NDLI: Reference Genes Selection for Quantitative Real-Time PCR Using RankAggreg Method in Different Tissues of Capra hircus

Content Provider	PubMed Central
Author	Javad, Najafpanah Mohammad Sadeghi, Mostafa Bakhtiarizadeh, Mohammad Reza
Editor	Niemann, Heiner
Copyright Year	2013
Abstract	Identification of reference genes with stable levels of gene expression is an important prerequisite for obtaining reliable results in analysis of gene expression data using quantitative real time PCR (RT-qPCR). Since the underlying assumption of reference genes is that expressed at the exact same level in all sample types, in this study, we evaluated the expression stability of nine most commonly used endogenous controls (GAPDH, ACTB, 18S rRNA, RPS18, HSP-90, ALAS, HMBS, ACAC, and B2M) in four different tissues of the domestic goat, Capra hircus, including liver, visceral, subcutaneous fat and longissimus muscles, across different experimental treatments (a standard diet prepared using the NRC computer software as control and the same diet plus one mg chromium/day). We used six different software programs for ranking of reference genes and found that individual rankings of the genes differed among them. Additionally, there was a significant difference in ranking patterns of the studied genes among different tissues. A rank aggregation method was applied to combine the ranking lists of the six programs to a consensus ranking. Our results revealed that HSP-90 was nearly always among the two most stable genes in all studied tissues. Therefore, it is recommended for accurate normalization of RT-qPCR data in goats, while GAPDH, ACTB, and RPS18 showed the most varied expressions and should be avoided as reference genes.
Related Links	http://dx.doi.org/10.1371/journal.pone.0083041
Starting Page	83041
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	12
Volume Number	8
Language	English
Publisher	Public Library of Science
Publisher Date	2013-12-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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