On reverse engineering of gene interaction networks using time course data with repeated measurements.

MOTIVATION: Gene expression measurements are the most common data source for reverse engineering gene interaction networks. When dealing with destructive sampling in time course experiments, it is common to average any available measurements for each time point and to treat this as the actual time series data for fitting the network, neglecting the variability contained in the repeated measurements. Proceeding in such a way can affect the retrieved network topology. RESULTS: We propose a fully Bayesian method for reverse engineering a gene interaction network, based on time course data with repeated measurements. The observations are treated as surrogate measurements of the underlying gene expression. As these measurements often contain outliers, we use a non-Gaussian specification for dealing with measurement error. The network interactions are assumed linear and an autoregressive model is specified, augmented with indicator variables that allow inference on the topology of the network. We analyse two in silico and one in vivo experiments, the latter dealing with the circadian clock in Arabidopsis thaliana. A systematic attenuation of the estimated regulation strengths and a concomitant overestimation of their precision is demonstrated when measurement error is disregarded. Thus, a clear improvement in the inferred topology for the synthetic datasets is demonstrated when this is included. Also, the influence of outliers in the retrieved network is demonstrated when using the in vivo data. AVAILABILITY: Matlab code and data used in the article are available from http://go.warwick.ac.uk/majuarez/home/materials.

Carbon Catabolite Repression Regulates Glyoxylate Cycle Gene Expression in Cucumber.

We have previously proposed that metabolic status is important in the regulation of cucumber malate synthase (MS) and isocitrate lyase (ICL) gene expression during plant development. In this article, we used a cell culture system to demonstrate that intracellular metabolic status does influence expression of both of these genes. Starvation of cucumber cell cultures resulted in the coordinate induction of the expression of MS and ICL genes, and this effect was reversed when sucrose was returned to the culture media. The induction of gene expression was closely correlated with a drop in intracellular sucrose, glucose, and fructose below threshold concentrations, but it was not correlated with a decrease in respiration rate. Glucose, fructose, or raffinose in the culture media also resulted in repression of MS and ICL. Both 2-deoxyglucose and mannose, which are phosphorylated by hexokinase but not further metabolized, specifically repressed MS and ICL gene expression relative to a third glyoxylate cycle gene, malate dehydrogenase. However, the addition of 3-methylglucose, an analog of glucose that is not phosphorylated, did not result in repression of either MS or ICL. It is proposed that the signal giving rise to a change in gene expression originates from the intracellular concentration of hexose sugars or the flux of hexose sugars into glycolysis.