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Selection and Verification of Appropriate Reference Genes for Expression Normalization in Cryptomeria fortunei under Abiotic Stress and Hormone Treatments.

ABSTRACT: Cryptomeria fortunei has become one of the main timber afforestation species in subtropical high-altitude areas of China due to its fast growth, good material quality, and strong adaptability, showing broad application prospects. Quantitative real-time PCR (qRT-PCR) is the most accurate and widely used gene expression evaluation technique, and selecting appropriate reference genes (RGs) is essential for normalizing qRT-PCR results. However, suitable RGs for gene expression normalization in C. fortunei have not been reported. Here, we tested the expression stability for 12 RGs in C. fortunei under various experimental conditions (simulated abiotic stresses (cold, heat, drought, and salinity) and hormone treatments (methyl jasmonate, abscisic acid, salicylic acid, and gibberellin) and in different tissues (stems, tender needles, needles, cones, and seeds) using four algorithms (delta Ct, geNorm, NormFinder, and BestKeeper). Then, geometric mean rankings from these algorithms and the RefFinder program were used to comprehensively evaluate RG stability. The results indicated CYP, actin, UBC, and 18S as good choices for studying C. fortunei gene expression. qRT-PCR analysis of the expression patterns of three target genes (CAT and MAPK1/6) further verified that the selected RGs were suitable for gene expression normalization. This study provides an important basis for C. fortunei gene expression standardization and quantification.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC8224294 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Oxytropis ochrocephala Bunge, an indigenous locoweed species in China, poses great threats to livestock on grasslands. There is a need for further genetic study in the plants per se, for understanding the basis of its acclimation mechanism in various unfavorable environmental conditions and to implement effective control measures. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is the most commonly used method for gene expression analysis. To facilitate gene expression studies and obtain more accurate qRT-PCR data, normalization relative to stable reference genes is required. The aim of this study was to select the most stable reference genes for transcriptional analysis in O. ochrocephala. RESULTS:We selected 12 candidate reference genes, 18S ribosomal RNA (18S RNA), actin2/7 (ACT7), ?-actin (ACTB), actin101 (ACT101), actin11 (ACT11), ?-tubulin (TUB), ?-tubulin (TUA), glyceraldehyde-3-phosphate dehydrogenase-1 (GAPDH1), GAPDH2, metallothionein-like protein (MET), fructose-bisphosphate aldolase (FBA) and histone H3 (HIS), from the transcriptome datasets of O. ochrocephala and determined the suitability by analyzing their expression levels when exposed to a range of abiotic stress conditions. By employing software packages including geNorm, NormFinder and BestKeeper, HIS, ACT7, and ACT101 were assessed as the most suitable set for normalization in all samples. When normalized with the most stable reference genes, the expression patterns of the three target genes were in accordance with those in the transcriptome data, indicating that the reference genes selected in this study are suitable. CONCLUSIONS:The study provided appropriate reference genes for accurate normalization in qRT-PCR analysis in O. ochrocephala and emphasized the importance of validating reference genes for gene expression analysis under specific experimental condition. The usage of inappropriate reference gene would cause misinterpretation.

Project description:Background:Stellera chamaejasme Linn, an important poisonous plant of the China grassland, is toxic to humans and livestock. The rapid expansion of S. chamaejasme has greatly damaged the grassland ecology and, consequently, seriously endangered the development of animal husbandry. To draft efficient prevention and control measures, it has become more urgent to carry out research on its adaptive and expansion mechanisms in different unfavorable habitats at the genetic level. Quantitative real-time polymerase chain reaction (qRT-PCR) is a widely used technique for studying gene expression at the transcript level; however, qRT-PCR requires reference genes (RGs) as endogenous controls for data normalization and only through appropriate RG selection and qRT-PCR can we guarantee the reliability and robustness of expression studies and RNA-seq data analysis. Unfortunately, little research on the selection of RGs for gene expression data normalization in S. chamaejasme has been reported. Method:In this study, 10 candidate RGs namely, 18S, 60S, CYP, GAPCP1, GAPDH2, EF1B, MDH, SAND, TUA1, and TUA6, were singled out from the transcriptome database of S. chamaejasme, and their expression stability under three abiotic stresses (drought, cold, and salt) and three hormone treatments (abscisic acid, ABA; gibberellin, GA; ethephon, ETH) were estimated with the programs geNorm, NormFinder, and BestKeeper. Result:Our results showed that GAPCP1 and EF1B were the best combination for the three abiotic stresses, whereas TUA6 and SAND, TUA1 and CYP, GAPDH2 and 60S were the best choices for ABA, GA, and ETH treatment, respectively. Moreover, GAPCP1 and 60S were assessed to be the best combination for all samples, and 18S was the least stable RG for use as an internal control in all of the experimental subsets. The expression patterns of two target genes (P5CS2 and GI) further verified that the RGs that we selected were suitable for gene expression normalization. Discussion:This work is the first attempt to comprehensively estimate the stability of RGs in S. chamaejasme. Our results provide suitable RGs for high-precision normalization in qRT-PCR analysis, thereby making it more convenient to analyze gene expression under these experimental conditions.

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Selection and Verification of Appropriate Reference Genes for Expression Normalization in Cryptomeria fortunei under Abiotic Stress and Hormone Treatments.

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