Identification of Reference Genes for Quantitative Real Time PCR Assays in Aortic Tissue of Syrian Hamsters with Bicuspid Aortic Valve

Rueda-Martínez, Carmen; Fernández, M.C.; Soto-Navarrete, María Teresa; Jiménez-Navarro, Manuel F.; Durán, Ana C.; Fernández, Borja

doi:10.1371/journal.pone.0164070

Cited by 8 publications

(13 citation statements)

References 53 publications

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“…Hence, the identification of suitable RGs is an essential step in qPCR analysis, since the selection of unstable genes for normalization could result in misleading conclusions. The number of publications reporting the validation of RGs for normalization of RT-qPCR studies has increased in different scientific research disciplines including: microbiology 25 – 27 , cancer 28 – 30 , plant sciences 31 – 33 , neurosciences 34 , and also cardiovascular research 35 , 36 . In endocrine research certain studies pertaining to obesity and diabetes have characterized most stable RGs for qPCR normalization purposes 37 – 39 .…”

Section: Discussionmentioning

confidence: 99%

“…The four algorithms considered as gold standard for determination of the stability of gene expression are Genorm, NormFinder, BestKeeper and ΔCt 36 . GeNorm calculates gene stability based on the arithmetic means of all pair-wise comparisons, but does not correct co-regulated genes.…”

Section: Discussionmentioning

confidence: 99%

“…However, the optimal number of RGs required for accurate normalization can be determined by using a pairwise variation implemented on the stand-alone application geNorm 13 . Several reports have shown that using two reference genes for normalization would be sufficient to obtain accurate data 36 , 39 without excessive cost and time constraints on RT-qPCR analyses. In our hands, geNorm V application 13 is a valuable tool for the purpose of selecting ideal number of RGs for data normalization.…”

Section: Discussionmentioning

confidence: 99%

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Validation of optimal reference genes for quantitative real time PCR in muscle and adipose tissue for obesity and diabetes research

Pérez

Rios

Trivedi

et al. 2017

Sci Rep

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The global incidence of obesity has led to an increasing need for understanding the molecular mechanisms that drive this epidemic and its comorbidities. Quantitative real-time RT-PCR (RT-qPCR) is the most reliable and widely used method for gene expression analysis. The selection of suitable reference genes (RGs) is critical for obtaining accurate gene expression information. The current study aimed to identify optimal RGs to perform quantitative transcriptomic analysis based on RT-qPCR for obesity and diabetes research, employing in vitro and mouse models, and human tissue samples. Using the ReFinder program we evaluated the stability of a total of 15 RGs. The impact of choosing the most suitable RGs versus less suitable RGs on RT-qPCR results was assessed. Optimal RGs differed between tissue and cell type, species, and experimental conditions. By employing different sets of RGs to normalize the mRNA expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), we show that sub-optimal RGs can markedly alter the PGC1α gene expression profile. Our study demonstrates the importance of validating RGs prior to normalizing transcriptional expression levels of target genes and identifies optimal RG pairs for reliable RT-qPCR normalization in cells and in human and murine muscle and adipose tissue for obesity/diabetes research.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Validation of optimal reference genes for quantitative real time PCR in muscle and adipose tissue for obesity and diabetes research

Pérez

Rios

Trivedi

et al. 2017

Sci Rep

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“…When additional data from the other program were incorporated through RefFinder, this shifted to Actb, Hprt1, RpI13a and Tubb in the lung, liver, spleen and pancreas respectively. A previous study using only GeNorm identified Cdkn1and G3pdh as the most appropriate housekeeping genes in aortic tissue of Syrian hamsters (Rueda-Martinez et al 2016). Given the differences we found between GeNorm and RefFinder, it may be appropriate to reevaluate these findings with additional methods.…”

Section: Appropriateness Of Housekeeping Genesmentioning

confidence: 80%

Validation of Stable Housekeeping Genes for Quantitative Real Time PCR in Golden Syrian Hamster

Miao¹,

Wang²,

Robl³

et al. 2020

IJAR

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Background: Golden Syrian hamster (GSH) have many advantages as animal models in preclinical research, but their application is currently limited by the lack of standardized techniques for analyzing gene expression. Quantitative real-time polymerase chain reaction (RT-qPCR) is a sensitive method for analyzing gene expression, but its reliability depends upon the selection of stable reference (“housekeeping”) genes for proper normalization. The current study was aimed to RT-qPCR for investigated to determine the stability housekeeping gene in golden Syrian hamster.Methods: During the period of June 2019 to October 2019, the expression stability of eight commonly-used housekeeping genes (glyceraldehyde-3phosphate dehydrogenase, Gapdh; b-actin, Actb; hypoxanthine phosphoribosyl transferase 1, Hprt1; ribosomal protein L13a, Rpl13a; ribosomal protein S18, Rps18; Beta-2-microglobulin, B2m; Tubulin beta class I, Tubb; Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta, Ywhaz) were investigated in lung, liver, spleen and pancreatic tissue of golden Syrian hamsters using BestKeeper, geNorm, NormFinder software, comparative delta Ct method and RefFinder. Result: It was found that the stability of gene expression varied among tissue where in Actb was the most stably expressed housekeeping gene for lung tissue, Hprt1 for liver, Rpl13a for spleen and Tubb for pancreatic tissue. In contrast, the least stable housekeeping gene in both liver and spleen was Gapdh, Rps18 in pancreas and Ywhaz in lung tissue. These data provide a critical evaluation of housekeeping genes in GSH tissues that can be used as a guide for selection of the appropriate genes in future studies.

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“…According to previous studies in rodents, nine candidate reference genes were selected [ 16 , 17 , 18 , 19 ]. Gapdh and β-actin are classic reference genes in various species, and Hprt1 , Rpl13a , Tbp , Sdha , Hmbs , PPIA , and B2M are high-frequency reference genes in rodents.…”

Section: Methodsmentioning

confidence: 99%

Validation of Reference Genes via qRT-PCR in Multiple Conditions in Brandt’s Voles, Lasiopodomys brandtii

Tian

Chen

Wang

et al. 2021

Animals

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The choice of optimal reference gene is challenging owing to the varied expression of reference genes in different organs, development stages, and experimental treatments. Brandt’s vole (Lasiopodomys brandtii) is an ideal animal to explore the regulatory mechanism of seasonal breeding, and many studies on this vole involve gene expression analysis using quantitative real-time polymerase chain reaction (qRT-PCR). In this study, we used the method of the coefficient of variation and the NormFinder algorithm to evaluate the performance of nine commonly used reference genes Gapdh, Hprt1, β-actin, PPIA, Rpl13a, Tbp, Sdha, Hmbs, and B2M using qRT-PCR in eight different tissues, five developmental stages, and three different photoperiods. We found that all nine genes were not uniformly expressed among different tissues. B2M and Rpl13a were the optimal reference genes for different postnatal development stages in the hypothalamus for males and females, respectively. Under different photoperiods in the hypothalamus, none of the selected genes were suitable as reference genes at 6 weeks postnatal; β-actin and PPIA were the optimal reference genes at 12 weeks postnatal; Hprt1, β-actin, PPIA, Hmbs, and B2M were excellent reference genes at 24 weeks postnatal. The present study provides a useful basis for selecting the appropriate reference gene in Lasiopodomys brandtii.

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Identification of Reference Genes for Quantitative Real Time PCR Assays in Aortic Tissue of Syrian Hamsters with Bicuspid Aortic Valve

Cited by 8 publications

References 53 publications

Validation of optimal reference genes for quantitative real time PCR in muscle and adipose tissue for obesity and diabetes research

Validation of optimal reference genes for quantitative real time PCR in muscle and adipose tissue for obesity and diabetes research

Validation of Stable Housekeeping Genes for Quantitative Real Time PCR in Golden Syrian Hamster

Validation of Reference Genes via qRT-PCR in Multiple Conditions in Brandt’s Voles, Lasiopodomys brandtii

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