AgroLD: a knowledge graph for the plant sciences

Pierre Larmande; Bertrand Pittolat; Ndomassi Tando; Yann Pomie; Bill Gates Happi Happi; Valentin Guignon; Manuel Ruiz

doi:10.1186/s12863-025-01359-6

AgroLD: a knowledge graph for the plant sciences

Pierre Larmande, Bertrand Pittolat, Ndomassi Tando, Yann Pomie, Bill Gates Happi Happi, Valentin Guignon Manuel Ruiz

BMC Genomic Data, Vol.26(1 supplement)

03/10/2025

: https://doi.org/10.1186/s12863-025-01359-6

: PMC12495601

: 41044475

Plant sciences

Knowledge graphs

FAIR

Linked data

Bioinformatics

graph

knowledge base

data set

dataset

shared knowledge

candidate gene

disease resistance

resistance to diseases

adaptive response

FAIR data

FAIR principles

linked data

bioinformatics

climate change

gentoype-phenotype interaction

genotype-phenotype relationship

crop yield

semantic web

Background: The demand for food is expected to grow substantially in the coming years. To address this challenge, especially in the context of climate change, a deeper understanding of genotype-phenotype relationships is crucial for improving crop yields. Recent advances in high-throughput technologies have transformed the landscape of plant science research. However, there is an urgent need to integrate and consolidate complementary data to understand the biological system.Results: We introduce AgroLD, a knowledge graph that uses Semantic Web technologies to seamlessly integrate plant science data. AgroLD is designed to facilitate hypothesis formulation and validation within the scientific community. With approximately 1.08 billion triples, it integrates and annotates data from more than 151 datasets across 19 distinct sources.Conclusion: The overarching goal is to provide a specialized knowledge platform addressing complex biological questions in the plant sciences, including gene participation in plant disease resistance and adaptive responses to climate change.

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https://doi.org/10.1186/s12863-025-01359-6

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: AgroLD: a knowledge graph for the plant sciences
: Pierre Larmande - Université de Montpellier, Diversité, Adaptation et Développement des plantes - DIADE
Bertrand Pittolat - Université de Montpellier, Institut Amélioration Génétique & Adaptation des Plantes méditerranéennes & tropicales - AGAP
Ndomassi Tando - Université de Montpellier, Diversité, Adaptation et Développement des plantes - DIADE
Yann Pomie - Université de Montpellier, Diversité, Adaptation et Développement des plantes - DIADE
Bill Gates Happi Happi - Université de Montpellier, Diversité, Adaptation et Développement des plantes - DIADE
Valentin Guignon - Université de Montpellier, Institut Amélioration Génétique & Adaptation des Plantes méditerranéennes & tropicales - AGAP
Manuel Ruiz - Université de Montpellier, Institut Amélioration Génétique & Adaptation des Plantes méditerranéennes & tropicales - AGAP
: BMC Genomic Data, Vol.26(1 supplement)
: The authors thank the South Green Bioinformatic Platform and the I-Trop IRD supercomputer for their long-standing support. AgroLD is a service delivery plan selected resource by the ELIXIR-FR IFB (French Institute of Bioinformatics). This work was granted access to the HPC resources of IDRIS under the allocation 2024-A0160315119 made by GENCI. Several research projects have supported the AgroLD platform. ETL pipelines have been endorsed by the D2KAB (ANR-18-CE23-0017) and FOOSIN (ANR-19-DATA-0019) projects. The AgroLD Knowledge Graph (Knowledge Graph (KG)) development has been supported by the IBC (Projet ANR-11-BINF-0002) and DIG-AI (ANR-22-CE23-0012) projects. The Web application has been supported by the IFB project (Projet ANR-11-INBS-0013) and IRD funding support.
: 99189695609311
: Institut Amélioration Génétique & Adaptation des Plantes méditerranéennes & tropicales - AGAP; Diversité, Adaptation et Développement des plantes - DIADE
: English
: Journal article
: hal-05501420