Quantitative reverse transcription PCR is a sensitive technique for evaluating transcriptional profiles in different experimental datasets. To obtain a reliable quantification of the transcripts level, data normalization with stable reference genes is required. Stable reference genes are identified after analysis of their transcripts profile in every new experiment and species of interest. In Silybum marianum, a widely cultivated officinal plant, only few gene expression studies exist, and reference genes for RT-qPCR studies in the diverse plant tissues have never been investigated before. In this work, the expression stability of 10 candidate reference genes was evaluated in leaves, roots, stems and fruits of S. marianum grown under physiological environmental condition. The stability values for each candidate reference gene were calculated by four canonical statistical algorithms GeNorm, NormFinder, Bestkeeper and ΔCt method in different subsets of samples, then they were ranked with RefFinder from the most to the least suitable for normalization. Best combinations of reference genes are finally proposed for different experimental data sets, including all tissues, vegetative, and reproductive tissues separately. Three target genes putatively involved in important biosynthetic pathway leading to key metabolites in the fruits of milk thistle, such as silymarin and fatty acids, were analyzed with the chosen panels of reference genes, in comparison to the ones used in previous papers. To the best of our knowledge, this is the first report on a reliable and systematic identification and validation of the reference genes for RT-qPCR normalization to study gene expression in S. marianum.
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http://dx.doi.org/10.1016/j.gene.2020.145272 | DOI Listing |
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