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Selection of suitable reference genes for normalization of quantitative real-time polymerase chain reaction in human cartilage endplate of the lumbar spine.

Zhou ZJ, Zhang JF, Xia P, Wang JY, Chen S, Fang XQ, Fan SW - PLoS ONE (2014)

Bottom Line: Our results showed that the rarely-used SDHA was the most stable single reference gene, and a combination of three, SDHA, B2M, and LDHA, was the most suitable gene set for normalization in all samples.Further simulated expression analysis validated that the arbitrary use of a reference gene could lead to the misinterpretation of data.Our study confirmed the necessity of exploring the expression stability of potential reference genes in each specific tissue and experimental situation before quantitative evaluation of gene expression by qRT-PCR.

View Article: PubMed Central - PubMed

Affiliation: Department of Orthopaedic Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou Zhejiang, China ; Sir Run Run Shaw Institute of Clinical Medicine of Zhejiang University, Hangzhou, Zhejiang, China.

ABSTRACT
The quantitative real-time polymerase chain reaction (qRT-PCR) is one of the most widely used methods to study gene expression profiles, and it requires appropriate normalization for accurate and reliable results. Although several genes are commonly used as reference genes (such as GAPDH, ACTB, and 18S rRNA), they are also regulated and can be expressed at varying levels. In this study, we evaluated twelve well-known reference genes to identify the most suitable housekeeping gene for normalization of qRT-PCR in human lumbar vertebral endplate with Modic changes, by using the geNorm, NormFinder, and BestKeeper algorithms. Our results showed that the rarely-used SDHA was the most stable single reference gene, and a combination of three, SDHA, B2M, and LDHA, was the most suitable gene set for normalization in all samples. In addition, the commonly-used genes, GAPDH, ACTB and 18S rRNA, were all inappropriate as internal standards. The rankings of reference genes for the three types of Modic change differed, although SDHA and RPL13A uniformly ranked in the first and last position, respectively. Further simulated expression analysis validated that the arbitrary use of a reference gene could lead to the misinterpretation of data. Our study confirmed the necessity of exploring the expression stability of potential reference genes in each specific tissue and experimental situation before quantitative evaluation of gene expression by qRT-PCR.

Show MeSH
Determination of optimal number of reference genes for each subset according to geNorm.The pairwise variation value (Vn/Vn+1) reflects the improvement obtained by the inclusion of an additional reference gene and was used to determine the optimal number of reference genes. Samples of (a) total cartilage endplate, (b) MC type I, (c) MC type II, and (d) MC type III.
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pone-0088892-g003: Determination of optimal number of reference genes for each subset according to geNorm.The pairwise variation value (Vn/Vn+1) reflects the improvement obtained by the inclusion of an additional reference gene and was used to determine the optimal number of reference genes. Samples of (a) total cartilage endplate, (b) MC type I, (c) MC type II, and (d) MC type III.

Mentions: The geNorm algorithm also calculates the pairwise variation (Vn/Vn+1) between two sequential normalization factors NFn and NFn+1 to determine the optimum number of reference genes. As a general rule, the stepwise inclusion of reference genes is performed until Vn/Vn+1 drops below the theoretical threshold of 0.15, when the benefit of adding an extra gene (n+1) is limited for accuracy normalization [17], [24]. And the use of at least the three most stable reference genes is recommended [16]. In this study, the pairwise variations V3/4 for total and subgroup analyses were all below 0.15, therefore the addition of the fourth-best gene to the gene set composed of the three best ones was not needed (Figure 3).


Selection of suitable reference genes for normalization of quantitative real-time polymerase chain reaction in human cartilage endplate of the lumbar spine.

Zhou ZJ, Zhang JF, Xia P, Wang JY, Chen S, Fang XQ, Fan SW - PLoS ONE (2014)

Determination of optimal number of reference genes for each subset according to geNorm.The pairwise variation value (Vn/Vn+1) reflects the improvement obtained by the inclusion of an additional reference gene and was used to determine the optimal number of reference genes. Samples of (a) total cartilage endplate, (b) MC type I, (c) MC type II, and (d) MC type III.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3928306&req=5

pone-0088892-g003: Determination of optimal number of reference genes for each subset according to geNorm.The pairwise variation value (Vn/Vn+1) reflects the improvement obtained by the inclusion of an additional reference gene and was used to determine the optimal number of reference genes. Samples of (a) total cartilage endplate, (b) MC type I, (c) MC type II, and (d) MC type III.
Mentions: The geNorm algorithm also calculates the pairwise variation (Vn/Vn+1) between two sequential normalization factors NFn and NFn+1 to determine the optimum number of reference genes. As a general rule, the stepwise inclusion of reference genes is performed until Vn/Vn+1 drops below the theoretical threshold of 0.15, when the benefit of adding an extra gene (n+1) is limited for accuracy normalization [17], [24]. And the use of at least the three most stable reference genes is recommended [16]. In this study, the pairwise variations V3/4 for total and subgroup analyses were all below 0.15, therefore the addition of the fourth-best gene to the gene set composed of the three best ones was not needed (Figure 3).

Bottom Line: Our results showed that the rarely-used SDHA was the most stable single reference gene, and a combination of three, SDHA, B2M, and LDHA, was the most suitable gene set for normalization in all samples.Further simulated expression analysis validated that the arbitrary use of a reference gene could lead to the misinterpretation of data.Our study confirmed the necessity of exploring the expression stability of potential reference genes in each specific tissue and experimental situation before quantitative evaluation of gene expression by qRT-PCR.

View Article: PubMed Central - PubMed

Affiliation: Department of Orthopaedic Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou Zhejiang, China ; Sir Run Run Shaw Institute of Clinical Medicine of Zhejiang University, Hangzhou, Zhejiang, China.

ABSTRACT
The quantitative real-time polymerase chain reaction (qRT-PCR) is one of the most widely used methods to study gene expression profiles, and it requires appropriate normalization for accurate and reliable results. Although several genes are commonly used as reference genes (such as GAPDH, ACTB, and 18S rRNA), they are also regulated and can be expressed at varying levels. In this study, we evaluated twelve well-known reference genes to identify the most suitable housekeeping gene for normalization of qRT-PCR in human lumbar vertebral endplate with Modic changes, by using the geNorm, NormFinder, and BestKeeper algorithms. Our results showed that the rarely-used SDHA was the most stable single reference gene, and a combination of three, SDHA, B2M, and LDHA, was the most suitable gene set for normalization in all samples. In addition, the commonly-used genes, GAPDH, ACTB and 18S rRNA, were all inappropriate as internal standards. The rankings of reference genes for the three types of Modic change differed, although SDHA and RPL13A uniformly ranked in the first and last position, respectively. Further simulated expression analysis validated that the arbitrary use of a reference gene could lead to the misinterpretation of data. Our study confirmed the necessity of exploring the expression stability of potential reference genes in each specific tissue and experimental situation before quantitative evaluation of gene expression by qRT-PCR.

Show MeSH