Quantitative expression analysis in Brassica napus by Northern blot analysis and reverse transcription-quantitative PCR in a complex experimental setting

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Rumlow, Annekathrin; Keunen, E.; Klein, Jan; Pallmann, P.; Riemenschneider, Anja et al.: Quantitative expression analysis in Brassica napus by Northern blot analysis and reverse transcription-quantitative PCR in a complex experimental setting. In: PLoS ONE 11 (2016), Nr. 9, e0163679. DOI: http://dx.doi.org/10.1371/journal.pone.0163679

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Sum total of downloads: 140




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Abstract: 
Analysis of gene expression is one of the major ways to better understand plant reactions to changes in environmental conditions. The comparison of many different factors influencing plant growth challenges the gene expression analysis for specific gene-targeted experiments, especially with regard to the choice of suitable reference genes. The aim of this study is to compare expression results obtained by Northern blot, semi-quantitative PCR and RT-qPCR, and to identify a reliable set of reference genes for oilseed rape (Brassica napus L.) suitable for comparing gene expression under complex experimental conditions. We investigated the influence of several factors such as sulfur deficiency, different time points during the day, varying light conditions, and their interaction on gene expression in oilseed rape plants. The expression of selected reference genes was indeed influenced under these conditions in different ways. Therefore, a recently developed algorithm, called GrayNorm, was applied to validate a set of reference genes for normalizing results obtained by Northern blot analysis. After careful comparison of the three methods mentioned above, Northern blot analysis seems to be a reliable and cost-effective alternative for gene expression analysis under a complex growth regime. For using this method in a quantitative way a number of references was validated revealing that for our experiment a set of three references provides an appropriate normalization. Semi-quantitative PCR was prone to many handling errors and difficult to control while RT-qPCR was very sensitive to expression fluctuations of the reference genes.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2016
Appears in Collections:Naturwissenschaftliche Fakultät

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1 image of flag of Germany Germany 102 72.86%
2 image of flag of United States United States 21 15.00%
3 image of flag of China China 8 5.71%
4 image of flag of Europe Europe 2 1.43%
5 image of flag of Vietnam Vietnam 1 0.71%
6 image of flag of No geo information available No geo information available 1 0.71%
7 image of flag of Taiwan Taiwan 1 0.71%
8 image of flag of Hungary Hungary 1 0.71%
9 image of flag of United Kingdom United Kingdom 1 0.71%
10 image of flag of Canada Canada 1 0.71%
    other countries 1 0.71%

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