LeGOO

LeGOO organizes heterogeneous Medicago truncatula omics and genetics data into a graph-oriented database to enable integration and cross-referencing of gene identifiers and published relations.

Key Features:

• Graph-oriented database: Represents biological information in a flexible graph format to encode relationships among genes and datasets.
• Identifier correlation: Correlates multiple identifiers for the same gene across heterogeneous datasets to enable cross-referencing.
• Multi-omics and genetics aggregation: Aggregates transcriptomics, other omics, genetics, and reverse genetics datasets across four Medicago truncatula genome sequence releases.
• Publication-derived relations: Incorporates over 200,000 relations extracted from 298 peer-reviewed publications.
• Integration with Mt5.0: Links to the Mt5.0 genome browser and incorporates gene functional annotations, expression profiles, methylome data, natural diversity information, and available insertion mutants.
• Data relationship visualization: Facilitates integration and visualization of complex data relationships for synthesis and interpretation.

Scientific Applications:

• Transcriptomics meta-analysis: Integration and cross-study analysis of heterogeneous transcriptomics datasets in Medicago truncatula.
• Gene function synthesis: Synthesis of omics, genetics, and reverse genetics evidence across multiple genome releases to support gene function inference.
• Symbiosis research: Analysis of Rhizobium-legume symbiosis and nitrogen-fixing interactions.
• Mycorrhizal studies: Investigation of arbuscular mycorrhizal endosymbioses.
• Developmental biology: Study of root, nodule, and seed development processes.
• Stress and pathology: Investigation of pathogenic interactions and responses to abiotic stress.
• Natural diversity and mutants: Exploration of natural diversity and available insertion mutants in the context of genomic annotations.
• Literature-derived network analysis: Construction and analysis of relational networks derived from publication-based relations.

Methodology:

Implements a graph-oriented database that aggregates and correlates multiple gene identifiers, ingests >200,000 relations from 298 peer-reviewed publications, and links integrated datasets to the Mt5.0 genome browser including gene annotations, expression profiles, methylome data, natural diversity information, and insertion mutant records.