PATO & Phenotypes: From model organisms to clinical medicine

transcript

PATO & Phenotypes:From model organisms to

clinical medicine

Suzanna LewisSeptember 4th, 2008

Signs, Symptoms and Findings WorkshopFirst Steps Toward an Ontology of Clinical

Phenotypes

Describing phenotype using ontologies will aid in the identification of models of disease & candidate causative genes

GWAS: Genome Wide Association Studies Any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition.

Given an identified gene, then what?

Animal disease models

Animal models

Mutant Gene

Mutant or missing Protein

Mutant Phenotype (disease model)

Mutant Gene

Mutant Phenotype (disease)

Humans Animal models

Mutant Gene

Phenotype data mining = text searching?

Text-based phenotype resources: OMIM (NCBI) DECIPHER (Sanger) HGMD (Cardiff) Disease-specific databases MODs PubMed

Query # of records

“large bone” 713

"enlarged bone" 136

"big bones" 16

"huge bones" 4

"massive bones" 28

"hyperplastic bones"

"hyperplastic bone" 34

"bone hyperplasia" 122

"increased bone growth"

543Thanks to:M Ashburner

Information retrieval from text-based resources (OMIM) is not

straightforward:

Even if we can find what we are looking for in one

organism, how can we associate that with phenotypes observed

in different organisms?

Methods to link phenotypic descriptions of human

diseases to animal models currently don’t exist.

Goal: Turn text-based phenotypes into ontology-based

computable annotations Define a model for representing phenotypes

SHH-/+ SHH-/-

shh-/+ shh-/-

Phenotype (clinical sign) = entity + attribute

P1 = eye + hypoteloric

P2 = midface + hypoplastic

P3 = kidney + hypertrophied

P1 = eye + hypoteloricP2 = midface + hypoplastic P3 = kidney + hypertrophied

PATO: hypoteloric

hypoplastic

hypertrophied

ZFIN: eye

midface

kidney

Anatomical ontology

Cell & tissue ontology

Developmental ontology

Gene ontology

biological process

molecular function

cellular component

+ PATO(phenotype and trait ontology)

P1 = eye + hypoteloricP2 = midface + hypoplastic P3 = kidney + hypertrophied

Syndrome = P1 + P2 + P3 (disease) (package) = holoprosencephaly

Entity Quality

Evidence Qualifier

relationship

EnvironmentGenetic Phenotype annotation model

Source

Attribution

Who makes the assertion

Properties

When, what organization

Assertion

OBD and annotations

Absenceof aorta

publish/create

Experiment/investigation

query/meta-analysis

Directannotation

annotation

Shh- AbsenceOf aorta

observation

Computational representation

Agent(human/computer)Community/expert

Information entity

investigator

bio-entity

Shh+ Heartdevelopment

Dev Biol 2005 Jul 15;283(2):357-72

“Sonic hedgehog is required for cardiac outflow tract and neural crest cell development”

communicate

local dblocal dblocal db

Multiple schemas

influences

Participatesin

represents

subj objrelation

annotation

submit/consume

Develop and extend requisite ontologies For the entities being described: anatomies, processes, …

It is critical that ontologies are developed cooperatively so thattheir classification strategies

augment one another.

Building a suite of orthogonal interoperable reference (evidence

based) ontologies in the biomedical domain.

Truth springs from arguments amongst friends. (David Hume)

RELATION TO TIME

GRANULARITY

CONTINUANT OCCURRENT

INDEPENDENT DEPENDENT

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy?)

Anatomical Entity(FMA, CARO)

OrganFunction

(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)

Requisite ontologies

An ontology of qualities (PATO) Organism specific anatomies A controlled vocabulary of homologous and analogous anatomical structures (Uberon)

Gene Ontology Cell Types

Develop an intuitive annotation environment for rigorously capturing phenotypes (“semantic authoring”)

Phenote: Simple software for annotating using ontologies

Provide tool for ontology-based annotation Standardized model to record annotations for increased compatibility of data between disparate communities.

Simple & intuitive user interface (especially for users that don’t know/care about what an ontology is)

Easy-to-configure for different user-communities

Pluggable architecture for external applications to interface/embed in application

Provide interfaces with external SOAP and REST services for streamlined workflow (OBD, NCBI, EBI, etc).

www.phenote.org

BioPortal

External siteLocal file

Ontologies can be utilized from various resources in OWL

and OBO format

Phenote tour

Editor

Refining terms on-the-spot

Post-composition: Join together 2 (or more) terms for specificity: Apoptosis of neuron in skin (GO,CL,FMA) S-phase of colon cancer cell (GO,CL) Aster of human spermatocyte (GO,FMA)

Combine terms from different ontologies

Increase “information content” of an annotation

Pre-composed: Have decomposed definitions of ~2/3rds of MP terms available to incorporate mouse data

Term Info Browser

Annotation Table

Retrieve data from NCBI: OMIM, PUBMED, …

(SOAP plug-in)

Graphical Viewer

Develop a set of guidelines for biocurators

Annotate mutant phenotypes (OMIM and models)

General Annotation Standards

Remarkable normality Absence Relative qualities (what does “small” mean?)

Rates/frequencies does it inhere in the heart or a process?

Homeotic transformation Phenotypes specific to a stage or temporal duration

Testing the methodology

Annotated 11 gene-linked human diseases described in OMIM, and their homologs in zebrafish and fruitfly. ATP2A1, BRODY MYOPATHY EPB41, ELLIPTOCYTOSIS EXT2, MULTIPLE EXOSTOSES EYA1, EYES ABSENT FECH, PROTOPORPHYRIA PAX2, RENAL-COLOBOMA SYNDROME SHH, HOLOPROSENCEPHALY SOX9, CAMPOMELIC DYSPLASIA SOX10, PERIPHERAL DEMYELINATING NEUROPATHY TNNT2, FAMILIAL HYPERTROPHIC CARDIOMYOPATHY TTN, MUSCULAR DYSTROPHY

An OMIM Record

Develop a set of guidelines for biocurators

Annotate mutant phenotypes (OMIM and models)

Collect & store annotations in a common resource (OBD) and make these broadly available

4355 genes and genotypes in OBD17782 entity-quality annotations in OBD

OBD model: Requirements

Generic We can’t define a rigid schema for all of biomedicine

Let the domain ontologies do the modeling of the domain

Expressive Use cases vary from simple ‘tagging’ to complex descriptions of biological phenomena

Formal semantics Amenable to logical reasoning First Order Logic and/or OWL1.1

Standards-compatible Integratable with semantic web

OBD Model: overview

Graph-based: nodes and links Nodes: Classes, instances, relations Links: Relation instances

Connect subject and object via relation plus additional properties

Annotations: Posited links with attribution / evidence

Equivalent expressivity as RDF and OWL Links aka axioms and facts in OWL Attributed links:

Named graphs Reification N-ary relation pattern

Supports construction of complex descriptions through graph model

OBD Dataflow

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Post-composition of phenotype classes

(PATO EQ formalism)

Post-composition of complex anatomical entity

descriptions

Example ofAnnotation in OBD

OBD Architecture

Two stacks1. Semantic web stack

Built using Sesame triplestore + OWLIM

Future iterations: Science-commons Virtuoso

2. OBD-SQL stack Current focus Traditional enterprise architecture Plugs into Semantic Web stack via

OBD-SQL Stack

Alpha version of API implemented Test clients access

via SOAP Phenote current

accesses via org.obo model & JDBC

Wraps org.obo model and OBD schema Share relational

abstraction layer Org.obo wraps OWLAPI

Phenote currently connects via JDBC connectivity in org.obo

computable annotations Define a model for representing phenotypes Develop and extend requisite ontologies

For the entities being described: anatomies, processes, …

Develop a set of guidelines for biocurators Annotate mutant phenotypes (OMIM and models) Collect & store annotations in a common resource (OBD) and make these broadly available

Develop tools & resources for mining data for novel discovery Developed a similarity search algorithm to identify genotypes with similar phenotype.

sox9 mutations curated in PATO syntax

Human, SOX9(Campomelic dysplasia)

Zebrafish, sox9a (jellyfish)

Male sex determination: disrupted

Scapula: hypoplastic Scapulocorocoid: aplasticLower jaw: decreased size

Cranial cartilage: hypoplastic

Heart: malformed or edematous Heart: edematous

Phalanges: decreased length Pectoral fin: decreased lengthLong bones: bowed Cartilage development: disrupted

1 2 3 4

EYA1 SOX10 SOX9 PAX2

0.78 0.71 0.61 0.72

congruence

total annotations

similar annotations

Average annotation consistency

Reasoning over phenotype descriptions recorded with

ontologies provides linkages in annotations.

Ontologies and reasoning can reveal

similarities in phenotype

annotations.

Gene Similarity

Citation Role in hedgehog pathway

smo 0.445 Ochi, et al. 2006

Membrane protein binds shh receptor ptc1

disp1 0.444 Nakano, et al. 2004

Regulates secretion of lipid modified shh from midline

prdm1a

0.43 Roy, et al., 2001

Zinc-finger domain transcription factor, downstream target of shh signaling

hdac1 0.427 Cunliffe and Casaccia-Bonnefil, 2006

Transcriptional regulator required for shh mediated expression of olig2 in ventral hindbrain

scube2

0.398 Hollway et al., 2006

May act during shh signal transduction at the plasma membrane

wnt11 0.380 Mullor et al., 2001

Extracellular cysteine rich glycoprotein required for gli2/3 induced mesoderm development

gli2a 0.348 Kalstrom, et al., 1999

Zinc finger transcription factor target of shh signaling

bmp2b 0.303 Ke et al., 2008

Downstream target of gli2 gene repression

gli1 0.303 Karlstrom, et al., 2003

Zinc finger transcription factor target of shh signaling

ndr2 0.289 Muller, et al., 2000

TGFbeta family member upstream of hedgehog signaling in the ventral neural tube

hhip 0.265 Ochi et al., 2006

Binds shh in membrane and modulates interaction with smo

A zebrafish shh similar-phenotype query returns known hedgehog pathway

members

OBD similarity query

A computational search that enables comparison of phenotypes within and across species. Given a set of phenotype annotations recorded for a mutant allele we can identify other alleles in the same gene.

We can identify other known pathway members in the same species and known gene orthologs in other species simply by comparing phenotypes alone.

This annotation and search method provides a novel means for laboratory researchers to identify potential gene candidates participating in regulatory and/or disease pathways.

Summary of (some of) the challenges

Curating the information Efficiency (pre-composed vs. post-composed) Consistency between curators Missing contextual information (genetic background and environment)

Observation vs. the inference made from this

Representing homology (bones named by relative position)

Those attempting this anyway: zebrafish, Drosophila, C. elegans, Cyprinoid fish (evolution), Dictyostelium, mouse (many), Xenopus, paramecium…

Credit to

Berkeley Christopher Mungall Mark Gibson Nicole Washington Rob Bruggner

U of Oregon Monte Westerfield Melissa Haendel

National Institutes of Health

U of Cambridge Michael Ashburner George Gkoutos (PATO)

David Osumi-Sutherland

OBO Foundry Michael Ashburner Christopher Mungall Alan Ruttenberg Richard Scheuermann Barry Smith

PATO & Phenotypes: From model organisms to clinical medicine

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