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Perturbations in Genetic Networks and Gene Expression

Overview | Procedures | Genetic Networks | cis and trans effects | People | Publications

Genetic Networks

Because we will uncover unprecedented information on homoeologous gene expression, the exciting prospect is raised for studying gene network perturbations and the key innovations on a homoeolog-specific basis. In addition to revealing differentially expressed genes, we will explore the degree to which gene co-expression networks (gene networks) are perturbed by introgression, in collaboration with A. Feltus. Biological networks have been shown to be have non-random structure and are scale-free, which means that their degree distribution approximates a power law, and most nodes have few links whereas some nodes are highly connected (‘hubs’). Based upon a gene set having more internal than external links, it is possible to identify sub-network modules that show a high degree of community structure using techniques such as the Girvan-Newman (G-N) algorithm. The hypothesis is that a tightly connected module contains genes with common function. Using the expanding microarray dataset being generated for G. hirsutum, we will construct a baseline gene network by determining the expression level correlation coefficient for all pair-wise gene combinations from all microarray experiments. A co-expression link in the network indicates that the gene pair is co-expressed regardless of environmental conditions due to the large number of biological and experimental variability across the dataset. We will then identify modules in the baseline gene network with the G-N algorithm, and attempt to attribute function to these modules through overrepresentation of conserved Pfam protein domain families and/or GO annotation classes or through the presence of known genes involved in cotton biology (‘guilt by association’). For each introgression line, we will compare its expression pattern against the baseline gene network and look for differences in hub and community structure. Specifically, we will identify gene pairs that have lost or gained co-expression through standard microarray analysis techniques, including cluster analysis. Any significant flux in gene modules will be determined. In this way, we aim to identify ‘broken’ or ‘spawned’ hubs/modules that are specific to an introgression line. These data, in a sense, will provide the first test in a relatively young polyploid of the tantalizing observation of "concerted divergence" of duplicated pathways, as introduced by Blanc and Wolfe.

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