RiceNet v2: an improved network prioritization server for rice genes

Area of Science:

• Plant Genomics
• Bioinformatics
• Crop Science

Background:

• Rice (Oryza sativa) is a crucial staple food and a model organism for bioenergy crop research.
• A previous genome-scale functional network, RiceNet, was developed for rice and demonstrated utility in dissecting biotic stress responses.
• Significant advancements in publicly available rice genomics data necessitate an updated network resource.

Purpose of the Study:

• To present RiceNet v2, an updated and expanded genome-scale functional network for rice (Oryza sativa ssp. japonica).
• To provide enhanced network prioritization tools for identifying candidate genes in grasses.
• To facilitate hypothesis generation for genetic studies in rice and related species.

Main Methods:

• Construction of RiceNet v2 integrating extensive, up-to-date rice genomics data.
• Implementation of two complementary network prioritization methods: direct neighborhood analysis and context-associated hub identification.
• Inclusion of gene data from Oryza sativa ssp. indica and Arabidopsis thaliana for broader applicability.

Main Results:

• RiceNet v2 encompasses 25,765 genes (70.1% of the coding genome) and 1,775,000 co-functional links.
• The updated network effectively identified candidate genes associated with rice root/shoot development and defense responses.
• Demonstrated utility of RiceNet v2 in identifying genes relevant to grass research.

Conclusions:

• RiceNet v2 represents a significant expansion and update of functional gene networks for rice.
• The enhanced prioritization methods and expanded gene set improve the identification of candidate genes for trait discovery.
• RiceNet v2 serves as a valuable resource for the broader grass research community, aiding in crop improvement and biological studies.