Normalization Of Gene Expression Data Research Articles

A Well-Controlled Experimental System to Study Interactions of Cytotoxic T Lymphocytes with Tumor Cells.

While T cell-based immunotherapies are steadily improving, there are still many patients who progress, despite T cell-infiltrated tumors. Emerging evidence suggests that T cells themselves may provoke immune escape of cancer cells. Here, we describe a well-controlled co-culture system for studying the dynamic T cell – cancer cell interplay, using human melanoma as a model. We explain starting material, controls, and culture parameters to establish reproducible and comparable cultures with highly heterogeneous tumor cells. Low passage melanoma cell lines and melanoma-specific CD8+ T cell clones generated from patient blood were cultured together for up to 3 days. Living melanoma cells were isolated from the co-culture system by fluorescence-activated cell sorting. We demonstrate that the characterization of isolated melanoma cells is feasible using flow cytometry for protein expression analysis as well as an Agilent whole human genome microarray and the NanoString technology for differential gene expression analysis. In addition, we identify five genes (ALG12, GUSB, RPLP0, KRBA2, and ADAT2) that are stably expressed in melanoma cells independent of the presence of T cells or the T cell-derived cytokines IFNγ and TNFα. These genes are essential for correct normalization of gene expression data by NanoString. Further to the characterization of melanoma cells after exposure to CTLs, this experimental system might be suitable to answer a series of questions, including how the affinity of CTLs for their target antigen influences the melanoma cell response and whether CTL-induced gene expression changes in melanoma cells are reversible. Taken together, our human T cell – melanoma cell culture system is well suited to characterize immune-related mechanisms in cancer cells.

Validation of Suitable Reference Genes for Assessing Gene Expression of MicroRNAs in Lonicera japonica.

MicroRNAs (miRNAs), which play crucial regulatory roles in plant secondary metabolism and responses to the environment, could be developed as promising biomarkers for different varieties and production areas of herbal medicines. However, limited information is available for miRNAs from Lonicera japonica, which is widely used in East Asian countries owing to various pharmaceutically active secondary metabolites. Selection of suitable reference genes for quantification of target miRNA expression through quantitative real-time (qRT)-PCR is important for elucidating the molecular mechanisms of secondary metabolic regulation in different tissues and varieties of L. japonica. For precise normalization of gene expression data in L. japonica, 16 candidate miRNAs were examined in three tissues, as well as 21 cultivated varieties collected from 16 production areas, using GeNorm, NormFinder, and RefFinder algorithms. Our results revealed combination of u534122 and u3868172 as the best reference genes across all samples. Their specificity was confirmed by detecting the cycling threshold (Ct) value ranges in different varieties of L. japonica collected from diverse production areas, suggesting the use of these two reference miRNAs is sufficient for accurate transcript normalization with different tissues, varieties, and production areas. To our knowledge, this is the first report on validation of reference miRNAs in honeysuckle (Lonicera spp.). Restuls from this study can further facilitate discovery of functional regulatory miRNAs in different varieties of L. japonica.

Genome-wide identification of suitable zebrafish Danio rerio reference genes for normalization of gene expression data by RT-qPCR.

In this study, to systematically identify the most stably expressed genes for internal reference in zebrafish Danio rerio investigations, 37 D. rerio transcriptomic datasets (both RNA sequencing and microarray data) were collected from gene expression omnibus (GEO) database and unpublished data, and gene expression variations were analysed under three experimental conditions: tissue types, developmental stages and chemical treatments. Forty-four putative candidate genes were identified with the c.v. <0·2 from all datasets. Following clustering into different functional groups, 21 genes, in addition to four conventional housekeeping genes (eef1a1l1, b2m, hrpt1l and actb1), were selected from different functional groups for further quantitative real-time (qrt-)PCR validation using 25 RNA samples from different adult tissues, developmental stages and chemical treatments. The qrt-PCR data were then analysed using the statistical algorithm refFinder for gene expression stability. Several new candidate genes showed better expression stability than the conventional housekeeping genes in all three categories. It was found that sep15 and metap1 were the top two stable genes for tissue types, ube2a and tmem50a the top two for different developmental stages, and rpl13a and rp1p0 the top two for chemical treatments. Thus, based on the extensive transcriptomic analyses and qrt-PCR validation, these new reference genes are recommended for normalization of D. rerio qrt-PCR data respectively for the three different experimental conditions.

Normalization of gene expression data using support vector machine approach

Normalization of gene expression data refers the process of minimizing non biological variation in measured probe intensity levels so that biological differences in gene expression can be appropriately detected. Several linear normalization within arrays approaches has already been proposed. Recently, use of non-linear methods has been gained quite attention. In this study, our objective is to formulate non-linear normalization methods using support vector regression (SVR) and support vector machine quantile regression (SVMQR) approaches, more easier way and, assess the consistency of these methods with respect to other standard normalization methods for further application in gene expression data. SVR and SVMQR normalization methods have been implemented and their performance have been evaluated with respect to other standard normalization methods namely, locally weighted scatter plot smoothing and Kernel regression. It has been found that the normalized data based on proposed methods are capable of producing minimum variances within replicate groups and also able to detect truly expressible significant genes with respect to above mentioned other normalized data.

Selection of suitable reference genes for assessing gene expression in pearl millet under different abiotic stresses and their combinations.

Pearl millet [Pennisetum glaucum (L.) R. Br.] a widely used grain and forage crop, is grown in areas frequented with one or more abiotic stresses, has superior drought and heat tolerance and considered a model crop for stress tolerance studies. Selection of suitable reference genes for quantification of target stress-responsive gene expression through quantitative real-time (qRT)-PCR is important for elucidating the molecular mechanisms of improved stress tolerance. For precise normalization of gene expression data in pearl millet, ten candidate reference genes were examined in various developmental tissues as well as under different individual abiotic stresses and their combinations at 1 h (early) and 24 h (late) of stress using geNorm, NormFinder and RefFinder algorithms. Our results revealed EF-1α and UBC-E2 as the best reference genes across all samples, the specificity of which was confirmed by assessing the relative expression of a PgAP2 like-ERF gene that suggested use of these two reference genes is sufficient for accurate transcript normalization under different stress conditions. To our knowledge this is the first report on validation of reference genes under different individual and multiple abiotic stresses in pearl millet. The study can further facilitate fastidious discovery of stress-tolerance genes in this important stress-tolerant crop.

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae).

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms.

Selection of reference genes in canine uterine tissues.

Real-time quantitative polymerase chain reaction (RT-qPCR) is usually employed in gene expression studies in veterinary research, including in studies on canine pyometra. Canine pyometra is a common clinical disease in bitches. When using RT-qPCR, internal standards, such as reference genes, are necessary to investigate relative gene expression by quantitative measurements of mRNA levels. The aim of this study was to evaluate the stability of reference genes and select reference genes suitable for canine pyometra studies. We collected 24 bitch uterine tissue samples, including five healthy and 19 pyometra infected samples. These were used to screen the best reference genes of seven candidate genes (18SrRNA, ACTB, B2M, GAPDH, HPRT, RPL13A, and YWHAZ). The method of KH Sadek and the GeNorm, Normfinder, BestKeeper, and RefFinder software were used to evaluate the stability of gene expression in both pyometra and healthy uterine samples. The results showed that the expression stability of the candidate gene in pyometra and healthy tissues differed. We showed that YWHAZ was the best reference gene, which could be used as an accurate internal control gene in canine pyometra studies. To further validate this recommendation, the expression profile of a target gene insulin-like growth factor 1 receptor gene (IGF1R) was investigated. We found that the expression of IGF1R was significantly altered when different reference genes were used. All reference genes identified in the present study will enable more accurate normalization of gene expression data in both pyometra infected and healthy uterine tissues.

Consensus reference gene(s) for gene expression studies in human cancers: end of the tunnel visible?

Gene expression studies are increasingly used to provide valuable information on the diagnosis and prognosis of human cancers. Also, for in vitro and in vivo experimental cancer models gene expression studies are widely used. The complex algorithms of differential gene expression analyses require normalization of data against a reference or normalizer gene, or a set of such genes. For this purpose, mostly invariant housekeeping genes are used. Unfortunately, however, there are no consensus (housekeeping) genes that serve as reference or normalizer for different human cancers. In fact, scientists have employed a wide range of reference genes across different types of cancer for normalization of gene expression data. As a consequence, comparisons of these data and/or data harmonizations are difficult to perform and challenging. In addition, an inadequate choice for a reference gene may obscure genuine changes and/or result in erroneous gene expression data comparisons. In our effort to highlight the importance of selecting the most appropriate reference gene(s), we have screened the literature for gene expression studies published since the turn of the century on thirteen of the most prevalent human cancers worldwide. Based on the analysis of the data at hand, we firstly recommend that in each study the suitability of candidate reference gene(s) should carefully be evaluated in order to yield reliable differential gene expression data. Secondly, we recommend that a combination of PPIA and either GAPDH, ACTB, HPRT and TBP, or appropriate combinations of two or three of these genes, should be employed in future studies, to ensure that results from different studies on different human cancers can be harmonized. This approach will ultimately increase the depth of our understanding of gene expression signatures across human cancers.

Selection and validation of reference genes for quantitative real-time PCR studies during Saccharomyces cerevisiae alcoholic fermentation in the presence of sulfite

Sulfur dioxide is extensively used during industrial fermentations and contributes to determine the harsh conditions of winemaking together with low pH, high sugar content and increasing ethanol concentration. Therefore the presence of sulfite has to be considered in yeast gene expression studies to properly understand yeast behavior in technological environments such as winemaking. A reliable expression pattern can be obtained only using an appropriate reference gene set that is constitutively expressed regardless of perturbations linked to the experimental conditions.In this work we tested 15 candidate reference genes suitable for analysis of gene expression during must fermentation in the presence of sulfite. New reference genes were selected from a genome-wide expression experiment, obtained by RNA sequencing of four Saccharomyces cerevisiae wine strains grown in enological conditions. Their performance was compared to that of the most common genes used in previous studies. The most popular software based on different statistical approaches (geNorm, NormFinder and BestKeeper) were chosen to evaluate expression stability of the candidate reference genes. Validation was obtained using other wine strains by comparing normalized gene expression data with transcriptome quantification both in the presence and absence of sulfite.Among 15 reference genes tested ALG9, FBA1, UBC6 and PFK1 appeared to be the most reliable while ENO1, PMA1, DED1 and FAS2 were the worst. The most popular reference gene ACT1, widely used for S. cerevisiae gene expression studies, showed a stability level markedly lower than those of our selected reference genes. Finally, as the expression of the new reference gene set remained constant over the entire fermentation process, irrespective of the perturbation due to sulfite addition, our results can be considered also when no sulfite is added to the must.

Abstract 4591: Differential expression of tight junction polarity genes in human colon cancer

Abstract Tight junctions perform significant and multifactorial functions in cellular polarity maintenance and paracellular transport. A number of studies have found structural disruption of epithelial colon cells can significantly impact early tumorigenesis and progression. However, little is known about the direct contribution of polarity gene expression in human colon cancer development. We compared the expression of tight junction genes in colon cancer with normal control mucosa. Total RNA was extracted from fresh frozen tissue biopsies of six white male patients (N = 3 for early stage tumore, N = 3 for late stage tumor, and N = 2 for normal adjacent controls) and four unrelated normal colon mucosa from polyp-free individuals. We used the Qiagen RT2 Profiler PCR array to determine the expression of 84 genes in the tight junction pathway. Student's t test was used to compare the expression levels between different groups (control vs. early-stage tumor and late-stage tumor) using normalized gene expression data. Functional annotation clustering of statistically significant genes by group was conducted using DAVID. Significant (P&amp;lt;0.05) down regulation of claudin (CLDN5, CLDN6, CLDN7) expression was seen in both early and late-stage tumor compared with controls, all with fold change (FC)&amp;gt; 2; while CLDN1 (FC = 15) was only significantly upregulated (P = 0.0007) in early-stage tumor. Down regulation (FC&amp;gt;2) of polarity complex gene PARD6A (P&amp;lt;.001) and associated genes (JAM2, P&amp;lt;.001 and JAM3, P &amp;lt;.001) were present in both early and late-stage tumors along with associated down-regulation of tumor suppressor PTEN (P&amp;lt;.0001). We found differential expression of tight junction genes in normal versus colon tumor. Down regulation of polarity genes is likely to affect apico-basal polarity and promote random non-coordinated migration which can lead to disruption of epithelial structure and to carcinogenic tissue infiltration. Further larger studies are warranted to investigate the role of tight junction proteins in the progression of human colon tumor. Citation Format: Kathryn E. Royse, Liang Chen, Jocelyn Uriostegui, Michael Ittmann, David Y. Graham, Hashem El-Serag, Li Jiao. Differential expression of tight junction polarity genes in human colon cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4591. doi:10.1158/1538-7445.AM2015-4591

Selection of reference genes for quantitative real-time PCR normalization in creeping bentgrass involved in four abiotic stresses.

This study identified stable reference genes for normalization of gene expression data in qRT-PCR analysis of leaf and root tissues in creeping bentgrass under four abiotic stresses. Examination of gene expression using quantitative real-time PCR (qRT-PCR) in plant responses to abiotic stresses can provide valuable information for stress-tolerance improvement. Selecting stable reference genes for qRT-PCR analysis is critically important. The objective of this study was to determine the stability of expression for eight candidate reference genes (ACT, EF1a, TUB, UPL7, GAPDH, PP2A, PEPKR1, and CACS) in two tissues (roots and leaves) of a perennial grass species under four abiotic stresses (salt, drought, cold, and heat) using four programs (GeNorm, NormFinder, BestKeeper, and RefFinder). The results showed that (1) the combinations of CACS and UPL7 or PP2A and ACT were stably expressed in salt-treated roots or leaves; (2) the combinations of GAPDH and CACS or PP2A and PEPKR1 were stable in roots and leaves under drought stress; (3) CACS and PP2A exhibited stable expression in cold-treated roots and the combination of EF1a and UPL7 was also stable in cold-treated leaves; and (4) CACS and PP2A were the two most stable reference genes in heat-stressed roots and UPL7 combined with GAPDH and PP2A was stably expressed in heat-stressed leaves. The qRT-PCR analysis of a target gene, AsSAP expression patterns in response to salinity and drought stress, confirmed the reliability of those selected and stable reference genes. Identification of stable reference genes in creeping bentgrass will improve assay accuracy for selecting stress-tolerance genes and identifying molecular mechanisms conferring stress tolerance in this species.

Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

Identification of stable reference genes in differentiating human pluripotent stem cells.

Reference genes, often referred to as housekeeping genes (HKGs), are frequently used to normalize gene expression data based on the assumption that they are expressed at a constant level in the cells. However, several studies have shown that there may be a large variability in the gene expression levels of HKGs in various cell types. In a previous study, employing human embryonic stem cells (hESCs) subjected to spontaneous differentiation, we observed that the expression of commonly used HKG varied to a degree that rendered them inappropriate to use as reference genes under those experimental settings. Here we present a substantially extended study of the HKG signature in human pluripotent stem cells (hPSC), including nine global gene expression datasets from both hESC and human induced pluripotent stem cells, obtained during directed differentiation toward endoderm-, mesoderm-, and ectoderm derivatives. Sets of stably expressed genes were compiled, and a handful of genes (e.g., EID2, ZNF324B, CAPN10, and RABEP2) were identified as generally applicable reference genes in hPSCs across all cell lines and experimental conditions. The stability in gene expression profiles was confirmed by reverse transcription quantitative PCR analysis. Taken together, the current results suggest that differentiating hPSCs have a distinct HKG signature, which in some aspects is different from somatic cell types, and underscore the necessity to validate the stability of reference genes under the actual experimental setup used. In addition, the novel putative HKGs identified in this study can preferentially be used for normalization of gene expression data obtained from differentiating hPSCs.

Quantification of expression of dehydrin isoforms in the desiccation tolerant plant Craterostigma plantagineum using specifically designed reference genes

Craterostigma plantagineum is a desiccation tolerant resurrection plant. Many genes are induced during desiccation. Dehydrins are a group of dehydration-induced genes present in all higher plants. The current study aims at classifying the most abundantly expressed dehydrin genes from vegetative tissues of C. plantagineum and quantifying their expression. To identify variations between dehydrin isoforms at different stages of desiccation and rehydration by RT-qPCR, the target mRNA requires an accurate and reliable normalization. Previously we reported that RNAs from leaves and roots of C. plantagineum are not degraded during desiccation and subsequent rehydration thus allowing the use of RT-qPCR to test the stability of reference genes. The expression stability of eight candidate reference genes was tested in leaves, roots and callus. These genes were ranked according to their stability of gene expression using GeNormPLUS and RefFinder. The most consistently expressed reference genes in each tissue were identified and used to normalize gene expression data. Dehydrin isoforms were divided in three groups based on the expression level during the desiccation process in three different tissues (leaves, roots and callus).

Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae)

BackgroundRecent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these studies used quantitative real-time PCR (qRT-PCR). Suitable reference genes are necessary to normalize gene expression data of qRT-PCR. However, a comprehensive study on the reference genes in H. armigera remains lacking. ResultsTwelve candidate reference genes of H. armigera were selected and evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD), were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. ConclusionThis study not only establishes an accurate method for normalizing qRT-PCR data in H. armigera but also serve as a reference for further study on gene transcription in H. armigera and other insects.

Effect of obesity and exercise on the expression of the novel myokines, Myonectin and Fibronectin type III domain containing 5.

Metabolic dysfunction in skeletal muscle is a major contributor to the development of type 2 diabetes. Endurance exercise training has long been established as an effective means to directly restore skeletal muscle glucose and lipid uptake and metabolism. However, in addition to the direct effects of skeletal muscle on glucose and lipids, there is renewed interest in the ability of skeletal muscle to coordinate metabolic activity of other tissues, such as adipose tissue and liver. The purpose of this study was to examine the effects of endurance exercise on the expression level of two novel muscle-derived secreted factors, or myokines, Myonectin and Fibronectin type III domain containing 5 (FNDC5), the precursor for Irisin.Methods. We performed immunoblot analysis and quantitative real-time PCR analysis of Myonectin and FNDC5 in the diaphragm muscles of obese Zucker rat (OZR) and lean Zucker rat (LZR) with 9 weeks of aerobic training on a motorized treadmill.Results. We show that myonectin gene expression is increased in the OZR model of obesity and decreases with exercise in both lean and obese Zucker rats. Conversely, myonectin protein concentration was elevated with exercise. Similarly, FNDC5 mRNA levels are significantly higher in the OZR, however exercise training had no effect on the expression level of FNDC5 in either the LZR or OZR. We did not observe any difference in muscle protein content of Irisin with obesity or exercise.Conclusion. Our data shows that exercise training does not increase either FNDC5 or myonectin gene expression, indicating that increased transcriptional regulation of these myokines is not induced by exercise. However, our data also indicates a yet to be explored disconnect between myonectin gene expression and protein content. Further, this report highlights the importance of verifying reference genes when completing gene expression analysis. We found that many commonly used reference genes varied significantly by obesity and/or exercise and would have skewed the results of this study if used to normalize gene expression data. The unstable reference genes include: beta-Actin, beta-2-microglobulin, Non-POU domain containing, octamer-binding, Peptidylprolyl isomerase H, 18S ribosomal RNA, TATA box binding protein and Transferrin receptor.

Identification of reference genes for gene expression studies during seed germination and seedling establishment in Ricinus communis L.

AbstractReverse transcription-quantitative polymerase chain reaction (RT-qPCR) is an important technology to analyse gene expression levels during plant development or in response to different treatments. An important requirement to measure gene expression levels accurately is a properly validated set of reference genes. In this context, we analysed the potential use of 17 candidate reference genes across a diverse set of samples, including several tissues, different stages and environmental conditions, encompassing seed germination and seedling growth in Ricinus communis L. These genes were tested by RT-qPCR and ranked according to the stability of their expression using two different approaches: GeNorm and NormFinder. GeNorm and Normfinder indicated that ACT, POB and PP2AA1 comprise the optimal combination for normalization of gene expression data in inter-tissue (heterogeneous sample panel) studies. We also describe the optimal combination of reference genes for a subset of root, endosperm and cotyledon samples. In general, the most stable genes suggested by GeNorm are very consistent with those indicated by NormFinder, which highlights the strength of the selection of reference genes in our study. We also validated the selected reference genes by normalizing the expression levels of three target genes involved in energy metabolism with the reference genes suggested by GeNorm and NormFinder. The approach used in this study to identify stably expressed genes, and thus potential reference genes, was applied successfully for R. communis and it provides important guidelines for RT-qPCR studies in seeds and seedlings for other species (especially in those cases where extensive microarray data are not available).

Normalization of a NAFLD gene expression signature

We read with great interest the article by Moylan et al.1 in which the authors demonstrate that a 64-gene profile reproducibly differentiated severe nonalcoholic fatty liver disease (NAFLD) from mild NAFLD, and that a 20-gene subset within this profile correlated with NAFLD severity, independent of other known factors impinging on NAFLD progression. The need for accurate risk stratification for NAFLD is urgent because the disease is epidemic, imposing a public health burden, and cirrhosis and/or hepatocellular carcinoma (HCC) may develop on an NAFLD background. The authors unraveled, using microarrays and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) in the livers of patients, a novel gene expression signature that independently correlated with NAFLD severity.1 Although these findings might help develop novel diagnostic tests and treatments that target NAFLD patients at greatest risk, there are some important aspects that need to be stressed. The choice of housekeeping (control) genes, whose expression is not susceptible to nutrients, is crucial to normalize results in gene expression studies involving liver tissue. Moylan et al. used ribosomal protein L35 (RPL35) as the only control gene for all analyses. Studies on the translatome (total proteins formed by mRNA translation) show tremendous fluctuations in polysome-associated RPL35 levels in the livers of obese versus chow-fed mice, and also between fasted and fed states.2 Gene expression of RPL35 is increased in HCC cell lines and tissues.3 Moylan et al. relied most likely on the fact that RPL35 levels did not vary significantly in the clinical samples analyzed. However, if the expression of a control gene is potentially heavily influenced by nutritional and proliferative status in the liver, that could pose a problem when defining a gene expression signature with clinical applications. There is now a strong consensus in the community on the validity of the “GeNorm” method, employing the geometric mean of multiple carefully selected housekeeping genes to achieve robust normalization of gene expression data.4, 5 It would be interesting to reassess the data obtained by Moylan et al. using three or more housekeeping genes for normalization. Without robust normalization strategies it will be hard to assess the prognostic power of gene expression signatures. Manlio Vinciguerra, Ph.D. University College London (UCL) Institute for Liver and Digestive Health UCL Medical School Royal Free Campus London, UK

Defining suitable reference genes for RT-qPCR analysis on human sertoli cells after 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposure.

Quantitative real-time RT-PCR (qPCR) has proven to be a valuable molecular technique to quantify gene expression. There are few studies in the literature that describe suitable reference genes to normalize gene expression data. Studies of transcriptionally disruptive toxins, like tetrachlorodibenzo-p-dioxin (TCDD), require careful consideration of reference genes. The present study was designed to validate potential reference genes in human Sertoli cells after exposure to TCDD. 32 candidate reference genes were analyzed to determine their applicability. geNorm and NormFinder softwares were used to obtain an estimation of the expression stability of the 32 genes and to identify the most suitable genes for qPCR data normalization.

Renal cells exposed to cadmium in vitro and in vivo: normalizing gene expression data.

Cadmium (Cd) is a toxic metal with a long half-life in biological systems. This half-life is partly as a result of metallothioneins (MTs), metal-binding proteins with a high affinity for Cd. The high retention properties of the kidneys reside in proximal tubular cells that possess transport mechanisms for Cd-MT uptake, ultimately leading to more Cd accumulation. Researchers have studied MT-metal interactions using various techniques including quantitative real-time PCR (qPCR), an efficient tool for quantifying gene expression. Often a poor choice of reference genes, which is represented by their instability and condition dependency, leads to inefficient normalization of gene expression data and misinterpretations. This study demonstrates the importance of an efficient normalization strategy in toxicological research. A selection of stable reference genes was proposed in order to acquire reliable and reproducible gene quantification under metal stress using MT expression as an example. Moreover, in vitro and in vivo setups were compared to identify the influence of toxicological compounds in function of the experimental design. This study shows that glyceraldehyde-3-phosphate dehydrogenase (Gapdh), tyrosine monooxygenase/tryptophan5-monooxygenase activation-protein, zeta polypeptide (Ywhaz) and beta-actin (Actb) are the most stable reference genes in a kidney proximal tubular cell line exposed to moderate and high Cd concentrations, applied as CdCl2 . A slightly different sequence in reference gene stability was found in renal cells isolated from rats in vivo exposed to Cd. It was further shown that three reference genes are required for efficient normalization in this experimental setup. This study demonstrates the importance of an efficient normalization strategy in toxicological research.