Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29789
Title: Selection of Appropriate Reference Genes for Gene Expression Analysis under Abiotic Stresses in Salix viminalis
Authors: AMBROISE, Valentin 
Legay, Sylvain
Guerriero, Gea
Hausman, Jean-Francois
CUYPERS, Ann 
Sergeant, Kjell
Issue Date: 2019
Source: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 20 (17), p. 4210-4210
Abstract: Salix viminalis is a fast growing willow species with potential as a plant used for biomass feedstock or for phytoremediation. However, few reference genes (RGs) for quantitative real-time polymerase chain reaction (qPCR) are available in S. viminalis, thereby limiting gene expression studies. Here, we investigated the expression stability of 14 candidate reference genes (RGs) across various organs exposed to five abiotic stresses (cold, heat, drought, salt, and poly-metals). Four RGs ranking algorithms, namely geNormPLUS, BestKeeper, NormFinder, and GrayNorm were applied to analyze the qPCR data and the outputs were merged into consensus lists with RankAggreg, a rank aggregation algorithm. In addition, the optimal RG combinations were determined with geNormPLUS and GrayNorm. The genes that were the most stable in the roots were TIP41 and CDC2. In the leaves, TIP41 was the most stable, followed by EF1b and ARI8, depending on the condition tested. Conversely, GAPDH and β-TUB, two genes commonly used for qPCR data normalization were the least stable across all organs. Nevertheless, both geNormPLUS and GrayNorm recommended the use of a combination of genes rather than a single one. These results are valuable for research of transcriptomic responses in different S. viminalis organs.
Notes: Sergeant, K (reprint author), Luxembourg Inst Sci & Technol, Environm Res & Innovat ERIN Dept, 5 Ave Hauts Fourneaux, L-4362 Esch Sur Alzette, Luxembourg. kjell.sergeant@list.lu
Keywords: real-time quantitative PCR; reference gene; BestKeeper; geNorm; GrayNorm; NormFinder; RankAggreg; Salix; abiotic stress
Document URI: http://hdl.handle.net/1942/29789
Link to publication/dataset: https://www.mdpi.com/1422-0067/20/17/4210
ISSN: 1661-6596
e-ISSN: 1422-0067
DOI: 10.3390/ijms20174210
ISI #: 000486888400142
Rights: 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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