Selection of reference genes for gene expression studies in astrocytomas.

This study was aimed to test a panel of six housekeeping genes (GAPDH, HPRT1, POLR2A, RPLP0, ACTB, and H3F) so as to identify and validate the most suitable reference genes for expression studies in astrocytomas. GAPDH was the most stable and HPRT1 was the least stable reference gene. The effect of reference gene selection on quantitative real-time polymerase chain reaction data interpretation was demonstrated, normalizing the expression data of a selected gene of interest. Thus, GAPDH may be recommended for data normalization in gene expression studies in astrocytomas. Nevertheless, a preliminary validation of reference gene stability is required prior to every study.

Identification of internal control genes for quantitative expression analysis by real-time PCR in bovine peripheral lymphocytes.

Gene expression studies in blood cells, particularly lymphocytes, are useful for monitoring potential exposure to toxicants or environmental pollutants in humans and livestock species. Quantitative PCR is the method of choice for obtaining accurate quantification of mRNA transcripts although variations in the amount of starting material, enzymatic efficiency, and the presence of inhibitors can lead to evaluation errors. As a result, normalization of data is of crucial importance. The most common approach is the use of endogenous reference genes as an internal control, whose expression should ideally not vary among individuals and under different experimental conditions. The accurate selection of reference genes is therefore an important step in interpreting quantitative PCR studies. Since no systematic investigation in bovine lymphocytes has been performed, the aim of the present study was to assess the expression stability of seven candidate reference genes in circulating lymphocytes collected from 15 dairy cows. Following the characterization by flow cytometric analysis of the cell populations obtained from blood through a density gradient procedure, three popular softwares were used to evaluate the gene expression data. The results showed that two genes are sufficient for normalization of quantitative PCR studies in cattle lymphocytes and that YWAHZ, S24 and PPIA are the most stable genes.

A sequence-based approach to identify reference genes for gene expression analysis.

BACKGROUND: An important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer) may not be suitable in another (e.g. breast cancer). Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate. METHODS: Serial analysis of gene expression (SAGE) profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR), and their impact on differential expression analysis of microarray data was evaluated. RESULTS: We show that (i) conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii) reference genes identified for lung cancer do not perform well for other cancer types (breast and brain), (iii) reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv) normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes. CONCLUSIONS: Our analyses found NDUFA1, RPL19, RAB5C, and RPS18 to occupy the top ranking positions among 15 suitable reference genes optimal for normalization of lung tissue expression data. Significantly, the approach used in this study can be applied to data generated using new generation sequencing platforms for the identification of reference genes optimal within diverse contexts.

Evaluation of potential reference genes for real time RT-PCR studies in Atlantic halibut (Hippoglossus Hippoglossus L.); during development, in tissues of healthy and NNV-injected fish, and in anterior kidney leucocytes.

BACKGROUND: Real time RT-PCR has become an important tool for analyzing gene expression in fish. Although several housekeeping genes have been evaluated in Atlantic halibut (Hippoglossus Hippoglossus L.), appropriate reference genes for low copy mRNA transcripts at the earliest developmental stages have not been identified. No attempts have been reported to identify suitable reference genes in halibut infected with NNV or in stimulated halibut leucocytes. In this study, beta-actin1 (ACTB1), elongation factor 1 alpha (EF1A1), hypoxanthine-guanine phosphoribosyltransferase 1 (HPRT1), ribosomal protein L7 (RPL7), tubulin beta 2C (Tubb2C), and ubiquitin-conjugating enzyme (UbcE) were evaluated as reference genes for normalization of real time RT-PCR data during Atlantic halibut development, in tissue of healthy and NNV-infected fish, and in in vivo and in vitro stimulated anterior kidney leucocytes. RESULTS: The expression of all six genes was relatively stable from the unfertilized egg until 12 day degrees post fertilization (ddpf). However, none of the selected genes were found to be stably expressed throughout halibut development. The mRNA levels of the six genes increased from 18 ddpf, when zygotic transcription is likely to be activated, and stabilized at different time points. The Excel-based software programs BestKeeper, geNorm, and NormFinder ranked EF1A1 and UbcE as the best candidate reference genes before activation of zygotic transcription, and RPL7 and EF1A1 as the best candidates after hatching. EF1A1 and RPL7 were also listed as the best reference genes when exploring the expression levels of the six genes in various halibut organs, both in non-injected fish and in mock- and NNV-injected fish. None of the reference genes were found optimal for normalization of real time RT-PCR data from in vitro stimulated anterior kidney leucocytes. CONCLUSION: Generally, it was found that EF1A1 and RPL7 were the genes that showed least variation, with HPRT1 and UbcE as intermediate genes, and ACTB1 and Tubb2C as the least stable ones. None of the six reference genes can be recommended as reference gene candidates in ConA-PMA stimulated leucocytes. However, UbcE can be a good candidate in other experimental setups. This study emphasizes the need for reference gene evaluation, as universal reference genes have not been identified.