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|A panel of the most suitable reference genes for RT-qPCR expression studies of coffee: screening their stability under different conditions
|FERNANDES-BRUM, C. N. et al. A panel of the most suitable reference genes for RT-qPCR expression studies of coffee: screening their stability under different conditions. Tree Genetics & Genomes, [S.l.], v. 13, n. 6, p. 1-13, Dec. 2017.
|The reliability of analyses using real-time quantitative polymerase chain reaction (RT-qPCR) depends on the selection of appropriate reference genes to correct for sample-to-sample and run-to-run variations. The aim of the present study was to select the most suitable reference genes for gene expression analyses in tissue samples from coffee, Coffea arabica L. (Arabica) grown under well-watered (WW) and water-deficit (WD) conditions and C. canephora Pierre ex A. Froehner (Robusta) grown under WW conditions. Expression profiles and stabilities were evaluated for 12 reference genes in different tissues from C. arabica and for 8 genes in tissues from C. canephora. The web-based RefFinder tool, which combines the geNorm, NormFinder, Bestkeeper, and Delta-Ct algorithms, was employed to assess the stability of the tested genes. The most stable reference genes identified for all tissues grouped (WW/WD) of C. arabica were clathrin adaptor protein medium subunit (AP47), ubiquitin (UBQ), 60S ribosomal protein L39 (RPL39), and elongation factor 1α (EF1α), while class III alcohol dehydrogenase (ADH2), β-actin (ACT), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and ubiquitin (UBQ) genes were the most stable for all tissues grouped (WW) of C. canephora tissues. Validation by the expression level analysis of CaACO-like demonstrated that the use of the best and the worst set of reference genes produced different expression results. The results reinforce the general assumption that there is no universal reference gene and that it is essential to select the most appropriate gene for each individual experiment to apply adequate normalization procedures of RT-qPCR data.
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