Exploring Valid Reference Genes for Quantitative Real-Time PCR Analysis in Sesamia inferens (Lepidoptera: Noctuidae)

Abstract

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (−8, −6, −4, −2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens.

Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi

“…Similar results were commonly obtained in many studies (e.g., Kuijk et al, 2007; Silveira et al, 2009;Guelke et al, 2015). Since the V value is dependent on both the diversity of samples and the stability of potential reference genes, dividing the data sets into more detailed sub-groups and applying as many reference genes as suggested by geNorm are the correspondingly feasible solutions (Sun et al, 2015). However, considering the complexity, economic cost and work load, the practical solution is the use of top three stable genes when greater than or equal to three reference genes were recommended by geNorm, and such a strategy has been widely employed in many studies (e.g.…”

“…However, considering the complexity, economic cost and work load, the practical solution is the use of top three stable genes when greater than or equal to three reference genes were recommended by geNorm, and such a strategy has been widely employed in many studies (e.g. Ma et al, 2013;Sun et al, 2015).…”

“…However, according to the geNorm manual, the threshold of 0.15 must not be taken as an absolute cut-off, and it may vary significantly depending on the selected genes and tested samples. Considering the complexity of the experimental work and higher cost when using more reference genes, three of the most stable genes should be employed in the situation of too many or even no optimal number of genes were determined (Sun et al, 2015). As demonstrated above, the gene combinations of RPS15 and RPL17 for siphon, TubB, TubA and RPL17 for pharynx, UBQ, RPS15 and RPL17 for intestine were recommended for further expression analysis in temperature stress assessment.…”

Selecting and validating reference genes for quantitative real-time PCR in Plutella xylostella (L.)

“…RPS13 and RPS20 were the most stably expressed genes in Sesamia inferens across different tissues (Sun et al 2015).…”

“…Although there have been extensive studies on selection and validation of reference genes in Lepidoptera insects Shakeel et al 2015;Sun et al 2015;Teng et al 2012;Zhu et al 2014), to the best of D r a f t our knowledge, two papers have been published regarding P. xylostella Teng et al 2012 glycerol-3-phosphate dehydrogenase-2 (G3PDH), E2F transcription factor 4 (E2F), and ribosomal protein 49 (rp49) Teng et al 2012). In this study, a comprehensive and systemic assessment of candidate reference genes from the P. and Delta Ct) and a web-based tool (RefFinder).…”