Whole transcriptome microarrays identify long non-coding RNAs associated with cardiac hypertrophy

Lu Zhang, Eman A. Hamad, Mélanie Vausort, Hajime Funakoshi, Nathalie Nicot, Petr V. Nazarov, Laurent Vallar, Arthur M. Feldman, Daniel R. Wagner, Yvan Devaux*, Cardiolinc network (www.cardiolinc.org)

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

Long non-coding RNAs (lncRNAs) have recently emerged as a novel group of non-coding RNAs able to regulate gene expression. While their role in cardiac disease is only starting to be understood, their involvement in cardiac hypertrophy is poorly known. We studied the association between lncRNAs and left ventricular hypertrophy using whole transcriptome microarrays. Wild-type mice and mice overexpressing the adenosine A2A receptor were subjected to transverse aortic constriction (TAC) to induce left ventricular hypertrophy. Expression profiles of lncRNAs in the heart were characterized using genome-wide microarrays. An analytical pipeline was specifically developed to extract lncRNA data from microarrays. We identified 2 lncRNAs up-regulated and 3 lncRNAs down-regulated in the hearts of A2A-receptor overexpressing-mice subjected to TAC compared to wild-type mice. Differential expression of these 2 lncRNAs was validated by quantitative PCR. Complete microarray dataset is available at Gene Expression Omnibus (GEO) database (. http://www.ncbi.nlm.nih.gov/geo/) under the accession number GSE45423. Here, we describe in details the experimental design, microarray performance and analysis.

Original languageEnglish
Pages (from-to)68-71
Number of pages4
JournalGenomics Data
Volume5
DOIs
Publication statusPublished - 1 Sep 2015

Keywords

  • Adenosine A2a receptor
  • Long non-coding RNA
  • Microarray
  • Transverse aortic constriction

Fingerprint

Dive into the research topics of 'Whole transcriptome microarrays identify long non-coding RNAs associated with cardiac hypertrophy'. Together they form a unique fingerprint.

Cite this