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      Identification and evaluation of PCR reference genes for host and pathogen in sugarcane -Sporisorium scitamineum interaction system

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          Abstract

          Background

          Sugarcane ( Saccharum L. plant) is an important crop for sugar and bio-energy production around the world. Among sugarcane diseases, smut caused by Sporisorium scitamineum is one of the major fungal diseases causing severe losses to the sugarcane industry. The use of PCR reference genes is essential to the normalization of data on gene expression involving the sugarcane- S. scitamineum interaction system; however, no report that addresses criteria in selecting these reference genes has been published to date.

          Results

          In this study, 10 sugarcane genes and eight S. scitamineum genes were selected as candidate PCR reference genes in the sugarcane- S. scitamineum interaction system. The stability and reliability of these 18 candidate genes were analyzed in smut-resistant (NCo376) and -susceptible (YC71–374) genotypes using the statistical algorithms geNorm, NormFinder, BestKeeper, and deltaCt method. Subsequently, the relative expression levels of the sugarcane chitinase I-3 gene and S. scitamineum chorismate mutase gene were determined to validate the applicability of these sugarcane and S. scitamineum PCR reference genes, respectively. We finally found that the acyl-CoA dehydrogenase gene ( ACAD), serine/arginine repetitive matrix protein 1 gene ( SARMp1), or their combination ( ACAD +  SARMp1) could be utilized as the most suitable reference genes for normalization of sugarcane gene expression in sugarcane bud tissues after S. scitamineum infection. Similarly, the inosine 5′-monophosphate dehydrogenase gene ( S10), the SEC65-signal recognition particle subunit gene ( S11), or their combination ( S10 +  S11) were suitable for normalization of S. scitamineum gene expression in sugarcane bud tissues.

          Conclusions

          The PCR reference genes ACAD, SARMp1, S10, and S11 may be employed in gene transcriptional studies involving the sugarcane- S. scitamineum interaction system.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-018-4854-z) contains supplementary material, which is available to authorized users.

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          Most cited references61

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          The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments.

          Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader's ability to evaluate critically the quality of the results presented or to repeat the experiments. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement. Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.
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            Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

            Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.
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              Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR

              Background Control genes, which are often referred to as housekeeping genes, are frequently used to normalise mRNA levels between different samples. However, the expression level of these genes may vary among tissues or cells and may change under certain circumstances. Thus, the selection of housekeeping genes is critical for gene expression studies. To address this issue, 7 candidate housekeeping genes including several commonly used ones were investigated in isolated human reticulocytes. For this, a simple ΔCt approach was employed by comparing relative expression of 'pairs of genes' within each sample. On this basis, stability of the candidate housekeeping genes was ranked according to repeatability of the gene expression differences among 31 samples. Results Initial screening of the expression pattern demonstrated that 1 of the 7 genes was expressed at very low levels in reticulocytes and was excluded from further analysis. The range of expression stability of the other 6 genes was (from most stable to least stable): GAPDH (glyceraldehyde 3-phosphate dehydrogenase), SDHA (succinate dehydrogenase), HPRT1 (hypoxanthine phosphoribosyl transferase 1), HBS1L (HBS1-like protein) and AHSP (alpha haemoglobin stabilising protein), followed by B2M (beta-2-microglobulin). Conclusion Using this simple approach, GAPDH was found to be the most suitable housekeeping gene for expression studies in reticulocytes while the commonly used B2M should be avoided.
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                Author and article information

                Contributors
                hning2012@126.com
                linghuich@163.com
                18359162091@163.com
                syc2009mail@163.com
                suweihua2016@126.com
                alocasiamao@126.com
                zxxez123@126.com
                15659763270@163.com
                fafu948@126.com
                queyouxiong@126.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                19 June 2018
                19 June 2018
                2018
                : 19
                : 479
                Affiliations
                [1 ]ISNI 0000 0004 1760 2876, GRID grid.256111.0, Key Laboratory of Sugarcane Biology and Genetic Breeding, Ministry of Agriculture, , Fujian Agriculture and Forestry University, ; Fuzhou, 350002 China
                [2 ]ISNI 0000 0004 1760 2876, GRID grid.256111.0, Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Crop Science, , Fujian Agriculture and Forestry University, ; Fuzhou, 350002 China
                [3 ]ISNI 0000 0001 2254 5798, GRID grid.256609.e, Guangxi Collaborative Innovation Center of Sugarcane Industry, , Guangxi University, ; Nanning, 530005 China
                Article
                4854
                10.1186/s12864-018-4854-z
                6006842
                29914370
                b093fea1-caba-4031-9a43-a89cd76e4731
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 September 2017
                : 6 June 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31671752
                Award ID: 3134006
                Award Recipient :
                Funded by: National Natural Science Foundation of China (CN)
                Award ID: 31101196
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003392, Natural Science Foundation of Fujian Province;
                Award ID: 2015J06006
                Funded by: Modern Agriculture Technology of China
                Award ID: CARS-17
                Funded by: New Century Excellent Talents in Fujian Province University
                Award ID: JA14095
                Funded by: Special fund for science and technology innovation of Fujian Agriculture And Forestry University
                Award ID: KFA17267A
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Genetics
                saccharum l.,smut fungus,quantitative real-time pcr,reference gene
                Genetics
                saccharum l., smut fungus, quantitative real-time pcr, reference gene

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