Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation

• Main Authors: Neretti Nicola, Remondini Daniel, Tatar Marc, Sedivy John M, Pierini Michela, Mazzatti Dawn, Powell Jonathan, Franceschi Claudio, Castellani Gastrone C
• Format: Article
• Language: English
• Published: BMC 2007-03-01
• Series: BMC Bioinformatics

<p>Abstract</p> <p>Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measures of their expression dynamics. In this paper we apply a correlation based approach to network reconstruction to three datasets of time series gene expression following system perturbation: 1) Conditional, Tamoxifen dependent, activation of the cMyc proto-oncogene in rat fibroblast; 2) Genomic response to nutrition changes in <it>D. melanogaster</it>; 3) Patterns of gene activity as a consequence of ageing occurring over a life-span time series (25y–90y) sampled from T-cells of human donors.</p> <p>We show that the three datasets undergo similar transitions from an "uncorrelated" regime to a positively or negatively correlated one that is symptomatic of a shift from a "ground" or "basal" state to a "polarized" state.</p> <p>In addition, we show that a similar transition is conserved at the pathway level, and that this information can be used for the construction of "meta-networks" where it is possible to assess new relations among functionally distant sets of molecular functions.</p>