Improving gene-set enrichment analysis of RNA-Seq data with small replicates

Deregulated pathways identified from transcriptome data of two sample groups have played a key role in many genomic studies. Gene-set enrichment analysis (GSEA) has been commonly used for pathway or functional analysis of microarray data, and it is also being applied to RNA-seq data. However, most RNA-seq data so far have only small replicates. This enforces to apply the gene-permuting GSEA method (or preranked GSEA) which results in a great number of false positives due to the inter-gene correlation in each gene-set. We demonstrate that incorporating the absolute gene statistic in one-tailed GSEA considerably improves the false-positive control and the overall discriminatory ability of the gene-permuting GSEA methods for RNA-seq data. To test the performance, a simulation method to generate correlated read counts within a gene-set was newly developed, and a dozen of currently available RNA-seq enrichment analysis methods were compared, where the proposed methods outperformed others that do not account for the inter-gene correlation. Analysis of real RNA-seq data also supported the proposed methods in terms of false positive control, ranks of true positives and biological relevance. An efficient R package (AbsFilterG- SEA) coded with C++ (Rcpp) is available from CRAN.open

Characterization of Promoter Activities of Four Different Japanese Flounder Promoters in Transgenic Zebrafish

An important consideration in transgenic research is the choice of promoter for regulating the expression of a foreign gene. In this study several tissue-specific and inducible promoters derived from Japanese flounder Paralichthys olivaceus were identified, and their promoter activity was examined in transgenic zebrafish. The 5′ flanking regions of the Japanese flounder complement component C3, gelatinase B, keratin, and tumor necrosis factor (TNF) genes were linked to green fluorescence protein (GFP) as a reporter gene. The promoter regulatory constructs were introduced into fertilized zebrafish eggs. As a result we obtained several stable transgenic zebrafish that displayed green fluorescence in different tissues. Complement component C3 promoter regulated GFP expression in liver, and gelatinase B promoter regulated it in the pectoral fin and gills. Keratin promoter regulated GFP expression in skin and liver. TNF gene promoter regulated GFP expression in the pharynx and heart. TNF promoter had lipoplysaccharide-inducible activity, such that when transgenic embryos were immersed lipopolysaccharide, GFP expression increased in the epithelial tissues. These 4 promoters regulated the expression of GFP in different patterns in transgenic zebrafish

Asian Society of Gynecologic Oncology International Workshop 2014

published_or_final_versio

Suppression subtractive hybridization coupled with microarray analysis to examine differential expression of genes in virus infected cells

High throughput detection of differential expression of genes is an efficient means of identifying genes and pathways that may play a role in biological systems under certain experimental conditions. There exist a variety of approaches that could be used to identify groups of genes that change in expression in response to a particular stimulus or environment. We here describe the application of suppression subtractive hybridization (SSH) coupled with cDNA microarray analysis for isolation and identification of chicken transcripts that change in expression on infection of host cells with a paramyxovirus. SSH was used for initial isolation of differentially expressed transcripts, a large-scale validation of which was accomplished by microarray analysis. The data reveals a large group of regulated genes constituting many biochemical pathways that could serve as targets for future investigations to explore their role in paramyxovirus pathogenesis. The detailed methods described herein could be useful and adaptable to any biological system for studying changes in gene expression

Research on an online self-organizing radial basis function neural network

A new growing and pruning algorithm is proposed for radial basis function (RBF) neural network structure design in this paper, which is named as self-organizing RBF (SORBF). The structure of the RBF neural network is introduced in this paper first, and then the growing and pruning algorithm is used to design the structure of the RBF neural network automatically. The growing and pruning approach is based on the radius of the receptive field of the RBF nodes. Meanwhile, the parameters adjusting algorithms are proposed for the whole RBF neural network. The performance of the proposed method is evaluated through functions approximation and dynamic system identification. Then, the method is used to capture the biochemical oxygen demand (BOD) concentration in a wastewater treatment system. Experimental results show that the proposed method is efficient for network structure optimization, and it achieves better performance than some of the existing algorithms

The antioxidant and antiproliferative activities of methanolic extracts from Njavara rice bran

<p>Abstract</p> <p>Background</p> <p>Free radical-induced oxidative stress is the root cause for many human diseases. Naturally occurring antioxidant supplements from plants are vital to counter the oxidative damage in cells. The main objective of the present study was to characterize the antioxidant and antiproliferative potential of rice bran extracted from an important Indian rice variety, Njavara and to compare the same with two commercially available basmati rice varieties: Vasumathi, Yamini and a non medicinal variety, Jyothi.</p> <p>Methods</p> <p>Methanolic extracts of rice bran from four varieties; Vasumathi, Yamini, Jyothi and Njavara were used to study their total phenolic and flavonoid contents, <it>in vitro </it>antioxidant activities including total antioxidant activity, scavenging of nitric oxide and 1,1-Diphenyl-2-picrylhydrazyl (DPPH) radical, reducing power and cytotoxic activity in C6 glioma cells. Correlation coefficient and regression analysis were done by using Sigmastat version 3.1 and Stata statistical package respectively.</p> <p>Results</p> <p>Rice bran methanolic extract from Njavara showed the highest antioxidant and cell cytotoxic properties compared to the other three rice varieties. IC₅₀values for scavenging DPPH and nitric oxide were in the range of 30.85-87.72 μg/ml and 52.25-107.18 μg/ml respectively. Total antioxidant activity and reducing power were increased with increasing amounts of the extract. Total phenolic and flavonoid contents were in the range of 3.2-12.4 mg gallic acid-equivalent (GAE)/g bran and 1.68-8.5 mg quercetin-equivalent (QEE)/g bran respectively. IC₅₀values of cytotoxic assay (MTT assay) were 17.53-57.78 μg/ml. Correlation coefficient and regression analysis of phenolic content with DPPH and NO scavenging, MTT (-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide) assay, total antioxidant assay and reducing power showed a highly significant correlation coefficient values (96-99%) and regression values (91-98%).</p> <p>Conclusion</p> <p>The results of the present study show that the crude methanolic extract from Njavara rice bran contains significantly high polyphenolic compounds with superior antioxidant activity as evidenced by scavenging of free radicals including DPPH and NO. Njavara extracts also showed highest reducing power activity, anti-proliferative property in C6 glioma cells. In conclusion, it is conceivable that the Njavara rice variety could be exploited as one of the potential sources for plant - based pharmaceutical products.</p

Impact of Reference Gene Selection for Target Gene Normalization on Experimental Outcome Using Real-Time qRT-PCR in Adipocytes

Background: With the current rise in obesity-related morbidities, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) has become a widely used method for assessment of genes expressed and regulated by adipocytes. In order to measure accurate changes in relative gene expression and monitor intersample variability, normalization to endogenous control genes that do not change in relative expression is commonly used with qRT-PCR determinations. However, historical evidence has clearly demonstrated that the expression profiles of traditional control genes (e.g., b-actin, GAPDH, a-tubulin) are differentially regulated across multiple tissue types and experimental conditions. Methodology/Principal Findings: Therefore, we validated six commonly used endogenous control genes under diverse experimental conditions of inflammatory stress, oxidative stress, synchronous cell cycle progression and cellular differentiation in 3T3-L1 adipocytes using TaqMan qRT-PCR. Under each study condition, we further evaluated the impact of reference gene selection on experimental outcome using examples of target genes relevant to adipocyte function and differentiation. We demonstrate that multiple reference genes are regulated in a condition-specific manner that is not suitable for use in target gene normalization. Conclusion/Significance: Data are presented demonstrating that inappropriate reference gene selection can have profound influence on study conclusions ranging from divergent statistical outcome to inaccurate data interpretation of significan

Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse

An Effective Assessment of Simvastatin-Induced Toxicity with NMR-Based Metabonomics Approach

BACKGROUND: Simvastatin, which is used to control elevated cholesterol levels, is one of the most widely prescribed drugs. However, a daily excessive dose can induce drug-toxicity, especially in muscle and liver. Current markers for toxicity reflect mostly the late stages of tissue damage; thus, more efficient methods of toxicity evaluation are desired. METHODOLOGY/PRINCIPAL FINDINGS: As a new way to evaluate toxicity, we performed NMR-based metabonomics analysis of urine samples. Compared to conventional markers, such as AST, ALT, and CK, the urine metabolic profile provided clearer distinction between the pre- and post-treatment groups treated with toxic levels of simvastatin. Through multivariate statistical analysis, we identified marker metabolites associated with the toxicity. Importantly, we observed that the treatment group could be further categorized into two subgroups based on the NMR profiles: weak toxicity (WT) and high toxicity (HT). The distinction between these two groups was confirmed by the enzyme values and histopathological exams. Time-dependent studies showed that the toxicity at 10 days could be reliably predicted from the metabolic profiles at 6 days. CONCLUSIONS/SIGNIFICANCE: This metabonomics approach may provide a non-invasive and effective way to evaluate the simvastatin-induced toxicity in a manner that can complement current measures. The approach is expected to find broader application in other drug-induced toxicity assessments