Using Ribosomal Protein Genes as Reference: A Tale of Caution

Background: Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms "reference genes'' and "housekeeping genes'' are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data. Methodology/Principal Findings: We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes. Conclusions/Significance: Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes

Age-related changes in relative expression stability of commonly used housekeeping genes in selected porcine tissues

<p>Abstract</p> <p>Background</p> <p>Gene expression analysis using real-time RT-PCR (qRT-PCR) is increasingly important in biological research due to the high-throughput and accuracy of qRT-PCR. For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes or internal control genes is required. The stability of reference genes has a tremendous effect on the results of relative quantification of gene expression by qRT-PCR. The expression stability of reference genes could vary according to tissues, age of individuals and experimental conditions. In the pig however, very little information is available on the expression stability of reference genes. The aim of this research was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in varieties of porcine tissues at different ages.</p> <p>Results</p> <p>The mRNA expression stability of nine commonly used reference genes (<it>B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP </it>and <it>YWHAZ</it>) was determined in varieties of tissues collected from newborn, young and adult pigs. geNorm, NormFinder and BestKeeper software were used to rank the genes according to their stability. geNorm software revealed that <it>RPL4, PPIA </it>and <it>YWHAZ </it>showed high stability in newborn and adult pigs, while <it>B2M, YWHAZ </it>and <it>SDHA </it>showed high stability in young pigs. In all cases, <it>GAPDH </it>showed the least stability in geNorm. NormFinder revealed that <it>TBP </it>was the most stable gene in newborn and young pigs, while <it>PPIA </it>was most stable in adult pigs. Moreover, geNorm software suggested that the geometric mean of three most stable gene would be the suitable combination for accurate normalization of gene expression study.</p> <p>Conclusions</p> <p>Although, there was discrepancy in the ranking order of reference genes obtained by different analysing software methods, the geometric mean of the <it>RPL4, PPIA </it>and <it>YWHAZ </it>seems to be the most appropriate combination of housekeeping genes for accurate normalization of gene expression data in different porcine tissues at different ages.</p

Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis

The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples.After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology.Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies

Gene expression markers of tendon fibroblasts in normal and diseased tissue compared to monolayer and three dimensional culture systems

<p>Abstract</p> <p>Background</p> <p>There is a paucity of data regarding molecular markers that identify the phenotype of the tendon cell. This study aims to quantify gene expression markers that distinguish between tendon fibroblasts and other mesenchymal cells which may be used to investigate tenogenesis.</p> <p>Methods</p> <p>Expression levels for 12 genes representative of musculoskeletal tissues, including the proposed tendon progenitor marker scleraxis, relative to validated reference genes, were evaluated in matched samples of equine tendon (harvested from the superficial digital flexor tendon), cartilage and bone using quantitative PCR (qPCR). Expression levels of genes associated with tendon phenotype were then evaluated in healthy, including developmental, and diseased equine tendon tissue and in tendon fibroblasts maintained in both monolayer culture and in three dimensional (3D) collagen gels.</p> <p>Results</p> <p>Significantly increased expression of scleraxis was found in tendon compared with bone (P = 0.002) but not compared to cartilage. High levels of COL1A2 and scleraxis and low levels of tenascin-C were found to be most representative of adult tensional tendon phenotype. While, relative expression of scleraxis in developing mid-gestational tendon or in acute or chronically diseased tendon did not differ significantly from normal adult tendon, tenascin-C message was significantly upregulated in acutely injured equine tendon (P = 0.001). Relative scleraxis gene expression levels in tendon cell monolayer and 3D cultures were significantly lower than in normal adult tendon (P = 0.002, P = 0.02 respectively).</p> <p>Conclusion</p> <p>The findings of this study indicate that high expression of both COL1A2 and scleraxis, and low expression of tenascin-C is representative of a tensional tendon phenotype. The <it>in vitro </it>culture methods used in these experiments however, may not recapitulate the phenotype of normal tensional tendon fibroblasts in tissues as evidenced by gene expression.</p

Genomic selection of reference genes for real-time PCR in human myocardium

<p>Abstract</p> <p>Background</p> <p>Reliability of real-time PCR (RT-qPCR) data is dependent on the use of appropriate reference gene(s) for normalization. To date, no validated reference genes have been reported for normalizing gene expression in human myocardium. This study aimed to identify validated reference genes for use in gene expression studies of failed and non-failed human myocardium.</p> <p>Methods</p> <p>Bioinformatic analysis of published human heart gene expression arrays (195 failed hearts, 16 donor hearts) was used to identify 10 stable and abundant genes for further testing. The expression stability of these genes was investigated in 28 failed and 28 non-failed human myocardium samples by RT-qPCR using geNorm software.</p> <p>Results</p> <p>Signal recognition particle 14 kDa (SRP14), tumor protein, translationally-controlled 1 (TPT1) and eukaryotic elongation factor 1A1 (EEF1A1) were ranked the most stable genes. The commonly used reference gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was ranked the least stable of the genes tested. The normalization strategy was tested by comparing RT-qPCR data of both normalized and raw expression levels of brain natriuretic peptide precursor (NPPB), a gene known to be up-regulated in heart failure. Non-normalized levels of NPPB exhibited a marginally significant difference between failed and non-failed samples (p = 0.058). In contrast, normalized NPPB expression levels were significantly higher in heart-failed patients compared with controls (p = 0.023).</p> <p>Conclusion</p> <p>This study used publicly available gene array data to identify a strategy for normalization involving two reference genes in combination that may have broad application for accurate and reliable normalization of RT-qPCR data in failed and non-failed human myocardium.</p