Abstract
Quantitative real-time PCR (qRT-PCR) is a reliable and reproducible technique for measuring mRNA expression. To facilitate gene expression studies and obtain more accurate qRT-PCR analysis, normalization relative to stable housekeeping genes is mandatory. In this study, ten housekeeping genes, including beta-actin (Actin) , elongation factor 1 α (EF1A) , glyceralde hyde-3-phosphate dehydrogenase (GAPDH) , ribosomal protein L13 (RPL13) , ribosomal protein 49 (RP49) , α-tubulin (Tubulin) , vacuolar-type H+-ATPase (v-ATPase) , succinate dehydrogenase subunit A (SDHA) , 28S ribosomal RNA (28S) , and 18S ribosomal RNA (18S) from the two-spotted spider mite, Tetranychus urticae, were selected as the candidate reference genes. Four algorithms, geNorm, Normfinder, BestKeeper, and the ΔCt method, were used to evaluate the performance of these candidates as endogenous controls across different developmental stages. In addition, RefFinder, which integrates the above-mentioned software tools, provided the overall ranking of the stability/suitability of these candidate reference genes. Among them, PRL13 and v-ATPase were the two most stable housekeeping genes across different developmental stages. This work is the first step toward establishing a standardized qRT-PCR analysis in T. urticae following the MIQE guideline. With the recent release of the T. urticae genome, results from this study provide a critical piece for the subsequent genomics and functional genomics research in this emerging model system.
Highlights
Quantitative real-time PCR is a rapid and reliable method for the detection and quantification of gene expression during different biological processes [1]
Validation and transcriptional profiling of candidate reference genes Initially, ten candidate reference genes were investigated by reverse transcription polymerase chain reaction (RT-PCR)
Discussion Quantitative real-time PCR (qRT-PCR) quantification demands a comprehensive normalization by reference genes to offset confounding variations among the extensive experimental datasets
Summary
Quantitative real-time PCR (qRT-PCR) is a rapid and reliable method for the detection and quantification of gene expression during different biological processes [1]. QRT-PCR analysis has been a primary tool in the molecular biology research, limitations still exist, including variation in RNA extraction, reverse transcription and normalization, and PCR efficiency [2, 3]. A critical component in qRT-PCR analysis is to normalize data by measuring in parallel the expression of a reference gene from the same samples. Housekeeping genes, involved in basic cellular functions, are typically maintaining stable and constitutive expression in all cells and regardless of physiological conditions. Housekeeping genes have been widely adopted in many molecular and genomics studies as a reference for calibration purposes, including qRT-PCR analysis [1,4]
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