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An Intragenic SRF-Dependent Regulatory Motif Directs Cardiac-Specific microRNA-1-1/133a-2 Expression

Overview of attention for article published in PLOS ONE, September 2013
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Title
An Intragenic SRF-Dependent Regulatory Motif Directs Cardiac-Specific microRNA-1-1/133a-2 Expression
Published in
PLOS ONE, September 2013
DOI 10.1371/journal.pone.0075470
Pubmed ID
Authors

Qi Li, Junli Guo, Xi Lin, Xiangsheng Yang, Yanlin Ma, Guo-Chang Fan, Jiang Chang

Abstract

Transcriptional regulation is essential for any gene expression including microRNA expression. MiR-1-1 and miR-133a-2 are essential microRNAs (miRs) involved in cardiac and skeletal muscle development and diseases. Early studies reveal two regulatory enhancers, an upstream and an intragenic, that direct the miR-1-1 and miR-133a-2 transcripts. In this study, we identify a unique serum response factor (SRF) binding motif within the enhancer through bioinformatic approaches. This motif is evolutionarily conserved and is present in a range of organisms from yeast, flies, to humans. We provide evidence to demonstrate that this regulatory motif is SRF-dependent in vitro by electrophoretic mobility shift assay, luciferase activity assay, and endogenous chromatin immunoprecipitation assay followed by DNA sequence confirmation, and in vivo by transgenic lacZ reporter mouse studies. Importantly, our transgenic mice indicate that this motif is indispensable for the expression of miR1-1/133a-2 in the heart, but not necessary in skeletal muscle, while the enhancer is sufficient for miR1-1/133a-2 gene expression in both tissues. The mutation of the motif alone completely abolishes miR-1-1/133a-2 gene expression in the animal heart, but not in the skeletal muscle. Our findings reveal an additional architecture of regulatory complex directing miR-1-1/133a-1 gene expression, and demonstrate how this intragenic enhancer differentially manages the expression of the two miRs in the heart and skeletal muscle, respectively.

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Geographical breakdown

Country Count As %
Turkey 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 4 19%
Researcher 4 19%
Student > Doctoral Student 3 14%
Student > Bachelor 2 10%
Student > Ph. D. Student 1 5%
Other 0 0%
Unknown 7 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 29%
Biochemistry, Genetics and Molecular Biology 3 14%
Nursing and Health Professions 1 5%
Medicine and Dentistry 1 5%
Neuroscience 1 5%
Other 0 0%
Unknown 9 43%