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Article|01 Aug 2021|OPEN
An optimized protocol for stepwise optimization of real-time RT-PCR analysis
Fangzhou Zhao1,2, Nathan A. Maren2,3, Pawel Z. Kosentka2, Ying-Yu Liao4, Hongyan Lu2,5, Debao Huang2, Hamid Ashrafi2, James R. Duduit2, Tuanjie Zhao1, Alejandra I. Huerta4, Thomas G. Ranney3 & Wusheng Liu 2,
1Soybean Research Institute, Nanjing Agricultural University, 210095 Nanjing, China
2Department of Horticultural Science, North Carolina State University, Raleigh, NC 27607, USA
3Mountain Crop Improvement Lab, Department of Horticultural Science, Mountain Horticultural Crops Research and Extension Center, North Carolina State University, Mills River, NC 28759, USA
4Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC 27607, USA
5College of Biosystems Engineering and Food Science, Zhejiang University, 310058 Hangzhou, China

Horticulture Research 8,
Article number: 179 (2021)
doi: 10.1038/hortres.2021.179
Views: 120

Received: 04 Mar 2021
Revised: 11 May 2021
Accepted: 06 Jun 2021
Published online: 01 Aug 2021


Computational tool-assisted primer design for real-time reverse transcription (RT) PCR (qPCR) analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome. It can lead to false confidence in the quality of the designed primers, which sometimes results in skipping the optimization steps for qPCR. However, the optimization of qPCR parameters plays an essential role in the efficiency, specificity, and sensitivity of each gene’s primers. Here, we proposed an optimized approach to sequentially optimizing primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference (and target) gene. Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms (SNPs) present in all the homologous sequences for each of the reference (and target) genes under study. By combining the efficiency calibrated and standard curve methods with the 2−ΔΔCt method, the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene. As a result, an R2 ≥ 0.9999 and the efficiency (E) = 100 ± 5% should be achieved for the best primer pair of each gene, which serve as the prerequisite for using the 2−ΔΔCt method for data analysis. We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae, an ornamental and biomass grass, and validated their utility under varying abiotic stress conditions. We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv. glycines (Xag). Thus, these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis.