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

Overview

Journal Genes (Basel)

Publisher MDPI

Date 2023 Sep 28

PMID 37761879

Authors

Yanyan Zhou

Huan Liu

Ting Wu

Yu Zheng

Ruimin Wang

Dong Xue

Qiang Yan

Xingxing Yuan

Xin Chen

Affiliations

Soon will be listed here.

Abstract

Mung bean () 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 (, , , , , and ) were selected to evaluate the expression stability under four soil-borne disease pathogens (, , , and ) and five hormone treatments (SA, MeJA, ETH, ABA, and GA). 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 to a maximum of 29.63 for . Under the condition of pathogen infection, the Ct value ranged from a minimum of 19.43 for to a maximum of 31.82 for . After primer specificity analysis, it was found that was not specific, so the five reference genes , , , and 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: for SA, ABA, GA3, and treatment; for ETH treatment; for MeJA and treatment; and for and treatment. The most stably expressed genes in all samples were , while 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 (, , , and ) selected from transcriptome data. Our results provide more accurate information for the normalization of qRT-PCR data in mung bean response to pathogen interaction.

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