Emergence of Gene Regulatory Networks Under Functional Constraints

Abstract

Gene regulatory networks allow the control of gene expression patterns in living cells. We ask here to what extent the network architecture is determined by the output patterns of gene regulatory networks. Given a framework for describing regulatory interactions and dynamics (Burda et al., Proc. Natl. Acad. Sci. USA, 108:17263, 2011), we consider in the space of all regulatory networks those that have prescribed functional capabilities. Markov Chain Monte Carlo sampling is then used to determine how these functional constraints lead to specific structures of the interactions. Particularly, we generate ensemble of regulatory networks with yeast cell-cycle (Li et al., Proc. Natl. Acad. Sci. USA, 101:4781, 2004) biological trajectory imposed. As a result, we find that on average 55 % of interactions are well reproduced, and concerning the whole ensemble almost all networks have from 40 % to 70 % of links in common with yeast cell-cycle network.