Validation of suitable reference genes for quantitative polymerase chain reaction analysis in rabbit bone marrow mesenchymal stem cell differentiation.

Bone marrow mesenchymal stem cells (BMSCs) are considered as multipotent cells, representing a multi-lineage potential to differentiate into mesodermal lineages of mesenchymal tissues, including cartilage, bone, fat, muscle and tendon. Tissue engineering in BMSCs has made great advances in the regeneration of cartilage and bone defects. To uncover the mechanisms of the multipotent differentiation process, the molecular changes in gene expression profiles during chondrogenic and osteogenic differentiation need to be evaluated with reliable, accurate, fast and sensitive methods. Reverse transcription-quantitative polymerase chain reaction is a commonly used technology for analyzing gene expression, depending on an appropriate reference gene to normalize the errors. The commonly used reference genes vary, and no ideal and universal reference genes suitable for all conditions exist; therefore validation of the stability of gene expression is required. In the present study, three common statistical algorithms, geNorm, Normfinder and BestKeeper, were used to identify the expression stability of 12 genes, and the target differentiation markers during the differentiation of BMSCs were evaluated accurately. Our results demonstrated that YWHAZ, PPIA and GAPDH were suitable as reference genes for chondrogenic differentiation, while RPL13a allowed an efficient normalization expression value of interest genes for osteogenic differentiation of BMSCs. By contrast, the most unstable reference genes were 18s rRNA, B2M and HPRT1 in all studies, and these should be avoided when investigating the differentiation of BMSCs. Our results demonstrate validation of the appropriate reference genes for accurate gene expression in chondrogenic and osteogenic differentiation of BMSCs.

[Novel reference gene RPN1 for normalization of quantitative data in lung and kidney cancer].

Quantitative methods of gene expression analysis in tumors require accurate data normalization, which allows comparison of different mRNA/cDNA samples with unknown concentration. For this purpose reference genes with stable expression level (such as GAPDH, ACTB, HPRT1, TBP) are used. The choice of appropriate reference genes is still actual because well-known reference genes are not suitable for certain cancer types frequently and their unreasonable use without additional tests lead to wrong conclusions. We have developed the bioinformatic approach and selected a new potential reference gene RPN1 for lung and kidney tumors. This gene is located at the long arm of chromosome 3. Our method includes mining of the dbEST and Oncomine databases and functional analysis of genes. The RPN1 was selected from 1500 candidate housekeeping genes. Using comparative genomic hybridization with NotI-microarrays we found no methylation, deletions and/or amplifications at the RPN1-containing locus in 56 non-small cell lung and 42 clear cell renal cancer samples. Using RT-qPCR we showed low variability of RPN1 mRNA level comparable to those of reference genes GAPDH and GUSB in lung and kidney cancer. The mRNA levels of two target genes coding hyalouronidases--HYAL1 and HYAL2--were estimated and normalized relative to pair RPN1--GAPDH genes for lung cancer and RPN1--GUSB for kidney cancer. These combinations were shown to be optimal for obtaining accurate and reproducible data. All obtained results allow us to suggest RPN1 as novel reference gene for quantitative data normalization in gene expression studies for lung and kidney cancers.

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples.

BACKGROUND: Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. RESULTS: Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. CONCLUSIONS: We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system.