Trans-Omics: How To Reconstruct Biochemical Networks Across Multiple 'Omic' Layers

Area of Science:

• Biochemistry
• Systems Biology
• Bioinformatics

Background:

• Reconstructing global biochemical networks is crucial for understanding cellular functions.
• Integrating multi-omic data presents a significant challenge in systems biology.
• Existing methods often lack a holistic approach to biochemical network analysis.

Purpose of the Study:

• To propose and validate a novel 'trans-omic' analysis framework.
• To enable the reconstruction of global biochemical networks across multiple omic layers.
• To characterize these networks based on static and dynamic properties.

Main Methods:

• Developed computational methods for integrating multi-omic measurements.
• Utilized prior knowledge of biochemical interactions to connect diverse data types.
• Applied network analysis to metabolism-centric case studies.
• Introduced a trans-ome-wide association study (trans-OWAS) framework.

Main Results:

• Demonstrated the reconstruction of biochemical trans-omic networks by connecting multi-omic data.
• Characterized the static and dynamic nature of reconstructed trans-omic networks.
• Showcased the utility of trans-omic analysis in metabolism-centric studies.
• Established trans-OWAS for linking phenotypes to comprehensive trans-omic networks.

Conclusions:

• Trans-omic analysis provides a powerful approach for global biochemical network reconstruction.
• The framework effectively integrates multi-omic data, revealing system-level insights.
• Trans-OWAS offers a novel method to study complex diseases influenced by genetic and environmental factors.