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microRNA evolution in a human transcription factor and microRNA regulatory network

DOI: 10.1186/1752-0509-4-90

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Abstract:

Here, we conducted the first systems-level analysis of miRNA evolution in a human transcription factor (TF)-miRNA regulatory network that describes the regulatory relations among TFs, miRNAs, and target genes. We found that the architectural structure of the network provides constraints and functional innovations for miRNA evolution and that miRNAs showed different and even opposite evolutionary patterns from TFs and other protein-coding genes. For example, miRNAs preferentially coevolved with their activators but not with their inhibitors. During transcription, rapidly evolving TFs frequently activated but rarely repressed miRNAs. In addition, conserved miRNAs tended to regulate rapidly evolving targets, and upstream miRNAs evolved more rapidly than downstream miRNAs.In this study, we performed the first systems level analysis of miRNA evolution. The findings suggest that miRNAs have a unique evolution process and thus may have unique functions and roles in various biological processes and diseases. Additionally, the network presented here is the first TF-miRNA regulatory network, which will be a valuable platform of systems biology.microRNAs (miRNAs) are a class of endogenous and small non-coding regulatory RNAs, which regulate genes at the post-transcriptional level [1]. In the past few years, studies of miRNAs have ranged from their biological functions to their evolution. Understanding the evolution of miRNAs is very important to the study of their function, genomic organization, human disease, and medicine [2,3]. Studies of miRNA evolution have focused on the molecular level. For example, the majority of miRNAs are conserved during evolution [1,4,5]. The structure of miRNA precursor stem loops exhibits significantly increased mutational robustness in comparison with random RNA sequences with the same stem-loop structure[6]. It was revealed that the genetic robustness observed in miRNA sequences is the byproduct of selection for environmental robustness [7]. Va

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