Identification of Suitable Reference Genes for Normalization of Real-Time Quantitative Polymerase Chain Reaction in an Intestinal Graft-Versus-Host Disease Mouse Model

Validation of Housekeeping Genes as Reference for Reverse-Transcription-qPCR Analysis in Busulfan-Injured Microvascular Endothelial Cells

Endothelial cells (ECs) could express some important cytokines and signal molecules which play a key role in normal hematopoiesis and repopulation. Busulfan-induced vascular endothelial injury is an important feature after hematopoietic stem cell transplantation (HSCT). But the molecular mechanism of how the injured ECs affect hematopoietic reconstruction is still unknown. It is possibly through modulation of the change of some gene expression. RT-qPCR is one of the most popular methods used to accurately determine gene expression levels, based on stable reference gene (RG) selection from housekeeping genes. So our aim is to select stable RGs for more accurate measures of mRNA levels during Busulfan-induced vascular endothelial injury. In this study, 14 RGs were selected to investigate their expression stability in ECs during 72 hours of EC injury treated with Busulfan. Our results revealed extreme variation in RG stability compared by five statistical algorithms. ywhaz and alas1 were recognized as the two idlest RGs on account of the final ranking, while the two most usually used RGs (gapdh and actb) were not the most stable RGs. Next, these data were verified by testing signalling pathway genes ctnnb1, robo4, and notch1 based on the above four genes ywha, alas1, gapdh, and actb. It shows that the normalization of mRNA expression data using unstable RGs greatly affects gene fold change, which means the reliability of the biological conclusions is questionable. Based on the best RGs used, we also found that robo4 is significantly overexpressed in Busulfan-impaired ECs. In conclusion, our data reaffirms the importance of RGs selection for the valid analysis of gene expression in Busulfan-impaired ECs. And it also provides very useful guidance and basis for more accurate differential expression gene screening and future expanding biomolecule study of different drugs such as cyclophosphamide and fludarabine-injured ECs.

Optimal reference genes for RT-qPCR normalization in the newborn

It is difficult to identify reliable reference genes for transcriptomic analyses in biofluids such as saliva. This situation is particularly relevant for the newborn population, where rapid development is associated with dynamic changes in gene expression. Real-time gene expression monitoring holds great promise for elucidating disrupted pathways that result in morbidities unique to this population, such as retinopathy of prematurity, but its impact depends on identifying stable and consistently expressed genes across a wide range of gestational ages. We extracted total RNA from 400 neonatal saliva samples (postconceptional ages: 32 5/7 to 48 2/7 weeks), converted it to cDNA, and pre-amplified and analyzed it by qPCR for three commonly used reference genes, ACTB, GAPDH, and YWHAZ. Relative quantification was determined using the Δ Ct method. Data were analyzed as a whole and also stratified by age and sex. Descriptive statistics and homogeneity of variance were performed to identify optimal reference genes. Data analyzed from all ages and both sexes showed significant expression variation for ACTB, while GAPDH and YWHAZ showed greater stability. Male infants exhibited increased expression variation compared to females for ACTB, but neither GAPDH nor YWHAZ showed significant variance for either sex. We suggest that ACTB is an unreliable reference gene for the newborn population. Males showed significantly more variation in ACTB expression compared to females, which suggests a sex-specific developmental role for this biomarker. By contrast, GAPDH and YWHAZ were less variable and therefore preferable for use in neonates. Our findings may improve the use of reference genes for the RT-qPCR platform in the newborn over a wide range of gestational ages, thereby minimizing the likelihood of erroneous interpretation of gene expression during rapid growth, development, and differentiation.

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

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.

The Challenge of Stability in High-Throughput Gene Expression Analysis: Comprehensive Selection and Evaluation of Reference Genes for BALB/c Mice Spleen Samples in the Leishmania infantum Infection Model

The interaction of Leishmania with BALB/c mice induces dramatic changes in transcriptome patterns in the parasite, but also in the target organs (spleen, liver…) due to its response against infection. Real-time quantitative PCR (qPCR) is an interesting approach to analyze these changes and understand the immunological pathways that lead to protection or progression of disease. However, qPCR results need to be normalized against one or more reference genes (RG) to correct for non-specific experimental variation. The development of technical platforms for high-throughput qPCR analysis, and powerful software for analysis of qPCR data, have acknowledged the problem that some reference genes widely used due to their known or suspected “housekeeping” roles, should be avoided due to high expression variability across different tissues or experimental conditions. In this paper we evaluated the stability of 112 genes using three different algorithms: geNorm, NormFinder and RefFinder in spleen samples from BALB/c mice under different experimental conditions (control and Leishmania infantum-infected mice). Despite minor discrepancies in the stability ranking shown by the three methods, most genes show very similar performance as RG (either good or poor) across this massive data set. Our results show that some of the genes traditionally used as RG in this model (i.e. B2m, Polr2a and Tbp) are clearly outperformed by others. In particular, the combination of Il2rg + Itgb2 was identified among the best scoring candidate RG for every group of mice and every algorithm used in this experimental model. Finally, we have demonstrated that using “traditional” vs rationally-selected RG for normalization of gene expression data may lead to loss of statistical significance of gene expression changes when using large-scale platforms, and therefore misinterpretation of results. Taken together, our results highlight the need for a comprehensive, high-throughput search for the most stable reference genes in each particular experimental model.