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Neolamarckia cadamba is an economically-important fast-growing tree species in South China and Southeast Asia. As a prerequisite first step for future gene expression studies, we have identified and characterized a series of stable reference genes that can be used as controls for quantitative real time PCR (qRT-PCR) expression analysis in this study. The expression stability of 15 candidate reference genes in various tissues and mature leaves under different conditions was evaluated using four different algorithms, i.e., geNorm, NormFinder, BestKeeper and RefFinder. Our results showed that SAMDC was the most stable of the selected reference genes across the set of all samples, mature leaves at different photosynthetic cycles and under drought stress, whereas RPL10A had the most stable expression in various tissues. PGK and RPS25 were considered the most suitable reference for mature leaves at different developmental stages and under cold treatment, respectively. Additionally, the gene expression profiles of sucrose transporter 4 (NcSUT4), and 9-cis-epoxycarotenoid dioxygenase 3 (NcNCED3) were used to confirm the validity of candidate reference genes. Collectively, our study is the first report to validate the optimal reference genes for normalization under various conditions in N. cadamba and will benefit the future discovery of gene function in this species.
Pubmed ID: 29915368
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Excel-based tool using pair-wise correlations for determination of stable housekeeping genes, differentially regulated target genes and sample integrity. It determines the best suited standards, out of ten candidates, and combines them into an index. The index can be compared with further ten target genes to decide, whether they are differentially expressed under an applied treatment. All data processing is based on crossing points.
View all literature mentionsSoftware for identifying the optimal normalization gene among a set of candidates. It ranks the set of candidate normalization genes according to their expression stability in a given sample set and given experimental design. It can analyze expression data obtained through any quantitative method e.g. real time RT-PCR and microarray based expression analysis. NormFinder.xla adds the NormFinder functionality directly to Excel. A version for R is also available.
View all literature mentionsSoftware to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.
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