Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Dec 1:2:261-263.
doi: 10.1016/j.gdata.2014.08.004.

Gene Expression Profiling of Valvular Interstitial Cells in Rapacz Familial Hypercholesterolemic Swine

Affiliations

Gene Expression Profiling of Valvular Interstitial Cells in Rapacz Familial Hypercholesterolemic Swine

Ana M Porras et al. Genom Data. .

Abstract

Rapacz familial hypercholesterolemic (RFH) swine are a well-established model of human FH, a highly prevalent hereditary disease associated with increased risk of coronary artery disease and calcific aortic valve disease (CAVD). However, while these animals have been used extensively for the study of atherosclerosis, the heart valves from RFH swine have not previously been examined. We report the analysis of valvular interstitial cell gene expression in adult (two year old) and juvenile (three months old) RFH and WT swine by microarray analysis via the Affymetrix Porcine Genome Array (GEO #: GSE53997). Principal component and hierarchical clustering analysis revealed grouping and almost no variability between the RFH juvenile and WT juvenile groups. Additionally, only 21 genes were found differentially expressed between these two experimental groups whereas over 900 genes were differentially expressed when comparing either RFH or WT juvenile swine to RFH adults.

Keywords: familial hypercholesterolemia; microarray; swine; valve disease.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Principal component plot of normalized expression values. The numbers in parentheses indicate the percentage of the variation captured by each principal component.
Fig. 2
Fig. 2
Hierarchical clustering of RFH and WT normalized microarray data based on the 30 genes with the highest variability across chips.
Fig. 3
Fig. 3
Histogram of the coefficients of variability for each probeset within (A) WT juvenile swine, (B) RFH juvenile swine, (C) RFH adult swine, and (D) all swine.

Similar articles

Cited by

References

    1. Gentleman R.C., Carey V.J., Bates D.M., Bolstad B., Dettling M., Dudoit S., Ellis B., Gautier L., Ge Y., Gentry J., Hornik K., Hothorn T., Huber W., Iacus S., Irizarry R., Leisch F., Li C., Maechler M., Rossini A.J., Sawitzki G., Smith C., Smyth G., Tierney L., Yang J.Y., Zhang J. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5:R80. - PMC - PubMed
    1. Shakya K., Ruskin H.J., Kerr G., Crane M., Becker J. Comparison of microarray preprocessing methods. Adv. Exp. Med. Biol. 2010;680:139–147. - PubMed
    1. Tsai S., Cassady J.P., Freking B.A., Nonneman D.J., Rohrer G.A., Piedrahita J.A. Annotation of the affymetrix porcine genome microarray. Anim. Genet. 2006;37:423–424. - PubMed
    1. Smyth G.K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 2004;3 (Article3Article3) - PubMed

LinkOut - more resources