Abstract
Because quantitative reverse transcription PCR (RT-qPCR) gene expression data are compositional, amounts of quantified RNAs must be normalized using reference genes. However, the two most used methods to select reference genes (NormFinder and geNorm) ignore the compositional nature of RT-qPCR data, and often lead to different results making reliable reference genes selection difficult. We propose a method, based on all pairwise equivalence tests on ratio of gene expressions, to select genes that are stable enough to be used as reference genes among a set a candidate genes. This statistical procedure controls the error of selecting an inappropriate gene. Application to 30 candidate reference genes commonly used in human studies, assessed by RT-qPCR in RNA samples from lymphoblastoid cell lines of 14 control subjects and 26 patients with bipolar disorder, allowed to select 7 reference genes. This selection was consistent with geNorm’s ranking, less with NormFinder’s ranking. Our results provide an important fundamental basis for reference genes identification using sound statistics taking into account the compositional nature of RT-qPCR data. The method, implemented in the SARP.compo package for R (available on the CRAN), can be used more generally to prove that a set of genes shares a common expression pattern.
Highlights
Comparison of gene expression levels among biological samples is used in a wide range of experimental conditions
Sixteen technical replicates failed, associated with five genes (G6PD [1 failure], HBB [10 failures, including one complete sample], POP4 [2 failures, on the same sample], RPLP0 [1 failure], and RPS17 [2 failures, on different samples]). Such genes were considered as second choice reference genes, since such failures may prevent further data analysis; especially, gene HBB with 62.5% of all failures was considered as unusable as a reference gene
Ranges (14.49 to 23.99), respectively. These results show that the expression levels of the 30 reference genes tested in lymphoblastoid cell lines (LCLs) from bipolar patients and control subjects varied significantly
Summary
Comparison of gene expression levels among biological samples is used in a wide range of experimental conditions. Like in most experiments performed to quantify the amounts of RNAs present in a sample, the total amount of RNA input is fixed in RT-qPCR Because of this constraint, any change in the amount of a single RNA will necessarily translate into opposite changes on all other RNA levels i.e. the RNA amounts are compositional, and their sum equals a fixed amount. Selection of reference genes is a key procedure in the design of RT-qPCR experiments, especially in differential expression experiments Such a selection assumes that one can assess that the expression level of a given reference gene does not change between the studied conditions. This is an impossible task with parisdescartes.fr www.nature.com/scientificreports/. The two methods often lead to different rankings[5,6,7,8,9,10], with presently no clear justification to prefer one ranking or another
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