Functional models for large-scale gene regulation networks: realism and fiction

Abstract

High-throughput experiments are shedding light on the topology of large regulatory networks and at the same time their functional states, namely the states of activation of the nodes (for example transcript or protein levels) in different conditions, times, environments. We now possess a certain amount of information about these two levels of description, stored in libraries, databases and ontologies. A current challenge is to bridge the gap between topology and function, i.e. developing quantitative models aimed at characterizing the expression patterns of large sets of genes. However, approaches that work well for small networks become impossible to master at large scales, mainly because parameters proliferate. In this review we discuss the state of the art of large-scale functional network models, addressing the issue of what can be considered as "realistic" and what the main limitations may be. We also show some directions for future work, trying to set the goals that future models should try to achieve. Finally, we will emphasize the possible benefits in the understanding of biological mechanisms underlying complex multifactorial diseases, and in the development of novel strategies for the description and the treatment of such pathologies.

Non-coding RNAs and a layered architecture of genetic networks

“…Qualitatively, such networks can be classified as "autocratic", "intermediate", and "democratic" [19]. Focusing on the former class, we notice that in this case there are at least two general principles that allow us to understand what often happens [20]. The first of these principles is that usually only a small fraction of genes has protein-mediated links with many other genes, while the majority of genes are sparsely connected.…”

“…The topology of the genetic networks containing mRNAS and proteins can be fairly complex [17][18][19][20]. Qualitatively, such networks can be classified as "autocratic", "intermediate", and "democratic" [19].…”

“…The whole process of gene expression is regulated at every gene expression). Kinetic models describing the mRNAprotein interplay are abundant as well (see the reviews focused on stochastic bursts, bistability and oscillations in simple genetic networks [12][13][14][15][16] and on complex genetic networks [17][18][19][20]). …”

“…[34][35][36][37][38][39][40][41][42][43], we use mean-field kinetic equations. Alternatively, the complex genetic mRNA-protein networks are often described by employing the Boolean rules [17,20]. For the networks including ncRNAs, the use of kinetic equations is more natural.…”

Two novel aspects of the kinetics of gene expression including miRNAs

“…[11][12][13] and references therein). The interplay of various steps has also been extensively studied as reviewed with emphasis on stochastic bursts and bistability in simple mRNA-protein networks [14][15][16], kinetic oscillations in such networks [17,18], complex mRNA-protein networks [19][20][21][22], and networks including mRNAs, proteins and non-coding RNAs [23].…”