Selecting control genes for RT-QPCR using public microarray data

Selection of Reliable Reference Genes for Gene Expression Normalization in Sagittaria trifolia

Real-time quantitative PCR (RT-qPCR) is a method with high sensitivity and convenience that has been extensively used to analyze the expression level of target genes. A reference gene with a highly stable expression is required to ensure the accuracy of experimental results. However, the report on appropriate reference genes in arrowheads (Sagittaria trifolia) is still limited. In this study, eight candidate reference genes (ACT5, UBQ, GAPDH, CYP, NAC, IDH, SLEEPER and PLA) were selected. The candidate genes were employed in a RT-qPCR assay in different tissues at different developmental stages of the same tissue (including corm, leaf and leafstalk) in arrowheads. Five statistical algorithms, GeNorm, NormFinder, BestKeeper, delta cycle threshold (ΔCt) and RefFinder, were used to evaluate the stability of these genes' expressions in order to identify the appropriate reference genes. The results showed that UBQ was the optimum reference gene in leaf, leafstalk, root, stolon and corm, IDH exhibited the most stable expression during the expansion of corm, UBQ and PLA were the most stable reference genes in developmental stages of leaf and leafstalk, respectively. Finally, the reliability of reference genes was further confirmed by the normalization of PDS and EXP1 genes under different arrowhead tissues and developmental stages of corm, respectively. This study constitutes important guidance for the selection of reliable reference genes for analyzing the tissue- and developmental-stage-specific expression of genes in arrowheads.

Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies

BACKGROUND

As the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable.

METHODS

In this study, we evaluate the expression profiles of six classical housekeeping genes (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues (AT) of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the expression stability of all genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database to identify sex-unbiased housekeeping genes (suHKG) suitable for use as internal controls. We perform a novel computational strategy based on meta-analysis techniques to identify any sexual dimorphisms in mRNA expression stability in AT and to properly validate potential candidates.

RESULTS

Just above half of the considered studies informed properly about the sex of the human samples, however, not enough female mouse samples were found to be included in this analysis. We found differences in the HKG expression stability in humans between female and male samples, with females presenting greater instability. We propose a suHKG signature including experimentally validated classical HKG like PPIA and RPL19 and novel potential markers for human AT and discarding others like the extensively used 18S gene due to a sex-based variability display in adipose tissue. Orthologs have also been assayed and proposed for mouse WAT suHKG signature. All results generated during this study are readily available by accessing an open web resource ( https://bioinfo.cipf.es/metafun-HKG ) for consultation and reuse in further studies.

CONCLUSIONS

This sex-based research proves that certain classical housekeeping genes fail to function adequately as controls when analyzing human adipose tissue considering sex as a variable. We confirm RPL19 and PPIA suitability as sex-unbiased human and mouse housekeeping genes derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB.

iRGvalid: A Robust in silico Method for Optimal Reference Gene Validation

Background

Appropriate reference genes are critical to accurately quantifying relative gene expression in research and clinical applications. Numerous efforts have been made to select the most stable reference gene(s), but a consensus has yet to be achieved. In this report, we propose an in silico reference gene validation method, iRGvalid, that can be used as a universal tool to validate the reference genes recommended from different resources so as to identify the best ones without a need for any wet lab validation tests.

Methods

iRGvalid takes advantage of high throughput gene expression data and is built on a double-normalization strategy. First, the expression level of each individual gene is normalized against the total gene expression level of each sample, followed by a target gene normalization to the candidate reference gene(s). Linear regression analysis is then performed between the pre- and post- normalized target gene across the whole sample set to evaluate the stability of the reference gene(s), which is positively associated with the Pearson correlation coefficient, Rt. The higher the Rt value, the more stable the reference gene. We applied iRGvalid to 14 candidate reference genes to validate and identify the most stable reference genes in four cancer types: lung adenocarcinoma, breast cancer, colon adenocarcinoma, and nasopharyngeal cancer. The stability of the reference gene is evaluated both individually and in groups of all possible combinations.

Results

Highly stable reference genes resulted in high Rt values regardless of the target gene used. The highest stability was achieved with a specific combination of 3 to 6 reference genes. A few genes were among the best reference genes across the cancer types studied here.

Conclusion

iRGvalid provides an easy and robust method to validate and identify the most stable reference gene or genes from a pool of candidate reference genes. The inclusivity of large expression data sets as well as the direct comparison of candidate reference genes makes it possible to identify reference genes with universal quality. This method can be used in any other gene expression studies when large cohorts of expression data are available.

Expression analysis of genes related to cold tolerance in Dendroctonus valens

Pine beetles are well known in North America for their widespread devastation of pine forests. However, Dendroctonus valens LeConte is an important invasive forest pest in China also. Adults and larvae of this bark beetle mainly winter at the trunks and roots of Pinus tabuliformis and Pinus sylvestris; larvae, in particular, result in pine weakness or even death. Since the species was introduced from the United States to Shanxi in 1998, its distribution has spread northward. In 2017, it invaded a large area at the junction of Liaoning, Inner Mongolia and Hebei provinces, showing strong cold tolerance. To identify genes relevant to cold tolerance and the process of overwintering, we sequenced the transcriptomes of wintering and non-wintering adult and larval D. valens using the Illumina HiSeq platform. Differential expression analysis methods for other non-model organisms were used to compare transcript abundances in adults and larvae at two time periods, followed by the identification of functions and metabolic pathways related to genes associated with cold tolerance. We detected 4,387 and 6,091 differentially expressed genes (DEGs) between sampling dates in larvae and adults, respectively, and 1,140 common DEGs, including genes encoding protein phosphatase, very long-chain fatty acids protein, cytochrome P450, and putative leucine-rich repeat-containing proteins. In a Gene Ontology (GO) enrichment analysis, 1,140 genes were assigned to 44 terms, with significant enrichment for cellulase activity, hydrolase activity, and carbohydrate metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) classification and enrichment analyses showed that the lysosomal and purine metabolism pathways involved the most DEGs, the highly enriched terms included autophagy-animal, pentose and glucuronate interconversions and lysosomal processes. We identified 140 candidate genes associated with cold tolerance, including genes with established roles in this trait (e.g., genes encoding trehalose transporter, fructose-1,6-bisphosphatase, and trehalase). Our comparative transcriptome analysis of adult and larval D. valens in different conditions provides basic data for the discovery of key genes and molecular mechanisms underlying cold tolerance.

Identification and Validation of Reference Genes for Quantitative Gene Expression Analysis in Ophraella communa

Ophraella communa is an effective bio-control agent of the invasive common weed. By now, the reference genes in O. communa have not yet been screened and validated. The aim of this study was to screen for the most stable reference genes in different backgrounds, such as different developmental stages, sexes, tissues, and male reproductive system with different body sizes. We selected 12 common housekeeping genes involved in different biological processes, including GAPDH, ACT1, ACT2, ARF1, ARF4, SDH, βTUBC, RPL4, RPL19, RPS18, EF1α, and COX as the candidate reference genes. To analyze the stability of the candidate reference genes, we first used three dedicated algorithms, GeNorm, NormFinder, and BestKeeper, and further comprehensive ranking was provided by ReFinder. The results showed that RPL19 and RPL4 exhibited the least variation in different developmental stages/sexes and in male reproductive systems with different body sizes. COX proved to be most suitable for normalizing the gene expression levels in different tissues, and coincidentally, RPL19 was also found to be second in terms of stability in this study. To the best of our knowledge, this is the first study to identify suitable reference genes for analyzing gene expression in O. communa; thus, this study would lay the foundation for future research on the molecular physiology and biochemistry of O. communa and other insects.

Identification of stable genes in the corpus luteum of lactating Holstein cows in pregnancy and luteolysis: Implications for selection of reverse-transcription quantitative PCR reference genes

In lactating dairy cattle, the corpus luteum (CL) is a dynamic endocrine tissue vital for pregnancy maintenance, fertility, and cyclicity. Understanding processes underlying luteal physiology is therefore necessary to increase reproductive efficiency in cattle. A common technique for investigating luteal physiology is reverse-transcription quantitative PCR (RT-qPCR), a valuable tool for quantifying gene expression. However, reference-gene-based RT-qPCR quantification methods require utilization of stably expressed genes to accurately assess mRNA expression. Historically, selection of reference genes in cattle has relied on subjective selection of a small pool of reference genes, many of which may have significant expression variation among different tissues or physiologic states. This is particularly concerning in dynamic tissues such as the CL, with its capacity for rapid physiologic changes during luteolysis, and likely in the less characterized period of CL maintenance during pregnancy. Thus, there is a clear need to identify reference genes well suited for the bovine CL over a wide range of physiological states. Whole-transcriptome RNA sequencing stands as an effective method to identify new reference genes by enabling the assessment of the expression profile of the entire pool of mRNA transcripts. We report the identification of 13 novel putative reference genes using RNA sequencing in the bovine CL throughout early pregnancy and luteolysis: RPL4, UQCRFS1, COX4I1, RPS4X, SSR3, CST3, ZNF266, CDC42, CD63, HIF1A, YWHAE, EIF3E, and PPIB. Independent RT-qPCR analyses were conducted confirming expression stability in another set of CL tissues from pregnancy and regression, with analyses performed for 3 groups of samples: (1) all samples, (2) samples from pregnancy alone, and (3) samples throughout the process of CL regression. Seven genes were found to be more stable in all states than 2 traditional reference genes (ACTB and GAPDH): RPS4X, COX4I1, PPIB, SSR3, RPL4, YWHAE, and CDC42. When CL tissues from pregnant animals alone were analyzed, CST3, HIF1A, and CD63 were also identified as more stable than ACTB and GAPDH. Identification of these new reference genes will aid in accurate normalization of RT-qPCR results, contributing to proper interpretation of gene expression relevant to luteal physiology. Furthermore, our analysis sheds light on the effects of luteolysis and pregnancy on the stability of gene expression in the bovine CL.

Selection of reference genes for tissue/organ samples of adults of Eucryptorrhynchus scrobiculatus

Eucryptorrhynchus scrobiculatus is an important wood-boring pest of Ailanthus altissima in China, where it causes a large number of these trees to weaken or even die. To identify genes related to economic traits or specific cellular processes in E. scrobiculatus, gene expression in multiple tissue/organ samples is commonly surveyed, and reference genes are required in this process as a control for normalization. In the present study, 18 candidate reference genes from E. scrobiculatus were identified, and the expression levels of these reference genes were estimated through quantitative real-time PCR. Differences in expression levels were analyzed with four algorithms (geNorm, NormFinder, BestKeeper and delta Ct) and comprehensively with RefFinder. With the most stable levels of expression in different tissues, RPL13, RPS3 and RPL36 were determined to be suitable for use as candidate reference genes. Moreover, the expression profile of one target gene (glycoside hydrolase family 45, GH45) confirmed the reliability of the selected candidate reference genes. This study provides the first set of suitable candidate reference genes for gene expression studies in E. scrobiculatus, and the findings will facilitate subsequent transcriptomics and functional gene research on this pest.

Selection of suitable reference genes for core clock gene expression analysis by real-time qPCR in rat ovary granulosa cells

Selection of a suitable endogenous reference gene is essential for investigating expression of clock genes Bmal1, Clock, Pers, Crys, Rev-erbα/β, and RORα/β/γ involved in the circadian system. In this study, we treated rat ovary granulosa cells with dexamethasone to synchronize circadian oscillation in vitro and determined expression levels of Bmal1 and Per2 and six candidate reference genes (Actb, Beta actin; B2m, Beta-2-microglobulin; Ppia, Cyclophilin A; Gapdh, Glyceraldehyde-3-phosphate dehydrogenase; Hprt, Hypoxanthine guanine phosphoribosyl transferase and Tbp, TATA-box-binding protein) using quantitative real-time PCR. We then employed three software programs, GeNorm, NormFinder, and BestKeeper, to analyze the expression data for the selection of the best reference gene. According to GeNorm, Tbp and B2m were assessed as the most stable reference genes; Tbp and Hprt were best by NormFinder and BestKeeper, respectively. Thus, we recommend Tbp as the most suitable reference gene for studying clock genes expression in rat ovary granulosa cells in vitro.

Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization

Quantitative PCR (qPCR) remains the most widely used technique for gene expression evaluation. Obtaining reliable data using this method requires reference genes (RGs) with stable mRNA level under experimental conditions. This issue is especially crucial in cancer studies because each tumor has a unique molecular portrait. The Cancer Genome Atlas (TCGA) project provides RNA-Seq data for thousands of samples corresponding to dozens of cancers and presents the basis for assessment of the suitability of genes as reference ones for qPCR data normalization. Using TCGA RNA-Seq data and previously developed CrossHub tool, we evaluated mRNA level of 32 traditionally used RGs in 12 cancer types, including those of lung, breast, prostate, kidney, and colon. We developed an 11-component scoring system for the assessment of gene expression stability. Among the 32 genes, PUM1 was one of the most stably expressed in the majority of examined cancers, whereas GAPDH, which is widely used as a RG, showed significant mRNA level alterations in more than a half of cases. For each of 12 cancer types, we suggested a pair of genes that are the most suitable for use as reference ones. These genes are characterized by high expression stability and absence of correlation between their mRNA levels. Next, the scoring system was expanded with several features of a gene: mutation rate, number of transcript isoforms and pseudogenes, participation in cancer-related processes on the basis of Gene Ontology, and mentions in PubMed-indexed articles. All the genes covered by RNA-Seq data in TCGA were analyzed using the expanded scoring system that allowed us to reveal novel promising RGs for each examined cancer type and identify several "universal" pan-cancer RG candidates, including SF3A1, CIAO1, and SFRS4. The choice of RGs is the basis for precise gene expression evaluation by qPCR. Here, we suggested optimal pairs of traditionally used RGs for 12 cancer types and identified novel promising RGs that demonstrate high expression stability and other features of reliable and convenient RGs (high expression level, low mutation rate, non-involvement in cancer-related processes, single transcript isoform, and absence of pseudogenes).

What's the norm in normalization? A frightening note on the use of RT-qPCR in the livestock science

Reverse-Transcription quantitative PCR (RT-qPCR) provides a valuable tool to study gene expression with exquisite sensitivity. To retain its inferential power, user-introduced technical variability must be reduced and accounted for. Selecting a set of stably expressed internal control genes (ICG), validated for each experimental condition/sample set, is widely accepted as a reliable way to normalize RT-qPCR data and account for said variability. Despite significant efforts in establishing standardized and resource-efficient normalization approaches, numerous recent reports have underlined deficiencies in the state of RT-qPCR normalization. Livestock science has benefitted tremendously from the use of RT-qPCR; however, the issue of lack of proper normalization likely affects this discipline as well. We thus decided to determine whether this is true, and to which extent. We conducted an in-depth analysis of all (225) RT-qPCR articles published in the six most prominent livestock journals in the field from 2013 to 2017. A quantitative scale was constructed, and values were assigned to each article based on the number of ICG used, the use of a publicly available algorithm to assess the reliability of ICG, and the reporting of pertinent information related to ICG (ranges from 0 = total noncompliance - to 100 = total compliance). Out of the surveyed group, only 10.7% of the publications obtained a score of 100, while the largest group (n = 158) was represented by articles that scored 0. Subdividing articles based on whether an algorithm to validate ICG was used (YAL) or not (NAL) revealed the use of a larger number of ICG to normalize RT-qPCR in the YAL group compared to NAL (1.4-fold more, 95% C.I.: 1.11–1.84) and was closer to the “gold standard” of three ICG. Using an algorithm also increased the diversity of ICG and significantly reduced the use of RNA18S, whose suitability as ICG has been thoroughly debated. These remarkably low normalization standards are likely to generate questionable results that can severely hinder the advance of transcriptomic studies in livestock science and related fields.

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Subpar normalization of reverse transcription qPCR was reported for the five major livestock journals over the period 2013-2017

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The use of algorithms for validation led to a greater number of ICG used, and greater variety of ICGs

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The issue could be solved by editors by enforcing the use of the standardized MIQE guidelines for RT-qPCR

A minimal set of internal control genes for gene expression studies in head and neck squamous cell carcinoma

Selection of the right reference gene(s) is crucial in the analysis and interpretation of gene expression data. The aim of the present study was to discover and validate a minimal set of internal control genes in head and neck tumor studies. We analyzed data from multiple sources (in house whole-genome gene expression microarrays, previously published quantitative real-time PCR (qPCR) data and RNA-seq data from TCGA) to come up with a list of 18 genes (discovery set) that had the lowest variance, a high level of expression across tumors, and their matched normal samples. The genes in the discovery set were ranked using four different algorithms (BestKeeper, geNorm, NormFinder, and comparative delta Ct) and a web-based comparative tool, RefFinder, for their stability and variance in expression across tissues. Finally, we validated their expression using qPCR in an additional set of tumor:matched normal samples that resulted in five genes (RPL30, RPL27, PSMC5, MTCH1, and OAZ1), out of which RPL30 and RPL27 were most stable and were abundantly expressed across the tissues. Our data suggest that RPL30 or RPL27 in combination with either PSMC5 or MTCH1 or OAZ1 can be used as a minimal set of control genes in head and neck tumor gene expression studies.

The Pathway Coexpression Network: Revealing pathway relationships

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/.

Genes do not function alone, but interact within pathways to carry out specific biological processes. Pathways, in turn, interact at a higher level to affect major cellular activities such as motility, growth and development. We present a pathway coexpression network (PCxN) that systematically maps and quantifies these high-level interactions and establishes a unifying reference for pathway relationships. The method uses 3,207 human microarrays from 72 normal human tissues and 1,330 of the most well established pathway annotations to describe global relationships between pathways. PCxN accounts for shared genes to estimate correlations between pathways with related functions rather than with redundant pathway definitions. PCxN can be used to discover and explore pathways correlated with a pathway of interest. We applied PCxN to identify key processes related to Alzheimer’s disease (AD), interpreting a mixed genetic association and experimental derived set of disease genes in the context of gene co-expression. We expand the known relationships between pathways identified by gene set enrichment analysis in brain tissues affected with AD. PCxN provides a high-level overview of pathway relationships. PCxN is available as a webtool at http://pcxn.org/, and as a Bioconductor package at http://bioconductor.org/packages/pcxn/.

Automated identification of reference genes based on RNA-seq data

Background

Gene expression analyses demand appropriate reference genes (RGs) for normalization, in order to obtain reliable assessments. Ideally, RG expression levels should remain constant in all cells, tissues or experimental conditions under study. Housekeeping genes traditionally fulfilled this requirement, but they have been reported to be less invariant than expected; therefore, RGs should be tested and validated for every particular situation. Microarray data have been used to propose new RGs, but only a limited set of model species and conditions are available; on the contrary, RNA-seq experiments are more and more frequent and constitute a new source of candidate RGs.

Results

An automated workflow based on mapped NGS reads has been constructed to obtain highly and invariantly expressed RGs based on a normalized expression in reads per mapped million and the coefficient of variation. This workflow has been tested with Roche/454 reads from reproductive tissues of olive tree (Olea europaea L.), as well as with Illumina paired-end reads from two different accessions of Arabidopsis thaliana and three different human cancers (prostate, small-cell cancer lung and lung adenocarcinoma). Candidate RGs have been proposed for each species and many of them have been previously reported as RGs in literature. Experimental validation of significant RGs in olive tree is provided to support the algorithm.

Conclusion

Regardless sequencing technology, number of replicates, and library sizes, when RNA-seq experiments are designed and performed, the same datasets can be analyzed with our workflow to extract suitable RGs for subsequent PCR validation. Moreover, different subset of experimental conditions can provide different suitable RGs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12938-017-0356-5) contains supplementary material, which is available to authorized users.

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium-high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross- and within-tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra- and inter-sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross-tissue width of expression for more than 31,000 transcripts. The present study conducted a meta-analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue- and organ-specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative, quantitative portrait of the relative, typical gene-expression profile in the form of searchable database tables.

Adrenodemedullation activates the Ca2+-dependent proteolysis in soleus muscles from rats exposed to cold

Previous studies have shown that catecholamines in vivo and in vitro inhibit the activity of Ca2+-dependent proteolysis in skeletal muscles under basal conditions. In the present study we sought to investigate the role of catecholamines in regulating the Ca2+-dependent proteolysis in soleus and extensor digitorum longus (EDL) muscles from rats acutely exposed to cold. Overall proteolysis, the activity of proteolytic systems, protein levels and gene expression of different components of the calpain system were investigated in rats submitted to adrenodemedullation (ADMX) and exposed to cold for 24 h. ADMX drastically reduced plasma epinephrine and promoted an additional increase in the overall proteolysis, which was already increased by cold exposure. The rise in the rate of protein degradation in soleus muscles from adrenodemedullated cold-exposed rats was caused by the high activity of the Ca2+-dependent proteolysis, which was associated with the generation of a 145-kDa cleaved α-fodrin fragment, a typical calpain substrate, and lower protein levels and mRNA expression of calpastatin, the endogenous calpain inhibitor. Unlike that observed for soleus muscles, the cold-induced muscle proteolysis in EDL was not affected by ADMX. In isolated soleus muscle, clenbuterol, a selective β2-adrenoceptor agonist, reduced the basal Ca2+-dependent proteolysis and completely abolished the activation of this pathway by the cholinergic agonist carbachol. These data suggest that catecholamines released from the adrenal medulla inhibit cold-induced protein breakdown in soleus, and this antiproteolytic effect on the Ca2+-dependent proteolytic system is apparently mediated through expression of calpastatin, which leads to suppression of calpain activation.

NEW & NOTEWORTHY Although many effects of the sympathetic nervous system on muscle physiology are known, the role of catecholamines in skeletal muscle protein metabolism has been scarcely studied. We suggest that catecholamines released from adrenal medulla may be of particular importance for restraining the activation of the Ca2+-dependent proteolysis in soleus muscles during acute cold exposure. This finding helps us to understand the adaptive changes that occur in skeletal muscle protein metabolism during cold stress.

MATE2 Expression Is Associated with Cancer Cell Response to Metformin

BACKGROUND

There is great interest in repurposing the commonly prescribed anti-diabetic drug metformin for cancer therapy. Intracellular uptake and retention of metformin is affected by the expression of organic cation transporters (OCT) 1-3 and by multidrug and toxic compound extrusion (MATE) 1-2. Inside cells, metformin inhibits mitochondrial function, which leads to reduced oxygen consumption and inhibition of proliferation. Reduced oxygen consumption can lead to improved tumor oxygenation and radiation response.

PURPOSE

Here we sought to determine if there is an association between the effects of metformin on inhibiting oxygen consumption, proliferation and expression of OCTs and MATEs in a panel of 19 cancer cell lines.

RESULTS

There was relatively large variability in the anti-proliferative response of different cell lines to metformin, with a subset of cell lines being very resistant. In contrast, all cell lines demonstrated sensitivity to the inhibition of oxygen consumption by metformin, with relatively small variation. The expression of OCT1 correlated with expression of both OCT2 and OCT3. OCT1 and OCT2 were relatively uniformly expressed, whereas expression of OCT3, MATE1 and MATE2 showed substantial variation across lines. There were statistically significant associations between resistance to inhibition of proliferation and MATE2 expression, as well as between sensitivity to inhibition of oxygen consumption and OCT3 expression. One cell line (LNCaP) with high OCT3 and low MATE2 expression in concert, had substantially higher intracellular metformin concentration than other cell lines, and was exquisitely sensitive to both anti-proliferative and anti-respiratory effects. In all other cell lines, the concentration of metformin required to inhibit oxygen consumption acutely in vitro was substantially higher than that achieved in the plasma of diabetic patients. However, administering anti-diabetic doses of metformin to tumor-bearing mice resulted in intratumoral accumulation of metformin and reduced hypoxic tumor fractions.

CONCLUSIONS

All cancer cells are susceptible to inhibition of oxygen consumption by metformin, which results in reduced hypoxic tumor fractions beneficial for the response to radiotherapy. High MATE2 expression may result in resistance to the anti-proliferative effect of metformin and should be considered as a negative predictive biomarker in clinical trials.

Analysis of Gene Expression in an Inbred Line of Soft-Shell Clams (Mya arenaria) Displaying Growth Heterosis: Regulation of Structural Genes and the NOD2 Pathway

Mya arenaria is a bivalve mollusk of commercial and economic importance, currently impacted by ocean warming, acidification, and invasive species. In order to inform studies on the growth of M. arenaria, we selected and inbred a population of soft-shell clams for a fast-growth phenotype. This population displayed significantly faster growth (p < 0.0001), as measured by 35.4% greater shell size. To assess the biological basis of this growth heterosis, we characterized the complete transcriptomes of six individuals and identified differentially expressed genes by RNAseq. Pathways differentially expressed included structural gene pathways. Also differentially expressed was the nucleotide-binding oligomerization domain 2 (NOD2) receptor pathway that contributes to determination of growth, immunity, apoptosis, and proliferation. NOD2 pathway members that were upregulated included a subset of isoforms of RIPK2 (mean 3.3-fold increase in expression), ERK/MAPK14 (3.8-fold), JNK/MAPK8 (4.1-fold), and NFκB (4.08-fold). These transcriptomes will be useful resources for both the aquaculture community and researchers with an interest in mollusks and growth heterosis.

Identification and Validation of Reference Genes for RT-qPCR Studies of Hypoxia in Squamous Cervical Cancer Patients

Hypoxia is an adverse factor in cervical cancer, and hypoxia-related gene expression could be a powerful biomarker for identifying the aggressive hypoxic tumors. Reverse transcription quantitative PCR (RT-qPCR) is a valuable method for gene expression studies, but suitable reference genes for data normalization that are independent of hypoxia status and clinical parameters of cervical tumors are lacking. In the present work, we aimed to identify reference genes for RT-qPCR studies of hypoxia in squamous cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia in cervical cancer, i.e. genes regulated by hypoxia in eight cervical cancer cell lines or correlating with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter A_Brix in 42 patients, were excluded. Among the 182 genes, nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, were selected for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the optimal set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (A_Brix) and clinical parameters. The suitability of the three reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalization, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n = 74) and A_Brix (P<0.05, n = 32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in squamous cervical cancer samples by RT-qPCR. Moreover, STC2 is a promising prognostic hypoxia biomarker in cervical cancer.

Discovery of a 29-gene panel in peripheral blood mononuclear cells for the detection of colorectal cancer and adenomas using high throughput real-time PCR

Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

Identification of stably expressed reference genes for RT-qPCR data normalization in defined localizations of cyclic bovine ovaries

Ovaries are highly complex organs displaying morphological, molecular and functional differences between their cortical zona parenchymatosa and medullary zona vasculosa, and also between the different cyclic luteal stages. Objective of the present study was to validate expression stability of twelve putative reference genes (RGs) in bovine ovaries, considering the intrinsic heterogeneity of bovine ovarian tissue with regard to different luteal stages and intra-ovarian localizations. The focus was on identifying RGs, which are suitable to normalize RT-qPCR results of ovaries collected from clinical healthy cattle, irrespective of localization and the hormonal stage. Expression profiles of twelve potential reference genes (GAPDH, ACTB, YWHAZ, HPRT1, SDHA, UBA52, POLR2C, RPS9, ACTG2, H3F3B, RPS18 and RPL19) were analysed. Evaluation of gene expression differences was performed using genorm, normfinder, and bestkeeper software. The most stably expressed genes according to genorm, normfinder and bestkeeper approaches contained the candidates H3F3B, RPS9, YWHAZ, RPS18, POLR2C and UBA52. Of this group, the genes YWHAZ, H3F3B and RPS9 could be recommended as best-suited RGs for normalization purposes on healthy bovine ovaries irrespective of the luteal stage or intra-ovarian localization.

Identification of novel reference genes based on MeSH categories

Transcriptome experiments are performed to assess protein abundance through mRNA expression analysis. Expression levels of genes vary depending on the experimental conditions and the cell response. Transcriptome data must be diverse and yet comparable in reference to stably expressed genes, even if they are generated from different experiments on the same biological context from various laboratories. In this study, expression patterns of 9090 microarray samples grouped into 381 NCBI-GEO datasets were investigated to identify novel candidate reference genes using randomizations and Receiver Operating Characteristic (ROC) curves. The analysis demonstrated that cell type specific reference gene sets display less variability than a united set for all tissues. Therefore, constitutively and stably expressed, origin specific novel reference gene sets were identified based on their coefficient of variation and percentage of occurrence in all GEO datasets, which were classified using Medical Subject Headings (MeSH). A large number of MeSH grouped reference gene lists are presented as novel tissue specific reference gene lists. The most commonly observed 17 genes in these sets were compared for their expression in 8 hepatocellular, 5 breast and 3 colon carcinoma cells by RT-qPCR to verify tissue specificity. Indeed, commonly used housekeeping genes GAPDH, Actin and EEF2 had tissue specific variations, whereas several ribosomal genes were among the most stably expressed genes in vitro. Our results confirm that two or more reference genes should be used in combination for differential expression analysis of large-scale data obtained from microarray or next generation sequencing studies. Therefore context dependent reference gene sets, as presented in this study, are required for normalization of expression data from diverse technological backgrounds.

Identification of genes with consistent methylation levels across different human tissues

DNA methylation plays an important role in regulating cell growth and disease development. Methylation profiles are examined by bisulfite conversion; however, the lack of markers for bisulfite conversion efficiency and appropriate internal control genes remains a major challenge. To address these issues, we utilized two bioinformatics approaches, coefficients of variances and resampling tests, to identify probes showing stable methylation levels from several independent microarray datasets. Mass spectrometry validated the consistently high methylation levels of the five probes (N4BP2, EGFL8, CTRB1, TSPAN3, and ZNF690) in 13 human tissue types from 24 cell lines. Linear associations between detected methylation levels and methyl concentrations of DNA samples were further demonstrated in three genes (N4BP2, EGFL8, and CTRB1). To summarize, we identified five genes which may serve as internal controls for methylation studies by analyzing large-scale microarray data, and three of them can be used as markers for evaluating the efficiency of bisulfite conversion.

RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells

Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. This list is enriched for components of the proteasome (ex. PSMA1) and spliceosome (ex. SF3B2), and also includes the translation initiation factor EIF4H, and many heterogeneous nuclear ribonucleoprotein genes (ex. HNRNPL). We have validated the consistency of our new control genes in 1933 cancer and normal tissues using publically available RNA-seq data, and their usefulness in qRT-PCR analysis is clearly demonstrated.

Effect of short-term cold exposure on skeletal muscle protein breakdown in rats

Although it is well established that carbohydrate and lipid metabolism are profoundly altered by cold stress, the effects of short-term cold exposure on protein metabolism in skeletal muscle are still poorly understood. Because cold acclimation requires that an organism adjust its metabolic flux, and muscle amino acids may be an important energy source for heat production, we hypothesize that muscle proteolysis is increased and protein synthesis is decreased under such a stress condition. Herein, cold exposure for 24 h decreased rates of protein synthesis and increased overall proteolysis in both soleus and extensor digitorum longus (EDL) muscles, but it did not affect muscle weight. An increase in proteolysis was accompanied by hyperactivity of the ubiquitin-proteasome system (UPS) in both soleus and EDL, and Ca(2+)-dependent proteolysis in EDL. Furthermore, muscles of rats exposed to cold showed increased mRNA and protein levels of atrogin-1 and muscle RING finger enzyme-1 (MuRF1). Additionally, cold stress reduced phosphorylation of Akt and Forkhead box class O1 (FoxO1), a well-known effect that increases FoxO translocation to the nucleus and leads to activation of proteolysis. Plasma insulin levels were lower, whereas catecholamines, corticosterone, and thyroid hormones were higher in cold-exposed rats compared with control rats. The present data provide the first direct evidence that short-term cold exposure for 24 h decreases rates of protein synthesis and increases the UPS and Ca(2+)-dependent proteolytic processes, and increases expression of atrogin-1 and MuRF1 in skeletal muscles of young rats. The activation of atrophy induced by acute cold stress seems to be mediated at least in part through the inactivation of Akt/FoxO signaling and activation of AMP-activated protein kinase.

High-throughput identification of reference genes for research and clinical RT-qPCR analysis of breast cancer samples

BACKGROUND

Quantification and normalization of RT-qPCR data critically depends on the expression of so called reference genes. Our goal was to develop a strategy for the selection of reference genes that utilizes microarray data analysis and combines known approaches for gene stability evaluation and to select a set of appropriate reference genes for research and clinical analysis of breast samples with different receptor and cancer status using this strategy.

METHODS

A preliminary search of reference genes was based on high-throughput analysis of microarray datasets. The final selection and validation of the candidate genes were based on the RT-qPCR data analysis using several known methods for expression stability evaluation: comparative ∆Ct method, geNorm, NormFinder and Haller equivalence test.

RESULTS

A set of five reference genes was identified: ACTB, RPS23, HUWE1, EEF1A1 and SF3A1. The initial selection was based on the analysis of publically available well-annotated microarray datasets containing different breast cancers and normal breast epithelium from breast cancer patients and epithelium from cancer-free patients. The final selection and validation were performed using RT-qPCR data from 39 breast cancer biopsy samples. Three genes from the final set were identified by the means of microarray analysis and were novel in the context of breast cancer assay. We showed that the selected set of reference genes is more stable in comparison not only with individual genes, but also with a system of reference genes used in commercial OncotypeDX test.

CONCLUSION

A selection of reference genes for RT-qPCR can be efficiently performed by combining a preliminary search based on the high-throughput analysis of microarray datasets and final selection and validation based on the analysis of RT-qPCR data with a simultaneous examination of different expression stability measures. The identified set of reference genes proved to be less variable and thus potentially more efficient for research and clinical analysis of breast samples comparing to individual genes and the set of reference genes used in OncotypeDX assay.

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

Background

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population.

Results

An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H.

Conclusions

Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.

Single-cell analysis of circulating tumor cells identifies cumulative expression patterns of EMT-related genes in metastatic prostate cancer

BACKGROUND

Prostate tumors shed circulating tumor cells (CTCs) into the blood stream. Increased evidence shows that CTCs are often present in metastatic prostate cancer and can be alternative sources for disease profiling and prognostication. Here we postulate that CTCs expressing genes related to epithelial-mesenchymal transition (EMT) are strong predictors of metastatic prostate cancer.

METHODS

A microfiltration system was used to trap CTCs from peripheral blood based on size selection of large epithelial-like cells without CD45 leukocyte marker. These cells individually retrieved with a micromanipulator device were assessed for cell membrane physical properties using atomic force microscopy. Additionally, 38 CTCs from eight prostate cancer patients were used to determine expression profiles of 84 EMT-related and reference genes using a microfluidics-based PCR system.

RESULTS

Increased cell elasticity and membrane smoothness were found in CTCs compared to noncancerous cells, highlighting their potential invasiveness and mobility in the peripheral circulation. Despite heterogeneous expression patterns of individual CTCs, genes that promote mesenchymal transitioning into a more malignant state, including IGF1, IGF2, EGFR, FOXP3, and TGFB3, were commonly observed in these cells. An additional subset of EMT-related genes (e.g., PTPRN2, ALDH1, ESR2, and WNT5A) were expressed in CTCs of castration-resistant cancer, but less frequently in castration-sensitive cancer.

CONCLUSIONS

The study suggests that an incremental expression of EMT-related genes in CTCs is associated with metastatic castration-resistant cancer. Although CTCs represent a group of highly heterogeneous cells, their unique EMT-related gene signatures provide a new opportunity for personalized treatments with targeted inhibitors in advanced prostate cancer patients.

Selecting housekeeping genes as references for the normalization of quantitative PCR data in breast cancer

OBJECTIVE

The common reference genes of choice in relative gene expression studies based on quantitative real time polymerase chain reaction, ACTB and B2M, were shown to be regulated differently in respect to tissue type. In this study, the stability of the selected housekeeping genes for normalizing the qPCR data were identified in the tumor and its adjacent tissues in invasive breast cancer, and the variability of their levels according to the stages and the histopathologic subtypes was analyzed.

METHODS

Four housekeeping genes: PUM1, RPL13A, B2M, and ACTB were analyzed in 99 surgically excised tissue specimens (50 tumor, 45 tumor adjacent and 4 normal breast tissues). Three of the most common softwares (GeNorm, NormFinder, and BestKeeper) were used for calculation purposes.

RESULTS

When all of the tissue samples were included in analyses, PUM1 was the most stable gene according to calculations made with both NormFinder and BestKeeper; while PUM1/RPL13A combination was the most stable by GeNorm software. The PUM1 gene was also identified as the most stable gene among the four in all sample groups (in both Estrogen Receptor positive and Estrogen Receptor negative subgroups of invasive breast carcinoma and in normal breast tissue) according to calculations made using the NormFinder software.

CONCLUSION

While suggesting PUM1 is one of the most stable single gene and the PUM1/RPL13A pair as one of the best housekeeping genes for the normalization of expression studies in invasive breast tumor studies, it will be more practical to evaluate stability once more and decide upon the reference gene accordingly within the sample group itself.

Identification of condition-specific reference genes from microarray data for locusts exposed to hypobaric hypoxia

Real-time quantitative polymerase chain reaction (qPCR) is a routine and robust approach for measuring gene expression. The stability of reference genes in qPCR is crucial for the accurate quantification of gene expression. To provide reliable reference genes for studying the transcriptional responses of locust muscles to hypobaric hypoxia, we first examined the gene expression stability of the frequently used housekeeping genes 18S, GAPDH, and β-actin. However, the expression of these three housekeeping genes was influenced by hypobaric hypoxia. Consequently, we identified five novel candidate reference genes from the locust microarray data. The gene expression stability of the five candidates, together with the three classical housekeeping genes, were evaluated using two distinct algorithms implemented in geNorm and NormFinder. GeNorm identified Ach (acetyl-CoA hydrolase) and Pgp (phosphoglycolate phosphatase-like) as the most stable genes and NormFinder further distinguished Ach as the most stable one. The validity of Ach as a reference gene was confirmed through comparison with 18S. This study exemplifies the necessity of validating reference genes before their application and the feasibility of identifying condition-specific reference genes from large-scale gene expression data.

Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines

Background

To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.

Methodology/Principal Findings

We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.

Conclusions/Significance

For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery.

Effects of rehydration nutrients on H2S metabolism and formation of volatile sulfur compounds by the wine yeast VL3

In winemaking, nutrient supplementation is a common practice for optimising fermentation and producing quality wine. Nutritionally suboptimal grape juices are often enriched with nutrients in order to manipulate the production of yeast aroma compounds. Nutrients are also added to active dry yeast (ADY) rehydration media to enhance subsequent fermentation performance. In this study we demonstrate that nutrient supplementation at rehydration also has a significant effect on the formation of volatile sulfur compounds during wine fermentations. The concentration of the 'fruity' aroma compounds, the polyfunctional thiols 3-mercaptohexan-1-ol (3MH) and 3-mercaptohexyl acetate (3MHA), was increased while the concentration of the 'rotten egg' aroma compound, hydrogen sulfide (H2S), was decreased. Nutrient supplementation of the rehydration media also changed the kinetics of H2S production during fermentation by advancing onset of H2S production. Microarray analysis revealed that this was not due to expression changes within the sulfate assimilation pathway, which is known to be a major contributor to H2S production. To gain insight into possible mechanisms responsible for this effect, a component of the rehydration nutrient mix, the tri-peptide glutathione (GSH) was added at rehydration and studied for its subsequent effects on H2S formation. GSH was found to be taken up during rehydration and to act as a source for H2S during the following fermentation. These findings represent a potential approach for managing sulfur aroma production through the use of rehydration nutrients.

Mll5 is required for normal spermatogenesis

Background

Mll5 is currently a member of the Mll family of SET domain histone methyltransferase proteins but studies have also showed that it could be part of the SET3 branch of proteins. Recently, constitutive knock out animal studies have shown that Mll5 is required for proper haematopoietic stem cell differentiation, and loss of Mll5 results in synthetic lethality for genome de-methylation. Mll5 deficient male mice are infertile and here we analyse the consequences of Mll5 deficiency for spermatogenesis.

Methodology/Principal Findings

Mll5 deficient male mice, but not female mice, are infertile. Here we show using RNA in-situ hybridization that Mll5 is expressed in the germ cells of the testes of wild type mice. Consistent with the expression of Mll5, we demonstrate by electron microscopy, video microscopy and in vitro fertilisation techniques that Mll5 deficient mice have defects in terminal maturation and packaging of sperm. The defects seen include detachment of the acrosomal cap and impaired excess cytoplasm removal. Functional tests of sperm motility show a lack of progressive motility of spermatozoa from Mll5 deficient animals. None of these defects could be rescued by in vitro fertilization. Using microarray analysis we show that transcripts implicated in spermatogenesis are dysregulated.

Conclusions/Significance

Our data demonstrate a clear role of Mll5 in mammalian spermatogenesis at the level of terminal differentiation providing further support for its classification in the SET3 branch of proteins. Moreover, this study identifies Tlk2, Utx, Gpr64, Sult4a1, Rap2ip, Vstm2 and HoxA10 as possible Mll5 targets that together may account for the observed spermatozoa maturation defects.

Cardiac proteasome activity in muscle ring finger-1 null mice at rest and following synthetic glucocorticoid treatment

Muscle ring finger-1 (MuRF1) is a muscle-specific E3 ubiquitin ligase that has been implicated in the regulation of cardiac mass through its control of the ubiquitin proteasome system. While it has been suggested that MuRF1 is required for cardiac atrophy, a resting cardiac phenotype has not been reported in mice with a null deletion [knockout (KO)] of MuRF1. Here, we report that MuRF1 KO mice have significantly larger hearts than age-matched wild-type (WT) littermates at ≥ 6 mo of age and that loss of cardiac mass can occur in the absence of MuRF1. The objective of this study was to determine whether changes in proteasome activity were responsible for the cardiac phenotypes observed in MuRF1 KO mice. Cardiac function, architecture, and proteasome activity were analyzed at rest and following 28 days of dexamethasone (Dex) treatment in 6-mo-old WT and MuRF1 KO mice. Echocardiography demonstrated normal cardiac function in the enlarged hearts in MURF1 KO mice. At rest, heart mass and cardiomyocyte diameter were significantly greater in MuRF1 KO than in WT mice. The increase in cardiac size in MuRF1 KO mice was related to a decrease in proteasome activity and an increase in Akt signaling relative to WT mice. Dex treatment induced a significant loss of cardiac mass in MuRF1 KO, but not WT, mice. Furthermore, Dex treatment resulted in an increase in proteasome activity in KO, but a decrease in WT, mice. In contrast, Akt/mammalian target of rapamycin signaling decreased in MuRF1 KO mice and increased in WT mice in response to Dex treatment. These findings demonstrate that MuRF1 plays an important role in regulating cardiac size through alterations in protein turnover and that MuRF1 is not required to induce cardiac atrophy.

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization

Background

RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts.

Results

Using the Genevestigator database of normalized and well-annotated microarray experiments, we describe the expression stability characteristics of the transciptomes of several organisms. The results show that a) no genes are universally stable, b) most commonly used reference genes yield very high transcript abundances as compared to the entire transcriptome, and c) for each biological context a subset of stable genes exists that has smaller variance than commonly used reference genes or genes that were selected for their stability across all conditions.

Conclusion

We therefore propose the normalization of RT-qPCR data using reference genes that are specifically chosen for the conditions under study. RefGenes is a community tool developed for that purpose. Validation RT-qPCR experiments across several organisms showed that the candidates proposed by RefGenes generally outperformed commonly used reference genes. RefGenes is available within Genevestigator at http://www.genevestigator.com.

Identification of reference genes across physiological states for qRT-PCR through microarray meta-analysis

Background

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.

Methodology/Principal Findings

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.

Conclusions/Significance

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.

A pipeline to determine RT-QPCR control genes for evolutionary studies: application to primate gene expression across multiple tissues

Because many species-specific phenotypic differences are assumed to be caused by differential regulation of gene expression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR) is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle), EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of gene expression among species.

Determination of reference genes for circadian studies in different tissues and mouse strains

BACKGROUND

Circadian rhythms have a profound effect on human health. Their disruption can lead to serious pathologies, such as cancer and obesity. Gene expression studies in these pathologies are often studied in different mouse strains by quantitative real time polymerase chain reaction (qPCR). Selection of reference genes is a crucial step of qPCR experiments. Recent studies show that reference gene stability can vary between species and tissues, but none has taken circadian experiments into consideration.

RESULTS

In the present study the expression of ten candidate reference genes (Actb, Eif2a, Gapdh, Hmbs, Hprt1, Ppib, Rn18s, Rplp0, Tbcc and Utp6c) was measured in 131 liver and 97 adrenal gland samples taken from three mouse strains (C57BL/6JOlaHsd, 129Pas plus C57BL/6J and Crem KO on 129Pas plus C57BL/6J background) every 4 h in a 24 h period. Expression stability was evaluated by geNorm and NormFinder programs. Differences in ranking of the most stable reference genes were observed both between individual mouse strains as well as between tissues within each mouse strain. We show that selection of reference gene (Actb) that is often used for analyses in individual mouse strains leads to errors if used for normalization when different mouse strains are compared. We identified alternative reference genes that are stable in these comparisons.

CONCLUSIONS

Genetic background and circadian time influence the expression stability of reference genes. Differences between mouse strains and tissues should be taken into consideration to avoid false interpretations. We show that the use of a single reference gene can lead to false biological conclusions. This manuscript provides a useful reference point for researchers that search for stable reference genes in the field of circadian biology.

Microarray-driven validation of reference genes for quantitative real-time polymerase chain reaction in a rat vocal fold model of mucosal injury

Relative quantification by normalization against a stably expressed reference gene is a widely used data analysis method in microarray and quantitative real-time polymerase chain reaction (qRT-PCR) platforms; however, recent evidence suggests that many commonly utilized reference genes are unstable in certain experimental systems and situations. The primary aim of this study, therefore, was to screen and identify stably expressed reference genes in a well-established rat model of vocal fold mucosal injury. We selected and evaluated the expression stability of nine candidate reference genes. Ablim1, Sptbn1, and Wrnip1 were identified as stably expressed in a model-specific microarray dataset and were further validated as suitable reference genes in an independent qRT-PCR experiment using 2(-DeltaCT) and pairwise comparison-based (geNorm) analyses. Parallel analysis of six commonly used reference genes identified Sdha as the only stably expressed candidate in this group. Sdha, Sptbn1, and the geometric mean of Sdha and Sptbn1 each provided accurate normalization of target gene Tgfb1; Gapdh, the least stable candidate gene in our dataset, provided inaccurate normalization and an invalid experimental result. The stable reference genes identified here are suitable for accurate normalization of target gene expression in vocal fold mucosal injury experiments.

Expectations, validity, and reality in gene expression profiling

OBJECTIVE

To provide a critical overview of gene expression profiling methodology and discuss areas of future development.

RESULTS

Gene expression profiling has been used extensively in biological research and has resulted in significant advances in the understanding of the molecular mechanisms of complex disorders, including cancer, heart disease, and metabolic disorders. However, translating this technology into genomic medicine for use in diagnosis and prognosis faces many challenges. In addition, gene expression profile analysis is frequently controversial, because its conclusions often lack reproducibility and claims of effective dissemination into translational medicine have, in some cases, been remarkably unjustified. In the last decade, a large number of methodological and technical solutions have been offered to overcome the challenges.

STUDY DESIGN AND SETTING

We consider the strengths, limitations, and appropriate applications of gene expression profiling techniques, with particular reference to the clinical relevance.

CONCLUSION

Some studies have demonstrated the ability and clinical utility of gene expression profiling for use as diagnostic, prognostic, and predictive molecular markers. The challenges of gene expression profiling lie with the standardization of analytic approaches and the evaluation of the clinical merit in broader heterogeneous populations by prospective clinical trials.

Microarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

Background

Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods.

We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA) on the Affymetrix^® GeneChip^® rhesus Macaque Genome Array.

Having shown that qRT-PCR and Affymetrix^® GeneChip^® data from the same hormone replacement therapy (HRT) study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study). Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages.

Results

Sequences co-annotated for ribosomal protein S27a (RPS27A), and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip^® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip^®. In the cycle study, multiple probe sets annotated for actin, gamma 1 (ACTG1) showed high signal intensity and were among the most stably expressed.

Conclusions

Using gene microarray analysis, we identified genes showing high expression stability under various sex-steroid environments in different regions of the rhesus macaque brain. Use of quantile-normalized microarray gene expression values represents an improvement over traditional methods of selecting internal reference genes for PCR analysis.

Selection of housekeeping genes for use in quantitative reverse transcription PCR assays on the murine cornea

PURPOSE

To evaluate the suitability of common housekeeping genes (HKGs) for use in quantitative reverse transcription PCR (qRT-PCR) assays of the cornea in various murine disease models.

METHODS

CORNEAL DISEASE MODELS STUDIED WERE: 1) corneal neovascularization (CorNV) induced by suture or chemical burn, 2) corneal infection with Candida albicans or Aspergillus fumigatus by intrastromal injection of live spores, and 3) perforating corneal injury (PCI) in Balb/c mice or C57BL/6 mice. Expression of 8 HKGs (glyceraldehyde-3-phosphate dehydrogenase [GAPDH], beta-actin [ACTB], lactate dehydrogenase A [LDHA], ribosomal protein L5 [RPL5], ubiquitin C [UBC], peptidylprolyl isomerase A [PPIA], TATA-box binding protein [TBP1], and hypoxanthine guanine phosphoribosyl transferase [HPRT1]) in the cornea were measured at various time points by microarray hybridization or qRT-PCR and the data analyzed using geNorm and NormFinder.

RESULTS

Microarray results showed that under the CorNV condition the expression stability of the 8 HKGs decreased in order of PPIA>RPL5>HPRT1>ACTB>UBC>TBP1>GAPDH>LDHA. qRT-PCR analyses demonstrated that expression of none of the 8 HKGs remained stable under all conditions, while GAPDH and ACTB were among the least stably expressed markers under most conditions. Both geNorm and NormFinder analyses proposed best HKGs or HKG combinations that differ between the various models. NormFinder proposed PPIA as best HKG for three CorNV models and PCI model, as well as UBC for two fungal keratitis models. geNorm analysis demonstrated that a similar model in different mice strains or caused by different stimuli may require different HKGs or HKG pairs for the best normalization. Namely, geNorm proposed PPIA and HRPT1 and PPIA and RPL5 pairs for chemical burn-induced CorNV in Balb/c and C57BL/6 mice, respectively, while UBC and HPRT1 and UBC and LDHA were best for Candida and Aspergillus induced keratitis in Balb/c mice, respectively.

CONCLUSIONS

When qRT-PCR is designed for studies of gene expression in murine cornea, preselection of situation-specific reference genes is recommended. In the absence of knowledge about situation-specific HKGs, PPIA and UBC, either alone or in combination with HPRT1 or RPL5, can be employed.

Genome-wide identification of new Wnt/beta-catenin target genes in the human genome using CART method

Background

The importance of in silico predictions for understanding cellular processes is now widely accepted, and a variety of algorithms useful for studying different biological features have been designed. In particular, the prediction of cis regulatory modules in non-coding human genome regions represents a major challenge for understanding gene regulation in several diseases. Recently, studies of the Wnt signaling pathway revealed a connection with neurodegenerative diseases such as Alzheimer's. In this article, we construct a classification tool that uses the transcription factor binding site motifs composition of some gene promoters to identify new Wnt/β-catenin pathway target genes potentially involved in brain diseases.

Results

In this study, we propose 89 new Wnt/β-catenin pathway target genes predicted in silico by using a method based on multiple Classification and Regression Tree (CART) analysis. We used as decision variables the presence of transcription factor binding site motifs in the upstream region of each gene. This prediction was validated by RT-qPCR in a sample of 9 genes. As expected, LEF1, a member of the T-cell factor/lymphoid enhancer-binding factor family (TCF/LEF1), was relevant for the classification algorithm and, remarkably, other factors related directly or indirectly to the inflammatory response and amyloidogenic processes also appeared to be relevant for the classification. Among the 89 new Wnt/β-catenin pathway targets, we found a group expressed in brain tissue that could be involved in diverse responses to neurodegenerative diseases, like Alzheimer's disease (AD). These genes represent new candidates to protect cells against amyloid β toxicity, in agreement with the proposed neuroprotective role of the Wnt signaling pathway.

Conclusions

Our multiple CART strategy proved to be an effective tool to identify new Wnt/β-catenin pathway targets based on the study of their regulatory regions in the human genome. In particular, several of these genes represent a new group of transcriptional dependent targets of the canonical Wnt pathway. The functions of these genes indicate that they are involved in pathophysiology related to Alzheimer's disease or other brain disorders.

Normalization with genes encoding ribosomal proteins but not GAPDH provides an accurate quantification of gene expressions in neuronal differentiation of PC12 cells

Background

Gene regulation at transcript level can provide a good indication of the complex signaling mechanisms underlying physiological and pathological processes. Transcriptomic methods such as microarray and quantitative real-time PCR require stable reference genes for accurate normalization of gene expression. Some but not all studies have shown that housekeeping genes (HGKs), β-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), which are routinely used for normalization, may vary significantly depending on the cell/tissue type and experimental conditions. It is currently unclear if these genes are stably expressed in cells undergoing drastic morphological changes during neuronal differentiation. Recent meta-analysis of microarray datasets showed that some but not all of the ribosomal protein genes are stably expressed. To test the hypothesis that some ribosomal protein genes can serve as reference genes for neuronal differentiation, a genome-wide analysis was performed and putative reference genes were identified based on stability of expressions. The stabilities of these potential reference genes were then analyzed by reverse transcription quantitative real-time PCR in six differentiation conditions.

Results

Twenty stably expressed genes, including thirteen ribosomal protein genes, were selected from microarray analysis of the gene expression profiles of GDNF and NGF induced differentiation of PC12 cells. The expression levels of these candidate genes as well as ACTB and GAPDH were further analyzed by reverse transcription quantitative real-time PCR in PC12 cells differentiated with a variety of stimuli including NGF, GDNF, Forskolin, KCl and ROCK inhibitor, Y27632. The performances of these candidate genes as stable reference genes were evaluated with two independent statistical approaches, geNorm and NormFinder.

Conclusions

The ribosomal protein genes, RPL19 and RPL29, were identified as suitable reference genes during neuronal differentiation of PC12 cells, regardless of the type of differentiation conditions. The combination of these two novel reference genes, but not the commonly used HKG, GAPDH, allows robust and accurate normalization of differentially expressed genes during PC12 differentiation.