Complex cellular activities are believed to be coordinately regulated by genes that function in networks. Reconstructing these gene networks can provide insights into the molecular mechanisms of the cellular activities and thus represents a fundamental challenge in systems biology. Although multiple methods have been proposed to reconstruct gene networks, elucidating the phenotype-gene interaction through the reconstruction of context-specific gene networks remains elusive.

Taking the phenotype of saturated free fatty acid (FFA)-induced cytotoxicity as an example, we present a novel integrative strategy that can be used to construct phenotype-specific gene networks. FFAs modulate multiple intracellular metabolic pathways, most of which are involved in the induction of cytotoxicity by saturated FFAs. Therefore, we first select the subset of genes by integrating multiple levels of information, i.e., gene expression and metabolite profiles. This strategy reflects the “multi-level” regulatory characteristic of cellular activities, and thereby aids in the selection of genes that are involved in the observed phenotype, and in the reconstruction of a phenotype-specific gene network. With the pool of genes selected, we then introduce the concept of synergy and build a network that consists of gene pairs with significant synergistic relations, which implies cooperation. Unlike other computational methods used to identify gene interactions, the fundamental concept of synergy is to identify the cooperative gene interactions responsible for the phenotype. Therefore, our method intrinsically emphasizes the construction of “phenotype-specific” gene network.

The reconstructed synergy network is scale-free and contains multiple-hub genes. Detailed analyses of the synergy network reveal important genes and cooperative gene-gene interactions that are potentially involved in the saturated FFA-induced cytotoxicity, therefore shedding light on the mechanism(s) of the phenotype.

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