A Practical Guide to Inferring Multi-Omics Networks in Plant Systems

Area of Science:

• Plant Biology
• Bioinformatics
• Systems Biology

Background:

• Gene regulatory networks (GRNs) are crucial for understanding plant biological processes.
• Previous GRN inference often relied on single omics data (e.g., transcriptomics).
• Multi-omics integration, combining data like transcriptomics and (phospho)proteomics, offers a more comprehensive approach.

Purpose of the Study:

• To describe a state-of-the-art method for integrating multi-omics data for GRN inference in plants.
• To uncover novel regulators and signaling pathways by building comprehensive networks.
• To provide a practical guide for analyzing multi-omics data in plant biology.

Main Methods:

• Downloading and processing transcriptomics and (phospho)proteomics data.
• Applying network inference algorithms to integrated multi-omics datasets.
• Utilizing visualization and analysis tools for the resulting integrative networks.

Main Results:

• Demonstration of a protocol for multi-omics GRN inference using plant hormone signaling data.
• Identification of molecular connections and potential novel regulators within the integrated network.
• Validation of the approach's utility for analyzing complex plant signaling pathways.

Conclusions:

• Integrating multi-omics data significantly enhances GRN inference in plants.
• The described protocol provides a valuable resource for bioinformaticians to analyze complex biological systems.
• This approach facilitates a deeper understanding of plant molecular mechanisms and signaling.