GUSB and ATP2B4 are suitable reference genes for CFTR gene expression data normalization in nasal epithelium cells

Validation of reference genes for use in untreated bovine fibroblasts

Proper normalization of RT-qPCR data is pivotal to the interpretation of results and accuracy of scientific conclusions. Though different approaches may be taken, normalization against multiple reference genes is now standard practice. Genes traditionally used and deemed constitutively expressed have demonstrated variability in expression under different experimental conditions, necessitating the proper validation of reference genes prior to utilization. Considering the wide use of fibroblasts in research and scientific applications, it is imperative that suitable reference genes for fibroblasts of different animal origins and conditions be elucidated. Previous studies on bovine fibroblasts have tested limited genes and/or samples. Herein, we present an extensive study investigating the expression stability of 16 candidate reference genes across 7 untreated bovine fibroblast cell lines subjected to controlled conditions. Data were analysed using various statistical tools and algorithms, including geNorm, NormFinder, BestKeeper, and RefFinder. A combined use of GUSB and RPL13A was determined to be the best approach for data normalization in untreated bovine fibroblasts.

Assessment of suitable reference genes for RT-qPCR studies in chronic rhinosinusitis

Reverse transcription–quantitative polymerase chain reaction is a valuable and reliable method for gene quantification. Target gene expression is usually quantified by normalization using reference genes (RGs), and accurate normalization is critical for producing reliable data. However, stable RGs in nasal polyps and sinonasal tissues from patients with chronic rhinosinusitis (CRS) have not been well investigated. Here, we used a two-stage study design to identify stable RGs. We assessed the stability of 15 commonly used candidate RGs using five programs—geNorm, NormFinder, BestKeeper, ΔCT, and RefFinder. Ribosomal protein lateral stalk subunit P1 (RPLP1) and ribosomal protein lateral stalk subunit P0 (RPLP0) were the two most stable RGs in the first stage of the study, and these results were validated in the second stage. The commonly used RGs β-actin (ACTB) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were unstable according to all of the algorithms used. The findings were further validated via relative quantification of IL-5, CCL11, IFN-γ, and IL-17A using the stable and unstable RGs. The relative expression levels varied greatly according to normalization with the selected RGs. Appropriate selection of stable RGs will allow more accurate determination of target gene expression levels in patients with CRS.

Assessing the residual CFTR gene expression in human nasal epithelium cells bearing CFTR splicing mutations causing cystic fibrosis

The major purpose of the present study was to quantify correctly spliced CFTR transcripts in human nasal epithelial cells from cystic fibrosis (CF) patients carrying the splicing mutations c.580-1G>T (712-1G>T) and c.2657+5G>A (2789+5G>A) and to assess the applicability of this model in CFTR therapeutic approaches. We performed the relative quantification of CFTR mRNA by reverse transcription quantitative PCR (RT-qPCR) of these splicing mutations in four groups (wild type, CF-F508del controls, CF patients and CF carriers) of individuals. In addition, in vitro assays using minigene constructs were performed to evaluate the effect of a new CF complex allele c.[2657+5G>A; 2562T>G]. Ex vivo qPCR data show that the primary consequence of both mutations at the RNA level is the skipping of their neighboring exon (6 and 16, respectively). The CFTR minigenes results mimicked the ex vivo data, as exon 16 skipping is the main aberrant transcript, and the correctly spliced transcript level was observed in a similar proportion when the c.2657+5G>A mutation is present. In summary, we provide evidence that ex vivo quantitative transcripts analysis using RT/qPCR is a robust technology that could be useful for measuring the efficacy of therapeutic approaches that attempt to achieve an increase in CFTR gene expression.

FFPE tissue as a feasible source for gene expression analysis--a comparison of three reference genes and one tumor marker

BACKGROUND

Formalin-fixation, paraffin-embedding is the standard processing technique for tumor tissue in modern pathology. New techniques such as cryo-conservation allow rapid fixation and long-time storage but come along with increased costs and enlarged storage complexity. However, formalin-fixed, paraffin-embedded (FFPE) tissue is available in a large quantity, making it the ideal material for retrospective studies. The following study was designed to investigate the influence of formalin-fixation on the quality of mRNA and applicability of FFPE-derived mRNA for gene expression analysis. Three potential reference genes for pulmonary tumors with neuroendocrine differentiation were included and tested for their robust expression.

MATERIALS AND METHODS

Eighty specimens collected from 2005 to 2012 at the Institute of Pathology and Neuropathology at the University Hospital Essen were analyzed for their gene expression by using TaqMan(®) gene expression assays on demand (AoD). Three distinct potential reference genes (ACTB, GAPDH, HPRT1) were evaluated for their expression, and a proteasome subunit (PSMA1) was included in the analysis as tumor marker and functioned as an internal technical control.

CONCLUSION

For GAPDH and ACTB, a highly significant correlation and consistent expression between the investigated entities was found, making them reliable reference genes for further research. Additionally, the feasibility for a FFPE tissue-based gene expression analysis was verified by showing that the mRNA quality is sufficient. When standardized FFPE preparation is performed carefully, sufficient mRNA can be isolated for reliable and successful gene expression analysis. That provides the basis the door for large, retrospective studies that correlate molecular and clinical follow-up data.