Deconvolution of the confounding variations for reverse transcription quantitative real-time polymerase chain reaction by separate analysis of biological replicate data

Abstract

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) uses threshold cycles (Ct values) for measuring relative gene expression. Ct values are signal-to-noise data composed of target gene expression and multiple sources of confounding variations. Data analysis is to minimize technical noises, evaluate biological variances, and estimate treatment-attributable expression changes of particular genes. However, this function is not sufficiently fulfilled in current analytic methods. An important but unrecognizable problem is that Ct values from all biological replicates and technical repeats are pooled across genes and treatment types. This violates the sample-specific association between target and reference genes, leading to inefficient removal of technical noises. To resolve this problem, here we propose to separate Ct values into replicate-specific data subsets and iteratively analyze expression ratios for individual data subsets. The individual expression ratios, rather than the raw Ct values, are pooled to determine the final expression change. The variances of all biological replicates and technical repeats across all target and reference genes are summed up. Our results from example data demonstrate that this separated method can substantially minimize RT-qPCR variance compared with the traditional methods using pooled Ct profiles. This analytic strategy is more effective in control of technical noises and improves the fidelity of RT-qPCR quantification.

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“…Relative expression values and standard deviation (SD) have been calculated using the ΔΔ C T approach, as previously described .…”

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“…C T values from real-time PCR were analyzed using a custom SASqPCR program (Ling, 2012 ). Mean normalized expression ratios were calculated as described (Ling et al, 2012 ).…”

Selection of reference genes for quantitative real‐time polymerase chain reaction normalization in Bradysia odoriphaga (Diptera: Sciaridae)

“…; Ling et al . ). To avoid biased results during RT‐qPCR analysis, a normalization step for calibrating the gene expression is using reference genes that must be expressed at stable levels across various experimental conditions (Bustin ; Pfaffl ; Huggett et al .…”

“…Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a sensitive and accurate approach to validating the transcriptional expression of target genes involved in all biological processes across diverse organisms and tissues and under different stress conditions (Hong et al 2008;Chen et al 2015;Kanakachari et al 2016). However, its accuracy and reliability are compromised by several experimental variations in sample collection, RNA extraction, reverse transcription and PCR amplification efficiency (Nolan et al 2006;Ling et al 2012). To avoid biased results during RT-qPCR analysis, a normalization step for calibrating the gene expression is using reference genes that must be expressed at stable levels across various experimental conditions (Bustin 2000;Pfaffl 2001;Huggett et al 2005).…”