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Evaluation of Reference Genes for RT-qPCR Expression Studies in Hop (Humulus lupulus L.) during Infection with Vascular Pathogen Verticillium albo-atrum
Authors:Nata?a ?tajner  Sara Cregeen  Branka Javornik
Institution:Biotechnical Faculty, Agronomy Department, University of Ljubljana, Ljubljana, Slovenia.; University of Texas Health Science Center, United States of America,
Abstract:Hop plant (Humulus lupulus L.), cultivated primarily for its use in the brewing industry, is faced with a variety of diseases, including severe vascular diseases, such as Verticillium wilt, against which no effective protection is available. The understanding of disease resistance with tools such as differentially expressed gene studies is an important objective of plant defense mechanisms. In this study, we evaluated twenty-three reference genes for RT-qPCR expression studies on hop under biotic stress conditions. The candidate genes were validated on susceptible and resistant hop cultivars sampled at three different time points after infection with Verticillium albo-atrum. The stability of expression and the number of genes required for accurate normalization were assessed by three different Excel-based approaches (geNorm v.3.5 software, NormFinder, and RefFinder). High consistency was found among them, identifying the same six best reference genes (YLS8, DRH1, TIP41, CAC, POAC and SAND) and five least stably expressed genes (CYCL, UBQ11, POACT, GAPDH and NADH). The candidate genes in different experimental subsets/conditions resulted in different rankings. A combination of the two best reference genes, YLS8 and DRH1, was used for normalization of RT-qPCR data of the gene of interest (PR-1) implicated in biotic stress of hop. We outlined the differences between normalized and non-normalized values and the importance of RT-qPCR data normalization. The high correlation obtained among data standardized with different sets of reference genes confirms the suitability of the reference genes selected for normalization. Lower correlations between normalized and non-normalized data may reflect different quantity and/or quality of RNA samples used in RT-qPCR analyses.
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