Abstract
BackgroundBiological networks characterize the interactions of biomolecules at a systems-level. One important property of biological networks is the modular structure, in which nodes are densely connected with each other, but between which there are only sparse connections. In this report, we attempted to find the relationship between the network topology and formation of modular structure by comparing gene co-expression networks with random networks. The organization of gene functional modules was also investigated.ResultsWe constructed a genome-wide Arabidopsis gene co-expression network (AGCN) by using 1094 microarrays. We then analyzed the topological properties of AGCN and partitioned the network into modules by using an efficient graph clustering algorithm. In the AGCN, 382 hub genes formed a clique, and they were densely connected only to a small subset of the network. At the module level, the network clustering results provide a systems-level understanding of the gene modules that coordinate multiple biological processes to carry out specific biological functions. For instance, the photosynthesis module in AGCN involves a very large number (> 1000) of genes which participate in various biological processes including photosynthesis, electron transport, pigment metabolism, chloroplast organization and biogenesis, cofactor metabolism, protein biosynthesis, and vitamin metabolism. The cell cycle module orchestrated the coordinated expression of hundreds of genes involved in cell cycle, DNA metabolism, and cytoskeleton organization and biogenesis. We also compared the AGCN constructed in this study with a graphical Gaussian model (GGM) based Arabidopsis gene network. The photosynthesis, protein biosynthesis, and cell cycle modules identified from the GGM network had much smaller module sizes compared with the modules found in the AGCN, respectively.ConclusionThis study reveals new insight into the topological properties of biological networks. The preferential hub-hub connections might be necessary for the formation of modular structure in gene co-expression networks. The study also reveals new insight into the organization of gene functional modules.
Highlights
Biological networks characterize the interactions of biomolecules at a systems-level
We focused our analysis on two gene functional modules, photosynthesis module and cell cycle module, that are central to plant growth and development
We found that 97% of the 382 hub genes showed higher expression levels with the treatment of 4-hour continuous white light compared with the treatment of 4-hour continuous darkness; whereas only 54% of the 6206 genes in Arabidopsis gene co-expresion network (AGCN) showed higher expression levels upon the light
Summary
Biological networks characterize the interactions of biomolecules at a systems-level. One important property of biological networks is the modular structure, in which nodes are densely connected with each other, but between which there are only sparse connections. A node in a graph represents a biomolecule such as a gene, a protein or a metabolite, and an edge (or link) indicates the interaction between these two biomolecules. Such interactions could be physical interactions, metabolite flow, regulatory relationships, co-expression relationships, etc. One important property of networks is the modular structure, in which nodes are densely connected with each other, but between which there are only sparse connections [2]. Biomolecules belonging to the same module interact with each other to carry out a specific biological function
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.