Abstract
Quantitative real-time PCR (qRT-PCR) is a powerful technique to quantify gene expression. To standardize gene expression studies and obtain more accurate qRT-PCR analysis, normalization relative to consistently expressed housekeeping genes (HKGs) is required. In this study, ten candidate HKGs including elongation factor 1 α (EF1A), ribosomal protein L11 (RPL11), ribosomal protein L14 (RPL14), ribosomal protein S8 (RPS8), ribosomal protein S23 (RPS23), NADH-ubiquinone oxidoreductase (NADH), vacuolar-type H+-ATPase (ATPase), heat shock protein 70 (HSP70), 18S ribosomal RNA (18S), and 12S ribosomal RNA (12S) from the cowpea aphid, Aphis craccivora Koch were selected. Four algorithms, geNorm, Normfinder, BestKeeper, and the ΔCt method were employed to evaluate the expression profiles of these HKGs as endogenous controls across different developmental stages and temperature regimes. Based on RefFinder, which integrates all four analytical algorithms to compare and rank the candidate HKGs, RPS8, RPL14, and RPL11 were the three most stable HKGs across different developmental stages and temperature conditions. This study is the first step to establish a standardized qRT-PCR analysis in A. craccivora following the MIQE guideline. Results from this study lay a foundation for the genomics and functional genomics research in this sap-sucking insect pest with substantial economic impact.
Highlights
Quantitative real-time PCR is a powerful technique to quantify gene expressions during different biological processes [1]
The entire candidate housekeeping genes (HKGs) were visualized as a single amplicon with expected size on a 1.5% agarose gel (S1 Fig)
Discussion Quantitative real-time PCR (qRT-PCR) quantification demands a comprehensive normalization by housekeeping genes to counteract confounding variations in experimental data
Summary
Quantitative real-time PCR (qRT-PCR) is a powerful technique to quantify gene expressions during different biological processes [1]. QRT-PCR is one of the premier research tools, limitations still exist, several factors can influence the threshold cycle values including RNA quality, cDNA concentration, and PCR efficiency [2,3]. The most extensively adopted approach in qRT-PCR analysis is to normalize the expressions of target genes through measuring in parallel the expression of a housekeeping gene (HKG). Housekeeping genes, involved in PLOS ONE | DOI:10.1371/journal.pone.0130593. Housekeeping genes, involved in PLOS ONE | DOI:10.1371/journal.pone.0130593 June 19, 2015
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