AtGGM2014, an Arabidopsis gene co-expression network for functional studies

ShiSong Ma, Hans J. Bohnert, Savithramma P. Dinesh-Kumar

Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the ArrayExpress database, we constructed an Arabidopsis gene co-expression network, termed AtGGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. AtGGM2014 offers a constructive tool for plant systems biology studies.