O papel modulador do gene AIRE - capes

MANUSCRITOinformation theory as ARACNE program (Basso et al., 2005; Margolin et al.,2006), the algorithms that consider ordinary differential equations as NIR, NMIand TSNI programs (Gardner et al., 2003; Di Bernardo et al., 2005; Bansal etal., 2006) and those which solve the inference problem by means of Bayesiannetworks as Banjo (Yu et al., 2004) and GeneNetwork (Wu et al., 2004)programs.Comparing the algorithms, GeneNetwork was chosen for the analysispurposes due to its differential features. The algorithm realizes the interpolationof data and is able to handle with more than one thousand of genes. Moreover,the resulting network is described by an oriented graph in which positive arrowsindicate induction and negative ones denote repression between genes.In an effort to provide a clearer understanding of the high-throughput dataresulting from microarray experiments and to establish regulatory interactions inPGE, normalized data were analyzed by the GeneNetwork program (Wu et al.,2004), which is based on dynamic Bayesian statistics inferring gene networks.Figure 5a shows that PTA genes featuring PGE in mTECs are in factconnected in network. It was found that the Gucy2d (guanylate cyclase 2d)gene, which was induced in control mTECs, plays a role as a gene node due toits numerous interactions, mostly as a positive controller, established amongother genes.Silencing Aire in mTECs, the Gucy2d gene was subsequently repressed butstill played a role as a gene node, which instead positive turned a negativecontroller, repressing mostly of PTA genes (Figure 5b).These findings are important firstly to evidentiate that PTA genes in mTECsare connected in network, which might reflect the existence of a feedback-like215