Functional analysis of legume genome arrays

Area of Science:

• Bioinformatics
• Plant Genomics
• Functional Genomics

Background:

• Functional analysis of post-genomics data is crucial for understanding biological processes.
• Existing ontological tools often require well-annotated genomes, limiting their application.
• Legume research benefits from specialized tools for gene expression data analysis.

Purpose of the Study:

• To provide an overview of two complementary tools, MapMan and GeneBins/PathExpress, for functional analysis of legume gene expression data.
• To highlight the utility of these tools for organisms with varying genome annotation levels.

Main Methods:

• MapMan: A stand-alone tool for visualizing large datasets on metabolic pathways and biological processes.
• GeneBins/PathExpress: Tools for enrichment analysis of functional groups and metabolic networks.
• Utilizing the KEGG database for analysis across different organisms, including legumes.

Main Results:

• MapMan can be adapted for non-model plants like legumes by mapping sequences to orthologs.
• GeneBins and PathExpress offer organism-independent functional enrichment analysis based on KEGG pathways.
• These tools facilitate the interpretation of gene expression data in legumes.

Conclusions:

• MapMan and GeneBins/PathExpress provide valuable, complementary approaches for legume functional genomics.
• These bioinformatics tools enhance the analysis of gene expression data, supporting biological discovery in plants.
• The described methods are applicable to a wide range of organisms, extending beyond model plants.