Computational protocol: Selection of reliable reference genes for RT-qPCR analysis during developmental stages and abiotic stress in Setaria viridis

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Protocol publication

[…] Based on previous systematic studies of reference genes suitable for transcript normalization in monocot species, thirteen candidate genes were selected to this study. Information about gene names, accession numbers, primer sequences and efficiency and gene description are provided in . Primers were designed to amplify one single PCR product, as confirmed on a 2% agarose gel and melting curve analysis performed in all RT-qPCR assays (see ). Mean PCR efficiency per gene was estimated using LinRegPCR (version 2016.0) program; the efficiency values ranged from 89 to 96% for reference genes and 90 to 100% for target genes (see ). Expression levels of the candidate genes for different developmental stages, drought and aluminum stresses and for all samples combined are presented in . Expression values are inversely proportional to the Cq values, and the mean and range of Cq indicate the most stable genes across all samples and to each experimental set. Cq values of candidate genes from each experimental set presented a high variation, ranging from 18.6 for GAPDH and 32.0 for POL. Expression levels to each subset of the candidate genes for different tissues/organs can be found in . [...] Performance of the thirteen genes as potential reference genes for S. viridis was assessed in 31 samples divided into three experimental sets; five developmental stages from whole seedlings, different tissues/organs, and two treatments, including samples submitted to different levels of drought or aluminum stresses. Using geNorm, we estimated two parameters to evaluate the expression stability of these genes; the average expression stability value (M value), based on the pairwise variation between a particular gene compared to all others, and the pairwise variation (Vn/n + 1), which determines the required number of genes to result in a more accurate normalization.When considering all dataset, CAC/KIN (M = 0.48) was the best pair to normalize all samples, while GAPDH was the least stable gene (M = 1.6) (). Comparing with NormFinder, SDH was the most stable gene and CUL/KIN were defined as the best pair for a reliable normalization. In both programs, ACT and GAPDH were ranked as the least stable genes ( and ).Due to the heterogeneity of these samples and conditions, each experimental set was analyzed individually using both algorithms. While geNorm performs a stepwise exclusion of the least stably expressed gene, NormFinder uses a model-based approach, which calculates both inter- and intra-group variability to estimate the stability of gene expression. Estimative of the best reference genes in each experimental set exhibited some particularities. For developmental stages, EXP/KIN pair (M = 0.47) was ranked as the most stable gene pair, while BIND was the most stable gene by NormFinder, followed by SDH ( and ; ). Once again, ACT/GAPDH showed the highest variation and hence, they were not suitable for normalization in different stages of development ( and ). We also analyzed the expression stability of these candidate genes in samples derived from whole seedlings in vegetative phase and in each tissue/organ at the subsequent stages of development. geNorm and NormFinder excluded the same reference genes, but defined different pair of genes as the best reference genes to each particular subset of tissue/organ. In general, SDH and eIF4α were selected as the preferred reference genes when considering both algorithms (see ; ).For drought treatment, SDH/SUI pair and SDH gene were considered the most stable genes according to geNorm and NormFinder, respectively. The best pair according to NormFinder was KIN/CUL, whereas ACT was estimated as the most variable reference gene by both algorithms (; and ).For aluminum treatment, CAC/KIN pair presented the best performance, according to geNorm ( and ). Although CUL was the most stable, according to NormFinder, CAC was ranked in the top-three position (). In both geNorm and NormFinder, EXP, SUI, EF1α and GAPDH showed the highest variation among all the reference genes tested under Al3+ treatment ( and ).In addition, to define the best pair using geNorm, we also estimated the pairwise variation to determine the minimal number of genes for reliable normalization. Assuming a cut-off of Vn/n + 1 ≤ 0.15, it was determined that the use of only the top two reference genes for each experimental set would be the appropriate number of genes required for normalization (; ). When the entire dataset were considered, the number of genes increased to six (). […]

Pipeline specifications

Software tools LinRegPCR, NormFinder
Application qPCR
Organisms Setaria viridis
Chemicals Aluminum