Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case study on grain legumes - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Conference Poster Year : 2023

Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case study on grain legumes

Baptiste Imbert
Jonathan Kreplak
Raphaël Flores
Grégoire Aubert
Judith Burstin
Nadim Tayeh

Abstract

While the continuing decline in genotyping and sequencing costs has largely benefited plant research, some key species for meeting the challenges of agriculture remain largely understudied. As a result, heterogeneous datasets for different traits are available for a significant number of these species. As gene structures and functions are to some extent conserved through evolution, comparative genomics can be used to transfer available knowledge from one species to another. However, such a translational research approach is complex due to the multiplicity of data sources and the non-harmonized description of the data. Here, we provide two pipelines, referred to as structural and functional pipelines, to create a framework for a NoSQL graph-database (Neo4j) to integrate and query heterogeneous data from multiple species. We call this framework Orthology-driven knowledge base framework for translational research (Ortho_KB). The structural pipeline builds bridges across species based on orthology. The functional pipeline integrates biological information, including quantitative trait loci (QTL), RNA-seq datasets, and uses the backbone from the structural pipeline to connect orthologs in the database. Queries can be written using the Neo4j Cypher language and can, for instance, lead to identify genes controlling main traits across species. To explore the possibilities offered by such a framework, we populated Ortho_KB to obtain OrthoLegKB, an instance dedicated to legumes. The proposed model was evaluated by studying the conservation of a flowering-promoting gene. Through a series of queries, we have demonstrated that our knowledge graph base provides an intuitive and powerful platform to support research and development programmes
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Dates and versions

hal-04279248 , version 1 (10-11-2023)

Identifiers

  • HAL Id : hal-04279248 , version 1

Cite

Baptiste Imbert, Jonathan Kreplak, Raphaël Flores, Grégoire Aubert, Judith Burstin, et al.. Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case study on grain legumes. JOBIM 2023 Edition multisite, Jun 2023, Nancy, Nice,, France. ⟨hal-04279248⟩
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