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

Targeted DNA Methylation Editing Using an All-in-One System Establishes Paradoxical Activation of EBF3

Cutaneous melanoma is rapidly on the rise globally, surpassing the growth rate of other cancers, with metastasis being the primary cause of death in melanoma patients. Consequently, understanding the mechanisms behind this metastatic process and exploring innovative treatments is of paramount importance. Recent research has shown promise in unravelling the role of epigenetic factors in melanoma progression to metastasis. While DNA hypermethylation at gene promoters typically suppresses gene expression, we have contributed to establishing the newly understood mechanism of paradoxical activation of genes via DNA methylation, where high methylation coincides with increased gene activity. This mechanism challenges the conventional paradigm that promoter methylation solely silences genes, suggesting that, for specific genes, it might actually activate them. Traditionally, altering DNA methylation in vitro has involved using global demethylating agents, which is insufficient for studying the mechanism and testing the direct consequence of gene methylation changes. To investigate promoter hypermethylation and its association with gene activation, we employed a novel approach utilising a CRISPR-SunTag All-in-one system. Here, we focused on editing the DNA methylation of a specific gene promoter segment (EBF3) in melanoma cells using the All-in-one system. Using bisulfite sequencing and qPCR with RNA-Seq, we successfully demonstrated highly effective methylation and demethylation of the EBF3 promoter, with subsequent gene expression changes, to establish and validate the paradoxical role of DNA methylation. Further, our study provides novel insights into the function of the EBF3 gene, which remains largely unknown. Overall, this study challenges the conventional view of methylation as solely a gene-silencing mechanism and demonstrates a potential function of EBF3 in IFN pathway signalling, potentially uncovering new insights into epigenetic drivers of malignancy and metastasis.

Identification of stable reference genes for relative quantification of long RNA expression in urinary extracellular vesicles

Urinary extracellular vesicles (uEVs) are rich in valuable biomolecule information which are increasingly recognized as potential biomarkers for various diseases. uEV long RNAs are among the critical cargos capable of providing unique transcriptome information of the source cells. However, consensus regarding ideal reference genes for relative long RNAs quantification in uEVs is not available as of date. Here we explored stable reference genes through profiling the long RNA expression by RNA-seq following unsupervised analysis and validation studies. Candidate reference genes were identified using four algorithms: NormFinder, GeNorm, BestKeeper and the Delta Ct method, followed by validation. RNA profile showed uEVs contained abundant long RNAs information and the core transcriptome was related to cellular structures, especially ribosome which functions mainly as translation, protein and RNA binding molecules. Analysis of RNA-seq data identified RPL18A, RPL11, RPL27, RACK1, RPSA, RPL41, H1-2, RPL4, GAPDH, RPS27A as candidate reference genes. RT-qPCR validation revealed that RPL41, RPSA and RPL18A were reliable reference genes for long RNA quantification in uEVs from patients with diabetes mellitus (DM), diabetic nephropathy (DN), IgA nephropathy (IgAN) and prostate cancer (PCA). Interestingly, RPL41 also outperformed traditional reference genes in renal tissues of DN and IgAN, as well as in plasma EVs of several types of cancers. The stable reference genes identified in this study may facilitate development of uEVs as novel biomarkers and increase the accuracy and comparability of biomarker studies.

Identification of Optimal Reference Genes for qRT-PCR Normalization for Physical Activity Intervention and Omega-3 Fatty Acids Supplementation in Humans

The quantitative polymerase chain reaction (qRT-PCR) technique gives promising opportunities to detect and quantify RNA targets and is commonly used in many research fields. This study aimed to identify suitable reference genes for physical exercise and omega-3 fatty acids supplementation intervention. Forty healthy, physically active men were exposed to a 12-week eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) supplementation and standardized endurance training protocol. Blood samples were collected before and after the intervention and mRNA levels of six potential reference genes were tested in the leukocytes of 18 eligible participants using the qRT-PCR method: GAPDH (Glyceraldehyde-3-phosphate dehydrogenase), ACTB (Beta actin), TUBB (Tubulin Beta Class I), RPS18 (Ribosomal Protein S18), UBE2D2 (Ubiquitin-conjugating enzyme E2 D2), and HPRT1 (Hypoxanthine Phosphoribosyltransferase 1). The raw quantification cycle (Cq) values were then analyzed using RefFinder, an online tool that incorporates four different algorithms: NormFinder, geNorm, BestKeeper, and the comparative delta-Ct method. Delta-Ct, NormFinder, BestKeeper, and RefFinder comprehensive ranking have found GAPDH to be the most stably expressed gene. geNorm has identified TUBB and HPRT as the most stable genes. All algorithms have found ACTB to be the least stably expressed gene. A combination of the three most stably expressed genes, namely GAPDH, TUBB, and HPRT, is suggested for obtaining the most reliable results.

Identifying stable reference genes in polyethene glycol precipitated urinary extracellular vesicles for RT-qPCR-based gene expression studies in renal graft dysfunction patients

BACKGROUND

Urinary extracellular vesicles (UEVs) hold RNA in their cargo and are potential sources of biomarkers for gene expression studies. The most used technique for gene-expression studies is quantitative polymerase chain reaction (qPCR). It is critical to use stable reference genes (RGs) as internal controls for normalising gene expression data, which aren't currently available for UEVs.

METHODS

UEVs were precipitated from urine of graft dysfunction patients and healthy controls by Polyethylene glycol, Mn6000 (PEG6K). Vesicular characterisation confirmed the presence of UEVs. Gene expression levels of five commonly used RGs, i.e., Beta-2-Microglobulin (B2M), ribosomal-protein-L13a (RPL13A), Peptidylprolyl-Isomerase-A (PPIA), hydroxymethylbilane synthase (HMBS), and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) were quantified, and their stability was established through the RefFinder. The stability of identified RGs was validated by quantification of Perforin and granzyme B, signature molecules of renal graft dysfunction.

RESULTS

Urine precipitated with 12% 6 K PEG yielded round and double-membraned UEVs of size ranging from 30 to 100 nm, as confirmed through transmission electron microscopy. Nanoparticle tracking analysis (59 ± 22 nm) and Dynamic-light-scattering (78 ± 56.5 nm) confirmed their size profile. Semi-quantitative Exocheck antibody array demonstrated the presence of EV protein markers in UEV. Using the comparative ΔCт method and RefFinder analysis, B2M (1.6) and RPL13A (1.8) genes emerged as the most stable reference genes. Validation of target gene expression in renal graft dysfunction patients confirmed the efficiency of B2M and RPL13A through significant upregulation compared to other RGs.

CONCLUSIONS

Our study identified and validated B2M and RPL13A as optimal RGs for mRNA quantification studies in the UEVs of patients with renal graft dysfunction.

Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data

Many studies in recent years have demonstrated that some messenger RNA (mRNA) in platelets can be used as biomarkers for the diagnosis of pan-cancer. The quantitative real-time polymerase chain reaction (RT-qPCR) molecular technique is most commonly used to determine mRNA expression changes in platelets. Accurate and reliable relative RT-qPCR is highly dependent on reliable reference genes. However, there is no study to validate the reference gene in platelets for pan-cancer. Given that the expression of some commonly used reference genes is altered in certain conditions, selecting and verifying the most suitable reference gene for pan-cancer in platelets is necessary to diagnose early stage cancer. This study performed bioinformatics and functional analysis from the RNA-seq of platelets data set (GSE68086). We generated 95 candidate reference genes after the primary bioinformatics step. Seven reference genes (YWHAZ, GNAS, GAPDH, OAZ1, PTMA, B2M, and ACTB) were screened out among the 95 candidate reference genes from the data set of the platelets’ transcriptome of pan-cancer and 73 commonly known reference genes. These candidate reference genes were verified by another platelets expression data set (GSE89843). Then, we used RT-qPCR to confirm the expression levels of these seven genes in pan-cancer patients and healthy individuals. These RT-qPCR results were analyzed using the internal stability analysis software programs (the comparative Delta CT method, geNorm, NormFinder, and BestKeeper) to rank the candidate genes in the order of decreasing stability. By contrast, the GAPDH gene was stably and constitutively expressed at high levels in all the tested samples. Therefore, GAPDH was recommended as the most suitable reference gene for platelet transcript analysis. In conclusion, our result may play an essential part in establishing a molecular diagnostic platform based on the platelets to diagnose pan-cancer.

Identification of new reference genes with stable expression patterns for gene expression studies using human cancer and normal cell lines

Reverse transcription—quantitative real-time PCR (RT-qPCR) is a ubiquitously used method in biological research, however, finding appropriate reference genes for normalization is challenging. We aimed to identify genes characterized with low expression variability among human cancer and normal cell lines. For this purpose, we investigated the expression of 12 candidate reference genes in 13 widely used human cancer cell lines (HeLa, MCF-7, A-549, K-562, HL-60(TB), HT-29, MDA-MB-231, HCT 116, U-937, SH-SY5Y, U-251MG, MOLT-4 and RPMI-8226) and, in addition, 7 normal cell lines (HEK293, MRC-5, HUVEC/TERT2, HMEC, HFF-1, HUES 9, XCL-1). In our set of genes, we included SNW1 and CNOT4 as novel candidate reference genes based on the RNA HPA cell line gene data from The Human Protein Atlas. HNRNPL and PCBP1 were also included along with the „classical” reference genes ACTB, GAPDH, IPO8, PPIA, PUM1, RPL30, TBP and UBC. Results were evaluated using GeNorm, NormFiner, BestKeeper and the Comparative ΔCt methods. In conclusion, we propose IPO8, PUM1, HNRNPL, SNW1 and CNOT4 as stable reference genes for comparing gene expression between different cell lines. CNOT4 was also the most stable gene upon serum starvation.

Molecular phylogenetic and in silico analysis of glyceraldeyde-3-phosphate dehydrogenase (GAPDH) gene from northern bobwhite quail (Colinus virginianus)

Many recent studies have been focused on prevalence and impact of two helminth parasites, eyeworm Oxyspirura petrowi and caecal worm Aulonocephalus pennula, in the northern bobwhite quail (Colinus virginianus). However, few studies have attempted to examine the effect of these parasites on the bobwhite immune system. This is likely due to the lack of proper reference genes for relative gene expression studies. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is a glycolytic enzyme that is often utilized as a reference gene, and in this preliminary study, we evaluated the similarity of bobwhite GAPDH to GAPDH in other avian species to evaluate its potential as a reference gene in bobwhite. GAPDH was identified in the bobwhite full genome sequence and multiple sets of PCR primers were designed to generate overlapping PCR products. These products were then sequenced and then aligned to generate the sequence for the full-length open reading frame (ORF) of bobwhite GAPDH. Utilizing this sequence, phylogenetic analyses and comparative analysis of the exon-intron pattern were conducted that revealed high similarity of GAPDH encoding sequences among bobwhite and other Galliformes. Additionally, This ORF sequence was also used to predict the encoded protein and its three-dimensional structure which like the phylogenetic analyses reveal that bobwhite GAPDH is similar to GAPDH in other Galliformes. Finally, GAPDH qPCR primers were designed, standardized, and tested with bobwhite both uninfected and infected with O. petrowi, and this preliminary test showed no statistical difference in expression of GAPDH between the two groups. These analyses are the first to investigate GAPDH in bobwhite. These efforts in phylogeny, sequence analysis, and protein structure suggest that there is > 97% conservation of GADPH among Galliformes. Furthermore, the results of these in silico tests and the preliminary qPCR indicate that GAPDH is a prospective candidate for use in gene expression analyses in bobwhite.

The reuse of public datasets in the life sciences: potential risks and rewards

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

Selection of reference genes for quantitative PCR: identifying reference genes for airway epithelial cells exposed to Pseudomonas aeruginosa

Most quantitative PCR (qPCR) experiments report differential expression relative to the expression of one or more reference genes. Therefore, when experimental conditions alter reference gene expression, qPCR results may be compromised. Little is known about the magnitude of this problem in practice. We found that reference gene responses are common and hard to predict and that their stability should be demonstrated in each experiment. Our reanalysis of 15 airway epithelia microarray data sets retrieved from the National Center for Biotechnology Information (NCBI) identified no common reference gene that was reliable in all 15 studies. Reanalysis of published RNA sequencing (RNA-seq) data in which human bronchial epithelial cells (HBEC) were exposed to Pseudomonas aeruginosa revealed that minor experimental details, including bacterial strain, may alter reference gene responses. Direct measurement of 32 TaqMan reference genes in primary cultures of HBEC exposed to P. aeruginosa (strain PA14) demonstrated that choosing an unstable reference gene could make it impossible to observe statistically significant changes in IL8 gene expression. We found that reference gene instability is a general phenomenon and not limited to studies of airway epithelial cells. In a diverse compendium of 986 human microarray experiments retrieved from the NCBI, reference genes were differentially expressed in 42% of studies. Experimentally induced changes in reference gene expression ranged from 21% to 212%. These results highlight the importance of identifying adequate reference genes for each experimental system and documenting their response to treatment in each experiment. This will enhance experimental rigor and reproducibility in qPCR studies.

Constitutive expression of a fluorescent protein reports the size of live human cells

Cell size is important for cell physiology because it sets the geometric scale of organelles and biosynthesis. A number of methods exist to measure different aspects of cell size, but each has significant drawbacks. Here, we present an alternative method to measure the size of single human cells using a nuclear localized fluorescent protein expressed from a constitutive promoter. We validate this method by comparing it to several established cell size measurement strategies, including flow cytometry optical scatter, total protein dyes, and quantitative phase microscopy. We directly compare our fluorescent protein measurement with the commonly used measurement of nuclear volume and show that our measurements are more robust and less dependent on image segmentation. We apply our method to examine how cell size impacts the cell division cycle and reaffirm that there is a negative correlation between size at cell birth and G1 duration. Importantly, combining our size reporter with fluorescent labeling of a different protein in a different color channel allows measurement of concentration dynamics using simple wide-field fluorescence imaging. Thus, we expect our method will be of use to researchers interested in how dynamically changing protein concentrations control cell fates.

Evaluation of reference genes for quantitative real-time PCR analysis of messenger RNAs and microRNAs in rainbow trout Oncorhynchus mykiss under heat stress

We assessed the expression stability of several messenger (m)RNAs and micro (mi)RNAs from liver and head kidney of rainbow trout Oncorhynchus mykiss using high-throughput RNA sequencing (RNA-seq) and miRNA-seq data. Additionally, four commonly used reference genes and one small non-coding RNA (u6) were also selected to identify ideal reference mRNAs and miRNAs for quantitative real-time (qrt)-PCR analysis of heat stress responses. GeNorm, NormFinder, BestKeeper and comparative ΔC_t were employed for analysis of qrt-PCR data to systematically assess the expression stability of candidate mRNAs and miRNAs and stability was ranked using geometric means. β-actin and ef1-α were the most stably expressed reference mRNAs in liver and head kidney, respectively and ssa-mir-26a-5p and ssa-mir-462b-5p were the most stably expressed miRNAs in these tissues. This is the first identification of appropriate reference mRNAs and miRNAs for qrt-PCR analysis of O. mykiss under heat stress.

Mechanical and Biochemical Effects of Progesterone on Engineered Cervical Tissue

Preterm birth is a leading cause of morbidity and mortality in newborns. Babies born prematurely are at increased risk of lifelong health problems, including neurodevelopmental abnormalities. Cervical shortening precedes preterm birth in many women. Cervical shortening is caused, in part, by excessive softening of the extracellular matrix (ECM) of the cervical stroma. In clinical obstetrics, cervical shortening prompts treatment with supplemental progesterone to prevent preterm birth. However, progesterone-mediated effects on the cervical ECM are not well understood. This research sought to study progesterone-mediated remodeling of ECM produced by human cervical fibroblasts in vitro. A previously developed three-dimensional (3D) engineered model of the cervical ECM was used for experiments. Cervical fibroblasts were seeded on porous scaffolds and cultured in spinner flasks to promote ECM synthesis. Scaffolds were exposed to two conditions: 10-8 M estradiol versus 10-8 M estradiol +10-6 M progesterone for 4 weeks. To measure ECM strength, two scaffolds were mounted end-to-end on a wire and cultured such that ECM filled the gap between the scaffolds. The force required to pull the scaffolds apart was measured. Collagen content and collagen crosslinks were measured with ultra performance liquid chromatography-electrospray ionization tandem mass spectrometry. Whole-transcriptome RNA sequencing (RNA-seq) was used to quantify gene expression between the two experimental conditions. Zymography was used to study the quantity and activity of matrix metalloproteinase-2 (MMP2) in the scaffolds. The study found that exposure to progesterone increased tissue softness of the engineered ECM over 28 days. Increased tissue softness correlated with decreased collagen content. With RNA-seq, progesterone exposure resulted in gene expression changes consistent with known progesterone effects. Pathway analysis of the RNA-seq data suggested MMPs were significantly dysregulated in progesterone-exposed engineered ECM. Increased expression of active MMP2 was confirmed in the progesterone-exposed engineered ECM. In summary, progesterone increased the softness of the ECM, which was correlated with decreased collagen production and altered histology. These results are important for deciphering the role of progesterone in preventing preterm birth.

Selection of internal references for qRT-PCR assays of human hepatocellular carcinoma cell lines

Selecting internal references is important for normalizing the loading quantity of samples in quantitative reverse-transcription PCR (qRT-PCR). In the present study, a systematic evaluation of reference genes among nine hepatocellular carcinoma (HCC) cell lines was conducted. After screening the microarray assay data of ten HCC cell lines, 19 candidate reference genes were preselected and then evaluated by qRT-PCR, together with ACTB, GAPDH, HPRT1 and TUBB The expression evenness of these candidate genes was evaluated using RefFinder. The stabilities of the reference genes were further evaluated under different experimental perturbations in Huh-7 and MHCC-97L, and the applicability of the reference genes was assessed by measuring the mRNA expression of CCND1, CCND3, CDK4 and CDK6 under sorafenib treatment in Huh-7. Results showed that TFG and SFRS4 are among the most reliable reference genes, and ACTB ranks third and acts quite well as a classical choice, whereas GAPDH, HPRT1 and TUBB are not proper reference genes in qRT-PCR assays among the HCC cell lines. SFRS4, YWHAB, SFRS4 and CNPY3 are the most stable reference genes of the MHCC-97L under the perturbations of chemotherapy, oxidative stress, starvation and hypoxia respectively, whereas YWHAB is the most stable one of Huh-7 under all perturbations. GAPDH is recommended as a reference gene under chemotherapy perturbations. YWHAB and UBE2B, TMED2 and TSFM, and GAPDH and TSFM are the two best reference genes under oxidative stress, starvation and hypoxia perturbations respectively. TSFM is stable in both cell lines across all the perturbations.

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 Selection of Reference Genes for the Normalization of Circulating RNA Transcripts in Pregnant Women Based on RNA-Seq Data

RNA transcripts circulating in peripheral blood represent an important source of non-invasive biomarkers. To accurately quantify the levels of circulating transcripts, one needs to normalize the data with internal control reference genes, which are detected at relatively constant levels across blood samples. A few reference gene candidates have to be selected from transcriptome data before the validation of their stable expression by reverse-transcription quantitative polymerase chain reaction. However, there is a lack of transcriptome, let alone whole-transcriptome, data from maternal blood. To overcome this shortfall, we performed RNA-sequencing on blood samples from women presenting with preterm labor. The coefficient of variation (CV) of expression levels was calculated. Of 11,215 exons detected in the maternal blood whole-transcriptome, a panel of 395 genes, including PPP1R15B, EXOC8, ACTB, and TPT1, were identified to comprise exons with considerably less variable expression level (CV, 7.75-17.7%) than any GAPDH exon (minimum CV, 27.3%). Upon validation, the selected genes from this panel remained more stably expressed than GAPDH in maternal blood. This panel is over-represented with genes involved with the actin cytoskeleton, macromolecular complex, and integrin signaling. This groundwork provides a starting point for systematically selecting reference gene candidates for normalizing the levels of circulating RNA transcripts in maternal blood.

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.

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

Up to now quantitative PCR based assay is the most common method for characterizing or confirming gene expression patterns and comparing mRNA levels in different sample populations. Since this technique is relative easy and low cost compared to other methods of characterization, e.g. flow cytometry, we used it to typify human adipose-derived stem cells (hASCs). hASCs possess several characteristics that make them attractive for scientific research and clinical applications. Accurate normalization of gene expression relies on good selection of reference genes and the best way to choose them appropriately is to follow the common rule of the “Best 3”, at least three reference genes, three different validation software and three sample replicates. Analysis was performed on hASCs cultivated until the eleventh cell confluence using twelve candidate reference genes, initially selected from literature, whose stability was evaluated by the algorithms NormFinder, BestKeeper, RefFinder and IdealRef, a home-made version of GeNorm. The best gene panel (RPL13A, RPS18, GAPDH, B2M, PPIA and ACTB), determined in one patient by IdealRef calculation, was then investigated in other four donors. Although patients demonstrated a certain gene expression variability, we can assert that ACTB is the most unreliable gene whereas ribosomal proteins (RPL13A and RPS18) show minor inconstancy in their mRNA expression. This work underlines the importance of validating reference genes before conducting each experiment and proposes a free software as alternative to those existing.

Identification of reference genes and miRNAs for qRT-PCR in human esophageal squamous cell carcinoma

It is important to select an appropriate reference gene and miRNA when using quantitative real-time polymerase chain reaction (qRT-PCR) to analyze gene and miRNA expression. However, many commonly used reference genes and miRNAs are not stably expressed and therefore not suitable for normalization or quantification of qRT-PCR data. This study aims to identify appropriate reference genes and miRNAs for use in human esophageal squamous carcinoma qRT-PCR analysis. Using data provided by The Cancer Genome Atlas, we identified DDX5, LAPTM4A, P4HB, RHOA, miR-28-5p, miR-34a-5p, and miR-186-5p as candidate reference genes and miRNAs. We used qRT-PCR to verify the expression levels of these candidates and another seven commonly used reference genes and miRNAs. A set of 50 paired human normal esophageal tissues and squamous cell carcinoma samples were used in the analysis. We then used geNorm and NormFinder to analyze the results. DDX5, LAPTM4A, RHOA, ACTB, RNU48, miR-28-5p, miR-34a-5p, and miR-186-5p were stably expressed, indicating they are suitable for used as references in qRT-PCR analysis of esophageal squamous cell carcinoma. However, expression levels of 18s rRNA, GAPDH, P4HB, 5s rRNA, U6, and RNU6B varied greatly between esophageal normal and squamous cell carcinoma samples, indicating that they are not suitable for use as references in the qRT-PCR analysis of esophageal squamous cell carcinoma.

Easy-to-use strategy for reference gene selection in quantitative real-time PCR experiments

Real-time PCR is an indispensable technique for mRNA expression analysis but conclusions depend on appropriate reference gene selection. However, while reference gene selection has been a topic of publications, this issue is often disregarded when measuring target mRNA expression. Therefore, we (1) evaluated the frequency of appropriate reference gene selection, (2) suggest an easy-to-use tool for least variability reference gene selection, (3) demonstrate application of this tool, and (4) show effects on target gene expression profiles. All 2015 published articles in Naunyn-Schmiedeberg's Archives of Pharmacology were screened for the use of quantitative real-time PCR analysis and selection of reference genes. Target gene expression (Vegfa, Grk2, Sirt4, and Timp3) in H9c2 cells was analyzed following various interventions (hypoxia, hyperglycemia, and/or isoflurane exposure with and without subsequent hypoxia) in relation to putative reference genes (Actb, Gapdh, B2m, Sdha, and Rplp1) using the least variability method vs. an arbitrarily selected but established reference gene. In the vast majority (18 of 21) of papers, no information was provided regarding selection of an appropriate reference gene. In only 1 of 21 papers, a method of appropriate reference gene selection was described and in 2 papers reference gene selection remains unclear. The method of reference gene selection had major impact on interpretation of target gene expression. With hypoxia, for instance, the least variability gene was Rplp1 and target gene expression (Vefga) heavily showed a 2-fold up-regulation (p = 0.022) but no change (p = 0.3) when arbitrarily using Gapdh. Frequency of appropriate reference gene selection in this journal is low, and we propose our strategy for reference gene selection as an easy tool for proper target gene expression.

Evaluation of 9-cis retinoic acid and mitotane as antitumoral agents in an adrenocortical xenograft model

The available drug treatment options for adrenocortical carcinoma (ACC) are limited. In our previous studies, the in vitro activity of 9-cis retinoic acid (9-cisRA) on adrenocortical NCI-H295R cells was shown along with its antitumoral effects in a small pilot xenograft study. Our aim was to dissect the antitumoral effects of 9-cisRA on ACC in a large-scale xenograft study involving mitotane, 9-cisRA and their combination. 43 male SCID mice inoculated with NCI-H295R cells were treated in four groups (i. control, ii. 9-cisRA, iii. mitotane, iv. 9-cisRA + mitotane) for 28 days. Tumor size follow-up, histological and immunohistochemical (Ki-67) analysis, tissue gene expression microarray, quantitative real-time-PCR for the validation of microarray results and to detect circulating microRNAs were performed. Protein expression was studied by proteomics and Western-blot validation. Only mitotane alone and the combination of 9-cisRA and mitotane resulted in significant tumor size reduction. The Ki-67 index was significantly reduced in both 9-cisRA and 9-cisRA+mitotane groups. Only modest changes at the mRNA level were found: the 9-cisRA-induced overexpression of apolipoprotein A4 and down-regulation of phosphodiesterase 4A was validated. The expression of circulating hsa-miR-483-5p was significantly reduced in the combined treatment group. The SET protein was validated as being significantly down-regulated in the combined mitotane+9-cisRA group. 9-cisRA might be a helpful additive agent in the treatment of ACC in combination with mitotane. Circulating hsa-miR-483-5p could be utilized for monitoring the treatment efficacy in ACC patients, and the treatment-induced reduction in protein SET expression might raise its relevance in ACC biology.

Genome-wide identification and characterization of reference genes with different transcript abundances for Streptomyces coelicolor

The lack of reliable reference genes (RGs) in the genus Streptomyces hampers effort to obtain the precise data of transcript levels. To address this issue, we aimed to identify reliable RGs in the model organism Streptomyces coelicolor. A pool of potential RGs containing 1,471 genes was first identified by determining the intersection of genes with stable transcript levels from four time-series transcriptome microarray datasets of S. coelicolor M145 cultivated in different conditions. Then, following a strict rational selection scheme including homology analysis, disturbance analysis, function analysis and transcript abundance analysis, 13 candidates were selected from the 1,471 genes. Based on real-time quantitative reverse transcription PCR assays, SCO0710, SCO6185, SCO1544, SCO3183 and SCO4758 were identified as the top five genes with the most stable transcript levels among the 13 candidates. Further analyses showed these five genes also maintained stable transcript levels in different S. coelicolor strains, as well as in Streptomyces avermitilis MA-4680 and Streptomyces clavuligerus NRRL 3585, suggesting they could fulfill the requirements of accurate data normalization in streptomycetes. Moreover, the systematic strategy employed in this work could be used for reference in other microorganism to select reliable RGs.

Clinical and prognostic implications of Roundabout 4 (robo4) in adult patients with acute myeloid leukemia

Background

Robo4 is involved in hematopoietic stem/progenitor cell homeostasis and essential for tumor angiogenesis. Expression of Robo4 was recently found in solid tumors and leukemia stem cells. However, the clinical implications of Robo4 expression in patients with acute myeloid leukemia (AML) remain unclear.

Methods

We investigated the clinical and prognostic relevance of mRNA expression of Robo4 in bone marrow (BM) mononuclear cells from 218 adult patients with de novo AML. We also performed immunohistochemical staining to assess the Robo4 protein expression in the BM biopsy specimens from 30 selected AML patients in the cohort.

Results

Higher Robo4 expression was closely associated with lower white blood cell counts, expression of HLA-DR, CD13, CD34 and CD56 on leukemia cells, t(8;21) and ASXL1 mutation, but negatively correlated with t(15;17) and CEBPA mutation. Compared to patients with lower Robo4 expression, those with higher expression had significantly shorter disease-free survival (DFS) and overall survival (OS). This result was confirmed in an independent validation cohort. Furthermore, multivariate analyses showed that higher Robo4 expression was an independent poor prognostic factor for DFS and OS in total cohort and patients with intermediate-risk cytogenetics, irrespective of age, WBC count, karyotype, and mutation status of NPM1/FLT3-ITD, and CEBPA.

Conclusions

BM Robo4 expression can serve as a new biomarker to predict clinical outcomes in AML patients and Robo4 may serve as a potential therapeutic target in patients with higher Robo4 expression.

Identification of reference miRNAs in human tumors by TCGA miRNA-seq data

Although the accuracy of detecting the expression of miRNAs by quantitative real-time polymerase chain reaction (qRT-PCR) is highly dependent on reliable reference miRNAs, many commonly used reference miRNAs are not stably expressed and as such are not suitable for quantification and normalization of qRT-PCR data. To solve this problem, we analyzed the global expression profiles of thousands of samples in 14 types of common human tumors released by The Cancer Genome Atlas (TCGA), and identified the most stably and highly expressed miRNAs as candidate reference miRNAs in each type of tumor. We found that miR-361-5p and let-7i-5p were the most recommended candidate reference miRNAs in nine and eight types of tumors, respectively, followed by let-7a-5p, mir-28-5p and miR-99b-5p. Our results are of important value to those researchers focused on miRNA; however, these candidate reference miRNAs still need to be validated prior to their use in qRT-PCR studies.

High-throughput DNA analysis shows the importance of methylation in the control of immune inflammatory gene transcription in chronic periodontitis

Background

Chronic periodontitis represents a complex disease that is hard to control and is not completely understood. Evidence from past studies suggests that there is a key role for DNA methylation in the pathogenesis of periodontitis. However, all reports have applied technologies that investigate genes in a low throughput. In order to advance in the knowledge of the disease, we analyzed DNA methylation variations associated with gene transcription using a high-throughput assay. Infinium® HumanMethylation450 (Illumina) was performed on gingival samples from 12 periodontitis cases and 11 age-matched healthy individuals. Methylation data of 1,284 immune-related genes and 1,038 cell cycle-related genes from Gene Ontology (GO) and 575 genes from a dataset of stably expressed genes (genes with consistent expression in different physiological states and tissues) were extracted from a microarray dataset and analyzed using bioinformatics tools. DNA methylation variations ranging from −2,000 to +2,000 bp from the transcription start site (TSS) were analyzed, and the results were tested against a differential expression microarray dataset between healthy and periodontitis gingival tissues. Differences were evaluated using tests from the R Statistical Project.

Results

The comparison of probes between periodontitis and normal gingival tissues showed that the mean methylation scores and the frequency of methylated probes were significantly lower in genes related to the immune process. In the immune group, these parameters were negatively correlated with gene expression (Mann-Whitney test, p < 2.2e − 16).

Conclusions

Our results show that variations in DNA methylation between healthy and periodontitis cases are higher in genes related to the immune-inflammatory process. Thus, DNA methylation must be modulating chromatin regions and, consequently, modulating the mRNA transcription of immune-inflammatory genes related with periodontitis, impacting the prognosis of disease.

Evaluation of reference genes for quantitative real-time PCR in the brain, pituitary, and gonads of songbirds

Quantitative real-time PCR (qPCR) is becoming a popular tool for the quantification of gene expression in the brain and endocrine tissues of songbirds. Accurate analysis of qPCR data relies on the selection of appropriate reference genes for normalization, yet few papers on songbirds contain evidence of reference gene validation. Here, we evaluated the expression of ten potential reference genes (18S, ACTB, GAPDH, HMBS, HPRT, PPIA, RPL4, RPL32, TFRC, and UBC) in brain, pituitary, ovary, and testis in two species of songbirds: zebra finch and white-throated sparrow. We used two algorithms, geNorm and NormFinder, to assess the stability of these reference genes in our samples. We found that the suitability of some of the most popular reference genes for target gene normalization in mammals, such as 18S, depended highly on tissue type. Thus, they are not the best choices for brain and gonad in these songbirds. In contrast, we identified alternative genes, such as HPRT, RPL4 and PPIA, that were highly stable in brain, pituitary, and gonad in these species. Our results suggest that the validation of reference genes in mammals does not necessarily extrapolate to other taxonomic groups. For researchers wishing to identify and evaluate suitable reference genes for qPCR in songbirds, our results should serve as a starting point and should help increase the power and utility of songbird models in behavioral neuroendocrinology.

Analysis of multiple transcriptomes of the African oil palm (Elaeis guineensis) to identify reference genes for RT-qPCR

The African oil palm (Elaeis guineensis), which is grown in tropical and subtropical regions, is a highly productive oil-bearing crop. For gene expression-based analyses such as reverse transcription-quantitative real time PCR (RT-qPCR), reference genes are essential to provide a baseline with which to quantify relative gene expression. Normalization using reliable reference genes is critical in correctly interpreting expression data from RT-qPCR. In order to identify suitable reference genes in African oil palm, 17 transcriptomes of different tissues obtained from NCBI were systematically assessed for gene expression variation. In total, 53 putative candidate reference genes with coefficient of variation values <3.0 were identified: 18 in reproductive tissue and 35 in vegetative tissue. Analysis for enriched functions showed that approximately 90% of identified genes were clustered in cell component gene functions, and 12 out of 53 genes were traditional housekeeping genes. We selected and validated 16 reference genes chosen from leaf tissue transcriptomes by using RT-qPCR in sets of cold, drought and high salinity treated samples, and ranked expression stability using statistical algorithms geNorm, Normfinder and Bestkeeper. Genes encoding actin, adenine phosphoribosyltransferase and eukaryotic initiation factor 4A genes were the most stable genes over the cold, drought and high salinity stresses. Identification of stably expressed genes as reference gene candidates from multiple transcriptome datasets was found to be reliable and efficient, and some traditional housekeeping genes were more stably expressed than others. We provide a useful molecular genetic resource for future gene expression studies in African oil palm, facilitating molecular genetics approaches for crop improvement in this species.

The choice of reference gene affects statistical efficiency in quantitative PCR data analysis

Quantitative polymerase chain reaction (qPCR), a highly sensitive method of measuring gene expression, is widely used in biomedical research. To produce reliable results, it is essential to use stably expressed reference genes (RGs) for data normalization so that sample-to-sample variation can be controlled. In this study, we examine the effect of different RGs on statistical efficiency by analyzing a qPCR data set that contains 12 target genes and 3 RGs. Our results show that choosing the most stably expressed RG for data normalization does not guarantee reduced variance or improved statistical efficiency. We also provide a formula for determining when data normalization will improve statistical efficiency and hence increase the power of statistical tests in data analysis.

Identification of reference genes for qRT-PCR in human lung squamous-cell carcinoma by RNA-Seq

Although the accuracy of quantitative real-time polymerase chain reaction (qRT-PCR) is highly dependent on the reliable reference genes, many commonly used reference genes are not stably expressed and as such are not suitable for quantification and normalization of qRT-PCR data. The aim of this study was to identify novel reliable reference genes in lung squamous-cell carcinoma. We used RNA sequencing (RNA-Seq) to survey the whole genome expression in 5 lung normal samples and 44 lung squamous-cell carcinoma samples. We evaluated the expression profiles of 15 commonly used reference genes and identified five additional candidate reference genes. To validate the RNA-Seq dataset, we used qRT-PCR to verify the expression levels of these 20 genes in a separate set of 100 pairs of normal lung tissue and lung squamous-cell carcinoma samples, and then analyzed these results using geNorm and NormFinder. With respect to 14 of the 15 common reference genes (B2M, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, POLR2A, PPIA, RPLP0, TBP, TFRC, UBC, and YWHAZ), the expression levels were either too low to be easily detected, or exhibited a high degree of variability either between lung normal and squamous-cell carcinoma samples, or even among samples of the same tissue type. In contrast, 1 of the 15 common reference genes (ACTB) and the 5 additional candidate reference genes (EEF1A1, FAU, RPS9, RPS11, and RPS14) were stably and constitutively expressed at high levels in all the samples tested. ACTB, EEF1A1, FAU, RPS9, RPS11, and RPS14 are ideal reference genes for qRT-PCR analysis of lung squamous-cell carcinoma, while 14 commonly used qRT-PCR reference genes are less appropriate in this context.

Antitumoral effects of 9-cis retinoic acid in adrenocortical cancer

The currently available medical treatment options of adrenocortical cancer (ACC) are limited. In our previous meta-analysis of adrenocortical tumor genomics data, ACC was associated with reduced retinoic acid production and retinoid X receptor-mediated signaling. Our objective has been to study the potential antitumoral effects of 9-cis retinoic acid (9-cisRA) on the ACC cell line NCI-H295R and in a xenograft model. Cell proliferation, hormone secretion, and gene expression have been studied in the NCI-H295R cell line. A complex bioinformatics approach involving pathway and network analysis has been performed. Selected genes have been validated by real-time qRT-PCR. Athymic nude mice xenografted with NCI-H295R have been used in a pilot in vivo xenograft model. 9-cisRA significantly decreased cell viability and steroid hormone secretion in a concentration- and time-dependent manner in the NCI-H295R cell line. Four major molecular pathways have been identified by the analysis of gene expression data. Ten genes have been successfully validated involved in: (1) steroid hormone secretion (HSD3B1, HSD3B2), (2) retinoic acid signaling (ABCA1, ABCG1, HMGCR), (3) cell-cycle damage (GADD45A, CCNE2, UHRF1), and the (4) immune response (MAP2K6, IL1R2). 9-cisRA appears to directly regulate the cell cycle by network analysis. 9-cisRA also reduced tumor growth in the in vivo xenograft model. In conclusion, 9-cisRA might represent a promising new candidate in the treatment of hormone-secreting adrenal tumors and adrenocortical cancer.

Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma

Background

Epigenetics refers to the reversible functional modifications of the genome that do not correlate to changes in the DNA sequence. The aim of this study is to understand DNA methylation patterns across different stages of lung adenocarcinoma (LUAD).

Results

Our study identified 72, 93 and 170 significant DNA methylated genes in Stages I, II and III respectively. A set of common 34 significant DNA methylated genes located in the promoter section of the true CpG islands were found across stages, and these were: HOX genes, FOXG1, GRIK3, HAND2, PRKCB, etc. Of the total significant DNA methylated genes, 65 correlated with transcription function. The epigenetic analysis identified the following novel genes across all stages: PTGDR, TLX3, and POU4F2. The stage-wise analysis observed the appearance of NEUROG1 gene in Stage I and its re-appearance in Stage III. The analysis showed similar epigenetic pattern across Stage I and Stage III. Pathway analysis revealed important signaling and metabolic pathways of LUAD to correlate with epigenetics. Epigenetic subnetwork analysis identified a set of seven conserved genes across all stages: UBC, KRAS, PIK3CA, PIK3R3, RAF1, BRAF, and RAP1A. A detailed literature analysis elucidated epigenetic genes like FOXG1, HLA-G, and NKX6-2 to be known as prognostic targets.

Conclusion

Integrating epigenetic information for genes with expression data can be useful for comprehending in-depth disease mechanism and for the ultimate goal of better target identification.

Assessing gene network stability and individual variability in the fathead minnow (Pimephales promelas) transcriptome

Transcriptomics is increasingly used to assess biological responses to environmental stimuli and stressors such as aquatic pollutants. However, fundamental studies characterizing individual variability in mRNA levels are lacking, which currently limits the use of transcriptomics in environmental monitoring assessments. To address individual variability in transcript abundance, we performed a meta-analysis on 231 microarrays that were conducted in the fathead minnow (FHM), a widely used toxicological model. The mean variability for gene probes was ranked from most to least variable based upon the coefficient of variation. Transcripts that were the most variable in individual tissues included NADH dehydrogenase flavoprotein 1, GTPase IMAP family member 7-like and v-set domain-containing T-cell activation inhibitor 1-like while genes encoding ribosomal proteins (rpl24 and rpl36), basic transcription factor 3, and nascent polypeptide-associated complex alpha subunit were the least variable in individuals across a range of microarray experiments. Gene networks that showed high variability (based upon the variation in expression of individual members within the network) included cell proliferation, metabolism (steroid, lipids, and glucose), cell adhesion, vascularization, and regeneration while those that showed low variability (more stability) included mRNA and rRNA processing, regulation of translational fidelity, RNA splicing, and ribosome biogenesis. Real-time PCR was conducted on a subset of genes for comparison of variability collected from the microarrays. There was a significant positive relationship between the two methods when measuring individual variability, suggesting that variability detected in microarray data can be used to guide decisions on sample sizes for measuring transcripts in real-time PCR experiments. A power analysis revealed that measuring estrogen receptor ba (esrba) requires fewer biological replicates than that of estrogen receptor bb (esrbb) in the gonad and samples sizes required to detect a 50% change for reproductive-related transcripts is between 12 and 20. Characterizing individual variability at the molecular level will prove necessary as efforts are made toward integrating molecular tools into environmental risk assessments.

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.

Cross-platform microarray meta-analysis for the mouse jejunum selects novel reference genes with highly uniform levels of expression

Reference genes (RGs) with uniform expression are used for normalization of reverse transcription quantitative PCR (RT-qPCR) data. Their optimization for a specific biological context, e.g. a specific tissue, has been increasingly considered. In this article, we compare RGs identified by expression data meta-analysis restricted to the context tissue, the jejunum of Mus musculus domesticus, i) to traditional RGs, ii) to expressed interspersed repeated DNA elements, and iii) to RGs identified by meta-analysis of expression data from diverse tissues and conditions. To select the set of candidate RGs, we developed a novel protocol for the cross-platform meta-analysis of microarray data. The expression stability of twenty-four putative RGs was analysed by RT-qPCR in at least 14 jejunum samples of the mouse strains C57Bl/6N, CD1, and OF1. Across strains, the levels of expression of the novel RGs Plekha7, Zfx, and Ube2v1 as well as of Oaz1 varied less than two-fold irrespective of genotype, sex or their combination. The gene set consisting of Plekha7 and Oaz1 showed superior expression stability analysed with the tool RefFinder. The novel RGs are functionally diverse. This facilitates expression studies over a wide range of conditions. The highly uniform expression of the optimized RGs in the jejunum points towards their involvement in tightly regulated pathways in this tissue. We also applied our novel protocol of cross-microarray platform meta-analysis to the identification of RGs in the duodenum, the ileum and the entire small intestine. The selection of RGs with improved expression stability in a specific biological context can reduce the number of RGs for the normalization step of RT-qPCR expression analysis, thus reducing the number of samples and experimental costs.

Translational signatures and mRNA levels are highly correlated in human stably expressed genes

Background

Gene expression is one of the most relevant biological processes of living cells. Due to the relative small population sizes, it is predicted that human gene sequences are not strongly influenced by selection towards expression efficiency. One of the major problems in estimating to what extent gene characteristics can be selected to maximize expression efficiency is the wide variation that exists in RNA and protein levels among physiological states and different tissues. Analyses of datasets of stably expressed genes (i.e. with consistent expression between physiological states and tissues) would provide more accurate and reliable measurements of associations between variations of a specific gene characteristic and expression, and how distinct gene features work to optimize gene expression.

Results

Using a dataset of human genes with consistent expression between physiological states we selected gene sequence signatures related to translation that can predict about 42% of mRNA variation. The prediction can be increased to 51% when selecting genes that are stably expressed in more than 1 tissue. These genes are enriched for translation and ribosome biosynthesis processes and have higher translation efficiency scores, smaller coding sequences and 3^′ UTR sizes and lower folding energies when compared to other datasets. Additionally, the amino acid frequencies weighted by expression showed higher correlations with isoacceptor tRNA gene copy number, and smaller absolute correlation values with biosynthetic costs.

Conclusion

Our results indicate that human gene sequence characteristics related to transcription and translation processes can co-evolve in an integrated manner in order to optimize gene expression.

Selection of new appropriate reference genes for RT-qPCR analysis via transcriptome sequencing of cynomolgus monkeys (Macaca fascicularis)

In the investigation of the expression levels of target genes, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is the most accurate and widely used method. However, a normalization step is a prerequisite to obtain accurate quantification results from RT-qPCR data. Therefore, many studies regarding the selection of reference genes have been carried out. Recently, these studies have involved large-scale gene analysis methods such as microarray and next generation sequencing. In our previous studies, we analyzed large amounts of transcriptome data from the cynomolgus monkey. Using a modification of this large-scale transcriptome sequencing dataset, we selected and compared 12 novel candidate reference genes (ARFGAP2, ARL1, BMI1, CASC3, DDX3X, MRFAP1, ORMDL1, RSL24D1, SAR1A, USP22, ZC3H11A, and ZRANB2) and 4 traditionally used reference genes (ACTB, GAPDH, RPS19, and YWHAZ) in 13 different whole-body tissues by the 3 well-known programs geNorm, NormFinder, and BestKeeper. Combined analysis by these 3 programs showed that ADP-ribosylation factor GTPase activating protein 2 (ARFGAP2), morf4 family associated protein 1 (MRFAP1), and ADP-ribosylation factor-like 1 (ARL1) are the most appropriate reference genes for accurate normalization. Interestingly, 4 traditionally used reference genes were the least stably expressed in this study. For this reason, selection of appropriate reference genes is vitally important, and large-scale analysis is a good method for finding new candidate reference genes. Our results could provide reliable reference gene lists for future studies on the expression of various target genes in the cynomolgus monkey.

Familial or Sporadic Idiopathic Scoliosis - classification based on artificial neural network and GAPDH and ACTB transcription profile

BACKGROUND

Importance of hereditary factors in the etiology of Idiopathic Scoliosis is widely accepted. In clinical practice some of the IS patients present with positive familial history of the deformity and some do not. Traditionally about 90% of patients have been considered as sporadic cases without familial recurrence. However the exact proportion of Familial and Sporadic Idiopathic Scoliosis is still unknown. Housekeeping genes encode proteins that are usually essential for the maintenance of basic cellular functions. ACTB and GAPDH are two housekeeping genes encoding respectively a cytoskeletal protein β-actin, and glyceraldehyde-3-phosphate dehydrogenase, an enzyme of glycolysis. Although their expression levels can fluctuate between different tissues and persons, human housekeeping genes seem to exhibit a preserved tissue-wide expression ranking order. It was hypothesized that expression ranking order of two representative housekeeping genes ACTB and GAPDH might be disturbed in the tissues of patients with Familial Idiopathic Scoliosis (with positive family history of idiopathic scoliosis) opposed to the patients with no family members affected (Sporadic Idiopathic Scoliosis). An artificial neural network (ANN) was developed that could serve to differentiate between familial and sporadic cases of idiopathic scoliosis based on the expression levels of ACTB and GAPDH in different tissues of scoliotic patients. The aim of the study was to investigate whether the expression levels of ACTB and GAPDH in different tissues of idiopathic scoliosis patients could be used as a source of data for specially developed artificial neural network in order to predict the positive family history of index patient.

RESULTS

The comparison of developed models showed, that the most satisfactory classification accuracy was achieved for ANN model with 18 nodes in the first hidden layer and 16 nodes in the second hidden layer. The classification accuracy for positive Idiopathic Scoliosis anamnesis only with the expression measurements of ACTB and GAPDH with the use of ANN based on 6-18-16-1 architecture was 8 of 9 (88%). Only in one case the prediction was ambiguous.

CONCLUSIONS

Specially designed artificial neural network model proved possible association between expression level of ACTB, GAPDH and positive familial history of Idiopathic Scoliosis.

Integrative analysis of neuroblastoma and pheochromocytoma genomics data

Background

Pheochromocytoma and neuroblastoma are the most common neural crest-derived tumors in adults and children, respectively. We have performed a large-scale in silico analysis of altogether 1784 neuroblastoma and 531 pheochromocytoma samples to establish similarities and differences using analysis of mRNA and microRNA expression, chromosome aberrations and a novel bioinformatics analysis based on cooperative game theory.

Methods

Datasets obtained from Gene Expression Omnibus and ArrayExpress have been subjected to a complex bioinformatics analysis using GeneSpring, Gene Set Enrichment Analysis, Ingenuity Pathway Analysis and own software.

Results

Comparison of neuroblastoma and pheochromocytoma with other tumors revealed the overexpression of genes involved in development of noradrenergic cells. Among these, the significance of paired-like homeobox 2b in pheochromocytoma has not been reported previously. The analysis of similar expression patterns in neuroblastoma and pheochromocytoma revealed the same anti-apoptotic strategies in these tumors. Cancer regulation by stathmin turned out to be the major difference between pheochromocytoma and neuroblastoma. Underexpression of genes involved in neuronal cell-cell interactions was observed in unfavorable neuroblastoma. By the comparison of hypoxia- and Ras-associated pheochromocytoma, we have found that enhanced insulin like growth factor 1 signaling may be responsible for the activation of Src homology 2 domain containing transforming protein 1, the main co-factor of RET. Hypoxia induced factor 1α and vascular endothelial growth factor signaling included the most prominent gene expression changes between von Hippel-Lindau- and multiple endocrine neoplasia type 2A-associated pheochromocytoma.

Conclusions

These pathways include previously undescribed pathomechanisms of neuroblastoma and pheochromocytoma and associated gene products may serve as diagnostic markers and therapeutic targets.

Selection of suitable reference genes for quantitative gene expression studies in milk somatic cells of lactating cows (Bos indicus)

We assessed the suitability of 9 internal control genes (ICG) in milk somatic cells of lactating cows to find suitable reference genes for use in quantitative PCR (qPCR). Eighteen multiparous lactating Sahiwal cows were used, 6 in each of 3 lactation stages: early (25 ± 5 d in milk), mid (160 ± 15 d in milk), and late (275 ± 25 d in milk) lactation. Nine candidate reference genes [glyceraldehyde 3-phosphate dehydrogenase (GAPDH), protein phosphatase 1 regulatory subunit 11 (PPP1R11), β-actin (ACTB), β-2 microglobulin (B2M), 40S ribosomal protein S15a (RPS15A), ubiquitously expressed transcript (UXT), mitochondrial GTPase 1 (MTG1), 18S rRNA (RN18S1), and ubiquitin (UBC)] were evaluated. Three genes, β-casein (CSN2), lactoferrin (LTF), and cathelicidin (CAMP) were chosen as target genes. Very high amplification was observed in 7 ICG and very low level amplification was observed in 2 ICG (UXT and MTG1). Thus, UXT and MTG1 were excluded from further analysis. The qPCR data were analyzed by 2 software packages, geNorm and NormFinder, to determine suitable reference genes, based on their stability and expression. Overall, PPP1R11, ACTB, UBC, and GAPDH were stably expressed among all candidate reference genes. Therefore, these genes could be used as ICG for normalization of qPCR data in milk somatic cells through lactation.

Effects of mitotane on gene expression in the adrenocortical cell line NCI-H295R: a microarray study

Aim: The adrenolytic agent mitotane is widely used in the treatment of adrenocortical cancer; however, its mechanism of action is poorly elucidated. We have studied mitotane-induced mRNA expression changes in the NCI-H295R adrenocortical cancer cell line. Materials & methods: Cell viability and hormone assays were used to select the optimal mitotane concentration effectively inhibiting hormone secretion without affecting cell viability. RNA isolated from cultures treated for 48 and 72 h was subjected to Agilent 4×44K microarray platforms. Microarray results were validated by quantitative reverse-transcription PCR. Results: Altogether, 117 significantly differentially expressed genes were detected at 48 h and 72 h (p < 0.05) in mitotane-treated samples relative to controls. Three significantly underexpressed genes involved in steroid hormone biosynthesis (HSD3B1, HSD3B2 and CYP21A2) and four significantly overexpressed genes (GDF15, ALDH1L2, TRIB3 and SERPINE2) have been validated. Conclusion: Gene-expression changes might be involved in the adrenal action of mitotane and in the inhibition of hormone secretion.

Original submitted 20 January 2012; Revision submitted 17 May 2012

Identification of human housekeeping genes and tissue-selective genes by microarray meta-analysis

Background

Categorizing protein-encoding transcriptomes of normal tissues into housekeeping genes and tissue-selective genes is a fundamental step toward studies of genetic functions and genetic associations to tissue-specific diseases. Previous studies have been mainly based on a few data sets with limited samples in each tissue, which restrained the representativeness of their identified genes, and resulted in low consensus among them.

Results

This study compiled 1,431 samples in 43 normal human tissues from 104 microarray data sets. We developed a new method to improve gene expression assessment, and showed that more than ten samples are needed to robustly identify the protein-encoding transcriptome of a tissue. We identified 2,064 housekeeping genes and 2,293 tissue-selective genes, and analyzed gene lists by functional enrichment analysis. The housekeeping genes are mainly involved in fundamental cellular functions, and the tissue-selective genes are strikingly related to functions and diseases corresponding to tissue-origin. We also compared agreements and related functions among our housekeeping genes and those of previous studies, and pointed out some reasons for the low consensuses.

Conclusions

The results indicate that sufficient samples have improved the identification of protein-encoding transcriptome of a tissue. Comprehensive meta-analysis has proved the high quality of our identified HK and TS genes. These results could offer a useful resource for future research on functional and genomic features of HK and TS genes.