Legume Research

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Research Article

Legume Research, volume 44 issue 6 (june 2021) : 646-651

Reference Genes for Quantitative Real-Time PCR Analysis of Gene Expression in Mung Bean under Abiotic Stress and Cercospora canescens Infection

X.W. Ke1, L.H. Yin1, J. Xu1, W.N. Sun1, X.D. Xu1, Y.X. Guo1, Y.H. Zuo1,*
1Heilongjiang Bayi Agricultural University, National Coarse Cereals Engineering Research Center, Heilongjiang Provincial Key Laboratory of Crop-Pest Interaction Biology and Ecological Control, Daqing 163319, China.

  • Submitted13-06-2019|

  • Accepted29-12-2019|

  • First Online 15-05-2020|

  • doi 10.18805/LR-507

Cite article:- Ke X.W., Yin L.H., Xu J., Sun W.N., Xu X.D., Guo Y.X., Zuo Y.H. (2020). Reference Genes for Quantitative Real-Time PCR Analysis of Gene Expression in Mung Bean under Abiotic Stress and Cercospora canescens Infection . Legume Research. 44(6): 646-651. doi: 10.18805/LR-507.

ABSTRACT

The objective of the study was to identify suitable reference genes that can be used for quantitative real-time PCR (qPCR) analysis in mung bean (Vigna radiata). Therefore, 10 potential reference genes were selected and the results showed that ubiquitin-conjugating enzyme was suitable as reference under drought and pathogen infection stress; elongation factor 1-á was the most stable gene under waterlogging; and actin performed the best under saline stress. These selected reference genes were further confirmed by analysis of the expression profiles of catalase and peroxidase under waterlogging. Our results will contribute to the improvement of the accuracy of gene expression evaluation in mung bean.

INTRODUCTION

Mung bean [Vigna radiata (L.) R. Wilczek] is one of the most important pulse crops in South, East and Southeast Asia (Gokulakrishnan et al., 2012). Similar to other legumes, mung bean fixes atmospheric nitrogen via its roots in symbiosis with Rhizobium bacteria to not only meet its own nitrogen needs but to benefit subsequent crops (Zang et al., 2015; Mondal et al., 2011). However, mung bean is often cultivated on marginal soils with low inputs, where it is subjected to the action of numerous abiotic and biotic stress, including high temperature, waterlogging, drought, salinity and pathogen infection and therefore severely hinders the yield (Hanumantharao et al., 2016; Manjunath et al., 2013; Duraimurugan and Tyagi, 2014; Dutta and Bera, 2014).
 
Determination of gene expression alterations during stress induction and recovery can provide important insight into how plants cope with stress factors. Thus, mung bean gene expression studies have profound implications on strategies to improve mung bean production. Gene expression analysis using qPCR is a widely used method due to its sensitivity, specificity, dynamic range and high throughput capacity (Wong and Medrano, 2005). However, qPCR analysis requires a suitable reference gene whose expression level remains stable under both control and experimental conditions (Guénin et al., 2009). Commonly used reference genes are housekeeping genes, such as actin (ACT), beta-tubulin (β-TUB), polyubiquitin (UBQ), glyceraldehyde-3-phoshate dehydrogenase (GAPDH), tonoplast intrinsic protein 41 (TIP41), alpha-tubulin (a-TUB), ubiquitin-conjugating enzyme (UBC), adenine phosphoribosyl transferase (APT), 60S ribosomal protein (60S) and the elongation factor (EF) (Chen et al., 2017; Li et al., 2017). However, no reference genes are universally applicable across different species and all experimental conditions. It is, therefore, crucial to verify the expression stability of putative normalizers in each set of experimental conditions, as the selection of a stably expressed reference gene is critically important for the accuracy of the results. To date, appropriate reference genes have not been reported for mung bean. Therefore, in order to identify suitable reference genes that could be used for qPCR analysis in mung bean, 10 potential reference genes (EF1a, ACT, UBQ, GAPDH, TIP41, a-TUB, β-TUB, UBC, APT and 60S) were selected and analyzed in a set of 24 samples. The results of this study should provide useful guidelines for further gene expression analyses in mung bean.

MATERIALS AND METHODS

The experiment was conducted in 2017-05 to 2018-03 at Heilongjiang Bayi Agricultural University, China. Mung bean cultivar LvFeng 5 (LF5) used in this study were obtained from National Coarse Cereals Engineering Research Center, Daqing, China. The plants were grown in a growth chamber at 24°C - 27°C under short-day conditions (8 h light/16 h dark, 150 μmolm-2s-1). Samples for drought stress was performed on 10-day old seedlings by withholding water (Nasrollahi et al., 2014) and euphylla were sampled at 0, 1, 3, 6, 9 and 12 d after treatment. For waterlogging, the potted 10-day old seedlings were placed into larger tanks and the soil surface was submerged approximately 2 cm below the surface of the water (Parelle et al., 2006) and samples were collected at 0, 1, 2, 5, 10 and 15 d after treatment. For salinity stress, 10-day old seedlings potted with river sand were treated with 100 mM neutral and alkali salts (NaCl: Na2SO4: NaHCO3: Na2CO3 = 3:3:5:1) (Zhang et al., 2010) and samples were collected at 0 h, 12 h, 24 h, 48 h, 72 h and 144 h after treatment. For biotic stress, the euphylla were inoculated with conidia suspension of Cercospora canescens (Booker and Umaharan, 2007). Leaves were harvested at 0, 1, 3, 6, 10 and 15 d post-inoculation (dpi). Each sample with three biological replicates were used for RNA extraction.
 
Total RNA was extracted using the TRIzol reagent (Invitrogen, USA) following the manufacturer instructions and 1 μg of total RNA was used for cDNA synthesis using a PrimeScriptTM RT Reagent Kit following the instructions (TaKaRa, China). The final cDNA products were diluted five folds prior to use in qPCR. Primers of the ten candidate genes were designed based on the sequences obtained from mung bean genome (Kang et al., 2014) using a web based PrimerQuest Tool (https://sg.idtdna.com/Primerquest/Home/Index) and listed in Table 1.
 

Table 1: Reference genes used for gene expression normalization in mung bean.


 
qPCR was performed in a Bio-Rad CFX96 PCR system using SYBR Premix EX Taq (TaKaRa, China) following the manufacturer instructions. The PCR conditions were as follows: 95°C for 1 min, 40 cycles of 95°C for 15 s, 55°C for 30 s and 72°C for 30 s; then, the temperature was increased by 0.3°C every 10 s to obtain the product melt curve. All qPCR assays were performed in three technical replicates. Amplification efficiency (E) and correlation coefficient (R2) were tested by a standard curve based on the diluted (4×) cDNA series. The value of E was estimated by using the slope of the standard curve and the equation E=(10-1/slope-1)×100% (Li et al., 2012).
 
Three programs geNorm (Vandesompele et al., 2002), NormFinder (Andersen et al., 2004) and BestKeeper (Pfaffl et al., 2004) were used to evaluate the expression stability of the 10 candidate genes. And the data generated by the three algorithms were further compared using the web-based comprehensive tool RefFinder (Xie et al., 2012).
 
To validate reliability of the reference genes obtained in this study, the expression level of catalase (CAT) and peroxidase (POD) genes of cv. LF5 under waterlogging were normalized against the most stable, the least stable and the most stable combination of genes. The amount of transcripts accumulated for the two genes normalized using these different reference genes were analyzed using the 2-ΔΔCt method (Livak and Schmittgen, 2001). Three technical and biological replicates were performed for all analyses in this study.

RESULTS AND DISCUSSION

Primer specificity and efficiency
 
The amplification specificity of the primers was confirmed by a single peak in the melting curve (Fig 1). According to the slope of the standard curve, the amplification efficiency of all primers ranged between 85% (UBQ) and 110% (APT) with regression coefficient (R2) varied from 0.991 to 0.999 (Table 1). Auler et al., (2017) mentioned that the amplification efficiency between 80% and 120% were considered acceptable, indicative of a reasonable amplification efficiency of the primers used in current study.
 

Table 1: Reference genes used for gene expression normalization in mung bean.


 
Ct value distribution
 
To investigate the expression stability of the 10 candidate reference genes, the expression levels of these genes in all samples tested in this study were confirmed by their cycle threshold (Ct) values. The Ct values of the 10 genes varied from 19 to 36 in all samples and most of them were between 20 and 25 (Fig 2). EF1a was the most highly expressed gene with lowest Ct values (from 19 to 22), while APT showed greatest difference range with Ct values from 25 to 36 indicating an unstable expression in different conditions.
 

Fig 2: Expression levels of 10 candidate reference genes across all experimental samples. The box graph indicates the interquartile range, the median and maximum/minimum values.


 
Gene expression stability
 
Under drought stress, UBQ, 60S and ACT were the most stable genes according to geNorm, NormFinder and BestKeeper, respectively (Table 2). However comprehensive ranking of genes by RefFinder showed that UBC was the most stable gene.
 

Table 2: Gene expression stability ranked by geNorm, NormFinder, BestKeeper and RefFinder.


       
Under waterlogging (Table 2), the stability ranking established by geNorm, NormFinder and BestKeeper showed that a-TUB, UBC and EF1a were the most stable genes, respectively. However, comprehensive ranking of genes by RefFinder indicated that the best reference gene was EF1a.
       
For C. canescens infection (Table 2), UBQ, UBC and EF1α was ranked highest by geNorm, NormFinder and BestKeeper, respectively. And further comprehensive comparison by RefFinder demonstrated that UBC was the most stable gene.
       
According to the geNorm, NormFinder and BestKeeper, ACT, TIP41 and β-TUB were the most stable genes under saline treatment, respectively, whereas the comprehensive ranking obtained from RefFinder revealed that ACT was the optimal reference gene (Table 2).
       
The discrepancies in these results from different programs were most likely due to the use of different algorithms. NormFinder and geNorm both select optimal internal reference genes based on gene expression stability (M value), while BestKeeper assesses stability based on correlation coefficient, standard deviation and coefficient of variation (Pfaffl et al., 2004). Therefore, a web tool RefFinder was used for overall final rankings by measuring the geometric mean of the attributed weights, which has been widely used to evaluate suitable reference genes (Duan et al., 2017; Walling et al., 2018).
 
The best pair of reference genes
 
Pairwise variation (Vn/Vn+1) with a threshold 0.15 was used to determine the optimal pair of reference genes by using geNorm (Fig 3). A V2/3 = 0.082 was obtained for the pair of UBQ and UBC under drought stress and the pair of a-TUB and UBC were determined to be the optimal normalization factors for waterlogging. Yet in fungal infection, the combination of UBQ and UBC yielded a V2/3 = 0.127. According to the V2/3 value (0.021), ACT combined with TIP41 was the best pair of genes for salinity stress.
 

Fig 3: Pairwise variation analyses of the candidate reference genes. The pairwise variation (Vn/Vn+1) was analyzed between the normalization factors NFn and NFn+1 by the geNorm program to determine the optimal number of reference genes required for qPCR data normalization.


 
Reference gene validation
 
To validate the selected reference genes, the expression levels of catalase (CAT) and peroxidase (POD) under waterlogging were analyzed by qPCR (Fig 3). The relative expression levels of CAT and POD were not significantly different when normalized by EF1a or the combination ofa-TUB and UBC, while the transcript levels were underestimated by using the least stable gene APT. These results further confirmed the importance of the appropriate choice of reference gene for normalization of the target gene expression levels.

CONCLUSION

In summary, we identified stable reference genes in mung bean using a set of different experimental stress conditions. UBC is an optimal reference gene under drought and inoculation conditions. In the waterlogging treatment, EF1α was the most stable reference gene and under saline stress, ACT is the best reference gene. These results will provide a basis for accurate gene expression evaluation in mung bean in future research.

ACKNOWLEDGEMENT

The authors would like to acknowledge Dr Yichao Huang (Jinan University, Guangzhou) for assisting in manuscript preparation. This work was supported by University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province (UNPYSCT-2016201 and UNPYSCT-2017113), Heilongjiang Bayi Agricultural University Support Program for San Heng San Zong (ZRCQC201901), Research and Development Plan of Applied Technology in Heilongjiang Province (GA19B104) and the Coarse Cereals Specialty Discipline Construction Project.

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