Towards a Reference Plant Trait Ontology for Modeling Knowledge

of Plant Traits and Phenotypes

Elizabeth Arnaud

, Laurel Cooper

, Rosemary Shrestha

, Naama Menda

, Rex T. Nelson

Luca Matteis

, Milko Skofic

, Ruth Bastow

, Pankaj Jaiswal

, Lukas Mueller

and Graham McLaren

Bioversity International, via dei Tre Denari, 174/a, Maccarese, Rome, Italy

Dept. of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, U.S.A.

Centro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT), Texcoco, Edo. de México, Mexico

GARNet, School of Life Sciences, University of Warwick, Wellesbourne, Warwick, CV35 9EF, U.K.

USDA-ARS CICGRU, 1012 Crop Informatics and Genetics Laboratory, Ames, IA 50011, U.S.A.

Boyce Thompson Institute for Plant Research, Tower Road, Ithaca, NY 14850, U.S.A.

Generation Challenge Program, ℅ CIMMYT, Texcoco, Edo. de México, Mexico

Keywords: Agriculture, Plant Phenotype, Plant Trait Ontology, Integrated Breeding Knowledge, Community of

Practice.

Abstract: Ontology engineering and knowledge modeling for the plant sciences is expected to contribute to the

understanding of the basis of plant traits that determine phenotypic expression in a given environment.

Several crop- or clade-specific plant trait ontologies have been developed to describe plant traits important

for agriculture in order to address major scientific challenges such as food security. We present three

successful species and/or clade-specific ontologies which address the needs of crop scientists to quickly

access a wide range of trait related data, but their scope limits their interoperability with one another. In this

paper, we present our vision of a species-neutral and overarching Reference Plant Trait Ontology which

would be the basis for linking the disparate knowledge domains and that will support data integration and

data mining across species.

1 INTRODUCTION

Agricultural crop- or clade-specific databases

provide comparative phenotypic and genotypic

information that helps elucidate functional aspects of

plant and agricultural biology. For researchers, it is

necessary to have seamless access to various

distributed and interrelated data sources such as

genetic, trait, genotypic and experimental data to

explore biologically interesting questions.

Agricultural centers have a huge amount of

historical data that reflects a sound scientific

knowledge of crop biology and physiology. Plant

scientists are producing large volumes of data on

genetic mapping, gene expression, and full genome

sequences that can be used to gain better insights

into plant traits and phenotypes.

Traditionally, phenotype information has been

captured in a free text manner, which cannot be

easily indexed and presents an obstacle to data

sharing. One approach to overcome this obstacle is

through the annotation of data using a common

controlled vocabulary or “ontology" (Ashburner et

al., 2000; Smith et al., 2007). An ontology is a way

of representing knowledge in a given domain that

includes a set of terms to describe the classes in that

domain, as well as the relationships among terms.

Each term can be associated with an array of data

such as names, definitions, identification numbers,

and genes involved. Ontologies are fundamental for

unifying diverse terminologies, and are increasingly

used by scientists in many fields and by the online

web search engines. In an ontology, terms are

carefully defined and are related to each other using

logically defined relationships as defined by the

OBO Foundry Relations Ontology (RO; Smith et al.,

2005) and supported by the prevailing knowledge.

Such structured ontology trees allow researchers to

220

Arnaud E., Cooper L., Shrestha R., Menda N., Nelson R., Matteis L., Skoﬁc M., Bastow R., Jaiswal P., Mueller L. and McLaren G..

Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes.

DOI: 10.5220/0004138302200225

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2012), pages 220-225

ISBN: 978-989-8565-30-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

use terms consistently in scientific publications or

standardized handbooks on quality/trait evaluations,

and to search for and integrate data linked to these

terms in anatomical, genetic, genomic, and other

types of biological databases.

2 THE SEMANTIC LANDSCAPE

OF GENOTYPE, PHENOTYPE,

AND TRAIT

The concepts of genotype and phenotype are among

the most fundamental in all of genetics,

developmental and evolutionary biology. Plant

breeding, particularly requires the integration of

these concepts to understand how and why

phenotypic expression varies with the environment.

A multidisciplinary approach will help address such

complex questions. Crop modeling can play a

crucial role and requires knowledge integration,

which means that molecular geneticists,

physiologists and crop modelers can share their

respective ‘language’ (Wollenweber, 2005) and

ontology engineering provides a mean to achieve

this.

A genotype of an organism is the inherited

instructions it carries within its genetic code (i.e. the

genome). A genotype can be characterized by

sequencing genes, as well as by genetic mapping to

characterize variations in the DNA sequence. Not all

organisms with the same genotype look or act the

same way because appearance and behavior are

modified by environmental and developmental

conditions. Likewise, not all organisms that look

alike necessarily have the same genotype.

A phenotype (from Greek phainein, 'to show' +

typos, 'type') is the composite of an organism's

observable characteristics such as its morphology,

development, biochemical or physiological

properties, phenology, behavior, and products of

behavior (Wollenweber, 2005). Phenotypes result

from the expression of an organism's genes and

develop over time as the outcome of cumulative

causal interactions between genotype and

environment (Malosetti et al, 2011). The phenotype

comprises the observable characteristics and the

expression of particular traits in a particular

organism or organism part. It is a composite of an

entity (e.g. fruit) and an attribute (e.g. shape) with a

value (e.g. round):

Entity + Attribute = Trait

(1)

Entity + (Attribute + Value) =

Phenotype (observed)

(2)

Example:

fruit + (shape + round) = fruit shape round

-> round fruit

3 ENGINEERING COMMON

SEMANTIC FRAMEWORK - A

REFERENCE PLANT TRAIT

ONTOLOGY

Complex free text descriptions used for phenotypes

are almost impossible to index and retrieve in a

useful way unless ontological concepts are used for

the metadata and text tagging. The semantic problem

is that, depending on the plant species, the same trait

can be given different names. For instance, the trait

term seed color is referred to as kernel color in

maize, grain or caryopsis color in rice and pod color

in beans but these are all based on the same

phenotypic descriptor- fruit color. Data integration

and/or mining of plant trait data require the

identification of equivalent concepts used by the

various agricultural research communities.

Having phenotype data scattered in various

online databases using their own vocabularies for

annotation prevents the integration and comparison

of phenotypic and genetic data between species and

even across taxa.

The solution to this problem is the development

of a true Reference Plant Trait Ontology (Ref-TO;

Figure 1). The basis of the proposed Ref-TO is the

existing Plant Trait Ontology (TO) (Figure 2) which

will integrate and link many crop- and clade-specific

trait ontologies. Initially the focus will be on

integrating the three crop or clade-specific

ontologies described below, but the long-term goal

is to describe traits of all plant species.

The development and expansion of such a

universal ontology will rely on the long-term

involvement of the various plant research

communities for maintaining the species-specific

terms and applying the ontological terms to their

data annotations.

TowardsaReferencePlantTraitOntologyforModelingKnowledgeofPlantTraitsandPhenotypes

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Figure 1: Vision of a Reference Plant Trait Ontology (Ref-TO) to link the crop- and clade-specific trait ontologies.

4 SPECIFIC ONTOLOGIES

PROVIDE PLANT PHENOTYPE

AND TRAIT INFORMATION

The agricultural research community requires crop

trait information, which may contribute to the

comparative analysis of genomes and to the

selection of promising plant material by crop

breeders.

4.1 Soybean Trait Ontology (SOY)

A controlled vocabulary (ontology) describing

soybean traits is under active development (SOY),

as part of SoyBase (http://soybase.org; Grant et al,

2010), the USDA-ARS soybean genetic and

genomic database, a professionally curated

biological database for soybean genetic and

molecular data. This controlled vocabulary uses

terms familiar to the soybean community to facilitate

its use. Genetic markers, QTL and soybean gene

data are linked to the SOY controlled vocabulary but

also cross-referenced to the Plant Trait Ontology

(TO) for extension to other crop species. Queries can

be initiated at the SoyBase portal using SOY, TO

and Plant Ontology (PO) identifiers to access

soybean data regarding soybean traits and/or

anatomical structures.

In anticipation of further development of the TO,

web services are also being developed to allow

programmatic access to soybean data using soybean

(SOY), Plant Trait (TO), Plant Ontology (PO) or

Gene Ontology (GO) identifiers. Semantic web

queries of SoyBase data are also available using

SSWAP (Gessler et al. 2009) services (Nelson et al.

2010).

4.2 Solanaceae Phenotype Ontology

(SPO)

As part of the community-driven SOL Genomics

Network (SGN;

http://solgenomics.net; Bombarely

et al., 2011, Menda 2008), an ontology for

Solanaceae phenotypes (SPO) has been developed to

describe traits and phenotypes scored by plant

breeders in the field. The SGN is a clade-oriented

comparative genomic database, focusing on the

Euasterid clade, including the Solanaceae family,

which has many important crop and model plants

such as tomato (Solanum lycopersicum), potato

(Solanum tuberosum), eggplant (Solanum

melongena), and pepper (Capsicum annuum).

Since many Solanaceae phenotype ontology

terms are pre-composed, these are also mapped to

one or more Plant Ontology (PO) terms, and the

Phenotype Quality Ontology (PATO) terms (e.g. the

SPO term ‘late fruit ripening’ is mapped to the

PATO term ‘delayed’ and PO growth stage term

‘ripening’ and plant anatomy term ‘fruit’).

4.3 The Crop Ontology (CO)

The Crop Ontology (CO) (http://

www.cropontology.org/) of the Generation

Challenge Programme (GCP) aims to provide a

semantic framework to the computational

architecture of the knowledge-based system called

KEOD2012-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

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the Integrated Breeding Platform (https://

www.integratedbreeding.net/).

The CO is designed to provide a structured,

controlled vocabulary for the phenotype of

important crops for food and agriculture and is

collectively developed by various Crop

Communities, associated with the centers of the

Consultative Group on International Agricultural

Research.

The aim is to foster consistency in annotation

and to aggregate datasets containing huge amount of

historic phenotypic data on a large range of crops

not adequately represented in the PO and the TO

(Shrestha et al., 2011). Crops currently included are:

banana, cassava, common bean, cowpea, groundnut,

maize, potato, rice, sorghum, soybean, wheat.

Barley, pigeon pea and yam will be added in 2013.

The CO describes agronomic, morphological,

physiological, quality, and abiotic and biotic stress

related traits of several crops using a number of

common relationship types. However, relations were

created such as ‘method_ of’, ‘scale_of’, and

’derived_from’ to meaningfully describe the traits

and their relations to methods and scales.

The CO contributes to the expansion of the Plant

Ontology (PO) and to the Plant Trait Ontology (TO),

through submission of new terms. Web links

between CO terms cross-referenced with major

agronomic information sources provide online

access to data annotated with similar ontological

terms.

The online Crop Ontology is a public resource

that acts as an open-source server for names of traits.

5 TOWARDS THE REFERENCE

TRAIT ONTOLOGY

5.1 The Trait Ontology (TO) and the

Plant Ontology (PO)

International collaborative efforts already exist to

develop multi-species ontologies for example the

Plant Ontology (PO) and Trait Ontology (TO). The

TO (Figure 2) describes phenotypic traits in plants.

In its current form, the TO is organized around eight

main classes, allowing it to encompass a broad range

of plant traits and be species-neutral. The TO is

being actively developed in close cooperation with

the Plant Ontology, which describes the

morphological and anatomical structures of all

plants, as well as the stages of development of the

plant structures. (Avraham et al, 2008, Jaiswal,

2005, Walls et al, 2012).

TO terms are “precomposed” (Entity-Quality

(EQ) form) using terms from the PO and the Gene

Ontology (GO), along with other ontologies such as

the Phenotype Quality Ontology (PATO), the

ontology of Chemical Entities of Biological Interest

(ChEBI), the Plant Environmental Conditions

Ontology (EO) and the Plant Disease Ontology

(PDO; currently under development), as well as

others.

The PO itself has been extensively revised over

the past two years, with the focus on expanding the

scope of the ontology to span all green plants. We

can apply the lessons learned from the PO

development to developing the TO as a reference

trait ontology for all plant species. Further

development of the TO is necessary to develop the

across-species terms that will be useful to

semantically link the crop- and clade- specific

ontologies to one another.

5.2 Common Platforms for Data

Integration through Web Services

All the crop- and clade-specific ontologies, as well

as the PO and TO, are being developed using a

common platform, the OBO-Edit software (Day-

Richter et al, 2007) developed and promoted by the

Gene Ontology (GO; The Gene Ontology

Consortium, 2010). This facilitates cross-linking.

All these ontologies also use a number of common

relationship types. The most common are ‘is_a’ and

‘part_of’ relations assigned by OBO-foundry (Smith

et al, 2005).

The ontologies presented in this paper are

available on the BioPortal site of the National Center

for Biomedical Ontology (NCBO) (http://

bioportal.bioontology.org) for public access, as well

as on their respective sites.

Via various processors or extractors, Resource

Description Framework (RDF; http://

www.w3.org/RDF/) can capture and convey the

metadata or information in unstructured (e.g. text),

semi-structured (e.g. HTML documents) or

structured sources (e.g. standard databases). This

makes RDF a perfect solution for representing data

that exists in various databases. RDF structures

enable synonyms or aliases to be easily mapped to

the same types or concepts. This kind of semantic

matching is a key capability of the semantic Web.

Currently, both the Plant Ontology and Crop

Ontology are available in RDF.

TowardsaReferencePlantTraitOntologyforModelingKnowledgeofPlantTraitsandPhenotypes

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Figure 2: A model of the existing Plant Trait Ontology (TO) showing the species-neutral approach and interaction with the

Gene Ontology (GO), the Phenotype Quality Ontology (PATO), the ontology of Chemical Entities of Biological Interest

(ChEBI), the Plant Environmental Conditions Ontology (EO) and the Plant Disease Ontology (PDO).

The final objective of a programmatic use of a

trait ontology is to support the integration of data

sets for given traits, retrieval through web services

and the discovery of any piece of information that is

annotated with analogous trait concepts. Currently,

the existence of many distinct ontologies results in a

discontinuous semantic framework. Each ontology is

presently taking further steps to use web services to

synchronize trait names and OBO files. For

example, the GCP crop databases and field books for

breeders are synchronized for data annotations with

CO through the API.

Developers who wish to use the Plant Ontology

in mobile or desktop applications can now access

terms, synonyms, definitions, and comments using

PO web services. Built with PHP (http://

www.php.net/) and modelling aspects of RESTful

software architecture (Fielding, 2000), these services

provide PO data encoded in JavaScript Object

Notation (JSON) format, a widely-used standard for

providing data over the internet. The PO plans to

continue to develop these web services and

envisions the Reference Plant Trait Ontology being

offered in a similar way in the future.

6 CONCLUSIONS

A Reference Plant Trait Ontology is necessary to

unify the clade- and crop- specific ontologies and

provide the semantic framework for querying,

reasoning and data mining across the various species

databases. Therefore, our objective is to develop the

Reference Plant Trait Ontology by improving and

expanding the existing Plant Trait Ontology. Our

vision for the future development of the Ref-TO is

one of an international consortium of the clade- and

crop-specific trait ontologies, and would also include

representatives from the model plant database

groups (such as GARNet, NASC and TAIR for

Arabidopsis) and representatives from the Plant

Ontology and Gene Ontology.

Cross-referencing species-specific terms will

unite the ontologies into a network and, by linking

plant phenotypes and traits to information, images

and documentation across species and even taxa, the

community is building a knowledge base with a

broad reach, which will be useful to elucidate

functional aspects of plant and agricultural biology.

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