Dataset Information

Selection of optimal reference genes for qRT-PCR analysis of shoot development and graviresponse in prostrate and erect chrysanthemums.

ABSTRACT: The prostrate cultivars of ground-cover chrysanthemum have been used in landscape gardening due to their small stature, large crown width and strong branching ability. qRT-PCR is a rapid and powerful tool for gene expression analysis, while its accuracy highly depends on the stability of reference genes. The paucity of authentic reference genes presents a major hurdle in understanding the genetic regulators of prostrate architecture. Therefore, in order to reveal the regulatory mechanism of prostrate growth of chrysanthemum stems, here, stable reference genes were selected for expression analysis of key genes involved in shoot development and graviresponse. Based on transcriptome data, eleven reference genes with relatively stable expression were identified as the candidate reference genes. After the comprehensive analysis of the stability of these reference genes with four programs (geNorm, NormFinder, BestKeeper and RefFinder), we found that TIP41 was the most stable reference gene in all of the samples. SAND was determined as a superior reference gene in different genotypes and during the process of shoot development. The optimal reference gene for gravitropic response was PP2A-1. In addition, the expression patterns of LA1 and PIN1 further verified the reliability of the screened reference genes. These results can provide more accurate and reliable qRT-PCR normalization for future studies on the expression patterns of genes regulating plant architecture of chrysanthemums.

SUBMITTER: Li X

PROVIDER: S-EPMC6880974 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Selection of optimal reference genes for qRT-PCR analysis of shoot development and graviresponse in prostrate and erect chrysanthemums.

Li Xiaowei X Yang Yujie Y Ahmad Sagheer S Sun Ming M Yuan Cunquan C Zheng Tangchun T Han Yu Y Cheng Tangren T Wang Jia J Zhang Qixiang Q

PloS one 20191127 11

The prostrate cultivars of ground-cover chrysanthemum have been used in landscape gardening due to their small stature, large crown width and strong branching ability. qRT-PCR is a rapid and powerful tool for gene expression analysis, while its accuracy highly depends on the stability of reference genes. The paucity of authentic reference genes presents a major hurdle in understanding the genetic regulators of prostrate architecture. Therefore, in order to reveal the regulatory mechanism of pros ...[more]

PMID: 31774840

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Project description:BackgroundNormalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.ResultsWe propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.ConclusionsThe proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.

Project description:Quantitative real-time polymerase chain reaction (qRT-PCR) is the most important tool in measuring levels of gene expression due to its accuracy, specificity, and sensitivity. However, the accuracy of qRT-PCR analysis strongly depends on transcript normalization using stably expressed reference genes. The aim of this study was to find internal reference genes for qRT-PCR analysis in various experimental conditions for seed, adventitious underground bud, and other organs of leafy spurge. Eleven candidate reference genes (BAM4, PU1, TRP-like, FRO1, ORE9, BAM1, SEU, ARF2, KAPP, ZTL, and MPK4) were selected from among 171 genes based on expression stabilities during seed germination and bud growth. The other ten candidate reference genes were selected from three different sources: (1) 3 stably expressed leafy spurge genes (60S, bZIP21, and MD-100) identified from the analyses of leafy spurge microarray data; (2) 3 orthologs of Arabidopsis "general purpose" traditional reference genes (GAPDH_1, GAPDH_2, and UBC); and (3) 4 orthologs of Arabidopsis stably expressed genes (UBC9, SAND, PTB, and F-box) identified from Affymetrix ATH1 whole-genome GeneChip studies. The expression stabilities of these 21 genes were ranked based on the C(T) values of 72 samples using four different computation programs including geNorm, Normfinder, BestKeeper, and the comparative ?C(T) method. Our analyses revealed SAND, PTB, ORE9, and ARF2 to be the most appropriate reference genes for accurate normalization of gene expression data. Since SAND and PTB were obtained from 4 orthologs of Arabidopsis, while ORE9 and ARF2 were selected from 171 leafy spurge genes, it was more efficient to identify good reference genes from the orthologs of other plant species that were known to be stably expressed than that of randomly testing endogenous genes. Nevertheless, the two newly identified leafy spurge genes, ORE9 and ARF2, can serve as orthologous candidates in the search for reference genes from other plant species.

Dataset Information

Selection of optimal reference genes for qRT-PCR analysis of shoot development and graviresponse in prostrate and erect chrysanthemums.

Publications

Selection of optimal reference genes for qRT-PCR analysis of shoot development and graviresponse in prostrate and erect chrysanthemums.

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