Real Time PCR: the Use of Reference Genes and Essential Rules Required to Obtain Normalisation Data Reliable to Quantitative Gene Expression

Abstract

Quantitative Real-time Polymerase Chain Reaction (qPCR) is an important tool for molecular biology and biotechnology research, widely used to determine the expression levels of mRNA. Two main methods to performing qPCR are largely used: The absolute quantification, in which the mRNA levels are determined by using a standard curve and the relative method, which is based on the use of reference genes. Reference genes are widely expressed in cells of animal and plant tissues and their expression pattern are theoretically unchanged within several situations, which makes them an excellent choice to normalize mRNA quantification data in relative qPCR studies. However, several reports are increasingly showing that the use of only one reference gene in relative qPCR studies should be avoided, because in the real world their expression levels can significantly change from tissue to tissue. Several softwares, such as geNorm, BestKeeper and NormFinder, have been developed to perform data normalisation, and these programs may assist in choosing the most stable reference genes. The aim of this review was to describe the current normalisation strategies used in qPCR assay, as well as to establish essential rules to perform reliable mRNA quantification. Finally, this review show some innovations in the advances on qPCR.

Identification of Suitable Reference Genes for Gene Expression Normalization in Jatropha curcas L During Development and Under Stress Conditions Using Real Time Quantitative PCR

“…Moreover, these genes should not be widely used under conditions other than the ones tested in the present study, such as stratification, cold and heat stress conditions. In these cases, the use of multiple reference genes across the experiment or the reevaluation of novel reference genes are recommended strategies (Rocha et al 2015). In conclusion, different tissues or experimental conditions requirespecific reference genes.…”

“…This provides information on the search of new genes with important contribution regarding the metabolism of this plant, that will certainly improve our understanding of the metabolic pathways underlying the developmental processes related to oil metabolism and of the biosynthesis of toxic and/or allergenic compounds (Soares et al2014;Shah et al 2015) qPCR is thought to be the appropriate approach to study the expression patterns of the relevant genes involved in these processes due to its accuracy, sensitivity and reproducibility (Rocha et al 2015). RNA quality, cDNA synthesis and stable reference genes are important factors to be considered in reverse transcription followed by qPCR experiments, because they account for the experimental variation that can occur during the process of amplification (Vandesopele et al 2002;Rocha et al 2015). To our knowledge only 2 previous studies have focused on evaluating the normalisation of qPCR using reference genes present in the biofuel plant Jatropha curcas.…”

“…Since qPCR results are highly dependent on the choice of appropriate reference gene(s) to control for experimental error, ideally these have to display only minor differences in their expression profile under various developmental conditions or tissue types. Reference genesare commonly investigated as internal controls for normalization in gene expression analyses, but there are evidences that the most widely used reference genes are not reliable controls, due to variations in their transcript levelsin different tissues (Paolacci et al 2011, Rocha et al 2015.Hence, the present study aimed to assess the stability of actin (ACTIN), tubulin alpha-2 (Tα2), tubulin beta (Tβ2), elongation factor 1-alpha (EF1-α), protein phosphatase 2A-2 (PP2A2), polyubiquitin (PUB), ciclofilin, ubiquitin conjugation protein (UCP) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as reference genes in RNA samples derived from developing seeds and leaves of J. curcas seedlings under four stress conditions.…”

Guidelines for Successful Quantitative Gene Expression in Real- Time qPCR Assays

“…High quality of RNA is an essential requirement for qPCR. There are several probable contaminants that may interfere in PCR reactions by inhibiting mainly transcriptase reverse and DNA polymerases enzymes, such as DNA genomic, excess of proteins and carbohydrates, as well as phenolic compounds [3]. RNA can be quantified at 260 nm in spectrophotometer and readings of absorbance at 280 and 230 are used to detect proteins and carbohydrates, respectively.…”

“…Summarily, several precautions must be considered in order to obtain consistent results and avoid mistakes in the data interpretation in qPCR assays [3], including: (i) an accurate primer design with respect to specificity and efficiency; (ii) a purified mRNA free of contaminants, such as carbohydrates, proteins and phenols; and (iii) a rigorous choice of reference gene, which must be stable for analyzed experimental condition.…”