How to build cross-species interoperable ontologies

Chris Mungall, LBNLMelissa Haendel, OHSU

The challenge..

• There are many fun and interesting issues involved in building and using cross-species ontologies– homology– evo-devo– reasoning using ontologies– connecting genomics databases to phenotypes

but…• Unfortunately, there are many more prosaic

issues with unsatisfying solutions– multiple ontologies already exist– limited cooperation between the developers of these

ontologies– they differ widely in every aspect imaginable– they are heavily embedded in existing databases and

applications and slow to change– tools and infrastructure support falls short of what we

need• FORTUNATELY, solutions are emerging..

Outline

• Anatomy Ontologies: Background• Case studies

– GO: A unified cross-species ontology– CL: Cell Ontology: Unifying multiple existing

efforts

• Building interoperable gross anatomy ontologies– (Melissa)

Ontologies• Computable qualitative representations of some

part of the world• Relationships with computable properties

– e.g. transitivity– languages and formats like owl and obo have a formal

semantics• Entities are grouped into classes• Relationships are statements about all the

members of a class– the most common form is the all-some statement

Ontologies are not smart• Deductive Logic is not flexible• Example

– Human knowledge:• chromosomes are found in the nucleus

– Naïve ontology encoding:• every chromosome part_of some nucleus

– But this is wrong• Ontologies don’t make exceptions!

– Solution:• (1) create location-specific subclasses

– nuclear chromosome– mitochondrial chromosome

• (2) – invert statement: every nucleus has chromosomes

Existing Anatomy Ontologies

• Human AOs• Model Organism AOs• Domain specific AOs• Cross-species AOs

FMA : Foundational Model of Anatomy

• Domain: adult human– no develops_from relationships, few embryonic structures

• Size: large (70k+ classes)• Language: frames• Approach

– formal, Strict single inheritance, Purely structural perspective– No computable definitions– Heavily pre-coordinated

• “Trunk of communicating branch of zygomatic branch of right facial nerve with zygomaticofacial branch of right zygomatic nerve”

• “Distal epiphysis of of distal phalanx of right little toe”– Extensive spatial relationships in selected areas

• e.g. veins, arteries• Uses

– not designed for one particular use

FMA Example / FMA:62955 ! Anatomical entity is_a FMA:61775 ! Physical anatomical entity is_a FMA:67165 ! Material anatomical entity is_a FMA:67135 ! Anatomical structure is_a FMA:67498 ! Organ is_a FMA:55670 ! Solid organ is_a FMA:55661 ! Parenchymatous organ is_a FMA:55662 ! Lobular organ is_a FMA:13889 ! Pituitary gland is_a FMA:20020 ! Vestibular gland is_a FMA:55533 ! Accessory thyroid gland is_a FMA:58090 ! Areolar gland is_a FMA:59101 ! Lacrimal gland is_a FMA:62088 ! Lactiferous gland is_a FMA:7195 ! Lung is_a FMA:7197 ! Liver is_a FMA:7198 ! Pancreas is_a FMA:7210 ! Testis is_a FMA:76835 ! Accessory pancreas is_a FMA:9597 ! Salivary gland is_a FMA:9599 ! Bulbo-urethral gland is_a FMA:9600 ! Prostate is_a FMA:9603 ! Thyroid gland

Model Organism Anatomy Ontologies

• Typically species-centric– FBbt : Drosophila melanogaster– WBbt: C elegans– ZFA: Danio rerio– XAO: Xenopus– MA: Adult Mouse (no develops from)– EMAP/EMAPA: developing mouse

• Uses– primarily gene expression, also phenotype description– others: Virtual FLy Brain, Phenoscape

• Approach:– use-case driven– practicality over formality– No computable definitions

• (exception FBbt)

Other anatomy ontologies• Developing human

– EHDAA2• Vectors

– TGMA – mosquito– TADS - tick

• Upper ontologies– CARO– AEO

• Domain-specific anatomy ontologies– NIF_Anatomy, NIF_Cell – neuroscience

• Phylogenetic or multi-taxon AOs– HAO – hymeoptera– PO – plant– TAO – telost– AAO – amphibian– SPD – Spider– …– we will return to these later..

Problem• These AOs are not developed in a coordinated

fashion– use of a shared upper ontology does not buy us much– even the 3 mammalian AOs are massively different

• Data annotated using these ontologies effectively becomes siloed

• There is redundancy of effort in areas of shared biology

• Are there lessons from existing ontologies?

Building ontologies that are interoperable across species

• Case Studies– GO– Cell Ontology

Gene Ontology

• Covers all kingdoms of life– viruses, bacteria, archaea– fungi, metazoans, plants

• Covers biology at different scales• Issues

– terminological confusion (e.g. “blood”)– large, difficult to maintain

How does GO deal with taxonomic variation?

• What GO says:– every nucleus is part_of some cell

• What GO does not say:– every cell has_part some nucleus

• wrong for bacteria (and mammalian erythrocytes)

• Take home:– Logical quantifiers are essential to understanding the

ontology– Saying what something is part of is safer than saying

what its parts are

Principle: avoidance of taxonomic differentia

• Not in GO:– vertebrate eye development– insect eye development– cephalopod eye development

• In GO:– eye development

• camera-type eye development• compound eye development

• Exceptions for usability:– cell wall

• fungal-type cell wall [differentia:cross-linked glycoproteins and carbohydrates, chitin / beta-glucan …]

• plant-type cell wall [differentia: cellulose, pectin, …]

} no implication ofhomology

The problem of vagueness in GO

• “limb development”• “wing development”

Adding taxonomic constraints to GO

• GO now includes two additional relations– only_in_taxon– never_in_taxon– See:

• Kusnierczyk, W: Taxonomy-based partitioning of the Gene Ontology, JBI 2008

• Deegan et al: Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development, BMC Bioinformatics 2010

Examples

• lactation only_in_taxon Mammalia (NCBITaxon:40674 )– OWL: lactation in_taxon only Mammalia

• odontogenesis never_in_taxon Aves (NCBITaxon:8782)– OWL: odontogenesis in_taxon only not Aves

• chloroplast only_in_taxon (Viridiplantae or Euglenozoa) (NCBITaxon:33682 or NCBITaxon:33090)

Uses of taxon relationships

1. Clarifying meaning of GO terms2. Detection of errors in electronic and manual

annotation• Automated reasoners• GO previously had chicken genes involved in

lactation, slime mold genes involved in fin regeneration…

3. Providing views over GO• e.g. subset of GO excluding terms that are never in

drosophila

Scalability of single-ontology approach: GO

• How does GO cope with wide taxonomic diversity?– conservation at molecular level, wide diversity of

phenotypes at level of gross anatomical development, physiology, and organismal behavior

• GO Development– Focused on model systems

• “beak development” added only recently

• GO Behavior– Very broad coverage– Some specific terms, e.g. drosophila courtship

Proposal: outsource portions of the ontology

Ontology Views• Ontologies, traditional

– independent standalone resources• Ontologies, new

– interconnected resources– multiple views possible

• Subsetting• Aggregation• Subsetting + Aggregation

– views can be manually specified (e.g. go slims) or automatically constructed

– Limited re-writing possible• e.g. names

Viewssubsetsubset aggregateaggregate

subsetsubset

aggregate+subset

aggregate+subset

subset

“slim”

domain/taxon-specificcut

scatteredsubset

Subset

of GO

vertebrate

subset

Outline

• Case studies– GO: A unified cross-species ontology– Cell Ontology: Unifying multiple existing efforts

• Gross Anatomy

Cell types• GO-Cell Component

– cell parts• CL – cell ontology• Anatomical Ontologies

– Includes cell types:• FBbt (Drosophila)• WBbt (C elegans)• ZFA, TAO (Danio rerio, Teleost)• FMA (Human)• PO (Plant)• FAO (Fungi)

– Excludes cell types:• MA (adult mouse)• EMAPA (developing mouse)• EHDAA2 (developing human)

Overlap (simplified view)

CLCL

MAMAFMAFMA

POPO

ZFAZFA

neuron

alveolarmacrophage

lung

brain

plantspore

NIFcellNIFcell

The Problem

• Duplicated work• No unified view• Confusion for users• Confusion for annotators

Alternative proposals

1. LUMP: Combine into one monolithic CL ontology

2. SPLIT: Taxon-specific cell types in taxon-centric ontologies

a) Obsolete generic cell types currently in tcAOs-vs-

b) Taxon-specific subclasses of generic cell types

LUMP

all cellsall cells

mousemousehumanhuman

plantsplants

fishfish

neuron

alveolarmacrophage

plantspore

CL Lumping proposal

• Advantages:– one stop shopping for CL

• (but this can be done with aggregate views)

• Disadvantages– tcAO IDs well-established– Little advantage to lumping plant cells with animal

cells– Harder to manage editorially– Cross-granular relationships

(Partial) Splitting proposal• Advantages:

– Easier to manage– Sensible subdivision of labor:

• Common cell types in shared common cell ontology– e.g. shared definition of “neuron”

• Taxon-specific subtypes in taxon-centric ontologies• Disadvantages

– Aggregate view is problematic• union of ontologies contains multiple classes labeled “neuron”

– Can be solved by obsoleting existing generic cell classes in tcAOs and replacing by CL IDs

• problem: cross-granular relationships

Current solution for CL: split and retain IDs

• Any cell type shared by two model taxa should be in CL

• tcAOs retain both generic and specific cell type classes– Formally connected to CL via subclass

relationships• or even stronger: taxon-specific equivalent

Example aggregate view

musclecell

musclecell

cellcellmuscleorgan

muscleorgan

i

i

p

musclecell

musclecell

cellcell

i

frontal pulsatile

organmuscle

frontal pulsatile

organmuscle

i

muscle cell

muscle cell

cellcell

i

i

FMAFMA FBbtFBbtCLCLCL-metazoa

Example aggregate+subset view

musclecell

musclecell

cellcell

i

i

musclecell

musclecell

cellcell

i

frontal pulsatile

organmuscle

frontal pulsatile

organmuscle

i

muscle cell

muscle cell

cellcell

i

i

FMAFMA FBbtFBbtCLCLCL-metazoa

Who maintains the connections and how?

• How:– maintained as xrefs for

convenience• Who:

– either tcAO or CL• Synchronization?

– hard– reasoning over aggregate

view

Who maintains the connections?[Term]id: CL:0000584name: enterocytedef: "An epithelial cell that has its apical plasma membrane folded into microvilli to provide ample surface for the absorption of nutrients from the intestinal lumen." [SANBI:mhl]xref: FMA:62122is_a: CL:0000239 ! brush border epithelial cell

[Term]id: ZFA:0009269name: enterocytenamespace: zebrafish_anatomydef: "An epithelial cell that has its apical plasma membrane folded into microvilli to provide ample surface for the absorption of nutrients from the intestinal lumen." [SANBI:curator]synonym: "enterocytes" EXACT PLURAL []xref: CL:0000584xref: TAO:0009269xref: ZFIN:ZDB-ANAT-070308-209is_a: ZFA:0009143 ! brush border epithelial cellrelationship: end ZFS:0000044 ! Adultrelationship: part_of ZFA:0005124 ! intestinal epitheliumrelationship: start ZFS:0000000 ! Unknown

cl.obo

zfa.obo

cl’s responsibilitycl’s responsibility

zfa’s responsibility

zfa’s responsibility

Issues with aggregate view

musclecell

musclecell

cellcell

i

i

musclecell

musclecell

cellcell

i

frontal pulsatile

organmuscle

frontal pulsatile

organmuscle

i

muscle cell

muscle cell

cellcell

i

i

FMAFMA FBbtFBbtCLCL

duplicate names

duplicate nameslattices =

hairballslattices = hairballs

Duplicate names• Searching for “muscle cell” returns

– CL:0000187 ! muscle cell– FBbt:00005074 ! muscle cell– FMA:67328 ! muscle cell– ZFA:0009114 ! muscle cell– NIF_Cell:sao519252327 ! Muscle Cell

• Proposed solutions1. rename in source ontology

• yuck2. make end-user applications smarter

• not practical for n applications3. auto-rename in ontology view

• best solution

Aggregate view[Term]id: CL:0000584name: enterocytedef: "An epithelial cell that has its apical plasma membrane folded into microvilli to provide ample surface for the absorption of nutrients from the intestinal lumen." [SANBI:mhl]xref: FMA:62122is_a: CL:0000239 ! brush border epithelial cell

[Term]id: ZFA:0009269name: zebrafish enterocytedef: "An epithelial cell that has its apical plasma membrane folded into microvilli to provide ample surface for the absorption of nutrients from the intestinal lumen." [SANBI:curator]synonym: "enterocytes" EXACT PLURAL []xref: CL:0000584xref: TAO:0009269xref: ZFIN:ZDB-ANAT-070308-209is_a: CL:0000584 ! enterocyteis_a: ZFA:0009143 ! brush border epithelial cellrelationship: end ZFS:0000044 ! Adultrelationship: part_of ZFA:0005124 ! intestinal epitheliumrelationship: start ZFS:0000000 ! Unknown

cl-metazoa.obo

generated from xref

generated from xref

FMA class not shown, but it

would also subclass

FMA class not shown, but it

would also subclass

rewritten name(or syn – TBD)

rewritten name(or syn – TBD)

latticelattice

Summary: taxon variation in CL

• Current solution is a compromise– Constraints

• integrate with pre-existing tcAO ontologies• these ontologies have links to gross anatomy

– tcAOs loosely integrated with CL– plant cell types should be left to PO– Synchronization remains a challenge

zebrafishzebrafish

caro / allcaro / allcellcell tissuetissue

metazoametazoa

muscletissue

muscletissue

vertebratavertebrata

mesonephrosmesonephros

limblimb

arthropodaarthropoda

antennaantenna

teleostteleost

weberian ossicle

weberian ossicle

mammaliamammalia

mammary gland

mammary gland

nervous systemnervous system

molluscamollusca

footfoot

cephalopodcephalopod

tentacletentacle

mantlemantle

drosophiladrosophila

neuron types XYZ

neuron types XYZ

mushroom body

mushroom body

brachial lobebrachial lobe

NO ponsNO pons

vertebravertebra

vertebralcolumn

vertebralcolumn

circulatory system

circulatory system

appendageappendage

mesodermmesoderm

gutgut

tibiatibia

glandgland

bonebone

skeletaltissue

skeletaltissue

parietalbone

parietalbone

finfin

gonadgonad

tracheatrachea

respiratoryairway

respiratoryairway

cross-ontologylink (sample)

amphibiaamphibia

tibiafibulatibiafibula

larvalarva

shellshellcuticlecuticle

skeletonskeleton

import

mousemouse humanhuman

Lessons for gross anatomy

Conclusions

• Historically anatomy ontologies have been developed by different groups largely in isolation

• The Phenotype RCN should coordinate these efforts

• Dynamic Views• Explicit taxonomic relationships

• end

• Melissa Here

Idealized model (M0)• A single ontology for ontology editors and

consumers• Different editors have editing rights to different

ontology partitions– by taxon– by domain (e.g. neuroscience, skeletal anatomy)

• No taxon-specific subtypes– use structure, function etc as differentia

• Users obtain dynamic views according to their needs

Example M0cellcell tissuetissue

muscletissue

muscletissue

mesonephrosmesonephros

limblimb

antennaantenna

weberian ossicle

weberian ossicle

mammary gland

mammary gland

nervous systemnervous system

mollusc foot

mollusc foot

tentacletentacle

mantlemantle

pupal DN3 period neuron

pupal DN3 period neuron

mushroom body

mushroom body

brachial lobebrachial lobe

ponspons

vertebravertebra

vertebralcolumn

vertebralcolumn

circulatory system

circulatory system appendageappendage

mesoderm

mesoderm

gutgut

tibiatibia

glandgland

bonebone

skeletaltissue

skeletaltissue

parietalbone

parietalbone

finfin

gonadgonad

tracheatrachea

respiratoryairway

respiratoryairway

link(small sample)

tibiafibulatibiafibula

larvalarva

user/editorview

metencephalonmetencephalon

molluscview

neuroview

skeletalview

mammalianview

ventralnervecord

ventralnervecord

Slightly less idealized model (M1)

• Maintain series of ontologies at different taxonomic levels– euk, plant, metazoan, vertebrate, mollusc, arthropod,

insect, mammal, human, drosophila• Each ontology imports/MIREOTs relevant subset

of ontology “above” it– this is recursive

• Subtypes are only introduced as needed• Work together on commonalities at appropriate

level above your ontology

zebrafishzebrafish

Example M1caro / allcaro / allcellcell tissuetissue

metazoametazoa

muscletissue

muscletissue

vertebratavertebrata

mesonephrosmesonephros

limblimb

arthropodaarthropoda

antennaantenna

teleostteleost

weberian ossicle

weberian ossicle

mammaliamammalia

mammary gland

mammary gland

nervous systemnervous system

molluscamollusca

footfoot

cephalopodcephalopod

tentacletentacle

mantlemantle

drosophiladrosophila

neuron types XYZ

neuron types XYZ

mushroom body

mushroom body

brachial lobebrachial lobe

NO ponsNO pons

vertebravertebra

vertebralcolumn

vertebralcolumn

circulatory system

circulatory system

appendageappendage

mesodermmesoderm

gutgut

tibiatibia

glandgland

bonebone

skeletaltissue

skeletaltissue

parietalbone

parietalbone

finfin

gonadgonad

tracheatrachea

respiratoryairway

respiratoryairway

cross-ontologylink (sample)

amphibiaamphibia

tibiafibulatibiafibula

larvalarva

shellshellcuticlecuticle

skeletonskeleton

import

mousemouse humanhuman

Objections to M1

• Biological– homology vs analogy– functional grouping classes

• e.g. respiratory airway, eye

• Practical– tools– what about existing AOs?

• new AOs should be designed for integration from the ground up

Protocol for new AOs

1. Collect draft list of terms2. subdivide roughly into applicability at taxonomic

levels3. request new terms from existing AOs above you4. is a new mid-level AO required?

• yes – collaborate and create, go to 1.5. import subset from next AO above6. Build your ontology

Example: the octopus ontology

• Collect and subdivide terms:– cephalopod: tentacle, brachial lobe, subesophageal mass,

beak, visceropericardial coelum, swim bladder– mollusc: mantle– metazoan: nervous system, muscle tissue

• Mollusc anatomy ontology does not exist– either: (i) find collaborators and create– or: (ii) keep mollusc terms in your ontology for now, but

mark them as possibly migrating upwards• Import terms from mollusc AO(i), or metazoan if (ii) no

mollusc AO

How are things organized now?

• 3 examples:– PO– TAO/ZFA– Uberon

• In Melissa’s talk

Some AOs are cross-granular

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ipmuscle

cell protoplasm

musclecell

protoplasm

subcellular cell tissue and gross anatomy

Cross-granular relationships

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

Cross-granular relationships

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

musclecell

musclecell

cellcell

i

i

CL

Obsoleting generic classes in tcAOs

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

musclecell

musclecell

cellcell

i

i

CL

Migrating cross-granular relationships

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

musclecell

musclecell

cellcell

i

i

CL

“true path” violations

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

musclecell

musclecell

cellcell

i

i

CL FBbt

frontal pulsatile

organmuscle

frontal pulsatile

organmuscle

i

fix

musclecell

musclecell

cellcellmuscleorgan

muscleorgani

p

FMA

ip

musclecell

musclecell

cellcell

i

i

CL FBbt

frontal pulsatile

organmuscle

frontal pulsatile

organmuscle

i

muscle cell AND part of

some human

muscle cell AND part of

some human

PO: Plants

• Single unified ontologies for all plants– cell types and gross anatomy

• Generalized from ontology of flowering plants

TAO and ZFA

• Teleost and Zebrafish

Uberon• Designed to unify existing tcAOs• Uses modern ontology development techniques

– heavily axiomatized = less work for humans, leave it to reasoners

• automated QC• automated classification

• Current size: 5k+ classes• Multiple relationship types• Links to and from GO, CL• Aggregate views possible using xrefs maintained in

uberon

Uberon lessons• Original Design Goals

– Unify metazoan tcAOs for cross-species phenotype queries– Seed initial version from text matching

• Was this a good idea?– metazoans are fairly diverse

• many original dubious grouping classes have been eliminated or split• functional grouping classes remain• tissues, germ layers, etc less controversial • Uberon is really a vertebrate AO in which we’ve added placeholder metazoan

terms – labels are misleading

• high false +ve, false –ve from txt matching• starting from textbook comparative anatomy knowledge would have been

better (give time)