Weile Matthew Pocock Simon Cockell James Dewar Katherine James Eva Holstein Edinburgh Igor Goryanin Andrew Millar Luna de Ferrari

14. From QTL to candidate genes Rae et al., 2008 Gene Prioritisation Can help to reduce hypothesis space from 100 potential candidates to few hot candidates. Next step experimental validation: Cloning and transformation in models (Arabidopsis/Poplar).