Effects of an RNA control layer on the state space of Boolean models of genetic regulatory networks

The general assumption in biology is that most genes encode proteins. However, it is now evident that much of the genome of humans and other complex organisms is transcribed into non-protein-coding RNAs. Some of these RNAs are processed into small regulatory RNAs, such as microRNAs, that control many aspects of animal and plant development. It has been suggested that regulatory RNAs represent an additional control layer that was critical to the emergence of complex organisms. We examine this possibility using a model of cell differentiation based on attractors in boolean networks. Our simulation studies show that an additional layer of RNA control modeled as fast temporal links can significantly increase the number of attractors in boolean models of genetic regulatory networks (analogous to the number of cell types in a complex organism). However, it also has the power to simplify the state space structure. We explore the conditions under which these different outcomes occur.