Selection of reliable reference genes for normalization of quantitative RT-PCR from different developmental stages and tissues in amphioxus

Abstract

Amphioxus is a closest living proxy to the ancestor of cephalochordates with vertebrates, and key animal for novel understanding in the evolutionary origin of vertebrate body plan, genome, tissues and immune system. Reliable analyses using quantitative real-time PCR (qRT-PCR) for answering these scientific questions is heavily dependent on reliable reference genes (RGs). In this study, we evaluated stability of thirteen candidate RGs in qRT-PCR for different developmental stages and tissues of amphioxus by four independent (geNorm, NormFinder, BestKeeper and deltaCt) and one comparative algorithms (RefFinder). The results showed that the top two stable RGs were the following: (1) S20 and 18 S in thirteen developmental stages, (2) EF1A and ACT in seven normal tissues, (3) S20 and L13 in both intestine and hepatic caecum challenged with lipopolysaccharide (LPS), and (4) S20 and EF1A in gill challenged with LPS. The expression profiles of two target genes (EYA and HHEX) in thirteen developmental stages were used to confirm the reliability of chosen RGs. This study identified optimal RGs that can be used to accurately measure gene expression under these conditions, which will benefit evolutionary and functional genomics studies in amphioxus.

Selection of reference genes for qRT‐PCR and expression analysis of high‐altitude‐related genes in grassland caterpillars (Lepidoptera: Erebidae: Gynaephora) along an altitude gradient

“…However, due to different statistical models among algorithms, some discrepancies were also observed among the four independent algorithms, as has been frequently reported in previous studies (Ibanez & Tamborindeguy, 2016; Koramutla et al., 2016; Yang, et al., 2015). The BestKeeper results were the most divergent from the other three independent algorithms, as reported in other studies (Lu et al., 2015; Zhang et al., 2016). In order to overcome differences among algorithms, we determined an overall ranking for the 17 candidates RGs based on another algorithm (RefFinder) to obtain the final stabilities.…”

“…The amplification efficiency and correlation coefficient ( R 2 ) of each primer were calculated using the standard curve generated from a 10‐fold dilution series of mixed cDNA samples at five dilution. The corresponding qRT‐PCR efficiencies ( E ) were calculated according to the equation E (%) = (10 (−1/slope)  − 1) × 100 (Zhang et al., 2016). …”

“…All data from three biological and technological replicates were used to calculate the average Ct value according to previous methods (Yang et al., 2015; Zhang et al., 2016). geNorm software calculates an expression stability value ( M ) and ranks the genes in order for a given set of samples.…”

“…The expression stability of each RG was evaluated with four independent algorithms: geNorm (Vandesompele et al, 2002), NormFinder (Andersen, Jensen, & Ørntoft, 2004), BestKeeper (Pfaffl, Tichopad, Prgomet, & Neuvians, 2004), and the deltaCt method (Silver, Best, Jiang, & Thein, 2006). All data from three biological and technological replicates were used to calculate the average Ct value according to previous methods Zhang et al, 2016). geNorm software calculates an expression stability value (M) and ranks the genes in order for a given set of samples.…”

“…However, previous studies have shown that these RGs are not always stably expression under various experimental conditions (Chapman & Waldenström, 2014; Thellin, Elmoualij, Heinen, & Zorzi, 2009). Moreover, several studies have highlighted the importance of the optimal number of RGs (normalization factors, NFs) being experimentally determined when normalizing target genes (Bansal et al., 2016; Yang, et al., 2015; Zhang et al., 2016). …”