An evolutionarily biased distribution of miRNA sites toward regulatory genes with high promoter-driven intrinsic transcriptional noise
1 Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis, Musculoskeletal and Skin Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA
2 Department of Biochemistry, Molecular Biology & Biophysics, Biotechnology Institute, University of Minnesota, 140 Gortner Labs, 1479 Gortner Avenue, St. Paul, MN 55108, USA
BMC Evolutionary Biology 2014, 14:74 doi:10.1186/1471-2148-14-74Published: 4 April 2014
miRNAs are a major class of regulators of gene expression in metazoans. By targeting cognate mRNAs, miRNAs are involved in regulating most, if not all, biological processes in different cell and tissue types. To better understand how this regulatory potential is allocated among different target gene sets, we carried out a detailed and systematic analysis of miRNA target sites distribution in the mouse genome.
We used predicted conserved and non-conserved sites for 779 miRNAs in 3′ UTR of 18440 genes downloaded from TargetScan website. Our analysis reveals that 3′ UTRs of genes encoding regulatory proteins harbor significantly greater number of miRNA sites than those of non-regulatory, housekeeping and structural, genes. Analysis of miRNA sites for orthologous 3′UTR’s in 10 other species indicates that the regulatory genes were maintaining or accruing miRNA sites while non-regulatory genes gradually shed them in the course of evolution. Furthermore, we observed that 3′ UTR of genes with higher gene expression variability driven by their promoter sequence content are targeted by many more distinct miRNAs compared to genes with low transcriptional noise.
Based on our results we envision a model, which we dubbed “selective inclusion”, whereby non-regulatory genes with low transcription noise and stable expression profile lost their sites, while regulatory genes which endure higher transcription noise retained and gained new sites. This adaptation is consistent with the requirements that regulatory genes need to be tightly controlled in order to have precise and optimum protein level to properly function.