Creating an integrated Ondex knowledge base for comparative gene function analysis

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

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

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

IEA
Comparing functional annotations between orthologous genes
Conserved
Arabidopsis
Rice
IMP

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

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)

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

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

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

Phenotypic information in literature
Keyword: Shoot branching

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

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

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).

Creating an integrated Ondex knowledge base for comparative gene function analysis

by Catherine Canevet on Apr 05, 2011

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Creating an integrated Ondex knowledge base for comparative gene function analysis — Presentation Transcript