Screening of Reference Genes under Biotic Stress and Hormone Treatment of Mung Bean (Vigna radiata) by Quantitative Real-Time PCR

Abstract

Mung bean (Vigna radiata) production has been greatly threatened by numerous diseases. Infection with these pathogens causes extensive changes in gene expression and the activation of hormone signal transduction. Quantitative real-time PCR (qRT-PCR) is the most common technique used for gene expression validation. Screening proper reference genes for mung bean under pathogen infection and hormone treatment is a prerequisite for ensuring the accuracy of qRT-PCR data in mung bean disease-resistance research. In this study, six candidate reference genes (Cons4, ACT, TUA, TUB, GAPDH, and EF1α) were selected to evaluate the expression stability under four soil-borne disease pathogens (Pythium myriotylum, Pythium aphanidermatum, Fusarium oxysporum, and Rhizoctonia solani) and five hormone treatments (SA, MeJA, ETH, ABA, and GA3). In the samples from different treatments, the Ct value distribution of the six candidate reference genes was different. Under the condition of hormone treatment, the Ct value ranged from a minimum of 17.87 for EF1α to a maximum of 29.63 for GAPDH. Under the condition of pathogen infection, the Ct value ranged from a minimum of 19.43 for EF1α to a maximum of 31.82 for GAPDH. After primer specificity analysis, it was found that GAPDH was not specific, so the five reference genes Cons4, ACT, TUA, TUB, and EF1α were used in subsequent experiments. The software products GeNorm, NormFinder, BestKeeper and RefFinder were used for qRT-PCR data analysis. In general, the best candidates reference genes were: TUA for SA, ABA, GA3, and Pythium myriotylum treatment; TUB for ETH treatment; ACT for MeJA and Fusarium oxysporum treatment; and EF1α for Pythium aphanidermatum and Rhizoctonia solani treatment. The most stably expressed genes in all samples were TUA, while Cons4 was the least stable reference gene. Finally, the reliability of the reference gene was further validated by analysis of the expression profiles of four mung bean genes (Vradi0146s00260, Vradi0158s00480, Vradi07g23860, and Vradi11g03350) selected from transcriptome data. Our results provide more accurate information for the normalization of qRT-PCR data in mung bean response to pathogen interaction.