Computational protocol: Selection and validation of reference genes for RT-qPCR analysis in potato under abiotic stress

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Protocol publication

[…] We selected 8 (CUL3A, EF1α, GAPDH, sec3, tubulin, L8, APRT and actin) commonly used reference genes for RT-qPCR analysis based on our previous publication [] and our unpublished second RNAseq data set; these genes contain more than one exon. The sequences of these eight potato reference genes were obtained from the GenBank database and from the Potato Genomics Resource ( Primer pairs were designed from these sequences with the NCBI Primer-BLAST program (Table ) ( []. Primers were designed across exon boundaries to avoid genomic DNA contamination and exon analysis using Splign ( []. Before RT-qPCR analysis, PCR was performed using primers as shown in Table  to determine the size specificity of the amplicons, then electrophoresed on ethoxylated gels and ethidium bromide, and the target amplicons were sequenced to confirm the identity of the PCR product. [...] A standard curve, repeated in three independent plates using a tenfold serial dilution of the mixed cDNAs was obtained from all tested samples as templates. The correlation coefficients (R2) and slope values were acquired from the standard curve. Then, we calculated the gene-specific PCR amplification efficiency of each gene. The corresponding real-time PCR efficiencies were calculated according to the equation: E=10-1/slope-1×100 [].Simultaneously, the amplicon characteristics, including Tm, length, amplification efficiency with standard deviation, and correlation coefficient, of the eight candidate reference genes are listed in Table .To compare stability of expression among the candidate reference genes, the computational methods, geNorm [], Normfinder [], and BestKeeper [] were applied to quantification cycle (Cq) for each gene’s expression data. These tools are based on different models and assumptions and each produced different results for the same gene’s expression data []. RefFinder was used to calculate a recommended comprehensive ranking based on the results of computational analysis, which in turn allowed us to identify the best reference genes for RT-qPCR data normalization in potato samples [].For geNorm and NormFinder analysis, the raw Cq values under different experimental designs were transformed into relative quantities using the formula 2−ΔCq (ΔCq = each corresponding Cq value-lowest Cq value) and then imported to geNorm to analyze gene expression stability value (M1). Similar to geNorm, NormFinder was further used to investigate the expression stability values (M2) for each gene and the pairwise variation of that gene with other reference genes. The reference gene with the highest M (M1 or M2) value is considered as the most unstable gene while the lowest M (M1 or M2) value indicated the most stable gene []. BestKeeper analysis was based on the untransformed Cq values and using coefficient of variance (CV) and the standard deviation (SD) of the Cq to evaluate the stability of reference genes. All three of the software programs were run based on the software manuals to select suitable reference genes []. By the combination of the three kinds of RefFinder ( software, we could easily rank the expression stability of reference genes in different experimental sets []. […]

Pipeline specifications

Software tools Primer-BLAST, Splign, NormFinder, BestKeeper
Applications RNA-seq analysis, qPCR
Organisms Solanum tuberosum, Solanum lycopersicum
Chemicals Glyceraldehyde 3-Phosphate