Validation of reference housekeeping genes for gene expression studies in western corn rootworm (Diabrotica virgifera virgifera).

Thaís Barros Rodrigues,Natalie Matz,Xuguo Zhou,Haichuan Wang,Danielle Cunha Cardoso,Blair Siegfried,Chitvan Khajuria,Fernando Hercos Valicente,Olle Terenius

doi:10.1371/journal.pone.0109825

Abstract

Quantitative Real-time PCR (qRT-PCR) is a powerful technique to investigate comparative gene expression. In general, normalization of results using a highly stable housekeeping gene (HKG) as an internal control is recommended and necessary. However, there are several reports suggesting that regulation of some HKGs is affected by different conditions. The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), is a serious pest of corn in the United States and Europe. The expression profile of target genes related to insecticide exposure, resistance, and RNA interference has become an important experimental technique for study of western corn rootworms; however, lack of information on reliable HKGs under different conditions makes the interpretation of qRT-PCR results difficult. In this study, four distinct algorithms (Genorm, NormFinder, BestKeeper and delta-CT) and five candidate HKGs to genes of reference (β-actin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; β-tubulin; RPS9, ribosomal protein S9; EF1a, elongation factor-1α) were evaluated to determine the most reliable HKG under different experimental conditions including exposure to dsRNA and Bt toxins and among different tissues and developmental stages. Although all the HKGs tested exhibited relatively stable expression among the different treatments, some differences were noted. Among the five candidate reference genes evaluated, β-actin exhibited highly stable expression among different life stages. RPS9 exhibited the most similar pattern of expression among dsRNA treatments, and both experiments indicated that EF1a was the second most stable gene. EF1a was also the most stable for Bt exposure and among different tissues. These results will enable researchers to use more accurate and reliable normalization of qRT-PCR data in WCR experiments.

Highlights

The western corn rootworm (WCR), Diabrotica v. virgifera LeConte (Coleoptera: Chrysomelidae), is one of the most important insect pests of cultivated maize in North America with annual losses in yield and control expenditures exceeding U.S $1 billion annually [1,2]
Some quantitative RT-PCR (qRT-PCR) normalization studies have reported a lack of stable expression of those genes among variables [12,15] and a number of studies have suggested that there is no single reference gene for all these variables [19,20,21,22]
This is the first study to validate a set of candidate reference genes for qRT-PCR in D. v. virgifera by several algorithms under different experimental conditions

Summary

Introduction

The western corn rootworm (WCR), Diabrotica v. virgifera LeConte (Coleoptera: Chrysomelidae), is one of the most important insect pests of cultivated maize in North America with annual losses in yield and control expenditures exceeding U.S $1 billion annually [1,2]. A number of strategies, such as chemical insecticides, crop rotation, biological control and transgenic plants expressing toxins from Bacillus thuringiensis (Bt), have been used to manage rootworm populations [3,4,5,6]. Because of interest in RNAi as a rootworm pest management tool and to identify differentially expressed genes associated with a number of different traits, including insecticide and Bt resistance, quantitative RT-PCR (qRT-PCR) has become an important research tool for WCR research. The accuracy, high sensitivity and specificity of qRT-PCR depend on many factors, such as the number of replications, primer efficiency, and the choice of appropriate reference genes [12]. The choice of appropriate reference HKGs is an essential and crucial step to allow proper interpretation of results. Many studies have been conducted to identify HKGs in a variety of organisms [12,15,16,17,18] and some studies have suggested that there is no single reference gene that is appropriate for all variables [19,20,21,22]

Methods

Results

Conclusion