Modeling evolutionary growth of a microRNA-mediated regulation system

Gene duplication plays a crucial role in the development of complex biosystems, but the evolutionary forces behind the growth of biosystems are poorly understood. In this work, we introduce a model for such a growth through gene duplication. Plant microRNAs (miRNAs) are considered as a model. miRNAs are one of the non-coding small RNAs (19–25 nucleotides), which are involved in the post-transcriptional gene regulation. A single kind of miRNAs can be encoded by multiple genomic regions called miRNA genes, and can regulate multiple kinds of functional gene families. It is assumed that a single miRNA system involves all these genes, miRNA genes and their target gene families. We are interested in how duplication of miRNA genes affects the evolution of the miRNA system by focusing on the numbers of miRNA genes and their target gene families, denoted by x and y, respectively. We here theoretically explore the evolutionary growth of (x,y); the former increases by duplication of the miRNA gene while the latter increases when an independent gene family acquires a novel binding site of the miRNA by mutations. We first investigate the evolutionary patterns of (x,y) under three commonly assumed scenarios for the evolution of duplicated genes, that is, the positive and negative dosage and neofunctionalization scenarios. The results indicate that under the three scenarios, the transient process of (x,y) is unidirectional, although the direction is different depending on the model. This pattern is not consistent with the observation in the Arabidopsis thaliana genome, suggesting that a model that incorporates at least two directional evolutionary forces is needed to explain the observation. Then, such a model called the “complexity growth model” is introduced, in which we assume that duplication of miRNA genes is evolutionary advantageous in that the system can encode a complex and sophisticated pattern of regulation because multiple miRNA genes can have different expression patterns. This is helpful to optimize the regulation of a few particular functional gene families, but there is a cost; once the system is optimized for one purpose, it could be difficult for other purposes to use it. That is, duplication of miRNA genes would narrow down the potential gene families that can join the system. Our theoretical analysis revealed that this model can explain the observation of Arabidopsis miRNAs. Although we consider plant miRNAs as an example in this work, the model can be readily applied to other regulation systems with some modifications. Further development of such models would provide insights into the evolutionary growth of the complexity of biosystems. ⺠We introduce a model for the evolutionary growth of a miRNA gene regulation system. ⺠We focus on the role of gene duplication in the evolution of complexity. ⺠The model flexibly incorporates the positive and negative effects of gene duplication. ⺠The model is applied to Arabidopsis thaliana miRNAs. ⺠The growth of Arabidopsis mRNA systems should involve bidirectional evolutionary forces.