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      Reference gene selection for qRT-PCR analysis of season- and tissue-specific gene expression profiles in the honey bee Apis mellifera

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          Abstract

          Honey bees are both important pollinators and model insects due to their highly developed sociality and colony management. To better understand the molecular mechanisms underlying honey bee colony management, it is important to investigate the expression of genes putatively involved in colony physiology. Although quantitative real-time PCR (qRT-PCR) can be used to quantify the relative expression of target genes, internal reference genes (which are stably expressed across different conditions) must first be identified to ensure accurate normalisation of target genes. To identify reliable reference genes in honey bee ( Apis mellifera) colonies, therefore, we evaluated seven candidate genes ( ACT, EIF, EF1, RPN2, RPS5, RPS18 and GAPDH) in samples collected from three honey bee tissue types (head, thorax and abdomen) across all four seasons using three analysis programmes (NormFinder, BestKeeper and geNorm). Subsequently, we validated various normalisation methods using each of the seven reference genes and a combination of multiple genes by calculating the expression of catalase ( CAT). Although the genes ranked as the most stable gene were slightly different on conditions and analysis methods, our results suggest that RPS5, RPS18 and GAPDH represent optimal honey bee reference genes for target gene normalisation in qRT-PCR analysis of various honey bee tissue samples collected across seasons.

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          An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development

          Background Accuracy in quantitative real-time RT-PCR is dependent on high quality RNA, consistent cDNA synthesis, and validated stable reference genes for data normalization. Reference genes used for normalization impact the results generated from expression studies and, hence, should be evaluated prior to use across samples and treatments. Few statistically validated reference genes have been reported in grapevine. Moreover, success in isolating high quality RNA from grapevine tissues is typically limiting due to low pH, and high polyphenolic and polysaccharide contents. Results We describe optimization of an RNA isolation procedure that compensates for the low pH found in grape berries and improves the ability of the RNA to precipitate. This procedure was tested on pericarp and seed developmental series, as well as steady-state leaf, root, and flower tissues. Additionally, the expression stability of actin, AP47 (clathrin-associated protein), cyclophilin, EF1-α (elongation factor 1-α), GAPDH (glyceraldehyde 3-phosphate dehydrogenase), MDH (malate dehydrogenase), PP2A (protein phosphatase), SAND, TIP41, α-tubulin, β-tubulin, UBC (ubiquitin conjugating enzyme), UBQ-L40 (ubiquitin L40) and UBQ10 (polyubiquitin) were evaluated on Vitis vinifera cv. Cabernet Sauvignon pericarp using three different statistical approaches. Although several of the genes proved to be relatively stable, no single gene outperformed all other genes in each of the three evaluation methods tested. Furthermore, the effect of using one reference gene versus normalizing to the geometric mean of several genes is presented for the expression of an aquaporin and a sucrose transporter over a developmental series. Conclusion In order to quantify relative transcript abundances accurately using real-time RT-PCR, we recommend that combinations of several genes be used for normalization in grape berry development studies. Our data support GAPDH, actin, EF1-α and SAND as the most relevant reference genes for this purpose.
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            Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber.

            Quantitative real-time polymerase chain reaction (QRT-PCR) has become one of the most widely used methods for gene expression analysis. However, the expression profile of a target gene may be misinterpreted due to unstable expression of the reference genes under different experimental conditions. Thus, a systematic evaluation of these reference genes is necessary before experiments are performed. In this study, 10 putative reference genes were chosen for identifying expression stability using geNorm, NormFinder, and BestKeeper statistical algorithms in 12 different cucumber sample pools, including those from different plant tissues and from plants treated with hormones and abiotic stresses. EF1alpha and UBI-ep exhibited the most stable expression across all of the tested cucumber samples. In different tissues, in addition to expression of EF1alpha and UBI-ep, the expression of TUA was also stable and was considered as an appropriate reference gene. Evaluation of samples treated with different hormones revealed that TUA and UBI-ep were the most stably expressed genes. However, for abiotic stress treatments, only EF1alpha showed a relatively stable expression level. In conclusion, TUA, UBI-ep, and EF1alpha will be particularly helpful for reliable QRT-PCR data normalization in these types of samples. This study also provides guidelines for selecting different reference genes under different conditions. Copyright 2009 Elsevier Inc. All rights reserved.
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              Evaluation of potential reference genes for reverse transcription-qPCR studies of physiological responses in Drosophila melanogaster.

              Drosophila melanogaster is one of the most important genetic models and techniques such as reverse transcription quantitative real-time PCR (RT-qPCR) are being employed extensively for deciphering the genetics basis of physiological functions. In RT-qPCR, the expression levels of target genes are estimated on the basis of endogenous controls. The purpose of these reference genes is to control for variations in RNA quantity and quality. Although determination of suitable reference genes is essential to RT-qPCR studies, reports on the evaluation of reference genes in D. melanogaster studies are lacking. We analyzed the expression levels of seven candidate reference genes (Actin, EF1, Mnf, Rps20, Rpl32, Tubulin and 18S) in flies that were injured, heat-stressed, or fed different diets. Statistical analyses of variation were determined using three established software programs for reference gene selection, geNorm, NormFinder and BestKeeper. Best-ranked references genes differed across the treatments. Normalization candidacy of the selected candidate reference genes was supported by an analysis of gene expression values obtained from microarray datasets available online. The differences between the experimental treatments suggest that assessing the stability of reference gene expression patterns, determining candidates and testing their suitability is required for each experimental investigation. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                yhkim05@knu.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 August 2020
                18 August 2020
                2020
                : 10
                : 13935
                Affiliations
                [1 ]GRID grid.258803.4, ISNI 0000 0001 0661 1556, Department of Applied Biology, , Kyungpook National University, ; Sangju, Gyeongbuk Republic of Korea
                [2 ]GRID grid.258803.4, ISNI 0000 0001 0661 1556, Department of Ecological Science, , Kyungpook National University, ; Sangju, Gyeongbuk Republic of Korea
                Article
                70965
                10.1038/s41598-020-70965-4
                7435199
                32811887
                ed7d3dd2-6d3c-4537-b07a-99450f7eda21
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 May 2020
                : 7 August 2020
                Funding
                Funded by: National Research Foundation of Korea
                Award ID: 2017R1C1B2008699
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                molecular biology,transcription,entomology
                Uncategorized
                molecular biology, transcription, entomology

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