# Harnessing Ontologies to Improve Translational Research: An Application in the Knowledge Graph Framework Ortho_KB

Baptiste Imbert, Jonathan Kreplak, Nadim Tayeh

► To cite this version:

Baptiste Imbert, Jonathan Kreplak, Nadim Tayeh. Harnessing Ontologies to Improve Translational Research: An Application in the Knowledge Graph Framework Ortho_KB. Plant & Animal Genome Conference (PAG), Systems Biology and Ontologies Workshop, Jan 2024, San Diego (CA), United States. hal-05249638

HAL Id: hal-05249638

https://hal.inrae.fr/hal-05249638v1

Submitted on 11 Sep 2025

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# Harnessing Ontologies to Improve
Translational Research: An Application in
the Knowledge Graph Framework Ortho_KB

## Systems Biology and Ontologies

Baptiste Imbert

3rd year PhD student

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>

- nitrogen source for next crops

- diversification crops in rotations

## Agronomy

### Seed composition

<figure><img src="image_4.png" /></figure>

- high protein content

- high starch content

<figure><img src="image_5.png" /></figure>

### Food

<figure><img src="image_6.png" /></figure>

### Globally consumed

- ~11 main crop species used worldwide

Semba et al., Global Food Security, 2021

<figure><img src="image_7.png" /></figure>

### Feed

<figure><img src="image_8.png" /></figure>

## Nutrition
<figure><img src="image_9.png" /><figcaption>Leaf weevils</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Bruchids</figcaption></figure>

## BIOTIC STRESSES

<figure><img src="image_11.png" /><figcaption>Root pathogens</figcaption></figure>

<figure><img src="image_12.png" /></figure>

## ABIOTIC STRESSES

<figure><img src="image_13.png" /><figcaption>Heat / drought</figcaption></figure>

and many others...
# We study conserved genetic determinism in legumes

* Most stresses are common to several legume species

* We hypothesize that stress resistance/tolerance in close species emerges from a conserved genetic determinism

* A piece of information obtained on one species under particular experimental conditions can be:

* compared with information obtained from separate datasets

* transferred to other close species (TRANSLATIONAL RESEARCH)

barrel medic

<figure><img src="image_14.png" /></figure>

lentil

faba bean
# We study conserved genetic determinism in legumes

* Most stresses are common to several legume species

* We hypothesize that stress resistance/tolerance in close species emerges from a conserved genetic determinism

* A piece of information obtained on one species under particular experimental conditions can be:

* compared with information obtained from separate datasets

* transferred to other close species [TRANSLATIONAL RESEARCH]

*How can we best take advantage of heterogeneous datasets and conduct successful translational research?*

<figure><img src="image_15.png" /></figure>
We developed **Ortho_KB**, a graph framework based on **neo4j**, to integrate **genetic** and **expression** data from multiple species and perform **translational research**.

<figure><img src="image_16.png" /></figure>
We developed a framework for translational research

We developed **Ortho_KB**, a graph framework based on **neo4j**, to integrate **genetic** and **expression** data from multiple species and perform **translational research**.

<figure><img src="image_17.png" /></figure>
* From research papers and data from the lab, we observe:

* difference in the scientific vocabulary used

* Issue of synonyms

<figure><img src="image_18.png" /><figcaption>Faba bean seeds infested
by bruchids</figcaption></figure>

bruchid beetles bruchid weevil

bruchids pea weevil
* From research papers and data from the lab, we observe:

* difference in the scientific vocabulary used

* **Issue of synonyms**

<figure><img src="image_19.png" /><figcaption>Faba bean seeds infested
by bruchids</figcaption></figure>

bruchid beetles bruchid weevil

bruchids pea weevil

* **Inconsistencies in the spelling of the trait name**

* resistance to seed weevil

* seed weevil resistance
* From research papers and data from the lab, we observe:

* difference in the scientific vocabulary used

* multiplicity of the methods used to measure a single trait

<figure><img src="image_20.png" /><figcaption>Faba bean seeds infested
by bruchids</figcaption></figure>

resistance to bruchids

percentage of seeds
showing infestation

can the larvae
**get inside** the
seed?

percentage of
larval mortality

can the larvae
**develop in the**
seed?
* From research papers and data from the lab, we observe:

* difference in the scientific vocabulary used

* multiplicity of the methods used to measure a single trait

<figure><img src="image_21.png" /></figure>

Faba bean seeds infested
by bruchids

<figure><img src="image_22.png" /></figure>

percentage of seeds
showing infestation

can the larvae
**get inside** the
seed?

<figure><img src="image_23.png" /></figure>

percentage of
larval mortality

can the larvae
**develop in the**
seed?

Ontologies?
# Neo4j can handle the integration of ontologies

* Genes are functionally annotated by transferring annotation using sequence similarity, with the **Gene Ontology** (The Gene Ontology Consortium, *Genetics*, 2023) and **MapMan** (Schwacke et al., *Molecular Plant*, 2019)

Protein
modification

<figure><img src="image_24.png" /></figure>
# Neo4j can handle the integration of ontologies

* Genes are functionally annotated by transferring annotation using sequence similarity, with the **Gene Ontology** (The Gene Ontology Consortium, *Genetics*, 2023) and **MapMan** (Schwacke et al., *Molecular Plant*, 2019)

Protein
modification

<figure><img src="image_25.png" /></figure>

* These ontologies are included in the graph of the database using the *neosemantics* plugin for Neo4j:

* each ontology term is a node with properties (name, label, uri)

* terms are linked to their parent node(s) by a **subClassOf** (SCO) edge
# Neo4j can handle the integration of ontologies

* Genes are functionally annotated by transferring annotation using sequence similarity, with the

**Gene Ontology** (The Gene Ontology Consortium, *Genetics*, 2023) and **MapMan** (Schwacke et al., *Molecular Plant*, 2019)

Protein modification

<figure><img src="image_26.png" /></figure>

* These ontologies are included in the graph of the database using the *neosemantics* plugin for Neo4j:

* each ontology term is a node with properties (name, label, uri)

* terms are linked to their parent node(s) by a **subClassOf** (SCO) edge

*How to precisely annotate complex entities like RNA-seq conditions and genetic loci (QTL mapping, GWAS) with ontologies?*
* Ontologies that allow to describe metadata for a variety of species are needed and used

* RNA-seq conditions are annotated using ontologies from

**Planteome** (Cooper et al., *Nucleic Acids Res*, 2018):

* **anatomy**: PO

* **growth stage**: PO

* **stress**: PECO

* **growth structure**: PECO

**PO**: Plant Ontology

**PECO**: Plant Experimental Condition Ontology

<figure><img src="image_27.png" /></figure>
# We enrich legume datasets with ontologies

* Support for annotating RNA-Seq metadata with ontologies is already built into the Ortho_KB framework

* Work is currently in progress for annotating *genetic* data with ontologies

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

Check the poster PE0696 for more info!

<figure><img src="image_30.png" /></figure>

Access the **OrthoLegKB** instance!

<figure><img src="image_31.png" /></figure>
# Annotation with ontologies is a slow but useful process

* QTL are being manually annotated with the same descriptors as for RNA-seq, with the addition of trait descriptors using the Plant Trait Ontology (TO)

* **1,125** QTL are currently integrated in the development instance

<figure><img src="image_32.png" /></figure>

Yes

No

## Successful trait annotation

1,109

16

* Some terms are missing in Planteome ontologies

* Temporary terms connected to to main ontologies are created

* Actions are required to manage this aspect

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

Node properties

<figure><img src="image_35.png" /></figure>

Manual

Resource

TO

<id>

829001

<figure><img src="image_36.png" /></figure>

definition

Evaluation of larval development of seed beetles after Bruchus exposure (to add to PECO) based on the damages inflicted to the seed (PO:0009010) or th... Show all

<figure><img src="image_37.png" /></figure>

label

seed beetle larval development trait

<figure><img src="image_38.png" /></figure>

name

TO_0000261_1_1

<figure><img src="image_39.png" /></figure>

status

Unofficial substitute term. Should be replaced with an official term.

<figure><img src="image_40.png" /></figure>

uri

http://purl.obolibrary.org/obo/TO:0000261_1_1

<figure><img src="image_41.png" /></figure>
* Ortho_KB can be queried in Cypher for QTL connected to TO terms

<figure><img src="image_42.png" /></figure>

MATCH (q:QTL)-[rel:HAS_TRAIT]->(trait:TO)
RETURN rel.original_desc, trait.label

<figure><img src="image_43.png" /></figure>

<table><thead><tr><td>Original trait name</td><td>TO trait name</td></tr></thead><tbody><tr><td>TGW</td><td>1000-grain weight</td></tr><tr><td>Thousand seed weight</td><td>1000-grain weight</td></tr><tr><td>1000 seed weight (g)</td><td>1000-grain weight</td></tr></tbody></table>

<figure><img src="image_44.png" /></figure>

It is now possible to easily retrieve all the genetic loci associated with the thousand seed weight
* **Transitivity** allows to collect QTL annotated with the term "seed beetle resistance" or any more specific term

<figure><img src="image_45.png" /></figure>

MATCH (trait:TO { label: "seed beetle resistance" })

CALL n10s.inference.nodesInCategory(trait, {
inCatRel: "HAS_TRAIT", subCatRel: "SCO" }) yield node as qtl

RETURN qtl, trait

<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /><figcaption>Faba bean seeds infested
by bruchids</figcaption></figure>
1

We required a database to efficiently query genetic and -omic data → we created **Ortho_KB**

3

The use of ontologies greatly helps the exploration of our translational research database

2

Consistency of metadata descriptors was crucial:

* Planteome ontologies allow us to annotate most entities for our needs

* Some temporary measures were implemented to deal with imprecise or missing ontology terms

<figure><img src="image_48.png" /></figure>
* Deal with **missing ontology terms**:

* Count on available species-specific ontologies which have mappings to the TO to achieve more granular descriptions (Laporte et al., *ICBO Workshop*, 2016)

* Communicate with the Planteome community to introduce new terms

* Accelerate the **pace of annotation** with ontologies, currently done by users themselves:

* Encourage the use of ontologies in research papers to promote easy integration of data into databases such as Ortho_KB
<figure><img src="image_49.png" /></figure>

Thanks to all the ECP team and
especially to:

* Nadim Tayeh (supervisor)

* Judith Burstin (co-supervisor)

* Jonathan Kreplak (bioinformatics engineer)

<figure><img src="image_50.png" /></figure>

RÉPUBLIQUE
FRANÇAISE

Liberté
Égalité
Fraternité

<figure><img src="image_51.png" /></figure>

anr

INRAE

CULTIVER
PROTÉGER
autrement

<figure><img src="image_52.png" /></figure>

SPECIFICS

<figure><img src="image_53.png" /></figure>

a special thanks to Sushma Naithani and Laurel
Cooper for letting me present my work here!
SUPPLEMENTARIES
# Ontologies allow to study pleiotropy using transitivity

Yield and flowering traits are known to be linked. We can query the database for all QTL associated to these traits to study their colocalization.

QTL found:
SW11_3_1,
SW06_4_1, SW04_3_1

Klein et al. 2020

3 large QTL intervals are associated to seed weight

<figure><img src="image_54.png" /></figure>

The locus in pea is also encompassed by the SN06_2_1 QTL annotated as *grain number per plant*. According to the TO, this is a morphology trait, not a yield trait!

<figure><img src="image_55.png" /><figcaption>faba bean
chr03</figcaption></figure>

yield trait
flowering time trait

<figure><img src="image_56.png" /><figcaption>Sallam et al. 2016</figcaption></figure>

seed
yield trait

days to
flowering trait

<figure><img src="image_57.png" /><figcaption>pea
chr06</figcaption></figure>

<figure><img src="image_58.png" /></figure>

syntenic QTL
in pea?

3 colocalizing QTL span a single gene