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Working in Real Time: Building Ontologies While Annotating the Mouse from Genotype to Phenotype Judith Blake, Ph.D. Mouse Genome Informatics The Jackson.

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Presentation on theme: "Working in Real Time: Building Ontologies While Annotating the Mouse from Genotype to Phenotype Judith Blake, Ph.D. Mouse Genome Informatics The Jackson."— Presentation transcript:

1 Working in Real Time: Building Ontologies While Annotating the Mouse from Genotype to Phenotype Judith Blake, Ph.D. Mouse Genome Informatics The Jackson Laboratory Bar Harbor, ME 04609

2 24Mar2002 Genotype Objective: Facilitate the use of the mouse as a model for human biology by furthering our understanding of the relationship between genotype and phenotype. PhenotypeExpression Mouse Genome Informatics Mouse Genome Database Project (MGD) Genes and Gene Products Comparative Analysis Alleles and Phenotypes Gene Expression DB Project (GXD) Embryonic gene expression Extensive experimental data Mouse Genome Sequence Project (MGS) Connecting sequence & biology

3 MGI Integration Efforts Integrated experimental and consensus views Mapping, molecular, alleles, expression, phenotypes Gene to GO associations Canonical gene and sequence Collaborations with SWISS-PROT and LocusLink Nomenclature standards, gene groupings Curated mammalian orthologies used in collaborations with RatDB, NCBI and others Index of primary literature Share knowledge from mouse disease models with medical informatics resources All data associations supported with evidence and citation

4 Common Issues for Model Organism Databases Data Integration From Genotype to Phenotype Experimental and Consensus Views Incorporation of large datasets Whole genome annotation pipelines Large scale mutagenesis projects Computational vs. Literature-based data collection and evaluation Data Mining…extraction of new knowledge

5 24Mar2002jblake-Manchester BioInform Wk Challenges Genotype Mouse and Human genome sequences Integrating genes/models with existing biological information Updates, emerging knowledge Phenotype Mega-mutagenesis programs Phenome project / baselines Standard screens Integration of mutant information, targeted mutations, transgenes, expression arrays

6 24Mar2002jblake Manchester BioInfor Wk Numbers (20 March 2002) No. of References70,874 No. of Genes35,404 No. of Markers54,834 Genes w/ NT Seq31,386 Genes w/ AA Seq12,875 Genes w/ Orthologs 7,051 Genes Mapped19,058

7 Strains and Polymorphisms Access to MGI resources Genes and Markers Sequences and Maps Embryonic Expression Mammalian Homology mouse BLAST, molecular segments Alleles and Phenotypes References, AccID,

8 24Mar2002jblake Manchester BioInfor Wk “Show me all genes with their human orthologs located between cM 5 and 7 on Chr. 3 whose gene products localize to the mitochondrial membrane and whose associated mutant phenotypes include ‘skeletal dysmophology” Enable Complex Queries

9 24Mar2002 GO annotations Gene detail page in MGD for the vitamin D receptor gene, Vdr

10 24Mar2002 Orthologs of Vdr Sets of Orthologs Data associations supported by evidence and citation

11 24Mar2002jblake Manchester BioInfor Wk Multiple Keyword Sets Gene/Marker Type Allele Type Assay Type Expression Mapping Molecular Mutation Inheritance Mode Nomenclature Evidence Codes Tissue Cell Lines Units Cytogenetic Molecular ES Cell Line Strain

12 Controlled Vocabularies for Describing Alleles Allele Query Form

13 24Mar2002jblake Manchester BioInfor Wk Anatomy GO: Molecular function, Biological process, Cellular component Phenotypes Disease Models Structured Vocabularies and Ontologies

14 24Mar2002 Anatomical Dictionary Theiler stage 10 (7 dpc) http://genex.hgu.mrc.ac.uk/Databases/Anatomy/ Collaboration with MRC / Edinburgh 3D-Atlas project

15 24Mar2002 Links between anatomical structures at successive stages of mouse development enable the analysis of differentiation pathways

16 Alternative anatomical hierarchies - describe and view anatomy from different anatomical, physiological, and disease perspectives (not just ‘geographical location’, but systems (circulatory) that ‘span geography’ - integrated analysis of expression and phenotype / disease data

17 Consolidated Anatomical Dictionary | heart | %cardiogenic plate | %primitive heart tube | | { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/12/3570983/slides/slide_17.jpg", "name": "Consolidated Anatomical Dictionary | heart | %cardiogenic plate | %primitive heart tube | |

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19 24Mar2002jblake Manchester BioInfor Wk Biol. Process Anatomy Phenotype Gene expression

20 24Mar2002 Data integration depends on indexing to defined sets of objects. Speaking the same language ‘Development’ ‘Heart’ Comparisons between model organisms Beyond mouse From The Heart by Margaret Kirby in “Embryos, Genes and Birth Defects”. Edited by Peter Thorogood Mouse Heart Development

21 24Mar2002 http://www.geneontology.org

22 24Mar2002 Develop structured vocabularies (ontologies) Unique ID, Definition, Defined relationships Annotate genes /gene products to vocabularies Evidence and citation Support common data resource for integrated queries across multiple organisms Goals of the Consortium

23 24Mar2002 Opens browser

24 Search returns children

25 24Mar2002 Returns annotated terms

26 24Mar2002jblake Manchester BioInfor Wk First-Pass Phenotype Set

27 EyEy Query: genes with mutants classified with term ‘eye dysmorphology’

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29 Genotype/Phenotype Classification TermRefAllele Pair 1 Allele Pair 2 Background Growth/weight abnormality postnatal 1Apc Tm1Rfc/Tm1Rfc B6;129F2 Survival: postnatal lethality1Apc Tm1Rfc/Tm1Rfc B6;129F2 Reproductive system: dysmorphology 1Apc Tm1Rfc/Tm1Rfc B6;129F2 A genotype consists of zero, one or more allele pairs on a defined genetic background. The genetic background may be an inbred strain, or it may be unknown.

30 24Mar2002jblake Manchester BioInfor Wk Some Definitions Trait: measurable characteristic of individual or population Blood pressure, coat color, % body fat May be associated with anatomical structure, e.g., an immune response with its site of action Phenotype: name for a group of traits, syndrome, condition e.g., type II diabetes, obesity, lymphocytic leukemia

31 24Mar2002jblake Manchester BioInfor Wk a phenotype can be characterized by many traits & a trait can help characterize many phenotypes Phenotype a Phenotype b Phenotype c Trait 1 Trait 2 ….. Trait n Lepr db-3J /Lepr db-3J

32 24Mar2002jblake Manchester BioInfor Wk Use existing and develop new controlled vocabularies that cover orthogonal concepts Combine terms from these vocabularies to describe traits Assign phenotype (disease) terms for nomenclature ease Joel Richardson, Michael Ashburner, Martin Ringwald Developing structured descriptors for traits

33 24Mar2002 System:Immune system, cardiovascular system Tissue: heart, lung, liver, eye, skin Cell type: epithelial, fibroblast, myoblast, melanocyte Age: E15, P25 Biol.Process: apoptosis, growth, cell differentiation, behavior Metabolite: Glucose, Calcium Qualifier: abnormal, absent, enlarged, increased, disrupted ConceptExamples DCS = dolichostenomelia = disproportionally long limbs, due to long bone overgrow

34 Relationships of Mouse Models to Human Diseases Mouse gene ortholog, same mutation –Same phenotype –Different phenotype Mouse gene ortholog, different or unknown mutations –Same or different phenotypes Mouse phenotype same as human –Mouse gene ortholog –Another mouse gene –Gene unknown Mouse phenotype similar –Unknown genetic component Gene same or different

35 24Mar2002 Relationship to human genes and disease

36 24Mar2002

37 Test Results 1676 disease listings in OMIM 382 have phenotype reports 3187 notated mouse/human orthologs –958 correspond to OMIM entries 305 have phenotype reports 8535 listings in MESH disease tree 709 correspond to orthologs 237 have phenotype reports Goal: Query Mouse Data by Human Disease

38 24Mar2002jblake Manchester BioInfor Wk Summary Integration Requires both manual and computational approaches Attention to data modeling, object identity, data migration issues Ontologies and standardized vocabularies Integral component of integration effort Essential for extracting knowledge Parallel development ontology representations data acquisition and integration efforts

39 24Mar2002 Acknowledgments - MGI Carol Bult Ben King Richard Baldarelli Dirck Bradt Sridhar Ramachandran Deborah Reed Diane Dahman Sophia Zhu Donnie Qi LongLong Yang Pat Grant Nancy Butler Janan Eppig Joel Richardson Martin Ringwald Jim Kadin Lois Maltais Louise McKenzie Harold Drabkin Tom Weigers Jon Beal Lori Corbani Cathy Lutz Cynthia Smith Teresa Chu Sharon Cousins Donna Burkart Ira Lu Li Ni Carroll Goldsmith Moyha Lennon-Pierce Antonio Planchart David Hill Dale Begley Terry Hayamizu Ingeborg McCright Connie Smith Matt, Mike, Leslie, Jeff, Prita, Jill, Diane, DebbieK, Dieter, Lucette, Janice, www.informatics.jax.org

40 24Mar2002jblake Manchester BioInfor Wk Mouse Genome Informatics http://www.informatics.jax.org Gene Ontology http://www.geneontology.org


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