3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples

Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast majority of archival tumor samples. To address this limitation of gene expression microarrays, we designed a novel procedure (3′-end sequencing for expression quantification (3SEQ)) for gene expression profiling from FFPET using next-generation sequencing. We performed gene expression profiling by 3SEQ and microarray on both frozen tissue and FFPET from two soft tissue tumors (desmoid type fibromatosis (DTF) and solitary fibrous tumor (SFT)) (total n = 23 samples, which were each profiled by at least one of the four platform-tissue preparation combinations). Analysis of 3SEQ data revealed many genes differentially expressed between the tumor types (FDR<0.01) on both the frozen tissue (∼9.6K genes) and FFPET (∼8.1K genes). Analysis of microarray data from frozen tissue revealed fewer differentially expressed genes (∼4.64K), and analysis of microarray data on FFPET revealed very few (69) differentially expressed genes. Functional gene set analysis of 3SEQ data from both frozen tissue and FFPET identified biological pathways known to be important in DTF and SFT pathogenesis and suggested several additional candidate oncogenic pathways in these tumors. These findings demonstrate that 3SEQ is an effective technique for gene expression profiling from archival tumor samples and may facilitate significant advances in translational cancer research.     

Selection of reliable reference genes for qRT-PCR analysis in human non-cancerous gastric tissue

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.     

Identification of suitable reference genes for gene expression studies of human serous ovarian cancer by real-time polymerase chain reaction

Quantitative real-time RT-PCR (RT-qPCR) has proven to be a valuable molecular technique in gene expression quantification. Target gene expression levels are usually normalized to a stably expressed reference gene simultaneously determined in the same sample. It is critical to select optimal reference genes to interpret data generated by RT-qPCR. However, no suitable reference genes have been identified in human ovarian cancer to date. In this study, 10 housekeeping genes, ACTB, ALAS1, GAPDH, GUSB, HPRT1, PBGD, PPIA, PUM1, RPL29, and TBP as well as 18S rRNA that were already used in various studies were analyzed to determine their applicability. Totally 20 serous ovarian cancer specimens and 20 normal ovarian epithelial tissue specimens were examined. All candidate reference genes showed significant differences in expression between malignant and nonmalignant groups except GUSB, PPIA, and TBP. The expression stability and suitability of the 11 genes were validated employing geNorm and NormFinder. GUSB, PPIA, and TBP were demonstrated as the most stable reference genes and thus could be used as reference genes for normalization in gene profiling studies of serous ovarian cancer, while the combination of two genes (GUSB and PPIA) or the all three genes should be recommended as a much more reliable normalization strategy.     

Selection of Reference Genes for qRT-PCR in High Fat Diet-Induced Hepatic Steatosis Mice Model

With the epidemic proportions of obesity worldwide and the concurrent prevalence of hepatic steatosis, there is an urgent need for better understanding the intrinsic mechanism of hepatic steatosis, especially the changes of gene expression underlying the development of hepatic steatosis and its associated abnormal liver function. Quantitative real-time PCR (qRT-PCR) is a sensitive and highly reproducible technique of gene expression analysis. However, for accurate and reliable gene expression results, it is vital to have an internal control gene expressed at constant levels under all the experimental conditions being analyzed for. In this study, the authors validated candidate reference genes suitable for qRT-PCR profiling experiments using livers from control mice and high fat diet-induced obese mice. Cross-validation of expression stability of ten selected reference genes using three popular algorithms, GeNorm, NormFinder, and BestKeeper found HPRT1 and GAPDH as most stable reference genes. Thus, HPRT1 and GAPDH are recommended as stable reference genes most suitable for gene expression studies in the development of hepatic steatosis.     

Identification of Suitable Reference Genes for Real Time Quantitative Polymerase Chain Reaction Assays on Pectoralis major Muscle in Chicken (Gallus gallus )

Thirteen reference genes were investigated to determine their stability to be used as a housekeeping in gene expression studies in skeletal muscle of chickens. Five different algorithms were used for ranking of reference genes and results suggested that individual rankings of the genes differed among them. The stability of the expression of reference genes were validated using samples obtained from the Pectoralis major muscle in chicken. Samples were obtained from chickens in different development periods post hatch and under different nutritional diets. For gene expression calculation the ΔΔCt approach was applied to compare relative expression of pairs of genes within each of 52 samples when normalized to mitochondrially encoded cytochrome c oxidase II (MT-CO2) target gene. Our findings showed that hydroxymethylbilane synthase (HMBS) and hypoxanthine phosphoribosyl transferase 1 (HPRT1) are the most stable reference genes while transferrin receptor (TFRC) and beta-2-microglobulin (B2M) ranked as the least stable genes in the Pectoralis major muscle of chickens. Moreover, our results revealed that HMBS and HPRT1 gene expression did not change due to dietary variations and thus it is recommended for accurate normalization of RT-qPCR data in chicken Pectoralis major muscle.     

Selection of reliable reference genes for qRT-PCR analysis in human non-cancerous gastric tissue

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.     

Selection of reference genes for tissue/organ samples on day 3 fifth‐instar larvae in silkworm,Bombyx mori

The silkworm, Bombyx mori, is one of the world's most economically important insect. Surveying variations in gene expression among multiple tissue/organ samples will provide clues for gene function assignments and will be helpful for identifying genes related to economic traits or specific cellular processes. To ensure their accuracy, commonly used gene expression quantification methods require a set of stable reference genes for data normalization. In this study, 24 candidate reference genes were assessed in 10 tissue/organ samples of day 3 fifth‐instar B. mori larvae using geNorm and NormFinder. The results revealed that, using the combination of the expression of BGIBMGA003186 and BGIBMGA008209 was the optimum choice for normalizing the expression data of the B. mori tissue/organ samples. The most stable gene, BGIBMGA003186, is recommended if just one reference gene is used. Moreover, the commonly used reference gene encoding cytoplasmic actin was the least appropriate reference gene of the samples investigated. The reliability of the selected reference genes was further confirmed by evaluating the expression profiles of two cathepsin genes. Our results may be useful for future studies involving the quantification of relative gene expression levels of different tissue/organ samples in B. mori.     

Selection of reference genes for gene expression studies in rats

Selection of the most stable reference gene is critical for a reliable interpretation of gene expression data using RT-PCR. In order so, 17 commonly used genes were analyzed in Wistar rat duodenum, jejunum, ileum and liver following a fat gavage and at two time periods. These reference genes were also tested in liver from Zucker (fa/fa) on a long-term dietary trial. Four strategies were used to select the most suitable reference gene for each tissue: ranking according to biological coefficient of variation and further validation by statistical comparison among groups, geNorm, NormFinder and BestKeeper programs. No agreement was observed among these approaches for a particular gene, nor a common gene for all tissues. Furthermore we demonstrated that normalising using an inadequate reference conveyed into false negative and positive results. The selection of genes provided by BestKeeper resulted in more reliable results than the other statistical packages. According to this program, Tbp, Ubc, Hprt and Rn18s were the best reference genes for duodenum, jejunum, ileum and liver, respectively following a fat gavage in Wistar rats and Rn18s for liver in another rat strain on a long-term dietary intervention. Therefore, BestKeeper is highly recommendable to select the most stable gene to be used as internal standard and the selection of a specific reference expression gene requires a validation for each tissue and experimental design.     

Selection of Reference Genes for Gene Expression Studies Related to Intramuscular Fat Deposition in Capra hircus Skeletal Muscle

The identification of suitable reference genes is critical for obtaining reliable results from gene expression studies using quantitative real-time PCR (qPCR) because the expression of reference genes may vary considerably under different experimental conditions. In most cases, however, commonly used reference genes are employed in data normalization without proper validation, which may lead to incorrect data interpretation. Here, we aim to select a set of optimal reference genes for the accurate normalization of gene expression associated with intramuscular fat (IMF) deposition during development. In the present study, eight reference genes (PPIB, HMBS, RPLP0, B2M, YWHAZ, 18S, GAPDH and ACTB) were evaluated by three different algorithms (geNorm, NormFinder and BestKeeper) in two types of muscle tissues (longissimus dorsi muscle and biceps femoris muscle) across different developmental stages. All three algorithms gave similar results. PPIB and HMBS were identified as the most stable reference genes, while the commonly used reference genes 18S and GAPDH were the most variably expressed, with expression varying dramatically across different developmental stages. Furthermore, to reveal the crucial role of appropriate reference genes in obtaining a reliable result, analysis of PPARG expression was performed by normalization to the most and the least stable reference genes. The relative expression levels of PPARG normalized to the most stable reference genes greatly differed from those normalized to the least stable one. Therefore, evaluation of reference genes must be performed for a given experimental condition before the reference genes are used. PPIB and HMBS are the optimal reference genes for analysis of gene expression associated with IMF deposition in skeletal muscle during development.     

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^−ΔCT 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.     

Correlations of expression of cell wall biosynthesis genes with variation in biomass composition in shrub willow (Salix spp.) biomass crops

We have measured significant genetically determined variation in biomass composition among breeding populations of shrub willow, a biomass feedstock crop. This project was aimed to ask whether patterns of cell wall gene expression can be correlated with genetic variation in biomass composition at harvest, in order to develop assays of early differences in gene expression as indicators of harvestable biomass chemical composition and potentially reduce the time of selection for new willow genotypes. Previous studies have demonstrated that manipulation of expression of cell wall biosynthetic genes results in altered biomass chemical composition. We analyzed genes encoding enzymes involved in lignin biosynthesis and carbohydrate active enzymes selected based on their functional characterization and conservation in Populus trichocarpa and Arabidopsis thaliana. Fragments of 20 genes were cloned from young stem cDNA of Salix sachalinensis and Salix miyabeana. Expression profiling in willow stem apical tissue and developing stem tissue was performed for each isolated gene using probe-based quantitative real-time PCR. Two willow parental genotypes and six progeny within a hybrid family were selected for analysis, and significant differences in expression among the individuals and between tissue types were observed for most of the genes. Significant correlations between patterns of gene expression and variation in the biomass chemical composition of those genotypes provide insight into the genetic regulation of lignocellulosic deposition in this important bioenergy crop and could be utilized as a tool for early selection of new genotypes.     

Genome-directed primers for selective labeling of bacterial transcripts for DNA microarray analysis

DNA microarrays have the ability to analyze the expression of thousands of the same set of genes under at least two different experimental conditions. However, DNA microarrays require substantial amounts of RNA to generate the probes, especially when bacterial RNA is used for hybridization (50 microg of bacterial total RNA contains approximately 2 microg of mRNA). We have developed a computer-based algorithm for prediction of the minimal number of primers to specifically anneal to all genes in a given genome. The algorithm predicts, for example, that 37 oligonucleotides should prime all genes in the Mycobacterium tuberculosis genome. We tested the usefulness of the genome-directed primers (GDPs) in comparison to random primers for gene expression profiling using DNA microarrays. Both types of primers were used to generate fluorescent-labeled probes and to hybridize to an array of 960 mycobacterial genes. Compared to random-primer probes, the GDP probes were more sensitive and more specific, especially when mammalian RNA samples were spiked with mycobacterial RNA. The GDPs were used for gene expression profiling of mycobacterial cultures grown to early log or stationary growth phases. This approach could be useful for accurate genome-wide expression analysis, especially for in vivo gene expression profiling, as well as directed amplification of sequenced genomes.