Comparative analysis of gene-coexpression networks across species

  • Authors:
  • Shiquan Wu;Jing Li

  • Affiliations:
  • Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH;Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH

  • Venue:
  • ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
  • Year:
  • 2007

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Abstract

This paper presents a large scale analysis of gene-coexpression networks (GCNs) across four plant species, i.e. Arabidopsis, Barley, Soybean, and Wheat, over 1471 DNA microarrays. We first identify a set of 5164 metagenes that are highly conserved across all of them. For each of the four species, a GCN is constructed by linking reliable coexpressed metagene pairs based on their expression profiles within each species. Similarly, an overall GCN for the four species is constructed based on gene expression profiles across the four species. On average, more than 50K correlation links have been generated for each of the five networks. A number of recent studies have shown that topological structures of GCNs and some other biological networks have some common characteristics, and GCNs across species may reveals conserved genetic modules that contain functionally related genes. But no studies on GCNs across crop species have been reported. In this study, we focus on the comparative analysis of statistical properties on the topological structure of the above five networks across Arabidopsis and three crop species. We show that: (1) the five networks are scale-free and their degree distributions follow the power law; (2) these networks have the small-world property; (3) these networks share very similar values for a variety of network parameters such as degree distributions, network diameters, cluster coefficients, and frequency distributions of correlation patterns (sub-graphs); (4) these networks are nonrandom and are stable; (5) cliques and clique-like subgraphs are overly present in these networks. Further analysis can be carried out to investigate conserved functional modules and regulatory pathways across the four species based on these networks. A web-based computing tool, available at http://cbc.case.edu/coexp.html, has been designed to visualize expression profiles of metagenes across the four species.