metaSHARK

metaSHARK identifies enzyme-encoding genes in unannotated genomic and transcriptomic sequences and maps them onto metabolic networks to support reconstruction and analysis of organismal metabolic pathways.

Key Features:

• SHARKhunt (Automated gene detection): Identifies enzyme-encoding genes from raw DNA sequences, expressed sequence tags, and genome survey sequences and runs on Linux systems.
• Comparative annotation analysis: Compares predictions to existing annotations such as PlasmoDB and PlasmoCyc for Plasmodium falciparum.
• Low-coverage performance: Demonstrates detection of enzymatic functions at low sequencing coverages (0.5x–7.5x) as evidenced for Eimeria tenella.
• Annotation enhancement: Has identified additional enzymatic functions in Eimeria tenella compared with existing annotation tools.
• SHARKview (Visualization and KEGG integration): Maps metabolic reconstructions onto the KEGG metabolic network for pathway-level visualization.
• Data integration and expression overlay: Accepts metabolic reconstruction outputs from SHARKhunt or other genome annotation tools and incorporates gene expression data to visualize differential expression within predicted metabolic networks.

Scientific Applications:

• Metabolic pathway reconstruction: Identification and mapping of enzyme-encoding genes enables reconstruction and analysis of organismal metabolic capabilities.
• Comparative genomics: Comparison of predictions with existing databases supports validation and expansion of genomic annotations.
• Pathway-specific studies: Applied to targeted pathway analyses such as coenzyme A biosynthesis in Plasmodium falciparum and Eimeria tenella.

Methodology:

SHARKhunt performs automated detection of enzyme-encoding genes from raw DNA sequences and compares predictions to existing annotations (e.g., PlasmoDB, PlasmoCyc), while SHARKview maps metabolic reconstructions onto the KEGG metabolic network and overlays gene expression data.