Selection of Reference Genes for RT-qPCR Analysis in the Hawthorn Spider Mite, Amphitetranychus viennensis (Acarina: Tetranychidae), Under Acaricide Treatments

Abstract

Hawthorn spider mite, Amphitetranychus viennensis Zacher, one of the most damaging arthropod pests for Rosaceaous fruit trees and ornamentals, has developed resistance to most of the commercially available acaricides. To understand the molecular basis of acaricide resistance, a standardized protocol for real-time quantitative reverse transcription PCR (RT-qPCR) following the MIQE (minimum information for publication of quantitative real time PCR experiments) guidelines is needed. In this study, we screened for the internal references in A. viennensis to study in acaricide resistance. In total, 10 candidate reference genes, including EF1A, 28S rRNA, 18S rRNA, α-tubulin, Actin3, RPS9, GAPDH, V-ATPase B, RPL13, and V-ATPase A, were assessed under the treatments of four commonly used acaricides with distinct mode-of-actions (MOAs). Based on the Insecticide Resistance Action Committee MOA classification, avermectin, bifenazate, spirodiclofen, and fenpropathrin belong to group 6, 20D, 23, and 3A, respectively. The expression profiles of these candidate genes were evaluated using geNorm, Normfinder, BestKeeper, and ∆Ct methods, respectively. Eventually, different sets of reference genes were recommended for each acaricide according to RefFinder, a comprehensive platform integrating all four above-mentioned algorithms. Specifically, the top three recommendations were 1) 28S, V-ATPase A, and Actin 3 for avermectin, 2) GAPDH, RPS9, and 28S for bifenazate, 3) Actin 3, V-ATPase B, and α-tubulin for spirodiclofen, and 4) Actin 3, α-tubulin, and V-ATPase A for fenpropathrin. Although unique sets of genes are proposed for each acaricide, α-tubulin, EF1A, and GAPDH are the most consistently stably expressed reference genes when A. viennensis was challenged chemically. Our findings lay the foundation for the study of acaricide resistance in the phytophagous mites in general, and in the hawthorn spider mite, A. viennensis, in particular.

Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles

“…Scatter plots were drawn to visualize the reference gene expression levels and variations. The comparative delta-Ct method [ 46 , 47 ], GeNorm [ 47 – 49 ], NormFinder [ 50 , 51 ], BestKeeper [ 52 – 55 ], and RefFinder [ 56 ] algorithms were used to assess the expression stability of selected genes. The specific methods of the five algorithms are shown in Supplementary 1 .…”

Identification and validation of the reference genes in the echiuran worm Urechis unicinctus based on transcriptome data

“…Real-time quantitative PCR (RT-qPCR) is the most widely used technique for relative gene quantification because of its good repeatability, high sensitivity, strong specificity, high throughput, simplicity, speed, and low cost [ 1 – 3 ]. However, the biological variability of initial materials and the technical factors involved in sample preparation, such as the quantity of cDNA, RNA extraction, RNA integrity, and storage conditions will inevitably affect the accuracy of RT-qPCR [ 4 – 6 ]. Therefore, normalization is necessary to correct for variations in template quantity.…”

“…In general, constitutively expressed housekeeping genes are used as reference genes, such as actin, elongation factor, glyceraldehyde-3-phosphate dehydrogenase, ribosomal RNA, translation initiation factor, tubulin, and ubiquitin [ 7 – 9 ]. However, many studies have shown that some of these genes are not always stable and their expression levels vary greatly under specific experimental conditions [ 6 , 10 , 11 ]. This is especially true for non-model organisms, which currently lag behind well-characterized model organisms in terms of genomic resources and empirically tested reference genes [ 4 , 6 , 10 , 11 ].…”

“…However, many studies have shown that some of these genes are not always stable and their expression levels vary greatly under specific experimental conditions [ 6 , 10 , 11 ]. This is especially true for non-model organisms, which currently lag behind well-characterized model organisms in terms of genomic resources and empirically tested reference genes [ 4 , 6 , 10 , 11 ]. Moreover, recent studies have shown that it is impossible to totally normalize gene expression data from all sample types using a single gene [ 6 , 10 ].…”

“…This is especially true for non-model organisms, which currently lag behind well-characterized model organisms in terms of genomic resources and empirically tested reference genes [ 4 , 6 , 10 , 11 ]. Moreover, recent studies have shown that it is impossible to totally normalize gene expression data from all sample types using a single gene [ 6 , 10 ]. Therefore, two or more reference genes are desirable to improve the reliability and accuracy of the RT-qPCR results.…”