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      Screening Reliable Reference Genes for RT-qPCR Analysis of Gene Expression in Moringa oleifera

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          Abstract

          Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associated with important agronomical traits. Here, we screened reliable reference genes for accurately quantifying the expression of target genes using the technique of real-time quantitative polymerase chain reaction (RT-qPCR) in M. oleifera. Eighteen candidate reference genes were selected from a transcriptome database, and their expression stabilities were examined in 90 samples collected from the pods in different developmental stages, various tissues, and the roots and leaves under different conditions (low or high temperature, sodium chloride (NaCl)- or polyethyleneglycol (PEG)- simulated water stress). Analyses with geNorm, NormFinder and BestKeeper algorithms revealed that the reliable reference genes differed across sample designs and that ribosomal protein L1 ( RPL1) and acyl carrier protein 2 ( ACP2) were the most suitable reference genes in all tested samples. The experiment results demonstrated the significance of using the properly validated reference genes and suggested the use of more than one reference gene to achieve reliable expression profiles. In addition, we applied three isotypes of the superoxide dismutase ( SOD) gene that are associated with plant adaptation to abiotic stress to confirm the efficacy of the validated reference genes under NaCl and PEG water stresses. Our results provide a valuable reference for future studies on identifying important functional genes from their transcriptional expressions via RT-qPCR technique in M. oleifera.

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          Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress.

          Nathalie Nicot, Jean-Francois Hausman, Lucien Hoffmann … (2005)
          Plant stress studies are more and more based on gene expression. The analysis of gene expression requires sensitive, precise, and reproducible measurements for specific mRNA sequences. Real-time RT-PCR is at present the most sensitive method for the detection of low abundance mRNA. To avoid bias, real-time RT-PCR is referred to one or several internal control genes, which should not fluctuate during treatments. Here, the non-regulation of seven housekeeping genes (beta-tubulin, cyclophilin, actin, elongation factor 1-alpha (ef1alpha), 18S rRNA, adenine phosphoribosyl transferase (aprt), and cytoplasmic ribosomal protein L2) during biotic (late blight) and abiotic stresses (cold and salt stress) was tested on potato plants using geNorm software. Results from the three experimental conditions indicated that ef1alpha was the most stable among the seven tested. The expression of the other housekeeping genes tested varied upon stress. In parallel, a study of the variability of expression of hsp20.2, shown to be implicated in late blight stress, was realized. The relative quantification of the hsp20.2 gene varied according to the internal control and the number of internal controls used, thus highlighting the importance of the choice of internal controls in such experiments.
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            Validation of housekeeping genes for normalizing RNA expression in real-time PCR.

            Keertan Dheda, Jim Huggett, Stephen A. Bustin … (2004)
            Analysis of RNA expression using techniques like real-time PCR has traditionally used reference or housekeeping genes to control for error between samples. This practice is being questioned as it becomes increasingly clear that some housekeeping genes may vary considerably in certain biological samples. We used real-time reverse transcription PCR (RT-PCR) to assess the levels of 13 housekeeping genes expressed in peripheral blood mononuclear cell culture and whole blood from healthy individuals and those with tuberculosis. Housekeeping genes were selected from conventionally used ones and from genes reported to be invariant in human T cell culture. None of the commonly used housekeeping genes [e.g., glyceraldehyde-phosphate-dehydrogenase (GAPDH)] were found to be suitable as internal references, as they were highly variable (>30-fold maximal variability). Furthermore, genes previously found to be invariant in human T cell culture also showed large variation in RNA expression (>34-fold maximal variability). Genes that were invariant in blood were highly variable in peripheral blood mononuclear cell culture. Our data show that RNA specifying human acidic ribosomal protein was the most suitable housekeeping gene for normalizing mRNA levels in human pulmonary tuberculosis. Validations of housekeeping genes are highly specific for a particular experimental model and are a crucial component in assessing any new model.
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              The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants.

              Laurent Gutierrez, Mélanie Mauriat, Stéphanie Guénin … (2008)
              Reverse transcription-polymerase chain reaction (RT-PCR) approaches have been used in a large proportion of transcriptome analyses published to date. The accuracy of the results obtained by this method strongly depends on accurate transcript normalization using stably expressed genes, known as references. Statistical algorithms have been developed recently to help validate reference genes, and most studies of gene expression in mammals, yeast and bacteria now include such validation. Surprisingly, this important approach is under-utilized in plant studies, where putative housekeeping genes tend to be used as references without any appropriate validation. Using quantitative RT-PCR, the expression stability of several genes commonly used as references was tested in various tissues of Arabidopsis thaliana and hybrid aspen (Populus tremula x Populus tremuloides). It was found that the expression of most of these genes was unstable, indicating that their use as references is inappropriate. The major impact of the use of such inappropriate references on the results obtained by RT-PCR is demonstrated in this study. Using aspen as a model, evidence is presented indicating that no gene can act as a universal reference, implying the need for a systematic validation of reference genes. For the first time, the extent to which the lack of a systematic validation of reference genes is a stumbling block to the reliability of results obtained by RT-PCR in plants is clearly shown.
              Article 0 comments Cited 244 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Haitao Shi: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 19 August 2016
                Publication date Collection: 2016
                Volume: 11
                Issue: 8
                Electronic Location Identifier: e0159458
                Affiliations
                [1 ]State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangdong, 510642, China
                [2 ]Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, South China Agricultural University, Guangdong, 510642, China
                [3 ]Guangdong Province Research Center of Woody Forage Engineering Technology, South China Agricultural University, Guangdong, 510642, China
                [4 ]College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, Guangdong, 510642, China
                Hainan University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: XYC LTD KXOY. Performed the experiments: LTD YLW JCL KXOY MMD JJZ SQL MFL HBC. Analyzed the data: LTD. Wrote the paper: LTD XSH XYC.

                Article
                Publisher ID: PONE-D-16-14914
                DOI: 10.1371/journal.pone.0159458
                PMC ID: 4991797
                PubMed ID: 27541138
                SO-VID: 51238bde-992f-4a6a-bc5e-507d92d1e520
                Copyright © © 2016 Deng et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 12 April 2016
                Date accepted : 1 July 2016
                Page count
                Figures: 6, Tables: 4, Pages: 18
                Funding
                Funded by: by the Forestry Sciences and Technology Innovation Project in Guangdong Province
                Award ID: 2015KJCX009
                Award Recipient :
                Funded by: the Department of Tropical crops, State Bureau for Land-Reclamation
                Award ID: 15RZNJ-62
                Award Recipient :
                This work was supported by the Forestry Sciences and Technology Innovation Project in Guangdong Province (2015KJCX009) and the Department of Tropical crops, State Bureau for Land-Reclamation (15RZNJ-62), P.R. China. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Gene Expression
                Subject: Biology and Life Sciences
                Subject: Biochemistry
                Subject: Enzymology
                Subject: Enzymes
                Subject: Dismutases
                Subject: Superoxide Dismutase
                Subject: Biology and Life Sciences
                Subject: Biochemistry
                Subject: Proteins
                Subject: Enzymes
                Subject: Dismutases
                Subject: Superoxide Dismutase
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Signs and Symptoms
                Subject: Hyperthermia
                Subject: Medicine and Health Sciences
                Subject: Pathology and Laboratory Medicine
                Subject: Signs and Symptoms
                Subject: Hyperthermia
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Applied Mathematics
                Subject: Algorithms
                Subject: Research and Analysis Methods
                Subject: Simulation and Modeling
                Subject: Algorithms
                Subject: Research and analysis methods
                Subject: Chemical synthesis
                Subject: Biosynthetic techniques
                Subject: Nucleic acid synthesis
                Subject: RNA synthesis
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Nucleic acids
                Subject: RNA
                Subject: RNA synthesis
                Subject: Biology and Life Sciences
                Subject: Molecular Biology
                Subject: Molecular Biology Techniques
                Subject: Artificial Gene Amplification and Extension
                Subject: Polymerase Chain Reaction
                Subject: Research and Analysis Methods
                Subject: Molecular Biology Techniques
                Subject: Artificial Gene Amplification and Extension
                Subject: Polymerase Chain Reaction
                Subject: Biology and Life Sciences
                Subject: Computational Biology
                Subject: Genome Analysis
                Subject: Transcriptome Analysis
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genomics
                Subject: Genome Analysis
                Subject: Transcriptome Analysis
                Subject: Biology and Life Sciences
                Subject: Plant Science
                Subject: Plant Anatomy
                Subject: Leaves
                Custom metadata
                Data Availability All relevant data are within the paper and its Supporting Information files.

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