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Long noncoding RNAs in cardiovascular diseases.

Circulation research | 2015

In recent year, increasing evidence suggests that noncoding RNAs play important roles in the regulation of tissue homeostasis and pathophysiological conditions. Besides small noncoding RNAs (eg, microRNAs), >200-nucleotide long transcripts, namely long noncoding RNAs (lncRNAs), can interfere with gene expressions and signaling pathways at various stages. In the cardiovascular system, studies have detected and characterized the expression of lncRNAs under normal physiological condition and in disease states. Several lncRNAs are regulated during acute myocardial infarction (eg, Novlnc6) and heart failure (eg, Mhrt), whereas others control hypertrophy, mitochondrial function and apoptosis of cardiomyocytes. In the vascular system, the endothelial-expressed lncRNAs (eg, MALAT1 and Tie-1-AS) can regulate vessel growth and function, whereas the smooth-muscle-expressed lncRNA smooth muscle and endothelial cell-enriched migration/differentiation-associated long noncoding RNA was recently shown to control the contractile phenotype of smooth muscle cells. This review article summarizes the data on lncRNA expressions in mouse and human and highlights identified cardiovascular lncRNAs that might play a role in cardiovascular diseases. Although our understanding of lncRNAs is still in its infancy, these examples may provide helpful insights how lncRNAs interfere with cardiovascular diseases.

Pubmed ID: 25677520 RIS Download

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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