Identification of reference genes for qPCR analysis during hASC long culture maintenance

Abstract

Up to now quantitative PCR based assay is the most common method for characterizing or confirming gene expression patterns and comparing mRNA levels in different sample populations. Since this technique is relative easy and low cost compared to other methods of characterization, e.g. flow cytometry, we used it to typify human adipose-derived stem cells (hASCs). hASCs possess several characteristics that make them attractive for scientific research and clinical applications. Accurate normalization of gene expression relies on good selection of reference genes and the best way to choose them appropriately is to follow the common rule of the “Best 3”, at least three reference genes, three different validation software and three sample replicates. Analysis was performed on hASCs cultivated until the eleventh cell confluence using twelve candidate reference genes, initially selected from literature, whose stability was evaluated by the algorithms NormFinder, BestKeeper, RefFinder and IdealRef, a home-made version of GeNorm. The best gene panel (RPL13A, RPS18, GAPDH, B2M, PPIA and ACTB), determined in one patient by IdealRef calculation, was then investigated in other four donors. Although patients demonstrated a certain gene expression variability, we can assert that ACTB is the most unreliable gene whereas ribosomal proteins (RPL13A and RPS18) show minor inconstancy in their mRNA expression. This work underlines the importance of validating reference genes before conducting each experiment and proposes a free software as alternative to those existing.

Determination of qPCR Reference Genes Suitable for Normalizing Gene Expression in a Canine Model of Duchenne Muscular Dystrophy

“…The accuracy of this technique is criticallydependent on good normalization: even with identical starting material, slight differences in the efficiency of RNA isolation or cDNA synthesis can significantly affect subsequent quantitation. Effective normalization requires appropriate reference genes, and indeed efforts to identify, validate and publicize such genes are becoming more common in a variety of disease states [20][21][22][23][24] and model organisms [25][26][27][28][29][30]. A review of the literature specifically within the DMD field however reveals a considerable number of candidates: selected examples in dystrophic dogs include GAPDH [31][32][33], RPS18 [34], HPRT1 [35,36], 18S [37]; in humans, TBP and GUSB [13]; and in mice GAPDH [33,38], ActB [39], 18S [40].…”

Effect of Nanostructured Scaffold on Human Adipose-Derived Stem Cells: Outcome of In Vitro Experiments

“…For qPCR, CD44 and CD90 genes were used as positive stemness markers, while fatty acid-binding protein 4 ( FABP4 ), adipocyte complement-related protein 30 ( ACRP30 ), and acetyl-coenzyme A synthetase 2 ( ACSS2 ) genes were taken as differentiation markers. According to the method of Palombella [ 18 ] glyceraldehyde-3-phosphate dehydrogenase - GAPDH and beta2-microglobulin - β2m ) were used as reference genes. Quantification has been conducted by using the 2 −ΔΔCt method.…”

Effects of Metal Micro and Nano-Particles on hASCs: An In Vitro Model

“…The analysis was performed on genes involved in oxidative stress ( CAT ; SOD ; MT1A ; Hsp70 ), apoptosis ( P53 ; CASP3 ; BCL2 ; EGR1 ), inflammatory response ( IL6 ; IL8 ; IL1b ), neovascularization, tissue regeneration ( HIF1α ; VEGFA ), and internalization ( AP2A1 ), see Table 1 [ 46 , 47 , 48 , 49 , 50 , 51 , 52 ]. Housekeeping genes ( ACTβ: β-actin ; B2M: beta-2-microglobulin ; GAPDH: glyceraldehyde-3-phosphate dehydrogenase ; RPL13A: ribosomal protein L13A ; RPS18: ribosomal protein S18 ; PPIA: peptidylprolyl isomerase A ) were selected as described in Palombella et al [ 53 ]. qPCR reaction was set up with 300 nM of each primer and 5 ng of cDNA in a total volume of 10 µL.…”