Bread wheat is the staple food for over 30% of world's population. It serves as a rich source of carbohydrates and protein. The 2016 release of the whole genome assembly for bread wheat, has facilitated genetic analysis of this important crop plant. To enhance our understanding of the genetic networks controlling key biological processes of bread wheat we have constructed a genome-scale functional gene network.

WheatNet is a first genome-scale functional gene network of bread wheat (Triticum aestivum). It was generated by integrating 20 individual omics datasets. Functional gene networks reconstructs the biological pathway of an organism by connecting genes with functional similarity. Therefore, WheatNet provides a blueprint of genetic architecture in wheat which aids our knowledge in how its genetic elements function. WheatNet web database provides all the individual networks generated by each datasets in addition to the integrated network. To address for homeologous genes, WheatNet was constructed by clustering the genes to form groups. These gene groups were clustered with orthoMCL by using the sequence similarity among genes that reside in chromosomes A,B and D. The gene groups and their constituting genes can be found in the download page.

By applying graph theory algorithms, WheatNet can predict and prioritize genes that are associated with specific traits. We have implemented two network based candidate prioritization methods in WheatNet database.
1) Gene prioritization based on network direct neighborhood takes in a set of guide genes and ranks the candidate genes by measuring the connectivity to the guide genes based on direct-neighborhood method. The guide genes would be user-submitted genes that are known to function in some particular pathway or show similar phenotypic outcome when mutated. WheatNet searches for candidate genes that are connected to the guide genes and prioritizes them to give ranks. Thus, genes that are highly ranked would be a strong candidate associated to a biological pathway.
2) Gene prioritization based on context-associated hubs takes differentially expressed genes (DEGs) as input which represent a biological context such as abiotic or biotic stress response, and then prioritize hub genes associated to the context. Since hub genes in the network have many linked partners, it has a high probability of being a master regulator in that biological context.

WheatNet: the first genome-scale functional gene network for a polyploid species, Triticum aestivum, Molecular Plant. 2017 Aug 7;10(8):1133-1136 (link)

Insuk Lee (insuklee (at) yonsei.ac.kr)
Tak Lee (leetak.net (at) gmail.com)

2016.06.01 WheatNet website launched