Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression in sugarcane

Iskandar, Hayati Minarsih; Simpson, Robert S.; Casu, Rosanne E.; Bonnett, G. D.; Maclean, D. J.; Manners, John M.

doi:10.1007/bf02772676

Cited by 265 publications

(216 citation statements)

References 17 publications

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“…The high abundance of mRNA requires higher dilutions of cDNA to allow direct comparison with the target gene amplification. These stock dilutions require more work and introduce more error, leading to greater inaccuracy in RT-qPCR analyses (Iskandar et al, 2004). Consequently, it is advantageous to have a reference gene that is expressed at levels similar to those of the genes of interest, and to choose treatments that have little effect on the reference gene (Suzuki et al, 2000).…”

Section: Resultsmentioning

confidence: 99%

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

Stolf-Moreira

Lemos

Abdelnoor

et al. 2011

Pesq. agropec. bras.

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-The objective of this work was to validate, by quantitative PCR in real time (RT-qPCR), genes to be used as reference in studies of gene expression in soybean in drought-stressed trials. Four genes commonly used in soybean were evaluated: Gmβ-actin, GmGAPDH, GmLectin and GmRNAr18S. Total RNA was extracted from six samples: three from roots in a hydroponic system with different drought intensities (0, 25, 50, 75 and 100 minutes of water stress), and three from leaves of plants grown in sand with different soil moistures (15, 5 and 2.5% gravimetric humidity). The raw cycle threshold (Ct) data were analyzed, and the efficiency of each primer was calculated for an overall analysis of the Ct range among the different samples. The GeNorm application was used to evaluate the best reference gene, according to its stability. The GmGAPDH was the least stable gene, with the highest mean values of expression stability (M), and the most stable genes, with the lowest M values, were the Gmβ-actin and GmRNAr18S, when both root and leaves samples were tested. These genes can be used in RT-qPCR as reference gene for expression analysis.Index terms: Glycine max, expression stability, RT-qPCR, water deficit. Identificação de genes de referência para análise de expressão por PCR quantitativo em tempo real, em soja submetida à secaResumo -O objetivo deste trabalho foi validar, pela técnica de PCR quantitativo em tempo real (RT-qPCR) genes para serem utilizados como referência em estudos de expressão gênica em soja, em ensaios de estresse hídrico. Foram avaliados quatro genes comumente utilizados em soja: Gmβ-actin, GmGAPDH, GmLectin e GmRNAr18S. O RNA total foi extraído de seis amostras: três amostras de raízes em sistema de hidroponia com diferentes intensidades de déficit hídrico (0, 25, 50, 75 e 100 minutos de estresse hídrico), e três amostras de folhas de plantas cultivadas em areia com diferentes umidades do solo (15, 5 e 2,5% de umidade gravimétrica). Os dados brutos do intervalo "cycle threshold" (Ct) foram analisados, e a eficiência de cada iniciador foi calculada para uma analise da Ct entre as diferentes amostras. A aplicação do programa GeNorm foi utilizada para a avaliação dos melhores genes de referência, de acordo com a estabilidade. O GmGAPDH foi o gene menos estável, com o maior valor médio de estabilidade de expressão (M), e os genes mais estáveis, com menor valor de M, foram o Gmβ-actin e GmRNAr18S, tanto nas amostras de raízes como nas de folhas. Estes genes podem ser usados em RT-qPCR como gens de referência para análises de expressão gênica.Termos para indexação: Glycine max, estabilidade de expressão, RT-qPCR, déficit hídrico.

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Section: Resultsmentioning

confidence: 99%

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

Stolf-Moreira

Lemos

Abdelnoor

et al. 2011

Pesq. agropec. bras.

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“…The transcriptomic data-based method has the advantage of identifying novel candidate reference genes that are more stable than the conventional ones. Validation of reference genes for qPCR has been reported in many plant species; for example, GAPDH in sugarcane and chickpea [15,28]; EF1a in potato, Arabidopsis, and rice [22,23,25,29]; RPL2, PP2Acs, ACT and UBI in tomato [21]; and SKIP16, UKN1 and UKN2 in soybean [9] (Table 1). In rice, UBQ5 and EF1a were found to be the most stable across 25 rice samples which were derived from different tissues at various developmental stages [22,25].…”

mentioning

confidence: 99%

High-quality reference genes for quantifying the transcriptional responses of Oryza sativa L. (ssp. indica and japonica) to abiotic stress conditions

2013

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Rice (Oryza sativa L.) is important to food security and is also an excellent model plant for numerous cereal crops. A functional genomics study in rice includes characterization of the expression dynamics of genes by quantitative real-time PCR (qPCR) analysis; this is a significant key for developing rice varieties that perform well in the face of adverse climate change. The qPCR analysis requires the use of appropriate reference genes in order to make any quantitative interpretations meaningful. Here, the new potential reference genes were selected from a huge public database of rice microarray experiments. The expression stability of 14 candidates and 4 conventional reference genes was validated by geNorm PLUS and NormFinder software. Seven candidates are superior to the conventionally used reference genes in qPCR and three genes can be used reliably for quantitating the expression of genes involved in abiotic stress responses. These high-quality references EP (LOC_Os05g08980), HNR (LOC_Os01g71770), and TBC (LOC_Os09g34040) worked very well in three indica genotypes and one japonica genotype. One of indica genotypes including the Jasmine rice, KDML105 developed in Thailand for which no reference genes have been reported until now.

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“…Most of these studies have been done with plants, such as wheat (Paolacci et al, 2009), barley (Burton et al, 2004), rice (Kim et al, 2003;Ding et al, 2004;Jain et al, 2006), potato (Nicot et al, 2005), soybean (Jian et al, 2008), grape (Reid et al, 2006), poplar (Brunner et al, 2004), tomato (Coker and Davies, 2003;Expósito-Rodríguez et al, 2008), coffee (BarsalobresCavallari et al, 2009), Arabidopsis thaliana (Czechowski et al, 2005;Remans et al, 2008), sugarcane (Iskandar et al, 2004), Eremosparton songoricum (Li et al, 2012), Lolium perenne (Lee et al, 2010), lettuce (Borowski et al, 2014), strawberry (Galli et al, 2015), and Salicornia europaea (Xiao et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Identification of reference genes for RT-qPCR analysis in peach genotypes with contrasting chilling requirements

et al. 2017

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ABSTRACT. Selecting and validating reference genes are the first steps in studying gene expression by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR). The present study aimed to evaluate the stability of five reference genes for the purpose of normalization when studying gene expression in various cultivars of Prunus persica with different chilling requirements. Flower bud tissues of nine peach genotypes from Embrapa's peach breeding program with different chilling requirements were used, and five candidate reference genes based on the RT-qPCR that were useful for studying the relative quantitative gene expression and stability were evaluated using geNorm, NormFinder, and bestKeeper software packages. The results indicated that among the genes tested, the most stable genes to be used as reference genes are Act and UBQ10. This study is the first survey of the stability of reference genes in peaches under chilling stress and provides guidelines for more accurate RT-qPCR results.

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Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression in sugarcane

Cited by 265 publications

References 17 publications

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

High-quality reference genes for quantifying the transcriptional responses of Oryza sativa L. (ssp. indica and japonica) to abiotic stress conditions

Identification of reference genes for RT-qPCR analysis in peach genotypes with contrasting chilling requirements

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