Comparison of Niskin vs. in situ approaches for analysis of gene expression in deep Mediterranean Sea water samples

NASA Astrophysics Data System (ADS)

Edgcomb, V. P.; Taylor, C.; Pachiadaki, M. G.; Honjo, S.; Engstrom, I.; Yakimov, M.

2016-07-01

Obtaining an accurate picture of microbial processes occurring in situ is essential for our understanding of marine biogeochemical cycles of global importance. Water samples are typically collected at depth and returned to the sea surface for processing and downstream experiments. Metatranscriptome analysis is one powerful approach for investigating metabolic activities of microorganisms in their habitat and which can be informative for determining responses of microbiota to disturbances such as the Deepwater Horizon oil spill. For studies of microbial processes occurring in the deep sea, however, sample handling, pressure, and other changes during sample recovery can subject microorganisms to physiological changes that alter the expression profile of labile messenger RNA. Here we report a comparison of gene expression profiles for whole microbial communities in a bathypelagic water column sample collected in the Eastern Mediterranean Sea using Niskin bottle sample collection and a new water column sampler for studies of marine microbial ecology, the Microbial Sampler - In Situ Incubation Device (MS-SID). For some taxa, gene expression profiles from samples collected and preserved in situ were significantly different from potentially more stressful Niskin sampling and preservation on deck. Some categories of transcribed genes also appear to be affected by sample handling more than others. This suggests that for future studies of marine microbial ecology, particularly targeting deep sea samples, an in situ sample collection and preservation approach should be considered.

Defining the limits of physiological plasticity: how gene expression can assess and predict the consequences of ocean change

PubMed Central

Evans, Tyler G.; Hofmann, Gretchen E.

2012-01-01

Anthropogenic stressors, such as climate change, are driving fundamental shifts in the abiotic characteristics of marine ecosystems. As the environmental aspects of our world's oceans deviate from evolved norms, of major concern is whether extant marine species possess the capacity to cope with such rapid change. In what many scientists consider the post-genomic era, tools that exploit the availability of DNA sequence information are being increasingly recognized as relevant to questions surrounding ocean change and marine conservation. In this review, we highlight the application of high-throughput gene-expression profiling, primarily transcriptomics, to the field of marine conservation physiology. Through the use of case studies, we illustrate how gene expression can be used to standardize metrics of sub-lethal stress, track organism condition in natural environments and bypass phylogenetic barriers that hinder the application of other physiological techniques to conservation. When coupled with fine-scale monitoring of environmental variables, gene-expression profiling provides a powerful approach to conservation capable of informing diverse issues related to ocean change, from coral bleaching to the spread of invasive species. Integrating novel approaches capable of improving existing conservation strategies, including gene-expression profiling, will be critical to ensuring the ecological and economic health of the global ocean. PMID:22566679

Influence of in vivo growth on human glioma cell line gene expression: Convergent profiles under orthotopic conditions

PubMed Central

Camphausen, Kevin; Purow, Benjamin; Sproull, Mary; Scott, Tamalee; Ozawa, Tomoko; Deen, Dennis F.; Tofilon, Philip J.

2005-01-01

Defining the molecules that regulate tumor cell survival is an essential prerequisite for the development of targeted approaches to cancer treatment. Whereas many studies aimed at identifying such targets use human tumor cells grown in vitro or as s.c. xenografts, it is unclear whether such experimental models replicate the phenotype of the in situ tumor cell. To begin addressing this issue, we have used microarray analysis to define the gene expression profile of two human glioma cell lines (U251 and U87) when grown in vitro and in vivo as s.c. or as intracerebral (i.c.) xenografts. For each cell line, the gene expression profile generated from tissue culture was significantly different from that generated from the s.c. tumor, which was significantly different from those grown i.c. The disparity between the i.c gene expression profiles and those generated from s.c. xenografts suggests that whereas an in vivo growth environment modulates gene expression, orthotopic growth conditions induce a different set of modifications. In this study the U251 and U87 gene expression profiles generated under the three growth conditions were also compared. As expected, the profiles of the two glioma cell lines were significantly different when grown as monolayer cultures. However, the glioma cell lines had similar gene expression profiles when grown i.c. These results suggest that tumor cell gene expression, and thus phenotype, as defined in vitro is affected not only by in vivo growth but also by orthotopic growth, which may have implications regarding the identification of relevant targets for cancer therapy. PMID:15928080

A biomarker-based screen of a gene expression compendium reveals regulation of Nrf2 by CAR and STAT5b

EPA Science Inventory

Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse l...

Genome-wide expression profiling in pediatric septic shock

PubMed Central

Wong, Hector R.

2013-01-01

For nearly a decade, our research group has had the privilege of developing and mining a multi-center, microarray-based, genome-wide expression database of critically ill children (≤ 10 years of age) with septic shock. Using bioinformatic and systems biology approaches, the expression data generated through this discovery-oriented, exploratory approach have been leveraged for a variety of objectives, which will be reviewed. Fundamental observations include wide spread repression of gene programs corresponding to the adaptive immune system, and biologically significant differential patterns of gene expression across developmental age groups. The data have also identified gene expression-based subclasses of pediatric septic shock having clinically relevant phenotypic differences. The data have also been leveraged for the discovery of novel therapeutic targets, and for the discovery and development of novel stratification and diagnostic biomarkers. Almost a decade of genome-wide expression profiling in pediatric septic shock is now demonstrating tangible results. The studies have progressed from an initial discovery-oriented and exploratory phase, to a new phase where the data are being translated and applied to address several areas of clinical need. PMID:23329198

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

A simple approach for human recombinant apolipoprotein E4 expression and purification.

PubMed

Argyri, Letta; Skamnaki, Vassiliki; Stratikos, Efstratios; Chroni, Angeliki

2011-10-01

We report a simple expression and purification procedure for the production of recombinant apolipoprotein E4 (apoE4), an important protein for the lipid homeostasis in humans that plays critical roles in the pathogenesis of cardiovascular and neurodegenerative diseases. Our approach is based on the expression of a thioredoxin-apoE4 fusion construct in bacterial cells and subsequent removal of the fused thioredoxin using the highly specific 3C protease, avoiding costly and laborious lipidation-delipidation steps used before. Our approach results in rapid, high-yield production of structurally and functionally competent apoE4 as evidenced by secondary structure measurements, thermal and chemical melting profiles and the kinetic profile of solubilization of dimyristoyl-phosphatidylcholine (DMPC) vesicles. This protocol is appropriate for laboratories with little experience in apolipoprotein biochemistry and will facilitate future studies on the role of apoE4 in the pathogenesis of cardiovascular disease and neurodegenerative diseases, including Alzheimer's disease. Copyright © 2011 Elsevier Inc. All rights reserved.

Transcriptomics analysis of lungs and peripheral blood of crystalline silica-exposed rats

PubMed Central

Sellamuthu, Rajendran; Umbright, Christina; Roberts, Jenny R.; Chapman, Rebecca; Young, Shih-Houng; Richardson, Diana; Cumpston, Jared; McKinney, Walter; Chen, Bean T.; Frazer, David; Li, Shengqiao; Kashon, Michael; Joseph, Pius

2015-01-01

Minimally invasive approaches to detect/predict target organ toxicity have significant practical applications in occupational toxicology. The potential application of peripheral blood transcriptomics as a practical approach to study the mechanisms of silica-induced pulmonary toxicity was investigated. Rats were exposed by inhalation to crystalline silica (15 mg/m3, 6 h/day, 5 days) and pulmonary toxicity and global gene expression profiles of lungs and peripheral blood were determined at 32 weeks following termination of exposure. A significant elevation in bronchoalveolar lavage fluid lactate dehydrogenase activity and moderate histological changes in the lungs, including type II pneumocyte hyperplasia and fibrosis, indicated pulmonary toxicity in the rats. Similarly, significant infiltration of neutrophils and elevated monocyte chemotactic protein-1 levels in the lungs showed pulmonary inflammation in the rats. Microarray analysis of global gene expression profiles identified significant differential expression [>1.5-fold change and false discovery rate (FDR) p < 0.01] of 520 and 537 genes, respectively, in the lungs and blood of the exposed rats. Bioinformatics analysis of the differentially expressed genes demonstrated significant similarity in the biological processes, molecular networks, and canonical pathways enriched by silica exposure in the lungs and blood of the rats. Several genes involved in functions relevant to silica-induced pulmonary toxicity such as inflammation, respiratory diseases, cancer, cellular movement, fibrosis, etc, were found significantly differentially expressed in the lungs and blood of the silica-exposed rats. The results of this study suggested the potential application of peripheral blood gene expression profiling as a toxicologically relevant and minimally invasive surrogate approach to study the mechanisms underlying silica-induced pulmonary toxicity. PMID:22861000

Chronomics of pressure overload-induced cardiac hypertrophy in mice reveals altered day/night gene expression and biomarkers of heart disease.

PubMed

Tsimakouridze, Elena V; Straume, Marty; Podobed, Peter S; Chin, Heather; LaMarre, Jonathan; Johnson, Ron; Antenos, Monica; Kirby, Gordon M; Mackay, Allison; Huether, Patsy; Simpson, Jeremy A; Sole, Michael; Gadal, Gerard; Martino, Tami A

2012-08-01

There is critical demand in contemporary medicine for gene expression markers in all areas of human disease, for early detection of disease, classification, prognosis, and response to therapy. The integrity of circadian gene expression underlies cardiovascular health and disease; however time-of-day profiling in heart disease has never been examined. We hypothesized that a time-of-day chronomic approach using samples collected across 24-h cycles and analyzed by microarrays and bioinformatics advances contemporary approaches, because it includes sleep-time and/or wake-time molecular responses. As proof of concept, we demonstrate the value of this approach in cardiovascular disease using a murine Transverse Aortic Constriction (TAC) model of pressure overload-induced cardiac hypertrophy in mice. First, microarrays and a novel algorithm termed DeltaGene were used to identify time-of-day differences in gene expression in cardiac hypertrophy 8 wks post-TAC. The top 300 candidates were further analyzed using knowledge-based platforms, paring the list to 20 candidates, which were then validated by real-time polymerase chain reaction (RTPCR). Next, we tested whether the time-of-day gene expression profiles could be indicative of disease progression by comparing the 1- vs. 8-wk TAC. Lastly, since protein expression is functionally relevant, we monitored time-of-day cycling for the analogous cardiac proteins. This approach is generally applicable and can lead to new understanding of disease.

Quantifying whole transcriptome size, a prerequisite for understanding transcriptome evolution across species: an example from a plant allopolyploid.

PubMed

Coate, Jeremy E; Doyle, Jeff J

2010-01-01

Evolutionary biologists are increasingly comparing gene expression patterns across species. Due to the way in which expression assays are normalized, such studies provide no direct information about expression per gene copy (dosage responses) or per cell and can give a misleading picture of genes that are differentially expressed. We describe an assay for estimating relative expression per cell. When used in conjunction with transcript profiling data, it is possible to compare the sizes of whole transcriptomes, which in turn makes it possible to compare expression per cell for each gene in the transcript profiling data set. We applied this approach, using quantitative reverse transcriptase-polymerase chain reaction and high throughput RNA sequencing, to a recently formed allopolyploid and showed that its leaf transcriptome was approximately 1.4-fold larger than either progenitor transcriptome (70% of the sum of the progenitor transcriptomes). In contrast, the allopolyploid genome is 94.3% as large as the sum of its progenitor genomes and retains > or =93.5% of the sum of its progenitor gene complements. Thus, "transcriptome downsizing" is greater than genome downsizing. Using this transcriptome size estimate, we inferred dosage responses for several thousand genes and showed that the majority exhibit partial dosage compensation. Homoeologue silencing is nonrandomly distributed across dosage responses, with genes showing extreme responses in either direction significantly more likely to have a silent homoeologue. This experimental approach will add value to transcript profiling experiments involving interspecies and interploidy comparisons by converting expression per transcriptome to expression per genome, eliminating the need for assumptions about transcriptome size.

Unravelling the neurophysiological basis of aggression in a fish model

PubMed Central

2010-01-01

Background Aggression is a near-universal behaviour with substantial influence on and implications for human and animal social systems. The neurophysiological basis of aggression is, however, poorly understood in all species and approaches adopted to study this complex behaviour have often been oversimplified. We applied targeted expression profiling on 40 genes, spanning eight neurological pathways and in four distinct regions of the brain, in combination with behavioural observations and pharmacological manipulations, to screen for regulatory pathways of aggression in the zebrafish (Danio rerio), an animal model in which social rank and aggressiveness tightly correlate. Results Substantial differences occurred in gene expression profiles between dominant and subordinate males associated with phenotypic differences in aggressiveness and, for the chosen gene set, they occurred mainly in the hypothalamus and telencephalon. The patterns of differentially-expressed genes implied multifactorial control of aggression in zebrafish, including the hypothalamo-neurohypophysial-system, serotonin, somatostatin, dopamine, hypothalamo-pituitary-interrenal, hypothalamo-pituitary-gonadal and histamine pathways, and the latter is a novel finding outside mammals. Pharmacological manipulations of various nodes within the hypothalamo-neurohypophysial-system and serotonin pathways supported their functional involvement. We also observed differences in expression profiles in the brains of dominant versus subordinate females that suggested sex-conserved control of aggression. For example, in the HNS pathway, the gene encoding arginine vasotocin (AVT), previously believed specific to male behaviours, was amongst those genes most associated with aggression, and AVT inhibited dominant female aggression, as in males. However, sex-specific differences in the expression profiles also occurred, including differences in aggression-associated tryptophan hydroxylases and estrogen receptors. Conclusions Thus, through an integrated approach, combining gene expression profiling, behavioural analyses, and pharmacological manipulations, we identified candidate genes and pathways that appear to play significant roles in regulating aggression in fish. Many of these are novel for non-mammalian systems. We further present a validated system for advancing our understanding of the mechanistic underpinnings of complex behaviours using a fish model. PMID:20846403

Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets.

PubMed

Amar, David; Hait, Tom; Izraeli, Shai; Shamir, Ron

2015-09-18

Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case-control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14,000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Conditional clustering of temporal expression profiles

PubMed Central

Wang, Ling; Montano, Monty; Rarick, Matt; Sebastiani, Paola

2008-01-01

Background Many microarray experiments produce temporal profiles in different biological conditions but common cluster techniques are not able to analyze the data conditional on the biological conditions. Results This article presents a novel technique to cluster data from time course microarray experiments performed across several experimental conditions. Our algorithm uses polynomial models to describe the gene expression patterns over time, a full Bayesian approach with proper conjugate priors to make the algorithm invariant to linear transformations, and an iterative procedure to identify genes that have a common temporal expression profile across two or more experimental conditions, and genes that have a unique temporal profile in a specific condition. Conclusion We use simulated data to evaluate the effectiveness of this new algorithm in finding the correct number of clusters and in identifying genes with common and unique profiles. We also use the algorithm to characterize the response of human T cells to stimulations of antigen-receptor signaling gene expression temporal profiles measured in six different biological conditions and we identify common and unique genes. These studies suggest that the methodology proposed here is useful in identifying and distinguishing uniquely stimulated genes from commonly stimulated genes in response to variable stimuli. Software for using this clustering method is available from the project home page. PMID:18334028

Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits: From RNA Integrity to Network Topology

PubMed Central

O'Brien, M.A.; Costin, B.N.; Miles, M.F.

2014-01-01

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313

Body Fluids as a Source of Diagnostic Biomarkers: Prostate — EDRN Public Portal

Cancer.gov

Recent advances in high-throughput protein expression profiling of bodily fluids has generated great enthusiasm and hope for this approach as a potent diagnostic tool. At the center of these efforts is the application of SELDI-TOF-MS and artificial intelligence algorithms by the EDRN BDL site at Eastern Virginia Medical School and the DMCC respectively. When the expression profiling process was applied to sera from individuals with prostate cancer (N=197), BPH (N=92) or from otherwise healthy donors (N=97) we achieved an overall misclassification rate of 90% sensitivity. Since this represents a noticeable improvement in current clinical approach we are proposing to embark upon a validation process. The described studies are designed to address validation issues and include three phases. Phase 1; Synchronization of SELDI Output within the EDRN-Prostate-SELDI Investigational Collaboration (EPSIC); addressing portability (A) Synchronize SELDI instrumentation and robotic sample processing across the EPSIC using pooled serum(QC); (B) Establish the portability and reproducibility of the SELDI protein profiling approach within the EPSIC using normal and prostate cancer patient’s serum from a single site; (C) Establish robustness of the approach toward geographic, sample collection and processing differences within EPSIC using case and control serum from five different sites. Phase 2; Population Validation Establish geographic variability and robustness in a large cross-sectional study among different sample population. Phase 3; Clinical Validation; validate the serum protein expression profiling coupled with a learning algorithm as a means for early detection of prostate cancer using longitudinal PCPT samples. We have assembled a cohesive multi-institutional team for completing these studies in a timely and efficient manner. The team consists of five EDRN laboratories, DMCC and CBI and the proposed budget reflects the total involvement.

A biomarker-based screen of a gene expression compendium ...

EPA Pesticide Factsheets

Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse liver. A gene expression biomarker of 48 genes which accurately predicted Nrf2 activation was used to identify factors which resulted in a gene expression profile with significant correlation to the biomarker. A number of novel insights were made. Chemicals that activated the xenosensor constitutive activated receptor (CAR) consistently activated Nrf2 across hundreds of profiles, possibly downstream of Cyp-induced increases in oxidative stress. Nrf2 activation was also found to be negatively regulated by the growth hormone (GH)- and androgen-regulated transcription factor STAT5b, a transcription factor suppressed by CAR. Nrf2 was activated when STAT5b was suppressed in female mice vs. male mice, after exposure to estrogens, or in genetic mutants in which GH signaling was disrupted. A subset of the mutants that show STAT5b suppression and Nrf2 activation result in increased resistance to environmental stressors and increased longevity. This study describes a novel approach for understanding the network of factors that regulate the Nrf2 pathway and highlights novel interactions between Nrf2, CAR and STAT5b transcription factors. (This abstract does not represent EPA policy.) Computational appr

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

PubMed Central

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers’ exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes. PMID:27832067

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

PubMed

Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-11-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers' exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes.

Genetic validation of whole-transcriptome sequencing for mapping expression affected by cis-regulatory variation.

PubMed

Babak, Tomas; Garrett-Engele, Philip; Armour, Christopher D; Raymond, Christopher K; Keller, Mark P; Chen, Ronghua; Rohl, Carol A; Johnson, Jason M; Attie, Alan D; Fraser, Hunter B; Schadt, Eric E

2010-08-13

Identifying associations between genotypes and gene expression levels using microarrays has enabled systematic interrogation of regulatory variation underlying complex phenotypes. This approach has vast potential for functional characterization of disease states, but its prohibitive cost, given hundreds to thousands of individual samples from populations have to be genotyped and expression profiled, has limited its widespread application. Here we demonstrate that genomic regions with allele-specific expression (ASE) detected by sequencing cDNA are highly enriched for cis-acting expression quantitative trait loci (cis-eQTL) identified by profiling of 500 animals in parallel, with up to 90% agreement on the allele that is preferentially expressed. We also observed widespread noncoding and antisense ASE and identified several allele-specific alternative splicing variants. Monitoring ASE by sequencing cDNA from as little as one sample is a practical alternative to expression genetics for mapping cis-acting variation that regulates RNA transcription and processing.

Integrating Genomic Analysis with the Genetic Basis of Gene Expression: Preliminary Evidence of the Identification of Causal Genes for Cardiovascular and Metabolic Traits Related to Nutrition in Mexicans123

PubMed Central

Bastarrachea, Raúl A.; Gallegos-Cabriales, Esther C.; Nava-González, Edna J.; Haack, Karin; Voruganti, V. Saroja; Charlesworth, Jac; Laviada-Molina, Hugo A.; Veloz-Garza, Rosa A.; Cardenas-Villarreal, Velia Margarita; Valdovinos-Chavez, Salvador B.; Gomez-Aguilar, Patricia; Meléndez, Guillermo; López-Alvarenga, Juan Carlos; Göring, Harald H. H.; Cole, Shelley A.; Blangero, John; Comuzzie, Anthony G.; Kent, Jack W.

2012-01-01

Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology. Synchronous in vivo expression profiles of lymphocytes, muscle, and subcutaneous fat were obtained from healthy Mexican men. Most genes were expressed at detectable levels in multiple tissues, and RNA levels were correlated between tissue types. A subset of transcripts with high reliability of expression across tissues (estimated by intraclass correlation coefficients) was enriched for cis-regulated genes, suggesting that proximal sequence variants may influence expression similarly in different cellular environments. This integrative global gene expression profiling approach is proving extremely useful for identifying genes and pathways that contribute to complex clinical traits. Clearly, the coincidence of clinical trait quantitative trait loci and expression quantitative trait loci can help in the prioritization of positional candidate genes. Such data will be crucial for the formal integration of positional and transcriptomic information characterized as genetical genomics. PMID:22797999

A method to identify differential expression profiles of time-course gene data with Fourier transformation

PubMed Central

2013-01-01

Background Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. Results This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization. The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Conclusions Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics. PMID:24134721

Gene expression profiling of the plant pathogenic basidiomycetous fungus Rhizoctonia solani AG 4 reveals putative virulence factors

USDA-ARS?s Scientific Manuscript database

Rhizoctonia solani is a ubiquitous basidiomycetous soilborne fungal pathogen causing damping off of seedlings, aerial blights and postharvest diseases. To gain insight into the molecular mechanisms of pathogenesis a global approach based on analysis of expressed sequence tags (ESTs) was undertaken. ...

Emergent Self-Organized Criticality in Gene Expression Dynamics: Temporal Development of Global Phase Transition Revealed in a Cancer Cell Line

PubMed Central

Tsuchiya, Masa; Giuliani, Alessandro; Hashimoto, Midori; Erenpreisa, Jekaterina; Yoshikawa, Kenichi

2015-01-01

Background The underlying mechanism of dynamic control of the genome-wide expression is a fundamental issue in bioscience. We addressed it in terms of phase transition by a systemic approach based on both density analysis and characteristics of temporal fluctuation for the time-course mRNA expression in differentiating MCF-7 breast cancer cells. Methodology In a recent work, we suggested criticality as an essential aspect of dynamic control of genome-wide gene expression. Criticality was evident by a unimodal-bimodal transition through flattened unimodal expression profile. The flatness on the transition suggests the existence of a critical transition at which up- and down-regulated expression is balanced. Mean field (averaging) behavior of mRNAs based on the temporal expression changes reveals a sandpile type of transition in the flattened profile. Furthermore, around the transition, a self-similar unimodal-bimodal transition of the whole expression occurs in the density profile of an ensemble of mRNA expression. These singular and scaling behaviors identify the transition as the expression phase transition driven by self-organized criticality (SOC). Principal Findings Emergent properties of SOC through a mean field approach are revealed: i) SOC, as a form of genomic phase transition, consolidates distinct critical states of expression, ii) Coupling of coherent stochastic oscillations between critical states on different time-scales gives rise to SOC, and iii) Specific gene clusters (barcode genes) ranging in size from kbp to Mbp reveal similar SOC to genome-wide mRNA expression and ON-OFF synchronization to critical states. This suggests that the cooperative gene regulation of topological genome sub-units is mediated by the coherent phase transitions of megadomain-scaled conformations between compact and swollen chromatin states. Conclusion and Significance In summary, our study provides not only a systemic method to demonstrate SOC in whole-genome expression, but also introduces novel, physically grounded concepts for a breakthrough in the study of biological regulation. PMID:26067993

TANDEM: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types.

PubMed

Aben, Nanne; Vis, Daniel J; Michaut, Magali; Wessels, Lodewyk F A

2016-09-01

Clinical response to anti-cancer drugs varies between patients. A large portion of this variation can be explained by differences in molecular features, such as mutation status, copy number alterations, methylation and gene expression profiles. We show that the classic approach for combining these molecular features (Elastic Net regression on all molecular features simultaneously) results in models that are almost exclusively based on gene expression. The gene expression features selected by the classic approach are difficult to interpret as they often represent poorly studied combinations of genes, activated by aberrations in upstream signaling pathways. To utilize all data types in a more balanced way, we developed TANDEM, a two-stage approach in which the first stage explains response using upstream features (mutations, copy number, methylation and cancer type) and the second stage explains the remainder using downstream features (gene expression). Applying TANDEM to 934 cell lines profiled across 265 drugs (GDSC1000), we show that the resulting models are more interpretable, while retaining the same predictive performance as the classic approach. Using the more balanced contributions per data type as determined with TANDEM, we find that response to MAPK pathway inhibitors is largely predicted by mutation data, while predicting response to DNA damaging agents requires gene expression data, in particular SLFN11 expression. TANDEM is available as an R package on CRAN (for more information, see http://ccb.nki.nl/software/tandem). m.michaut@nki.nl or l.wessels@nki.nl Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Behavioral profiling as a translational approach in an animal model of posttraumatic stress disorder.

PubMed

Ardi, Ziv; Albrecht, Anne; Richter-Levin, Alon; Saha, Rinki; Richter-Levin, Gal

2016-04-01

Diagnosis of psychiatric disorders in humans is based on comparing individuals to the normal population. However, many animal models analyze averaged group effects, thus compromising their translational power. This discrepancy is particularly relevant in posttraumatic stress disorder (PTSD), where only a minority develop the disorder following a traumatic experience. In our PTSD rat model, we utilize a novel behavioral profiling approach that allows the classification of affected and unaffected individuals in a trauma-exposed population. Rats were exposed to underwater trauma (UWT) and four weeks later their individual performances in the open field and elevated plus maze were compared to those of the control group, allowing the identification of affected and resilient UWT-exposed rats. Behavioral profiling revealed that only a subset of the UWT-exposed rats developed long-lasting behavioral symptoms. The proportion of affected rats was further enhanced by pre-exposure to juvenile stress, a well-described risk factor of PTSD. For a biochemical proof of concept we analyzed the expression levels of the GABAA receptor subunits α1 and α2 in the ventral, dorsal hippocampus and basolateral amygdala. Increased expression, mainly of α1, was observed in ventral but not dorsal hippocampus of exposed animals, which would traditionally be interpreted as being associated with the exposure-resultant psychopathology. However, behavioral profiling revealed that this increased expression was confined to exposed-unaffected individuals, suggesting a resilience-associated expression regulation. The results provide evidence for the importance of employing behavioral profiling in animal models of PTSD, in order to better understand the neural basis of stress vulnerability and resilience. Copyright © 2016 Elsevier Inc. All rights reserved.

[Preliminary analysis of retinal gene expression profile of diabetic rat].

PubMed

Mei, Yan; Zhou, Hong-ying; Xiang, Tao; Lu, You-guang; Li, Ai-dong; Tang, En-jie; Yang, Hui-jun

2005-10-01

Establishing the retinal gene expression profiles of non-diabetic rat and diabetic rat and comparing the profiles in order to analyze the possible genes related with diabetic retinopathy. The whole retinal transcriptional fragments of non-diabetic rat and 8-week diabetic rat were obtained by restriction fragments differential display-PCR (RFDD-PCR). Bioinformatic analysis of retinal gene expression was performed using soft wares, including Fragment Analysis. After comparison of the expression profiles, the related gene fragments of diabetic retinopathy were initially selected as the target gene of further approach. A total of 3639 significant fragments were obtained. By means of more than 3-fold contrast of fluorescent intensity as the differential expression standard, the authors got 840 differential fragments, accounting for 23.08% of the expressed numbers and including 5 visual related genes, 13 excitatory neruotransmitter genes and 3 inhibitory neurotransmitter genes. At the 8th week, the expression of Rhodopsin kinase, beta-arrestin, Phosducinìrod photoreceptor cGMP-gated channel and Rpe65 as well as iGlu R1-4 were down-regulated. mGluRs and GABA-Rs were all up-regulated, whereas the expression of GlyR was unchanged. These results prompt again that the changes in retinal nervous layer of rat have occurred at an early stage of diabetes. The genes expression pattern of visual related genes and excitatory and inhibitory neurotransmitters in rat diabetic retina have been involved in neuro-dysfunctions of diabetic retina.

Establishment of a New Quality Control and Vaccine Safety Test for Influenza Vaccines and Adjuvants Using Gene Expression Profiling

PubMed Central

Momose, Haruka; Mizukami, Takuo; Kuramitsu, Madoka; Takizawa, Kazuya; Masumi, Atsuko; Araki, Kumiko; Furuhata, Keiko; Yamaguchi, Kazunari; Hamaguchi, Isao

2015-01-01

We have previously identified 17 biomarker genes which were upregulated by whole virion influenza vaccines, and reported that gene expression profiles of these biomarker genes had a good correlation with conventional animal safety tests checking body weight and leukocyte counts. In this study, we have shown that conventional animal tests showed varied and no dose-dependent results in serially diluted bulk materials of influenza HA vaccines. In contrast, dose dependency was clearly shown in the expression profiles of biomarker genes, demonstrating higher sensitivity of gene expression analysis than the current animal safety tests of influenza vaccines. The introduction of branched DNA based-concurrent expression analysis could simplify the complexity of multiple gene expression approach, and could shorten the test period from 7 days to 3 days. Furthermore, upregulation of 10 genes, Zbp1, Mx2, Irf7, Lgals9, Ifi47, Tapbp, Timp1, Trafd1, Psmb9, and Tap2, was seen upon virosomal-adjuvanted vaccine treatment, indicating that these biomarkers could be useful for the safety control of virosomal-adjuvanted vaccines. In summary, profiling biomarker gene expression could be a useful, rapid, and highly sensitive method of animal safety testing compared with conventional methods, and could be used to evaluate the safety of various types of influenza vaccines, including adjuvanted vaccine. PMID:25909814

Ribosome profiling reveals the what, when, where and how of protein synthesis.

PubMed

Brar, Gloria A; Weissman, Jonathan S

2015-11-01

Ribosome profiling, which involves the deep sequencing of ribosome-protected mRNA fragments, is a powerful tool for globally monitoring translation in vivo. The method has facilitated discovery of the regulation of gene expression underlying diverse and complex biological processes, of important aspects of the mechanism of protein synthesis, and even of new proteins, by providing a systematic approach for experimental annotation of coding regions. Here, we introduce the methodology of ribosome profiling and discuss examples in which this approach has been a key factor in guiding biological discovery, including its prominent role in identifying thousands of novel translated short open reading frames and alternative translation products.

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Advancing the use of noncoding RNA in regulatory toxicology: Report of an ECETOC workshop.

PubMed

Aigner, Achim; Buesen, Roland; Gant, Tim; Gooderham, Nigel; Greim, Helmut; Hackermüller, Jörg; Hubesch, Bruno; Laffont, Madeleine; Marczylo, Emma; Meister, Gunter; Petrick, Jay S; Rasoulpour, Reza J; Sauer, Ursula G; Schmidt, Kerstin; Seitz, Hervé; Slack, Frank; Sukata, Tokuo; van der Vies, Saskia M; Verhaert, Jan; Witwer, Kenneth W; Poole, Alan

2016-12-01

The European Centre for the Ecotoxicology and Toxicology of Chemicals (ECETOC) organised a workshop to discuss the state-of-the-art research on noncoding RNAs (ncRNAs) as biomarkers in regulatory toxicology and as analytical and therapeutic agents. There was agreement that ncRNA expression profiling data requires careful evaluation to determine the utility of specific ncRNAs as biomarkers. To advance the use of ncRNA in regulatory toxicology, the following research priorities were identified: (1) Conduct comprehensive literature reviews to identify possibly suitable ncRNAs and areas of toxicology where ncRNA expression profiling could address prevailing scientific deficiencies. (2) Develop consensus on how to conduct ncRNA expression profiling in a toxicological context. (3) Conduct experimental projects, including, e.g., rat (90-day) oral toxicity studies, to evaluate the toxicological relevance of the expression profiles of selected ncRNAs. Thereby, physiological ncRNA expression profiles should be established, including the biological variability of healthy individuals. To substantiate the relevance of key ncRNAs for cell homeostasis or pathogenesis, molecular events should be dose-dependently linked with substance-induced apical effects. Applying a holistic approach, knowledge on ncRNAs, 'omics and epigenetics technologies should be integrated into adverse outcome pathways to improve the understanding of the functional roles of ncRNAs within a regulatory context. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

PubMed

Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

2013-01-01

A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal and reactive cellular mechanisms, transcriptomic changes may thus have future potential in the diagnosis of a wide array of heterogeneous diseases that result from genetic disturbances.

In vivo Assessment and Potential Diagnosis of Xenobiotics that Perturb the Thyroid Pathway: Proteomic Analysis of Xenopus laevis Brain Tissue following Exposure to Model T4 Inhibitors

EPA Science Inventory

As part of a multi-endpoint systems approach to develop comprehensive methods for assessing endocrine stressors in vertebrates, differential protein profiling was used to investigate expression profiles in the brain of an amphibian model (Xenopus laevis) following in vivo exposur...

Computational Prediction and Validation of BAHD1 as a Novel Molecule for Ulcerative Colitis

NASA Astrophysics Data System (ADS)

Zhu, Huatuo; Wan, Xingyong; Li, Jing; Han, Lu; Bo, Xiaochen; Chen, Wenguo; Lu, Chao; Shen, Zhe; Xu, Chenfu; Chen, Lihua; Yu, Chaohui; Xu, Guoqiang

2015-07-01

Ulcerative colitis (UC) is a common inflammatory bowel disease (IBD) producing intestinal inflammation and tissue damage. The precise aetiology of UC remains unknown. In this study, we applied a rank-based expression profile comparative algorithm, gene set enrichment analysis (GSEA), to evaluate the expression profiles of UC patients and small interfering RNA (siRNA)-perturbed cells to predict proteins that might be essential in UC from publicly available expression profiles. We used quantitative PCR (qPCR) to characterize the expression levels of those genes predicted to be the most important for UC in dextran sodium sulphate (DSS)-induced colitic mice. We found that bromo-adjacent homology domain (BAHD1), a novel heterochromatinization factor in vertebrates, was the most downregulated gene. We further validated a potential role of BAHD1 as a regulatory factor for inflammation through the TNF signalling pathway in vitro. Our findings indicate that computational approaches leveraging public gene expression data can be used to infer potential genes or proteins for diseases, and BAHD1 might act as an indispensable factor in regulating the cellular inflammatory response in UC.

Benzoate-mediated changes on expression profile of soluble proteins in Serratia sp. DS001.

PubMed

Pandeeti, E V P; Chinnaboina, M R; Siddavattam, D

2009-05-01

To assess differences in protein expression profile associated with shift in carbon source from succinate to benzoate in Serratia sp. DS001 using a proteomics approach. A basic proteome map was generated for the soluble proteins extracted from Serratia sp. DS001 grown in succinate and benzoate. The differently and differentially expressed proteins were identified using ImageMaster 2D Platinum software (GE Healthcare). The identity of the proteins was determined by employing MS or MS/MS. Important enzymes such as Catechol 1,2 dioxygenase and transcriptional regulators that belong to the LysR superfamily were identified. Nearly 70 proteins were found to be differentially expressed when benzoate was used as carbon source. Based on the protein identity and degradation products generated from benzoate it is found that ortho pathway is operational in Serratia sp. DS001. Expression profile of the soluble proteins associated with shift in carbon source was mapped. The study also elucidates degradation pathway of benzoate in Serratia sp. DS001 by correlating the proteomics data with the catabolites of benzoate.

Gene-expression profiling for rejection surveillance after cardiac transplantation.

PubMed

Pham, Michael X; Teuteberg, Jeffrey J; Kfoury, Abdallah G; Starling, Randall C; Deng, Mario C; Cappola, Thomas P; Kao, Andrew; Anderson, Allen S; Cotts, William G; Ewald, Gregory A; Baran, David A; Bogaev, Roberta C; Elashoff, Barbara; Baron, Helen; Yee, James; Valantine, Hannah A

2010-05-20

Endomyocardial biopsy is the standard method of monitoring for rejection in recipients of a cardiac transplant. However, this procedure is uncomfortable, and there are risks associated with it. Gene-expression profiling of peripheral-blood specimens has been shown to correlate with the results of an endomyocardial biopsy. We randomly assigned 602 patients who had undergone cardiac transplantation 6 months to 5 years previously to be monitored for rejection with the use of gene-expression profiling or with the use of routine endomyocardial biopsies, in addition to clinical and echocardiographic assessment of graft function. We performed a noninferiority comparison of the two approaches with respect to the composite primary outcome of rejection with hemodynamic compromise, graft dysfunction due to other causes, death, or retransplantation. During a median follow-up period of 19 months, patients who were monitored with gene-expression profiling and those who underwent routine biopsies had similar 2-year cumulative rates of the composite primary outcome (14.5% and 15.3%, respectively; hazard ratio with gene-expression profiling, 1.04; 95% confidence interval, 0.67 to 1.68). The 2-year rates of death from any cause were also similar in the two groups (6.3% and 5.5%, respectively; P=0.82). Patients who were monitored with the use of gene-expression profiling underwent fewer biopsies per person-year of follow-up than did patients who were monitored with the use of endomyocardial biopsies (0.5 vs. 3.0, P<0.001). Among selected patients who had received a cardiac transplant more than 6 months previously and who were at a low risk for rejection, a strategy of monitoring for rejection that involved gene-expression profiling, as compared with routine biopsies, was not associated with an increased risk of serious adverse outcomes and resulted in the performance of significantly fewer biopsies. (ClinicalTrials.gov number, NCT00351559.) 2010 Massachusetts Medical Society

Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

PubMed

Brogden, Kim A; Parashar, Deepak; Hallier, Andrea R; Braun, Terry; Qian, Fang; Rizvi, Naiyer A; Bossler, Aaron D; Milhem, Mohammed M; Chan, Timothy A; Abbasi, Taher; Vali, Shireen

2018-02-27

Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.

Gene expression profiling of intestinal regeneration in the sea cucumber

PubMed Central

Ortiz-Pineda, Pablo A; Ramírez-Gómez, Francisco; Pérez-Ortiz, Judit; González-Díaz, Sebastián; Santiago-De Jesús, Francisco; Hernández-Pasos, Josue; Del Valle-Avila, Cristina; Rojas-Cartagena, Carmencita; Suárez-Castillo, Edna C; Tossas, Karen; Méndez-Merced, Ana T; Roig-López, José L; Ortiz-Zuazaga, Humberto; García-Arrarás, José E

2009-01-01

Background Among deuterostomes, the regenerative potential is maximally expressed in echinoderms, animals that can quickly replace most injured organs. In particular, sea cucumbers are excellent models for studying organ regeneration since they regenerate their digestive tract after evisceration. However, echinoderms have been sidelined in modern regeneration studies partially because of the lack of genome-wide profiling approaches afforded by modern genomic tools. For the last decade, our laboratory has been using the sea cucumber Holothuria glaberrima to dissect the cellular and molecular events that allow for such amazing regenerative processes. We have already established an EST database obtained from cDNA libraries of normal and regenerating intestine at two different regeneration stages. This database now has over 7000 sequences. Results In the present work we used a custom-made microchip from Agilent with 60-mer probes for these ESTs, to determine the gene expression profile during intestinal regeneration. Here we compared the expression profile of animals at three different intestinal regeneration stages (3-, 7- and 14-days post evisceration) against the profile from normal (uneviscerated) intestines. The number of differentially expressed probes ranged from 70% at p < 0.05 to 39% at p < 0.001. Clustering analyses show specific profiles of expression for early (first week) and late (second week) regeneration stages. We used semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) to validate the expression profile of fifteen microarray detected differentially expressed genes which resulted in over 86% concordance between both techniques. Most of the differentially expressed ESTs showed no clear similarity to sequences in the databases and might represent novel genes associated with regeneration. However, other ESTs were similar to genes known to be involved in regeneration-related processes, wound healing, cell proliferation, differentiation, morphological plasticity, cell survival, stress response, immune challenge, and neoplastic transformation. Among those that have been validated, cytoskeletal genes, such as actins, and developmental genes, such as Wnt and Hox genes, show interesting expression profiles during regeneration. Conclusion Our findings set the base for future studies into the molecular basis of intestinal regeneration. Moreover, it advances the use of echinoderms in regenerative biology, animals that because of their amazing properties and their key evolutionary position, might provide important clues to the genetic basis of regenerative processes. PMID:19505337

Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis.

PubMed

Fujita, André; Sato, João Ricardo; Demasi, Marcos Angelo Almeida; Sogayar, Mari Cleide; Ferreira, Carlos Eduardo; Miyano, Satoru

2009-08-01

DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association approaches, namely Pearson's correlation, Spearman's correlation and Hoeffding's D measure, we aimed at assessing the most appropriate one for each purpose. Using simulations, we demonstrate that the Hoeffding's D measure outperforms Pearson's and Spearman's approaches in identifying nonlinear associations. Our results demonstrate that Hoeffding's D measure is less sensitive to outliers and is a more powerful tool to identify nonlinear and non-monotonic associations. We have also applied Hoeffding's D measure in order to identify new putative genes associated with tp53. Therefore, we propose the Hoeffding's D measure to identify nonlinear associations between gene expression profiles.

Functional discovery via a compendium of expression profiles.

PubMed

Hughes, T R; Marton, M J; Jones, A R; Roberts, C J; Stoughton, R; Armour, C D; Bennett, H A; Coffey, E; Dai, H; He, Y D; Kidd, M J; King, A M; Meyer, M R; Slade, D; Lum, P Y; Stepaniants, S B; Shoemaker, D D; Gachotte, D; Chakraburtty, K; Simon, J; Bard, M; Friend, S H

2000-07-07

Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.

Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes

PubMed Central

Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia

2007-01-01

Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544

PmiRExAt: plant miRNA expression atlas database and web applications

PubMed Central

Gurjar, Anoop Kishor Singh; Panwar, Abhijeet Singh; Gupta, Rajinder; Mantri, Shrikant S.

2016-01-01

High-throughput small RNA (sRNA) sequencing technology enables an entirely new perspective for plant microRNA (miRNA) research and has immense potential to unravel regulatory networks. Novel insights gained through data mining in publically available rich resource of sRNA data will help in designing biotechnology-based approaches for crop improvement to enhance plant yield and nutritional value. Bioinformatics resources enabling meta-analysis of miRNA expression across multiple plant species are still evolving. Here, we report PmiRExAt, a new online database resource that caters plant miRNA expression atlas. The web-based repository comprises of miRNA expression profile and query tool for 1859 wheat, 2330 rice and 283 maize miRNA. The database interface offers open and easy access to miRNA expression profile and helps in identifying tissue preferential, differential and constitutively expressing miRNAs. A feature enabling expression study of conserved miRNA across multiple species is also implemented. Custom expression analysis feature enables expression analysis of novel miRNA in total 117 datasets. New sRNA dataset can also be uploaded for analysing miRNA expression profiles for 73 plant species. PmiRExAt application program interface, a simple object access protocol web service allows other programmers to remotely invoke the methods written for doing programmatic search operations on PmiRExAt database. Database URL: http://pmirexat.nabi.res.in. PMID:27081157

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

Genetic validation of whole-transcriptome sequencing for mapping expression affected by cis-regulatory variation

PubMed Central

2010-01-01

Background Identifying associations between genotypes and gene expression levels using microarrays has enabled systematic interrogation of regulatory variation underlying complex phenotypes. This approach has vast potential for functional characterization of disease states, but its prohibitive cost, given hundreds to thousands of individual samples from populations have to be genotyped and expression profiled, has limited its widespread application. Results Here we demonstrate that genomic regions with allele-specific expression (ASE) detected by sequencing cDNA are highly enriched for cis-acting expression quantitative trait loci (cis-eQTL) identified by profiling of 500 animals in parallel, with up to 90% agreement on the allele that is preferentially expressed. We also observed widespread noncoding and antisense ASE and identified several allele-specific alternative splicing variants. Conclusion Monitoring ASE by sequencing cDNA from as little as one sample is a practical alternative to expression genetics for mapping cis-acting variation that regulates RNA transcription and processing. PMID:20707912

A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy.

PubMed

Gillet, Jean-Pierre; Andersen, Jesper B; Madigan, James P; Varma, Sudhir; Bagni, Rachel K; Powell, Katie; Burgan, William E; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V; Thorgeirsson, Snorri S; Gottesman, Michael M

2016-02-01

Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. U.S. Government work not protected by U.S. copyright.

Validation of the β-amy1 transcription profiling assay and selection of reference genes suited for a RT-qPCR assay in developing barley caryopsis.

PubMed

Ovesná, Jaroslava; Kučera, Ladislav; Vaculová, Kateřina; Štrymplová, Kamila; Svobodová, Ilona; Milella, Luigi

2012-01-01

Reverse transcription coupled with real-time quantitative PCR (RT-qPCR) is a frequently used method for gene expression profiling. Reference genes (RGs) are commonly employed to normalize gene expression data. A limited information exist on the gene expression and profiling in developing barley caryopsis. Expression stability was assessed by measuring the cycle threshold (Ct) range and applying both the GeNorm (pair-wise comparison of geometric means) and Normfinder (model-based approach) principles for the calculation. Here, we have identified a set of four RGs suitable for studying gene expression in the developing barley caryopsis. These encode the proteins GAPDH, HSP90, HSP70 and ubiquitin. We found a correlation between the frequency of occurrence of a transcript in silico and its suitability as an RG. This set of RGs was tested by comparing the normalized level of β-amylase (β-amy1) transcript with directly measured quantities of the BMY1 gene product in the developing barley caryopsis. This panel of genes could be used for other gene expression studies, as well as to optimize β-amy1 analysis for study of the impact of β-amy1 expression upon barley end-use quality.

Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.

PubMed

Cox, Amanda J; Zhang, Ping; Evans, Tiffany J; Scott, Rodney J; Cripps, Allan W; West, Nicholas P

Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n=21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n=11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p<0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p<0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10 -8 ; AUC: 0.909, CR: 72.7%). These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Immunological network signatures of cancer progression and survival

PubMed Central

2011-01-01

Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides. PMID:21453479

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Unsupervised Outlier Profile Analysis

PubMed Central

Ghosh, Debashis; Li, Song

2014-01-01

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study. PMID:25452686

Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis

PubMed Central

Akilesh, Shreeram; Shaffer, Daniel J.; Roopenian, Derry

2003-01-01

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm—Global Pattern Recognition—to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes. PMID:12840047

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms.

PubMed

Milnthorpe, Andrew T; Soloviev, Mikhail

2011-04-15

The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used.

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

PubMed Central

2011-01-01

Background The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. Results We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Conclusion Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used. PMID:21496233

Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes Using HMMs and Hierarchical Bayesian Modeling Approaches.

PubMed

Oh, Sunghee; Song, Seongho

2017-01-01

In gene expression profile, data analysis pipeline is categorized into four levels, major downstream tasks, i.e., (1) identification of differential expression; (2) clustering co-expression patterns; (3) classification of subtypes of samples; and (4) detection of genetic regulatory networks, are performed posterior to preprocessing procedure such as normalization techniques. To be more specific, temporal dynamic gene expression data has its inherent feature, namely, two neighboring time points (previous and current state) are highly correlated with each other, compared to static expression data which samples are assumed as independent individuals. In this chapter, we demonstrate how HMMs and hierarchical Bayesian modeling methods capture the horizontal time dependency structures in time series expression profiles by focusing on the identification of differential expression. In addition, those differential expression genes and transcript variant isoforms over time detected in core prerequisite steps can be generally further applied in detection of genetic regulatory networks to comprehensively uncover dynamic repertoires in the aspects of system biology as the coupled framework.

A cell-based systems biology assessment of human blood to monitor immune responses after influenza vaccination.

PubMed

Hoek, Kristen L; Samir, Parimal; Howard, Leigh M; Niu, Xinnan; Prasad, Nripesh; Galassie, Allison; Liu, Qi; Allos, Tara M; Floyd, Kyle A; Guo, Yan; Shyr, Yu; Levy, Shawn E; Joyce, Sebastian; Edwards, Kathryn M; Link, Andrew J

2015-01-01

Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.

Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.

PubMed

Zheng, Yu-Jun; Sheng, Wei-Guo; Sun, Xing-Ming; Chen, Sheng-Yong

2017-12-01

Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profiling. The center of our approach is a Pythagorean fuzzy deep Boltzmann machine (PFDBM), whose parameters are expressed by Pythagorean fuzzy numbers such that each neuron can learn how a feature affects the production of the correct output from both the positive and negative sides. We propose a hybrid algorithm combining a gradient-based method and an evolutionary algorithm for training the PFDBM. Based on the novel learning model, we develop a deep neural network (DNN) for classifying normal passengers and potential attackers, and further develop an integrated DNN for identifying group attackers whose individual features are insufficient to reveal the abnormality. Experiments on data sets from Air China show that our approach provides much higher learning ability and classification accuracy than existing profilers. It is expected that the fuzzy deep learning approach can be adapted for a variety of complex pattern analysis tasks.

A Systematic Approach to Time-series Metabolite Profiling and RNA-seq Analysis of Chinese Hamster Ovary Cell Culture.

PubMed

Hsu, Han-Hsiu; Araki, Michihiro; Mochizuki, Masao; Hori, Yoshimi; Murata, Masahiro; Kahar, Prihardi; Yoshida, Takanobu; Hasunuma, Tomohisa; Kondo, Akihiko

2017-03-02

Chinese hamster ovary (CHO) cells are the primary host used for biopharmaceutical protein production. The engineering of CHO cells to produce higher amounts of biopharmaceuticals has been highly dependent on empirical approaches, but recent high-throughput "omics" methods are changing the situation in a rational manner. Omics data analyses using gene expression or metabolite profiling make it possible to identify key genes and metabolites in antibody production. Systematic omics approaches using different types of time-series data are expected to further enhance understanding of cellular behaviours and molecular networks for rational design of CHO cells. This study developed a systematic method for obtaining and analysing time-dependent intracellular and extracellular metabolite profiles, RNA-seq data (enzymatic mRNA levels) and cell counts from CHO cell cultures to capture an overall view of the CHO central metabolic pathway (CMP). We then calculated correlation coefficients among all the profiles and visualised the whole CMP by heatmap analysis and metabolic pathway mapping, to classify genes and metabolites together. This approach provides an efficient platform to identify key genes and metabolites in CHO cell culture.

Informative Top-k Retrieval for Advanced Skill Management

NASA Astrophysics Data System (ADS)

Colucci, Simona; di Noia, Tommaso; Ragone, Azzurra; Ruta, Michele; Straccia, Umberto; Tinelli, Eufemia

The paper presents a knowledge-based framework for skills and talent management based on an advanced matchmaking between profiles of candidates and available job positions. Interestingly, informative content of top-k retrieval is enriched through semantic capabilities. The proposed approach allows to: (1) express a requested profile in terms of both hard constraints and soft ones; (2) provide a ranking function based also on qualitative attributes of a profile; (3) explain the resulting outcomes (given a job request, a motivation for the obtained score of each selected profile is provided). Top-k retrieval allows to select most promising candidates according to an ontology formalizing the domain knowledge. Such a knowledge is further exploited to provide a semantic-based explanation of missing or conflicting features in retrieved profiles. They also indicate additional profile characteristics emerging by the retrieval procedure for a further request refinement. A concrete case study followed by an exhaustive experimental campaign is reported to prove the approach effectiveness.

Prediction of the acoustic pressure above periodically uneven facings in industrial workplaces

NASA Astrophysics Data System (ADS)

Ducourneau, J.; Bos, L.; Planeau, V.; Faiz, Adil; Skali Lami, Salah; Nejade, A.

2010-05-01

The aim of this work is to predict sound pressure in front of wall facings based on periodic sound scattering surface profiles. The method involves investigating plane wave reflections randomly incident upon an uneven surface. The waveguide approach is well suited to the geometries usually encountered in industrial workplaces. This method simplifies the profile geometry by using elementary rectangular volumes. The acoustic field in the profile interstices can then be expressed as the superposition of waveguide modes. In past work, walls considered are of infinite dimensions and are subjected to a periodic surface profile in only one direction. We therefore generalise this approach by extending its applicability to "double-periodic" wall facings. Free-field measurements have been taken and the observed agreement between numerical and experimental results supports the validity of the waveguide method.

Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

PubMed

Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

2015-11-01

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional clustering of time series gene expression data by Granger causality

PubMed Central

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Identifying antimalarial compounds targeting dihydrofolate reductase-thymidylate synthase (DHFR-TS) by chemogenomic profiling.

PubMed

Aroonsri, Aiyada; Akinola, Olugbenga; Posayapisit, Navaporn; Songsungthong, Warangkhana; Uthaipibull, Chairat; Kamchonwongpaisan, Sumalee; Gbotosho, Grace O; Yuthavong, Yongyuth; Shaw, Philip J

2016-07-01

The mode of action of many antimalarial drugs is unknown. Chemogenomic profiling is a powerful method to address this issue. This experimental approach entails disruption of gene function and phenotypic screening for changes in sensitivity to bioactive compounds. Here, we describe the application of reverse genetics for chemogenomic profiling in Plasmodium. Plasmodium falciparum parasites harbouring a transgenic insertion of the glmS ribozyme downstream of the dihydrofolate reductase-thymidylate synthase (DHFR-TS) gene were used for chemogenomic profiling of antimalarial compounds to identify those which target DHFR-TS. DHFR-TS expression can be attenuated by exposing parasites to glucosamine. Parasites with attenuated DHFR-TS expression were significantly more sensitive to antifolate drugs known to target DHFR-TS. In contrast, no change in sensitivity to other antimalarial drugs with different modes of action was observed. Chemogenomic profiling was performed using the Medicines for Malaria Venture (Switzerland) Malaria Box compound library, and two compounds were identified as novel DHFR-TS inhibitors. We also tested the glmS ribozyme in Plasmodium berghei, a rodent malaria parasite. The expression of reporter genes with downstream glmS ribozyme could be attenuated in transgenic parasites comparable with that obtained in P. falciparum. The chemogenomic profiling method was applied in a P. berghei line expressing a pyrimethamine-resistant Toxoplasma gondii DHFR-TS reporter gene under glmS ribozyme control. Parasites with attenuated expression of this gene were significantly sensitised to antifolates targeting DHFR-TS, but not other drugs with different modes of action. In conclusion, these data show that the glmS ribozyme reverse genetic tool can be applied for identifying primary targets of antimalarial compounds in human and rodent malaria parasites. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.

Evidence for the importance of personalized molecular profiling in pancreatic cancer.

PubMed

Lili, Loukia N; Matyunina, Lilya V; Walker, L DeEtte; Daneker, George W; McDonald, John F

2014-03-01

There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses. In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses. We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses. Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

PubMed

Martini, Paolo; Risso, Davide; Sales, Gabriele; Romualdi, Chiara; Lanfranchi, Gerolamo; Cagnin, Stefano

2011-04-11

In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets. We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach). In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies. STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.

Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.

PubMed

Bourdon-Lacombe, Julie A; Moffat, Ivy D; Deveau, Michelle; Husain, Mainul; Auerbach, Scott; Krewski, Daniel; Thomas, Russell S; Bushel, Pierre R; Williams, Andrew; Yauk, Carole L

2015-07-01

Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Comparative transcriptional profiling identifies takeout as a gene that regulates life span

PubMed Central

Bauer, Johannes; Antosh, Michael; Chang, Chengyi; Schorl, Christoph; Kolli, Santharam; Neretti, Nicola; Helfand, Stephen L.

2010-01-01

A major challenge in translating the positive effects of dietary restriction (DR) for the improvement of human health is the development of therapeutic mimics. One approach to finding DR mimics is based upon identification of the proximal effectors of DR life span extension. Whole genome profiling of DR in Drosophila shows a large number of changes in gene expression, making it difficult to establish which changes are involved in life span determination as opposed to other unrelated physiological changes. We used comparative whole genome expression profiling to discover genes whose change in expression is shared between DR and two molecular genetic life span extending interventions related to DR, increased dSir2 and decreased Dmp53 activity. We find twenty-one genes shared among the three related life span extending interventions. One of these genes, takeout, thought to be involved in circadian rhythms, feeding behavior and juvenile hormone binding is also increased in four other life span extending conditions: Rpd3, Indy, chico and methuselah. We demonstrate takeout is involved in longevity determination by specifically increasing adult takeout expression and extending life span. These studies demonstrate the power of comparative whole genome transcriptional profiling for identifying specific downstream elements of the DR life span extending pathway. PMID:20519778

RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.

PubMed

Schäfer, Reinhold; Sers, Christine

2011-01-01

Transcriptome analysis of cancer cells has developed into a standard procedure to elucidate multiple features of the malignant process and to link gene expression to clinical properties. Gene expression profiling based on microarrays provides essentially correlative information and needs to be transferred to the functional level in order to understand the activity and contribution of individual genes or sets of genes as elements of the gene signature. To date, there exist significant gaps in the functional understanding of gene expression profiles. Moreover, the processes that drive the profound transcriptional alterations that characterize cancer cells remain mainly elusive. We have used pathway-restricted gene expression profiles derived from RAS oncogene-transformed cells and from RAS-expressing cancer cells to identify regulators downstream of the MAPK pathway.We describe the role of epigenetic regulation exemplified by the control of several immune genes in generic cell lines and colorectal cancer cells, particularly the functional interaction between signaling and DNA methylation. Moreover, we assess the role of the architectural transcription factor high mobility AT-hook 2 (HMGA2) as a regulator of the RAS-responsive transcriptome in ovarian epithelial cells. Finally, we describe an integrated approach combining pathway interference in colorectal cancer cells, gene expression profiling and computational analysis of regulatory elements of deregulated target genes. This strategy resulted in the identification of Y-box binding protein 1 (YBX1) as a regulator of MAPK-dependent proliferation and gene expression. The implications for a therapeutic application of HMGA2 gene silencing and the role of YBX1 as a prognostic factor are discussed.

Studying the MicroRNA role as a survival predictor and revealing its part in malignancy level determination in patients with supratentorial gliomas of brain

NASA Astrophysics Data System (ADS)

Stupak, E. V.; Veryaskina, Yu. A.; Titov, S. E.; Achmerova, L. G.; Stupak, V. V.; Dolzhenko, D. A.; Rabinovich, S. S.; Narodov, A. A.; Ivanov, M. K.; Zhimulev, I. F.; Kolesnikov, N. N.

2017-09-01

The numerous data show, that microRNA (miRNA) are direct participants of carcinogenesis. Also miRNA plays the role of a diagnostic and prognostic marker for different types of cancer, including gliomas. The aim of this research is to make the comparative analysis of 10 micro RNA (miR-124, -125b, -16, -181b, -191, -21, -221, -223, -31 and -451) expression profiles. The analysis was made for gliomas with different malignancy degree, then compared with the samples of the adjacent not changed tissues (n = 90). During the study the specific profiles of miRNA expression for various histotypes of tumors were revealed. It was determined, that miRNA acts as a predictor of patient survival in the cases with malignant supratentorial brain tumors. The diagnostic approaches based on miRNA expression profile were designed. It will help to determine the malignancy level and to predict the course of the disease.

Bayesian approach to transforming public gene expression repositories into disease diagnosis databases.

PubMed

Huang, Haiyan; Liu, Chun-Chi; Zhou, Xianghong Jasmine

2010-04-13

The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also demonstrated that the power of our method can increase significantly with the continued growth of public gene expression repositories. Finally, we showed how our disease diagnosis system can be used to characterize complex phenotypes and to construct a disease-drug connectivity map.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921

Feasibility of the AML profiler (Skyline™ Array) for patient risk stratification in a multicentre trial: a preliminary comparison with the conventional approach.

PubMed

Nomdedéu, Josep F; Puigdecanet, Eulalia; Bussaglia, Elena; Hernández, Juan José; Carricondo, Maite; Estivill, Camino; Martí-Tutusaus, Josep Maria; Tormo, Mar; Zamora, Lurdes; Serrano, Elena; Perea, Granada; de Llano, Maria Paz Queipo; García, Antoni; Sánchez-Ortega, Isabel; Ribera, Josep Maria; Nonell, Lara; Aventin, Anna; Solé, Francesc; Brunet, Maria Salut; Sierra, Jorge

2017-12-01

Deoxyribonucleic acid microarrays allow researchers to measure mRNA levels of thousands of genes in a single experiment and could be useful for diagnostic purposes in patients with acute myeloid leukaemia (AML). We assessed the feasibility of the AML profiler (Skyline™ Array) in genetic stratification of patients with de novo AML and compared the results with those obtained using the standard cytogenetic and molecular approach. Diagnostic bone marrow from 31 consecutive de novo AML cases was used to test MLL-PTD, FLT3-ITD and TKD, NPM1 and CEBPAdm mutations. Purified RNA was used to assess RUNX1-RUNX1T1, PML-RARα and CBFβ-MYH11 rearrangements. RNA remnants underwent gene expression profiling analysis using the AML profiler, which detects chromosomal aberrations: t(8;21), t(15;17), inv(16), mutations (CEBPAdm, ABD-NPM1) and BAALC and EVI1 expression. Thirty cases were successfully analysed with both methods. Five cases had FLT3-ITD. In one case, a t(8;21) was correctly detected by both methods. Four cases had inv(16); in one, the RNA quality was unsatisfactory and it was not hybridized, and in the other three, the AML profiler detected the genetic lesion - this being a rare type I translocation in one case. Two cases with acute promyelocytic leukaemia were diagnosed by both methods. Results for NPM1 mutations were concordant in all but two cases (2/11, non-ABD mutations). Analysis of costs and turnaround times showed that the AML profiler was no more expensive than the conventional molecular approach. These results suggest that the AML profiler could be useful in multicentre trials to rapidly identify patients with AML with a good prognosis. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Genome-wide identification and expression profiling of dehydrin gene family in Malus domestica.

PubMed

Liang, Dong; Xia, Hui; Wu, Shan; Ma, Fengwang

2012-12-01

The family of dehydrin genes has important roles in protecting higher plants against abiotic stress, such as drought, salinity and cold. However, knowledge about apple dehydrin gene family is limited. In the present study, we used a bioinformatics approach to identify members of that family in apple (Malus domestica). A total of 12 apple dehydrin genes (MdDHNs) were identified and located on various chromosomes. All putative proteins from those genes contained a typical K domain. Among 12 MdDHNs, nine were cloned and their expression patterns were investigated. Expression profiling indicated that the these nine dehydrin genes display differential expression patterns in various tissues. Moreover, transcript levels of some MdDHNs were up-regulated significantly under drought, low temperature, or ABA treatment, which indicated their important roles during stress adaptation. These results demonstrate that the apple dehydrin gene family may function in tissue development and plant stress responses.

Two-pass imputation algorithm for missing value estimation in gene expression time series.

PubMed

Tsiporkova, Elena; Boeva, Veselka

2007-10-01

Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different initial rough imputation methods.

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Analysis of differential gene expression by bead-based fiber-optic array in nonfunctioning pituitary adenomas.

PubMed

Jiang, Z; Gui, S; Zhang, Y

2011-05-01

Nonfunctioning pituitary adenomas (NFPAs) are relatively common, accounting for 30% of all pituitary adenomas; however, their pathogenesis remains enigmatic. To explore the possible pathogenesis of NFPAs, we used fiber-optic BeadArray to examine gene expression in 5 NFPAs compared with 3 normal pituitaries. 4 differentially expressed genes were chosen randomly for validation by reverse transcriptase-real time quantitative polymerase chain reaction (RT-qPCR). We then analyzed the differentially expressed gene profile with Kyoto Encyclopedia of Genes and Genomes (KEGG). The array analysis indentified significant increases in the expression of 1,402 genes and 383 expressed sequence tags (ESTs), and decreases in 1,697 genes and 113 ESTs in the NFPAs. Bioinformatic and pathway analysis showed that the genes HIGD1B, FAM5C, PMAIP1 and the pathway cell-cycle regulation may play an important role in tumorigenesis and progression of NFPAs. Our data suggest fiber-optic BeadArray combined with pathway analysis of differential gene expression profile appears to be a valid approach for investigating the pathogenesis of tumors. © Georg Thieme Verlag KG Stuttgart · New York.

Development of a tissue-specific ribosome profiling approach in Drosophila enables genome-wide evaluation of translational adaptations

PubMed Central

2017-01-01

Recent advances in next-generation sequencing approaches have revolutionized our understanding of transcriptional expression in diverse systems. However, measurements of transcription do not necessarily reflect gene translation, the process of ultimate importance in understanding cellular function. To circumvent this limitation, biochemical tagging of ribosome subunits to isolate ribosome-associated mRNA has been developed. However, this approach, called TRAP, lacks quantitative resolution compared to a superior technology, ribosome profiling. Here, we report the development of an optimized ribosome profiling approach in Drosophila. We first demonstrate successful ribosome profiling from a specific tissue, larval muscle, with enhanced resolution compared to conventional TRAP approaches. We next validate the ability of this technology to define genome-wide translational regulation. This technology is leveraged to test the relative contributions of transcriptional and translational mechanisms in the postsynaptic muscle that orchestrate the retrograde control of presynaptic function at the neuromuscular junction. Surprisingly, we find no evidence that significant changes in the transcription or translation of specific genes are necessary to enable retrograde homeostatic signaling, implying that post-translational mechanisms ultimately gate instructive retrograde communication. Finally, we show that a global increase in translation induces adaptive responses in both transcription and translation of protein chaperones and degradation factors to promote cellular proteostasis. Together, this development and validation of tissue-specific ribosome profiling enables sensitive and specific analysis of translation in Drosophila. PMID:29194454

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues

PubMed Central

Pao, Sheng-Ying; Lin, Win-Li; Hwang, Ming-Jing

2006-01-01

Background Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. Results To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. Conclusion Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website , for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes. PMID:16626500

IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

EPA Science Inventory

Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

PubMed Central

Furge, Kyle A; Dykema, Karl; Petillo, David; Westphal, Michael; Zhang, Zhongfa; Kort, Eric J; Teh, Bin Tean

2007-01-01

Using high-throughput gene-expression profiling technology, we can now gain a better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup of the cancer cells. This abnormal genetic makeup can have profound effects on cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeutic agents and radiation. These approaches will lead to better molecular subclassification of tumours, the basis of personalized medicine. We have, to date, done whole-genome microarray gene-expression profiling on several hundreds of kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used to identify both cytogenetic abnormalities and molecular pathways that are deregulated in renal cell carcinoma (RCC). For example, we have identified the deregulation of the VHL-hypoxia pathway in clear-cell RCC, as previously known, and the c-Myc pathway in aggressive papillary RCC. Besides the more common clear-cell, papillary and chromophobe RCCs, we are currently characterizing the molecular signatures of rarer forms of renal neoplasia such as carcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosome Xp11 translocations associated with papillary RCC, renal medullary carcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response. PMID:18542781

Small RNA-based prediction of hybrid performance in maize.

PubMed

Seifert, Felix; Thiemann, Alexander; Schrag, Tobias A; Rybka, Dominika; Melchinger, Albrecht E; Frisch, Matthias; Scholten, Stefan

2018-05-21

Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program. Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics. Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.

Genome-wide expression profiling of five mouse models identifies similarities and differences with human psoriasis.

PubMed

Swindell, William R; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P; Voorhees, John J; Elder, James T; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P; DiGiovanni, John; Pittelkow, Mark R; Ward, Nicole L; Gudjonsson, Johann E

2011-04-04

Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis.

A focused microarray approach to functional glycomics: transcriptional regulation of the glycome.

PubMed

Comelli, Elena M; Head, Steven R; Gilmartin, Tim; Whisenant, Thomas; Haslam, Stuart M; North, Simon J; Wong, Nyet-Kui; Kudo, Takashi; Narimatsu, Hisashi; Esko, Jeffrey D; Drickamer, Kurt; Dell, Anne; Paulson, James C

2006-02-01

Glycosylation is the most common posttranslational modification of proteins, yet genes relevant to the synthesis of glycan structures and function are incompletely represented and poorly annotated on the commercially available arrays. To fill the need for expression analysis of such genes, we employed the Affymetrix technology to develop a focused and highly annotated glycogene-chip representing human and murine glycogenes, including glycosyltransferases, nucleotide sugar transporters, glycosidases, proteoglycans, and glycan-binding proteins. In this report, the array has been used to generate glycogene-expression profiles of nine murine tissues. Global analysis with a hierarchical clustering algorithm reveals that expression profiles in immune tissues (thymus [THY], spleen [SPL], lymph node, and bone marrow [BM]) are more closely related, relative to those of nonimmune tissues (kidney [KID], liver [LIV], brain [BRN], and testes [TES]). Of the biosynthetic enzymes, those responsible for synthesis of the core regions of N- and O-linked oligosaccharides are ubiquitously expressed, whereas glycosyltransferases that elaborate terminal structures are expressed in a highly tissue-specific manner, accounting for tissue and ultimately cell-type-specific glycosylation. Comparison of gene expression profiles with matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) profiling of N-linked oligosaccharides suggested that the alpha1-3 fucosyltransferase 9, Fut9, is the enzyme responsible for terminal fucosylation in KID and BRN, a finding validated by analysis of Fut9 knockout mice. Two families of glycan-binding proteins, C-type lectins and Siglecs, are predominately expressed in the immune tissues, consistent with their emerging functions in both innate and acquired immunity. The glycogene chip reported in this study is available to the scientific community through the Consortium for Functional Glycomics (CFG) (http://www.functionalglycomics.org).

Modulation of intestinal gene expression by dietary zinc status: Effectiveness of cDNA arrays for expression profiling of a single nutrient deficiency

PubMed Central

Blanchard, Raymond K.; Moore, J. Bernadette; Green, Calvert L.; Cousins, Robert J.

2001-01-01

Mammalian nutritional status affects the homeostatic balance of multiple physiological processes and their associated gene expression. Although DNA array analysis can monitor large numbers of genes, there are no reports of expression profiling of a micronutrient deficiency in an intact animal system. In this report, we have tested the feasibility of using cDNA arrays to compare the global changes in expression of genes of known function that occur in the early stages of rodent zinc deficiency. The gene-modulating effects of this deficiency were demonstrated by real-time quantitative PCR measurements of altered mRNA levels for metallothionein 1, zinc transporter 2, and uroguanylin, all of which have been previously documented as zinc-regulated genes. As a result of the low level of inherent noise within this model system and application of a recently reported statistical tool for statistical analysis of microarrays [Tusher, V.G., Tibshirani, R. & Chu, G. (2001) Proc. Natl. Acad. Sci. USA 98, 5116–5121], we demonstrate the ability to reproducibly identify the modest changes in mRNA abundance produced by this single micronutrient deficiency. Among the genes identified by this array profile are intestinal genes that influence signaling pathways, growth, transcription, redox, and energy utilization. Additionally, the influence of dietary zinc supply on the expression of some of these genes was confirmed by real-time quantitative PCR. Overall, these data support the effectiveness of cDNA array expression profiling to investigate the pleiotropic effects of specific nutrients and may provide an approach to establishing markers for assessment of nutritional status. PMID:11717422

The Role of Vitamin D in the Transcriptional Program of Human Pregnancy

PubMed Central

Al-Garawi, Amal; Carey, Vincent J.; Chhabra, Divya; Morrow, Jarrett; Lasky-Su, Jessica; Qiu, Weiliang; Laranjo, Nancy; Litonjua, Augusto A.; Weiss, Scott T.

2016-01-01

Background Patterns of gene expression of human pregnancy are poorly understood. In a trial of vitamin D supplementation in pregnant women, peripheral blood transcriptomes were measured longitudinally on 30 women and used to characterize gene co-expression networks. Objective Studies suggest that increased maternal Vitamin D levels may reduce the risk of asthma in early life, yet the underlying mechanisms have not been examined. In this study, we used a network-based approach to examine changes in gene expression profiles during the course of normal pregnancy and evaluated their association with maternal Vitamin D levels. Design The VDAART study is a randomized clinical trial of vitamin D supplementation in pregnancy for reduction of pediatric asthma risk. The trial enrolled 881 women at 10–18 weeks of gestation. Longitudinal gene expression measures were obtained on thirty pregnant women, using RNA isolated from peripheral blood samples obtained in the first and third trimesters. Differentially expressed genes were identified using significance of analysis of microarrays (SAM), and clustered using a weighted gene co-expression network analysis (WGCNA). Gene-set enrichment was performed to identify major biological pathways. Results Comparison of transcriptional profiles between first and third trimesters of pregnancy identified 5839 significantly differentially expressed genes (FDR<0.05). Weighted gene co-expression network analysis clustered these transcripts into 14 co-expression modules of which two showed significant correlation with maternal vitamin D levels. Pathway analysis of these two modules revealed genes enriched in immune defense pathways and extracellular matrix reorganization as well as genes enriched in notch signaling and transcription factor networks. Conclusion Our data show that gene expression profiles of healthy pregnant women change during the course of pregnancy and suggest that maternal Vitamin D levels influence transcriptional profiles. These alterations of the maternal transcriptome may contribute to fetal immune imprinting and reduce allergic sensitization in early life. Trial Registration clinicaltrials.gov NCT00920621 PMID:27711190

Characterization of the transcriptome profiles related to globin gene switching during in vitro erythroid maturation

PubMed Central

2012-01-01

Background The fetal and adult globin genes in the human β-globin cluster on chromosome 11 are sequentially expressed to achieve normal hemoglobin switching during human development. The pharmacological induction of fetal γ-globin (HBG) to replace abnormal adult sickle βS-globin is a successful strategy to treat sickle cell disease; however the molecular mechanism of γ-gene silencing after birth is not fully understood. Therefore, we performed global gene expression profiling using primary erythroid progenitors grown from human peripheral blood mononuclear cells to characterize gene expression patterns during the γ-globin to β-globin (γ/β) switch observed throughout in vitro erythroid differentiation. Results We confirmed erythroid maturation in our culture system using cell morphologic features defined by Giemsa staining and the γ/β-globin switch by reverse transcription-quantitative PCR (RT-qPCR) analysis. We observed maximal γ-globin expression at day 7 with a switch to a predominance of β-globin expression by day 28 and the γ/β-globin switch occurred around day 21. Expression patterns for transcription factors including GATA1, GATA2, KLF1 and NFE2 confirmed our system produced the expected pattern of expression based on the known function of these factors in globin gene regulation. Subsequent gene expression profiling was performed with RNA isolated from progenitors harvested at day 7, 14, 21, and 28 in culture. Three major gene profiles were generated by Principal Component Analysis (PCA). For profile-1 genes, where expression decreased from day 7 to day 28, we identified 2,102 genes down-regulated > 1.5-fold. Ingenuity pathway analysis (IPA) for profile-1 genes demonstrated involvement of the Cdc42, phospholipase C, NF-Kβ, Interleukin-4, and p38 mitogen activated protein kinase (MAPK) signaling pathways. Transcription factors known to be involved in γ-and β-globin regulation were identified. The same approach was used to generate profile-2 genes where expression was up-regulated over 28 days in culture. IPA for the 2,437 genes with > 1.5-fold induction identified the mitotic roles of polo-like kinase, aryl hydrocarbon receptor, cell cycle control, and ATM (Ataxia Telangiectasia Mutated Protein) signaling pathways; transcription factors identified included KLF1, GATA1 and NFE2 among others. Finally, profile-3 was generated from 1,579 genes with maximal expression at day 21, around the time of the γ/β-globin switch. IPA identified associations with cell cycle control, ATM, and aryl hydrocarbon receptor signaling pathways. Conclusions The transcriptome analysis completed with erythroid progenitors grown in vitro identified groups of genes with distinct expression profiles, which function in metabolic pathways associated with cell survival, hematopoiesis, blood cells activation, and inflammatory responses. This study represents the first report of a transcriptome analysis in human primary erythroid progenitors to identify transcription factors involved in hemoglobin switching. Our results also demonstrate that the in vitro liquid culture system is an excellent model to define mechanisms of global gene expression and the DNA-binding protein and signaling pathways involved in globin gene regulation. PMID:22537182

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

PubMed Central

Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

Comprehensive RNA-Seq Expression Analysis of Sensory Ganglia with a Focus on Ion Channels and GPCRs in Trigeminal Ganglia

PubMed Central

Manteniotis, Stavros; Lehmann, Ramona; Flegel, Caroline; Vogel, Felix; Hofreuter, Adrian; Schreiner, Benjamin S. P.; Altmüller, Janine; Becker, Christian; Schöbel, Nicole; Hatt, Hanns; Gisselmann, Günter

2013-01-01

The specific functions of sensory systems depend on the tissue-specific expression of genes that code for molecular sensor proteins that are necessary for stimulus detection and membrane signaling. Using the Next Generation Sequencing technique (RNA-Seq), we analyzed the complete transcriptome of the trigeminal ganglia (TG) and dorsal root ganglia (DRG) of adult mice. Focusing on genes with an expression level higher than 1 FPKM (fragments per kilobase of transcript per million mapped reads), we detected the expression of 12984 genes in the TG and 13195 in the DRG. To analyze the specific gene expression patterns of the peripheral neuronal tissues, we compared their gene expression profiles with that of the liver, brain, olfactory epithelium, and skeletal muscle. The transcriptome data of the TG and DRG were scanned for virtually all known G-protein-coupled receptors (GPCRs) as well as for ion channels. The expression profile was ranked with regard to the level and specificity for the TG. In total, we detected 106 non-olfactory GPCRs and 33 ion channels that had not been previously described as expressed in the TG. To validate the RNA-Seq data, in situ hybridization experiments were performed for several of the newly detected transcripts. To identify differences in expression profiles between the sensory ganglia, the RNA-Seq data of the TG and DRG were compared. Among the differentially expressed genes (> 1 FPKM), 65 and 117 were expressed at least 10-fold higher in the TG and DRG, respectively. Our transcriptome analysis allows a comprehensive overview of all ion channels and G protein-coupled receptors that are expressed in trigeminal ganglia and provides additional approaches for the investigation of trigeminal sensing as well as for the physiological and pathophysiological mechanisms of pain. PMID:24260241

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

PubMed

Kim, Kyu-Tae; Lee, Hye Won; Lee, Hae-Ock; Kim, Sang Cheol; Seo, Yun Jee; Chung, Woosung; Eum, Hye Hyeon; Nam, Do-Hyun; Kim, Junhyong; Joo, Kyeung Min; Park, Woong-Yang

2015-06-19

Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS(G12D), were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS(G12D) mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS(G12D) and low risk score. Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.

Discovering functional modules by topic modeling RNA-Seq based toxicogenomic data.

PubMed

Yu, Ke; Gong, Binsheng; Lee, Mikyung; Liu, Zhichao; Xu, Joshua; Perkins, Roger; Tong, Weida

2014-09-15

Toxicogenomics (TGx) endeavors to elucidate the underlying molecular mechanisms through exploring gene expression profiles in response to toxic substances. Recently, RNA-Seq is increasingly regarded as a more powerful alternative to microarrays in TGx studies. However, realizing RNA-Seq's full potential requires novel approaches to extracting information from the complex TGx data. Considering read counts as the number of times a word occurs in a document, gene expression profiles from RNA-Seq are analogous to a word by document matrix used in text mining. Topic modeling aiming at to discover the latent structures in text corpora would be helpful to explore RNA-Seq based TGx data. In this study, topic modeling was applied on a typical RNA-Seq based TGx data set to discover hidden functional modules. The RNA-Seq based gene expression profiles were transformed into "documents", on which latent Dirichlet allocation (LDA) was used to build a topic model. We found samples treated by the compounds with the same modes of actions (MoAs) could be clustered based on topic similarities. The topic most relevant to each cluster was identified as a "marker" topic, which was interpreted by gene enrichment analysis with MoAs then confirmed by compound and pathways associations mined from literature. To further validate the "marker" topics, we tested topic transferability from RNA-Seq to microarrays. The RNA-Seq based gene expression profile of a topic specifically associated with peroxisome proliferator-activated receptors (PPAR) signaling pathway was used to query samples with similar expression profiles in two different microarray data sets, yielding accuracy of about 85%. This proof-of-concept study demonstrates the applicability of topic modeling to discover functional modules in RNA-Seq data and suggests a valuable computational tool for leveraging information within TGx data in RNA-Seq era.

Cell and tissue microarray technologies for protein and nucleic acid expression profiling.

PubMed

Cardano, Marina; Diaferia, Giuseppe R; Falavigna, Maurizio; Spinelli, Chiara C; Sessa, Fausto; DeBlasio, Pasquale; Biunno, Ida

2013-02-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform.

Integrated analysis of microRNAs, transcription factors and target genes expression discloses a specific molecular architecture of hyperdiploid multiple myeloma

PubMed Central

Caracciolo, Daniele; Agnelli, Luca; Neri, Antonino; Walker, Brian A.; Morgan, Gareth J.; Cannataro, Mario

2015-01-01

Multiple Myeloma (MM) is a malignancy characterized by the hyperdiploid (HD-MM) and the non-hyperdiploid (nHD-MM) subtypes. To shed light within the molecular architecture of these subtypes, we used a novel integromics approach. By annotated MM patient mRNA/microRNA (miRNA) datasets, we investigated mRNAs and miRNAs profiles with relation to changes in transcriptional regulators expression. We found that HD-MM displays specific gene and miRNA expression profiles, involving the Signal Transducer and Activator of Transcription (STAT)3 pathway as well as the Transforming Growth Factor–beta (TGFβ) and the transcription regulator Nuclear Protein-1 (NUPR1). Our data define specific molecular features of HD-MM that may translate in the identification of novel relevant druggable targets. PMID:26056083

Estimation of the uncertainty of analyte concentration from the measurement uncertainty.

PubMed

Brown, Simon; Cooke, Delwyn G; Blackwell, Leonard F

2015-09-01

Ligand-binding assays, such as immunoassays, are usually analysed using standard curves based on the four-parameter and five-parameter logistic models. An estimate of the uncertainty of an analyte concentration obtained from such curves is needed for confidence intervals or precision profiles. Using a numerical simulation approach, it is shown that the uncertainty of the analyte concentration estimate becomes significant at the extremes of the concentration range and that this is affected significantly by the steepness of the standard curve. We also provide expressions for the coefficient of variation of the analyte concentration estimate from which confidence intervals and the precision profile can be obtained. Using three examples, we show that the expressions perform well.

Suppressed anger, evaluative threat, and cardiovascular reactivity: a tripartite profile approach.

PubMed

Jorgensen, Randall S; Kolodziej, Monika E

2007-11-01

Despite decades of theory and research implicating suppressed anger in the development of cardiovascular disorders involving cardiovascular reactivity (CVR), to date the theoretical components of low anger expression, guilt feelings over agonistic reactions, and defensive strivings to avoid social disapproval have not been used conjointly to profile suppressed anger for the prediction of CVR. The purpose of this study, then, was to cluster analyze measures of anger expression, hostility guilt, and social defensiveness to create a suppressed anger profile (low anger expression, high hostility guilt, high social defensiveness) and a non-suppressed profile from a sample of college males. Social evaluative threat may be a potent stressor for people who defensively suppress anger expression. Thus, to examine the combined effects of suppressed anger and social evaluative threat, participants, prior to telling a story to a Thematic Apperception Card (TAT), were randomly assigned to either a high-threat (story will be compared to stories created by the mentally ill) or a low-threat condition (story used to study effects of talking on cardiovascular responses). Blood pressure (BP) and heart rate (HR) were monitored during a rest period and the subsequent TAT card period. As predicted, suppressed anger males in the high-threat condition showed the highest levels of diastolic BP and HR change from the rest period. The suppressed anger group's systolic BP reactivity was independent of threat manipulation. Research implications are discussed.

Proteomic profiling of developing cotton fibers from wild and domesticated Gossypium barbadense.

PubMed

Hu, Guanjing; Koh, Jin; Yoo, Mi-Jeong; Grupp, Kara; Chen, Sixue; Wendel, Jonathan F

2013-10-01

Pima cotton (Gossypium barbadense) is widely cultivated because of its long, strong seed trichomes ('fibers') used for premium textiles. These agronomically advanced fibers were derived following domestication and thousands of years of human-mediated crop improvement. To gain an insight into fiber development and evolution, we conducted comparative proteomic and transcriptomic profiling of developing fiber from an elite cultivar and a wild accession. Analyses using isobaric tag for relative and absolute quantification (iTRAQ) LC-MS/MS technology identified 1317 proteins in fiber. Of these, 205 were differentially expressed across developmental stages, and 190 showed differential expression between wild and cultivated forms, 14.4% of the proteome sampled. Human selection may have shifted the timing of developmental modules, such that some occur earlier in domesticated than in wild cotton. A novel approach was used to detect possible biased expression of homoeologous copies of proteins. Results indicate a significant partitioning of duplicate gene expression at the protein level, but an approximately equal degree of bias for each of the two constituent genomes of allopolyploid cotton. Our results demonstrate the power of complementary transcriptomic and proteomic approaches for the study of the domestication process. They also provide a rich database for mining for functional analyses of cotton improvement or evolution. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Discovering Functions of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates

PubMed Central

Ellison, Christopher E.; Kowbel, David; Glass, N. Louise; Taylor, John W.

2014-01-01

ABSTRACT Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems. PMID:24692637

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

PubMed Central

Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.

2014-01-01

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557

Picking Cell Lines for High-Throughput Transcriptomic Toxicity Screening (SOT)

EPA Science Inventory

High throughput, whole genome transcriptomic profiling is a promising approach to comprehensively evaluate chemicals for potential biological effects. To be useful for in vitro toxicity screening, gene expression must be quantified in a set of representative cell types that captu...

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

Protein expression profiling in head fragments during planarian regeneration after amputation.

PubMed

Chen, Xiaoguang; Xu, Cunshuan

2015-04-01

Following amputation, a planarian tail fragment can regrow into a complete organism including a well-organized brain within about 2-3 weeks, thus restoring the structure and function to presurgical levels. Despite the enormous potential of these animals for regenerative medicine, our understanding of the exact mechanism of planarian regeneration is incomplete. To better understand the molecular nature of planarian head regeneration, we applied two-dimensional electrophoresis (2-DE)/matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF)/time-of-flight mass spectrometry (TOF MS) technique to analyze the dynamic proteomic expression profiles over the course of 6 to 168 h post-decapitation. This approach identified a total of 141 differentially expressed proteins, 47 of which exhibited exceptionally high fold changes (≥3-fold change). Of these, Rx protein, an important regulator of head and brain development, was considered to be closely related to planarian head regeneration because of its exceptional high expression almost throughout the time course of regeneration process. Functional annotation analysis classified the 141 proteins into eight categories: (1) signaling, (2) Ca(2+) binding and translocation, (3) transcription and translation, (4) cytoskeleton, (5) metabolism, (6) cell protection, (7) tissue differentiation, and (8) cell cycle. Signaling pathway analysis indicated that Wnt1/Ca(2+) signaling pathway was activated during head regeneration. Integrating the analyses of proteome expression profiling, functional annotation, and signaling pathway, amputation-induced head reformation requires some mechanisms to promote cell proliferation and differentiation, including differential regulation of proapoptotic and antiapoptotic proteins, and the regulation of proliferation and differentiation-related proteins. Importantly, Wnt1/Ca(2+) signaling pathway upregulates Rx expression, finally facilitating the differentiation of neoblasts into various cell types. Taken together, our study demonstrated that proteomic analysis approach used by us is a powerful tool in understanding molecular process related to head regeneration of planarian.

Gene expression profiling--Opening the black box of plant ecosystem responses to global change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leakey, A.D.B.; Ainsworth, E.A.; Bernard, S.M.

The use of genomic techniques to address ecological questions is emerging as the field of genomic ecology. Experimentation under environmentally realistic conditions to investigate the molecular response of plants to meaningful changes in growth conditions and ecological interactions is the defining feature of genomic ecology. Since the impact of global change factors on plant performance are mediated by direct effects at the molecular, biochemical and physiological scales, gene expression analysis promises important advances in understanding factors that have previously been consigned to the 'black box' of unknown mechanism. Various tools and approaches are available for assessing gene expression in modelmore » and non-model species as part of global change biology studies. Each approach has its own unique advantages and constraints. A first generation of genomic ecology studies in managed ecosystems and mesocosms have provided a testbed for the approach and have begun to reveal how the experimental design and data analysis of gene expression studies can be tailored for use in an ecological context.« less

A novel toxicogenomics-based approach to categorize (non-)genotoxic carcinogens.

PubMed

Schaap, Mirjam M; Wackers, Paul F K; Zwart, Edwin P; Huijskens, Ilse; Jonker, Martijs J; Hendriks, Giel; Breit, Timo M; van Steeg, Harry; van de Water, Bob; Luijten, Mirjam

2015-12-01

Alternative methods to detect non-genotoxic carcinogens are urgently needed, as this class of carcinogens goes undetected in the current testing strategy for carcinogenicity under REACH. A complicating factor is that non-genotoxic carcinogens act through several distinctive modes of action, which makes prediction of their carcinogenic property difficult. We have recently demonstrated that gene expression profiling in primary mouse hepatocytes is a useful approach to categorize non-genotoxic carcinogens according to their modes of action. In the current study, we improved the methods used for analysis and added mouse embryonic stem cells as a second in vitro test system, because of their features complementary to hepatocytes. Our approach involved an unsupervised analysis based on the 30 most significantly up- and down-regulated genes per chemical. Mouse embryonic stem cells and primary mouse hepatocytes were exposed to a selected set of chemicals and subsequently subjected to gene expression profiling. We focused on non-genotoxic carcinogens, but also included genotoxic carcinogens and non-carcinogens to test the robustness of this approach. Application of the optimized comparison approach resulted in improved categorization of non-genotoxic carcinogens. Mouse embryonic stem cells were a useful addition, especially for genotoxic substances, but also for detection of non-genotoxic carcinogens that went undetected by primary hepatocytes. The approach presented here is an important step forward to categorize chemicals, especially those that are carcinogenic.

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

PubMed Central

Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

2007-01-01

Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (<4 kgs weight loss). We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box) approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%±8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier) improved prediction accuracy to 80.9%±2.2%. Conclusion Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

Building gene expression profile classifiers with a simple and efficient rejection option in R.

PubMed

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez

2011-01-01

The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be available.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

PubMed Central

McArt, Darragh G.; Dunne, Philip D.; Blayney, Jaine K.; Salto-Tellez, Manuel; Van Schaeybroeck, Sandra; Hamilton, Peter W.; Zhang, Shu-Dong

2013-01-01

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. PMID:23840550

MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias

PubMed Central

Calin, George Adrian; Liu, Chang-Gong; Sevignani, Cinzia; Ferracin, Manuela; Felli, Nadia; Dumitru, Calin Dan; Shimizu, Masayoshi; Cimmino, Amelia; Zupo, Simona; Dono, Mariella; Dell'Aquila, Marie L.; Alder, Hansjuerg; Rassenti, Laura; Kipps, Thomas J.; Bullrich, Florencia; Negrini, Massimo; Croce, Carlo M.

2004-01-01

Little is known about the expression levels or function of micro-RNAs (miRNAs) in normal and neoplastic cells, although it is becoming clear that miRNAs play important roles in the regulation of gene expression during development [Ambros, V. (2003) Cell 113, 673–676; McManus, M. T. (2003) Semin. Cancer Biol. 13, 253–258]. We now report the genomewide expression profiling of miRNAs in human B cell chronic lymphocytic leukemia (CLL) by using a microarray containing hundreds of human precursor and mature miRNA oligonucleotide probes. This approach allowed us to identify significant differences in miRNome expression between CLL samples and normal CD5+ B cells; data were confirmed by Northern blot analyses and real-time RT-PCR. At least two distinct clusters of CLL samples can be identified that were associated with the presence or absence of Zap-70 expression, a predictor of early disease progression. Two miRNA signatures were associated with the presence or absence of mutations in the expressed Ig variableregion genes or with deletions at 13q14, respectively. These data suggest that miRNA expression patterns have relevance to the biological and clinical behavior of this leukemia. PMID:15284443

Gene Expression Profiling in the Thiamethoxam Resistant and Susceptible B-biotype Sweetpotato Whitefly, Bemisia tabaci

PubMed Central

Xie, Wen; Yang, Xin; Wang, Shao-Ii; Wu, Qing-jun; Yang, Ni-na; Li, Ru-mei; Jiao, Xiaoguo; Pan, Hui-peng; Liu, Bai-ming; Feng, Yun-tao; Xu, Bao-yun; Zhou, Xu-guo; Zhang, You-jun

2012-01-01

Thiamethoxam has been used as a major insecticide to control the B-biotype sweetpotato whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae). Due to its excessive use, a high level of resistance to thiamethoxam has developed worldwide over the past several years. To better understand the molecular mechanisms underlying this resistance in B. tabaci, gene profiles between the thiamethoxam-resistant and thiamethoxam-susceptible strains were investigated using the suppression subtractive hybridization (SSH) library approach. A total of 72 and 52 upand down-regulated genes were obtained from the forward and reverse SSH libraries, respectively. These expressed sequence tags (ESTs) belong to several functional categories based on their gene ontology annotation. Some categories such as cell communication, response to abiotic stimulus, lipid particle, and nuclear envelope were identified only in the forward library of thiamethoxam-resistant strains. In contrast, categories such as behavior, cell proliferation, nutrient reservoir activity, sequence-specific DNA binding transcription factor activity, and signal transducer activity were identified solely in the reverse library. To study the validity of the SSH method, 16 differentially expressed genes from both forward and reverse SSH libraries were selected randomly for further analyses using quantitative realtime PCR (qRT-PCR). The qRT-PCR results were fairly consistent with the SSH results; however, only 50% of the genes showed significantly different expression profiles between the thiamethoxam-resistant and thiamethoxam-susceptible whiteflies. Among these genes, a putative NAD-dependent methanol dehydrogenase was substantially over-expressed in the thiamethoxamresistant adults compared to their susceptible counterparts. The distributed profiles show that it was highly expressed during the egg stage, and was most abundant in the abdomen of adult females. PMID:22957505

Informatic selection of a neural crest-melanocyte cDNA set for microarray analysis

PubMed Central

Loftus, S. K.; Chen, Y.; Gooden, G.; Ryan, J. F.; Birznieks, G.; Hilliard, M.; Baxevanis, A. D.; Bittner, M.; Meltzer, P.; Trent, J.; Pavan, W.

1999-01-01

With cDNA microarrays, it is now possible to compare the expression of many genes simultaneously. To maximize the likelihood of finding genes whose expression is altered under the experimental conditions, it would be advantageous to be able to select clones for tissue-appropriate cDNA sets. We have taken advantage of the extensive sequence information in the dbEST expressed sequence tag (EST) database to identify a neural crest-derived melanocyte cDNA set for microarray analysis. Analysis of characterized genes with dbEST identified one library that contained ESTs representing 21 neural crest-expressed genes (library 198). The distribution of the ESTs corresponding to these genes was biased toward being derived from library 198. This is in contrast to the EST distribution profile for a set of control genes, characterized to be more ubiquitously expressed in multiple tissues (P < 1 × 10−9). From library 198, a subset of 852 clustered ESTs were selected that have a library distribution profile similar to that of the 21 neural crest-expressed genes. Microarray analysis demonstrated the majority of the neural crest-selected 852 ESTs (Mel1 array) were differentially expressed in melanoma cell lines compared with a non-neural crest kidney epithelial cell line (P < 1 × 10−8). This was not observed with an array of 1,238 ESTs that was selected without library origin bias (P = 0.204). This study presents an approach for selecting tissue-appropriate cDNAs that can be used to examine the expression profiles of developmental processes and diseases. PMID:10430933

Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

PubMed Central

Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

2011-01-01

Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

Organogenic nodule development in hop (Humulus lupulus L.): Transcript and metabolic responses

PubMed Central

Fortes, Ana M; Santos, Filipa; Choi, Young H; Silva, Marta S; Figueiredo, Andreia; Sousa, Lisete; Pessoa, Fernando; Santos, Bartolomeu A; Sebastiana, Mónica; Palme, Klaus; Malhó, Rui; Verpoorte, Rob; Pais, Maria S

2008-01-01

Background Hop (Humulus lupulus L.) is an economically important plant forming organogenic nodules which can be used for genetic transformation and micropropagation. We are interested in the mechanisms underlying reprogramming of cells through stress and hormone treatments. Results An integrated molecular and metabolomic approach was used to investigate global gene expression and metabolic responses during development of hop's organogenic nodules. Transcript profiling using a 3,324-cDNA clone array revealed differential regulation of 133 unigenes, classified into 11 functional categories. Several pathways seem to be determinant in organogenic nodule formation, namely defense and stress response, sugar and lipid metabolism, synthesis of secondary metabolites and hormone signaling. Metabolic profiling using 1H NMR spectroscopy associated to two-dimensional techniques showed the importance of metabolites related to oxidative stress response, lipid and sugar metabolism and secondary metabolism in organogenic nodule formation. Conclusion The expression profile of genes pivotal for energy metabolism, together with metabolites profile, suggested that these morphogenic structures gain energy through a heterotrophic, transport-dependent and sugar-degrading anaerobic metabolism. Polyamines and auxins are likely to be involved in the regulation of expression of many genes related to organogenic nodule formation. These results represent substantial progress toward a better understanding of this complex developmental program and reveal novel information regarding morphogenesis in plants. PMID:18823540

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma

PubMed Central

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-01-01

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis. PMID:18305825

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma.

PubMed

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-12-30

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis.

Cell and Tissue Microarray Technologies for Protein and Nucleic Acid Expression Profiling

PubMed Central

Cardano, Marina; Diaferia, Giuseppe R.; Falavigna, Maurizio; Spinelli, Chiara C.; Sessa, Fausto; DeBlasio, Pasquale

2013-01-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform. PMID:23172795

Very Low Abundance Single-Cell Transcript Quantification with 5-Plex ddPCRTM Assays.

PubMed

Karlin-Neumann, George; Zhang, Bin; Litterst, Claudia

2018-01-01

Gene expression studies have provided one of the most accessible windows for understanding the molecular basis of cell and tissue phenotypes and how these change in response to stimuli. Current PCR-based and next generation sequencing methods offer great versatility in allowing the focused study of the roles of small numbers of genes or comprehensive profiling of the entire transcriptome of a sample at one time. Marrying of these approaches to various cell sorting technologies has recently enabled the profiling of expression in single cells, thereby increasing the resolution and sensitivity and strengthening the inferences from observed expression levels and changes. This chapter presents a quick and efficient 1-day workflow for sorting single cells with a small laboratory cell-sorter followed by an ultrahigh sensitivity, multiplexed digital PCR method for quantitative tracking of changes in 5-10 genes per single cell.

miRNA expression and function in thyroid carcinomas: a comparative and critical analysis and a model for other cancers.

PubMed

Saiselet, Manuel; Pita, Jaime M; Augenlicht, Alice; Dom, Geneviève; Tarabichi, Maxime; Fimereli, Danai; Dumont, Jacques E; Detours, Vincent; Maenhaut, Carine

2016-08-09

As in many cancer types, miRNA expression profiles and functions have become an important field of research on non-medullary thyroid carcinomas, the most common endocrine cancers. This could lead to the establishment of new diagnostic tests and new cancer therapies. However, different studies showed important variations in their research strategies and results. In addition, the action of miRNAs is poorly considered as a whole because of the use of underlying dogmatic truncated concepts. These lead to discrepancies and limits rarely considered. Recently, this field has been enlarged by new miRNA functional and expression studies. Moreover, studies using next generation sequencing give a new view of general miRNA differential expression profiles of papillary thyroid carcinoma. We analyzed in detail this literature from both physiological and differential expression points of view. Based on explicit examples, we reviewed the progresses but also the discrepancies and limits trying to provide a critical approach of where this literature may lead. We also provide recommendations for future studies. The conclusions of this systematic analysis could be extended to other cancer types.

New vistas in refractive laser beam shaping with an analytic design approach

NASA Astrophysics Data System (ADS)

Duerr, Fabian; Thienpont, Hugo

2014-05-01

Many commercial, medical and scientific applications of the laser have been developed since its invention. Some of these applications require a specific beam irradiance distribution to ensure optimal performance. Often, it is possible to apply geometrical methods to design laser beam shapers. This common design approach is based on the ray mapping between the input plane and the output beam. Geometric ray mapping designs with two plano-aspheric lenses have been thoroughly studied in the past. Even though analytic expressions for various ray mapping functions do exist, the surface profiles of the lenses are still calculated numerically. In this work, we present an alternative novel design approach that allows direct calculation of the rotational symmetric lens profiles described by analytic functions. Starting from the example of a basic beam expander, a set of functional differential equations is derived from Fermat's principle. This formalism allows calculating the exact lens profiles described by Taylor series coefficients up to very high orders. To demonstrate the versatility of this new approach, two further cases are solved: a Gaussian to at-top irradiance beam shaping system, and a beam shaping system that generates a more complex dark-hollow Gaussian (donut-like) irradiance profile with zero intensity in the on-axis region. The presented ray tracing results confirm the high accuracy of all calculated solutions and indicate the potential of this design approach for refractive beam shaping applications.

Molecular profiling of single circulating tumor cells from lung cancer patients.

PubMed

Park, Seung-Min; Wong, Dawson J; Ooi, Chin Chun; Kurtz, David M; Vermesh, Ophir; Aalipour, Amin; Suh, Susie; Pian, Kelsey L; Chabon, Jacob J; Lee, Sang Hun; Jamali, Mehran; Say, Carmen; Carter, Justin N; Lee, Luke P; Kuschner, Ware G; Schwartz, Erich J; Shrager, Joseph B; Neal, Joel W; Wakelee, Heather A; Diehn, Maximilian; Nair, Viswam S; Wang, Shan X; Gambhir, Sanjiv S

2016-12-27

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

New approaches in analyzing the pharmacological properties of herbal extracts.

PubMed

Hamburger, Matthias

2007-01-01

Herbal extracts are widely used and accepted in the population. The pharmacological characterization of such products meets some specific challenges, given the chemical complexity of the active ingredient. An overview is given on modern methods and approaches that can be used for that purpose. In particular, HPLC-based activity profiling is discussed as a means to identify pharmacologically active compounds in an extract, and expression profiling is described as a means for global assessment of effects exerted by multi-component mixtures such as extracts. These methods are illustrated with selected axamples from our labs, including woad (Isatis tinctoria), the traditional Chinese herb Danshen (Salvia miltiorrhiza) and black cohosh (Cimicifuga racemosa).

Theory of Fiber Optical Bragg Grating: Revisited

NASA Technical Reports Server (NTRS)

Tai, H.

2003-01-01

The reflected signature of an optical fiber Bragg grating is analyzed using the transfer function method. This approach is capable to cast all relevant quantities into proper places and provides a better physical understanding. The relationship between reflected signal, number of periods, index of refraction, and reflected wave phase is elucidated. The condition for which the maximum reflectivity is achieved is fully examined. We also have derived an expression to predict the reflectivity minima accurately when the reflected wave is detuned. Furthermore, using the segmented potential approach, this model can handle arbitrary index of refraction profiles and compare the strength of optical reflectivity of different profiles. The condition of a non-uniform grating is also addressed.

Effects of surface roughness and absorption on light propagation in graded-profile waveguides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danilenko, S S; Osovitskii, A N

2011-06-30

This paper examines the effects of surface roughness and absorption on laser light propagation in graded-profile waveguiding structures. We derive analytical expressions for the scattering and absorption coefficients of guided waves and analyse these coefficients in relation to parameters of the waveguiding structure and the roughness of its boundary. A new approach is proposed to measuring roughness parameters of precision dielectric surfaces. Experimental evidence is presented which supports the main conclusions of the theory. (integraled-optical waweguides)

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

PubMed Central

Schwahn, Kevin; Nikoloski, Zoran

2018-01-01

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana. PMID:29731765

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

PubMed

Jung, Ki-Hong; Dardick, Christopher; Bartley, Laura E; Cao, Peijian; Phetsom, Jirapa; Canlas, Patrick; Seo, Young-Su; Shultz, Michael; Ouyang, Shu; Yuan, Qiaoping; Frank, Bryan C; Ly, Eugene; Zheng, Li; Jia, Yi; Hsia, An-Ping; An, Kyungsook; Chou, Hui-Hsien; Rocke, David; Lee, Geun Cheol; Schnable, Patrick S; An, Gynheung; Buell, C Robin; Ronald, Pamela C

2008-10-06

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli.

PubMed

Ståhlberg, Anders; Elbing, Karin; Andrade-Garda, José Manuel; Sjögreen, Björn; Forootan, Amin; Kubista, Mikael

2008-04-16

The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli

PubMed Central

Ståhlberg, Anders; Elbing, Karin; Andrade-Garda, José Manuel; Sjögreen, Björn; Forootan, Amin; Kubista, Mikael

2008-01-01

Background The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. Results We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Conclusion Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains. PMID:18412983

Characterization of Conserved and Non-conserved Imprinted Genes in Swine

USDA-ARS?s Scientific Manuscript database

In order to increase our understanding of the role of imprinted genes in swine reproduction we used two complementary approaches, analysis of imprinting by pyrosequencing, and expression profiling of parthenogenetic fetuses, to carry out a comprehensive analysis of this gene family in swine. Using A...

Salicylate and catechol levels are maintained in nahG transgenic poplar

Treesearch

Alison M. Morse; Timothy J. Tschaplinski; Christopher Dervinis; Paula M. Pijut; Eric A. Schmelz; Wendy Day; John M. Davis

2007-01-01

Metabolic profiling was used to investigate the molecular phenotypes of a transgenic Populus tremula × P. alba hybrid expressing the nahG transgene, a bacterial gene encoding salicylate hydroxylase that converts salicylic acid to catechol. Despite the efficacy of this transgenic approach to reduce...

High interleukin-15 expression characterizes childhood acute lymphoblastic leukemia with involvement of the CNS.

PubMed

Cario, Gunnar; Izraeli, Shai; Teichert, Anja; Rhein, Peter; Skokowa, Julia; Möricke, Anja; Zimmermann, Martin; Schrauder, Andre; Karawajew, Leonid; Ludwig, Wolf-Dieter; Welte, Karl; Schünemann, Holger J; Schlegelberger, Brigitte; Schrappe, Martin; Stanulla, Martin

2007-10-20

Applying current diagnostic methods, overt CNS involvement is a rare event in childhood acute lymphoblastic leukemia (ALL). In contrast, CNS-directed therapy is essential for all patients with ALL because without it, the majority of patients eventually will experience relapse. To approach this discrepancy and to explore potential distinct biologic properties of leukemic cells that migrate into the CNS, we compared gene expression profiles of childhood ALL patients with initial CNS involvement with the profiles of CNS-negative patients. We evaluated leukemic gene expression profiles from the bone marrow of 17 CNS-positive patients and 26 CNS-negative patients who were frequency matched for risk factors associated with CNS involvement. Results were confirmed by real-time quantitative polymerase chain reaction analysis and validated using independent patient samples. Interleukin-15 (IL-15) expression was consistently upregulated in leukemic cells of CNS-positive patients compared with CNS-negative patients. In multivariate analysis, IL-15 expression levels greater than the median were associated with CNS involvement compared with expression equal to or less than the median (odds ratio [OR] = 10.70; 95% CI, 2.95 to 38.81). Diagnostic likelihood ratios for CNS positivity were 0.09 (95% CI, 0.01 to 0.65) for the first and 6.93 (95% CI, 2.55 to 18.83) for the fourth IL-15 expression quartiles. In patients who were CNS negative at diagnosis, IL-15 levels greater than the median were associated with subsequent CNS relapse compared with expression equal to or less than the median (OR = 13.80; 95% CI, 3.38 to 56.31). Quantification of leukemic IL-15 expression at diagnosis predicts CNS status and could be a new tool to further tailor CNS-directed therapy in childhood ALL.

Reprogramming Methods Do Not Affect Gene Expression Profile of Human Induced Pluripotent Stem Cells.

PubMed

Trevisan, Marta; Desole, Giovanna; Costanzi, Giulia; Lavezzo, Enrico; Palù, Giorgio; Barzon, Luisa

2017-01-20

Induced pluripotent stem cells (iPSCs) are pluripotent cells derived from adult somatic cells. After the pioneering work by Yamanaka, who first generated iPSCs by retroviral transduction of four reprogramming factors, several alternative methods to obtain iPSCs have been developed in order to increase the yield and safety of the process. However, the question remains open on whether the different reprogramming methods can influence the pluripotency features of the derived lines. In this study, three different strategies, based on retroviral vectors, episomal vectors, and Sendai virus vectors, were applied to derive iPSCs from human fibroblasts. The reprogramming efficiency of the methods based on episomal and Sendai virus vectors was higher than that of the retroviral vector-based approach. All human iPSC clones derived with the different methods showed the typical features of pluripotent stem cells, including the expression of alkaline phosphatase and stemness maker genes, and could give rise to the three germ layer derivatives upon embryoid bodies assay. Microarray analysis confirmed the presence of typical stem cell gene expression profiles in all iPSC clones and did not identify any significant difference among reprogramming methods. In conclusion, the use of different reprogramming methods is equivalent and does not affect gene expression profile of the derived human iPSCs.

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimating replicate time shifts using Gaussian process regression

PubMed Central

Liu, Qiang; Andersen, Bogi; Smyth, Padhraic; Ihler, Alexander

2010-01-01

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual replicate. Our approach is based on Gaussian process regression (GPR) combined with a probabilistic model that accounts for uncertainty about the biological development time of each replicate. Results: We apply GPR with uncertain measurement times to a microarray dataset of mRNA expression for the hair-growth cycle in mouse back skin, predicting both profile shapes and biological times for each replicate. The predicted time shifts show high consistency with independently obtained morphological estimates of relative development. We also show that the method systematically reduces prediction error on out-of-sample data, significantly reducing the mean squared error in a cross-validation study. Availability: Matlab code for GPR with uncertain time shifts is available at http://sli.ics.uci.edu/Code/GPRTimeshift/ Contact: ihler@ics.uci.edu PMID:20147305

HIV-1 Infection of Primary CD4+ T Cells Regulates the Expression of Specific Human Endogenous Retrovirus HERV-K (HML-2) Elements.

PubMed

Young, George R; Terry, Sandra N; Manganaro, Lara; Cuesta-Dominguez, Alvaro; Deikus, Gintaras; Bernal-Rubio, Dabeiba; Campisi, Laura; Fernandez-Sesma, Ana; Sebra, Robert; Simon, Viviana; Mulder, Lubbertus C F

2018-01-01

Endogenous retroviruses (ERVs) occupy extensive regions of the human genome. Although many of these retroviral elements have lost their ability to replicate, those whose insertion took place more recently, such as the HML-2 group of HERV-K elements, still retain intact open reading frames and the capacity to produce certain viral RNA and/or proteins. Transcription of these ERVs is, however, tightly regulated by dedicated epigenetic control mechanisms. Nonetheless, it has been reported that some pathological states, such as viral infections and certain cancers, coincide with ERV expression, suggesting that transcriptional reawakening is possible. HML-2 elements are reportedly induced during HIV-1 infection, but the conserved nature of these elements has, until recently, rendered their expression profiling problematic. Here, we provide comprehensive HERV-K HML-2 expression profiles specific for productively HIV-1-infected primary human CD4 + T cells. We combined enrichment of HIV-1 infected cells using a reporter virus expressing a surface reporter for gentle and efficient purification with long-read single-molecule real-time sequencing. We show that three HML-2 proviruses-6q25.1, 8q24.3, and 19q13.42-are upregulated on average between 3- and 5-fold in HIV-1-infected CD4 + T cells. One provirus, HML-2 12q24.33, in contrast, was repressed in the presence of active HIV replication. In conclusion, this report identifies the HERV-K HML-2 loci whose expression profiles differ upon HIV-1 infection in primary human CD4 + T cells. These data will help pave the way for further studies on the influence of endogenous retroviruses on HIV-1 replication. IMPORTANCE Endogenous retroviruses inhabit big portions of our genome. Moreover, although they are mainly inert, some of the evolutionarily younger members maintain the ability to express both RNA and proteins. We have developed an approach using long-read single-molecule real-time (SMRT) sequencing that produces long reads that allow us to obtain detailed and accurate HERV-K HML-2 expression profiles. We applied this approach to study HERV-K expression in the presence or absence of productive HIV-1 infection of primary human CD4 + T cells. In addition to using SMRT sequencing, our strategy also includes the magnetic selection of the infected cells so that levels of background expression due to uninfected cells are kept at a minimum. The results presented here provide a blueprint for in-depth studies of the interactions of the authentic upregulated HERV-K HML-2 elements and HIV-1. Copyright © 2017 American Society for Microbiology.

Breast Tumors with Elevated Expression of 1q Candidate Genes Confer Poor Clinical Outcome and Sensitivity to Ras/PI3K Inhibition

PubMed Central

Viveka Thangaraj, Soundara; Periasamy, Jayaprakash; Bhaskar Rao, Divya; Barnabas, Georgina D.; Raghavan, Swetha; Ganesan, Kumaresan

2013-01-01

Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K / AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA–drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors. PMID:24147022

Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data

PubMed Central

Raju, Hemalatha B.; Tsinoremas, Nicholas F.; Capobianco, Enrico

2016-01-01

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein–protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches. PMID:27803687

Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data.

PubMed

Raju, Hemalatha B; Tsinoremas, Nicholas F; Capobianco, Enrico

2016-01-01

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein-protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.

Using expression genetics to study the neurobiology of ethanol and alcoholism.

PubMed

Farris, Sean P; Wolen, Aaron R; Miles, Michael F

2010-01-01

Recent simultaneous progress in human and animal model genetics and the advent of microarray whole genome expression profiling have produced prodigious data sets on genetic loci, potential candidate genes, and differential gene expression related to alcoholism and ethanol behaviors. Validated target genes or gene networks functioning in alcoholism are still of meager proportions. Genetical genomics, which combines genetic analysis of both traditional phenotypes and whole genome expression data, offers a potential methodology for characterizing brain gene networks functioning in alcoholism. This chapter will describe concepts, approaches, and recent findings in the field of genetical genomics as it applies to alcohol research. Copyright 2010 Elsevier Inc. All rights reserved.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums.

PubMed

Shakoor, Nadia; Nair, Ramesh; Crasta, Oswald; Morris, Geoffrey; Feltus, Alex; Kresovich, Stephen

2014-01-23

Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

PubMed Central

2014-01-01

Background Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community. PMID:24456189

Disruption of Fibroblast Growth Factor Receptor (FGFR) Signaling as an Approach to Prostate Cancer Therapy

DTIC Science & Technology

2006-04-01

and the abstract was published in the Journal of Molecular Diagnostics . The full length manuscript entitled “Increased expression and activity of...Recurrence. The Journal of Molecular Diagnostics 2004, (6)4: 431. Ozen M, Dixit S and Ittmann M: Molecular profiling of differentially expressed genes...in response to FGFR disruption in prostate cancer. the Journal of Molecular Diagnostics 7 (5): 680, 2005. Full Articles: 1. Ozen M and Ittmann M

Classification and Compression of Multi-Resolution Vectors: A Tree Structured Vector Quantizer Approach

DTIC Science & Technology

2002-01-01

their expression profile and for classification of cells into tumerous and non- tumerous classes. Then we will present a parallel tree method for... cancerous cells. We will use the same dataset and use tree structured classifiers with multi-resolution analysis for classifying cancerous from non- cancerous ...cells. We have the expressions of 4096 genes from 98 different cell types. Of these 98, 72 are cancerous while 26 are non- cancerous . We are interested

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

A comparison between observed and analytical velocity dispersion profiles of 20 nearby galaxy clusters

NASA Astrophysics Data System (ADS)

Khan, Mohammad S.; Abdullah, Mohamed H.; Ali, Gamal B.

2014-05-01

We derive analytical expression for the velocity dispersion of galaxy clusters, using the statistical mechanical approach. We compare the observed velocity dispersion profiles for 20 nearby ( z≤0.1) galaxy clusters with the analytical ones. It is interesting to find that the analytical results closely match with the observed velocity dispersion profiles only if the presence of the diffuse matter in clusters is taken into consideration. This takes us to introduce a new approach to detect the ratio of diffuse mass, M diff , within a galaxy cluster. For the present sample, the ratio f= M diff / M, where M the cluster's total mass is found to has an average value of 45±12 %. This leads us to the result that nearly 45 % of the cluster mass is impeded outside the galaxies, while around 55 % of the cluster mass is settled in the galaxies.

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*

PubMed Central

Xiao, Yongsheng; Guo, Lei; Wang, Yinsheng

2014-01-01

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy. PMID:24520089

ALTERED GENE EXPRESSION PROFILES OF RAT LUNG IN RESPONSE TO AN EMISSION PARTICULATE AND ITS METAL CONSTITUENTS

EPA Science Inventory

Comprehensive and systematic approaches are needed to understand the molecular basis for the proposed adverse health effects of PM exposure reported in epidemiological studies. Due to the complex nature of the pollutant and the altered physiological conditions in the predisposed...

Cloning and expression profiling of odorant-binding proteins in the tarnished plant bug, Lygus lineolaris

USDA-ARS?s Scientific Manuscript database

In insects, the perception and discrimination of odorants requires the involvement of odorant binding proteins (OBPs). To gain a better molecular understanding of olfaction in the agronomic pest, Lygus lineolaris (tarnished plant bug), we used a transcriptomics-based approach to identify potential ...

In vivo transcriptional profile analysis reveals RNA splicing and chromatin remodeling as prominent processes for adult neurogenesis.

PubMed

Lim, Daniel A; Suárez-Fariñas, Mayte; Naef, Felix; Hacker, Coleen R; Menn, Benedicte; Takebayashi, Hirohide; Magnasco, Marcelo; Patil, Nila; Alvarez-Buylla, Arturo

2006-01-01

Neural stem cells and neurogenesis persist in the adult mammalian brain subventricular zone (SVZ). Cells born in the rodent SVZ migrate to the olfactory bulb (Ob) where they differentiate into interneurons. To determine the gene expression and functional profile of SVZ neurogenesis, we performed three complementary sets of transcriptional analysis experiments using Affymetrix GeneChips: (1) comparison of adult mouse SVZ and Ob gene expression profiles with those of the striatum, cerebral cortex, and hippocampus; (2) profiling of SVZ stem cells and ependyma isolated by fluorescent-activated cell sorting (FACS); and (3) analysis of gene expression changes during in vivo SVZ regeneration after anti-mitotic treatment. Gene Ontology (GO) analysis of data from these three separate approaches showed that in adult SVZ neurogenesis, RNA splicing and chromatin remodeling are biological processes as statistically significant as cell proliferation, transcription, and neurogenesis. In non-neurogenic brain regions, RNA splicing and chromatin remodeling were not prominent processes. Fourteen mRNA splicing factors including Sf3b1, Sfrs2, Lsm4, and Khdrbs1/Sam68 were detected along with 9 chromatin remodeling genes including Mll, Bmi1, Smarcad1, Baf53a, and Hat1. We validated the transcriptional profile data with Northern blot analysis and in situ hybridization. The data greatly expand the catalogue of cell cycle components, transcription factors, and migration genes for adult SVZ neurogenesis and reveal RNA splicing and chromatin remodeling as prominent biological processes for these germinal cells.

Personality factors in flight operations. Volume 1: Leader characteristics and crew performance in a full-mission air transport simulation

NASA Technical Reports Server (NTRS)

Chidester, Thomas R.; Kanki, Barbara G.; Foushee, H. Clayton; Dickinson, Cortlandt L.; Bowles, Stephen V.

1990-01-01

Crew effectiveness is a joint product of the piloting skills, attitudes, and personality characteristics of team members. As obvious as this point might seem, both traditional approaches to optimizing crew performance and more recent training development highlighting crew coordination have emphasized only the skill and attitudinal dimensions. This volume is the first in a series of papers on this simulation. A subsequent volume will focus on patterns of communication within crews. The results of a full-mission simulation research study assessing the impact of individual personality on crew performance is reported. Using a selection algorithm described in previous research, captains were classified as fitting one of three profiles along a battery of personality assessment scales. The performances of 23 crews led by captains fitting each profile were contrasted over a one-and-one-half-day simulated trip. Crews led by captains fitting a positive Instrumental-Expressive profile (high achievement motivation and interpersonal skill) were consistently effective and made fewer errors. Crews led by captains fitting a Negative Expressive profile (below average achievement motivation, negative expressive style, such as complaining) were consistently less effective and made more errors. Crews led by captains fitting a Negative Instrumental profile (high levels of competitiveness, verbal aggressiveness, and impatience and irritability) were less effective on the first day but equal to the best on the second day. These results underscore the importance of stable personality variables as predictors of team coordination and performance.

Role of bioinformatics in establishing microRNAs as modulators of abiotic stress responses: the new revolution

PubMed Central

Tripathi, Anita; Goswami, Kavita; Sanan-Mishra, Neeti

2015-01-01

microRNAs (miRs) are a class of 21–24 nucleotide long non-coding RNAs responsible for regulating the expression of associated genes mainly by cleavage or translational inhibition of the target transcripts. With this characteristic of silencing, miRs act as an important component in regulation of plant responses in various stress conditions. In recent years, with drastic change in environmental and soil conditions different type of stresses have emerged as a major challenge for plants growth and productivity. The identification and profiling of miRs has itself been a challenge for research workers given their small size and large number of many probable sequences in the genome. Application of computational approaches has expedited the process of identification of miRs and their expression profiling in different conditions. The development of High-Throughput Sequencing (HTS) techniques has facilitated to gain access to the global profiles of the miRs for understanding their mode of action in plants. Introduction of various bioinformatics databases and tools have revolutionized the study of miRs and other small RNAs. This review focuses the role of bioinformatics approaches in the identification and study of the regulatory roles of plant miRs in the adaptive response to stresses. PMID:26578966

MicroRNA Profiling Reveals Marker of Motor Neuron Disease in ALS Models.

PubMed

Hoye, Mariah L; Koval, Erica D; Wegener, Amy J; Hyman, Theodore S; Yang, Chengran; O'Brien, David R; Miller, Rebecca L; Cole, Tracy; Schoch, Kathleen M; Shen, Tao; Kunikata, Tomonori; Richard, Jean-Philippe; Gutmann, David H; Maragakis, Nicholas J; Kordasiewicz, Holly B; Dougherty, Joseph D; Miller, Timothy M

2017-05-31

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder marked by the loss of motor neurons (MNs) in the brain and spinal cord, leading to fatally debilitating weakness. Because this disease predominantly affects MNs, we aimed to characterize the distinct expression profile of that cell type to elucidate underlying disease mechanisms and to identify novel targets that inform on MN health during ALS disease time course. microRNAs (miRNAs) are short, noncoding RNAs that can shape the expression profile of a cell and thus often exhibit cell-type-enriched expression. To determine MN-enriched miRNA expression, we used Cre recombinase-dependent miRNA tagging and affinity purification in mice. By defining the in vivo miRNA expression of MNs, all neurons, astrocytes, and microglia, we then focused on MN-enriched miRNAs via a comparative analysis and found that they may functionally distinguish MNs postnatally from other spinal neurons. Characterizing the levels of the MN-enriched miRNAs in CSF harvested from ALS models of MN disease demonstrated that one miRNA (miR-218) tracked with MN loss and was responsive to an ALS therapy in rodent models. Therefore, we have used cellular expression profiling tools to define the distinct miRNA expression of MNs, which is likely to enrich future studies of MN disease. This approach enabled the development of a novel, drug-responsive marker of MN disease in ALS rodents. SIGNIFICANCE STATEMENT Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons (MNs) in the brain and spinal cord are selectively lost. To develop tools to aid in our understanding of the distinct expression profiles of MNs and, ultimately, to monitor MN disease progression, we identified small regulatory microRNAs (miRNAs) that were highly enriched or exclusive in MNs. The signal for one of these MN-enriched miRNAs is detectable in spinal tap biofluid from an ALS rat model, where its levels change as disease progresses, suggesting that it may be a clinically useful marker of disease status. Furthermore, rats treated with ALS therapy have restored expression of this MN RNA marker, making it an MN-specific and drug-responsive marker for ALS rodents. Copyright © 2017 the authors 0270-6474/17/375574-13$15.00/0.

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiac allograft gene expression profiling test... Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a) Identification. A cardiac allograft gene expression profiling test system is a device that measures the...

Transcriptional profiling reveals regulated genes in the hippocampus during memory formation

NASA Technical Reports Server (NTRS)

Donahue, Christine P.; Jensen, Roderick V.; Ochiishi, Tomoyo; Eisenstein, Ingrid; Zhao, Mingrui; Shors, Tracey; Kosik, Kenneth S.

2002-01-01

Transcriptional profiling (TP) offers a powerful approach to identify genes activated during memory formation and, by inference, the molecular pathways involved. Trace eyeblink conditioning is well suited for the study of regional gene expression because it requires the hippocampus, whereas the highly parallel task, delay conditioning, does not. First, we determined when gene expression was most regulated during trace conditioning. Rats were exposed to 200 trials per day of paired and unpaired stimuli each day for 4 days. Changes in gene expression were most apparent 24 h after exposure to 200 trials. Therefore, we profiled gene expression in the hippocampus 24 h after 200 trials of trace eyeblink conditioning, on multiple arrays using additional animals. Of 1,186 genes on the filter array, seven genes met the statistical criteria and were also validated by real-time polymerase chain reaction. These genes were growth hormone (GH), c-kit receptor tyrosine kinase (c-kit), glutamate receptor, metabotropic 5 (mGluR5), nerve growth factor-beta (NGF-beta), Jun oncogene (c-Jun), transmembrane receptor Unc5H1 (UNC5H1), and transmembrane receptor Unc5H2 (UNC5H2). All these genes, except for GH, were downregulated in response to trace conditioning. GH was upregulated; therefore, we also validated the downregulation of the GH inhibitor, somatostatin (SST), even though it just failed to meet criteria on the arrays. By during situ hybridization, GH was expressed throughout the cell layers of the hippocampus in response to trace conditioning. None of the genes regulated in trace eyeblink conditioning were similarly affected by delay conditioning, a task that does not require the hippocampus. These findings demonstrate that transcriptional profiling can exhibit a repertoire of genes sensitive to the formation of hippocampal-dependent associative memories.

Dissecting modes of action of non-genotoxic carcinogens in primary mouse hepatocytes.

PubMed

Schaap, Mirjam M; Zwart, Edwin P; Wackers, Paul F K; Huijskens, Ilse; van de Water, Bob; Breit, Timo M; van Steeg, Harry; Jonker, Martijs J; Luijten, Mirjam

2012-11-01

Under REACH, the European Community Regulation on chemicals, the testing strategy for carcinogenicity is based on in vitro and in vivo genotoxicity assays. Given that non-genotoxic carcinogens are negative for genotoxicity and chronic bioassays are no longer regularly performed, this class of carcinogens will go undetected. Therefore, test systems detecting non-genotoxic carcinogens, or even better their modes of action, are required. Here, we investigated whether gene expression profiling in primary hepatocytes can be used to distinguish different modes of action of non-genotoxic carcinogens. For this, primary mouse hepatocytes were exposed to 16 non-genotoxic carcinogens with diverse modes of action. Upon profiling, pathway analysis was performed to obtain insight into the biological relevance of the observed changes in gene expression. Subsequently, both a supervised and an unsupervised comparison approach were applied to recognize the modes of action at the transcriptomic level. These analyses resulted in the detection of three of eight compound classes, that is, peroxisome proliferators, metalloids and skin tumor promotors. In conclusion, gene expression profiles in primary hepatocytes, at least in rodent hepatocytes, appear to be useful to detect some, certainly not all, modes of action of non-genotoxic carcinogens.

Gene expression complex networks: synthesis, identification, and analysis.

PubMed

Lopes, Fabrício M; Cesar, Roberto M; Costa, Luciano Da F

2011-10-01

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdös-Rényi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabási-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree variation, decreasing its network recovery rate with the increase of . The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Cancer cell redirection biomarker discovery using a mutual information approach.

PubMed

Roche, Kimberly; Feltus, F Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B S; Bentires-Alj, Mohamed; Booth, Brian W

2017-01-01

Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state.

Cancer cell redirection biomarker discovery using a mutual information approach

PubMed Central

Roche, Kimberly; Feltus, F. Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B. S.; Bentires-Alj, Mohamed

2017-01-01

Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state. PMID:28594912

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.

PubMed

Devonshire, Alison S; Elaswarapu, Ramnath; Foy, Carole A

2010-11-24

Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting. Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms. ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.

The transcriptomic and evolutionary signature of social interactions regulating honey bee caste development.

PubMed

Vojvodic, Svjetlana; Johnson, Brian R; Harpur, Brock A; Kent, Clement F; Zayed, Amro; Anderson, Kirk E; Linksvayer, Timothy A

2015-11-01

The caste fate of developing female honey bee larvae is strictly socially regulated by adult nurse workers. As a result of this social regulation, nurse-expressed genes as well as larval-expressed genes may affect caste expression and evolution. We used a novel transcriptomic approach to identify genes with putative direct and indirect effects on honey bee caste development, and we subsequently studied the relative rates of molecular evolution at these caste-associated genes. We experimentally induced the production of new queens by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their caregiving nurses before and after queen removal. By comparing the gene expression profiles of queen-destined versus worker-destined larvae as well as nurses observed feeding these two types of larvae, we identified larval and nurse genes associated with caste development. Of 950 differentially expressed genes associated with caste, 82% were expressed in larvae with putative direct effects on larval caste, and 18% were expressed in nurses with putative indirect effects on caste. Estimated selection coefficients suggest that both nurse and larval genes putatively associated with caste are rapidly evolving, especially those genes associated with worker development. Altogether, our results suggest that indirect effect genes play important roles in both the expression and evolution of socially influenced traits such as caste.

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

PubMed Central

Schütte, Judith; Wang, Huange; Antoniou, Stella; Jarratt, Andrew; Wilson, Nicola K; Riepsaame, Joey; Calero-Nieto, Fernando J; Moignard, Victoria; Basilico, Silvia; Kinston, Sarah J; Hannah, Rebecca L; Chan, Mun Chiang; Nürnberg, Sylvia T; Ouwehand, Willem H; Bonzanni, Nicola; de Bruijn, Marella FTR; Göttgens, Berthold

2016-01-01

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001 PMID:26901438

Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.

PubMed

Grimes, Tyler; Walker, Alejandro R; Datta, Susmita; Datta, Somnath

2018-05-30

Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles. The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets. Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients. This article was reviewed by Subharup Guha and Isabel Nepomuceno.

Acclimation to different depths by the marine angiosperm Posidonia oceanica: transcriptomic and proteomic profiles

PubMed Central

Dattolo, Emanuela; Gu, Jenny; Bayer, Philipp E.; Mazzuca, Silvia; Serra, Ilia A.; Spadafora, Antonia; Bernardo, Letizia; Natali, Lucia; Cavallini, Andrea; Procaccini, Gabriele

2013-01-01

For seagrasses, seasonal and daily variations in light and temperature represent the mains factors driving their distribution along the bathymetric cline. Changes in these environmental factors, due to climatic and anthropogenic effects, can compromise their survival. In a framework of conservation and restoration, it becomes crucial to improve our knowledge about the physiological plasticity of seagrass species along environmental gradients. Here, we aimed to identify differences in transcriptomic and proteomic profiles, involved in the acclimation along the depth gradient in the seagrass Posidonia oceanica, and to improve the available molecular resources in this species, which is an important requisite for the application of eco-genomic approaches. To do that, from plant growing in shallow (−5 m) and deep (−25 m) portions of a single meadow, (i) we generated two reciprocal Expressed Sequences Tags (EST) libraries using a Suppressive Subtractive Hybridization (SSH) approach, to obtain depth/specific transcriptional profiles, and (ii) we identified proteins differentially expressed, using the highly innovative USIS mass spectrometry methodology, coupled with 1D-SDS electrophoresis and labeling free approach. Mass spectra were searched in the open source Global Proteome Machine (GPM) engine against plant databases and with the X!Tandem algorithm against a local database. Transcriptional analysis showed both quantitative and qualitative differences between depths. EST libraries had only the 3% of transcripts in common. A total of 315 peptides belonging to 64 proteins were identified by mass spectrometry. ATP synthase subunits were among the most abundant proteins in both conditions. Both approaches identified genes and proteins in pathways related to energy metabolism, transport and genetic information processing, that appear to be the most involved in depth acclimation in P. oceanica. Their putative rules in acclimation to depth were discussed. PMID:23785376

Acclimation to different depths by the marine angiosperm Posidonia oceanica: transcriptomic and proteomic profiles.

PubMed

Dattolo, Emanuela; Gu, Jenny; Bayer, Philipp E; Mazzuca, Silvia; Serra, Ilia A; Spadafora, Antonia; Bernardo, Letizia; Natali, Lucia; Cavallini, Andrea; Procaccini, Gabriele

2013-01-01

For seagrasses, seasonal and daily variations in light and temperature represent the mains factors driving their distribution along the bathymetric cline. Changes in these environmental factors, due to climatic and anthropogenic effects, can compromise their survival. In a framework of conservation and restoration, it becomes crucial to improve our knowledge about the physiological plasticity of seagrass species along environmental gradients. Here, we aimed to identify differences in transcriptomic and proteomic profiles, involved in the acclimation along the depth gradient in the seagrass Posidonia oceanica, and to improve the available molecular resources in this species, which is an important requisite for the application of eco-genomic approaches. To do that, from plant growing in shallow (-5 m) and deep (-25 m) portions of a single meadow, (i) we generated two reciprocal Expressed Sequences Tags (EST) libraries using a Suppressive Subtractive Hybridization (SSH) approach, to obtain depth/specific transcriptional profiles, and (ii) we identified proteins differentially expressed, using the highly innovative USIS mass spectrometry methodology, coupled with 1D-SDS electrophoresis and labeling free approach. Mass spectra were searched in the open source Global Proteome Machine (GPM) engine against plant databases and with the X!Tandem algorithm against a local database. Transcriptional analysis showed both quantitative and qualitative differences between depths. EST libraries had only the 3% of transcripts in common. A total of 315 peptides belonging to 64 proteins were identified by mass spectrometry. ATP synthase subunits were among the most abundant proteins in both conditions. Both approaches identified genes and proteins in pathways related to energy metabolism, transport and genetic information processing, that appear to be the most involved in depth acclimation in P. oceanica. Their putative rules in acclimation to depth were discussed.

Gene expression profiling in whole blood of patients with coronary artery disease

PubMed Central

Taurino, Chiara; Miller, William H.; McBride, Martin W.; McClure, John D.; Khanin, Raya; Moreno, María U.; Dymott, Jane A.; Delles, Christian; Dominiczak, Anna F.

2010-01-01

Owing to the dynamic nature of the transcriptome, gene expression profiling is a promising tool for discovery of disease-related genes and biological pathways. In the present study, we examined gene expression in whole blood of 12 patients with CAD (coronary artery disease) and 12 healthy control subjects. Furthermore, ten patients with CAD underwent whole-blood gene expression analysis before and after the completion of a cardiac rehabilitation programme following surgical coronary revascularization. mRNA and miRNA (microRNA) were isolated for expression profiling. Gene expression analysis identified 365 differentially expressed genes in patients with CAD compared with healthy controls (175 up- and 190 down-regulated in CAD), and 645 in CAD rehabilitation patients (196 up- and 449 down-regulated post-rehabilitation). Biological pathway analysis identified a number of canonical pathways, including oxidative phosphorylation and mitochondrial function, as being significantly and consistently modulated across the groups. Analysis of miRNA expression revealed a number of differentially expressed miRNAs, including hsa-miR-140-3p (control compared with CAD, P=0.017), hsa-miR-182 (control compared with CAD, P=0.093), hsa-miR-92a and hsa-miR-92b (post- compared with pre-exercise, P<0.01). Global analysis of predicted miRNA targets found significantly reduced expression of genes with target regions compared with those without: hsa-miR-140-3p (P=0.002), hsa-miR-182 (P=0.001), hsa-miR-92a and hsa-miR-92b (P=2.2×10−16). In conclusion, using whole blood as a ‘surrogate tissue’ in patients with CAD, we have identified differentially expressed miRNAs, differentially regulated genes and modulated pathways which warrant further investigation in the setting of cardiovascular function. This approach may represent a novel non-invasive strategy to unravel potentially modifiable pathways and possible therapeutic targets in cardiovascular disease. PMID:20528768

Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data.

PubMed

Kannan, Soumya; Sams, Thomas; Maury, Jérôme; Workman, Christopher T

2018-03-16

Accurate characterization of promoter activity is important when designing expression systems for systems biology and metabolic engineering applications. Promoters that respond to changes in the environment enable the dynamic control of gene expression without the necessity of inducer compounds, for example. However, the dynamic nature of these processes poses challenges for estimating promoter activity. Most experimental approaches utilize reporter gene expression to estimate promoter activity. Typically the reporter gene encodes a fluorescent protein that is used to infer a constant promoter activity despite the fact that the observed output may be dynamic and is a number of steps away from the transcription process. In fact, some promoters that are often thought of as constitutive can show changes in activity when growth conditions change. For these reasons, we have developed a system of ordinary differential equations for estimating dynamic promoter activity for promoters that change their activity in response to the environment that is robust to noise and changes in growth rate. Our approach, inference of dynamic promoter activity (PromAct), improves on existing methods by more accurately inferring known promoter activity profiles. This method is also capable of estimating the correct scale of promoter activity and can be applied to quantitative data sets to estimate quantitative rates.

Cell Fate Decision as High-Dimensional Critical State Transition

PubMed Central

Zhou, Joseph; Castaño, Ivan G.; Leong-Quong, Rebecca Y. Y.; Chang, Hannah; Trachana, Kalliopi; Giuliani, Alessandro; Huang, Sui

2016-01-01

Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of “rebellious cells” that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease. PMID:28027308

Genetics, gene expression and bioinformatics of the pituitary gland.

PubMed

Davis, Shannon W; Potok, Mary Anne; Brinkmeier, Michelle L; Carninci, Piero; Lyons, Robert H; MacDonald, James W; Fleming, Michelle T; Mortensen, Amanda H; Egashira, Noboru; Ghosh, Debashis; Steel, Karen P; Osamura, Robert Y; Hayashizaki, Yoshihide; Camper, Sally A

2009-04-01

Genetic cases of congenital pituitary hormone deficiency are common and many are caused by transcription factor defects. Mouse models with orthologous mutations are invaluable for uncovering the molecular mechanisms that lead to problems in organ development and typical patient characteristics. We are using mutant mice defective in the transcription factors PROP1 and POU1F1 for gene expression profiling to identify target genes for these critical transcription factors and candidates for cases of pituitary hormone deficiency of unknown aetiology. These studies reveal critical roles for Wnt signalling pathways, including the TCF/LEF transcription factors and interacting proteins of the groucho family, bone morphogenetic protein antagonists and targets of notch signalling. Current studies are investigating the roles of novel homeobox genes and pathways that regulate the transition from proliferation to differentiation, cell adhesion and cell migration. Pituitary adenomas are a common human health problem, yet most cases are sporadic, necessitating alternative approaches to traditional Mendelian genetic studies. Mouse models of adenoma formation offer the opportunity for gene expression profiling during progressive stages of hyperplasia, adenoma and tumorigenesis. This approach holds promise for the identification of relevant pathways and candidate genes as risk factors for adenoma formation, understanding mechanisms of progression, and identifying drug targets and clinically relevant biomarkers. Copyright 2009 S. Karger AG, Basel.

Profiling the resting venom gland of the scorpion Tityus stigmurus through a transcriptomic survey.

PubMed

Almeida, Diego D; Scortecci, Katia C; Kobashi, Leonardo S; Agnez-Lima, Lucymara F; Medeiros, Silvia R B; Silva-Junior, Arnóbio A; Junqueira-de-Azevedo, Inácio de L M; Fernandes-Pedrosa, Matheus de F

2012-08-01

The scorpion Tityus stigmurus is widely distributed in Northeastern Brazil and known to cause severe human envenoming, inducing pain, hyposthesia, edema, erythema, paresthesia, headaches and vomiting. The present study uses a transcriptomic approach to characterize the gene expression profile from the non-stimulated venom gland of Tityus stigmurus scorpion. A cDNA library was constructed and 540 clones were sequenced and grouped into 153 clusters, with one or more ESTs (expressed sequence tags). Forty-one percent of ESTs belong to recognized toxin-coding sequences, with transcripts encoding antimicrobial toxins (AMP-like) being the most abundant, followed by alfa KTx- like, beta KTx-like, beta NaTx-like and alfa NaTx-like. Our analysis indicated that 34% of the transcripts encode "other possible venom molecules", which correspond to anionic peptides, hypothetical secreted peptides, metalloproteinases, cystein-rich peptides and lectins. Fifteen percent of ESTs are similar to cellular transcripts. Sequences without good matches corresponded to 11%. This investigation provides the first global view of gene expression of the venom gland from Tityus stigmurus under resting conditions. This approach enables characterization of a large number of venom gland component molecules, which belong either to known or non yet described types of venom peptides and proteins from the Buthidae family.

Genetics, Gene Expression and Bioinformatics of the Pituitary Gland

PubMed Central

Davis, Shannon W; Potok, Mary Anne; Brinkmeier, Michelle L; Carninci, Piero; Lyons, Robert H; MacDonald, James W.; Fleming, Michelle T; Mortensen, Amanda H; Egashira, Noboru; Ghosh, Debashis; Steel, Karen P.; Osamura, Robert Y; Hayashizaki, Yoshihide; Camper, Sally A

2011-01-01

Genetic cases of congenital pituitary hormone deficiency are common and many are caused by transcription factor defects. Mouse models with orthologous mutations are invaluable for uncovering the molecular mechanisms that lead to problems in organ development and typical patient characteristics. We are using mutant mice defective in the transcription factors PROP1 and POU1F1 for gene expression profiling to identify target genes for these critical transcription factors and candidates for cases of pituitary hormone deficiency of unknown etiology. These studies reveal critical roles for Wnt signalling pathways including the TCF/LEF transcription factors and interacting proteins of the groucho family, bone morphogenetic proteins antagonists, and targets of notch signalling. Current studies are investigating roles of novel homeobox genes and pathways that regulate the transition from proliferation to differentiation, cell adhesion and cell migration. Pituitary adenomas are a common human health problem, yet most cases are sporadic, necessitating alternative approaches to traditional Mendelian genetic studies. Mouse models of adenoma formation offer the opportunity for gene expression profiling during progressive stages of hyperplasia, adenoma and tumorigenesis. This approach holds promise for identification of relevant pathways and candidate genes as risk factors for adenoma formation, understanding mechanisms of progression, and identifying drug targets and clinically relevant biomarkers. PMID:19407506

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Circulating MicroRNAs as Novel Biomarkers of Stenosis Progression in Asymptomatic Carotid Stenosis.

PubMed

Dolz, Sandra; Górriz, David; Tembl, José Ignacio; Sánchez, Dolors; Fortea, Gerardo; Parkhutik, Vera; Lago, Aida

2017-01-01

Progression of asymptomatic carotid artery stenosis (ACAS) in patients with >50% luminal narrowing is considered a potential risk factor for ischemic stroke; however, subclinical molecular biomarkers of ACAS progression are lacking. Recent studies suggest a regulatory function for several microRNAs (miRNAs) on the evolution of carotid plaque, but its role in ACAS progression is mostly unknown. The aim of our study was to investigate a wide miRNA panel in peripheral blood exosomes from patients with ACAS to associate circulating miRNA expression profiles with stenosis progression. The study included 60 patients with ACAS carrying >50% luminal narrowing. First, miRNA expression profiles of circulating exosomes were determined by Affymetrix microarrays from plasma samples of 16 patients from the cohort. Second, those miRNAs among the most differentially expressed in patients with ACAS progression were quantified by real-time polymerase chain reaction in a separate replication cohort of 39 subjects within the patient sample. Our results showed that ACAS progression was associated with development of stroke. MiR-199b-3p, miR-27b-3p, miR-130a-3p, miR-221-3p, and miR-24-3p presented significant higher expression in those patients with ACAS progression. In conclusion, our study supports that specific circulating miRNA expression profiles could provide a new tool that complements the monitoring of ACAS progression, improving therapeutic approaches to prevent ischemic stroke. © 2016 American Heart Association, Inc.

Use of Partial Least Squares improves the efficacy of removing unwanted variability in differential expression analyses based on RNA-Seq data.

PubMed

Chakraborty, Sutirtha

2018-05-26

RNA-Seq technology has revolutionized the face of gene expression profiling by generating read count data measuring the transcript abundances for each queried gene on multiple experimental subjects. But on the downside, the underlying technical artefacts and hidden biological profiles of the samples generate a wide variety of latent effects that may potentially distort the actual transcript/gene expression signals. Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses. In this work I demonstrate the use of Partial Least Squares (built as an R package 'SVAPLSseq') to correct for the traces of extraneous variability in RNA-Seq data. A novel and thorough comparative analysis of the PLS based method is presented along with some of the other popularly used approaches for latent variable correction in RNA-Seq. Overall, the method is found to achieve a substantially improved estimation of the hidden effect signatures in the RNA-Seq transcriptome expression landscape compared to other available techniques. Copyright © 2017. Published by Elsevier Inc.

RNA Expression Analysis of Passive Transfer Myasthenia Supports Extraocular Muscle as a Unique Immunological Environment

PubMed Central

Zhou, Yuefang; Kaminski, Henry J.; Gong, Bendi; Cheng, Georgiana; Feuerman, Jason M.; Kusner, Linda

2014-01-01

Purpose. Myasthenia gravis demonstrates a distinct predilection for involvement of the extraocular muscles (EOM), and we have hypothesized that this may be due to a unique immunological environment. To assess this hypothesis, we took an unbiased approach to analyze RNA expression profiles in EOM, diaphragm, and extensor digitorum longus (EDL) in rats with experimentally acquired myasthenia gravis (EAMG). Methods. Experimentally acquired myasthenia gravis was induced in rats by intraperitoneal injection of antibody directed against the acetylcholine receptor (AChR), whereas control rats received antibody known to bind the AChR but not induce disease. After 48 hours, animals were killed and muscles analyzed by RNA expression profiling. Profiling results were validated using qPCR and immunohistochemical analysis. Results. Sixty-two genes common among all muscle groups were increased in expression. These fell into four major categories: 12.8% stress response, 10.5% immune response, 10.5% metabolism, and 9.0% transcription factors. EOM expressed 212 genes at higher levels, not shared by the other two muscles, and a preponderance of EOM gene changes fell into the immune response category. EOM had the most uniquely reduced genes (126) compared with diaphragm (26) and EDL (50). Only 18 downregulated genes were shared by the three muscles. Histological evaluation and disease load index (sum of fold changes for all genes) demonstrated that EOM had the greatest degree of pathology. Conclusions. Our studies demonstrated that consistent with human myasthenia gravis, EOM demonstrates a distinct RNA expression signature from EDL and diaphragm, which is based on differences in the degree of muscle injury and inflammatory response. PMID:24917137

Reverse engineering of gene regulatory networks.

PubMed

Cho, K H; Choo, S M; Jung, S H; Kim, J R; Choi, H S; Kim, J

2007-05-01

Systems biology is a multi-disciplinary approach to the study of the interactions of various cellular mechanisms and cellular components. Owing to the development of new technologies that simultaneously measure the expression of genetic information, systems biological studies involving gene interactions are increasingly prominent. In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. Various approaches of inferring GRNs from gene expression profiles and biological information, including machine learning approaches, have been reviewed, with a brief introduction of DNA microarray experiments as typical tools for measuring levels of messenger ribonucleic acid (mRNA) expression. In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect to the other methods. In addition, recent developments in this field are introduced and discussions on the challenges and opportunities for future research are provided.

Comparison of the Functional microRNA Expression in Immune Cell Subsets of Neonates and Adults

PubMed Central

Yu, Hong-Ren; Hsu, Te-Yao; Huang, Hsin-Chun; Kuo, Ho-Chang; Li, Sung-Chou; Yang, Kuender D.; Hsieh, Kai-Sheng

2016-01-01

Diversity of biological molecules in newborn and adult immune cells contributes to differences in cell function and atopic properties. Micro RNAs (miRNAs) are reported to involve in the regulation of immune system. Therefore, determining the miRNA expression profile of leukocyte subpopulations is important for understanding immune system regulation. In order to explore the unique miRNA profiling that contribute to altered immune in neonates, we comprehensively analyzed the functional miRNA signatures of eight leukocyte subsets (polymorphonuclear cells, monocytes, CD4+ T cells, CD8+ T cells, natural killer cells, B cells, plasmacytoid dendritic cells, and myeloid dendritic cells) from both neonatal and adult umbilical cord and peripheral blood samples, respectively. We observed distinct miRNA profiles between adult and neonatal blood leukocyte subsets, including unique miRNA signatures for each cell lineage. Leukocyte miRNA signatures were altered after stimulation. Adult peripheral leukocytes had higher let-7b-5p expression levels compared to neonatal cord leukocytes across multiple subsets, irrespective of stimulation. Transfecting neonatal monocytes with a let-7b-5p mimic resulted in a reduction of LPS-induced interleukin (IL)-6 and TNF-α production, while transfection of a let-7b-5p inhibitor into adult monocytes enhanced IL-6 and TNF-α production. With this functional approach, we provide intact differential miRNA expression profiling of specific immune cell subsets between neonates and adults. These studies serve as a basis to further understand the altered immune response observed in neonates and advance the development of therapeutic strategies. PMID:28066425

Host-Microbe Interactions in the Neonatal Intestine: Role of Human Milk Oligosaccharides123

PubMed Central

Donovan, Sharon M.; Wang, Mei; Li, Min; Friedberg, Iddo; Schwartz, Scott L.; Chapkin, Robert S.

2012-01-01

The infant intestinal microbiota is shaped by genetics and environment, including the route of delivery and early dietary intake. Data from germ-free rodents and piglets support a critical role for the microbiota in regulating gastrointestinal and immune development. Human milk oligosaccharides (HMO) both directly and indirectly influence intestinal development by regulating cell proliferation, acting as prebiotics for beneficial bacteria and modulating immune development. We have shown that the gut microbiota, the microbial metatranscriptome, and metabolome differ between porcine milk–fed and formula-fed (FF) piglets. Our goal is to define how early nutrition, specifically HMO, shapes host-microbe interactions in breast-fed (BF) and FF human infants. We an established noninvasive method that uses stool samples containing intact sloughed epithelial cells to quantify intestinal gene expression profiles in human infants. We hypothesized that a systems biology approach, combining i) HMO composition of the mother’s milk with the infant’s gut gene expression and fecal bacterial composition, ii) gene expression, and iii short-chain fatty acid profiles would identify important mechanistic pathways affecting intestinal development of BF and FF infants in the first few months of life. HMO composition was analyzed by HLPC Chip/time-of-flight MS and 3 HMO clusters were identified using principle component analysis. Initial findings indicated that both host epithelial cell mRNA expression and the microbial phylogenetic profiles provided strong feature sets that distinctly classified the BF and FF infants. Ongoing analyses are designed to integrate the host transcriptome, bacterial phylogenetic profiles, and functional metagenomic data using multivariate statistical analyses. PMID:22585924

The role of childhood maltreatment in the altered trait and global expression of personality in cocaine addiction

PubMed Central

Brents, Lisa K; Tripathi, Shanti Prakash; Young, Jonathan; James, G Andrew; Kilts, Clinton D

2015-01-01

Background and aims Drug addictions are debilitating disorders that are highly associated with personality abnormalities. Early life stress (ELS) is a common risk factor for addiction and personality disturbances, but the relationships between ELS, addiction, and personality are poorly understood. Methods Ninety-five research participants were assessed for and grouped by ELS history and cocaine dependence. NEO-FFI personality measures were compared between the groups to define ELS− and addiction-related differences in personality traits. ELS and cocaine dependence were then examined as predictors of personality trait scores. Finally, k-means clustering was used to uncover clusters of personality trait configurations within the sample. Odds of cluster membership across subject groups was then determined. Results Trait expression differed significantly across subject groups. Cocaine-dependent subjects with a history of ELS (cocaine+/ELS+) displayed the greatest deviations in normative personality. Cocaine dependence significantly predicted four traits, while ELS predicted neuroticism and agreeableness; there was no interaction effect between ELS and cocaine dependence. The cluster analysis identified four distinct personality profiles: Open, Gregarious, Dysphoric, and Closed. Distribution of these profiles across subject groups differed significantly. Inclusion in cocaine+/ELS+, cocaine−/ELS+, and cocaine−/ELS− groups significantly increased the odds of expressing the Dysphoric, Open and Gregarious profiles, respectively. Conclusions Cocaine dependence and early life stress were significantly and differentially associated with altered expression of individual personality traits and their aggregation as personality profiles, suggesting that individuals who are at-risk for developing addictions due to ELS exposure may benefit from personality centered approaches as an early intervention and prevention. PMID:25805246

Quantitative proteomics reveals protein profiles underlying major transitions in aspen wood development.

PubMed

Obudulu, Ogonna; Bygdell, Joakim; Sundberg, Björn; Moritz, Thomas; Hvidsten, Torgeir R; Trygg, Johan; Wingsle, Gunnar

2016-02-18

Wood development is of outstanding interest both to basic research and industry due to the associated cellulose and lignin biomass production. Efforts to elucidate wood formation (which is essential for numerous aspects of both pure and applied plant science) have been made using transcriptomic analyses and/or low-resolution sampling. However, transcriptomic data do not correlate perfectly with levels of expressed proteins due to effects of post-translational modifications and variations in turnover rates. In addition, high-resolution analysis is needed to characterize key transitions. In order to identify protein profiles across the developmental region of wood formation, an in-depth and tissue specific sampling was performed. We examined protein profiles, using an ultra-performance liquid chromatography/quadrupole time of flight mass spectrometry system, in high-resolution tangential sections spanning all wood development zones in Populus tremula from undifferentiated cambium to mature phloem and xylem, including cell expansion and cell death zones. In total, we analyzed 482 sections, 20-160 μm thick, from four 47-year-old trees growing wild in Sweden. We obtained high quality expression profiles for 3,082 proteins exhibiting consistency across the replicates, considering that the trees were growing in an uncontrolled environment. A combination of Principal Component Analysis (PCA), Orthogonal Projections to Latent Structures (OPLS) modeling and an enhanced stepwise linear modeling approach identified several major transitions in global protein expression profiles, pinpointing (for example) locations of the cambial division leading to phloem and xylem cells, and secondary cell wall formation zones. We also identified key proteins and associated pathways underlying these developmental landmarks. For example, many of the lignocellulosic related proteins were upregulated in the expansion to the early developmental xylem zone, and for laccases with a rapid decrease in early xylem zones. We observed upregulation of two forms of xylem cysteine protease (Potri.002G005700.1 and Potri.005G256000.2; Pt-XCP2.1) in early xylem and their downregulation in late maturing xylem. Our data also show that Pt-KOR1.3 (Potri.003G151700.2) exhibits an expression pattern that supports the hypothesis put forward in previous studies that this is a key xyloglucanase involved in cellulose biosynthesis in primary cell walls and reduction of cellulose crystallinity in secondary walls. Our novel multivariate approach highlights important processes and provides confirmatory insights into the molecular foundations of wood development.

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

PubMed

Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Sulforaphane reduces hepatic glucose production and improves glucose control in patients with type 2 diabetes

USDA-ARS?s Scientific Manuscript database

A potentially useful approach for drug discovery is to connect gene expression profiles of disease-affected tissues ("disease signatures") to drug signatures, but it remains to be shown whether it can be used to identify clinically relevant treatment options. We analyzed coexpression networks and ge...

GENOMICS SYMPOSIUM: Using genomic approaches to uncover sources of variation in age at puberty and reproductive longevity in sows

USDA-ARS?s Scientific Manuscript database

Genetic variants associated with traits such as age at puberty and litter size could provide insight into the underlying genetic sources of variation impacting sow reproductive longevity and productivity. Genomewide characterization and gene expression profiling were used using gilts from the Univer...

Integrative genomic and proteomic profiling of human neuroblastoma SH-SY5Y cells reveals signatures of endosulfan exposure.

PubMed

Gandhi, Deepa; Tarale, Prashant; Naoghare, Pravin K; Bafana, Amit; Kannan, Krishnamurthi; Sivanesan, Saravanadevi

2016-01-01

Endosulfan, an organochlorine pesticide, is known to induce multiple disorders/abnormalities including neuro-degenerative disorders in many animal species. However, the molecular mechanism of endosulfan induced neuronal alterations is still not well understood. In the present study, the effect of sub-lethal concentration of endosulfan (3 μM) on human neuroblastoma cells (SH-SY5Y) was investigated using genomic and proteomic approaches. Microarray and 2D-PAGE followed by MALDI-TOF-MS analysis revealed differential expression of 831 transcripts and 16 proteins in exposed cells. A gene ontology enrichment analysis revealed that the differentially expressed genes and proteins were involved in variety of cellular events such as neuronal developmental pathway, immune response, cell differentiation, apoptosis, transmission of nerve impulse, axonogenesis, etc. The present study attempted to explore the possible molecular mechanism of endosulfan induced neuronal alterations in SH-SY5Y cells using an integrated genomic and proteomic approach. Based on the gene and protein profile possible mechanisms underlying endosulfan neurotoxicity were predicted. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantifying wall turbulence via a symmetry approach: A Lie group theory

NASA Astrophysics Data System (ADS)

She, Zhen-Su; Chen, Xi; Hussain, Fazle

2017-11-01

We present a symmetry-based approach which yields analytic expressions for the mean velocity and kinetic energy profiles from a Lie-group analysis. After verifying the dilation-group invariance of the Reynolds averaged Navier-Stokes equation in the presence of a wall, we select a stress and energy length function as similarity variables which are assumed to have a simple dilation-invariant form. Three kinds of (local) invariant forms of the length functions are postulated, a combination of which yields a multi-layer formula giving its distribution in the entire flow region normal to the wall. The mean velocity profile is then predicted using the mean momentum equation, which yields, in particular, analytic expressions for the (universal) wall function and separate wake functions for pipe and channel - which are validated by data from direct numerical simulations (DNS). Future applications to a variety of wall flows such as flows around flat plate or airfoil, in a Rayleigh-Benard cell or Taylor-Couette system, etc., are discussed, for which the dilation group invariance is valid in the wall-normal direction.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shakoor, N; Nair, R; Crasta, O

2014-01-23

Background: Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results: This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specificmore » probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e. g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions: Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.« less

Multi-targeted priming for genome-wide gene expression assays.

PubMed

Adomas, Aleksandra B; Lopez-Giraldez, Francesc; Clark, Travis A; Wang, Zheng; Townsend, Jeffrey P

2010-08-17

Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and precise assay of the transcribed sequences within the genome.

De novo assembled expressed gene catalog of a fast-growing Eucalyptus tree produced by Illumina mRNA-Seq

PubMed Central

2010-01-01

Background De novo assembly of transcript sequences produced by short-read DNA sequencing technologies offers a rapid approach to obtain expressed gene catalogs for non-model organisms. A draft genome sequence will be produced in 2010 for a Eucalyptus tree species (E. grandis) representing the most important hardwood fibre crop in the world. Genome annotation of this valuable woody plant and genetic dissection of its superior growth and productivity will be greatly facilitated by the availability of a comprehensive collection of expressed gene sequences from multiple tissues and organs. Results We present an extensive expressed gene catalog for a commercially grown E. grandis × E. urophylla hybrid clone constructed using only Illumina mRNA-Seq technology and de novo assembly. A total of 18,894 transcript-derived contigs, a large proportion of which represent full-length protein coding genes were assembled and annotated. Analysis of assembly quality, length and diversity show that this dataset represent the most comprehensive expressed gene catalog for any Eucalyptus tree. mRNA-Seq analysis furthermore allowed digital expression profiling of all of the assembled transcripts across diverse xylogenic and non-xylogenic tissues, which is invaluable for ascribing putative gene functions. Conclusions De novo assembly of Illumina mRNA-Seq reads is an efficient approach for transcriptome sequencing and profiling in Eucalyptus and other non-model organisms. The transcriptome resource (Eucspresso, http://eucspresso.bi.up.ac.za/) generated by this study will be of value for genomic analysis of woody biomass production in Eucalyptus and for comparative genomic analysis of growth and development in woody and herbaceous plants. PMID:21122097

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

A Microwave Radiometric Method to Obtain the Average Path Profile of Atmospheric Temperature and Humidity Structure Parameters and Its Application to Optical Propagation System Assessment

NASA Technical Reports Server (NTRS)

Manning, Robert M.; Vyhnalek, Brian E.

2015-01-01

The values of the key atmospheric propagation parameters Ct2, Cq2, and Ctq are highly dependent upon the vertical height within the atmosphere thus making it necessary to specify profiles of these values along the atmospheric propagation path. The remote sensing method suggested and described in this work makes use of a rapidly integrating microwave profiling radiometer to capture profiles of temperature and humidity through the atmosphere. The integration times of currently available profiling radiometers are such that they are approaching the temporal intervals over which one can possibly make meaningful assessments of these key atmospheric parameters. Since these parameters are fundamental to all propagation conditions, they can be used to obtain Cn2 profiles for any frequency, including those for an optical propagation path. In this case the important performance parameters of the prevailing isoplanatic angle and Greenwood frequency can be obtained. The integration times are such that Kolmogorov turbulence theory and the Taylor frozen-flow hypothesis must be transcended. Appropriate modifications to these classical approaches are derived from first principles and an expression for the structure functions are obtained. The theory is then applied to an experimental scenario and shows very good results.

Subcellular RNA profiling links splicing and nuclear DICER1 to alternative cleavage and polyadenylation

PubMed Central

Neve, Jonathan; Burger, Kaspar; Li, Wencheng; Hoque, Mainul; Patel, Radhika; Tian, Bin; Gullerova, Monika; Furger, Andre

2016-01-01

Alternative cleavage and polyadenylation (APA) plays a crucial role in the regulation of gene expression across eukaryotes. Although APA is extensively studied, its regulation within cellular compartments and its physiological impact remains largely enigmatic. Here, we used a rigorous subcellular fractionation approach to compare APA profiles of cytoplasmic and nuclear RNA fractions from human cell lines. This approach allowed us to extract APA isoforms that are subjected to differential regulation and provided us with a platform to interrogate the molecular regulatory pathways that shape APA profiles in different subcellular locations. Here, we show that APA isoforms with shorter 3′ UTRs tend to be overrepresented in the cytoplasm and appear to be cell-type–specific events. Nuclear retention of longer APA isoforms occurs and is partly a result of incomplete splicing contributing to the observed cytoplasmic bias of transcripts with shorter 3′ UTRs. We demonstrate that the endoribonuclease III, DICER1, contributes to the establishment of subcellular APA profiles not only by expected cytoplasmic miRNA-mediated destabilization of APA mRNA isoforms, but also by affecting polyadenylation site choice. PMID:26546131

A stochastic model for optimizing composite predictors based on gene expression profiles.

PubMed

Ramanathan, Murali

2003-07-01

This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Distinct polyadenylation landscapes of diverse human tissues revealed by a modified PA-seq strategy

PubMed Central

2013-01-01

Background Polyadenylation is a key regulatory step in eukaryotic gene expression and one of the major contributors of transcriptome diversity. Aberrant polyadenylation often associates with expression defects and leads to human diseases. Results To better understand global polyadenylation regulation, we have developed a polyadenylation sequencing (PA-seq) approach. By profiling polyadenylation events in 13 human tissues, we found that alternative cleavage and polyadenylation (APA) is prevalent in both protein-coding and noncoding genes. In addition, APA usage, similar to gene expression profiling, exhibits tissue-specific signatures and is sufficient for determining tissue origin. A 3′ untranslated region shortening index (USI) was further developed for genes with tandem APA sites. Strikingly, the results showed that different tissues exhibit distinct patterns of shortening and/or lengthening of 3′ untranslated regions, suggesting the intimate involvement of APA in establishing tissue or cell identity. Conclusions This study provides a comprehensive resource to uncover regulated polyadenylation events in human tissues and to characterize the underlying regulatory mechanism. PMID:24025092

Current status of gene expression profiling in the diagnosis and management of acute leukaemia.

PubMed

Bacher, Ulrike; Kohlmann, Alexander; Haferlach, Torsten

2009-06-01

Gene expression profiling (GEP) enables the simultaneous investigation of the expression of tens of thousands of genes and was successfully introduced in leukaemia research a decade ago. Aiming to better understand the diversity of genetic aberrations in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), pioneer studies investigated and confirmed the predictability of many cytogenetic and molecular subclasses in AML and ALL. In addition, GEP can define new prognostic subclasses within distinct leukaemia subgroups, as illustrated in AML with normal karyotype. Another approach is the development of treatment-specific sensitivity assays, which might contribute to targeted therapy studies. Finally, GEP might enable the detection of new molecular targets for therapy in patients with acute leukaemia. Meanwhile, large multicentre studies, e.g. the Microarray Innovations in LEukaemia (MILE) study, prepare for a standardised introduction of GEP in leukaemia diagnostic algorithms, aiming to translate this novel methodology into clinical routine for the benefit of patients with the complex disorders of AML and ALL.

Analysis of microRNA profile of Anopheles sinensis by deep sequencing and bioinformatic approaches.

PubMed

Feng, Xinyu; Zhou, Xiaojian; Zhou, Shuisen; Wang, Jingwen; Hu, Wei

2018-03-12

microRNAs (miRNAs) are small non-coding RNAs widely identified in many mosquitoes. They are reported to play important roles in development, differentiation and innate immunity. However, miRNAs in Anopheles sinensis, one of the Chinese malaria mosquitoes, remain largely unknown. We investigated the global miRNA expression profile of An. sinensis using Illumina Hiseq 2000 sequencing. Meanwhile, we applied a bioinformatic approach to identify potential miRNAs in An. sinensis. The identified miRNA profiles were compared and analyzed by two approaches. The selected miRNAs from the sequencing result and the bioinformatic approach were confirmed with qRT-PCR. Moreover, target prediction, GO annotation and pathway analysis were carried out to understand the role of miRNAs in An. sinensis. We identified 49 conserved miRNAs and 12 novel miRNAs by next-generation high-throughput sequencing technology. In contrast, 43 miRNAs were predicted by the bioinformatic approach, of which two were assigned as novel. Comparative analysis of miRNA profiles by two approaches showed that 21 miRNAs were shared between them. Twelve novel miRNAs did not match any known miRNAs of any organism, indicating that they are possibly species-specific. Forty miRNAs were found in many mosquito species, indicating that these miRNAs are evolutionally conserved and may have critical roles in the process of life. Both the selected known and novel miRNAs (asi-miR-281, asi-miR-184, asi-miR-14, asi-miR-nov5, asi-miR-nov4, asi-miR-9383, and asi-miR-2a) could be detected by quantitative real-time PCR (qRT-PCR) in the sequenced sample, and the expression patterns of these miRNAs measured by qRT-PCR were in concordance with the original miRNA sequencing data. The predicted targets for the known and the novel miRNAs covered many important biological roles and pathways indicating the diversity of miRNA functions. We also found 21 conserved miRNAs and eight counterparts of target immune pathway genes in An. sinensis based on the analysis of An. gambiae. Our results provide the first lead to the elucidation of the miRNA profile in An. sinensis. Unveiling the roles of mosquito miRNAs will undoubtedly lead to a better understanding of mosquito biology and mosquito-pathogen interactions. This work lays the foundation for the further functional study of An. sinensis miRNAs and will facilitate their application in vector control.

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

Extension of microRNA expression pattern associated with high-risk neuroblastoma.

PubMed

Bienertova-Vasku, Julie; Mazanek, Pavel; Hezova, Renata; Curdova, Anna; Nekvindova, Jana; Kren, Leos; Sterba, Jaroslav; Slaby, Ondrej

2013-08-01

Clinical behavior of neuroblastoma (NBL) is remarkably heterogeneous, as it ranges from spontaneous regression to aggressive clinical phenotype and death. There is increasing body of evidence demonstrating that microRNAs could be considered the potential biomarkers for clinical applications in NBL. In this report, we focus on molecular characterization of high-risk as well as low-risk and intermediate-risk NBL cases in the context of the microRNA expression profile that is specific for the given risk category of the disease. We investigated a total of 30 NBL patients, out of whom there were 19 patients with low- to intermediate-risk and 11 with high-risk NBLs as defined by the Clinical Oncology Group. We determined the expression profiles of 754 microRNAs (miRNAs), whereas the miRNA expression levels were normalized to RNU44, mean expression levels were calculated, and data were analyzed by use of the microarray biostatistical approaches. We identified the signature of 38 miRNAs differentially expressed between these groups of NBL patients (P < 0.05): 17 miRNAs were upregulated and 21 miRNAs were downregulated in the tumors of high-risk NBL patients. We confirm some of the previous observations and we report several new microRNAs associated with aggressive NBL, both being relevant subjects for further translational validation and functional studies.

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

Express path analysis identifies a tyrosine kinase Src-centric network regulating divergent host responses to Mycobacterium tuberculosis infection.

PubMed

Karim, Ahmad Faisal; Chandra, Pallavi; Chopra, Aanchal; Siddiqui, Zaved; Bhaskar, Ashima; Singh, Amit; Kumar, Dhiraj

2011-11-18

Global gene expression profiling has emerged as a major tool in understanding complex response patterns of biological systems to perturbations. However, a lack of unbiased analytical approaches has restricted the utility of complex microarray data to gain novel system level insights. Here we report a strategy, express path analysis (EPA), that helps to establish various pathways differentially recruited to achieve specific cellular responses under contrasting environmental conditions in an unbiased manner. The analysis superimposes differentially regulated genes between contrasting environments onto the network of functional protein associations followed by a series of iterative enrichments and network analysis. To test the utility of the approach, we infected THP1 macrophage cells with a virulent Mycobacterium tuberculosis strain (H37Rv) or the attenuated non-virulent strain H37Ra as contrasting perturbations and generated the temporal global expression profiles. EPA of the results provided details of response-specific and time-dependent host molecular network perturbations. Further analysis identified tyrosine kinase Src as the major regulatory hub discriminating the responses between wild-type and attenuated Mtb infection. We were then able to verify this novel role of Src experimentally and show that Src executes its role through regulating two vital antimicrobial processes of the host cells (i.e. autophagy and acidification of phagolysosome). These results bear significant potential for developing novel anti-tuberculosis therapy. We propose that EPA could prove extremely useful in understanding complex cellular responses for a variety of perturbations, including pathogenic infections.

Signal transduction profile of chemical sensitisers in dendritic cells: An endpoint to be included in a cell-based in vitro alternative approach to hazard identification?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neves, Bruno Miguel; Centro de Neurociencias e Biologia Celular, Universidade de Coimbra, Coimbra 3004-517; Goncalo, Margarida

2011-01-15

The development of non-animal testing methods for the assessment of skin sensitisation potential is an urgent challenge within the framework of existing and forthcoming legislation. Efforts have been made to replace current animal tests, but so far no alternative methods have been developed. It is widely recognised that alternatives to animal testing cannot be accomplished with a single approach, but rather will require the integration of results obtained from different in vitro and in silico assays. The argument subjacent to the development of in vitro dendritic cell (DC)-based assays is that sensitiser-induced changes in the DC phenotype can be differentiatedmore » from those induced by irritants. This assumption is derived from the unique capacity of DC to convert environmental signals encountered at the skin into a receptor expression pattern (MHC class II molecules, co-stimulatory molecules, chemokine receptors) and a soluble mediator release profile that will stimulate T lymphocytes. Since signal transduction cascades precede changes in surface marker expression and cytokine/chemokine secretion, these phenotypic modifications are a consequence of a signal transduction profile that is specifically triggered by sensitisers and not by irritants. A limited number of studies have addressed this subject and the present review attempts to summarise and highlight all of the signalling pathways modulated by skin sensitisers and irritants. Furthermore, we conclude this review by focusing on the most promising strategies suitable for inclusion into a cell-based in vitro alternative approach to hazard identification.« less

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Integrative functional genomics of salt acclimatization in the model legume Lotus japonicus.

PubMed

Sanchez, Diego H; Lippold, Felix; Redestig, Henning; Hannah, Matthew A; Erban, Alexander; Krämer, Ute; Kopka, Joachim; Udvardi, Michael K

2008-03-01

The model legume Lotus japonicus was subjected to non-lethal long-term salinity and profiled at the ionomic, transcriptomic and metabolomic levels. Two experimental designs with various stress doses were tested: a gradual step acclimatization and an initial acclimatization approach. Ionomic profiling by inductively coupled plasma/atomic emission spectrometry (ICP-AES) revealed salt stress-induced reductions in potassium, phosphorus, sulphur, zinc and molybdenum. Microarray profiling using the Lotus Genechip allowed the identification of 912 probesets that were differentially expressed under the acclimatization regimes. Gas chromatography/mass spectrometry-based metabolite profiling identified 147 differentially accumulated soluble metabolites, indicating a change in metabolic phenotype upon salt acclimatization. Metabolic changes were characterized by a general increase in the steady-state levels of many amino acids, sugars and polyols, with a concurrent decrease in most organic acids. Transcript and metabolite changes exhibited a stress dose-dependent response within the range of NaCl concentrations used, although threshold and plateau behaviours were also observed. The combined observations suggest a successive and increasingly global requirement for the reprogramming of gene expression and metabolic pathways to maintain ionic and osmotic homeostasis. A simple qualitative model is proposed to explain the systems behaviour of plants during salt acclimatization.

Characterizing mutation-expression network relationships in multiple cancers.

PubMed

Ghazanfar, Shila; Yang, Jean Yee Hwa

2016-08-01

Data made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics. Using somatic mutation and gene expression information across 19 cancers, we generated mutation-expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p<0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load. This study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation-expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Group psychotherapy for parents of patients with schizophrenia.

PubMed

Gruber, Ema N; Kajević, Milka; Agius, Mark; Martić-Biocina, Sanja

2006-11-01

During a four-month period, the authors provided group psychotherapy combining psychodynamic, supportive and psycho-educational approaches. The aim was to investigate whether this approach would enable parents of patients with schizophrenia to re-establish their psychic balance and the balance of the whole family system by reducing high expressed emotion. The following tools were administered: a socio-cultural questionnaire, MMPI and PIE psychological tests and two questionnaires for group evaluation. The socio-cultural questionnaire showed that the group of parents is heterogeneous. MMPI profiles showed truthful answers and well organized thinking; there were no psychopathological symptoms. The PIE test showed increased dimensions of sociability and trust. The dimensions of fear, sorrow and anger were decreased. Combinations of primary emotions (marked sociability and high self-protection) show that the parents are cautious, responsible and tend to feel guilt. The parents evaluated the group work as interesting and helpful and the group as a place where the parents can overcome the stigma of the disease that affects them, get information, find help and friends and find a way out of their social isolation. This combined approach changes the emotional profile of parents, reduces high expressed emotions (fear, sorrow and anger) in parents and helps re-establish their psychic balance and the balance of the whole family system.

Validation of high-throughput single cell analysis methodology.

PubMed

Devonshire, Alison S; Baradez, Marc-Olivier; Morley, Gary; Marshall, Damian; Foy, Carole A

2014-05-01

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

PubMed

Nelson, Peter T; Wang, Wang-Xia; Wilfred, Bernard R; Tang, Guiliang

2008-11-01

MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies.

A microfluidic approach to parallelized transcriptional profiling of single cells.

PubMed

Sun, Hao; Olsen, Timothy; Zhu, Jing; Tao, Jianguo; Ponnaiya, Brian; Amundson, Sally A; Brenner, David J; Lin, Qiao

2015-12-01

The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine, as it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. We present a microfluidic approach to parallelized, rapid, quantitative analysis of messenger RNA from single cells via RT-qPCR. The approach leverages an array of single-cell RT-qPCR analysis units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of single cells in a drastically simplified operation procedure using a relatively small number of microvalves. All steps for single-cell RT-qPCR, including cell isolation and immobilization, cell lysis, mRNA purification, reverse transcription and qPCR, are integrated on a single chip, eliminating the need for off-chip manual cell and reagent transfer and qPCR amplification as commonly used in existing approaches. Additionally, the approach incorporates optically transparent microfluidic components to allow monitoring of single-cell trapping without the need for molecular labeling that can potentially alter the targeted gene expression and utilizes a polycarbonate film as a barrier against evaporation to minimize the loss of reagents at elevated temperatures during the analysis. We demonstrate the utility of the approach by the transcriptional profiling for the induction of the cyclin-dependent kinase inhibitor 1a and the glyceraldehyde 3-phosphate dehydrogenase in single cells from the MCF-7 breast cancer cell line. Furthermore, the methyl methanesulfonate is employed to allow measurement of the expression of the genes in individual cells responding to a genotoxic stress.

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666

Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

PubMed Central

Gehan, Malia A; Mockler, Todd C; Weinig, Cynthia; Ewers, Brent E

2017-01-01

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought. PMID:28826479

Gene Expression Profiling in Fish Toxicology: A Review.

PubMed

Kumar, Girish; Denslow, Nancy D

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring gene expression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressed gene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressed genes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

Large-scale screening of transcription factor–promoter interactions in spruce reveals a transcriptional network involved in vascular development

PubMed Central

Lachance, Denis; Giguère, Isabelle; Séguin, Armand

2014-01-01

This research aimed to investigate the role of diverse transcription factors (TFs) and to delineate gene regulatory networks directly in conifers at a relatively high-throughput level. The approach integrated sequence analyses, transcript profiling, and development of a conifer-specific activation assay. Transcript accumulation profiles of 102 TFs and potential target genes were clustered to identify groups of coordinately expressed genes. Several different patterns of transcript accumulation were observed by profiling in nine different organs and tissues: 27 genes were preferential to secondary xylem both in stems and roots, and other genes were preferential to phelloderm and periderm or were more ubiquitous. A robust system has been established as a screening approach to define which TFs have the ability to regulate a given promoter in planta. Trans-activation or repression effects were observed in 30% of TF–candidate gene promoter combinations. As a proof of concept, phylogenetic analysis and expression and trans-activation data were used to demonstrate that two spruce NAC-domain proteins most likely play key roles in secondary vascular growth as observed in other plant species. This study tested many TFs from diverse families in a conifer tree species, which broadens the knowledge of promoter–TF interactions in wood development and enables comparisons of gene regulatory networks found in angiosperms and gymnosperms. PMID:24713992

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

Genome-wide identification of translationally inhibited and degraded miR-155 targets using RNA-interacting protein-IP

PubMed Central

Meier, Jan; Hovestadt, Volker; Zapatka, Marc; Pscherer, Armin; Lichter, Peter; Seiffert, Martina

2013-01-01

MicroRNAs (miRNAs) are single-stranded, small, non-coding RNAs, which fine-tune protein expression by degrading and/or translationally inhibiting mRNAs. Manipulation of miRNA expression in animal models frequently results in severe phenotypes indicating their relevance in controlling cellular functions, most likely by interacting with multiple targets. To better understand the effect of miRNA activities, genome-wide analysis of their targets are required. MicroRNA profiling as well as transcriptome analysis upon enforced miRNA expression were frequently used to investigate their relevance. However, these approaches often fail to identify relevant miRNAs targets. Therefore, we tested the precision of RNA-interacting protein immunoprecipitation (RIP) using AGO2-specific antibodies, a core component of the “RNA-induced silencing complex” (RISC), followed by RNA sequencing (Seq) in a defined cellular system, the HEK293T cells with stable, ectopic expression of miR-155. Thereby, we identified 100 AGO2-associated mRNAs in miR-155-expressing cells, of which 67 were in silico predicted miR-155 target genes. An integrated analysis of the corresponding expression profiles indicated that these targets were either regulated by mRNA decay or by translational repression. Of the identified miR-155 targets, 17 were related to cell cycle control, suggesting their involvement in the observed increase in cell proliferation of HEK293T cells upon miR-155 expression. Additional, secondary changes within the gene expression profile were detected and might contribute to this phenotype as well. Interestingly, by analyzing RIP-Seq data of HEK-293T cells and two B-cell lines we identified a recurrent disproportional enrichment of several miRNAs, including miR-155 and miRNAs of the miR-17-92 cluster, in the AGO2-associated precipitates, suggesting discrepancies in miRNA expression and activity. PMID:23673373

Yeast Interspecies Comparative Proteomics Reveals Divergence in Expression Profiles and Provides Insights into Proteome Resource Allocation and Evolutionary Roles of Gene Duplication*

PubMed Central

Kito, Keiji; Ito, Haruka; Nohara, Takehiro; Ohnishi, Mihoko; Ishibashi, Yuko; Takeda, Daisuke

2016-01-01

Omics analysis is a versatile approach for understanding the conservation and diversity of molecular systems across multiple taxa. In this study, we compared the proteome expression profiles of four yeast species (Saccharomyces cerevisiae, Saccharomyces mikatae, Kluyveromyces waltii, and Kluyveromyces lactis) grown on glucose- or glycerol-containing media. Conserved expression changes across all species were observed only for a small proportion of all proteins differentially expressed between the two growth conditions. Two Kluyveromyces species, both of which exhibited a high growth rate on glycerol, a nonfermentative carbon source, showed distinct species-specific expression profiles. In K. waltii grown on glycerol, proteins involved in the glyoxylate cycle and gluconeogenesis were expressed in high abundance. In K. lactis grown on glycerol, the expression of glycolytic and ethanol metabolic enzymes was unexpectedly low, whereas proteins involved in cytoplasmic translation, including ribosomal proteins and elongation factors, were highly expressed. These marked differences in the types of predominantly expressed proteins suggest that K. lactis optimizes the balance of proteome resource allocation between metabolism and protein synthesis giving priority to cellular growth. In S. cerevisiae, about 450 duplicate gene pairs were retained after whole-genome duplication. Intriguingly, we found that in the case of duplicates with conserved sequences, the total abundance of proteins encoded by a duplicate pair in S. cerevisiae was similar to that of protein encoded by nonduplicated ortholog in Kluyveromyces yeast. Given the frequency of haploinsufficiency, this observation suggests that conserved duplicate genes, even though minor cases of retained duplicates, do not exhibit a dosage effect in yeast, except for ribosomal proteins. Thus, comparative proteomic analyses across multiple species may reveal not only species-specific characteristics of metabolic processes under nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history. PMID:26560065

Yeast Interspecies Comparative Proteomics Reveals Divergence in Expression Profiles and Provides Insights into Proteome Resource Allocation and Evolutionary Roles of Gene Duplication.

PubMed

Kito, Keiji; Ito, Haruka; Nohara, Takehiro; Ohnishi, Mihoko; Ishibashi, Yuko; Takeda, Daisuke

2016-01-01

Omics analysis is a versatile approach for understanding the conservation and diversity of molecular systems across multiple taxa. In this study, we compared the proteome expression profiles of four yeast species (Saccharomyces cerevisiae, Saccharomyces mikatae, Kluyveromyces waltii, and Kluyveromyces lactis) grown on glucose- or glycerol-containing media. Conserved expression changes across all species were observed only for a small proportion of all proteins differentially expressed between the two growth conditions. Two Kluyveromyces species, both of which exhibited a high growth rate on glycerol, a nonfermentative carbon source, showed distinct species-specific expression profiles. In K. waltii grown on glycerol, proteins involved in the glyoxylate cycle and gluconeogenesis were expressed in high abundance. In K. lactis grown on glycerol, the expression of glycolytic and ethanol metabolic enzymes was unexpectedly low, whereas proteins involved in cytoplasmic translation, including ribosomal proteins and elongation factors, were highly expressed. These marked differences in the types of predominantly expressed proteins suggest that K. lactis optimizes the balance of proteome resource allocation between metabolism and protein synthesis giving priority to cellular growth. In S. cerevisiae, about 450 duplicate gene pairs were retained after whole-genome duplication. Intriguingly, we found that in the case of duplicates with conserved sequences, the total abundance of proteins encoded by a duplicate pair in S. cerevisiae was similar to that of protein encoded by nonduplicated ortholog in Kluyveromyces yeast. Given the frequency of haploinsufficiency, this observation suggests that conserved duplicate genes, even though minor cases of retained duplicates, do not exhibit a dosage effect in yeast, except for ribosomal proteins. Thus, comparative proteomic analyses across multiple species may reveal not only species-specific characteristics of metabolic processes under nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression.

PubMed

Dobon, Albor; Bunting, Daniel C E; Cabrera-Quio, Luis Enrique; Uauy, Cristobal; Saunders, Diane G O

2016-05-20

Understanding how plants and pathogens modulate gene expression during the host-pathogen interaction is key to uncovering the molecular mechanisms that regulate disease progression. Recent advances in sequencing technologies have provided new opportunities to decode the complexity of such interactions. In this study, we used an RNA-based sequencing approach (RNA-seq) to assess the global expression profiles of the wheat yellow rust pathogen Puccinia striiformis f. sp. tritici (PST) and its host during infection. We performed a detailed RNA-seq time-course for a susceptible and a resistant wheat host infected with PST. This study (i) defined the global gene expression profiles for PST and its wheat host, (ii) substantially improved the gene models for PST, (iii) evaluated the utility of several programmes for quantification of global gene expression for PST and wheat, and (iv) identified clusters of differentially expressed genes in the host and pathogen. By focusing on components of the defence response in susceptible and resistant hosts, we were able to visualise the effect of PST infection on the expression of various defence components and host immune receptors. Our data showed sequential, temporally coordinated activation and suppression of expression of a suite of immune-response regulators that varied between compatible and incompatible interactions. These findings provide the framework for a better understanding of how PST causes disease and support the idea that PST can suppress the expression of defence components in wheat to successfully colonize a susceptible host.

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

Circular RNA profile in gliomas revealed by identification tool UROBORUS.

PubMed

Song, Xiaofeng; Zhang, Naibo; Han, Ping; Moon, Byoung-San; Lai, Rose K; Wang, Kai; Lu, Wange

2016-05-19

Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play roles in biological processes. However, the expression patterns and functions of circRNAs in human diseases are not well understood. Computationally identifying circRNAs from total RNA-seq data is a primary step in studying their expression pattern and biological roles. In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected thousands of circRNAs supported by at least two read counts, followed by successful experimental validation on 24 circRNAs from the randomly selected 27 circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low expression levels in total RNA-seq without RNase R treatment. The circRNAs expression profiling revealed more than 476 circular RNAs differentially expressed in control brain tissues and gliomas. Together with parental gene expression, we found that circRNA and its parental gene have diversified expression patterns in gliomas and control brain tissues. This study establishes an efficient and sensitive approach for predicting circRNAs using total RNA-seq data. The UROBORUS pipeline can be accessed freely for non-commercial purposes at http://uroborus.openbioinformatics.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472.

PubMed

Baraúna, Rafael A; Santos, Agenor V; Graças, Diego A; Santos, Daniel M; Ghilardi, Rubens; Pimenta, Adriano M C; Carepo, Marta S P; Schneider, Maria P C; Silva, Artur

2015-05-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

Utilization of Lymphoblastoid Cell Lines as a System for the Molecular Modeling of Autism

ERIC Educational Resources Information Center

Baron, Colin A.; Liu, Stephenie Y.; Hicks, Chindo; Gregg, Jeffrey P.

2006-01-01

In order to provide an alternative approach for understanding the biology and genetics of autism, we performed statistical analysis of gene expression profiles of lymphoblastoid cell lines derived from children with autism and their families. The goal was to assess the feasibility of using this model in identifying autism-associated genes.…

A systems biology approach using transcriptomic data reveals genes and pathways in porcine skeletal muscle affected by dietary lysine

USDA-ARS?s Scientific Manuscript database

Meeting the increasing market demands for pork products requires improvement of the feed efficiency of growing pigs. The use of Affymetrix Porcine Gene 1.0 ST array containing 19,211 genes in this study provides a comprehensive gene expression profile of skeletal muscle of finishing pigs in response...

Gene expression profiling to characterize sediment toxicity – a pilot study using Caenorhabditis elegans whole genome microarrays

PubMed Central

Menzel, Ralph; Swain, Suresh C; Hoess, Sebastian; Claus, Evelyn; Menzel, Stefanie; Steinberg, Christian EW; Reifferscheid, Georg; Stürzenbaum, Stephen R

2009-01-01

Background Traditionally, toxicity of river sediments is assessed using whole sediment tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth or reproduction. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bio-available fraction of pollutants. Results In this pilot study, we exposed the nematode Caenorhabditis elegans to three sediments of German rivers with varying (low, medium and high) levels of heavy metal and organic contamination. Beside chemical analysis, three standard bioassays were performed: reproduction of C. elegans, genotoxicity (Comet assay) and endocrine disruption (YES test). Gene expression was profiled using a whole genome DNA-microarray approach to identify overrepresented functional gene categories and derived cellular processes. Disaccharide and glycogen metabolism were found to be affected, whereas further functional pathways, such as oxidative phosphorylation, ribosome biogenesis, metabolism of xenobiotics, aging and several developmental processes were found to be differentially regulated only in response to the most contaminated sediment. Conclusion This study demonstrates how ecotoxicogenomics can identify transcriptional responses in complex mixture scenarios to distinguish different samples of river sediments. PMID:19366437

Optimal aggregation of binary classifiers for multiclass cancer diagnosis using gene expression profiles.

PubMed

Yukinawa, Naoto; Oba, Shigeyuki; Kato, Kikuya; Ishii, Shin

2009-01-01

Multiclass classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. There have been many studies of aggregating binary classifiers to construct a multiclass classifier based on one-versus-the-rest (1R), one-versus-one (11), or other coding strategies, as well as some comparison studies between them. However, the studies found that the best coding depends on each situation. Therefore, a new problem, which we call the "optimal coding problem," has arisen: how can we determine which coding is the optimal one in each situation? To approach this optimal coding problem, we propose a novel framework for constructing a multiclass classifier, in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. Although there is no a priori answer to the optimal coding problem, our weight tuning method can be a consistent answer to the problem. We apply this method to various classification problems including a synthesized data set and some cancer diagnosis data sets from gene expression profiling. The results demonstrate that, in most situations, our method can improve classification accuracy over simple voting heuristics and is better than or comparable to state-of-the-art multiclass predictors.

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina

2007-01-01

Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300

Whole blood genome-wide expression profiling and network analysis suggest MELAS master regulators.

PubMed

Mende, Susanne; Royer, Loic; Herr, Alexander; Schmiedel, Janet; Deschauer, Marcus; Klopstock, Thomas; Kostic, Vladimir S; Schroeder, Michael; Reichmann, Heinz; Storch, Alexander

2011-07-01

The heteroplasmic mitochondrial DNA (mtDNA) mutation A3243G causes the mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome as one of the most frequent mitochondrial diseases. The process of reconfiguration of nuclear gene expression profile to accommodate cellular processes to the functional status of mitochondria might be a key to MELAS disease manifestation and could contribute to its diverse phenotypic presentation. To determine master regulatory protein networks and disease-modifying genes in MELAS syndrome. Analyses of whole blood transcriptomes from 10 MELAS patients using a novel strategy by combining classic Affymetrix oligonucleotide microarray profiling with regulatory and protein interaction network analyses. Hierarchical cluster analysis elucidated that the relative abundance of mutant mtDNA molecules is decisive for the nuclear gene expression response. Further analyses confirmed not only transcription factors already known to be involved in mitochondrial diseases (such as TFAM), but also detected the hypoxia-inducible factor 1 complex, nuclear factor Y and cAMP responsive element-binding protein-related transcription factors as novel master regulators for reconfiguration of nuclear gene expression in response to the MELAS mutation. Correlation analyses of gene alterations and clinico-genetic data detected significant correlations between A3243G-induced nuclear gene expression changes and mutant mtDNA load as well as disease characteristics. These potential disease-modifying genes influencing the expression of the MELAS phenotype are mainly related to clusters primarily unrelated to cellular energy metabolism, but important for nucleic acid and protein metabolism, and signal transduction. Our data thus provide a framework to search for new pathogenetic concepts and potential therapeutic approaches to treat the MELAS syndrome.

A New Approach to Construct Pathway Connected Networks and Its Application in Dose Responsive Gene Expression Profiles of Rat Liver Regulated by 2,4DNT

DTIC Science & Technology

2010-12-01

differentially expressed genes after 2,4DNT treatment. The most affected pathways included: long term depression, breast cancer regulation by stathmin1, WNT...toxic to reproductive organs in rats [2] and cause genetic toxicity in munitions facility workers and copper miners using explosives [3,4]. DNTs...including 2,4DNT are listed as a priority pollutant by the U.S. Environmental Protection Agency [3]. It is therefore important to develop methods to

Usefulness of DIGE for the detection of protein profile in retained and released bovine placental tissues.

PubMed

Kankofer, M; Wawrzykowski, J; Miller, I; Hoedemaker, M

2015-02-01

Regardless intensive research, the etiology and mechanisms of retention of fetal membranes in cows, still require elucidation. In our research approach, difference in gel electrophoresis (DIGE) and matrix-assisted laser desorption/ionization (MALDI) identification were used to obtain first results on protein profile of bovine placental membranes which were properly released or retained for more than 12 h after parturition. Placentomes from 6 cows that released placenta and from 6 cows that retained fetal membranes were homogenized, fluorescence labeled and subjected to DIGE. Selected spots that significantly differed between retained and released placenta as well as spots with constant appearance were identified by MALDI. This allowed identification of the following proteins with high statistical reliability: Transforming growth factor beta 2 - high expression in maternal and fetal part of retained fetal membranes, Short transient receptor potential channel 5 -high expression in maternal part of retained and not retained fetal membranes, Rab GDP dissociation inhibitor beta - high expression in fetal part of retained and not retained fetal membranes, Proline dehydrogenase 2 - similar expression in all examined samples, Ras-related protein Rab-7b -high expression only in maternal part of not retained fetal membranes. Up to now, these proteins have not been considered as possibly important molecules for the separation/retention of fetal membranes, but their biological roles may suggest it. Further studies are necessary to establish a full profile of bovine placental proteins and define target molecules that may be involved in separation/retention of fetal membranes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kinetics of IFN-gamma and TNF-alpha gene expression and their relationship with disease progression after infection with Mycobacterium tuberculosis in guinea pigs.

PubMed

Roh, In Soon; Cho, Sungae; Eum, Seok-Yong; Cho, Sang-Nae

2013-05-01

Guinea pig is one of the most suitable animal models for Mycobacterium tuberculosis (M. tb) infection since it shows similarities to pulmonary infection in humans. Although guinea pig shows hematogenous spread of M. tb infection into the whole body, immunological studies have mainly focused on granulomatous tissues in lungs and spleens. In order to investigate the time-course of disease pathogenesis and immunological profiles in each infected organ, we performed the following approaches with guinea pigs experimentally infected with M. tb over a 22-week post-infection period. We examined body weight changes, M. tb growth curve, cytokine gene expression (IFN-γ and TNF-α), and histopathology in liver, spleen, lungs and lymph nodes of infected guinea pigs. The body weights of infected guinea pigs did not increase as much as uninfected ones and the number of M. tb bacilli in their organs increased except bronchotracheal lymph node during the experimental period. The gene expression of IFN-γ and TNF-α was induced between 3 and 6 weeks of infection; however, kinetic profiles of cytokine gene expression showed heterogeneity among organs over the study period. Histophathologically granulomatous lesions were developed in all four organs of infected guinea pigs. Although IFN-γ and TNF-α gene expression profiles showed heterogeneity, the granuloma formation was clearly observed in every organ regardless of whether the number of bacilli increased or decreased. However, this protective immunity was accompanied with severe tissue damage in all four organs, which may lead to the death of guinea pigs.

Indications for distinct pathogenic mechanisms of asbestos and silica through gene expression profiling of the response of lung epithelial cells

PubMed Central

Perkins, Timothy N.; Peeters, Paul M.; Shukla, Arti; Arijs, Ingrid; Dragon, Julie; Wouters, Emiel F.M.; Reynaert, Niki L.; Mossman, Brooke T.

2015-01-01

Occupational and environmental exposures to airborne asbestos and silica are associated with the development of lung fibrosis in the forms of asbestosis and silicosis, respectively. However, both diseases display distinct pathologic presentations, likely associated with differences in gene expression induced by different mineral structures, composition and bio-persistent properties. We hypothesized that effects of mineral exposure in the airway epithelium may dictate deviating molecular events that may explain the different pathologies of asbestosis versus silicosis. Using robust gene expression-profiling in conjunction with in-depth pathway analysis, we assessed early (24 h) alterations in gene expression associated with crocidolite asbestos or cristobalite silica exposures in primary human bronchial epithelial cells (NHBEs). Observations were confirmed in an immortalized line (BEAS-2B) by QRT-PCR and protein assays. Utilization of overall gene expression, unsupervised hierarchical cluster analysis and integrated pathway analysis revealed gene alterations that were common to both minerals or unique to either mineral. Our findings reveal that both minerals had potent effects on genes governing cell adhesion/migration, inflammation, and cellular stress, key features of fibrosis. Asbestos exposure was most specifically associated with aberrant cell proliferation and carcinogenesis, whereas silica exposure was highly associated with additional inflammatory responses, as well as pattern recognition, and fibrogenesis. These findings illustrate the use of gene-profiling as a means to determine early molecular events that may dictate pathological processes induced by exogenous cellular insults. In addition, it is a useful approach for predicting the pathogenicity of potentially harmful materials. PMID:25351596

The transcriptome of the human mast cell leukemia cells HMC-1.2: an approach to identify specific changes in the gene expression profile in KitD816V systemic mastocytosis.

PubMed

Haenisch, B; Herms, S; Molderings, G J

2013-05-01

To circumvent the costly isolation procedure associated with tissue mast cells, human mast cell lines such as HMC-1 are employed in mastocytosis research, but their relation to mutated mast cells in systemic mastocytosis has not been investigated systematically. In the present study, we determined the transcriptome of HMC-1.2 cells and compared the expression data with those reported in the literature for normal human resting lung and tonsillar mast cells as well as leukocytes from peripheral blood and mononuclear cells from bone marrow aspirates of patients with D816 V-positive systemic mastocytosis. Our results suggest that HMC-1.2 cells are an appropriate model for the investigation of this variant of systemic mast cell activation disease. The data confirm previous suggestions that the pathologically increased activity of mast cells in patients with D816 V-positive systemic mastocytosis can be deduced from the detection of mutation-related changes in the gene expression profile in leukocytes from peripheral blood and in mononuclear cells from bone marrow aspirates. Thus, mutation-related changes of the expression profile can serve as surrogates (besides clustering of mast cells, expression of CD25, and increased release of tryptase) for the presence of the mutation D816 V in tyrosine kinase Kit in patients with systemic mastocytosis according to the WHO criteria. Whether this also holds true for systemic mast cell activation disease caused by other mutations in Kit or other mast cell activity-related genes is a subject for future studies.

Metabolic Disturbances in Adult-Onset Still's Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis.

PubMed

Chen, Der-Yuan; Chen, Yi-Ming; Chien, Han-Ju; Lin, Chi-Chen; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting; Lai, Chien-Chen

2016-01-01

Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still's disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis.

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system

PubMed Central

Sowa, Steven W.; Gelderman, Grant; Leistra, Abigail N.; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A.; Romeo, Tony; Baldea, Michael

2017-01-01

Abstract Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. PMID:28126921

Toward a Model-Based Approach for Flight System Fault Protection

NASA Technical Reports Server (NTRS)

Day, John; Meakin, Peter; Murray, Alex

2012-01-01

Use SysML/UML to describe the physical structure of the system This part of the model would be shared with other teams - FS Systems Engineering, Planning & Execution, V&V, Operations, etc., in an integrated model-based engineering environment Use the UML Profile mechanism, defining Stereotypes to precisely express the concepts of the FP domain This extends the UML/SysML languages to contain our FP concepts Use UML/SysML, along with our profile, to capture FP concepts and relationships in the model Generate typical FP engineering products (the FMECA, Fault Tree, MRD, V&V Matrices)

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

Digital sorting of complex tissues for cell type-specific gene expression profiles.

PubMed

Zhong, Yi; Wan, Ying-Wooi; Pang, Kaifang; Chow, Lionel M L; Liu, Zhandong

2013-03-07

Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations. Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies. The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.

Fatigue-related crashes involving express buses in Malaysia: will the proposed policy of banning the early-hour operation reduce fatigue-related crashes and benefit overall road safety?

PubMed

Mohamed, Norlen; Mohd-Yusoff, Mohammad-Fadhli; Othman, Ilhamah; Zulkipli, Zarir-Hafiz; Osman, Mohd Rasid; Voon, Wong Shaw

2012-03-01

Fatigue-related crashes have long been the topic of discussion and study worldwide. The relationship between fatigue-related crashes and time of day is well documented. In Malaysia, the possibility of banning express buses from operating during the early-hours of the morning has emerged as an important consideration for passenger safety. This paper highlights the findings of an impact assessment study. The study was conducted to determine all possible impacts prior to the government making any decision on the proposed banning. This study is an example of a simple and inexpensive approach that may influence future policy-making process. The impact assessment comprised two major steps. The first step involved profiling existing operation scenarios, gathering information on crashes involving public express buses and stakeholders' views. The second step involved a qualitative impact assessment analysis using all information gathered during the profiling stage to describe the possible impacts. Based on the assessment, the move to ban early-hour operations could possibly result in further negative impacts on the overall road safety agenda. These negative impacts may occur if the fundamental issues, such as driving and working hours, and the need for rest and sleep facilities for drivers, are not addressed. In addition, a safer and more accessible public transportation system as an alternative for those who choose to travel at night would be required. The proposed banning of early-hour operations is also not a feasible solution for sustainability of express bus operations in Malaysia, especially for those operating long journeys. The paper concludes by highlighting the need to design a more holistic approach for preventing fatigue-related crashes involving express buses in Malaysia. Copyright © 2011 Elsevier Ltd. All rights reserved.

Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction.

PubMed

Suresh, Rahul; Li, Xing; Chiriac, Anca; Goel, Kashish; Terzic, Andre; Perez-Terzic, Carmen; Nelson, Timothy J

2014-09-01

Whole-genome gene expression analysis has been successfully utilized to diagnose, prognosticate, and identify potential therapeutic targets for high-risk cardiovascular diseases. However, the feasibility of this approach to identify outcome-related genes and dysregulated pathways following first-time myocardial infarction (AMI) remains unknown and may offer a novel strategy to detect affected expressome networks that predict long-term outcome. Whole-genome expression microarray on blood samples from normal cardiac function controls (n=21) and first-time AMI patients (n=31) within 48-hours post-MI revealed expected differential gene expression profiles enriched for inflammation and immune-response pathways. To determine molecular signatures at the time of AMI associated with long-term outcomes, transcriptional profiles from sub-groups of AMI patients with (n=5) or without (n=22) any recurrent events over an 18-month follow-up were compared. This analysis identified 559 differentially-expressed genes. Bioinformatic analysis of this differential gene-set for associated pathways revealed 1) increasing disease severity in AMI patients is associated with a decreased expression of genes involved in the developmental epithelial-to-mesenchymal transition pathway, and 2) modulation of cholesterol transport genes that include ABCA1, CETP, APOA1, and LDLR is associated with clinical outcome. Differentially regulated genes and modulated pathways were identified that were associated with recurrent cardiovascular outcomes in first-time AMI patients. This cell-based approach for risk stratification in AMI could represent a novel, non-invasive platform to anticipate modifiable pathways and therapeutic targets to optimize long-term outcome for AMI patients and warrants further study to determine the role of metabolic remodeling and regenerative processes required for optimal outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Proteomic Analysis of Whole Human Saliva Detects Enhanced Expression of Interleukin-1 Receptor Antagonist, Thioredoxin and Lipocalin-1 in Cigarette Smokers Compared to Non-Smokers

PubMed Central

Jessie, Kala; Pang, Wei Wei; Haji, Zubaidah; Rahim, Abdul; Hashim, Onn Haji

2010-01-01

A gel-based proteomics approach was used to screen for proteins of differential abundance between the saliva of smokers and those who had never smoked. Subjecting precipitated proteins from whole human saliva of healthy non-smokers to two-dimensional electrophoresis (2-DE) generated typical profiles comprising more than 50 proteins. While 35 of the proteins were previously established by other researchers, an additional 22 proteins were detected in the 2-DE saliva protein profiles generated in the present study. When the 2-DE profiles were compared to those obtained from subjects considered to be heavy cigarette smokers, three saliva proteins, including interleukin-1 receptor antagonist, thioredoxin and lipocalin-1, showed significant enhanced expression. The distribution patterns of lipocalin-1 isoforms were also different between cigarette smokers and non-smokers. The three saliva proteins have good potential to be used as biomarkers for the adverse effects of smoking and the risk for inflammatory and chronic diseases that are associated with it. PMID:21151451

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

PubMed

Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian

2012-10-24

Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

The complexity of gene expression dynamics revealed by permutation entropy

PubMed Central

2010-01-01

Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199

Optimal shutdown management

NASA Astrophysics Data System (ADS)

Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.

2014-06-01

The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.

Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

PubMed Central

Kennedy, Laura; Vass, J. Keith; Haggart, D. Ross; Moore, Steve; Burczynski, Michael E.; Crowther, Dan; Miele, Gino

2008-01-01

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies. PMID:19578521

Gene Expression Profiles in Rice Developing Ovules Provided Evidence for the Role of Sporophytic Tissue in Female Gametophyte Development.

PubMed

Wu, Ya; Yang, Liyu; Cao, Aqin; Wang, Jianbo

2015-01-01

The development of ovule in rice (Oryza sativa) is vital during its life cycle. To gain more understanding of the molecular events associated with the ovule development, we used RNA sequencing approach to perform transcriptome-profiling analysis of the leaf and ovules at four developmental stages. In total, 25,401, 23,343, 23,647 and 23,806 genes were identified from the four developmental stages of the ovule, respectively. We identified a number of differently expressed genes (DEGs) from three adjacent stage comparisons, which may play crucial roles in ovule development. The DEGs were then conducted functional annotations and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses. Genes related to cellular component biogenesis, membrane-bounded organelles and reproductive regulation were identified to be highly expressed during the ovule development. Different expression levels of auxin-related and cytokinin-related genes were also identified at various stages, providing evidence for the role of sporophytic ovule tissue in female gametophyte development from the aspect of gene expression. Generally, an overall transcriptome analysis for rice ovule development has been conducted. These results increased our knowledge of the complex molecular and cellular events that occur during the development of rice ovule and provided foundation for further studies on rice ovule development.

The Drosophila Duox maturation factor is a key component of a positive feedback loop that sustains regeneration signaling.

PubMed

Khan, Sumbul Jawed; Abidi, Syeda Nayab Fatima; Skinner, Andrea; Tian, Yuan; Smith-Bolton, Rachel K

2017-07-01

Regenerating tissue must initiate the signaling that drives regenerative growth, and sustain that signaling long enough for regeneration to complete. How these key signals are sustained is unclear. To gain a comprehensive view of the changes in gene expression that occur during regeneration, we performed whole-genome mRNAseq of actively regenerating tissue from damaged Drosophila wing imaginal discs. We used genetic tools to ablate the wing primordium to induce regeneration, and carried out transcriptional profiling of the regeneration blastema by fluorescently labeling and sorting the blastema cells, thus identifying differentially expressed genes. Importantly, by using genetic mutants of several of these differentially expressed genes we have confirmed that they have roles in regeneration. Using this approach, we show that high expression of the gene moladietz (mol), which encodes the Duox-maturation factor NIP, is required during regeneration to produce reactive oxygen species (ROS), which in turn sustain JNK signaling during regeneration. We also show that JNK signaling upregulates mol expression, thereby activating a positive feedback signal that ensures the prolonged JNK activation required for regenerative growth. Thus, by whole-genome transcriptional profiling of regenerating tissue we have identified a positive feedback loop that regulates the extent of regenerative growth.

The Drosophila Duox maturation factor is a key component of a positive feedback loop that sustains regeneration signaling

PubMed Central

Skinner, Andrea; Tian, Yuan

2017-01-01

Regenerating tissue must initiate the signaling that drives regenerative growth, and sustain that signaling long enough for regeneration to complete. How these key signals are sustained is unclear. To gain a comprehensive view of the changes in gene expression that occur during regeneration, we performed whole-genome mRNAseq of actively regenerating tissue from damaged Drosophila wing imaginal discs. We used genetic tools to ablate the wing primordium to induce regeneration, and carried out transcriptional profiling of the regeneration blastema by fluorescently labeling and sorting the blastema cells, thus identifying differentially expressed genes. Importantly, by using genetic mutants of several of these differentially expressed genes we have confirmed that they have roles in regeneration. Using this approach, we show that high expression of the gene moladietz (mol), which encodes the Duox-maturation factor NIP, is required during regeneration to produce reactive oxygen species (ROS), which in turn sustain JNK signaling during regeneration. We also show that JNK signaling upregulates mol expression, thereby activating a positive feedback signal that ensures the prolonged JNK activation required for regenerative growth. Thus, by whole-genome transcriptional profiling of regenerating tissue we have identified a positive feedback loop that regulates the extent of regenerative growth. PMID:28753614

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation.

PubMed

De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

2013-01-01

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology 'reverse engineering' approaches. We 'reverse engineered' an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression ('hubs'). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central 'hub' of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

Microarray Data Mining for Potential Selenium Targets in Chemoprevention of Prostate Cancer

PubMed Central

ZHANG, HAITAO; DONG, YAN; ZHAO, HONGJUAN; BROOKS, JAMES D.; HAWTHORN, LESLEYANN; NOWAK, NORMA; MARSHALL, JAMES R.; GAO, ALLEN C.; IP, CLEMENT

2008-01-01

Background A previous clinical trial showed that selenium supplementation significantly reduced the incidence of prostate cancer. We report here a bioinformatics approach to gain new insights into selenium molecular targets that might be relevant to prostate cancer chemoprevention. Materials and Methods We first performed data mining analysis to identify genes which are consistently dysregulated in prostate cancer using published datasets from gene expression profiling of clinical prostate specimens. We then devised a method to systematically analyze three selenium microarray datasets from the LNCaP human prostate cancer cells, and to match the analysis to the cohort of genes implicated in prostate carcinogenesis. Moreover, we compared the selenium datasets with two datasets obtained from expression profiling of androgen-stimulated LNCaP cells. Results We found that selenium reverses the expression of genes implicated in prostate carcinogenesis. In addition, we found that selenium could counteract the effect of androgen on the expression of a subset obtained from androgen-regulated genes. Conclusions The above information provides us with a treasure of new clues to investigate the mechanism of selenium chemoprevention of prostate cancer. Furthermore, these selenium target genes could also serve as biomarkers in future clinical trials to gauge the efficacy of selenium intervention. PMID:18548127

Transcriptome Analysis of Thermal Parthenogenesis of the Domesticated Silkworm.

PubMed

Liu, Peigang; Wang, Yongqiang; Du, Xin; Yao, Lusong; Li, Fengbo; Meng, Zhiqi

2015-01-01

Thermal induction of parthenogenesis (also known as thermal parthenogenesis) in silkworms is an important technique that has been used in artificial insemination, expansion of hybridization, transgenesis and sericultural production; however, the exact mechanisms of this induction remain unclear. This study aimed to investigate the gene expression profile in silkworms undergoing thermal parthenogenesis using RNA-seq analysis. The transcriptome profiles indicated that in non-induced and induced eggs, the numbers of differentially expressed genes (DEGs) for the parthenogenetic line (PL) and amphigenetic line (AL) were 538 and 545, respectively, as determined by fold-change ≥ 2. Gene ontology (GO) analysis showed that DEGs between two lines were mainly involved in reproduction, formation of chorion, female gamete generation and cell development pathways. Upregulation of many chorion genes in AL suggests that the maturation rate of AL eggs was slower than PL eggs. Some DEGs related to reactive oxygen species removal, DNA repair and heat shock response were differentially expressed between the two lines, such as MPV-17, REV1 and HSP68. These results supported the view that a large fraction of genes are differentially expressed between PL and AL, which offers a new approach to identifying the molecular mechanism of silkworm thermal parthenogenesis.

Transcriptome Analysis of Thermal Parthenogenesis of the Domesticated Silkworm

PubMed Central

Du, Xin; Yao, Lusong; Li, Fengbo; Meng, Zhiqi

2015-01-01

Thermal induction of parthenogenesis (also known as thermal parthenogenesis) in silkworms is an important technique that has been used in artificial insemination, expansion of hybridization, transgenesis and sericultural production; however, the exact mechanisms of this induction remain unclear. This study aimed to investigate the gene expression profile in silkworms undergoing thermal parthenogenesis using RNA-seq analysis. The transcriptome profiles indicated that in non-induced and induced eggs, the numbers of differentially expressed genes (DEGs) for the parthenogenetic line (PL) and amphigenetic line (AL) were 538 and 545, respectively, as determined by fold-change ≥ 2. Gene ontology (GO) analysis showed that DEGs between two lines were mainly involved in reproduction, formation of chorion, female gamete generation and cell development pathways. Upregulation of many chorion genes in AL suggests that the maturation rate of AL eggs was slower than PL eggs. Some DEGs related to reactive oxygen species removal, DNA repair and heat shock response were differentially expressed between the two lines, such as MPV-17, REV1 and HSP68. These results supported the view that a large fraction of genes are differentially expressed between PL and AL, which offers a new approach to identifying the molecular mechanism of silkworm thermal parthenogenesis. PMID:26274803

Genetic biomarkers for brain hemisphere differentiation in Parkinson's Disease

NASA Astrophysics Data System (ADS)

Hourani, Mou'ath; Mendes, Alexandre; Berretta, Regina; Moscato, Pablo

2007-11-01

This work presents a study on the genetic profile of the left and right hemispheres of the brain of a mouse model of Parkinson's disease (PD). The goal is to characterize, in a genetic basis, PD as a disease that affects these two brain regions in different ways. Using the same whole-genome microarray expression data introduced by Brown et al. (2002) [1], we could find significant differences in the expression of some key genes, well-known to be involved in the mechanisms of dopamine production control and PD. The problem of selecting such genes was modeled as the MIN (α,β)—FEATURE SET problem [2]; a similar approach to that employed previously to find biomarkers for different types of cancer using gene expression microarray data [3]. The Feature Selection method produced a series of genetic signatures for PD, with distinct expression profiles in the Parkinson's model and control mice experiments. In addition, a close examination of the genes composing those signatures shows that many of them belong to genetic pathways or have ontology annotations considered to be involved in the onset and development of PD. Such elements could provide new clues on which mechanisms are implicated in hemisphere differentiation in PD.

Correlating cellular and molecular signatures of mucosal immunity that distinguish HIV controllers from noncontrollers.

PubMed

Loke, P'ng; Favre, David; Hunt, Peter W; Leung, Jacqueline M; Kanwar, Bittoo; Martin, Jeffrey N; Deeks, Steven G; McCune, Joseph M

2010-04-15

HIV "controllers" are persons infected with human immunodeficiency virus, type I (HIV) who maintain long-term control of viremia without antiviral therapy and who usually do not develop the acquired immune deficiency syndrome (AIDS). In this study, we have correlated results from polychromatic flow cytometry and oligonucleotide expression arrays to characterize the mucosal immune responses of these subjects in relation to untreated HIV(+) persons with high viral loads and progressive disease ("noncontrollers"). Paired peripheral blood and rectosigmoid biopsies were analyzed from 9 controllers and 11 noncontrollers. Several cellular immune parameters were found to be concordant between the 2 compartments. Compared with noncontrollers, the mucosal tissues of controllers had similar levels of effector T cells and fewer regulatory T cells (Tregs). Using principal component analysis to correlate immunologic parameters with gene expression profiles, transcripts were identified that accurately distinguished between controllers and noncontrollers. Direct 2-way comparison also revealed genes that are significantly different in their expression between controllers and noncontrollers, all of which had reduced expression in controllers. In addition to providing an approach that integrates flow cytometry datasets with transcriptional profiling analysis, these results underscore the importance of the sustained inflammatory response that attends progressive HIV disease.

Specific aspects of a combined approach to male face correction: botulinum toxin A and volumetric fillers.

PubMed

Scherer, Max-Adam

2016-12-01

Cosmetologists in the last decade face a permanently increasing number of male patients. The necessity of a gender-adjusted approach in treatment of this patient category is obvious. An adequate correction requires consideration of the anatomic and physiologic features of male faces together with a whole set of interrelated aspects of psychologic perception of the male face esthetics, socially formed understanding of masculine features and appropriate emotional expressions, also of the motivations and expectations of men coming to a cosmetologist. The author explains in detail the elaborated out of own vast experience methods of complex male face correction using the above-mentioned gender-specific approach to create a naturally looking and harmonic facial expression and appearance. The presented botulinum therapy specifics concern the injection point location and toxin doses for every point. As a result, a rather distinct smoothening of the skin profile without detriment to the facial expressiveness and gender-related features is achieved. The importance and methods of an extremely delicate approach to volumetric plasty with stabilized hyaluronic acid-based fillers in men for avoiding hypercorrection and retaining the gender-specific features are discussed. © 2016 Wiley Periodicals, Inc.

A Practical Platform for Blood Biomarker Study by Using Global Gene Expression Profiling of Peripheral Whole Blood

PubMed Central

Schmid, Patrick; Yao, Hui; Galdzicki, Michal; Berger, Bonnie; Wu, Erxi; Kohane, Isaac S.

2009-01-01

Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study. PMID:19381341

A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.

PubMed

He, Xu-Jiang; Jiang, Wu-Jun; Zhou, Mi; Barron, Andrew B; Zeng, Zhi-Jiang

2017-11-06

Honeybees (Apis mellifera) have haplodiploid sex determination: males develop from unfertilized eggs and females develop from fertilized ones. The differences in larval food also determine the development of females. Here we compared the total somatic gene expression profiles of 2-day and 4-day-old drone, queen and worker larvae by RNA-Seq. The results from a co-expression network analysis on all expressed genes showed that 2-day-old drone and worker larvae were closer in gene expression profiles than 2-day-old queen larvae. This indicated that for young larvae (2-day-old) environmental factors such as larval diet have a greater effect on gene expression profiles than ploidy or sex determination. Drones had the most distinct gene expression profiles at the 4-day larval stage, suggesting that haploidy, or sex dramatically affects the gene expression of honeybee larvae. Drone larvae showed fewer differences in gene expression profiles at the 2-day and 4-day time points than the worker and queen larval comparisons (598 against 1190 and 1181), suggesting a different pattern of gene expression regulation during the larval development of haploid males compared to diploid females. This study indicates that early in development the queen caste has the most distinct gene expression profile, perhaps reflecting the very rapid growth and morphological specialization of this caste compared to workers and drones. Later in development the haploid male drones have the most distinct gene expression profile, perhaps reflecting the influence of ploidy or sex determination on gene expression. © 2017 Institute of Zoology, Chinese Academy of Sciences.

An ensemble predictive modeling framework for breast cancer classification.

PubMed

Nagarajan, Radhakrishnan; Upreti, Meenakshi

2017-12-01

Molecular changes often precede clinical presentation of diseases and can be useful surrogates with potential to assist in informed clinical decision making. Recent studies have demonstrated the usefulness of modeling approaches such as classification that can predict the clinical outcomes from molecular expression profiles. While useful, a majority of these approaches implicitly use all molecular markers as features in the classification process often resulting in sparse high-dimensional projection of the samples often comparable to that of the sample size. In this study, a variant of the recently proposed ensemble classification approach is used for predicting good and poor-prognosis breast cancer samples from their molecular expression profiles. In contrast to traditional single and ensemble classifiers, the proposed approach uses multiple base classifiers with varying feature sets obtained from two-dimensional projection of the samples in conjunction with a majority voting strategy for predicting the class labels. In contrast to our earlier implementation, base classifiers in the ensembles are chosen based on maximal sensitivity and minimal redundancy by choosing only those with low average cosine distance. The resulting ensemble sets are subsequently modeled as undirected graphs. Performance of four different classification algorithms is shown to be better within the proposed ensemble framework in contrast to using them as traditional single classifier systems. Significance of a subset of genes with high-degree centrality in the network abstractions across the poor-prognosis samples is also discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Conjugated bilirubin affects cytokine profiles in hepatitis A virus infection by modulating function of signal transducer and activator of transcription factors

PubMed Central

Castro-García, Flor P; Corral-Jara, Karla F; Escobedo-Melendez, Griselda; Sandoval-Hernandez, Monserrat A; Rosenstein, Yvonne; Roman, Sonia; Panduro, Arturo; Fierro, Nora A

2014-01-01

Hepatitis A virus (HAV) infection is the major cause of acute liver failure in paediatric patients. The clinical spectrum of infection is variable, and liver injury is determined by altered hepatic enzyme function and bilirubin concentration. We recently reported differences in cytokine profiles between distinct HAV-induced clinical courses, and bilirubin has been recognized as a potential immune-modulator. However, how bilirubin may affect cytokine profiles underlying the variability in the course of infection has not been determined. Herein, we used a transcription factor (TF) binding site identification approach to retrospectively analyse cytokine expression in HAV-infected children and to predict the entire set of TFs associated with the expression of specific cytokine profiles. The results suggested that modulation of the activity of signal transducers and activators of transcription proteins (STATs) may play a central role during HAV infection. This led us to compare the degree of STAT phosphorylation in peripheral blood lymphoid cells (PBLCs) from paediatric patients with distinct levels of conjugated bilirubin (CB). Low CB levels in sera were associated with increased STAT-1 and STAT-5 phosphorylation. A positive correlation was observed between the serum interleukin-6 (IL-6) content and CB values, whereas higher levels of CB correlated with reduced serum IL-8 values and with a reduction in the proportion of PBLCs positive for STAT-5 phosphorylation. When CB was used to stimulate patients’ PBLCs in vitro, the levels of IL-6 and tumour necrosis factor-α were increased. The data showed that bilirubin plays a role in STAT function and affects cytokine profile expression during HAV infection. PMID:24943111

Conjugated bilirubin affects cytokine profiles in hepatitis A virus infection by modulating function of signal transducer and activator of transcription factors.

PubMed

Castro-García, Flor P; Corral-Jara, Karla F; Escobedo-Melendez, Griselda; Sandoval-Hernandez, Monserrat A; Rosenstein, Yvonne; Roman, Sonia; Panduro, Arturo; Fierro, Nora A

2014-12-01

Hepatitis A virus (HAV) infection is the major cause of acute liver failure in paediatric patients. The clinical spectrum of infection is variable, and liver injury is determined by altered hepatic enzyme function and bilirubin concentration. We recently reported differences in cytokine profiles between distinct HAV-induced clinical courses, and bilirubin has been recognized as a potential immune-modulator. However, how bilirubin may affect cytokine profiles underlying the variability in the course of infection has not been determined. Herein, we used a transcription factor (TF) binding site identification approach to retrospectively analyse cytokine expression in HAV-infected children and to predict the entire set of TFs associated with the expression of specific cytokine profiles. The results suggested that modulation of the activity of signal transducers and activators of transcription proteins (STATs) may play a central role during HAV infection. This led us to compare the degree of STAT phosphorylation in peripheral blood lymphoid cells (PBLCs) from paediatric patients with distinct levels of conjugated bilirubin (CB). Low CB levels in sera were associated with increased STAT-1 and STAT-5 phosphorylation. A positive correlation was observed between the serum interleukin-6 (IL-6) content and CB values, whereas higher levels of CB correlated with reduced serum IL-8 values and with a reduction in the proportion of PBLCs positive for STAT-5 phosphorylation. When CB was used to stimulate patients' PBLCs in vitro, the levels of IL-6 and tumour necrosis factor-α were increased. The data showed that bilirubin plays a role in STAT function and affects cytokine profile expression during HAV infection. © 2014 John Wiley & Sons Ltd.

Early diffusion of gene expression profiling in breast cancer patients associated with areas of high income inequality.

PubMed

Ponce, Ninez A; Ko, Michelle; Liang, Su-Ying; Armstrong, Joanne; Toscano, Michele; Chanfreau-Coffinier, Catherine; Haas, Jennifer S

2015-04-01

With the Affordable Care Act reducing coverage disparities, social factors could prominently determine where and for whom innovations first diffuse in health care markets. Gene expression profiling is a potentially cost-effective innovation that guides chemotherapy decisions in early-stage breast cancer, but adoption has been uneven across the United States. Using a sample of commercially insured women, we evaluated whether income inequality in metropolitan areas was associated with receipt of gene expression profiling during its initial diffusion in 2006-07. In areas with high income inequality, gene expression profiling receipt was higher than elsewhere, but it was associated with a 10.6-percentage-point gap between high- and low-income women. In areas with low rates of income inequality, gene expression profiling receipt was lower, with no significant differences by income. Even among insured women, income inequality may indirectly shape diffusion of gene expression profiling, with benefits accruing to the highest-income patients in the most unequal places. Policies reducing gene expression profiling disparities should address low-inequality areas and, in unequal places, practice settings serving low-income patients. Project HOPE—The People-to-People Health Foundation, Inc.

Benchmarking Water Quality from Wastewater to Drinking Waters Using Reduced Transcriptome of Human Cells.

PubMed

Xia, Pu; Zhang, Xiaowei; Zhang, Hanxin; Wang, Pingping; Tian, Mingming; Yu, Hongxia

2017-08-15

One of the major challenges in environmental science is monitoring and assessing the risk of complex environmental mixtures. In vitro bioassays with limited key toxicological end points have been shown to be suitable to evaluate mixtures of organic pollutants in wastewater and recycled water. Omics approaches such as transcriptomics can monitor biological effects at the genome scale. However, few studies have applied omics approach in the assessment of mixtures of organic micropollutants. Here, an omics approach was developed for profiling bioactivity of 10 water samples ranging from wastewater to drinking water in human cells by a reduced human transcriptome (RHT) approach and dose-response modeling. Transcriptional expression of 1200 selected genes were measured by an Ampliseq technology in two cell lines, HepG2 and MCF7, that were exposed to eight serial dilutions of each sample. Concentration-effect models were used to identify differentially expressed genes (DEGs) and to calculate effect concentrations (ECs) of DEGs, which could be ranked to investigate low dose response. Furthermore, molecular pathways disrupted by different samples were evaluated by Gene Ontology (GO) enrichment analysis. The ability of RHT for representing bioactivity utilizing both HepG2 and MCF7 was shown to be comparable to the results of previous in vitro bioassays. Finally, the relative potencies of the mixtures indicated by RHT analysis were consistent with the chemical profiles of the samples. RHT analysis with human cells provides an efficient and cost-effective approach to benchmarking mixture of micropollutants and may offer novel insight into the assessment of mixture toxicity in water.

Transcriptome Analysis of Chlorantraniliprole Resistance Development in the Diamondback Moth Plutella xylostella

PubMed Central

Hu, Zhendi; Chen, Huanyu; Yin, Fei; Li, Zhenyu; Dong, Xiaolin; Zhang, Deyong; Ren, Shunxiang; Feng, Xia

2013-01-01

Background The diamondback moth Plutella xyllostella has developed a high level of resistance to the latest insecticide chlorantraniliprole. A better understanding of P. xylostella’s resistance mechanism to chlorantraniliprole is needed to develop effective approaches for insecticide resistance management. Principal Findings To provide a comprehensive insight into the resistance mechanisms of P. xylostella to chlorantraniliprole, transcriptome assembly and tag-based digital gene expression (DGE) system were performed using Illumina HiSeq™ 2000. The transcriptome analysis of the susceptible strain (SS) provided 45,231 unigenes (with the size ranging from 200 bp to 13,799 bp), which would be efficient for analyzing the differences in different chlorantraniliprole-resistant P. xylostella stains. DGE analysis indicated that a total of 1215 genes (189 up-regulated and 1026 down-regulated) were gradient differentially expressed among the susceptible strain (SS) and different chlorantraniliprole-resistant P. xylostella strains, including low-level resistance (GXA), moderate resistance (LZA) and high resistance strains (HZA). A detailed analysis of gradient differentially expressed genes elucidated the existence of a phase-dependent divergence of biological investment at the molecular level. The genes related to insecticide resistance, such as P450, GST, the ryanodine receptor, and connectin, had different expression profiles in the different chlorantraniliprole-resistant DGE libraries, suggesting that the genes related to insecticide resistance are involved in P. xylostella resistance development against chlorantraniliprole. To confirm the results from the DGE, the expressional profiles of 4 genes related to insecticide resistance were further validated by qRT-PCR analysis. Conclusions The obtained transcriptome information provides large gene resources available for further studying the resistance development of P. xylostella to pesticides. The DGE data provide comprehensive insights into the gene expression profiles of the different chlorantraniliprole-resistant stains. These genes are specifically related to insecticide resistance, with different expressional profiles facilitating the study of the role of each gene in chlorantraniliprole resistance development. PMID:23977278

Clustering gene expression regulators: new approach to disease subtyping.

PubMed

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

PubMed Central

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

Police attitudes toward policing partner violence against women: do they correspond to different psychosocial profiles?

PubMed

Gracia, Enrique; García, Fernando; Lila, Marisol

2011-01-01

This study analyzed whether police attitudes toward policing partner violence against women corresponded with different psychosocial profiles. Two attitudes toward policing partner violence were considered-one reflecting a general preference for a conditional law enforcement (depending on the willingness of the victim to press charges against the offender) and the other reflecting a general preference for unconditional law enforcement (regardless of the victim's willingness to press charges against the offender). Results from a sample of 378 police officers showed that those police officers who expressed a general preference for unconditional law enforcement scored higher in other-oriented empathy, were less sexist, tended to perceive the same incidents of partner violence as more serious, and felt more personally responsible, as compared to the group of police officers who expressed a preference for a conditional law enforcement approach. Implications for police education are considered.

General Exact Solution to the Problem of the Probability Density for Sums of Random Variables

NASA Astrophysics Data System (ADS)

Tribelsky, Michael I.

2002-07-01

The exact explicit expression for the probability density pN(x) for a sum of N random, arbitrary correlated summands is obtained. The expression is valid for any number N and any distribution of the random summands. Most attention is paid to application of the developed approach to the case of independent and identically distributed summands. The obtained results reproduce all known exact solutions valid for the, so called, stable distributions of the summands. It is also shown that if the distribution is not stable, the profile of pN(x) may be divided into three parts, namely a core (small x), a tail (large x), and a crossover from the core to the tail (moderate x). The quantitative description of all three parts as well as that for the entire profile is obtained. A number of particular examples are considered in detail.

General exact solution to the problem of the probability density for sums of random variables.

PubMed

Tribelsky, Michael I

2002-08-12

The exact explicit expression for the probability density p(N)(x) for a sum of N random, arbitrary correlated summands is obtained. The expression is valid for any number N and any distribution of the random summands. Most attention is paid to application of the developed approach to the case of independent and identically distributed summands. The obtained results reproduce all known exact solutions valid for the, so called, stable distributions of the summands. It is also shown that if the distribution is not stable, the profile of p(N)(x) may be divided into three parts, namely a core (small x), a tail (large x), and a crossover from the core to the tail (moderate x). The quantitative description of all three parts as well as that for the entire profile is obtained. A number of particular examples are considered in detail.

Genomics and drug profiling of fatal TCF3-HLF-positive acute lymphoblastic leukemia identifies recurrent mutation patterns and therapeutic options

PubMed Central

Bornhauser, Beat; Gombert, Michael; Kratsch, Christina; Stütz, Adrian M.; Sultan, Marc; Tchinda, Joelle; Worth, Catherine L.; Amstislavskiy, Vyacheslav; Badarinarayan, Nandini; Baruchel, André; Bartram, Thies; Basso, Giuseppe; Canpolat, Cengiz; Cario, Gunnar; Cavé, Hélène; Dakaj, Dardane; Delorenzi, Mauro; Dobay, Maria Pamela; Eckert, Cornelia; Ellinghaus, Eva; Eugster, Sabrina; Frismantas, Viktoras; Ginzel, Sebastian; Haas, Oskar A.; Heidenreich, Olaf; Hemmrich-Stanisak, Georg; Hezaveh, Kebria; Höll, Jessica I.; Hornhardt, Sabine; Husemann, Peter; Kachroo, Priyadarshini; Kratz, Christian P.; te Kronnie, Geertruy; Marovca, Blerim; Niggli, Felix; McHardy, Alice C.; Moorman, Anthony V.; Panzer-Grümayer, Renate; Petersen, Britt S.; Raeder, Benjamin; Ralser, Meryem; Rosenstiel, Philip; Schäfer, Daniel; Schrappe, Martin; Schreiber, Stefan; Schütte, Moritz; Stade, Björn; Thiele, Ralf; von der Weid, Nicolas; Vora, Ajay; Zaliova, Marketa; Zhang, Langhui; Zichner, Thomas; Zimmermann, Martin; Lehrach, Hans; Borkhardt, Arndt; Bourquin, Jean-Pierre; Franke, Andre; Korbel, Jan O.; Stanulla, Martin; Yaspo, Marie-Laure

2015-01-01

TCF3-HLF-fusion positive acute lymphoblastic leukemia (ALL) is currently incurable. Employing an integrated approach, we uncovered distinct mutation, gene expression, and drug response profiles in TCF3-HLF-positive and treatment-responsive TCF3-PBX1-positive ALL. Recurrent intragenic deletions of PAX5 or VPREB1 were identified in constellation with TCF3-HLF. Moreover somatic mutations in the non-translocated allele of TCF3 and a reduction of PAX5 gene dosage in TCF3-HLF ALL suggest cooperation within a restricted genetic context. The enrichment for stem cell and myeloid features in the TCF3-HLF signature may reflect reprogramming by TCF3-HLF of a lymphoid-committed cell of origin towards a hybrid, drug-resistant hematopoietic state. Drug response profiling of matched patient-derived xenografts revealed a distinct profile for TCF3-HLF ALL with resistance to conventional chemotherapeutics, but sensitivity towards glucocorticoids, anthracyclines and agents in clinical development. Striking on-target sensitivity was achieved with the BCL2-specific inhibitor venetoclax (ABT-199). This integrated approach thus provides alternative treatment options for this deadly disease. PMID:26214592

Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature.

PubMed

Haberman, Yael; Tickle, Timothy L; Dexheimer, Phillip J; Kim, Mi-Ok; Tang, Dora; Karns, Rebekah; Baldassano, Robert N; Noe, Joshua D; Rosh, Joel; Markowitz, James; Heyman, Melvin B; Griffiths, Anne M; Crandall, Wallace V; Mack, David R; Baker, Susan S; Huttenhower, Curtis; Keljo, David J; Hyams, Jeffrey S; Kugathasan, Subra; Walters, Thomas D; Aronow, Bruce; Xavier, Ramnik J; Gevers, Dirk; Denson, Lee A

2014-08-01

Interactions between the host and gut microbial community likely contribute to Crohn disease (CD) pathogenesis; however, direct evidence for these interactions at the onset of disease is lacking. Here, we characterized the global pattern of ileal gene expression and the ileal microbial community in 359 treatment-naive pediatric patients with CD, patients with ulcerative colitis (UC), and control individuals. We identified core gene expression profiles and microbial communities in the affected CD ilea that are preserved in the unaffected ilea of patients with colon-only CD but not present in those with UC or control individuals; therefore, this signature is specific to CD and independent of clinical inflammation. An abnormal increase of antimicrobial dual oxidase (DUOX2) expression was detected in association with an expansion of Proteobacteria in both UC and CD, while expression of lipoprotein APOA1 gene was downregulated and associated with CD-specific alterations in Firmicutes. The increased DUOX2 and decreased APOA1 gene expression signature favored oxidative stress and Th1 polarization and was maximally altered in patients with more severe mucosal injury. A regression model that included APOA1 gene expression and microbial abundance more accurately predicted month 6 steroid-free remission than a model using clinical factors alone. These CD-specific host and microbe profiles identify the ileum as the primary inductive site for all forms of CD and may direct prognostic and therapeutic approaches.

microRNA expression profiling on individual breast cancer patients identifies novel panel of circulating microRNA for early detection.

PubMed

Hamam, Rimi; Ali, Arwa M; Alsaleh, Khalid A; Kassem, Moustapha; Alfayez, Musaed; Aldahmash, Abdullah; Alajez, Nehad M

2016-05-16

Breast cancer (BC) is the most common cancer type and the second cause of cancer-related death among women. Therefore, better understanding of breast cancer tumor biology and the identification of novel biomarkers is essential for the early diagnosis and for better disease stratification and management choices. Herein we developed a novel approach which relies on the isolation of circulating microRNAs through an enrichment step using speed-vacuum concentration which resulted in 5-fold increase in microRNA abundance. Global miRNA microarray expression profiling performed on individual samples from 23 BC and 9 normals identified 18 up-regulated miRNAs in BC patients (p(corr) < 0.05). Nine miRNAs (hsa-miR-4270, hsa-miR-1225-5p, hsa-miR-188-5p, hsa-miR-1202, hsa-miR-4281, hsa-miR-1207-5p, hsa-miR-642b-3p, hsa-miR-1290, and hsa-miR-3141) were subsequently validated using qRT-PCR in a cohort of 46 BC and 14 controls. The expression of those microRNAs was overall higher in patients with stage I, II, and III, compared to stage IV, with potential utilization for early detection. The expression of this microRNA panel was slightly higher in the HER2 and TN compared to patients with luminal subtype. Therefore, we developed a novel approach which led to the identification of a novel microRNA panel which was upregulated in BC patients with potential utilization in disease diagnosis and stratification.

Use of Gene Expression, Biochemical and Metabolite Profiles to Enhance Exposure and Effects Assessment of the Model Androgen 17β-trenbolone in Fish

EPA Science Inventory

The impact of exposure by water to a model androgen, 17β-trenbolone (TRB), was assessed in fathead minnows using an integrated molecular approach. This included classical measures of endocrine exposure such as impacts on testosterone (T), 17β-estradiol (E2), and vitellogenin (VTG...

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472

PubMed Central

Baraúna, Rafael A.; Santos, Agenor V.; Graças, Diego A.; Santos, Daniel M.; Ghilardi, Rubens; Pimenta, Adriano M. C.; Carepo, Marta S. P.; Schneider, Maria P.C.; Silva, Artur

2015-01-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field. PMID:26273227

Evidence of Dynamically Dysregulated Gene Expression Pathways in Hyperresponsive B Cells from African American Lupus Patients

PubMed Central

Dozmorov, Igor; Dominguez, Nicolas; Sestak, Andrea L.; Robertson, Julie M.; Harley, John B.; James, Judith A.; Guthridge, Joel M.

2013-01-01

Recent application of gene expression profiling to the immune system has shown a great potential for characterization of complex regulatory processes. It is becoming increasingly important to characterize functional systems through multigene interactions to provide valuable insights into differences between healthy controls and autoimmune patients. Here we apply an original systematic approach to the analysis of changes in regulatory gene interconnections between in Epstein-Barr virus transformed hyperresponsive B cells from SLE patients and normal control B cells. Both traditional analysis of differential gene expression and analysis of the dynamics of gene expression variations were performed in combination to establish model networks of functional gene expression. This Pathway Dysregulation Analysis identified known transcription factors and transcriptional regulators activated uniquely in stimulated B cells from SLE patients. PMID:23977035

DMirNet: Inferring direct microRNA-mRNA association networks.

PubMed

Lee, Minsu; Lee, HyungJune

2016-12-05

MicroRNAs (miRNAs) play important regulatory roles in the wide range of biological processes by inducing target mRNA degradation or translational repression. Based on the correlation between expression profiles of a miRNA and its target mRNA, various computational methods have previously been proposed to identify miRNA-mRNA association networks by incorporating the matched miRNA and mRNA expression profiles. However, there remain three major issues to be resolved in the conventional computation approaches for inferring miRNA-mRNA association networks from expression profiles. 1) Inferred correlations from the observed expression profiles using conventional correlation-based methods include numerous erroneous links or over-estimated edge weight due to the transitive information flow among direct associations. 2) Due to the high-dimension-low-sample-size problem on the microarray dataset, it is difficult to obtain an accurate and reliable estimate of the empirical correlations between all pairs of expression profiles. 3) Because the previously proposed computational methods usually suffer from varying performance across different datasets, a more reliable model that guarantees optimal or suboptimal performance across different datasets is highly needed. In this paper, we present DMirNet, a new framework for identifying direct miRNA-mRNA association networks. To tackle the aforementioned issues, DMirNet incorporates 1) three direct correlation estimation methods (namely Corpcor, SPACE, Network deconvolution) to infer direct miRNA-mRNA association networks, 2) the bootstrapping method to fully utilize insufficient training expression profiles, and 3) a rank-based Ensemble aggregation to build a reliable and robust model across different datasets. Our empirical experiments on three datasets demonstrate the combinatorial effects of necessary components in DMirNet. Additional performance comparison experiments show that DMirNet outperforms the state-of-the-art Ensemble-based model [1] which has shown the best performance across the same three datasets, with a factor of up to 1.29. Further, we identify 43 putative novel multi-cancer-related miRNA-mRNA association relationships from an inferred Top 1000 direct miRNA-mRNA association network. We believe that DMirNet is a promising method to identify novel direct miRNA-mRNA relations and to elucidate the direct miRNA-mRNA association networks. Since DMirNet infers direct relationships from the observed data, DMirNet can contribute to reconstructing various direct regulatory pathways, including, but not limited to, the direct miRNA-mRNA association networks.

Mass spectrometry-based proteomic analysis of human liver cytochrome(s) P450

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shrivas, Kamlesh; Mindaye, Samuel T.; Getie-Kebtie, Melkamu

2013-02-15

The major objective of personalized medicine is to select optimized drug therapies and to a large degree such mission is determined by the expression profiles of cytochrome(s) P450 (CYP). Accordingly, a proteomic case study in personalized medicine is provided by the superfamily of cytochromes P450. Our knowledge about CYP isozyme expression on a protein level is very limited and based exclusively on DNA/mRNA derived data. Such information is not sufficient because transcription and translation events do not lead to correlated levels of expressed proteins. Here we report expression profiles of CYPs in human liver obtained by mass spectrometry (MS)-based proteomicmore » approach. We analyzed 32 samples of human liver microsomes (HLM) of different sexes, ages and ethnicity along with samples of recombinant human CYPs. We have experimentally confirmed that each CYP isozyme can be effectively differentiated by their unique isozyme-specific tryptic peptide(s). Trypsin digestion patterns for almost 30 human CYP isozymes were established. Those findings should assist in selecting tryptic peptides suitable for MS-based quantitation. The data obtained demonstrate remarkable differences in CYP expression profiles. CYP2E1, CYP2C8 and CYP4A11 were the only isozymes found in all HLM samples. Female and pediatric HLM samples revealed much more diverse spectrum of expressed CYPs isozymes compared to male HLM. We have confirmed expression of a number of “rare” CYP (CYP2J2, CYP4B1, CYP4V2, CYP4F3, CYP4F11, CYP8B1, CYP19A1, CYP24A1 and CYP27A1) and obtained first direct experimental data showing expression of such CYPs as CYP2F1, CYP2S1, CYP2W1, CYP4A22, CYP4X1, and CYP26A1 on a protein level. - Highlights: ► First detailed proteomic analysis of CYP isozymes expression in human liver ► Trypsin digestion patterns for almost 30 human CYP isozymes established ► The data obtained demonstrate remarkable differences in CYP expression profiles. ► Female HLM samples revealed more diverse spectrum of CYP isozymes than male. ► First data showing expression of 2F1, 2S1, 2W1, 4A22, 4X1, 26A1 on a protein level.« less

Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

PubMed Central

Gan, Lin; Denecke, Bernd

2013-01-01

Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner. PMID:27605179

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-06-14

Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors

PubMed Central

Andersson, Claes R; Hvidsten, Torgeir R; Isaksson, Anders; Gustafsson, Mats G; Komorowski, Jan

2007-01-01

Background We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process. Results We explain the regulatory mechanisms of the inferred periodic classes with cis-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of cis-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach. Conclusion The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes. PMID:17939860

Increased Bisecting N-Acetylglucosamine and Decreased Branched Chain Glycans of N-linked Glycoproteins in Expressed Prostatic Secretions Associated with Prostate Cancer Progression

PubMed Central

Nyalwidhe, Julius O.; Betesh, Lucy R.; Powers, Thomas W.; Jones, E. Ellen; White, Krista Y.; Burch, Tanya C.; Brooks, Jasmin; Watson, Megan T.; Lance, Raymond S.; Troyer, Dean A.; Semmes, O. John; Mehta, Anand; Drake, Richard R.

2013-01-01

Purpose Using prostatic fluids rich in glycoproteins like prostate specific antigen (PSA) and prostatic acid phosphatase (PAP) , the goal of this study was to identify the structural types and relative abundance of glycans associated with prostate cancer status for subsequent use in emerging mass spectrometry-based glycopeptide analysis platforms. Experimental Design A series of pooled samples of expressed prostatic secretions (EPS) and exosomes reflecting different stages of prostate cancer disease were used for N-linked glycan profiling by three complementary methods, MALDI-TOF profiling, normal-phase HPLC separation, and triple quadropole MS analysis of PAP glycopeptides. Results Glycan profiling of N-linked glycans from different EPS fluids indicated a global decrease in larger branched tri- and tetra-antennary glycans. Differential exoglycosidase treatments indicated a substantial increase in bisecting N-acetylglucosamines correlated with disease severity. A triple quadrupole MS analysis of the N-linked glycopeptides sites from PAP in aggressive prostate cancer pools was done to cross-reference with the glycan profiling data. Conclusion and clinical relevance Changes in glycosylation as detected in EPS fluids reflect the clinical status of prostate cancer. Defining these molecular signatures at the glycopeptide level in individual samples could improve current approaches of diagnosis and prognosis. PMID:23775902

Cancer survival classification using integrated data sets and intermediate information.

PubMed

Kim, Shinuk; Park, Taesung; Kon, Mark

2014-09-01

Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS was 75.51% (RF), 87.76% (SVM) 85.71% (FSCOX_median), 85.71% (FSCOX_SVM). These results are higher than the results of using miRNA expression and mRNA expression alone. In addition we predict 16 hsa-miR-23b and hsa-miR-27b target genes in ovarian cancer data sets, obtained by SVM-based feature selection through integration of sequence information and gene expression profiles. Among the approaches used, the integrated miRNA and mRNA data set yielded better results than the individual data sets. The best performance was achieved using the FSCOX_SVM method with independent feature selection, which uses intermediate survival information between short-term and long-term survival time and the combination of the 2 different data sets. The results obtained using the combined data set suggest that there are some strong interactions between miRNA and mRNA features that are not detectable in the individual analyses. Copyright © 2014 Elsevier B.V. All rights reserved.

MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system

PubMed Central

Kapsimali, Marika; Kloosterman, Wigard P; de Bruijn, Ewart; Rosa, Frederic; Plasterk, Ronald HA; Wilson, Stephen W

2007-01-01

Background MicroRNA (miRNA) encoding genes are abundant in vertebrate genomes but very few have been studied in any detail. Bioinformatic tools allow prediction of miRNA targets and this information coupled with knowledge of miRNA expression profiles facilitates formulation of hypotheses of miRNA function. Although the central nervous system (CNS) is a prominent site of miRNA expression, virtually nothing is known about the spatial and temporal expression profiles of miRNAs in the brain. To provide an overview of the breadth of miRNA expression in the CNS, we performed a comprehensive analysis of the neuroanatomical expression profiles of 38 abundant conserved miRNAs in developing and adult zebrafish brain. Results Our results show miRNAs have a wide variety of different expression profiles in neural cells, including: expression in neuronal precursors and stem cells (for example, miR-92b); expression associated with transition from proliferation to differentiation (for example, miR-124); constitutive expression in mature neurons (miR-124 again); expression in both proliferative cells and their differentiated progeny (for example, miR-9); regionally restricted expression (for example, miR-222 in telencephalon); and cell-type specific expression (for example, miR-218a in motor neurons). Conclusion The data we present facilitate prediction of likely modes of miRNA function in the CNS and many miRNA expression profiles are consistent with the mutual exclusion mode of function in which there is spatial or temporal exclusion of miRNAs and their targets. However, some miRNAs, such as those with cell-type specific expression, are more likely to be co-expressed with their targets. Our data provide an important resource for future functional studies of miRNAs in the CNS. PMID:17711588

Evolutionary conserved microRNAs are ubiquitously expressed compared to tick-specific miRNAs in the cattle tick Rhipicephalus (Boophilus) microplus

PubMed Central

2011-01-01

Background MicroRNAs (miRNAs) are small non-coding RNAs that act as regulators of gene expression in eukaryotes modulating a large diversity of biological processes. The discovery of miRNAs has provided new opportunities to understand the biology of a number of species. The cattle tick, Rhipicephalus (Boophilus) microplus, causes significant economic losses in cattle production worldwide and this drives us to further understand their biology so that effective control measures can be developed. To be able to provide new insights into the biology of cattle ticks and to expand the repertoire of tick miRNAs we utilized Illumina technology to sequence the small RNA transcriptomes derived from various life stages and selected organs of R. microplus. Results To discover and profile cattle tick miRNAs we employed two complementary approaches, one aiming to find evolutionary conserved miRNAs and another focused on the discovery of novel cattle-tick specific miRNAs. We found 51 evolutionary conserved R. microplus miRNA loci, with 36 of these previously found in the tick Ixodes scapularis. The majority of the R. microplus miRNAs are perfectly conserved throughout evolution with 11, 5 and 15 of these conserved since the Nephrozoan (640 MYA), Protostomian (620MYA) and Arthropoda (540 MYA) ancestor, respectively. We then employed a de novo computational screening for novel tick miRNAs using the draft genome of I. scapularis and genomic contigs of R. microplus as templates. This identified 36 novel R. microplus miRNA loci of which 12 were conserved in I. scapularis. Overall we found 87 R. microplus miRNA loci, of these 15 showed the expression of both miRNA and miRNA* sequences. R. microplus miRNAs showed a variety of expression profiles, with the evolutionary-conserved miRNAs mainly expressed in all life stages at various levels, while the expression of novel tick-specific miRNAs was mostly limited to particular life stages and/or tick organs. Conclusions Anciently acquired miRNAs in the R. microplus lineage not only tend to accumulate the least amount of nucleotide substitutions as compared to those recently acquired miRNAs, but also show ubiquitous expression profiles through out tick life stages and organs contrasting with the restricted expression profiles of novel tick-specific miRNAs. PMID:21699734

Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius

PubMed Central

Faherty, Sheena L.; Villanueva-Cañas, José Luis; Klopfer, Peter H.; Albà, M. Mar; Yoder, Anne D.

2016-01-01

Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators—Madagascar’s dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

Transcriptomic Analysis of the Claudin Interactome in Malignant Pleural Mesothelioma: Evaluation of the Effect of Disease Phenotype, Asbestos Exposure, and CDKN2A Deletion Status

PubMed Central

Rouka, Erasmia; Vavougios, Georgios D.; Solenov, Evgeniy I.; Gourgoulianis, Konstantinos I.; Hatzoglou, Chrissi; Zarogiannis, Sotirios G.

2017-01-01

Malignant pleural mesothelioma (MPM) is a highly aggressive tumor primarily associated with asbestos exposure. Early detection of MPM is restricted by the long latency period until clinical presentation, the ineffectiveness of imaging techniques in early stage detection and the lack of non-invasive biomarkers with high sensitivity and specificity. In this study we used transcriptome data mining in order to determine which CLAUDIN (CLDN) genes are differentially expressed in MPM as compared to controls. Using the same approach we identified the interactome of the differentially expressed CLDN genes and assessed their expression profile. Subsequently, we evaluated the effect of tumor histology, asbestos exposure, CDKN2A deletion status, and gender on the gene expression level of the claudin interactome. We found that 5 out of 15 studied CLDNs (4, 5, 8, 10, 15) and 4 out of 27 available interactors (S100B, SHBG, CDH5, CXCL8) were differentially expressed in MPM specimens vs. healthy tissues. The genes encoding the CLDN-15 and S100B proteins present differences in their expression profile between the three histological subtypes of MPM. Moreover, CLDN-15 is significantly under-expressed in the cohort of patients with previous history of asbestos exposure. CLDN-15 was also found significantly underexpressed in patients lacking the CDKN2A gene. These results warrant the detailed in vitro investigation of the role of CDLN-15 in the pathobiology of MPM. PMID:28377727

Transcriptomic Analysis of the Claudin Interactome in Malignant Pleural Mesothelioma: Evaluation of the Effect of Disease Phenotype, Asbestos Exposure, and CDKN2A Deletion Status.

PubMed

Rouka, Erasmia; Vavougios, Georgios D; Solenov, Evgeniy I; Gourgoulianis, Konstantinos I; Hatzoglou, Chrissi; Zarogiannis, Sotirios G

2017-01-01

Malignant pleural mesothelioma (MPM) is a highly aggressive tumor primarily associated with asbestos exposure. Early detection of MPM is restricted by the long latency period until clinical presentation, the ineffectiveness of imaging techniques in early stage detection and the lack of non-invasive biomarkers with high sensitivity and specificity. In this study we used transcriptome data mining in order to determine which CLAUDIN (CLDN) genes are differentially expressed in MPM as compared to controls. Using the same approach we identified the interactome of the differentially expressed CLDN genes and assessed their expression profile. Subsequently, we evaluated the effect of tumor histology, asbestos exposure, CDKN2A deletion status, and gender on the gene expression level of the claudin interactome. We found that 5 out of 15 studied CLDNs ( 4, 5, 8, 10, 15 ) and 4 out of 27 available interactors ( S100B, SHBG, CDH5, CXCL8 ) were differentially expressed in MPM specimens vs. healthy tissues. The genes encoding the CLDN-15 and S100B proteins present differences in their expression profile between the three histological subtypes of MPM. Moreover, CLDN-15 is significantly under-expressed in the cohort of patients with previous history of asbestos exposure. CLDN-15 was also found significantly underexpressed in patients lacking the CDKN2A gene. These results warrant the detailed in vitro investigation of the role of CDLN-15 in the pathobiology of MPM.

Detection of growth hormone doping by gene expression profiling of peripheral blood.

PubMed

Mitchell, Christopher J; Nelson, Anne E; Cowley, Mark J; Kaplan, Warren; Stone, Glenn; Sutton, Selina K; Lau, Amie; Lee, Carol M Y; Ho, Ken K Y

2009-12-01

GH abuse is a significant problem in many sports, and there is currently no robust test that allows detection of doping beyond a short window after administration. Our objective was to evaluate gene expression profiling in peripheral blood leukocytes in-vivo as a test for GH doping in humans. Seven men and thirteen women were administered GH, 2 mg/d sc for 8 wk. Blood was collected at baseline and at 8 wk. RNA was extracted from the white cell fraction. Microarray analysis was undertaken using Agilent 44K G4112F arrays using a two-color design. Quantitative RT-PCR using TaqMan gene expression assays was performed for validation of selected differentially expressed genes. GH induced an approximately 2-fold increase in circulating IGF-I that was maintained throughout the 8 wk of the study. GH induced significant changes in gene expression with 353 in women and 41 in men detected with a false discovery rate of less than 5%. None of the differentially expressed genes were common between men and women. The maximal changes were a doubling for up-regulated or halving for down-regulated genes, similar in magnitude to the variation between individuals. Quantitative RT-PCR for seven target genes showed good concordance between microarray and quantitative PCR data in women but not in men. Gene expression analysis of peripheral blood leukocytes is unlikely to be a viable approach for the detection of GH doping.

Direct and indirect drift assessment means. Part 2: wind tunnel experiments.

PubMed

Nuyttens, D; De Schampheleire, M; Baetens, K; Sonck, B

2008-01-01

Wind tunnel measurements, performed in Silsoe Research Institute (SRI), were used to measure airborne and fallout spray volumes under directly comparable and repeatable conditions for single and static nozzles. Based on these measurements, drift potential reduction percentages (DPRP), expressing the percentage reduction of the drift potential compared with the reference spraying, were calculated following three approaches. The first approach was based on the calculation of the first moment of the airborne spray profile (DPRPv1). In the second and third approach, the surface under the measured airborne (DPRPv2) and fallout (DPRP(H)) deposit curve were used. These DPRP values express the percentage reduction of the drift potential compared with the reference spraying. Ten different spray nozzles were tested. The results showed the expected fallout profiles with the highest deposits closest to the nozzle and a systematic decrease with distance from the nozzle. For the airborne deposit profiles, the highest deposits were found at the Lowest collectors with an important systematic decrease with increasing heights. For the same nozzle size and spray pressure, DPRP values are generally higher for the air inclusion nozzles followed by the low-drift nozzles and the standard flat fan nozzles and the effect of nozzle type is most important for smaller nozzle sizes. In general, the bigger the ISO nozzle size, the higher the DPRP values. Comparing results from the three different approaches namely, DPRPv1, DPRPv2 and DPRP(H), some interesting conclusions can be drawn. For the standard flat fan nozzles, DPRPv1, values were the highest followed by DPRPv2 and DPRP(H) while for the low-drift nozzles opposite results were found. For the air inclusion nozzles, there was a relatively good agreement between DPRPv1, DPRPv1 and DPRP(H) values. All of this is important in the interpretation of wind tunnel data for different nozzle types and sampling methodologies.

A novel approach for data integration and disease subtyping

PubMed Central

Tagett, Rebecca; Diaz, Diana

2017-01-01

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data. PMID:29066617

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

PubMed

Tabassum, Rubina; Sivadas, Ambily; Agrawal, Vartika; Tian, Haozheng; Arafat, Dalia; Gibson, Greg

2015-08-13

Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. People express an "omic personality" consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

A Graphical Modelling Approach to the Dissection of Highly Correlated Transcription Factor Binding Site Profiles

PubMed Central

Stojnic, Robert; Fu, Audrey Qiuyan; Adryan, Boris

2012-01-01

Inferring the combinatorial regulatory code of transcription factors (TFs) from genome-wide TF binding profiles is challenging. A major reason is that TF binding profiles significantly overlap and are therefore highly correlated. Clustered occurrence of multiple TFs at genomic sites may arise from chromatin accessibility and local cooperation between TFs, or binding sites may simply appear clustered if the profiles are generated from diverse cell populations. Overlaps in TF binding profiles may also result from measurements taken at closely related time intervals. It is thus of great interest to distinguish TFs that directly regulate gene expression from those that are indirectly associated with gene expression. Graphical models, in particular Bayesian networks, provide a powerful mathematical framework to infer different types of dependencies. However, existing methods do not perform well when the features (here: TF binding profiles) are highly correlated, when their association with the biological outcome is weak, and when the sample size is small. Here, we develop a novel computational method, the Neighbourhood Consistent PC (NCPC) algorithms, which deal with these scenarios much more effectively than existing methods do. We further present a novel graphical representation, the Direct Dependence Graph (DDGraph), to better display the complex interactions among variables. NCPC and DDGraph can also be applied to other problems involving highly correlated biological features. Both methods are implemented in the R package ddgraph, available as part of Bioconductor (http://bioconductor.org/packages/2.11/bioc/html/ddgraph.html). Applied to real data, our method identified TFs that specify different classes of cis-regulatory modules (CRMs) in Drosophila mesoderm differentiation. Our analysis also found depletion of the early transcription factor Twist binding at the CRMs regulating expression in visceral and somatic muscle cells at later stages, which suggests a CRM-specific repression mechanism that so far has not been characterised for this class of mesodermal CRMs. PMID:23144600

Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone

PubMed Central

Moody, Laura R; Herbst, Allen J; Yoo, Han Sang; Vanderloo, Joshua P

2009-01-01

Identification of genes expressed in response to prion infection may elucidate biomarkers for disease, identify factors involved in agent replication, mechanisms of neuropathology and therapeutic targets. Although several groups have sought to identify gene expression changes specific to prion disease, expression profiles rife with cell population changes have consistently been identified. Cuprizone, a neurotoxicant, qualitatively mimics the cell population changes observed in prion disease, resulting in both spongiform change and astrocytosis. The use of cuprizone-treated animals as an experimental control during comparative expression profiling allows for the identification of transcripts whose expression increases during prion disease and remains unchanged during cuprizone-triggered neuropathology. In this study, expression profiles from the brains of mice preclinically and clinically infected with Rocky Mountain Laboratory (RML) mouse-adapted scrapie agent and age-matched controls were profiled using Affymetrix gene arrays. In total, 164 genes were differentially regulated during prion infection. Eighty-three of these transcripts have been previously undescribed as differentially regulated during prion disease. A 0.4% cuprizone diet was utilized as a control for comparative expression profiling. Cuprizone treatment induced spongiosis and astrocyte proliferation as indicated by glial fibrillary acidic protein (Gfap) transcriptional activation and immunohistochemistry. Gene expression profiles from brain tissue obtained from cuprizone-treated mice identified 307 differentially regulated transcript changes. After comparative analysis, 17 transcripts unaffected by cuprizone treatment but increasing in expression from preclinical to clinical prion infection were identified. Here we describe the novel use of the prion disease mimetic, cuprizone, to control for cell population changes in the brain during prion infection. PMID:19535908

Defining the molecular profile of planarian pluripotent stem cells using a combinatorial RNAseq, RNA interference and irradiation approach.

PubMed

Solana, Jordi; Kao, Damian; Mihaylova, Yuliana; Jaber-Hijazi, Farah; Malla, Sunir; Wilson, Ray; Aboobaker, Aziz

2012-01-01

Planarian stem cells, or neoblasts, drive the almost unlimited regeneration capacities of freshwater planarians. Neoblasts are traditionally described by their morphological features and by the fact that they are the only proliferative cell type in asexual planarians. Therefore, they can be specifically eliminated by irradiation. Irradiation, however, is likely to induce transcriptome-wide changes in gene expression that are not associated with neoblast ablation. This has affected the accurate description of their specific transcriptomic profile. We introduce the use of Smed-histone-2B RNA interference (RNAi) for genetic ablation of neoblast cells in Schmidtea mediterranea as an alternative to irradiation. We characterize the rapid, neoblast-specific phenotype induced by Smed-histone-2B RNAi, resulting in neoblast ablation. We compare and triangulate RNA-seq data after using both irradiation and Smed-histone-2B RNAi over a time course as means of neoblast ablation. Our analyses show that Smed-histone-2B RNAi eliminates neoblast gene expression with high specificity and discrimination from gene expression in other cellular compartments. We compile a high confidence list of genes downregulated by both irradiation and Smed-histone-2B RNAi and validate their expression in neoblast cells. Lastly, we analyze the overall expression profile of neoblast cells. Our list of neoblast genes parallels their morphological features and is highly enriched for nuclear components, chromatin remodeling factors, RNA splicing factors, RNA granule components and the machinery of cell division. Our data reveal that the regulation of planarian stem cells relies on posttranscriptional regulatory mechanisms and suggest that planarians are an ideal model for this understudied aspect of stem cell biology.

Defining the molecular profile of planarian pluripotent stem cells using a combinatorial RNA-seq, RNA interference and irradiation approach

PubMed Central

2012-01-01

Background Planarian stem cells, or neoblasts, drive the almost unlimited regeneration capacities of freshwater planarians. Neoblasts are traditionally described by their morphological features and by the fact that they are the only proliferative cell type in asexual planarians. Therefore, they can be specifically eliminated by irradiation. Irradiation, however, is likely to induce transcriptome-wide changes in gene expression that are not associated with neoblast ablation. This has affected the accurate description of their specific transcriptomic profile. Results We introduce the use of Smed-histone-2B RNA interference (RNAi) for genetic ablation of neoblast cells in Schmidtea mediterranea as an alternative to irradiation. We characterize the rapid, neoblast-specific phenotype induced by Smed-histone-2B RNAi, resulting in neoblast ablation. We compare and triangulate RNA-seq data after using both irradiation and Smed-histone-2B RNAi over a time course as means of neoblast ablation. Our analyses show that Smed-histone-2B RNAi eliminates neoblast gene expression with high specificity and discrimination from gene expression in other cellular compartments. We compile a high confidence list of genes downregulated by both irradiation and Smed-histone-2B RNAi and validate their expression in neoblast cells. Lastly, we analyze the overall expression profile of neoblast cells. Conclusions Our list of neoblast genes parallels their morphological features and is highly enriched for nuclear components, chromatin remodeling factors, RNA splicing factors, RNA granule components and the machinery of cell division. Our data reveal that the regulation of planarian stem cells relies on posttranscriptional regulatory mechanisms and suggest that planarians are an ideal model for this understudied aspect of stem cell biology. PMID:22439894

Gene expression profiles in rainbow trout, Onchorynchus mykiss, exposed to a simple chemical mixture.

PubMed

Hook, Sharon E; Skillman, Ann D; Gopalan, Banu; Small, Jack A; Schultz, Irvin R

2008-03-01

Among proposed uses for microarrays in environmental toxiciology is the identification of key contributors to toxicity within a mixture. However, it remains uncertain whether the transcriptomic profiles resulting from exposure to a mixture have patterns of altered gene expression that contain identifiable contributions from each toxicant component. We exposed isogenic rainbow trout Onchorynchus mykiss, to sublethal levels of ethynylestradiol, 2,2,4,4-tetrabromodiphenyl ether, and chromium VI or to a mixture of all three toxicants Fluorescently labeled complementary DNA (cDNA) were generated and hybridized against a commercially available Salmonid array spotted with 16,000 cDNAs. Data were analyzed using analysis of variance (p<0.05) with a Benjamani-Hochberg multiple test correction (Genespring [Agilent] software package) to identify up and downregulated genes. Gene clustering patterns that can be used as "expression signatures" were determined using hierarchical cluster analysis. The gene ontology terms associated with significantly altered genes were also used to identify functional groups that were associated with toxicant exposure. Cross-ontological analytics approach was used to assign functional annotations to genes with "unknown" function. Our analysis indicates that transcriptomic profiles resulting from the mixture exposure resemble those of the individual contaminant exposures, but are not a simple additive list. However, patterns of altered genes representative of each component of the mixture are clearly discernible, and the functional classes of genes altered represent the individual components of the mixture. These findings indicate that the use of microarrays to identify transcriptomic profiles may aid in the identification of key stressors within a chemical mixture, ultimately improving environmental assessment.

A Comprehensive Approach to Sequence-oriented IsomiR annotation (CASMIR): demonstration with IsomiR profiling in colorectal neoplasia.

PubMed

Wu, Chung Wah; Evans, Jared M; Huang, Shengbing; Mahoney, Douglas W; Dukek, Brian A; Taylor, William R; Yab, Tracy C; Smyrk, Thomas C; Jen, Jin; Kisiel, John B; Ahlquist, David A

2018-05-25

MicroRNA (miRNA) profiling is an important step in studying biological associations and identifying marker candidates. miRNA exists in isoforms, called isomiRs, which may exhibit distinct properties. With conventional profiling methods, limitations in assay and analysis platforms may compromise isomiR interrogation. We introduce a comprehensive approach to sequence-oriented isomiR annotation (CASMIR) to allow unbiased identification of global isomiRs from small RNA sequencing data. In this approach, small RNA reads are maintained as independent sequences instead of being summarized under miRNA names. IsomiR features are identified through step-wise local alignment against canonical forms and precursor sequences. Through customizing the reference database, CASMIR is applicable to isomiR annotation across species. To demonstrate its application, we investigated isomiR profiles in normal and neoplastic human colorectal epithelia. We also ran miRDeep2, a popular miRNA analysis algorithm to validate isomiRs annotated by CASMIR. With CASMIR, specific and biologically relevant isomiR patterns could be identified. We note that specific isomiRs are often more abundant than their canonical forms. We identify isomiRs that are commonly up-regulated in both colorectal cancer and advanced adenoma, and illustrate advantages in targeting isomiRs as potential biomarkers over canonical forms. Studying miRNAs at the isomiR level could reveal new insight into miRNA biology and inform assay design for specific isomiRs. CASMIR facilitates comprehensive annotation of isomiR features in small RNA sequencing data for isomiR profiling and differential expression analysis.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Symptomatic and asymptomatic benign prostatic hyperplasia: Molecular differentiation by using microarrays

NASA Astrophysics Data System (ADS)

Prakash, Kulkarni; Pirozzi, Gregorio; Elashoff, Michael; Munger, William; Waga, Iwao; Dhir, Rajiv; Kakehi, Yoshiyuki; Getzenberg, Robert H.

2002-05-01

Benign prostatic hyperplasia (BPH) is a disease of unknown etiology that significantly affects the quality of life in aging men. Histologic BPH may present itself either as symptomatic or asymptomatic in nature. To elucidate the molecular differences underlying BPH, gene expression profiles from the prostate transition zone tissue have been analyzed by using microarrays. A set of 511 differentially expressed genes distinguished symptomatic and asymptomatic BPH. This genetic signature separates BPH from normal tissue but does not seem to change with age. These data could provide novel approaches for alleviating symptoms and hyperplasia in BPH.

Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study

PubMed Central

Yan, Benedict; Hu, Yongli; Ban, Kenneth H.K.; Tiang, Zenia; Ng, Christopher; Lee, Joanne; Tan, Wilson; Chiu, Lily; Tan, Tin Wee; Seah, Elaine; Ng, Chin Hin; Chng, Wee-Joo; Foo, Roger

2017-01-01

Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. PMID:28454300

Global PROTOMAP profiling to search for biomarkers of early-recurrent hepatocellular carcinoma.

PubMed

Taoka, Masato; Morofuji, Noriaki; Yamauchi, Yoshio; Ojima, Hidenori; Kubota, Daisuke; Terukina, Goro; Nobe, Yuko; Nakayama, Hiroshi; Takahashi, Nobuhiro; Kosuge, Tomoo; Isobe, Toshiaki; Kondo, Tadashi

2014-11-07

This study used global protein expression profiling to search for biomarkers to predict early recurrent hepatocellular carcinoma (HCC). HCC tissues surgically resected from patients with or without recurrence within 2 years (early recurrent) after surgery were compared with adjacent nontumor tissue and with normal liver tissue. We used the PROTOMAP strategy for comparative profiling, which integrates denaturing polyacrylamide gel electrophoresis migratory rates and high-resolution, semiquantitative mass-spectrometry-based identification of in-gel-digested tryptic peptides. PROTOMAP allows examination of global changes in the size, topography, and abundance of proteins in complex tissue samples. This approach identified 8438 unique proteins from 45 708 nonredundant peptides and generated a proteome-wide map of changes in expression and proteolytic events potentially induced by intrinsic apoptotic/necrotic pathways. In the early recurrent HCC tissue, 87 proteins were differentially expressed (≥20-fold) relative to the other tissues, 46 of which were up-regulated or specifically proteolyzed and 41 of which were down-regulated. This data set consisted of proteins that fell into various functional categories, including signal transduction and cell organization and, notably, the major catalytic pathways responsible for liver function, such as the urea cycle and detoxification metabolism. We found that aberrant proteolysis appeared to occur frequently during recurrence of HCC in several key signal transducers, including STAT1 and δ-catenin. Further investigation of these proteins will facilitate the development of novel clinical applications.

In vitro manipulation of gene expression in larval Schistosoma: a model for postgenomic approaches in Trematoda

PubMed Central

YOSHINO, TIMOTHY P.; DINGUIRARD, NATHALIE; DE MORAES MOURÃO, MARINA

2013-01-01

SUMMARY With rapid developments in DNA and protein sequencing technologies, combined with powerful bioinformatics tools, a continued acceleration of gene identification in parasitic helminths is predicted, potentially leading to discovery of new drug and vaccine targets, enhanced diagnostics and insights into the complex biology underlying host-parasite interactions. For the schistosome blood flukes, with the recent completion of genome sequencing and comprehensive transcriptomic datasets, there has accumulated massive amounts of gene sequence data, for which, in the vast majority of cases, little is known about actual functions within the intact organism. In this review we attempt to bring together traditional in vitro cultivation approaches and recent emergent technologies of molecular genomics, transcriptomics and genetic manipulation to illustrate the considerable progress made in our understanding of trematode gene expression and function during development of the intramolluscan larval stages. Using several prominent trematode families (Schistosomatidae, Fasciolidae, Echinostomatidae), we have focused on the current status of in vitro larval isolation/cultivation as a source of valuable raw material supporting gene discovery efforts in model digeneans that include whole genome sequencing, transcript and protein expression profiling during larval development, and progress made in the in vitro manipulation of genes and their expression in larval trematodes using transgenic and RNA interference (RNAi) approaches. PMID:19961646

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system.

PubMed

Sowa, Steven W; Gelderman, Grant; Leistra, Abigail N; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A; Romeo, Tony; Baldea, Michael; Contreras, Lydia M

2017-02-28

Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Investigating the Receptive-Expressive Vocabulary Profile in Children with Idiopathic ASD and Comorbid ASD and Fragile X Syndrome.

PubMed

Haebig, Eileen; Sterling, Audra

2017-02-01

Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD.

Investigating the Receptive-Expressive Vocabulary Profile in Children with Idiopathic ASD and Comorbid ASD and Fragile X Syndrome

PubMed Central

Sterling, Audra

2016-01-01

Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD. PMID:27796729

Vascular biology: cellular and molecular profiling.

PubMed

Baird, Alison E; Wright, Violet L

2006-02-01

Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

Dexamethasone Stimulated Gene Expression in Peripheral Blood is a Sensitive Marker for Glucocorticoid Receptor Resistance in Depressed Patients

PubMed Central

Menke, Andreas; Arloth, Janine; Pütz, Benno; Weber, Peter; Klengel, Torsten; Mehta, Divya; Gonik, Mariya; Rex-Haffner, Monika; Rubel, Jennifer; Uhr, Manfred; Lucae, Susanne; Deussing, Jan M; Müller-Myhsok, Bertram; Holsboer, Florian; Binder, Elisabeth B

2012-01-01

Although gene expression profiles in peripheral blood in major depression are not likely to identify genes directly involved in the pathomechanism of affective disorders, they may serve as biomarkers for this disorder. As previous studies using baseline gene expression profiles have provided mixed results, our approach was to use an in vivo dexamethasone challenge test and to compare glucocorticoid receptor (GR)-mediated changes in gene expression between depressed patients and healthy controls. Whole genome gene expression data (baseline and following GR-stimulation with 1.5 mg dexamethasone p.o.) from two independent cohorts were analyzed to identify gene expression pattern that would predict case and control status using a training (N=18 cases/18 controls) and a test cohort (N=11/13). Dexamethasone led to reproducible regulation of 2670 genes in controls and 1151 transcripts in cases. Several genes, including FKBP5 and DUSP1, previously associated with the pathophysiology of major depression, were found to be reliable markers of GR-activation. Using random forest analyses for classification, GR-stimulated gene expression outperformed baseline gene expression as a classifier for case and control status with a correct classification of 79.1 vs 41.6% in the test cohort. GR-stimulated gene expression performed best in dexamethasone non-suppressor patients (88.7% correctly classified with 100% sensitivity), but also correctly classified 77.3% of the suppressor patients (76.7% sensitivity), when using a refined set of 19 genes. Our study suggests that in vivo stimulated gene expression in peripheral blood cells could be a promising molecular marker of altered GR-functioning, an important component of the underlying pathology, in patients suffering from depressive episodes. PMID:22237309

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Characterization of a Genomic Signature of Pregnancy in the Breast

PubMed Central

Belitskaya-Lévy, Ilana; Zeleniuch-Jacquotte, Anne; Russo, Jose; Russo, Irma H.; Bordás, Pal; Åhman, Janet; Afanasyeva, Yelena; Johansson, Robert; Lenner, Per; Li, Xiaochun; de Cicco, Ricardo López; Peri, Suraj; Ross, Eric; Russo, Patricia A.; Santucci-Pereira, Julia; Sheriff, Fathima S.; Slifker, Michael; Hallmans, Göran; Toniolo, Paolo; Arslan, Alan A.

2012-01-01

The objective of the current study was to comprehensively compare the genomic profiles in the breast of parous and nulliparous postmenopausal women to identify genes that permanently change their expression following pregnancy. The study was designed as a two-phase approach. In the discovery phase, we compared breast genomic profiles of 37 parous with 18 nulliparous postmenopausal women. In the validation phase, confirmation of the genomic patterns observed in the discovery phase was sought in an independent set of 30 parous and 22 nulliparous postmenopausal women. RNA was hybridized to Affymetrix HG_U133 Plus 2.0 oligonucleotide arrays containing probes to 54,675 transcripts; scanned and the images analyzed using Affymetrix GCOS software. Surrogate variable analysis, logistic regression and significance analysis for microarrays were used to identify statistically significant differences in expression of genes. The False Discovery Rate (FDR) approach was used to control for multiple comparisons. We found that 208 genes (305 probe sets) were differentially expressed between parous and nulliparous women in both discovery and validation phases of the study at a FDR of 10% and with at least a 1.25-fold change. These genes are involved in regulation of transcription, centrosome organization, RNA splicing, cell cycle control, adhesion and differentiation. The results provide persuasive evidence that full-term pregnancy induces long-term genomic changes in the breast. The genomic signature of pregnancy could be used as an intermediate marker to assess potential chemopreventive interventions with hormones mimicking the effects of pregnancy for prevention of breast cancer. PMID:21622728

Liver protein profiles in insulin receptor-knockout mice reveal novel molecules involved in the diabetes pathophysiology.

PubMed

Capuani, Barbara; Della-Morte, David; Donadel, Giulia; Caratelli, Sara; Bova, Luca; Pastore, Donatella; De Canio, Michele; D'Aguanno, Simona; Coppola, Andrea; Pacifici, Francesca; Arriga, Roberto; Bellia, Alfonso; Ferrelli, Francesca; Tesauro, Manfredi; Federici, Massimo; Neri, Anna; Bernardini, Sergio; Sbraccia, Paolo; Di Daniele, Nicola; Sconocchia, Giuseppe; Orlandi, Augusto; Urbani, Andrea; Lauro, Davide

2015-05-01

Liver has a principal role in glucose regulation and lipids homeostasis. It is under a complex control by substrates such as hormones, nutrients, and neuronal impulses. Insulin promotes glycogen synthesis, lipogenesis, and lipoprotein synthesis and inhibits gluconeogenesis, glycogenolysis, and VLDL secretion by modifying the expression and enzymatic activity of specific molecules. To understand the pathophysiological mechanisms leading to metabolic liver disease, we analyzed liver protein patterns expressed in a mouse model of diabetes by proteomic approaches. We used insulin receptor-knockout (IR(-/-)) and heterozygous (IR(+/-)) mice as a murine model of liver metabolic dysfunction associated with diabetic ketoacidosis and insulin resistance. We evaluated liver fatty acid levels by microscopic examination and protein expression profiles by orthogonal experimental strategies using protein 2-DE MALDI-TOF/TOF and peptic nLC-MS/MS shotgun profiling. Identified proteins were then loaded into Ingenuity Pathways Analysis to find possible molecular networks. Twenty-eight proteins identified by 2-DE analysis and 24 identified by nLC-MS/MS shotgun were differentially expressed among the three genotypes. Bioinformatic analysis revealed a central role of high-mobility group box 1/2 and huntigtin never reported before in association with metabolic and related liver disease. A different modulation of these proteins in both blood and hepatic tissue further suggests their role in these processes. These results provide new insight into pathophysiology of insulin resistance and hepatic steatosis and could be useful in identifying novel biomarkers to predict risk for diabetes and its complications. Copyright © 2015 the American Physiological Society.

Identification of Chiari Type I Malformation subtypes using whole genome expression profiles and cranial base morphometrics

PubMed Central

2014-01-01

Background Chiari Type I Malformation (CMI) is characterized by herniation of the cerebellar tonsils through the foramen magnum at the base of the skull, resulting in significant neurologic morbidity. As CMI patients display a high degree of clinical variability and multiple mechanisms have been proposed for tonsillar herniation, it is hypothesized that this heterogeneous disorder is due to multiple genetic and environmental factors. The purpose of the present study was to gain a better understanding of what factors contribute to this heterogeneity by using an unsupervised statistical approach to define disease subtypes within a case-only pediatric population. Methods A collection of forty-four pediatric CMI patients were ascertained to identify disease subtypes using whole genome expression profiles generated from patient blood and dura mater tissue samples, and radiological data consisting of posterior fossa (PF) morphometrics. Sparse k-means clustering and an extension to accommodate multiple data sources were used to cluster patients into more homogeneous groups using biological and radiological data both individually and collectively. Results All clustering analyses resulted in the significant identification of patient classes, with the pure biological classes derived from patient blood and dura mater samples demonstrating the strongest evidence. Those patient classes were further characterized by identifying enriched biological pathways, as well as correlated cranial base morphological and clinical traits. Conclusions Our results implicate several strong biological candidates warranting further investigation from the dura expression analysis and also identified a blood gene expression profile corresponding to a global down-regulation in protein synthesis. PMID:24962150

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling

PubMed Central

Narayanan, Manikandan; Martins, Andrew J.; Tsang, John S.

2016-01-01

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies. PMID:27438699

Multi-q pattern classification of polarization curves

NASA Astrophysics Data System (ADS)

Fabbri, Ricardo; Bastos, Ivan N.; Neto, Francisco D. Moura; Lopes, Francisco J. P.; Gonçalves, Wesley N.; Bruno, Odemir M.

2014-02-01

Several experimental measurements are expressed in the form of one-dimensional profiles, for which there is a scarcity of methodologies able to classify the pertinence of a given result to a specific group. The polarization curves that evaluate the corrosion kinetics of electrodes in corrosive media are applications where the behavior is chiefly analyzed from profiles. Polarization curves are indeed a classic method to determine the global kinetics of metallic electrodes, but the strong nonlinearity from different metals and alloys can overlap and the discrimination becomes a challenging problem. Moreover, even finding a typical curve from replicated tests requires subjective judgment. In this paper, we used the so-called multi-q approach based on the Tsallis statistics in a classification engine to separate the multiple polarization curve profiles of two stainless steels. We collected 48 experimental polarization curves in an aqueous chloride medium of two stainless steel types, with different resistance against localized corrosion. Multi-q pattern analysis was then carried out on a wide potential range, from cathodic up to anodic regions. An excellent classification rate was obtained, at a success rate of 90%, 80%, and 83% for low (cathodic), high (anodic), and both potential ranges, respectively, using only 2% of the original profile data. These results show the potential of the proposed approach towards efficient, robust, systematic and automatic classification of highly nonlinear profile curves.

Metal-cluster ionization energy: A profile-insensitive exact expression for the size effect

NASA Astrophysics Data System (ADS)

Seidl, Michael; Perdew, John P.; Brajczewska, Marta; Fiolhais, Carlos

1997-05-01

The ionization energy of a large spherical metal cluster of radius R is I(R)=W+(+c)/R, where W is the bulk work function and c~-0.1 is a material-dependent quantum correction to the electrostatic size effect. We present 'Koopmans' and 'displaced-profile change-in-self-consistent-field' expressions for W and c within the ordinary and stabilized-jellium models. These expressions are shown to be exact and equivalent when the exact density profile of a large neutral cluster is employed; these equivalences generalize the Budd-Vannimenus theorem. With an approximate profile obtained from a restricted variational calculation, the 'displaced-profile' expressions are the more accurate ones. This profile insensitivity is important, because it is not practical to extract c from solutions of the Kohn-Sham equations for small metal clusters.

Parkinson's disease candidate gene prioritization based on expression profile of midbrain dopaminergic neurons

PubMed Central

2010-01-01

Background Parkinson's disease is the second most common neurodegenerative disorder. The pathological hallmark of the disease is degeneration of midbrain dopaminergic neurons. Genetic association studies have linked 13 human chromosomal loci to Parkinson's disease. Identification of gene(s), as part of the etiology of Parkinson's disease, within the large number of genes residing in these loci can be achieved through several approaches, including screening methods, and considering appropriate criteria. Since several of the indentified Parkinson's disease genes are expressed in substantia nigra pars compact of the midbrain, expression within the neurons of this area could be a suitable criterion to limit the number of candidates and identify PD genes. Methods In this work we have used the combination of findings from six rodent transcriptome analysis studies on the gene expression profile of midbrain dopaminergic neurons and the PARK loci in OMIM (Online Mendelian Inheritance in Man) database, to identify new candidate genes for Parkinson's disease. Results Merging the two datasets, we identified 20 genes within PARK loci, 7 of which are located in an orphan Parkinson's disease locus and one, which had been identified as a disease gene. In addition to identifying a set of candidates for further genetic association studies, these results show that the criteria of expression in midbrain dopaminergic neurons may be used to narrow down the number of genes in PARK loci for such studies. PMID:20716345

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation

PubMed Central

De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

2013-01-01

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology ‘reverse engineering’ approaches. We ‘reverse engineered’ an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression (‘hubs’). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central ‘hub’ of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation. PMID:23180766

Genome-Wide Identification and Expression Profiling of ATP-Binding Cassette (ABC) Transporter Gene Family in Pineapple (Ananas comosus (L.) Merr.) Reveal the Role of AcABCG38 in Pollen Development

PubMed Central

Chen, Piaojuan; Li, Yi; Zhao, Lihua; Hou, Zhimin; Yan, Maokai; Hu, Bingyan; Liu, Yanhui; Azam, Syed Muhammad; Zhang, Ziyan; Rahman, Zia ur; Liu, Liping; Qin, Yuan

2017-01-01

Pineapple (Ananas comosus L.) cultivation commonly relies on asexual reproduction which is easily impeded by many factors in agriculture production. Sexual reproduction might be a novel approach to improve the pineapple planting. However, genes controlling pineapple sexual reproduction are still remain elusive. In different organisms a conserved superfamily proteins known as ATP binding cassette (ABC) participate in various biological processes. Whereas, till today the ABC gene family has not been identified in pineapple. Here 100 ABC genes were identified in the pineapple genome and grouped into eight subfamilies (5 ABCAs, 20 ABCBs, 16 ABCCs, 2 ABCDs, one ABCEs, 5 ABCFs, 42 ABCGs and 9 ABCIs). Gene expression profiling revealed the dynamic expression pattern of ABC gene family in various tissues and different developmental stages. AcABCA5, AcABCB6, AcABCC4, AcABCC7, AcABCC9, AcABCG26, AcABCG38 and AcABCG42 exhibited preferential expression in ovule and stamen. Over-expression of AcABCG38 in the Arabidopsis double mutant abcg1-2abcg16-2 partially restored its pollen abortion defects, indicating that AcABCG38 plays important roles in pollen development. Our study on ABC gene family in pineapple provides useful information for developing sexual pineapple plantation which could be utilized to improve pineapple agricultural production. PMID:29312399

Genome-Wide Identification and Expression Profiling of ATP-Binding Cassette (ABC) Transporter Gene Family in Pineapple (Ananas comosus (L.) Merr.) Reveal the Role of AcABCG38 in Pollen Development.

PubMed

Chen, Piaojuan; Li, Yi; Zhao, Lihua; Hou, Zhimin; Yan, Maokai; Hu, Bingyan; Liu, Yanhui; Azam, Syed Muhammad; Zhang, Ziyan; Rahman, Zia Ur; Liu, Liping; Qin, Yuan

2017-01-01

Pineapple ( Ananas comosus L .) cultivation commonly relies on asexual reproduction which is easily impeded by many factors in agriculture production. Sexual reproduction might be a novel approach to improve the pineapple planting. However, genes controlling pineapple sexual reproduction are still remain elusive. In different organisms a conserved superfamily proteins known as ATP binding cassette (ABC) participate in various biological processes. Whereas, till today the ABC gene family has not been identified in pineapple. Here 100 ABC genes were identified in the pineapple genome and grouped into eight subfamilies (5 ABCAs , 20 ABCB s, 16 ABCCs , 2 ABCDs , one ABCEs , 5 ABCFs , 42 ABCGs and 9 ABCIs ). Gene expression profiling revealed the dynamic expression pattern of ABC gene family in various tissues and different developmental stages. AcABCA5, AcABCB6, AcABCC4 , AcABCC7 , AcABCC9 , AcABCG26 , AcABCG38 and AcABCG42 exhibited preferential expression in ovule and stamen. Over-expression of AcABCG38 in the Arabidopsis double mutant abcg1-2abcg16-2 partially restored its pollen abortion defects, indicating that AcABCG38 plays important roles in pollen development. Our study on ABC gene family in pineapple provides useful information for developing sexual pineapple plantation which could be utilized to improve pineapple agricultural production.

Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

Absolute quantification of microbial taxon abundances.

PubMed

Props, Ruben; Kerckhof, Frederiek-Maarten; Rubbens, Peter; De Vrieze, Jo; Hernandez Sanabria, Emma; Waegeman, Willem; Monsieurs, Pieter; Hammes, Frederik; Boon, Nico

2017-02-01

High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

A community effort to assess and improve drug sensitivity prediction algorithms

PubMed Central

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2015-01-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods. PMID:24880487

A community effort to assess and improve drug sensitivity prediction algorithms.

PubMed

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2014-12-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.

Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Profiling of Benign and Malignant Nerve Sheath

DTIC Science & Technology

2007-05-01

Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis Patients PRINCIPAL INVESTIGATOR: Matt van de Rijn, M.D., Ph.D. Torsten...Annual 3. DATES COVERED 1 May 2006 –30 Apr 2007 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Genomic and Expression Profiling of Benign and Malignant Nerve...Award Number: DAMD17-03-1-0297 Title: Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis

Gibberellin-regulated gene in the basal region of rice leaf sheath encodes basic helix-loop-helix transcription factor.

PubMed

Komatsu, Setsuko; Takasaki, Hironori

2009-07-01

Genes regulated by gibberellin (GA) during leaf sheath elongation in rice seedlings were identified using the transcriptome approach. mRNA from the basal regions of leaf sheaths treated with GA3 was analyzed by high-coverage gene expression profiling. 33,004 peaks were detected, and 30 transcripts showed significant changes in the presence of GA3. Among these, basic helix-loop-helix transcription factor (AK073385) was significantly upregulated. Quantitative PCR analysis confirmed that expression of AK073385 was controlled by GA3 in a time- and dose-dependent manner. Basic helix-loop-helix transcription factor (AK073385) is therefore involved in the regulation of gene expression by GA3.

Gene Expression Profiles of Sporadic Canine Hemangiosarcoma Are Uniquely Associated with Breed

PubMed Central

Tamburini, Beth A.; Trapp, Susan; Phang, Tzu Lip; Schappa, Jill T.; Hunter, Lawrence E.; Modiano, Jaime F.

2009-01-01

The role an individual's genetic background plays on phenotype and biological behavior of sporadic tumors remains incompletely understood. We showed previously that lymphomas from Golden Retrievers harbor defined, recurrent chromosomal aberrations that occur less frequently in lymphomas from other dog breeds, suggesting spontaneous canine tumors provide suitable models to define how heritable traits influence cancer genotypes. Here, we report a complementary approach using gene expression profiling in a naturally occurring endothelial sarcoma of dogs (hemangiosarcoma). Naturally occurring hemangiosarcomas of Golden Retrievers clustered separately from those of non-Golden Retrievers, with contributions from transcription factors, survival factors, and from pro-inflammatory and angiogenic genes, and which were exclusively present in hemangiosarcoma and not in other tumors or normal cells (i.e., they were not due simply to variation in these genes among breeds). Vascular Endothelial Growth Factor Receptor 1 (VEGFR1) was among genes preferentially enriched within known pathways derived from gene set enrichment analysis when characterizing tumors from Golden Retrievers versus other breeds. Heightened VEGFR1 expression in these tumors also was apparent at the protein level and targeted inhibition of VEGFR1 increased proliferation of hemangiosarcoma cells derived from tumors of Golden Retrievers, but not from other breeds. Our results suggest heritable factors mold gene expression phenotypes, and consequently biological behavior in sporadic, naturally occurring tumors. PMID:19461996

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Macromolecular Expression and Function: A New Paradigm for NASA Risk Assessment

NASA Technical Reports Server (NTRS)

Richmond, Robert

2003-01-01

Predicting risks in humans of either acute effects such as bone loss or muscle wasting, or late effects such as cancer, is challenging. To an approximation, this is because uncertainties of exposure to stress factors or toxic agents and the uniformity of processing subsequent damage at the cellular level within a complex set of biological variables degrade the confidence of predicting pathologic outcome. A cellular biodosimeter that simultaneously reports 1) the type of damage due to that exposure, 2) the quantity of damage incurred by that exposure, and 3) the dataset used to assess risk of developing pathologic outcome caused by that exposure would therefore be useful for predicting ultimate risks faced by an individual, such as an astronaut. It is suggested that such a biodosimeter can be based upon analyses of gene-expression and protein expression whereby large datasets of cellular response to damage are obtained and analyzed for expression-profiles correlated with established end points and molecular markers predictive for risks being assessed. The usefulness of multiparametric cellular biodosimeters could be realized by quantitatively profiling these datasets using techniques of bioinformatics. Such an approach contributes to the foundation of molecular epidemiology as a new scientific discipline, and represents a new paradigm of risk assessment.

Differentially expressed genes and proteins upon drought acclimation in tolerant and sensitive genotypes of Coffea canephora

PubMed Central

Marraccini, Pierre; Vinecky, Felipe; Alves, Gabriel S.C.; Ramos, Humberto J.O.; Elbelt, Sonia; Vieira, Natalia G.; Carneiro, Fernanda A.; Sujii, Patricia S.; Alekcevetch, Jean C.; Silva, Vânia A.; DaMatta, Fábio M.; Ferrão, Maria A.G.; Leroy, Thierry; Pot, David; Vieira, Luiz G.E.; da Silva, Felipe R.; Andrade, Alan C.

2012-01-01

The aim of this study was to investigate the molecular mechanisms underlying drought acclimation in coffee plants by the identification of candidate genes (CGs) using different approaches. The first approach used the data generated during the Brazilian Coffee expressed sequence tag (EST) project to select 13 CGs by an in silico analysis (electronic northern). The second approach was based on screening macroarrays spotted with plasmid DNA (coffee ESTs) with separate hybridizations using leaf cDNA probes from drought-tolerant and susceptible clones of Coffea canephora var. Conilon, grown under different water regimes. This allowed the isolation of seven additional CGs. The third approach used two-dimensional gel electrophoresis to identify proteins displaying differential accumulation in leaves of drought-tolerant and susceptible clones of C. canephora. Six of them were characterized by MALDI-TOF-MS/MS (matrix-assisted laser desorption-time of flight-tandem mass spectrometry) and the corresponding proteins were identified. Finally, additional CGs were selected from the literature, and quantitative real-time polymerase chain reaction (qPCR) was performed to analyse the expression of all identified CGs. Altogether, >40 genes presenting differential gene expression during drought acclimation were identified, some of them showing different expression profiles between drought-tolerant and susceptible clones. Based on the obtained results, it can be concluded that factors involved a complex network of responses probably involving the abscisic signalling pathway and nitric oxide are major molecular determinants that might explain the better efficiency in controlling stomata closure and transpiration displayed by drought-tolerant clones of C. canephora. PMID:22511801

miRNome Expression Analysis Reveals New Players on Leprosy Immune Physiopathology

PubMed Central

Salgado, Claudio Guedes; Pinto, Pablo; Bouth, Raquel Carvalho; Gobbo, Angélica Rita; Messias, Ana Caroline Cunha; Sandoval, Tatiana Vinasco; dos Santos, André Mauricio Ribeiro; Moreira, Fabiano Cordeiro; Vidal, Amanda Ferreira; Goulart, Luiz Ricardo; Barreto, Josafá Gonçalves; da Silva, Moisés Batista; Frade, Marco Andrey Cipriani; Spencer, John Stewart; Santos, Sidney; Ribeiro-dos-Santos, Ândrea

2018-01-01

Leprosy remains as a public health problem and its physiopathology is still not fully understood. MicroRNAs (miRNA) are small RNA non-coding that can interfere with mRNA to regulate gene expression. A few studies using DNA chip microarrays have explored the expression of miRNA in leprosy patients using a predetermined set of genes as targets, providing interesting findings regarding the regulation of immune genes. However, using a predetermined set of genes restricted the possibility of finding new miRNAs that might be involved in different mechanisms of disease. Thus, we examined the miRNome of tuberculoid (TT) and lepromatous (LL) patients using both blood and lesional biopsies from classical leprosy patients (LP) who visited the Dr. Marcello Candia Reference Unit in Sanitary Dermatology in the State of Pará and compared them with healthy subjects. Using a set of tools to correlate significantly differentially expressed miRNAs with their gene targets, we identified possible interactions and networks of miRNAs that might be involved in leprosy immunophysiopathology. Using this approach, we showed that the leprosy miRNA profile in blood is distinct from that in lesional skin as well as that four main groups of genes are the targets of leprosy miRNA: (1) recognition and phagocytosis, with activation of immune effector cells, where the immunosuppressant profile of LL and immunoresponsive profile of TT are clearly affected by miRNA expression; (2) apoptosis, with supportive data for an antiapoptotic leprosy profile based on BCL2, MCL1, and CASP8 expression; (3) Schwann cells (SCs), demyelination and epithelial–mesenchymal transition (EMT), supporting a role for different developmental or differentiation gene families, such as Sox, Zeb, and Hox; and (4) loss of sensation and neuropathic pain, revealing that RHOA, ROCK1, SIGMAR1, and aquaporin-1 (AQP1) may be involved in the loss of sensation or leprosy pain, indicating possible new therapeutic targets. Additionally, AQP1 may also be involved in skin dryness and loss of elasticity, which are well known signs of leprosy but with unrecognized physiopathology. In sum, miRNA expression reveals new aspects of leprosy immunophysiopathology, especially on the regulation of the immune system, apoptosis, SC demyelination, EMT, and neuropathic pain. PMID:29593724

miRNome Expression Analysis Reveals New Players on Leprosy Immune Physiopathology.

PubMed

Salgado, Claudio Guedes; Pinto, Pablo; Bouth, Raquel Carvalho; Gobbo, Angélica Rita; Messias, Ana Caroline Cunha; Sandoval, Tatiana Vinasco; Dos Santos, André Mauricio Ribeiro; Moreira, Fabiano Cordeiro; Vidal, Amanda Ferreira; Goulart, Luiz Ricardo; Barreto, Josafá Gonçalves; da Silva, Moisés Batista; Frade, Marco Andrey Cipriani; Spencer, John Stewart; Santos, Sidney; Ribeiro-Dos-Santos, Ândrea

2018-01-01

Leprosy remains as a public health problem and its physiopathology is still not fully understood. MicroRNAs (miRNA) are small RNA non-coding that can interfere with mRNA to regulate gene expression. A few studies using DNA chip microarrays have explored the expression of miRNA in leprosy patients using a predetermined set of genes as targets, providing interesting findings regarding the regulation of immune genes. However, using a predetermined set of genes restricted the possibility of finding new miRNAs that might be involved in different mechanisms of disease. Thus, we examined the miRNome of tuberculoid (TT) and lepromatous (LL) patients using both blood and lesional biopsies from classical leprosy patients (LP) who visited the Dr. Marcello Candia Reference Unit in Sanitary Dermatology in the State of Pará and compared them with healthy subjects. Using a set of tools to correlate significantly differentially expressed miRNAs with their gene targets, we identified possible interactions and networks of miRNAs that might be involved in leprosy immunophysiopathology. Using this approach, we showed that the leprosy miRNA profile in blood is distinct from that in lesional skin as well as that four main groups of genes are the targets of leprosy miRNA: (1) recognition and phagocytosis, with activation of immune effector cells, where the immunosuppressant profile of LL and immunoresponsive profile of TT are clearly affected by miRNA expression; (2) apoptosis, with supportive data for an antiapoptotic leprosy profile based on BCL2, MCL1 , and CASP8 expression; (3) Schwann cells (SCs), demyelination and epithelial-mesenchymal transition (EMT), supporting a role for different developmental or differentiation gene families, such as Sox, Zeb, and Hox; and (4) loss of sensation and neuropathic pain, revealing that RHOA, ROCK1, SIGMAR1 , and aquaporin-1 ( AQP1 ) may be involved in the loss of sensation or leprosy pain, indicating possible new therapeutic targets. Additionally, AQP1 may also be involved in skin dryness and loss of elasticity, which are well known signs of leprosy but with unrecognized physiopathology. In sum, miRNA expression reveals new aspects of leprosy immunophysiopathology, especially on the regulation of the immune system, apoptosis, SC demyelination, EMT, and neuropathic pain.

De novo transcriptome characterization and gene expression profiling of the desiccation tolerant moss Bryum argenteum following rehydration.

PubMed

Gao, Bei; Zhang, Daoyuan; Li, Xiaoshuang; Yang, Honglan; Zhang, Yuanming; Wood, Andrew J

2015-05-28

The desiccation-tolerant moss Bryum argenteum is an important component of the Biological Soil Crusts (BSCs) found in the Gurbantunggut desert. Desiccation tolerance is defined as the ability to revive from the air dried state. To elucidate the molecular mechanisms related to desiccation tolerance, we employed RNA-Seq and digital gene expression (DGE) technologies to study the genome-wide expression profiles of the dehydration and rehydration processes in this important desert plant. We applied a two-step approach to investigate the gene expression profile upon rehydration in the moss Bryum argenteum using Illumina HiSeq2000 sequencing platform. First, a total of 57,247 transcript assembly contigs (TACs) were obtained from 54.79 million reads by de novo assembly, with an average length of 863 bp and N50 of 1,372 bp. Among the reconstructed TACs, 36,916 (64.5%) revealed similarity with existing protein sequences in the public databases. 23,509 and 21,607 TACs were assigned GO and KEGG annotation information, respectively. Second, samples were taken from 3 hydration stages: desiccated (Dry), rehydrated 2 h (R2) and rehydrated 24 h (R24), and DEG libraries were constructed for Differentially Expressed Genes (DEGs) discovery. 4,081 and 6,709 DEGs were identified in R2 and R24, compared with Dry, respectively. Compared to the desiccated sample, up-regulated genes after two hours of hydration are primarily related to stress responses. GO function enrichment network, EKGG metabolic pathway and MapMan analysis supports the idea of the rapid recovery of photosynthesis after 24 h of rehydration. We identified 770 transcription factors (TFs) which were classified into 50 TF families. 142 TF transcripts were up-regulated upon rehydration including 23 members of the ERF family. In this study, we constructed a pioneering, high-quality reference transcriptome in B. argenteum and generated three DGE libraries to elucidate the changes of gene expression upon rehydration. Expression profiles consistent with the rapid recovery of photosynthesis (at R2) and the re-establishment of a positive carbon balance following rehydration (at R24) were observed. Our study will extend our knowledge of bryophyte transcriptomes and provide further insight into the molecular mechanisms related to rehydration and desiccation-tolerance.

How to normalize metatranscriptomic count data for differential expression analysis.

PubMed

Klingenberg, Heiner; Meinicke, Peter

2017-01-01

Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it has not been clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscriptomics. We propose a model for differential expression in metatranscriptomics that explicitly accounts for variations in the taxonomic composition of transcripts across different samples. As a main consequence the correct normalization of metatranscriptomic count data under this model requires the taxonomic separation of the data into organism-specific bins. Then the taxon-specific scaling of organism profiles yields a valid normalization and allows us to recombine the scaled profiles into a metatranscriptomic count matrix. This matrix can then be analyzed with statistical tools for transcriptomic count data. For taxon-specific scaling and recombination of scaled counts we provide a simple R script. When applying transcriptomic tools for differential expression analysis directly to metatranscriptomic data with an organism-independent (global) scaling of counts the resulting differences may be difficult to interpret. The differences may correspond to changing functional profiles of the contributing organisms but may also result from a variation of taxonomic abundances. Taxon-specific scaling eliminates this variation and therefore the resulting differences actually reflect a different behavior of organisms under changing conditions. In simulation studies we show that the divergence between results from global and taxon-specific scaling can be drastic. In particular, the variation of organism abundances can imply a considerable increase of significant differences with global scaling. Also, on real metatranscriptomic data, the predictions from taxon-specific and global scaling can differ widely. Our studies indicate that in real data applications performed with global scaling it might be impossible to distinguish between differential expression in terms of transcriptomic changes and differential composition in terms of changing taxonomic proportions. As in transcriptomics, a proper normalization of count data is also essential for differential expression analysis in metatranscriptomics. Our model implies a taxon-specific scaling of counts for normalization of the data. The application of taxon-specific scaling consequently removes taxonomic composition variations from functional profiles and therefore provides a clear interpretation of the observed functional differences.

Functional Proteomic Profiling of Secreted Serine Proteases in Health and Inflammatory Bowel Disease.

PubMed

Denadai-Souza, Alexandre; Bonnart, Chrystelle; Tapias, Núria Solà; Marcellin, Marlène; Gilmore, Brendan; Alric, Laurent; Bonnet, Delphine; Burlet-Schiltz, Odile; Hollenberg, Morley D; Vergnolle, Nathalie; Deraison, Céline

2018-05-18

While proteases are essential in gastrointestinal physiology, accumulating evidence indicates that dysregulated proteolysis plays a pivotal role in the pathophysiology of inflammatory bowel disease (IBD). Nonetheless, the identity of overactive proteases released by human colonic mucosa remains largely unknown. Studies of protease abundance have primarily investigated expression profiles, not taking into account their enzymatic activity. Herein we have used serine protease-targeted activity-based probes (ABPs) coupled with mass spectral analysis to identify active forms of proteases secreted by the colonic mucosa of healthy controls and IBD patients. Profiling of (Pro-Lys)-ABP bound proteases revealed that most of hyperactive proteases from IBD secretome are clustered at 28-kDa. We identified seven active proteases: the serine proteases cathepsin G, plasma kallikrein, plasmin, tryptase, chymotrypsin-like elastase 3 A, and thrombin and the aminopeptidase B. Only cathepsin G and thrombin were overactive in supernatants from IBD patient tissues compared to healthy controls. Gene expression analysis highlighted the transcription of genes encoding these proteases into intestinal mucosae. The functional ABP-targeted proteomic approach that we have used to identify active proteases in human colonic samples bears directly on the understanding of the role these enzymes may play in the pathophysiology of IBD.

Quantitative confirmation of diffusion-limited oxidation theories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gillen, K.T.; Clough, R.L.

1990-01-01

Diffusion-limited (heterogeneous) oxidation effects are often important for studies of polymer degradation. Such effects are common in polymers subjected to ionizing radiation at relatively high dose rate. To better understand the underlying oxidation processes and to aid in the planning of accelerated aging studies, it would be desirable to be able to monitor and quantitatively understand these effects. In this paper, we briefly review a theoretical diffusion approach which derives model profiles for oxygen surrounded sheets of material by combining oxygen permeation rates with kinetically based oxygen consumption expressions. The theory leads to a simple governing expression involving the oxygenmore » consumption and permeation rates together with two model parameters {alpha} and {beta}. To test the theory, gamma-initiated oxidation of a sheet of commercially formulated EPDM rubber was performed under conditions which led to diffusion-limited oxidation. Profile shapes from the theoretical treatments are shown to accurately fit experimentally derived oxidation profiles. In addition, direct measurements on the same EPDM material of the oxygen consumption and permeation rates, together with values of {alpha} and {beta} derived from the fitting procedure, allow us to quantitatively confirm for the first time the governing theoretical relationship. 17 refs., 3 figs.« less

snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation.

PubMed

Lim, Q E; Zhou, L; Ho, Y K; Wan, G; Too, H P

2011-12-29

Accurate profiling of microRNAs (miRNAs) is an essential step for understanding the functional significance of these small RNAs in both physiological and pathological processes. Quantitative real-time PCR (qPCR) has gained acceptance as a robust and reliable transcriptomic method to profile subtle changes in miRNA levels and requires reference genes for accurate normalization of gene expression. 5S and snoU6 RNAs are commonly used as reference genes in microRNA quantification. It is currently unknown if these small RNAs are stably expressed during neuronal differentiation. Panels of miRNAs have been suggested as alternative reference genes to 5S and snoU6 in various physiological contexts. To test the hypothesis that miRNAs may serve as stable references during neuronal differentiation, the expressions of eight miRNAs, 5S and snoU6 RNAs in five differentiating neuronal cell types were analyzed using qPCR. The stabilities of the expressions were evaluated using two complementary statistical approaches (geNorm and Normfinder). Expressions of 5S and snoU6 RNAs were stable under some but not all conditions of neuronal differentiation and thus are not suitable reference genes. In contrast, a combination of three miRNAs (miR-103, miR-106b and miR-26b) allowed accurate expression normalization across different models of neuronal differentiation. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Proteomic Plasma Membrane Profiling Reveals an Essential Role for gp96 in the Cell Surface Expression of LDLR Family Members, Including the LDL Receptor and LRP6

PubMed Central

2012-01-01

The endoplasmic reticulum chaperone gp96 is required for the cell surface expression of a narrow range of proteins, including toll-like receptors (TLRs) and integrins. To identify a more comprehensive repertoire of proteins whose cell surface expression is dependent on gp96, we developed plasma membrane profiling (PMP), a technique that combines SILAC labeling with selective cell surface aminooxy-biotinylation. This approach allowed us to compare the relative abundance of plasma membrane (PM) proteins on gp96-deficient versus gp96-reconstituted murine pre-B cells. Analysis of unfractionated tryptic peptides initially identified 113 PM proteins, which extended to 706 PM proteins using peptide prefractionation. We confirmed a requirement for gp96 in the cell surface expression of certain TLRs and integrins and found a marked decrease in cell surface expression of four members of the extended LDL receptor family (LDLR, LRP6, Sorl1 and LRP8) in the absence of gp96. Other novel gp96 client proteins included CD180/Ly86, important in the B-cell response to lipopolysaccharide. We highlight common structural motifs in these client proteins that may be recognized by gp96, including the beta-propeller and leucine-rich repeat. This study therefore identifies the extended LDL receptor family as an important new family of proteins whose cell surface expression is regulated by gp96. PMID:22292497

Proteomic plasma membrane profiling reveals an essential role for gp96 in the cell surface expression of LDLR family members, including the LDL receptor and LRP6.

PubMed

Weekes, Michael P; Antrobus, Robin; Talbot, Suzanne; Hör, Simon; Simecek, Nikol; Smith, Duncan L; Bloor, Stuart; Randow, Felix; Lehner, Paul J

2012-03-02

The endoplasmic reticulum chaperone gp96 is required for the cell surface expression of a narrow range of proteins, including toll-like receptors (TLRs) and integrins. To identify a more comprehensive repertoire of proteins whose cell surface expression is dependent on gp96, we developed plasma membrane profiling (PMP), a technique that combines SILAC labeling with selective cell surface aminooxy-biotinylation. This approach allowed us to compare the relative abundance of plasma membrane (PM) proteins on gp96-deficient versus gp96-reconstituted murine pre-B cells. Analysis of unfractionated tryptic peptides initially identified 113 PM proteins, which extended to 706 PM proteins using peptide prefractionation. We confirmed a requirement for gp96 in the cell surface expression of certain TLRs and integrins and found a marked decrease in cell surface expression of four members of the extended LDL receptor family (LDLR, LRP6, Sorl1 and LRP8) in the absence of gp96. Other novel gp96 client proteins included CD180/Ly86, important in the B-cell response to lipopolysaccharide. We highlight common structural motifs in these client proteins that may be recognized by gp96, including the beta-propeller and leucine-rich repeat. This study therefore identifies the extended LDL receptor family as an important new family of proteins whose cell surface expression is regulated by gp96.

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

PubMed

Łabaj, Paweł P; Leparc, Germán G; Linggi, Bryan E; Markillie, Lye Meng; Wiley, H Steven; Kreil, David P

2011-07-01

Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means. We report on a comprehensive study of target identification and measurement precision, including their dependence on transcript expression levels, read depth and other parameters. In particular, an impressive recall of 84% of the estimated true transcript population could be achieved with 331 million 50 bp reads, with diminishing returns from longer read lengths and even less gains from increased sequencing depths. Most of the measurement power (75%) is spent on only 7% of the known transcriptome, however, making less strongly expressed transcripts harder to measure. Consequently, <30% of all transcripts could be quantified reliably with a relative error<20%. Based on established tools, we then introduce a new approach for mapping and analysing sequencing reads that yields substantially improved performance in gene expression profiling, increasing the number of transcripts that can reliably be quantified to over 40%. Extrapolations to higher sequencing depths highlight the need for efficient complementary steps. In discussion we outline possible experimental and computational strategies for further improvements in quantification precision. rnaseq10@boku.ac.at

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

PubMed

Lukashin, A V; Fuchs, R

2001-05-01

Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib

PubMed Central

Bradford, James R.; Farren, Matthew; Powell, Steve J.; Runswick, Sarah; Weston, Susie L.; Brown, Helen; Delpuech, Oona; Wappett, Mark; Smith, Neil R.; Carr, T. Hedley; Dry, Jonathan R.; Gibson, Neil J.; Barry, Simon T.

2013-01-01

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers. PMID:23840389

PROFILES OF GENE EXPRESSION ASSOCIATED WITH TETRACYCLINE OVER EXPRESSION OF HSP70 IN MCF-7 BREAST CANCER CELLS

EPA Science Inventory

Profiles of gene expression associated with tetracycline over expression of HSP70 in MCF-7 breast cancer cells.

Heat shock proteins (HSPs) protect cells from damage through their function as molecular chaperones. Some cancers reveal high levels of HSP70 expression in asso...

Development and application of a comparative fatty acid analysis method to investigate voriconazole-induced hepatotoxicity.

PubMed

Chen, Guan-yuan; Chiu, Huai-hsuan; Lin, Shu-wen; Tseng, Yufeng Jane; Tsai, Sung-jeng; Kuo, Ching-hua

2015-01-01

As fatty acids play an important role in biological regulation, the profiling of fatty acid expression has been used to discover various disease markers and to understand disease mechanisms. This study developed an effective and accurate comparative fatty acid analysis method using differential labeling to speed up the metabolic profiling of fatty acids. Fatty acids were derivatized with unlabeled (D0) or deuterated (D3) methanol, followed by GC-MS analysis. The comparative fatty acid analysis method was validated using a series of samples with different ratios of D0/D3-labeled fatty acid standards and with mouse liver extracts. Using a lipopolysaccharide (LPS)-treated mouse model, we found that the fatty acid profiles after LPS treatment were similar between the conventional single-sample analysis approach and the proposed comparative approach, with a Pearson's correlation coefficient of approximately 0.96. We applied the comparative method to investigate voriconazole-induced hepatotoxicity and revealed the toxicity mechanism as well as the potential of using fatty acids as toxicity markers. In conclusion, the comparative fatty acid profiling technique was determined to be fast and accurate and allowed the discovery of potential fatty acid biomarkers in a more economical and efficient manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Global Analysis of Transcriptome Responses and Gene Expression Profiles to Cold Stress of Jatropha curcas L.

PubMed Central

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Background Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. Results In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. Conclusions This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas. PMID:24349370

Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

PubMed

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas.

miR-30-HNF4γ and miR-194-NR2F2 regulatory networks contribute to the up-regulation of metaplasia markers in the stomach

PubMed Central

Sousa, Josane F.; Nam, Ki Taek; Petersen, Christine P.; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Goldenring, James R.

2016-01-01

Objective Intestinal metaplasia and spasmolytic polypeptide-expressing metaplasia (SPEM) are considered neoplastic precursors of gastric adenocarcinoma and are both marked by gene expression alterations in comparison to normal stomach. Since miRNAs are important regulators of gene expression, we sought to investigate the role of miRNAs on the development of stomach metaplasias. Design We performed miRNA profiling using a qRT-PCR approach on laser capture microdissected human intestinal metaplasia and SPEM. Data integration of the miRNA profile with a previous mRNA profile from the same samples was performed to detect potential miRNA-mRNA regulatory circuits. Transfection of gastric cancer cell lines with selected miRNA mimics and inhibitors was used to evaluate their effects on the expression of putative targets and additional metaplasia markers. Results We identified several genes as potential targets of miRNAs altered during metaplasia progression. We showed evidence that HNF4γ (upregulated in intestinal metaplasia) is targeted by miR-30 and that miR-194 targets a known co-regulator of HNF4 activity, NR2F2 (downregulated in intestinal metaplasia). Intestinal metaplasia markers such as VIL1, TFF2 and TFF3 were down-regulated after overexpression of miR-30a in a HNF4γ-dependent manner. In addition, overexpression of HNF4γ was sufficient to induce the expression of VIL1 and this effect was potentiated by down-regulation of NR2F2. Conclusion The interplay of the two transcription factors HNF4γ and NR2F2 and their coordinate regulation by miR-30 and miR-194, respectively, represent a miRNA to transcription factor network responsible for the expression of intestinal transcripts in stomach cell lineages during the development of intestinal metaplasia. PMID:25800782

First Trimester Pregnancy Loss and the Expression of Alternatively Spliced NKp30 Isoforms in Maternal Blood and Placental Tissue

PubMed Central

Shemesh, Avishai; Tirosh, Dan; Sheiner, Eyal; Benshalom-Tirosh, Neta; Brusilovsky, Michael; Segev, Rotem; Rosental, Benyamin; Porgador, Angel

2015-01-01

Capsule: We observed that first trimester pregnancy loss is associated with an altered expression profile of the three isoforms of the NK receptor NKp30 expressed by NKs in PBMC and placental tissue. In this study, we aimed to investigate whether first trimester pregnancy loss is associated with differences in expression of NKp30 splice variants (isoforms) in maternal peripheral blood or placental tissue. We conducted a prospective case–control study; a total of 33 women undergoing dilation and curettage due to first trimester pregnancy loss were further subdivided into groups with sporadic or recurrent pregnancy loss. The control group comprises women undergoing elective termination of pregnancy. The qPCR approach was employed to assess the relative expression of NKp30 isoforms as well as the total expression of NKp30 and NKp46 receptors between the selected groups. Results show that in both PBMC and placental tissue, NKp46 and NKp30 expressions were mildly elevated in the pregnancy loss groups compared with the elective group. In particular, NKp46 elevation was significant. Moreover, expression analysis of NKp30 isoforms manifested a different profile between PBMC and the placenta. NKp30-a and NKp30-b isoforms in the placental tissue, but not in PBMC, showed a significant increase in the pregnancy loss groups compared with the elective group. Placental expression of NKp30 activating isoforms-a and -b in the pregnancy loss groups was negatively correlated with PLGF expression. By contrast, placental expression of these isoforms in the elective group was positively correlated with TNFα, IL-10, and VEGF-A expression. The altered expression of NKp30 activating isoforms in placental tissue from patients with pregnancy loss compared to the elective group and the different correlations with cytokine expression point to the involvement of NKp30-mediated function in pregnancy loss. PMID:26082773

Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators.

PubMed

Silberstein, Lev; Goncalves, Kevin A; Kharchenko, Peter V; Turcotte, Raphael; Kfoury, Youmna; Mercier, Francois; Baryawno, Ninib; Severe, Nicolas; Bachand, Jacqueline; Spencer, Joel A; Papazian, Ani; Lee, Dongjun; Chitteti, Brahmananda Reddy; Srour, Edward F; Hoggatt, Jonathan; Tate, Tiffany; Lo Celso, Cristina; Ono, Noriaki; Nutt, Stephen; Heino, Jyrki; Sipilä, Kalle; Shioda, Toshihiro; Osawa, Masatake; Lin, Charles P; Hu, Guo-Fu; Scadden, David T

2016-10-06

Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function. Copyright © 2016 Elsevier Inc. All rights reserved.

A Gene Co-Expression Network in Whole Blood of Schizophrenia Patients Is Independent of Antipsychotic-Use and Enriched for Brain-Expressed Genes

PubMed Central

de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

NATbox: a network analysis toolbox in R.

PubMed

Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

2009-10-08

There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments. NATbox is especially suited for interdisciplinary researchers and biologists with minimal programming experience and would like to use systems biology approaches without delving into the algorithmic aspects. The GUI provides appropriate parameter recommendations for the various menu options including default parameter choices for the user. NATbox can also prove to be a useful demonstration and teaching tool in graduate and undergraduate course in systems biology. It has been tested successfully under Windows and Linux operating systems. The source code along with installation instructions and accompanying tutorial can be found at http://bioinformatics.ualr.edu/natboxWiki/index.php/Main_Page.

Integrated analysis of DNA methylation, immunohistochemistry and mRNA expression, data identifies a Methylation Expression Index (MEI) robustly associated with survival of ER-positive breast cancer patients

PubMed Central

Garcia-Closas, Montserrat; Davis, Sean; Meltzer, Paul; Lissowska, Jolanta; Horne, Hisani N.; Sherman, Mark E.; Lee, Maxwell

2015-01-01

Identification of prognostic gene expression signatures may enable improved decisions about management of breast cancer. To identify a prognostic signature for breast cancer, we performed DNA methylation profiling and identified methylation markers that were associated with expression of ER, PR, HER2, CK5/6 and EGFR proteins. Methylation markers that were correlated with corresponding mRNA expression levels were identified using 208 invasive tumors from a population-based case-control study conducted in Poland. Using this approach, we defined the Methylation Expression Index (MEI) signature that was based on a weighted sum of mRNA levels of 57 genes. Classification of cases as low or high MEI scores were related to survival using Cox regression models. In the Polish study, women with ER-positive low MEI cancers had reduced survival at a median of 5.20 years of follow-up, HR=2.85 95%CI=1.25-6.47. Low MEI was also related to decreased survival in four independent datasets totaling over 2500 ER-positive breast cancers. These results suggest that integrated analysis of tumor expression markers, DNA methylation, and mRNA data can be an important approach for identifying breast cancer prognostic signatures. Prospective assessment of MEI along with other prognostic signatures should be evaluated in future studies. PMID:25773928

Identification and expression analysis of cold and freezing stress responsive genes of Brassica oleracea.

PubMed

Ahmed, Nasar Uddin; Jung, Hee-Jeong; Park, Jong-In; Cho, Yong-Gu; Hur, Yoonkang; Nou, Ill-Sup

2015-01-10

Cold and freezing stress is a major environmental constraint to the production of Brassica crops. Enhancement of tolerance by exploiting cold and freezing tolerance related genes offers the most efficient approach to address this problem. Cold-induced transcriptional profiling is a promising approach to the identification of potential genes related to cold and freezing stress tolerance. In this study, 99 highly expressed genes were identified from a whole genome microarray dataset of Brassica rapa. Blast search analysis of the Brassica oleracea database revealed the corresponding homologous genes. To validate their expression, pre-selected cold tolerant and susceptible cabbage lines were analyzed. Out of 99 BoCRGs, 43 were differentially expressed in response to varying degrees of cold and freezing stress in the contrasting cabbage lines. Among the differentially expressed genes, 18 were highly up-regulated in the tolerant lines, which is consistent with their microarray expression. Additionally, 12 BoCRGs were expressed differentially after cold stress treatment in two contrasting cabbage lines, and BoCRG54, 56, 59, 62, 70, 72 and 99 were predicted to be involved in cold regulatory pathways. Taken together, the cold-responsive genes identified in this study provide additional direction for elucidating the regulatory network of low temperature stress tolerance and developing cold and freezing stress resistant Brassica crops. Copyright © 2014 Elsevier B.V. All rights reserved.

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

PubMed

Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi

2016-03-01

Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

Object-location training elicits an overlapping but temporally distinct transcriptional profile from contextual fear conditioning.

PubMed

Poplawski, Shane G; Schoch, Hannah; Wimmer, Mathieu; Hawk, Joshua D; Walsh, Jennifer L; Giese, Karl P; Abel, Ted

2014-12-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Object-Location Training Elicits an Overlapping but Temporally Distinct Transcriptional Profile from Contextual Fear Conditioning

PubMed Central

Wimmer, Mathieu; Hawk, Joshua D.; Walsh, Jennifer L.; Giese, Karl P.; Abel, Ted

2014-01-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. PMID:25242102

Profound Effect of Profiling Platform and Normalization Strategy on Detection of Differentially Expressed MicroRNAs – A Comparative Study

PubMed Central

Meyer, Swanhild U.; Kaiser, Sebastian; Wagner, Carola; Thirion, Christian; Pfaffl, Michael W.

2012-01-01

Background Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms. Methodology/Principal Findings We included data from miRNA profiling analyses derived from a hybridization-based platform (Agilent Technologies) and an RT-qPCR platform (Applied Biosystems). Furthermore, we validated a subset of miRNAs by individual RT-qPCR assays. Our analyses incorporated data from the effect of differentiation and tumor necrosis factor alpha treatment on primary human skeletal muscle cells and a murine skeletal muscle cell line. Distinct normalization methods differed in their impact on (i) standard deviations, (ii) the area under the receiver operating characteristic (ROC) curve, (iii) the similarity of differential expression. Loess, loessM, and quantile analysis were most effective in minimizing standard deviations on the Agilent and TLDA platform. Moreover, loess, loessM, invariant selection and generalized procrustes analysis increased the area under the ROC curve, a measure for the statistical performance of a test. The Jaccard index revealed that inter-platform concordance of differential expression tended to be increased by loess, loessM, quantile, and GPA normalization of AGL and TLDA data as well as RGI normalization of TLDA data. Conclusions/Significance We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments. PMID:22723911

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

PubMed

Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

2014-04-04

Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling and trait-associated transcript analysis using an apple F1 population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available.

Identification of novel serum peptide biomarkers for high-altitude adaptation: a comparative approach

NASA Astrophysics Data System (ADS)

Yang, Juan; Li, Wenhua; Liu, Siyuan; Yuan, Dongya; Guo, Yijiao; Jia, Cheng; Song, Tusheng; Huang, Chen

2016-05-01

We aimed to identify serum biomarkers for screening individuals who could adapt to high-altitude hypoxia at sea level. HHA (high-altitude hypoxia acclimated; n = 48) and HHI (high-altitude hypoxia illness; n = 48) groups were distinguished at high altitude, routine blood tests were performed for both groups at high altitude and at sea level. Serum biomarkers were identified by comparing serum peptidome profiling between HHI and HHA groups collected at sea level. Routine blood tests revealed the concentration of hemoglobin and red blood cells were significantly higher in HHI than in HHA at high altitude. Serum peptidome profiling showed that ten significantly differentially expressed peaks between HHA and HHI at sea level. Three potential serum peptide peaks (m/z values: 1061.91, 1088.33, 4057.63) were further sequence identified as regions of the inter-α trypsin inhibitor heavy chain H4 fragment (ITIH4 347-356), regions of the inter-α trypsin inhibitor heavy chain H1 fragment (ITIH1 205-214), and isoform 1 of fibrinogen α chain precursor (FGA 588-624). Expression of their full proteins was also tested by ELISA in HHA and HHI samples collected at sea level. Our study provided a novel approach for identifying potential biomarkers for screening people at sea level who can adapt to high altitudes.

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

PubMed Central

Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D

2007-01-01

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344

Potential of gene expression profiling in the management of childhood acute lymphoblastic leukemia.

PubMed

Bhojwani, Deepa; Moskowitz, Naomi; Raetz, Elizabeth A; Carroll, William L

2007-01-01

Childhood acute lymphoblastic leukemia (ALL) is a heterogeneous disease. Current treatment approaches are tailored according to the clinical features of the host, genotypic features of the leukemic blast, and early response to therapy. Although these approaches have been successful in dramatically improving outcomes, approximately 20% of children with ALL still relapse and many of these children do not have an identifiable adverse risk factor at presentation. Further insights into the biologic basis of the disease may contribute to novel, rational treatment strategies. Childhood ALL has served as an example for demonstrating the feasibility and potential of high-throughput technologies such as global gene expression or transcript profiling. In the last decade or so, utilization of these techniques has grown exponentially. As the methodology undergoes refinement and validation, it is plausible that microarrays may be used in the routine management of childhood ALL in the next few years. This article discusses the numerous applications to date of gene expression profiling in childhood ALL. Multiple investigators have made it evident that microarrays can be used as a single platform for the accurate classification of ALL into the various cytogenetic subtypes. Additional promising utilities include prediction of early response to therapy, overall outcome, and adverse effects. Identification of patients who are predicted to have an unfavorable outcome may allow for early intervention such as intensification of therapy or avoidance of drugs that are associated with specific secondary effects such as therapy-related acute myelogenous leukemia. Knowledge has been gained into pathways contributing to leukemogenesis and chemoresistance. Therapeutic targets have been identified, some of which are entering clinical trials following validation in additional preclinical models. These newer methods of genome analyses complemented by studies involving the proteome as well as host polymorphisms will have a profound impact on the diagnosis and management of childhood ALL.

Application of community phylogenetic approaches to understand gene expression: differential exploration of venom gene space in predatory marine gastropods.

PubMed

Chang, Dan; Duda, Thomas F

2014-06-05

Predatory marine gastropods of the genus Conus exhibit substantial variation in venom composition both within and among species. Apart from mechanisms associated with extensive turnover of gene families and rapid evolution of genes that encode venom components ('conotoxins'), the evolution of distinct conotoxin expression patterns is an additional source of variation that may drive interspecific differences in the utilization of species' 'venom gene space'. To determine the evolution of expression patterns of venom genes of Conus species, we evaluated the expression of A-superfamily conotoxin genes of a set of closely related Conus species by comparing recovered transcripts of A-superfamily genes that were previously identified from the genomes of these species. We modified community phylogenetics approaches to incorporate phylogenetic history and disparity of genes and their expression profiles to determine patterns of venom gene space utilization. Less than half of the A-superfamily gene repertoire of these species is expressed, and only a few orthologous genes are coexpressed among species. Species exhibit substantially distinct expression strategies, with some expressing sets of closely related loci ('under-dispersed' expression of available genes) while others express sets of more disparate genes ('over-dispersed' expression). In addition, expressed genes show higher dN/dS values than either unexpressed or ancestral genes; this implies that expression exposes genes to selection and facilitates rapid evolution of these genes. Few recent lineage-specific gene duplicates are expressed simultaneously, suggesting that expression divergence among redundant gene copies may be established shortly after gene duplication. Our study demonstrates that venom gene space is explored differentially by Conus species, a process that effectively permits the independent and rapid evolution of venoms in these species.

Proteomic analysis on the alteration of protein expression in the early-stage placental villous tissue of electromagnetic fields associated with cell phone exposure.

PubMed

Luo, Qiong; Jiang, Ying; Jin, Min; Xu, Jian; Huang, He-Feng

2013-09-01

To explore the possible adverse effects and search for cell phone electromagnetic field (EMF)-responsive proteins in human early reproduction, a proteomics approach was employed to investigate the changes in protein expression profile induced by cell phone EMF in human chorionic tissues of early pregnancy in vivo. Volunteer women about 50 days pregnant were exposed to EMF at the average absorption rate of 1.6 to 8.8 W/kg for 1 hour with the irradiation device placed 10 cm away from the umbilicus at the midline of the abdomen. The changes in protein profile were examined using 2-dimensional electrophoresis (2-DE). Up to 15 spots have yielded significant change at least 2- to 2.5-folds up or down compared to sham-exposed group. Twelve proteins were identified- procollagen-proline, eukaryotic translation elongation factor 1 delta, chain D crystal structure of human vitamin D-binding protein, thioredoxin-like 3, capping protein, isocitrate dehydrogenase 3 alpha, calumenin, Catechol-O-methyltransferase protein, proteinase inhibitor 6 (PI-6; SerpinB6) protein, 3,2-trans-enoyl-CoA isomerase protein, chain B human erythrocyte 2,3-bisphosphoglycerate mutase, and nucleoprotein. Cell phone EMF might alter the protein profile of chorionic tissue of early pregnancy, during the most sensitive stage of the embryos. The exposure to EMF may cause adverse effects on cell proliferation and development of nervous system in early embryos. Furthermore, 2-DE coupled with mass spectrometry is a promising approach to elucidate the effects and search for new biomarkers for environmental toxic effects.

Recapitulation of Tumor Heterogeneity and Molecular Signatures in a 3D Brain Cancer Model with Decreased Sensitivity to Histone Deacetylase Inhibition

PubMed Central

Smith, Stuart J.; Wilson, Martin; Ward, Jennifer H.; Rahman, Cheryl V.; Peet, Andrew C.; Macarthur, Donald C.; Rose, Felicity R. A. J.; Grundy, Richard G.; Rahman, Ruman

2012-01-01

Introduction Physiologically relevant pre-clinical ex vivo models recapitulating CNS tumor micro-environmental complexity will aid development of biologically-targeted agents. We present comprehensive characterization of tumor aggregates generated using the 3D Rotary Cell Culture System (RCCS). Methods CNS cancer cell lines were grown in conventional 2D cultures and the RCCS and comparison with a cohort of 53 pediatric high grade gliomas conducted by genome wide gene expression and microRNA arrays, coupled with immunohistochemistry, ex vivo magnetic resonance spectroscopy and drug sensitivity evaluation using the histone deacetylase inhibitor, Vorinostat. Results Macroscopic RCCS aggregates recapitulated the heterogeneous morphology of brain tumors with a distinct proliferating rim, necrotic core and oxygen tension gradient. Gene expression and microRNA analyses revealed significant differences with 3D expression intermediate to 2D cultures and primary brain tumors. Metabolic profiling revealed differential profiles, with an increase in tumor specific metabolites in 3D. To evaluate the potential of the RCCS as a drug testing tool, we determined the efficacy of Vorinostat against aggregates of U87 and KNS42 glioblastoma cells. Both lines demonstrated markedly reduced sensitivity when assaying in 3D culture conditions compared to classical 2D drug screen approaches. Conclusions Our comprehensive characterization demonstrates that 3D RCCS culture of high grade brain tumor cells has profound effects on the genetic, epigenetic and metabolic profiles of cultured cells, with these cells residing as an intermediate phenotype between that of 2D cultures and primary tumors. There is a discrepancy between 2D culture and tumor molecular profiles, and RCCS partially re-capitulates tissue specific features, allowing drug testing in a more relevant ex vivo system. PMID:23272238

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Ion channel profile of TRPM8 cold receptors reveals a novel role of TASK-3 potassium channels in thermosensation

PubMed Central

Morenilla-Palao, Cruz; Luis, Enoch; Fernández-Peña, Carlos; Quintero, Eva; Weaver, Janelle L.; Bayliss, Douglas A.; Viana, Félix

2017-01-01

Summary Animals sense cold ambient temperatures through the activation of peripheral thermoreceptors that express TRPM8, a cold- and menthol-activated ion channel. These receptors can discriminate a very wide range of temperatures from innocuous to noxious. The molecular mechanism responsible for the variable sensitivity of individual cold receptors to temperature is unclear. To address this question, we performed a detailed ion channel expression analysis of cold sensitive neurons, combining BAC transgenesis with a molecular profiling approach in FACS purified TRPM8 neurons. We found that TASK-3 leak potassium channels are highly enriched in a subpopulation of these sensory neurons. The thermal threshold of TRPM8 cold neurons is decreased during TASK-3 blockade and in mice lacking TASK-3 and, most importantly, these mice display hypersensitivity to cold. Our results demonstrate a novel role of TASK-3 channels in thermosensation, showing that a channel-based combinatorial strategy in TRPM8 cold thermoreceptors leads to molecular specialization and functional diversity. PMID:25199828

Phage phenomics: Physiological approaches to characterize novel viral proteins

ScienceCinema

Sanchez, Savannah E. [San Diego State Univ., San Diego, CA (United States); Cuevas, Daniel A. [San Diego State Univ., San Diego, CA (United States); Rostron, Jason E. [San Diego State Univ., San Diego, CA (United States); Liang, Tiffany Y. [San Diego State Univ., San Diego, CA (United States); Pivaroff, Cullen G. [San Diego State Univ., San Diego, CA (United States); Haynes, Matthew R. [San Diego State Univ., San Diego, CA (United States); Nulton, Jim [San Diego State Univ., San Diego, CA (United States); Felts, Ben [San Diego State Univ., San Diego, CA (United States); Bailey, Barbara A. [San Diego State Univ., San Diego, CA (United States); Salamon, Peter [San Diego State Univ., San Diego, CA (United States); Edwards, Robert A. [San Diego State Univ., San Diego, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Burgin, Alex B. [Broad Institute, Cambridge, MA (United States); Segall, Anca M. [San Diego State Univ., San Diego, CA (United States); Rohwer, Forest [San Diego State Univ., San Diego, CA (United States)

2018-06-21

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Inhibition of Super-Enhancer Activity in Autoinflammatory Site-Derived T Cells Reduces Disease-Associated Gene Expression.

PubMed

Peeters, Janneke G C; Vervoort, Stephin J; Tan, Sander C; Mijnheer, Gerdien; de Roock, Sytze; Vastert, Sebastiaan J; Nieuwenhuis, Edward E S; van Wijk, Femke; Prakken, Berent J; Creyghton, Menno P; Coffer, Paul J; Mokry, Michal; van Loosdregt, Jorg

2015-09-29

The underlying molecular mechanisms for many autoimmune diseases are poorly understood. Juvenile idiopathic arthritis (JIA) is an exceptionally well-suited model for studying autoimmune diseases due to its early onset and the possibility to analyze cells derived from the site of inflammation. Epigenetic profiling, utilizing primary JIA patient-derived cells, can contribute to the understanding of autoimmune diseases. With H3K27ac chromatin immunoprecipitation, we identified a disease-specific, inflammation-associated, typical enhancer and super-enhancer signature in JIA patient synovial-fluid-derived CD4(+) memory/effector T cells. RNA sequencing of autoinflammatory site-derived patient T cells revealed that BET inhibition, utilizing JQ1, inhibited immune-related super-enhancers and preferentially reduced disease-associated gene expression, including cytokine-related processes. Altogether, these results demonstrate the potential use of enhancer profiling to identify disease mediators and provide evidence for BET inhibition as a possible therapeutic approach for the treatment of autoimmune diseases. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Chitin enhances biocontrol of Rhodotorula mucilaginosa to postharvest decay of peaches.

PubMed

Zhang, Hongyin; Yang, Qiya; Ge, Lingling; Zhang, Guochao; Zhang, Xiaoli; Zhang, Xiaoyun

2016-07-01

Biological control using microbial antagonists is a promising alternative approach to synthetic fungicides. However, effective biological control requires enhancing the consistency and efficacy of the antagonists used to control postharvest diseases. This study investigated the effect of chitin on the biocontrol efficacy of Rhodotorula mucilaginosa against blue mold and Rhizopus decay of peaches and on the protein expression profiles of R. mucilaginosa. The antagonistic activity of R. mucilaginosa harvested from the nutrient yeast dextrose broth (NYDB) with 0.5% chitin added was significantly improved compared with culture in NYDB without chitin. The R. mucilaginosa population cultured in chitin-supplement NYDB and nutrient yeast chitin borth (NYCB) harvested from peach wounds was more than that of R. mucilaginosa cultured in NYDB without chitin throughout the storage period except at 1 d. The protein expression profiles findings revealed that there were several differentially expressed proteins of R. mucilaginosa in the 0.5% chitin-supplemented NYDB and NYCB compared with that of R. mucilaginosa in NYDB. Most of these were cellular proteomes relating to the primary metabolic reactions such as glycoside hydrolases, phosphoribosyl pyrophosphate, and NADH dehydrogenases. Some proteins were also related to signal transmission and stress response. Copyright © 2016 Elsevier B.V. All rights reserved.

Shotgun proteomic monitoring of Clostridium acetobutylicum during stationary phase of butanol fermentation using xylose and comparison with the exponential phase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sivagnanam, Kumaran; Raghavan, Vijaya G. S.; Shah, Manesh B

2012-01-01

Economically viable production of solvents through acetone butanol ethanol (ABE) fermentation requires a detailed understanding of Clostridium acetobutylicum. This study focuses on the proteomic profiling of C. acetobutylicum ATCC 824 from the stationary phase of ABE fermentation using xylose and compares with the exponential growth by shotgun proteomics approach. Comparative proteomic analysis revealed 22.9% of the C. acetobutylicum genome and 18.6% was found to be common in both exponential and stationary phases. The proteomic profile of C. acetobutylicum changed during the ABE fermentation such that 17 proteins were significantly differentially expressed between the two phases. Specifically, the expression of fivemore » proteins namely, CAC2873, CAP0164, CAP0165, CAC3298, and CAC1742 involved in the solvent production pathway were found to be significantly lower in the stationary phase compared to the exponential growth. Similarly, the expression of fucose isomerase (CAC2610), xylulose kinase (CAC2612), and a putative uncharacterized protein (CAC2611) involved in the xylose utilization pathway were also significantly lower in the stationary phase. These findings provide an insight into the metabolic behavior of C. acetobutylicum between different phases of ABE fermentation using xylose.« less

Transcriptome profiling of sleeping, waking, and sleep deprived adult heterozygous Aldh1L1 - eGFP-L10a mice.

PubMed

Bellesi, Michele; de Vivo, Luisa; Tononi, Giulio; Cirelli, Chiara

2015-12-01

Transcriptomic studies revealed that hundreds of mRNAs show differential expression in the brains of sleeping relative to awake rats, mice, flies, and sparrows. Although these results have offered clues regarding the molecular consequences of sleep and sleep loss, their functional significance thus far has been limited. This is probably because the previous studies pooled transcripts from all brain cells, including neurons and glia. In Bellesi et al. 2015 [1], we used the translating ribosome affinity purification technology (TRAP) and microarray analysis to obtain a genome-wide mRNA profiling of astrocytes as a function of sleep and wake. We used bacterial artificial chromosome (BAC) transgenic mice expressing eGFP tagged ribosomal protein L10a under the promoter of the Aldh1L1 gene, a highly expressed astrocytic gene. Using this approach, we could extract only the astrocytic mRNAs, and only those already committed to be translated into proteins (L10a is part of the translational machinery). Here, we report a detailed description of the protocol used in the study [1]. Array data have been submitted to NCBI GEO under accession number (GSE69079).

Gene expression profiling provides insights into the immune mechanism of Plutella xylostella midgut to microbial infection.

PubMed

Lin, Junhan; Xia, Xiaofeng; Yu, Xiao-Qiang; Shen, Jinhong; Li, Yong; Lin, Hailan; Tang, Shanshan; Vasseur, Liette; You, Minsheng

2018-03-20

Insect gut immunity plays a key role in defense against microorganism infection. The knowledge of insect gut immunity has been obtained mostly from Drosophila melanogaster. Little is known about gut immunity in the diamondback moth, Plutella xylostella (L.), a pest destroying cruciferous crops worldwide. In this study, expressions of the immune-related genes in the midgut of P. xylostella orally infected with Staphylococcus aureus, Escherichia coli and Pichia pastoris were profiled by RNA-seq and qRT-PCR approaches. The results revealed that the Toll, IMD, JNK and JAK-STAT pathways and possibly the prophenoloxidase activation system in P. xylostella could be activated by oral infections, and moricins, gloverins and lysozyme2 might act as important effectors against microorganisms. Subsequent knock-down of IMD showed that this gene was involved in regulating the expression of down-stream genes in the IMD pathway. Our work indicates that the Toll, IMD, JNK and JAK-STAT pathways may synergistically modulate immune responses in the P. xylostella midgut, implying a complex and diverse immune system in the midgut of insects. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

Analysis of gene expression in single live neurons.

PubMed Central

Eberwine, J; Yeh, H; Miyashiro, K; Cao, Y; Nair, S; Finnell, R; Zettel, M; Coleman, P

1992-01-01

We present here a method for broadly characterizing single cells at the molecular level beyond the more common morphological and transmitter/receptor classifications. The RNA from defined single cells is amplified by microinjecting primer, nucleotides, and enzyme into acutely dissociated cells from a defined region of rat brain. Further processing yields amplified antisense RNA. A second round of amplification results in greater than 10(6)-fold amplification of the original starting material, which is adequate for analysis--e.g., use as a probe, making of cDNA libraries, etc. We demonstrate this method by constructing expression profiles of single live cells from rat hippocampus. This profiling suggests that cells that appear to be morphologically similar may show marked differences in patterns of expression. In addition, we characterize several mRNAs from a single cell, some of which were previously undescribed, perhaps due to "rarity" when averaged over many cell types. Electrophysiological analysis coupled with molecular biology within the same cell will facilitate a better understanding of how changes at the molecular level are manifested in functional properties. This approach should be applicable to a wide variety of studies, including development, mutant models, aging, and neurodegenerative disease. Images PMID:1557406

Gene expression profiles in liver of mouse after chronic exposure to drinking water.

PubMed

Wu, Bing; Zhang, Yan; Zhao, Dayong; Zhang, Xuxiang; Kong, Zhiming; Cheng, Shupei

2009-10-01

cDNA micorarray approach was applied to hepatic transcriptional profile analysis in male mouse (Mus musculus, ICR) to assess the potential health effects of drinking water in Nanjing, China. Mice were treated with continuous exposure to drinking water for 90 days. Hepatic gene expression was analyzed with Affymetrix Mouse Genome 430A 2.0 arrays, and pathway analysis was carried out by Molecule Annotation System 2.0 and KEGG pathway database. A total of 836 genes were found to be significantly altered (1.5-fold, P < or = 0.05), including 294 up-regulated genes and 542 down-regulated genes. According to biological pathway analysis, drinking water exposure resulted in aberration of gene expression and biological pathways linked to xenobiotic metabolism, signal transduction, cell cycle and oxidative stress response. Further, deregulation of several genes associated with carcinogenesis or tumor progression including Ccnd1, Egfr, Map2k3, Mcm2, Orc2l and Smad2 was observed. Although transcription changes in identified genes are unlikely to be used as a sole indicator of adverse health effects, the results of this study could enhance our understanding of early toxic effects of drinking water exposure and support future studies on drinking water safety.

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

PubMed

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

GENE EXPRESSION PROFILES IN ARSENIC-TREATED MCF-7 BREAST CANCER CELLS EXPRESSING DIFFERENT LEVELS OF HSP70

EPA Science Inventory

Gene expression profiles in arsenic-treated MCF-7 breast cancer cells expressing different levels of HSP70

Gail Nelson, Susan Hester, Ernest Winkfield, Jill Barnes, James Allen
Environmental Carcinogenesis Division, NHEERL, ORD, US Environmental Protection Agency, Rese...

Heterogeneity of circulating epithelial tumour cells from individual patients with respect to expression profiles and clonal growth (sphere formation) in breast cancer.

PubMed

Pizon, M; Zimon, D; Carl, S; Pachmann, U; Pachmann, K; Camara, O

2013-01-01

The detection of tumour cells circulating in the peripheral blood of patients with breast cancer is a sign that cells have been able to leave the primary tumour and survive in the circulation. However, in order to form metastases, they require additional properties such as the ability to adhere, self-renew, and grow. Here we present data that a variable fraction among the circulating tumour cells detected by the Maintrac(®) approach expresses mRNA of the stem cell gene NANOG and of the adhesion molecule vimentin and is capable of forming tumour spheres, a property ascribed to tumour-initiating cells (TICs). Between ten and 50 circulating epithelial antigen-positive cells detected by the Maintrac approach were selected randomly from each of 20 patients with breast cancer before and after surgery and were isolated using automated capillary aspiration and deposited individually onto slides for expression profiling. In addition, the circulating tumour cells were cultured without isolation among the white blood cells from 39 patients with breast cancer in different stages of disease using culture methods favouring growth of epithelial cells. Although no epithelial cell adhesion molecule (EpCAM)-positive cells expressing stem cell genes or the adhesion molecule vimentin was detected before surgery, 10%-20% of the cells were found to be positive for mRNA of these genes after surgery. Tumour spheres from circulating cells of 39 patients with different stages of breast cancer were grown without previous isolation in a fraction increasing with the aggressivity of the tumour. Here we show that among the peripherally circulating tumour cells, a variable fraction is able to express stem cell and adhesion properties and can be grown into tumour spheres, a property ascribed to cells capable of initiating tumours and metastases.

Selection and assessment of reference genes for quantitative PCR normalization in migratory locust Locusta migratoria (Orthoptera: Acrididae).

PubMed

Yang, Qingpo; Li, Zhen; Cao, Jinjun; Zhang, Songdou; Zhang, Huaijiang; Wu, Xiaoyun; Zhang, Qingwen; Liu, Xiaoxia

2014-01-01

Locusta migratoria is a classic hemimetamorphosis insect and has caused widespread economic damage to crops as a migratory pest. Researches on the expression pattern of functional genes in L. migratoria have drawn focus in recent years, especially with the release of genome information. Real-time quantitative PCR is the most reproducible and sensitive approach for detecting transcript expression levels of target genes, but optimal internal standards are key factors for its accuracy and reliability. Therefore, it's necessary to provide a systematic stability assessment of internal control for well-performed tests of target gene expression profile. In this study, twelve candidate genes (Ach, Act, Cht2, EF1α, RPL32, Hsp70, Tub, RP49, SDH, GAPDH, 18S, and His) were analyzed with four statistical methods: the delta Ct approach, geNorm, Bestkeeper and NormFinder. The results from these analyses aimed to choose the best suitable reference gene across different experimental situations for gene profile study in L. migratoria. The result demonstrated that for different developmental stages, EF1α, Hsp70 and RPL32 exhibited the most stable expression status for all samples; EF1α and RPL32 were selected as the best reference genes for studies involving embryo and larvae stages, while SDH and RP49 were identified for adult stage. The best-ranked reference genes across different tissues are RPL32, Hsp70 and RP49. For abiotic treatments, the most appropriate genes we identified were as follows: Act and SDH for larvae subjected to different insecticides; RPL32 and Ach for larvae exposed to different temperature treatments; and Act and Ach for larvae suffering from starvation. The present report should facilitate future researches on gene expression in L. migratoria with accessibly optimal reference genes under different experimental contexts.

iPcc: a novel feature extraction method for accurate disease class discovery and prediction

PubMed Central

Ren, Xianwen; Wang, Yong; Zhang, Xiang-Sun; Jin, Qi

2013-01-01

Gene expression profiling has gradually become a routine procedure for disease diagnosis and classification. In the past decade, many computational methods have been proposed, resulting in great improvements on various levels, including feature selection and algorithms for classification and clustering. In this study, we present iPcc, a novel method from the feature extraction perspective to further propel gene expression profiling technologies from bench to bedside. We define ‘correlation feature space’ for samples based on the gene expression profiles by iterative employment of Pearson’s correlation coefficient. Numerical experiments on both simulated and real gene expression data sets demonstrate that iPcc can greatly highlight the latent patterns underlying noisy gene expression data and thus greatly improve the robustness and accuracy of the algorithms currently available for disease diagnosis and classification based on gene expression profiles. PMID:23761440

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

PubMed Central

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

PubMed

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Validation of reference genes aiming accurate normalization of qRT-PCR data in Dendrocalamus latiflorus Munro.

PubMed

Liu, Mingying; Jiang, Jing; Han, Xiaojiao; Qiao, Guirong; Zhuo, Renying

2014-01-01

Dendrocalamus latiflorus Munro distributes widely in subtropical areas and plays vital roles as valuable natural resources. The transcriptome sequencing for D. latiflorus Munro has been performed and numerous genes especially those predicted to be unique to D. latiflorus Munro were revealed. qRT-PCR has become a feasible approach to uncover gene expression profiling, and the accuracy and reliability of the results obtained depends upon the proper selection of stable reference genes for accurate normalization. Therefore, a set of suitable internal controls should be validated for D. latiflorus Munro. In this report, twelve candidate reference genes were selected and the assessment of gene expression stability was performed in ten tissue samples and four leaf samples from seedlings and anther-regenerated plants of different ploidy. The PCR amplification efficiency was estimated, and the candidate genes were ranked according to their expression stability using three software packages: geNorm, NormFinder and Bestkeeper. GAPDH and EF1α were characterized to be the most stable genes among different tissues or in all the sample pools, while CYP showed low expression stability. RPL3 had the optimal performance among four leaf samples. The application of verified reference genes was illustrated by analyzing ferritin and laccase expression profiles among different experimental sets. The analysis revealed the biological variation in ferritin and laccase transcript expression among the tissues studied and the individual plants. geNorm, NormFinder, and BestKeeper analyses recommended different suitable reference gene(s) for normalization according to the experimental sets. GAPDH and EF1α had the highest expression stability across different tissues and RPL3 for the other sample set. This study emphasizes the importance of validating superior reference genes for qRT-PCR analysis to accurately normalize gene expression of D. latiflorus Munro.

Pan-Cancer Analysis of the Mediator Complex Transcriptome Identifies CDK19 and CDK8 as Therapeutic Targets in Advanced Prostate Cancer.

PubMed

Brägelmann, Johannes; Klümper, Niklas; Offermann, Anne; von Mässenhausen, Anne; Böhm, Diana; Deng, Mario; Queisser, Angela; Sanders, Christine; Syring, Isabella; Merseburger, Axel S; Vogel, Wenzel; Sievers, Elisabeth; Vlasic, Ignacija; Carlsson, Jessica; Andrén, Ove; Brossart, Peter; Duensing, Stefan; Svensson, Maria A; Shaikhibrahim, Zaki; Kirfel, Jutta; Perner, Sven

2017-04-01

Purpose: The Mediator complex is a multiprotein assembly, which serves as a hub for diverse signaling pathways to regulate gene expression. Because gene expression is frequently altered in cancer, a systematic understanding of the Mediator complex in malignancies could foster the development of novel targeted therapeutic approaches. Experimental Design: We performed a systematic deconvolution of the Mediator subunit expression profiles across 23 cancer entities ( n = 8,568) using data from The Cancer Genome Atlas (TCGA). Prostate cancer-specific findings were validated in two publicly available gene expression cohorts and a large cohort of primary and advanced prostate cancer ( n = 622) stained by immunohistochemistry. The role of CDK19 and CDK8 was evaluated by siRNA-mediated gene knockdown and inhibitor treatment in prostate cancer cell lines with functional assays and gene expression analysis by RNAseq. Results: Cluster analysis of TCGA expression data segregated tumor entities, indicating tumor-type-specific Mediator complex compositions. Only prostate cancer was marked by high expression of CDK19 In primary prostate cancer, CDK19 was associated with increased aggressiveness and shorter disease-free survival. During cancer progression, highest levels of CDK19 and of its paralog CDK8 were present in metastases. In vitro , inhibition of CDK19 and CDK8 by knockdown or treatment with a selective CDK8/CDK19 inhibitor significantly decreased migration and invasion. Conclusions: Our analysis revealed distinct transcriptional expression profiles of the Mediator complex across cancer entities indicating differential modes of transcriptional regulation. Moreover, it identified CDK19 and CDK8 to be specifically overexpressed during prostate cancer progression, highlighting their potential as novel therapeutic targets in advanced prostate cancer. Clin Cancer Res; 23(7); 1829-40. ©2016 AACR . ©2016 American Association for Cancer Research.

Unraveling the oral cancer lncRNAome: Identification of novel lncRNAs associated with malignant progression and HPV infection.

PubMed

Nohata, Nijiro; Abba, Martin C; Gutkind, J Silvio

2016-08-01

The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, we aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival. The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed. Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, we found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, we found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), we found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC. LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Unraveling the Oral Cancer lncRNAome: Identification of Novel lncRNAs Associated with Malignant Progression and HPV Infection

PubMed Central

Nohata, Nijiro; Abba, Martin C.; Gutkind, J. Silvio

2017-01-01

Objectives The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, we aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival. Materials and Methods The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed. Results Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, we found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, we found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), we found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC. Conclusion LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis. PMID:27424183

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

Metabolic Engineering for Probiotics and their Genome-Wide Expression Profiling.

PubMed

Yadav, Ruby; Singh, Puneet K; Shukla, Pratyoosh

2018-01-01

Probiotic supplements in food industry have attracted a lot of attention and shown a remarkable growth in this field. Metabolic engineering (ME) approaches enable understanding their mechanism of action and increases possibility of designing probiotic strains with desired functions. Probiotic microorganisms generally referred as industrially important lactic acid bacteria (LAB) which are involved in fermenting dairy products, food, beverages and produces lactic acid as final product. A number of illustrations of metabolic engineering approaches in industrial probiotic bacteria have been described in this review including transcriptomic studies of Lactobacillus reuteri and improvement in exopolysaccharide (EPS) biosynthesis yield in Lactobacillus casei LC2W. This review summaries various metabolic engineering approaches for exploring metabolic pathways. These approaches enable evaluation of cellular metabolic state and effective editing of microbial genome or introduction of novel enzymes to redirect the carbon fluxes. In addition, various system biology tools such as in silico design commonly used for improving strain performance is also discussed. Finally, we discuss the integration of metabolic engineering and genome profiling which offers a new way to explore metabolic interactions, fluxomics and probiogenomics using probiotic bacteria like Bifidobacterium spp and Lactobacillus spp. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Existence of Inverted Profile in Chemically Responsive Molecular Pathways in the Zebrafish Liver

PubMed Central

Zhang, Xun; Li, Hu; Ma, Jing; Zhang, Louxin; Li, Baowen; Gong, Zhiyuan

2011-01-01

How a living organism maintains its healthy equilibrium in response to endless exposure of potentially harmful chemicals is an important question in current biology. By transcriptomic analysis of zebrafish livers treated by various chemicals, we defined hubs as molecular pathways that are frequently perturbed by chemicals and have high degree of functional connectivity to other pathways. Our network analysis revealed that these hubs were organized into two groups showing inverted functionality with each other. Intriguingly, the inverted activity profiles in these two groups of hubs were observed to associate only with toxicopathological states but not with physiological changes. Furthermore, these inverted profiles were also present in rat, mouse, and human under certain toxicopathological conditions. Thus, toxicopathological-associated anti-correlated profiles in hubs not only indicate their potential use in diagnosis but also development of systems-based therapeutics to modulate gene expression by chemical approach in order to rewire the deregulated activities of hubs back to normal physiology. PMID:22140468

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications

PubMed Central

Harris, R. Alan; Wang, Ting; Coarfa, Cristian; Nagarajan, Raman P.; Hong, Chibo; Downey, Sara L.; Johnson, Brett E.; Fouse, Shaun D.; Delaney, Allen; Zhao, Yongjun; Olshen, Adam; Ballinger, Tracy; Zhou, Xin; Forsberg, Kevin J.; Gu, Junchen; Echipare, Lorigail; O’Geen, Henriette; Lister, Ryan; Pelizzola, Mattia; Xi, Yuanxin; Epstein, Charles B.; Bernstein, Bradley E.; Hawkins, R. David; Ren, Bing; Chung, Wen-Yu; Gu, Hongcang; Bock, Christoph; Gnirke, Andreas; Zhang, Michael Q.; Haussler, David; Ecker, Joseph; Li, Wei; Farnham, Peggy J.; Waterland, Robert A.; Meissner, Alexander; Marra, Marco A.; Hirst, Martin; Milosavljevic, Aleksandar; Costello, Joseph F.

2010-01-01

Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression. PMID:20852635

Arginine and Polyamines Fate in Leishmania Infection

PubMed Central

Muxel, Sandra M.; Aoki, Juliana I.; Fernandes, Juliane C. R.; Laranjeira-Silva, Maria F.; Zampieri, Ricardo A.; Acuña, Stephanie M.; Müller, Karl E.; Vanderlinde, Rubia H.; Floeter-Winter, Lucile M.

2018-01-01

Leishmania is a protozoan parasite that alternates its life cycle between the sand fly and the mammalian host macrophages, involving several environmental changes. The parasite responds to these changes by promoting a rapid metabolic adaptation through cellular signaling modifications that lead to transcriptional and post-transcriptional gene expression regulation and morphological modifications. Molecular approaches such as gene expression regulation, next-generation sequencing (NGS), microRNA (miRNA) expression profiling, in cell Western blot analyses and enzymatic activity profiling, have been used to characterize the infection of murine BALB/c and C57BL/6 macrophages, as well as the human monocytic cell-lineage THP-1, with Leishmania amazonensis wild type (La-WT) or arginase knockout (La-arg-). These models are being used to elucidate physiological roles of arginine and polyamines pathways and the importance of arginase for the establishment of the infection. In this review, we will describe the main aspects of Leishmania-host interaction, focusing on the arginine and polyamines pathways and pointing to possible targets to be used for prognosis and/or in the control of the infection. The parasite enzymes, arginase and nitric oxide synthase-like, have essential roles in the parasite survival and in the maintenance of infection. On the other hand, in mammalian macrophages, defense mechanisms are activated inducing alterations in the mRNA, miRNA and enzymatic profiles that lead to the control of infection. Furthermore, the genetic background of both parasite and host are also important to define the fate of infection. PMID:29379478

The differential metabolite profiles of acute lymphoblastic leukaemic patients treated with 6-mercaptopurine using untargeted metabolomics approach.

PubMed

Bannur, Z; Teh, L K; Hennesy, T; Rosli, W R W; Mohamad, N; Nasir, A; Ankathil, R; Zakaria, Z A; Baba, A; Salleh, M Z

2014-04-01

Acute lymphoblastic leukaemia (ALL) has posed challenges to the clinician due to variable patients' responses and late diagnosis. With the advance in metabolomics, early detection and personalised treatment are possible. Metabolomic profile of 21 ALL patients treated with 6-mercaptopurine and 10 healthy volunteers were analysed using liquid chromatography/mass spectrometry quadrupole-time of flight (LC/MS Q-TOF). Principal components analysis (PCA), recursive analysis, clustering and pathway analysis were performed using MassHunter Qualitative and Mass Profiler Professional (MPP) software. Several metabolites were found to be expressed differently in patients treated with 6-mercaptopurine. Interestingly, 13 metabolites were significantly differently expressed [p-value <0.01 (unpaired t-test) and 2-fold change] in 19% of the patients who had relapses in their treatment. Down-regulated metabolites in relapsed patients were 1-tetrahexanoyl-2-(8-[3]-ladderane-octanyl)-sn-GPEtn, GPEtn (18:1(9Z)/0:0), GPCho(O-6:0/O-6:0), GPCho(O-2:0/O-1:0), methyl 8-[2-(2-formyl-vinyl)-3-hydroxy-5-oxo-cyclopentyl]-octanoate and plasma free amino acids (PFAA). Characterizing the subjects according to their ITPA 94C>A genotypes reveal differential expression of metabolites. Our research contributes to identification of metabolites that could be used to monitor disease progress of patients and allow targeted therapy for ALL at different stages, especially in preventing complication of relapse. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Ma, Zihao; Carr, Steven A.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC).more » Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. Molecular & Cellular Proteomics 16: 10.1074/mcp.M116.060301, 121–134, 2017.« less

Dysregulation of miRNAs in bladder cancer: altered expression with aberrant biogenesis procedure

PubMed Central

Dong, Fan; Xu, Tianyuan; Shen, Yifan; Zhong, Shan; Chen, Shanwen; Ding, Qiang; Shen, Zhoujun

2017-01-01

Aberrant expression profiles of miRNAs are widely observed in the clinical tissue specimens and urine samples as well as the blood samples of bladder cancer patients. These profiles are closely related to the pathological features of bladder cancer, such as the tumour stage/grade, metastasis, recurrence and chemo-sensitivity. MiRNA biogenesis forms the basis of miRNA expression and function, and its dysregulation has been shown to be essential for variations in miRNA expression profiles as well as tumourigenesis and cancer progression. In this review, we summarize the up-to-date and widely reported miRNAs in bladder cancer that display significantly altered expression. We then compare the miRNA expression profiles among three different sample types (tissue, urine and blood) from patients with bladder cancer. Moreover, for the first time, we outline the dysregulated miRNA biogenesis network in bladder cancer from different levels and analyse its possible relationship with aberrant miRNA expression and the pathological characteristics of the disease. PMID:28187437

Molecular profiles of pre- and postoperative breast cancer tumours reveal differentially expressed genes.

PubMed

Riis, Margit L H; Lüders, Torben; Markert, Elke K; Haakensen, Vilde D; Nesbakken, Anne-Jorun; Kristensen, Vessela N; Bukholm, Ida R K

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.

Molecular Profiles of Pre- and Postoperative Breast Cancer Tumours Reveal Differentially Expressed Genes

PubMed Central

Riis, Margit L. H.; Lüders, Torben; Markert, Elke K.; Haakensen, Vilde D.; Nesbakken, Anne-Jorun; Kristensen, Vessela N.; Bukholm, Ida R. K.

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology. PMID:23227362

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

PubMed

Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square test. By successive operations of two modules, users can clarify how gene expression levels are affected by the phenotype specific genomic alterations. As CHESS was developed in both Java application and web environments, it can be run on a web browser or a local machine. It also supports all experimental platforms if a properly formatted text file is provided to include the chromosomal position of probes and their gene identifiers. CHESS is a user-friendly tool for investigating disease specific genomic alterations and quantitative relationships between those genomic alterations and genome-wide gene expression profiling.

A model-based design and validation approach with OMEGA-UML and the IF toolset

NASA Astrophysics Data System (ADS)

Ben-hafaiedh, Imene; Constant, Olivier; Graf, Susanne; Robbana, Riadh

2009-03-01

Intelligent, embedded systems such as autonomous robots and other industrial systems are becoming increasingly more heterogeneous with respect to the platforms on which they are implemented, and thus the software architecture more complex to design and analyse. In this context, it is important to have well-defined design methodologies which should be supported by (1) high level design concepts allowing to master the design complexity, (2) concepts for the expression of non-functional requirements and (3) analysis tools allowing to verify or invalidate that the system under development will be able to conform to its requirements. We illustrate here such an approach for the design of complex embedded systems on hand of a small case study used as a running example for illustration purposes. We briefly present the important concepts of the OMEGA-RT UML profile, we show how we use this profile in a modelling approach, and explain how these concepts are used in the IFx verification toolbox to integrate validation into the design flow and make scalable verification possible.

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

PubMed

Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

2017-09-01

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.

CPEB1 modulates differentiation of glioma stem cells via downregulation of HES1 and SIRT1 expression

PubMed Central

Lee, Jeong Eun; Park, Ju Young; Kim, Tae-Hoon; Kim, Youn-Jae; Lee, Seung-Hoon; Yoo, Heon; Kim, Jong Heon; Park, Jong Bae

2014-01-01

Glioma stemness has been recognized as the most important reason for glioma relapse and drug resistance. Differentiation of glioma stem cells (GSCs) has been implicated as a novel approach to target recurrent glioma. However, the detailed molecular mechanism involved in the differentiation of GSCs has not yet been elucidated. This study identified CPEB1 as the key modulator that induces the differentiation of GSCs at the post-transcriptional level. Gain and loss of function experiments showed that CPEB1 expression reduced sphere formation ability and the expression of stemness markers such as Nestin and Notch. To elucidate the detailed molecular mechanism underlying the action of CPEB1, we investigated the interacting ribonome of the CPEB1 complex using a Ribonomics approach. CPEB1 specifically suppressed the translation of HES1 and SIRT1 by interacting with a cytoplasmic polyadenylation element. The expression profile of CPEB1 negatively correlated with overall survival in glioma patients. Overexpression of CPEB1 decreased the number of GSCs in an orthotopically implanted glioma animal model. These results suggest that CPEB1-mediated translational control is essential for the differentiation of GSCs and provides novel therapeutic concepts for differentiation therapy. PMID:25216517

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Novel miRNA-31 and miRNA-200a-Mediated Regulation of Retinoblastoma Proliferation.

PubMed

Montoya, Vanessa; Fan, Hanli; Bryar, Paul J; Weinstein, Joanna L; Mets, Marilyn B; Feng, Gang; Martin, Joshua; Martin, Alissa; Jiang, Hongmei; Laurie, Nikia A

2015-01-01

Retinoblastoma is the most common intraocular tumor in children. Current management includes broad-based treatments such as chemotherapy, enucleation, laser therapy, or cryotherapy. However, therapies that target specific pathways important for retinoblastoma progression could provide valuable alternatives for treatment. MicroRNAs are short, noncoding RNA transcripts that can regulate the expression of target genes, and their aberrant expression often facilitates disease. The identification of post-transcriptional events that occur after the initiating genetic lesions could further define the rapidly aggressive growth displayed by retinoblastoma tumors. In this study, we used two phenotypically different retinoblastoma cell lines to elucidate the roles of miRNA-31 and miRNA-200a in tumor proliferation. Our approach confirmed that miRNAs-31 and -200a expression is significantly reduced in human retinoblastomas. Moreover, overexpression of these two miRNAs restricts the expansion of a highly proliferative cell line (Y79), but does not restrict the growth rate of a less aggressive cell line (Weri1). Gene expression profiling of miRNA-31 and/or miRNA-200a-overexpressing cells identified differentially expressed mRNAs associated with the divergent response of the two cell lines. This work has the potential to enhance the development of targeted therapeutic approaches for retinoblastoma and improve the efficacy of treatment.

Baculovirus induced transcripts in hemocytes from Heliothis virescens

USDA-ARS?s Scientific Manuscript database

Using RNA-sequencing digital difference expression profiling methods we have assessed the gene expression profiles of hemocytes harvested from Heliothis virescens that were challenged with Helicoverpa zea single nucleopolyhedrovirus (HzSNPV). A reference transcriptome of hemocyte-expressed transcri...

Application of the whole-transcriptome shotgun sequencing approach to the study of Philadelphia-positive acute lymphoblastic leukemia

PubMed Central

Iacobucci, I; Ferrarini, A; Sazzini, M; Giacomelli, E; Lonetti, A; Xumerle, L; Ferrari, A; Papayannidis, C; Malerba, G; Luiselli, D; Boattini, A; Garagnani, P; Vitale, A; Soverini, S; Pane, F; Baccarani, M; Delledonne, M; Martinelli, G

2012-01-01

Although the pathogenesis of BCR–ABL1-positive acute lymphoblastic leukemia (ALL) is mainly related to the expression of the BCR–ABL1 fusion transcript, additional cooperating genetic lesions are supposed to be involved in its development and progression. Therefore, in an attempt to investigate the complex landscape of mutations, changes in expression profiles and alternative splicing (AS) events that can be observed in such disease, the leukemia transcriptome of a BCR–ABL1-positive ALL patient at diagnosis and at relapse was sequenced using a whole-transcriptome shotgun sequencing (RNA-Seq) approach. A total of 13.9 and 15.8 million sequence reads was generated from de novo and relapsed samples, respectively, and aligned to the human genome reference sequence. This led to the identification of five validated missense mutations in genes involved in metabolic processes (DPEP1, TMEM46), transport (MVP), cell cycle regulation (ABL1) and catalytic activity (CTSZ), two of which resulted in acquired relapse variants. In all, 6390 and 4671 putative AS events were also detected, as well as expression levels for 18 315 and 18 795 genes, 28% of which were differentially expressed in the two disease phases. These data demonstrate that RNA-Seq is a suitable approach for identifying a wide spectrum of genetic alterations potentially involved in ALL. PMID:22829256

A gene profiling deconvolution approach to estimating immune cell composition from complex tissues.

PubMed

Chen, Shu-Hwa; Kuo, Wen-Yu; Su, Sheng-Yao; Chung, Wei-Chun; Ho, Jen-Ming; Lu, Henry Horng-Shing; Lin, Chung-Yen

2018-05-08

A new emerged cancer treatment utilizes intrinsic immune surveillance mechanism that is silenced by those malicious cells. Hence, studies of tumor infiltrating lymphocyte populations (TILs) are key to the success of advanced treatments. In addition to laboratory methods such as immunohistochemistry and flow cytometry, in silico gene expression deconvolution methods are available for analyses of relative proportions of immune cell types. Herein, we used microarray data from the public domain to profile gene expression pattern of twenty-two immune cell types. Initially, outliers were detected based on the consistency of gene profiling clustering results and the original cell phenotype notation. Subsequently, we filtered out genes that are expressed in non-hematopoietic normal tissues and cancer cells. For every pair of immune cell types, we ran t-tests for each gene, and defined differentially expressed genes (DEGs) from this comparison. Equal numbers of DEGs were then collected as candidate lists and numbers of conditions and minimal values for building signature matrixes were calculated. Finally, we used v -Support Vector Regression to construct a deconvolution model. The performance of our system was finally evaluated using blood biopsies from 20 adults, in which 9 immune cell types were identified using flow cytometry. The present computations performed better than current state-of-the-art deconvolution methods. Finally, we implemented the proposed method into R and tested extensibility and usability on Windows, MacOS, and Linux operating systems. The method, MySort, is wrapped as the Galaxy platform pluggable tool and usage details are available at https://testtoolshed.g2.bx.psu.edu/view/moneycat/mysort/e3afe097e80a .

Transcriptomic Profiling of Differential Responses to Drought in Two Freshwater Mussel Species, the Giant Floater Pyganodon grandis and the Pondhorn Uniomerus tetralasmus

PubMed Central

Landis, Andrew Gascho; Wang, Guiling; Stoeckel, James; Peatman, Eric

2014-01-01

The southeastern US has experienced recurrent drought during recent decades. Increasing demand for water, as precipitation decreases, exacerbates stress on the aquatic biota of the Southeast: a global hotspot for freshwater mussel, crayfish, and fish diversity. Freshwater unionid mussels are ideal candidates to study linkages between ecophysiological and behavioral responses to drought. Previous work on co-occurring mussel species suggests a coupling of physiology and behavior along a gradient ranging from intolerant species such as Pyganodon grandis (giant floater) that track receding waters and rarely burrow in the substrates to tolerant species such as Uniomerus tetralasmus (pondhorn) that rarely track receding waters, but readily burrow into the drying sediments. We utilized a next-generation sequencing-based RNA-Seq approach to examine heat/desiccation-induced transcriptomic profiles of these two species in order to identify linkages between patterns of gene expression, physiology and behavior. Sequencing produced over 425 million 100 bp reads. Using the de novo assembly package Trinity, we assembled the short reads into 321,250 contigs from giant floater (average length 835 bp) and 385,735 contigs from pondhorn (average length 929 bp). BLAST-based annotation and gene expression analysis revealed 2,832 differentially expressed genes in giant floater and 2,758 differentially expressed genes in pondhorn. Trancriptomic responses included changes in molecular chaperones, oxidative stress profiles, cell cycling, energy metabolism, immunity, and cytoskeletal rearrangements. Comparative analyses between species indicated significantly higher induction of molecular chaperones and cytoskeletal elements in the intolerant P. grandis as well as important differences in genes regulating apoptosis and immunity. PMID:24586812

Host Response Signature to Staphylococcus aureus Alpha-Hemolysin Implicates Pulmonary Th17 Response

PubMed Central

Zhou, Tong; Moreno-Vinasco, Liliana; Hollett, Brian; Garcia, Joe G. N.

2012-01-01

Staphylococcus aureus pneumonia causes significant morbidity and mortality. Alpha-hemolysin (Hla), a pore-forming cytotoxin of S. aureus, has been identified through animal models of pneumonia as a critical virulence factor that induces lung injury. In spite of considerable molecular knowledge of how this cytotoxin injures the host, the precise host response to Hla in the context of infection remains poorly understood. We employed whole-genome expression profiling of infected lungs to define the host response to wild-type S. aureus compared with the response to an Hla-deficient isogenic mutant in experimental pneumonia. These data provide a complete expression profile at 4 and at 24 h postinfection, revealing a unique response to the toxin-expressing strain. Gene ontogeny analysis revealed significant differences in the extracellular matrix and cardiomyopathy pathways, both of which govern cellular interactions in the tissue microenvironment. Evaluation of individual transcript responses to Hla-secreting staphylococci was notable for upregulation of host cytokine and chemokine genes, including the p19 subunit of interleukin-23. Consistent with this observation, the cellular immune response to infection was characterized by a prominent Th17 response to the wild-type pathogen. These findings define specific host mRNA responses to Hla-producing S. aureus, coupling the pulmonary Th17 response to the secretion of this cytotoxin. Expression profiling to define the host response to a single virulence factor proved to be a valuable tool in identifying pathways for further investigation in S. aureus pneumonia. This approach may be broadly applicable to the study of bacterial toxins, defining host pathways that can be targeted to mitigate toxin-induced disease. PMID:22733574

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

Proteomic and transcriptomic analyses of rigid and membranous cuticles and epidermis from the elytra and hindwings of the red flour beetle, Tribolium castaneum.

PubMed

Dittmer, Neal T; Hiromasa, Yasuaki; Tomich, John M; Lu, Nanyan; Beeman, Richard W; Kramer, Karl J; Kanost, Michael R

2012-01-01

The insect cuticle is a composite biomaterial made up primarily of chitin and proteins. The physical properties of the cuticle can vary greatly from hard and rigid to soft and flexible. Understanding how different cuticle types are assembled can aid in the development of novel biomimetic materials for use in medicine and technology. Toward this goal, we have taken a combined proteomics and transcriptomics approach with the red flour beetle, Tribolium castaneum, to examine the protein and gene expression profiles of the elytra and hindwings, appendages that contain rigid and soft cuticles, respectively. Two-dimensional gel electrophoresis analysis revealed distinct differences in the protein profiles between elytra and hindwings, with four highly abundant proteins dominating the elytral cuticle extract. MALDI/TOF mass spectrometry identified 19 proteins homologous to known or hypothesized cuticular proteins (CPs), including a novel low complexity protein enriched in charged residues. Microarray analysis identified 372 genes with a 10-fold or greater difference in transcript levels between elytra and hindwings. CP genes with higher expression in the elytra belonged to the Rebers and Riddiford family (CPR) type 2, or cuticular proteins of low complexity (CPLC) enriched in glycine or proline. In contrast, a majority of the CP genes with higher expression in hindwings were classified as CPR type 1, cuticular proteins analogous to peritrophins (CPAP), or members of the Tweedle family. This research shows that the elyra and hindwings, representatives of rigid and soft cuticles, have different protein and gene expression profiles for structural proteins that may influence the mechanical properties of these cuticles.

A gene expression resource generated by genome-wide lacZ profiling in the mouse

PubMed Central

Tuck, Elizabeth; Estabel, Jeanne; Oellrich, Anika; Maguire, Anna Karin; Adissu, Hibret A.; Souter, Luke; Siragher, Emma; Lillistone, Charlotte; Green, Angela L.; Wardle-Jones, Hannah; Carragher, Damian M.; Karp, Natasha A.; Smedley, Damian; Adams, Niels C.; Bussell, James N.; Adams, David J.; Ramírez-Solis, Ramiro; Steel, Karen P.; Galli, Antonella; White, Jacqueline K.

2015-01-01

ABSTRACT Knowledge of the expression profile of a gene is a critical piece of information required to build an understanding of the normal and essential functions of that gene and any role it may play in the development or progression of disease. High-throughput, large-scale efforts are on-going internationally to characterise reporter-tagged knockout mouse lines. As part of that effort, we report an open access adult mouse expression resource, in which the expression profile of 424 genes has been assessed in up to 47 different organs, tissues and sub-structures using a lacZ reporter gene. Many specific and informative expression patterns were noted. Expression was most commonly observed in the testis and brain and was most restricted in white adipose tissue and mammary gland. Over half of the assessed genes presented with an absent or localised expression pattern (categorised as 0-10 positive structures). A link between complexity of expression profile and viability of homozygous null animals was observed; inactivation of genes expressed in ≥21 structures was more likely to result in reduced viability by postnatal day 14 compared with more restricted expression profiles. For validation purposes, this mouse expression resource was compared with Bgee, a federated composite of RNA-based expression data sets. Strong agreement was observed, indicating a high degree of specificity in our data. Furthermore, there were 1207 observations of expression of a particular gene in an anatomical structure where Bgee had no data, indicating a large amount of novelty in our data set. Examples of expression data corroborating and extending genotype-phenotype associations and supporting disease gene candidacy are presented to demonstrate the potential of this powerful resource. PMID:26398943

F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PubMed Central

Shahdoust, Maryam; Mahjub, Hossein; Sadeghi, Mehdi

2017-01-01

The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches. PMID:28938012

The Use of EST Expression Matrixes for the Quality Control of Gene Expression Data

PubMed Central

Milnthorpe, Andrew T.; Soloviev, Mikhail

2012-01-01

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding “tissue-specific” genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging. PMID:22412959

A Straightforward and Highly Efficient Precipitation/On-pellet Digestion Procedure Coupled to a Long Gradient Nano-LC Separation and Orbitrap Mass Spectrometry for Label-free Expression Profiling of the Swine Heart Mitochondrial Proteome

PubMed Central

Duan, Xiaotao; Young, Rebecca; Straubinger, Robert M.; Page, Brian J.; Cao, Jin; Wang, Hao; Yu, Haoying; Canty, John M.; Qu, Jun

2009-01-01

For label-free expression profiling of tissue proteomes, efficient protein extraction, thorough and quantitative sample cleanup and digestion procedures, as well as sufficient and reproducible chromatographic separation, are highly desirable but remain challenging. However, optimal methodology has remained elusive, especially for proteomes that are rich in membrane proteins, such as the mitochondria. Here we describe a straightforward and reproducible sample preparation procedure, coupled with a highly selective and sensitive nano-LC/Orbitrap analysis, which enables reliable and comprehensive expression profiling of tissue mitochondria. The mitochondrial proteome of swine heart was selected as a test system. Efficient protein extraction was accomplished using a strong buffer containing both ionic and non-ionic detergents. Overnight precipitation was used for cleanup of the extract, and the sample was subjected to an optimized 2-step, on-pellet digestion approach. In the first step, the protein pellet was dissolved via a 4 h tryptic digestion under vigorous agitation, which nano-LC/LTQ/ETD showed to produce large and incompletely cleaved tryptic peptides. The mixture was then reduced, alkylated, and digested into its full complement of tryptic peptides with additional trypsin. This solvent precipitation/on-pellet digestion procedure achieved significantly higher and more reproducible peptide recovery of the mitochondrial preparation, than observed using a prevalent alternative procedure for label-free expression profiling, SDS-PAGE/in-gel digestion (87% vs. 54%). Furthermore, uneven peptide losses were lower than observed with SDS-PAGE/in-gel digestion. The resulting peptides were sufficiently resolved by a 5 h gradient using a nano-LC configuration that features a low-void-volume, high chromatographic reproducibility, and an LTQ/Orbitrap analyzer for protein identification and quantification. The developed method was employed for label-free comparison of the mitochondrial proteomes of myocardium from healthy animals vs. those with hibernating myocardium. Each experimental group consisted of a relatively large number of animals (n=10), and samples were analyzed in random order to minimize quantitative false-positives. Using this approach, 904 proteins were identified and quantified with high confidence, and those mitochondrial proteins that were altered significantly between groups were compared with the results of a parallel 2D-DIGE analysis. The sample preparation and analytical strategy developed here represents an advancement that can be adapted to analyze other tissue proteomes. PMID:19290621

Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis.

PubMed

Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng

2018-06-08

Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PubMed Central

Campbell, Kieran R.

2016-01-01

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

Regulation of osteogenesis by long noncoding RNAs: An epigenetic mechanism contributing to bone formation.

PubMed

Tye, Coralee E; Boyd, Joseph R; Page, Natalie A; Falcone, Michelle M; Stein, Janet L; Stein, Gary S; Lian, Jane B

2018-12-01

Long noncoding RNAs (lncRNAs) have recently emerged as novel regulators of lineage commitment, differentiation, development, viability, and disease progression. Few studies have examined their role in osteogenesis; however, given their critical and wide-ranging roles in other tissues, lncRNAs are most likely vital regulators of osteogenesis. In this study, we extensively characterized lncRNA expression in mesenchymal cells during commitment and differentiation to the osteoblast lineage using a whole transcriptome sequencing approach (RNA-Seq). Using mouse primary mesenchymal stromal cells (mMSC), we identified 1438 annotated lncRNAs expressed during MSC differentiation, 462 of which are differentially expressed. We performed guilt-by-association analysis using lncRNA and mRNA expression profiles to identify lncRNAs influencing MSC commitment and differentiation. These findings open novel dimensions for exploring lncRNAs in regulating normal bone formation and in skeletal disorders.

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Exact Analytic Result of Contact Value for the Density in a Modified Poisson-Boltzmann Theory of an Electrical Double Layer.

PubMed

Lou, Ping; Lee, Jin Yong

2009-04-14

For a simple modified Poisson-Boltzmann (SMPB) theory, taking into account the finite ionic size, we have derived the exact analytic expression for the contact values of the difference profile of the counterion and co-ion, as well as of the sum (density) and product profiles, near a charged planar electrode that is immersed in a binary symmetric electrolyte. In the zero ionic size or dilute limit, these contact values reduce to the contact values of the Poisson-Boltzmann (PB) theory. The analytic results of the SMPB theory, for the difference, sum, and product profiles were compared with the results of the Monte-Carlo (MC) simulations [ Bhuiyan, L. B.; Outhwaite, C. W.; Henderson, D. J. Electroanal. Chem. 2007, 607, 54 ; Bhuiyan, L. B.; Henderson, D. J. Chem. Phys. 2008, 128, 117101 ], as well as of the PB theory. In general, the analytic expression of the SMPB theory gives better agreement with the MC data than the PB theory does. For the difference profile, as the electrode charge increases, the result of the PB theory departs from the MC data, but the SMPB theory still reproduces the MC data quite well, which indicates the importance of including steric effects in modeling diffuse layer properties. As for the product profile, (i) it drops to zero as the electrode charge approaches infinity; (ii) the speed of the drop increases with the ionic size, and these behaviors are in contrast with the predictions of the PB theory, where the product is identically 1.

A Novel Real-Time PCR Assay of microRNAs Using S-Poly(T), a Specific Oligo(dT) Reverse Transcription Primer with Excellent Sensitivity and Specificity

PubMed Central

Kang, Kang; Zhang, Xiaoying; Liu, Hongtao; Wang, Zhiwei; Zhong, Jiasheng; Huang, Zhenting; Peng, Xiao; Zeng, Yan; Wang, Yuna; Yang, Yi; Luo, Jun; Gou, Deming

2012-01-01

Background MicroRNAs (miRNAs) are small, non-coding RNAs capable of postranscriptionally regulating gene expression. Accurate expression profiling is crucial for understanding the biological roles of miRNAs, and exploring them as biomarkers of diseases. Methodology/Principal Findings A novel, highly sensitive, and reliable miRNA quantification approach,termed S-Poly(T) miRNA assay, is designed. In this assay, miRNAs are subjected to polyadenylation and reverse transcription with a S-Poly(T) primer that contains a universal reverse primer, a universal Taqman probe, an oligo(dT)11 sequence and six miRNA-specific bases. Individual miRNAs are then amplified by a specific forward primer and a universal reverse primer, and the PCR products are detected by a universal Taqman probe. The S-Poly(T) assay showed a minimum of 4-fold increase in sensitivity as compared with the stem-loop or poly(A)-based methods. A remarkable specificity in discriminating among miRNAs with high sequence similarity was also obtained with this approach. Using this method, we profiled miRNAs in human pulmonary arterial smooth muscle cells (HPASMC) and identified 9 differentially expressed miRNAs associated with hypoxia treatment. Due to its outstanding sensitivity, the number of circulating miRNAs from normal human serum was significantly expanded from 368 to 518. Conclusions/Significance With excellent sensitivity, specificity, and high-throughput, the S-Poly(T) method provides a powerful tool for miRNAs quantification and identification of tissue- or disease-specific miRNA biomarkers. PMID:23152780

Integration of miRNA and Protein Profiling Reveals Coordinated Neuroadaptations in the Alcohol-Dependent Mouse Brain

PubMed Central

Gorini, Giorgio; Nunez, Yury O.; Mayfield, R. Dayne

2013-01-01

The molecular mechanisms underlying alcohol dependence involve different neurochemical systems and are brain region-dependent. Chronic Intermittent Ethanol (CIE) procedure, combined with a Two-Bottle Choice voluntary drinking paradigm, represents one of the best available animal models for alcohol dependence and relapse drinking. MicroRNAs, master regulators of the cellular transcriptome and proteome, can regulate their targets in a cooperative, combinatorial fashion, ensuring fine tuning and control over a large number of cellular functions. We analyzed cortex and midbrain microRNA expression levels using an integrative approach to combine and relate data to previous protein profiling from the same CIE-subjected samples, and examined the significance of the data in terms of relative contribution to alcohol consumption and dependence. MicroRNA levels were significantly altered in CIE-exposed dependent mice compared with their non-dependent controls. More importantly, our integrative analysis identified modules of coexpressed microRNAs that were highly correlated with CIE effects and predicted target genes encoding differentially expressed proteins. Coexpressed CIE-relevant proteins, in turn, were often negatively correlated with specific microRNA modules. Our results provide evidence that microRNA-orchestrated translational imbalances are driving the behavioral transition from alcohol consumption to dependence. This study represents the first attempt to combine ex vivo microRNA and protein expression on a global scale from the same mammalian brain samples. The integrative systems approach used here will improve our understanding of brain adaptive changes in response to drug abuse and suggests the potential therapeutic use of microRNAs as tools to prevent or compensate multiple neuroadaptations underlying addictive behavior. PMID:24358208

Substrate mass transfer: analytical approach for immobilized enzyme reactions

NASA Astrophysics Data System (ADS)

Senthamarai, R.; Saibavani, T. N.

2018-04-01

In this paper, the boundary value problem in immobilized enzyme reactions is formulated and approximate expression for substrate concentration without external mass transfer resistance is presented. He’s variational iteration method is used to give approximate and analytical solutions of non-linear differential equation containing a non linear term related to enzymatic reaction. The relevant analytical solution for the dimensionless substrate concentration profile is discussed in terms of dimensionless reaction parameters α and β.

Integrated lipidomics and transcriptomic analysis of peripheral blood reveals significantly enriched pathways in type 2 diabetes mellitus.

PubMed

Zhao, Chen; Mao, Jinghe; Ai, Junmei; Shenwu, Ming; Shi, Tieliu; Zhang, Daqing; Wang, Xiaonan; Wang, Yunliang; Deng, Youping

2013-01-01

Insulin resistance is a key element in the pathogenesis of type 2 diabetes mellitus. Plasma free fatty acids were assumed to mediate the insulin resistance, while the relationship between lipid and glucose disposal remains to be demonstrated across liver, skeletal muscle and blood. We profiled both lipidomics and gene expression of 144 total peripheral blood samples, 84 from patients with T2D and 60 from healthy controls. Then, factor and partial least squares models were used to perform a combined analysis of lipidomics and gene expression profiles to uncover the bioprocesses that are associated with lipidomic profiles in type 2 diabetes. According to factor analysis of the lipidomic profile, several species of lipids were found to be correlated with different phenotypes, including diabetes-related C23:2CE, C23:3CE, C23:4CE, ePE36:4, ePE36:5, ePE36:6; race-related (African-American) PI36:1; and sex-related PE34:1 and LPC18:2. The major variance of gene expression profile was not caused by known factors and no significant difference can be directly derived from differential gene expression profile. However, the combination of lipidomic and gene expression analyses allows us to reveal the correlation between the altered lipid profile with significantly enriched pathways, such as one carbon pool by folate, arachidonic acid metabolism, insulin signaling pathway, amino sugar and nucleotide sugar metabolism, propanoate metabolism, and starch and sucrose metabolism. The genes in these pathways showed a good capability to classify diabetes samples. Combined analysis of gene expression and lipidomic profiling reveals type 2 diabetes-associated lipid species and enriched biological pathways in peripheral blood, while gene expression profile does not show direct correlation. Our findings provide a new clue to better understand the mechanism of disordered lipid metabolism in association with type 2 diabetes.

Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles.

PubMed

Piao, Yongjun; Piao, Minghao; Ryu, Keun Ho

2017-01-01

Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data. In this article, we propose a feature subset-based ensemble method in which each model is learned from a different projection of the original feature space to classify multiple cancers. In our method, the feature relevance and redundancy are considered to generate multiple feature subsets, the base classifiers are learned from each independent miRNA subset, and the average posterior probability is used to combine the base classifiers. To test the performance of our method, we used bead-based and sequence-based miRNA expression datasets and conducted 10-fold and leave-one-out cross validations. The experimental results show that the proposed method yields good results and has higher prediction accuracy than popular ensemble methods. The Java program and source code of the proposed method and the datasets in the experiments are freely available at https://sourceforge.net/projects/mirna-ensemble/. Copyright © 2016 Elsevier Ltd. All rights reserved.

Surviving in a toxic world: transcriptomics and gene expression profiling in response to environmental pollution in the critically endangered European eel.

PubMed

Pujolar, Jose Martin; Marino, Ilaria A M; Milan, Massimo; Coppe, Alessandro; Maes, Gregory E; Capoccioni, Fabrizio; Ciccotti, Eleonora; Bervoets, Lieven; Covaci, Adrian; Belpaire, Claude; Cramb, Gordon; Patarnello, Tomaso; Bargelloni, Luca; Bortoluzzi, Stefania; Zane, Lorenzo

2012-09-25

Genomic and transcriptomic approaches have the potential for unveiling the genome-wide response to environmental perturbations. The abundance of the catadromous European eel (Anguilla anguilla) stock has been declining since the 1980s probably due to a combination of anthropogenic and climatic factors. In this paper, we explore the transcriptomic dynamics between individuals from high (river Tiber, Italy) and low pollution (lake Bolsena, Italy) environments, which were measured for 36 PCBs, several organochlorine pesticides and brominated flame retardants and nine metals. To this end, we first (i) updated the European eel transcriptome using deep sequencing data with a total of 640,040 reads assembled into 44,896 contigs (Eeelbase release 2.0), and (ii) developed a transcriptomic platform for global gene expression profiling in the critically endangered European eel of about 15,000 annotated contigs, which was applied to detect differentially expressed genes between polluted sites. Several detoxification genes related to metabolism of pollutants were upregulated in the highly polluted site, including genes that take part in phase I of the xenobiotic metabolism (CYP3A), phase II (glutathione-S-transferase) and oxidative stress (glutathione peroxidase). In addition, key genes in the mitochondrial respiratory chain and oxidative phosphorylation were down-regulated at the Tiber site relative to the Bolsena site. Together with the induced high expression of detoxification genes, the suggested lowered expression of genes supposedly involved in metabolism suggests that pollution may also be associated with decreased respiratory and energy production.

Magnesium supplementation, metabolic and inflammatory markers, and global genomic and proteomic profiling: a randomized, double-blind, controlled, crossover trial in overweight individuals.

PubMed

Chacko, Sara A; Sul, James; Song, Yiqing; Li, Xinmin; LeBlanc, James; You, Yuko; Butch, Anthony; Liu, Simin

2011-02-01

Dietary magnesium intake has been favorably associated with reduced risk of metabolic outcomes in observational studies; however, few randomized trials have introduced a systems-biology approach to explore molecular mechanisms of pleiotropic metabolic actions of magnesium supplementation. We examined the effects of oral magnesium supplementation on metabolic biomarkers and global genomic and proteomic profiling in overweight individuals. We undertook this randomized, crossover, pilot trial in 14 healthy, overweight volunteers [body mass index (in kg/m(2)) ≥25] who were randomly assigned to receive magnesium citrate (500 mg elemental Mg/d) or a placebo for 4 wk with a 1-mo washout period. Fasting blood and urine specimens were collected according to standardized protocols. Biochemical assays were conducted on blood specimens. RNA was extracted and subsequently hybridized with the Human Gene ST 1.0 array (Affymetrix, Santa Clara, CA). Urine proteomic profiling was analyzed with the CM10 ProteinChip array (Bio-Rad Laboratories, Hercules, CA). We observed that magnesium treatment significantly decreased fasting C-peptide concentrations (change: -0.4 ng/mL after magnesium treatment compared with +0.05 ng/mL after placebo treatment; P = 0.004) and appeared to decrease fasting insulin concentrations (change: -2.2 μU/mL after magnesium treatment compared with 0.0 μU/mL after placebo treatment; P = 0.25). No consistent patterns were observed across inflammatory biomarkers. Gene expression profiling revealed up-regulation of 24 genes and down-regulation of 36 genes including genes related to metabolic and inflammatory pathways such as C1q and tumor necrosis factor-related protein 9 (C1QTNF9) and pro-platelet basic protein (PPBP). Urine proteomic profiling showed significant differences in the expression amounts of several peptides and proteins after treatment. Magnesium supplementation for 4 wk in overweight individuals led to distinct changes in gene expression and proteomic profiling consistent with favorable effects on several metabolic pathways. This trial was registered at clinicaltrials.gov as NCT00737815.

From DNA Copy Number to Gene Expression: Local aberrations, Trisomies and Monosomies

NASA Astrophysics Data System (ADS)

Shay, Tal

The goal of my PhD research was to study the effect of DNA copy number changes on gene expression. DNA copy number aberrations may be local, encompassing several genes, or on the level of an entire chromosome, such as trisomy and monosomy. The main dataset I studied was of Glioblastoma, obtained in the framework of a collaboration, but I worked also with public datasets of cancer and Down's Syndrome. The molecular basis of expression changes in Glioblastoma. Glioblastoma is the most common and aggressive type of primary brain tumors in adults. In collaboration with Prof. Hegi (CHUV, Switzerland), we analyzed a rich Glioblastoma dataset including clinical information, DNA copy number (array CGH) and expression profiles. We explored the correlation between DNA copy number and gene expression at the level of chromosomal arms and local genomic aberrations. We detected known amplification and over expression of oncogenes, as well as deletion and down-regulation of tumor suppressor genes. We exploited that information to map alterations of pathways that are known to be disrupted in Glioblastoma, and tried to characterize samples that have no known alteration in any of the studied pathways. Identifying local DNA aberrations of biological significance. Many types of tumors exhibit chromosomal losses or gains and local amplifications and deletions. A region that is aberrant in many tumors, or whose copy number change is stronger, is more likely to be clinically relevant, and not just a by-product of genetic instability. We developed a novel method that defines and prioritizes aberrations by formalizing these intuitions. The method scores each aberration by the fraction of patients harboring it, its length and its amplitude, and assesses the significance of the score by comparing it to a null distribution obtained by permutations. This approach detects genetic locations that are significantly aberrant, generating a 'genomic aberration profile' for each sample. The 'genomic aberration profile' is then combined with chromosomal arm status (gain/loss) to define a succinct genomic signature for each tumor. Unsupervised clustering of the samples based on these genomic signatures can reveal novel tumor subtypes. This approach was applied to datasets from three types of brain tumors: Glioblastoma, Medulloblastoma and Neuroblastoma, and identified a new subtype in Medulloblastoma, characterized by many chromosomal aberrations. Elucidating the transcriptional effect of monosomy and trisomy. Trisomy and monosomy are expected to impact the expression of genes that are located on the affected chromosome. Analysis of several cancer datasets revealed that not all the genes on the aberrant chromosome are affected by the change of copy number. Affected genes exhibit a wide range of expression changes with varying penetrance. Specifically, (1) The effect of trisomy is much more conserved among individuals than the effect of monosomy and (2) the expression level of a gene in the diploid is significantly correlated with the level of change between the diploid and the trisomy or monosomy.

Bridging the gap between high-throughput genetic and transcriptional data reveals cellular pathways responding to alpha-synuclein toxicity

PubMed Central

Yeger-Lotem, Esti; Riva, Laura; Su, Linhui Julie; Gitler, Aaron D.; Cashikar, Anil; King, Oliver D.; Auluck, Pavan K.; Geddie, Melissa L.; Valastyan, Julie S.; Karger, David R.; Lindquist, Susan; Fraenkel, Ernest

2009-01-01

Cells respond to stimuli by changes in various processes, including signaling pathways and gene expression. Efforts to identify components of these responses increasingly depend on mRNA profiling and genetic library screens, yet the functional roles of the genes identified by these assays often remain enigmatic. By comparing the results of these two assays across various cellular responses, we found that they are consistently distinct. Moreover, genetic screens tend to identify response regulators, while mRNA profiling frequently detects metabolic responses. We developed an integrative approach that bridges the gap between these data using known molecular interactions, thus highlighting major response pathways. We harnessed this approach to reveal cellular pathways related to alpha-synuclein, a small lipid-binding protein implicated in several neurodegenerative disorders including Parkinson disease. For this we screened an established yeast model for alpha-synuclein toxicity to identify genes that when overexpressed alter cellular survival. Application of our algorithm to these data and data from mRNA profiling provided functional explanations for many of these genes and revealed novel relations between alpha-synuclein toxicity and basic cellular pathways. PMID:19234470

Versatile Gene-Specific Sequence Tags for Arabidopsis Functional Genomics: Transcript Profiling and Reverse Genetics Applications

PubMed Central

Hilson, Pierre; Allemeersch, Joke; Altmann, Thomas; Aubourg, Sébastien; Avon, Alexandra; Beynon, Jim; Bhalerao, Rishikesh P.; Bitton, Frédérique; Caboche, Michel; Cannoot, Bernard; Chardakov, Vasil; Cognet-Holliger, Cécile; Colot, Vincent; Crowe, Mark; Darimont, Caroline; Durinck, Steffen; Eickhoff, Holger; de Longevialle, Andéol Falcon; Farmer, Edward E.; Grant, Murray; Kuiper, Martin T.R.; Lehrach, Hans; Léon, Céline; Leyva, Antonio; Lundeberg, Joakim; Lurin, Claire; Moreau, Yves; Nietfeld, Wilfried; Paz-Ares, Javier; Reymond, Philippe; Rouzé, Pierre; Sandberg, Goran; Segura, Maria Dolores; Serizet, Carine; Tabrett, Alexandra; Taconnat, Ludivine; Thareau, Vincent; Van Hummelen, Paul; Vercruysse, Steven; Vuylsteke, Marnik; Weingartner, Magdalena; Weisbeek, Peter J.; Wirta, Valtteri; Wittink, Floyd R.A.; Zabeau, Marc; Small, Ian

2004-01-01

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics. PMID:15489341

Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity

PubMed Central

Pantazatos, Spiro P.; Huang, Yung-yu; Rosoklija, Gorazd B.; Dwork, Andrew J.; Arango, Victoria; Mann, J. John

2016-01-01

Brain gene expression profiling studies of suicide and depression using oligonucleotide microarrays have often failed to distinguish these two phenotypes. Moreover, next generation sequencing (NGS) approaches are more accurate in quantifying gene expression and can detect alternative splicing. Using RNA-seq, we examined whole-exome gene and exon expression in non-psychiatric controls (CON, N=29), DSM-IV major depressive disorder suicides (MDD-S, N=21) and MDD non-suicides (MDD, N=9) in dorsal lateral prefrontal cortex (Brodmann Area 9) of sudden-death medication-free individuals postmortem. Using small RNA-seq, we also examined miRNA expression (9 samples per group). DeSeq2 identified thirty-five genes differentially expressed between groups and surviving adjustment for false discovery rate (adjusted p<0.1). In depression, altered genes include humanin like-8 (MTRNRL8), interleukin-8 (IL8), and serpin peptidase inhibitor, clade H (SERPINH1) and chemokine ligand 4 (CCL4), while exploratory gene ontology (GO) analyses revealed lower expression of immune-related pathways such as chemokine receptor activity, chemotaxis and cytokine biosynthesis, and angiogenesis and vascular development in (adjusted p<0.1). Hypothesis-driven GO analysis suggests lower expression of genes involved in oligodendrocyte differentiation, regulation of glutamatergic neurotransmission, and oxytocin receptor expression in both suicide and depression, and provisional evidence for altered DNA-dependent ATPase expression in suicide only. DEXSEq analysis identified differential exon usage in ATPase, class II, type 9B (adjusted p<0.1) in depression. Differences in miRNA expression or structural gene variants were not detected. Results lend further support for models in which deficits in microglial, endothelial (blood-brain barrier), ATPase activity and astrocytic cell functions contribute to MDD and suicide, and identify putative pathways and mechanisms for further study in these disorders. PMID:27528462

Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity.

PubMed

Pantazatos, S P; Huang, Y-Y; Rosoklija, G B; Dwork, A J; Arango, V; Mann, J J

2017-05-01

Brain gene expression profiling studies of suicide and depression using oligonucleotide microarrays have often failed to distinguish these two phenotypes. Moreover, next generation sequencing approaches are more accurate in quantifying gene expression and can detect alternative splicing. Using RNA-seq, we examined whole-exome gene and exon expression in non-psychiatric controls (CON, N=29), DSM-IV major depressive disorder suicides (MDD-S, N=21) and MDD non-suicides (MDD, N=9) in the dorsal lateral prefrontal cortex (Brodmann Area 9) of sudden death medication-free individuals post mortem. Using small RNA-seq, we also examined miRNA expression (nine samples per group). DeSeq2 identified 35 genes differentially expressed between groups and surviving adjustment for false discovery rate (adjusted P<0.1). In depression, altered genes include humanin-like-8 (MTRNRL8), interleukin-8 (IL8), and serpin peptidase inhibitor, clade H (SERPINH1) and chemokine ligand 4 (CCL4), while exploratory gene ontology (GO) analyses revealed lower expression of immune-related pathways such as chemokine receptor activity, chemotaxis and cytokine biosynthesis, and angiogenesis and vascular development in (adjusted P<0.1). Hypothesis-driven GO analysis suggests lower expression of genes involved in oligodendrocyte differentiation, regulation of glutamatergic neurotransmission, and oxytocin receptor expression in both suicide and depression, and provisional evidence for altered DNA-dependent ATPase expression in suicide only. DEXSEq analysis identified differential exon usage in ATPase, class II, type 9B (adjusted P<0.1) in depression. Differences in miRNA expression or structural gene variants were not detected. Results lend further support for models in which deficits in microglial, endothelial (blood-brain barrier), ATPase activity and astrocytic cell functions contribute to MDD and suicide, and identify putative pathways and mechanisms for further study in these disorders.

Transcriptomics of environmental acclimatization and survival in wild adult Pacific sockeye salmon (Oncorhynchus nerka) during spawning migration.

PubMed

Evans, Tyler G; Hammill, Edd; Kaukinen, Karia; Schulze, Angela D; Patterson, David A; English, Karl K; Curtis, Janelle M R; Miller, Kristina M

2011-11-01

Environmental shifts accompanying salmon spawning migrations from ocean feeding grounds to natal freshwater streams can be severe, with the underlying stress often cited as a cause of increased mortality. Here, a salmonid microarray was used to characterize changes in gene expression occurring between ocean and river habitats in gill and liver tissues of wild migrating sockeye salmon (Oncorhynchus nerka Walbaum) returning to spawn in the Fraser River, British Columbia, Canada. Expression profiles indicate that the transcriptome of migrating salmon is strongly affected by shifting abiotic and biotic conditions encountered along migration routes. Conspicuous shifts in gene expression associated with changing salinity, temperature, pathogen exposure and dissolved oxygen indicate that these environmental variables most strongly impact physiology during spawning migrations. Notably, transcriptional changes related to osmoregulation were largely preparatory and occurred well before salmon encountered freshwater. In the river environment, differential expression of genes linked with elevated temperatures indicated that thermal regimes within the Fraser River are approaching tolerance limits for adult salmon. To empirically correlate gene expression with survival, biopsy sampling of gill tissue and transcriptomic profiling were combined with telemetry. Many genes correlated with environmental variables were differentially expressed between premature mortalities and successful migrants. Parametric survival analyses demonstrated a broad-scale transcriptional regulator, cofactor required for Sp1 transcriptional activation (CRSP), to be significantly predictive of survival. As the environmental characteristics of salmon habitats continue to change, establishing how current environmental conditions influence salmon physiology under natural conditions is critical to conserving this ecologically and economically important fish species. © 2011 Blackwell Publishing Ltd.

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

Divergence between motoneurons: gene expression profiling provides a molecular characterization of functionally discrete somatic and autonomic motoneurons

PubMed Central

Cui, Dapeng; Dougherty, Kimberly J.; Machacek, David W.; Sawchuk, Michael; Hochman, Shawn; Baro, Deborah J.

2009-01-01

Studies in the developing spinal cord suggest that different motoneuron (MN) cell types express very different genetic programs, but the degree to which adult programs differ is unknown. To compare genetic programs between adult MN columnar cell types, we used laser capture micro-dissection (LCM) and Affymetrix microarrays to create expression profiles for three columnar cell types: lateral and medial MNs from lumbar segments and sympathetic preganglionic motoneurons located in the thoracic intermediolateral nucleus. A comparison of the three expression profiles indicated that ~7% (813/11,552) of the genes showed significant differences in their expression levels. The largest differences were observed between sympathetic preganglionic MNs and the lateral motor column, with 6% (706/11,552) of the genes being differentially expressed. Significant differences in expression were observed for 1.8% (207/11,552) of the genes when comparing sympathetic preganglionic MNs with the medial motor column. Lateral and medial MNs showed the least divergence, with 1.3% (150/11,552) of the genes being differentially expressed. These data indicate that the amount of divergence in expression profiles between identified columnar MNs does not strictly correlate with divergence of function as defined by innervation patterns (somatic/muscle vs. autonomic/viscera). Classification of the differentially expressed genes with regard to function showed that they underpin all fundamental cell systems and processes, although most differentially expressed genes encode proteins involved in signal transduction. Mining the expression profiles to examine transcription factors essential for MN development suggested that many of the same transcription factors participatein combinatorial codes in embryonic and adult neurons, but patterns of expression change significantly. PMID:16317082

Cusped magnetic field mercury ion thruster. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Beattie, J. R.

1976-01-01

The importance of a uniform current density profile in the exhaust beam of an electrostatic ion thruster is discussed in terms of thrust level and accelerator system lifetime. A residence time approach is used to explain the nonuniform beam current density profile of the divergent magnetic field thruster. Mathematical expressions are derived which relate the thruster discharge power loss, propellant utilization, and double to single ion density ratio to the geometry and plasma properties of the discharge chamber. These relationships are applied to a cylindrical discharge chamber model of the thruster. Experimental results are presented for a wide range of the discharge chamber length. The thruster designed for this investigation was operated with a cusped magnetic field as well as a divergent field geometry, and the cusped field geometry is shown to be superior from the standpoint of beam profile uniformity, performance, and double ion population.

Application of activity-based protein profiling to study enzyme function in adipocytes.

PubMed

Galmozzi, Andrea; Dominguez, Eduardo; Cravatt, Benjamin F; Saez, Enrique

2014-01-01

Activity-based protein profiling (ABPP) is a chemical proteomics approach that utilizes small-molecule probes to determine the functional state of enzymes directly in native systems. ABPP probes selectively label active enzymes, but not their inactive forms, facilitating the characterization of changes in enzyme activity that occur without alterations in protein levels. ABPP can be a tool superior to conventional gene expression and proteomic profiling methods to discover new enzymes active in adipocytes and to detect differences in the activity of characterized enzymes that may be associated with disorders of adipose tissue function. ABPP probes have been developed that react selectively with most members of specific enzyme classes. Here, using as an example the serine hydrolase family that includes many enzymes with critical roles in adipocyte physiology, we describe methods to apply ABPP analysis to the study of adipocyte enzymatic pathways. © 2014 Elsevier Inc. All rights reserved.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

Face in profile view reduces perceived facial expression intensity: an eye-tracking study.

PubMed

Guo, Kun; Shaw, Heather

2015-02-01

Recent studies measuring the facial expressions of emotion have focused primarily on the perception of frontal face images. As we frequently encounter expressive faces from different viewing angles, having a mechanism which allows invariant expression perception would be advantageous to our social interactions. Although a couple of studies have indicated comparable expression categorization accuracy across viewpoints, it is unknown how perceived expression intensity and associated gaze behaviour change across viewing angles. Differences could arise because diagnostic cues from local facial features for decoding expressions could vary with viewpoints. Here we manipulated orientation of faces (frontal, mid-profile, and profile view) displaying six common facial expressions of emotion, and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. In comparison with frontal faces, profile faces slightly reduced identification rates for disgust and sad expressions, but significantly decreased perceived intensity for all tested expressions. Although quantitatively viewpoint had expression-specific influence on the proportion of fixations directed at local facial features, the qualitative gaze distribution within facial features (e.g., the eyes tended to attract the highest proportion of fixations, followed by the nose and then the mouth region) was independent of viewpoint and expression type. Our results suggest that the viewpoint-invariant facial expression processing is categorical perception, which could be linked to a viewpoint-invariant holistic gaze strategy for extracting expressive facial cues. Copyright © 2014 Elsevier B.V. All rights reserved.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

PubMed

Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-02-07

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

An Adaptive Genetic Association Test Using Double Kernel Machines.

PubMed

Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

2015-10-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

Transcriptomic Modification in the Cerebral Cortex following Noninvasive Brain Stimulation: RNA-Sequencing Approach

PubMed Central

Holmes, Ben; Jung, Seung Ho; Lu, Jing; Wagner, Jessica A.; Rubbi, Liudmilla; Pellegrini, Matteo

2016-01-01

Transcranial direct current stimulation (tDCS) has been shown to modulate neuroplasticity. Beneficial effects are observed in patients with psychiatric disorders and enhancement of brain performance in healthy individuals has been observed following tDCS. However, few studies have attempted to elucidate the underlying molecular mechanisms of tDCS in the brain. This study was conducted to assess the impact of tDCS on gene expression within the rat cerebral cortex. Anodal tDCS was applied at 3 different intensities followed by RNA-sequencing and analysis. In each current intensity, approximately 1,000 genes demonstrated statistically significant differences compared to the sham group. A variety of functional pathways, biological processes, and molecular categories were found to be modified by tDCS. The impact of tDCS on gene expression was dependent on current intensity. Results show that inflammatory pathways, antidepressant-related pathways (GTP signaling, calcium ion binding, and transmembrane/signal peptide pathways), and receptor signaling pathways (serotonergic, adrenergic, GABAergic, dopaminergic, and glutamate) were most affected. Of the gene expression profiles induced by tDCS, some changes were observed across multiple current intensities while other changes were unique to a single stimulation intensity. This study demonstrates that tDCS can modify the expression profile of various genes in the cerebral cortex and that these tDCS-induced alterations are dependent on the current intensity applied. PMID:28119786

Transcriptional network inference from functional similarity and expression data: a global supervised approach.

PubMed

Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc

2012-01-06

An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Activation of choline kinase drives aberrant choline metabolism in esophageal squamous cell carcinomas.

PubMed

Ma, Wang; Wang, Shuangyuan; Zhang, Tengfei; Zhang, Erik Y; Zhou, Lina; Hu, Chunxiu; Yu, Jane J; Xu, Guowang

2018-06-05

Esophageal squamous cell carcinoma (ESCC) is a major health threat worldwide. Research focused on molecular events associated with ESCC carcinogenesis for diagnosis, treatment and prevention is needed. Our goal is to discover novel biomarkers and investigate the underlying molecular mechanisms of ESCC progression by employing a global metabolomic approach. Sera from 34 ESCC patients and 32 age and sex matched healthy controls were profiled using two-dimensional liquid chromatography-mass spectrometry (2D LC-MS). We identified 120 differential metabolites in ESCC patient serums compared to healthy controls. Several amino acids, serine, arginine, lysine and histidine were significantly changed in ESCC patients. Most importantly, we found dysregulated lipid metabolism as an important characteristic in ESCC patients. Several free fat acids (FFA) and carnitines were found down-regulated in ESCC patients. Choline was significantly increased and phosphatidylcholines (PC) were significantly decreased in ESCC serum. The high expression of choline and low expression of total PC in patient serum were associated with the high expression of choline kinase (Chok) and activated Kennedy pathway in ESCC cells. Chok expression can serve as a significant biomarker for ESCC prognosis. In conclusion, metabolite profiles in the ESCC patient serum were significantly different from those in the healthy controls. Phosphatidylcholines and Chok, the key enzyme in the PC metabolism pathway, may serve as novel biomarkers for ESCC. Copyright © 2018 Elsevier B.V. All rights reserved.

Microbiota diversity and gene expression dynamics in human oral biofilms

PubMed Central

2014-01-01

Background Micro-organisms inhabiting teeth surfaces grow on biofilms where a specific and complex succession of bacteria has been described by co-aggregation tests and DNA-based studies. Although the composition of oral biofilms is well established, the active portion of the bacterial community and the patterns of gene expression in vivo have not been studied. Results Using RNA-sequencing technologies, we present the first metatranscriptomic study of human dental plaque, performed by two different approaches: (1) A short-reads, high-coverage approach by Illumina sequencing to characterize the gene activity repertoire of the microbial community during biofilm development; (2) A long-reads, lower-coverage approach by pyrosequencing to determine the taxonomic identity of the active microbiome before and after a meal ingestion. The high-coverage approach allowed us to analyze over 398 million reads, revealing that microbial communities are individual-specific and no bacterial species was detected as key player at any time during biofilm formation. We could identify some gene expression patterns characteristic for early and mature oral biofilms. The transcriptomic profile of several adhesion genes was confirmed through qPCR by measuring expression of fimbriae-associated genes. In addition to the specific set of gene functions overexpressed in early and mature oral biofilms, as detected through the short-reads dataset, the long-reads approach detected specific changes when comparing the metatranscriptome of the same individual before and after a meal, which can narrow down the list of organisms responsible for acid production and therefore potentially involved in dental caries. Conclusions The bacteria changing activity during biofilm formation and after meal ingestion were person-specific. Interestingly, some individuals showed extreme homeostasis with virtually no changes in the active bacterial population after food ingestion, suggesting the presence of a microbial community which could be associated to dental health. PMID:24767457

Microbiota diversity and gene expression dynamics in human oral biofilms.

PubMed

Benítez-Páez, Alfonso; Belda-Ferre, Pedro; Simón-Soro, Aurea; Mira, Alex

2014-04-27

Micro-organisms inhabiting teeth surfaces grow on biofilms where a specific and complex succession of bacteria has been described by co-aggregation tests and DNA-based studies. Although the composition of oral biofilms is well established, the active portion of the bacterial community and the patterns of gene expression in vivo have not been studied. Using RNA-sequencing technologies, we present the first metatranscriptomic study of human dental plaque, performed by two different approaches: (1) A short-reads, high-coverage approach by Illumina sequencing to characterize the gene activity repertoire of the microbial community during biofilm development; (2) A long-reads, lower-coverage approach by pyrosequencing to determine the taxonomic identity of the active microbiome before and after a meal ingestion. The high-coverage approach allowed us to analyze over 398 million reads, revealing that microbial communities are individual-specific and no bacterial species was detected as key player at any time during biofilm formation. We could identify some gene expression patterns characteristic for early and mature oral biofilms. The transcriptomic profile of several adhesion genes was confirmed through qPCR by measuring expression of fimbriae-associated genes. In addition to the specific set of gene functions overexpressed in early and mature oral biofilms, as detected through the short-reads dataset, the long-reads approach detected specific changes when comparing the metatranscriptome of the same individual before and after a meal, which can narrow down the list of organisms responsible for acid production and therefore potentially involved in dental caries. The bacteria changing activity during biofilm formation and after meal ingestion were person-specific. Interestingly, some individuals showed extreme homeostasis with virtually no changes in the active bacterial population after food ingestion, suggesting the presence of a microbial community which could be associated to dental health.

Systems-level analysis of cell-specific AQP2 gene expression in renal collecting duct.

PubMed

Yu, Ming-Jiun; Miller, R Lance; Uawithya, Panapat; Rinschen, Markus M; Khositseth, Sookkasem; Braucht, Drew W W; Chou, Chung-Lin; Pisitkun, Trairak; Nelson, Raoul D; Knepper, Mark A

2009-02-17

We used a systems biology-based approach to investigate the basis of cell-specific expression of the water channel aquaporin-2 (AQP2) in the renal collecting duct. Computational analysis of the 5'-flanking region of the AQP2 gene (Genomatix) revealed 2 conserved clusters of putative transcriptional regulator (TR) binding elements (BEs) centered at -513 bp (corresponding to the SF1, NFAT, and FKHD TR families) and -224 bp (corresponding to the AP2, SRF, CREB, GATA, and HOX TR families). Three other conserved motifs corresponded to the ETS, EBOX, and RXR TR families. To identify TRs that potentially bind to these BEs, we carried out mRNA profiling (Affymetrix) in mouse mpkCCDc14 collecting duct cells, revealing expression of 25 TRs that are also expressed in native inner medullary collecting duct. One showed a significant positive correlation with AQP2 mRNA abundance among mpkCCD subclones (Ets1), and 2 showed a significant negative correlation (Elf1 and an orphan nuclear receptor Nr1h2). Transcriptomic profiling in native proximal tubules (PT), medullary thick ascending limbs (MTAL), and IMCDs from kidney identified 14 TRs (including Ets1 and HoxD3) expressed in the IMCD but not PT or MTAL (candidate AQP2 enhancer roles), and 5 TRs (including HoxA5, HoxA9 and HoxA10) expressed in PT and MTAL but not in IMCD (candidate AQP2 repressor roles). In luciferase reporter assays, overexpression of 3 ETS family TRs transactivated the mouse proximal AQP2 promoter. The results implicate ETS family TRs in cell-specific expression of AQP2 and point to HOX, RXR, CREB and GATA family TRs as playing likely additional roles.

Individuality in harpsichord performance: disentangling performer- and piece-specific influences on interpretive choices

PubMed Central

Gingras, Bruno; Asselin, Pierre-Yves; McAdams, Stephen

2013-01-01

Although a growing body of research has examined issues related to individuality in music performance, few studies have attempted to quantify markers of individuality that transcend pieces and musical styles. This study aims to identify such meta-markers by discriminating between influences linked to specific pieces or interpretive goals and performer-specific playing styles, using two complementary statistical approaches: linear mixed models (LMMs) to estimate fixed (piece and interpretation) and random (performer) effects, and similarity analyses to compare expressive profiles on a note-by-note basis across pieces and expressive parameters. Twelve professional harpsichordists recorded three pieces representative of the Baroque harpsichord repertoire, including three interpretations of one of these pieces, each emphasizing a different melodic line, on an instrument equipped with a MIDI console. Four expressive parameters were analyzed: articulation, note onset asynchrony, timing, and velocity. LMMs showed that piece-specific influences were much larger for articulation than for other parameters, for which performer-specific effects were predominant, and that piece-specific influences were generally larger than effects associated with interpretive goals. Some performers consistently deviated from the mean values for articulation and velocity across pieces and interpretations, suggesting that global measures of expressivity may in some cases constitute valid markers of artistic individuality. Similarity analyses detected significant associations among the magnitudes of the correlations between the expressive profiles of different performers. These associations were found both when comparing across parameters and within the same piece or interpretation, or on the same parameter and across pieces or interpretations. These findings suggest the existence of expressive meta-strategies that can manifest themselves across pieces, interpretive goals, or expressive devices. PMID:24348446

Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

PubMed

Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

2015-06-01

White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

Loss of ATRX, associated with DNA methylation pattern of chromosome end, impacted biological behaviors of astrocytic tumors

PubMed Central

Zhang, Wei; Yang, Pei; Zhang, Chuanbao; Li, Mingyang; Yao, Kun; Wang, Hongjun; Li, Qingbin; Jiang, Chuanlu; Jiang, Tao

2015-01-01

Loss of ATRX leads to epigenetic alterations, including abnormal levels of DNA methylation at repetitive elements such as telomeres in murine cells. We conducted an extensive DNA methylation and mRNA expression profile study on a cohort of 82 patients with astrocytic tumors to study whether ATRX expression was associated with DNA methylation level in astrocytic tumors and in which cellular functions it participated. We observed that astrocytic tumors with lower ATRX expression harbored higher DNA methylation level at chromatin end and astrocytic tumors with ATRX-low had distinct gene expression profile and DNA methylation profile compared with ATRX-high tumors. Then, we uncovered that several ATRX associated biological functions in the DNA methylation and mRNA expression profile (GEP), including apoptotic process, DNA-dependent positive regulation of transcription, chromatin modification, and observed that ATRX expression was companied by MGMT methylation and expression. We also found that loss of ATRX caused by siRNA induced apoptotic cells increasing, reduced tumor cell proliferation and repressed the cell migration in glioma cells. Our results showed ATRX-related regulatory functions of the combined profiles from DNA methylation and mRNA expression in astrocytic tumors, and delineated that loss of ATRX impacted biological behaviors of astrocytic tumor cells, providing important resources for future dissection of ATRX role in glioma. PMID:25971279

Loss of ATRX, associated with DNA methylation pattern of chromosome end, impacted biological behaviors of astrocytic tumors.

PubMed

Cai, Jinquan; Chen, Jing; Zhang, Wei; Yang, Pei; Zhang, Chuanbao; Li, Mingyang; Yao, Kun; Wang, Hongjun; Li, Qingbin; Jiang, Chuanlu; Jiang, Tao

2015-07-20

Loss of ATRX leads to epigenetic alterations, including abnormal levels of DNA methylation at repetitive elements such as telomeres in murine cells. We conducted an extensive DNA methylation and mRNA expression profile study on a cohort of 82 patients with astrocytic tumors to study whether ATRX expression was associated with DNA methylation level in astrocytic tumors and in which cellular functions it participated. We observed that astrocytic tumors with lower ATRX expression harbored higher DNA methylation level at chromatin end and astrocytic tumors with ATRX-low had distinct gene expression profile and DNA methylation profile compared with ATRX-high tumors. Then, we uncovered that several ATRX associated biological functions in the DNA methylation and mRNA expression profile (GEP), including apoptotic process, DNA-dependent positive regulation of transcription, chromatin modification, and observed that ATRX expression was companied by MGMT methylation and expression. We also found that loss of ATRX caused by siRNA induced apoptotic cells increasing, reduced tumor cell proliferation and repressed the cell migration in glioma cells. Our results showed ATRX-related regulatory functions of the combined profiles from DNA methylation and mRNA expression in astrocytic tumors, and delineated that loss of ATRX impacted biological behaviors of astrocytic tumor cells, providing important resources for future dissection of ATRX role in glioma.

A nutrigenomics approach for the study of anti-aging interventions: olive oil phenols and the modulation of gene and microRNA expression profiles in mouse brain.

PubMed

Luceri, Cristina; Bigagli, Elisabetta; Pitozzi, Vanessa; Giovannelli, Lisa

2017-03-01

Middle-aged C57Bl/6J mice fed for 6 months with extra-virgin olive oil rich in phenols (H-EVOO, phenol dose/day: 6 mg/kg) showed cognitive and motor improvement compared to controls fed the same olive oil deprived of phenolics (L-EVOO). The aim of the present study was to evaluate whether these behavioral modifications were associated with changes in gene and miRNA expression in the brain. Two brain areas involved in cognitive and motor processes were chosen: cortex and cerebellum. Gene and miRNA profiling were analyzed by microarray and correlated with performance in behavioral tests. After 6 months, most of the gene expression changes were restricted to the cerebral cortex. The genes modulated by aging were mainly down-regulated, and the treatment with H-EVOO was associated with a significant up-regulation of genes compared to L-EVOO. Among those, we found genes previously associated with synaptic plasticity and with motor and cognitive behavior, such as Notch1, BMPs, NGFR, GLP1R and CRTC3. The agrin pathway was also significantly modulated. miRNAs were mostly up-regulated in old L-EVOO animals compared to young. However, H-EVOO-fed mice cortex displayed miRNA expression profiles similar to those observed in young mice. Sixty-three miRNAs, out of 1203 analyzed, were significantly down-regulated compared to the L-EVOO group; among them, we found miRNAs whose predicted target genes were up-regulated by the treatment, such as mir-484, mir-27, mir-137, mir-30, mir-34 and mir-124. We are among the first to report that a dietary intervention starting from middle age with food rich in phenols can modulate at the central level the expression of genes and miRNAs involved in neuronal function and synaptic plasticity, along with cognitive, motor and emotional behavior.

Application of dynamic topic models to toxicogenomics data.

PubMed

Lee, Mikyung; Liu, Zhichao; Huang, Ruili; Tong, Weida

2016-10-06

All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation. In this study, we propose, for the first time, the application of dynamic topic models (DTM) for analyzing time-series gene expression data. A large time-series toxicogenomics dataset was studied. It contains over 3144 microarrays of gene expression data corresponding to rat livers treated with 131 compounds (most are drugs) at two doses (control and high dose) in a repeated schedule containing four separate time points (4-, 8-, 15- and 29-day). We analyzed, with DTM, the topics (consisting of a set of genes) and their biological interpretations over these four time points. We identified hidden patterns embedded in this time-series gene expression profiles. From the topic distribution for compound-time condition, a number of drugs were successfully clustered by their shared mode-of-action such as PPARɑ agonists and COX inhibitors. The biological meaning underlying each topic was interpreted using diverse sources of information such as functional analysis of the pathways and therapeutic uses of the drugs. Additionally, we found that sample clusters produced by DTM are much more coherent in terms of functional categories when compared to traditional clustering algorithms. We demonstrated that DTM, a text mining technique, can be a powerful computational approach for clustering time-series gene expression profiles with the probabilistic representation of their dynamic features along sequential time frames. The method offers an alternative way for uncovering hidden patterns embedded in time series gene expression profiles to gain enhanced understanding of dynamic behavior of gene regulation in the biological system.

Examining the Genetic Background of Porcine Muscle Growth and Development Based on Transcriptome and miRNAome Data.

PubMed

Ropka-Molik, Katarzyna; Pawlina-Tyszko, Klaudia; Żukowski, Kacper; Piórkowska, Katarzyna; Żak, Grzegorz; Gurgul, Artur; Derebecka, Natalia; Wesoły, Joanna

2018-04-16

Recently, selection in pigs has been focused on improving the lean meat content in carcasses; this focus has been most evident in breeds constituting a paternal component in breeding. Such sire-breeds are used to improve the meat quantity of cross-breed pig lines. However, even in one breed, a significant variation in the meatiness level can be observed. In the present study, the comprehensive analysis of genes and microRNA expression profiles in porcine muscle tissue was applied to identify the genetic background of meat content. The comparison was performed between whole gene expression and miRNA profiles of muscle tissue collected from two sire-line pig breeds (Pietrain, Hampshire). The RNA-seq approach allowed the identification of 627 and 416 differentially expressed genes (DEGs) between pig groups differing in terms of loin weight between Pietrain and Hampshire breeds, respectively. The comparison of miRNA profiles showed differential expression of 57 microRNAs for Hampshire and 34 miRNAs for Pietrain pigs. Next, 43 genes and 18 miRNAs were selected as differentially expressed in both breeds and potentially related to muscle development. According to Gene Ontology analysis, identified DEGs and microRNAs were involved in the regulation of the cell cycle, fatty acid biosynthesis and regulation of the actin cytoskeleton. The most deregulated pathways dependent on muscle mass were the Hippo signalling pathway connected with the TGF-β signalling pathway and controlling organ size via the regulation of ubiquitin-mediated proteolysis, cell proliferation and apoptosis. The identified target genes were also involved in pathways such as the FoxO signalling pathway, signalling pathways regulating pluripotency of stem cells and the PI3K-Akt signalling pathway. The obtained results indicate molecular mechanisms controlling porcine muscle growth and development. Identified genes ( SOX2 , SIRT1 , KLF4 , PAX6 and genes belonging to the transforming growth factor beta superfamily) could be considered candidate genes for determining muscle mass in pigs.

Two-dimensional gel analysis of protein expression in ovarian tumors shows a low degree of intratumoral heterogeneity.

PubMed

Alaiya, A A; Franzén, B; Moberger, B; Silfverswärd, C; Linder, S; Auer, G

1999-01-01

The process of tumor progression leads to the emergence of multiple clones, and to the development of tumor heterogeneity. One approach to the study of the extent of such heterogeneity is to examine the expression of marker proteins in different tumor areas. Two-dimensional gel electrophoresis (2-DE) is a powerful tool for such studies, since the expression of a large number of polypeptide markers can be evaluated. In the present study, tumor cells were prepared from human ovarian tumors and analyzed by 2-DE and PDQUEST. As judged from the analysis of two different areas in each of nine ovarian tumors, the intratumoral variation in protein expression was low. In contrast, large differences were observed when the protein profiles of different tumors were compared. The differences in gene expression between pairs of malignant carcinomas were slightly larger than the differences observed between pairs of benign tumors. We conclude that 2-DE analysis of intratumoral heterogeneity in ovarian cancer tissue indicates a low degree of heterogeneity.

A microcosm of musical expression: II. Quantitative analysis of pianists' dynamics in the initial measures of Chopin's Etude in E major.

PubMed

Repp, B H

1999-03-01

Patterns of expressive dynamics were measured in bars 1-5 of 115 commercially recorded performances of Chopin's Etude in E major, op. 10, No. 3. The grand average pattern (or dynamic profile) was representative of many performances and highly similar to the average dynamic profile of a group of advanced student performances, which suggests a widely shared central norm of expressive dynamics. The individual dynamic profiles were subjected to principal components analysis, which yielded Varimax-rotated components, each representing a different, nonstandard dynamic profile associated with a small subset of performances. Most performances had dynamic patterns resembling a mixture of several components, and no clustering of of performances into distinct groups was apparent. Some weak relationships of dynamic profiles with sociocultural variables were found, most notably a tendency of female pianists to exhibit a greater dynamic range in the melody. Within the melody, there were no significant relationships between expressive timing [Repp, J. Acoust. Soc. Am. 104, 1085-1100 (1998)] and expressive dynamics. These two important dimensions seemed to be controlled independently at this local level and thus offer the artist many degrees of freedom in giving a melody expressive shape.

Medroxyprogesterone acetate-treated human, primary endometrial epithelial cells reveal unique gene expression signature linked to innate immunity and HIV-1 susceptibility.

PubMed

Woods, Matthew W; Zahoor, Muhammad Atif; Dizzell, Sara; Verschoor, Chris P; Kaushic, Charu

2018-01-01

Medroxyprogesterone acetate (MPA), a progestin-based hormonal contraceptive designed to mimic progesterone, has been linked to increased human immunodeficiency virus (HIV-1) susceptibility. Genital epithelial cells (GECs) form the mucosal lining of the female genital tract (FGT) and provide the first line of protection against HIV-1. The impact of endogenous sex hormones or MPA on the gene expression profile of GECs has not been comprehensively documented. Using microarray analysis, we characterized the transcriptional profile of primary endometrial epithelial cells grown in physiological levels of E2, P4, and MPA. Each hormone treatment altered the gene expression profile of GECs in a unique manner. Interestingly, although MPA is a progestogen, the gene expression profile induced by it was distinct from P4. MPA increased gene expression of genes related to inflammation and cholesterol synthesis linked to innate immunity and HIV-1 susceptibility. The analysis of gene expression profiles provides insights into the effects of sex hormones and MPA on GECs and allows us to posit possible mechanisms of the MPA-mediated increase in HIV-1 acquisition. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Label-free Quantitative Protein Profiling of vastus lateralis Muscle During Human Aging*

PubMed Central

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers. PMID:24217021

Label-free quantitative protein profiling of vastus lateralis muscle during human aging.

PubMed

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers.

Synergistic Activation of Latent HIV-1 Expression by Novel Histone Deacetylase Inhibitors and Bryostatin-1.

PubMed

Martínez-Bonet, Marta; Clemente, Maria Isabel; Serramía, Maria Jesús; Muñoz, Eduardo; Moreno, Santiago; Muñoz-Fernández, Maria Ángeles

2015-11-13

Viral reactivation from latently infected cells has become a promising therapeutic approach to eradicate HIV. Due to the complexity of the viral latency, combinations of efficient and available drugs targeting different pathways of latency are needed. In this work, we evaluated the effect of various combinations of bryostatin-1 (BRY) and novel histone deacetylase inhibitors (HDACIs) on HIV-reactivation and on cellular phenotype. The lymphocyte (J89GFP) or monocyte/macrophage (THP89GFP) latently infected cell lines were treated with BRY, panobinostat (PNB) and romidepsin (RMD) either alone or in combination. Thus, the effect on the viral reactivation was evaluated. We calculated the combination index for each drug combination; the BRY/HDACIs showed a synergistic HIV-reactivation profile in the majority of the combinations tested, whereas non-synergistic effects were observed when PNB was mixed with RMD. Indeed, the 75% effective concentrations of BRY, PNB and RMD were reduced in these combinations. Moreover, primary CD4 T cells treated with such drug combinations presented similar activation and proliferation profiles in comparison with single drug treated cells. Summing up, combinations between BRY, PNB and/or RMD presented a synergistic profile by inducing virus expression in HIV-latently infected cells, rendering these combinations an attractive novel and safe option for future clinical trials.

Single-cell gene expression analysis reveals diversity among human spermatogonia.

PubMed

Neuhaus, N; Yoon, J; Terwort, N; Kliesch, S; Seggewiss, J; Huge, A; Voss, R; Schlatt, S; Grindberg, R V; Schöler, H R

2017-02-10

Is the molecular profile of human spermatogonia homogeneous or heterogeneous when analysed at the single-cell level? Heterogeneous expression profiles may be a key characteristic of human spermatogonia, supporting the existence of a heterogeneous stem cell population. Despite the fact that many studies have sought to identify specific markers for human spermatogonia, the molecular fingerprint of these cells remains hitherto unknown. Testicular tissues from patients with spermatogonial arrest (arrest, n = 1) and with qualitatively normal spermatogenesis (normal, n = 7) were selected from a pool of 179 consecutively obtained biopsies. Gene expression analyses of cell populations and single-cells (n = 105) were performed. Two OCT4-positive individual cells were selected for global transcriptional capture using shallow RNA-seq. Finally, expression of four candidate markers was assessed by immunohistochemistry. Histological analysis and blood hormone measurements for LH, FSH and testosterone were performed prior to testicular sample selection. Following enzymatic digestion of testicular tissues, differential plating and subsequent micromanipulation of individual cells was employed to enrich and isolate human spermatogonia, respectively. Endpoint analyses were qPCR analysis of cell populations and individual cells, shallow RNA-seq and immunohistochemical analyses. Unexpectedly, single-cell expression data from the arrest patient (20 cells) showed heterogeneous expression profiles. Also, from patients with normal spermatogenesis, heterogeneous expression patterns of undifferentiated (OCT4, UTF1 and MAGE A4) and differentiated marker genes (BOLL and PRM2) were obtained within each spermatogonia cluster (13 clusters with 85 cells). Shallow RNA-seq analysis of individual human spermatogonia was validated, and a spermatogonia-specific heterogeneous protein expression of selected candidate markers (DDX5, TSPY1, EEF1A1 and NGN3) was demonstrated. The heterogeneity of human spermatogonia at the RNA and protein levels is a snapshot. To further assess the functional meaning of this heterogeneity and the dynamics of stem cell populations, approaches need to be developed to facilitate the repeated analysis of individual cells. Our data suggest that heterogeneous expression profiles may be a key characteristic of human spermatogonia, supporting the model of a heterogeneous stem cell population. Future studies will assess the dynamics of spermatogonial populations in fertile and infertile patients. RNA-seq data is published in the GEO database: GSE91063. This work was supported by the Max Planck Society and the Deutsche Forschungsgemeinschaft DFG-Research Unit FOR 1041 Germ Cell Potential (grant numbers SCHO 340/7-1, SCHL394/11-2). The authors declare that there is no conflict of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

DEVELOPMENT OF PROTEIN PROFILE TECHNOLOGY TO EVALUATE ECOLOGICAL EFFECTS OF ENVIRONMENTAL CHEMICALS USING A SMALL FISH MODEL

EPA Science Inventory

The rationale for this research is: i) Protein expression changes with life stage, disease, tissue type and environmental stressors; ii) Technology allows rapid analysis of large numbers of proteins to provide protein expression profiles; iii) Protein profiles are used as specifi...

Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.

PubMed

Xu, Joshua; Gong, Binsheng; Wu, Leihong; Thakkar, Shraddha; Hong, Huixiao; Tong, Weida

2016-03-15

Studies on gene expression in response to therapy have led to the discovery of pharmacogenomics biomarkers and advances in precision medicine. Whole transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene expression and has received wide adoption in the biomedical research community. However, its value in regulatory decision making requires rigorous assessment and consensus between various stakeholders, including the research community, regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC) consortium has made considerable progress in this direction, and is the subject of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites to assess cross-site and cross-platform reproducibility. The results demonstrated that relative gene expression measurements were consistently comparable across labs and platforms, but not so for the measurement of absolute expression levels. As part of the quality evaluation several studies were included to evaluate the utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma study profiled tumor samples from 498 pediatric neuroblastoma patients by both microarray and RNA-seq. RNA-seq offers more utilities than microarray in determining the transcriptomic characteristics of cancer. However, RNA-seq and microarray-based models were comparable in clinical endpoint prediction, even when including additional features unique to RNA-seq beyond gene expression. The toxicogenomics study compared microarray and RNA-seq profiles of the liver samples from rats exposed to 27 different chemicals representing multiple toxicity modes of action. Cross-platform concordance was dependent on chemical treatment and transcript abundance. Though both RNA-seq and microarray are suitable for developing gene expression based predictive models with comparable prediction performance, RNA-seq offers advantages over microarray in profiling genes with low expression. The rat BodyMap study provided a comprehensive rat transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the transferability study demonstrated that signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development using a comprehensive approach with two large clinical data sets. This result suggests continued usefulness of legacy microarray data in the coming RNA-seq era. In conclusion, the SEQC project enhances our understanding of RNA-seq and provides valuable guidelines for RNA-seq based clinical application and safety evaluation to advance precision medicine.

The Combined Effects of Ethylene and MeJA on Metabolic Profiling of Phenolic Compounds in Catharanthus roseus Revealed by Metabolomics Analysis

PubMed Central

Liu, Jia; Liu, Yang; Wang, Yu; Zhang, Zhong-Hua; Zu, Yuan-Gang; Efferth, Thomas; Tang, Zhong-Hua

2016-01-01

Phenolic compounds belong to a class of secondary metabolites and are implicated in a wide range of responsive mechanisms in plants triggered by both biotic and abiotic elicitors. In this study, we approached the combinational effects of ethylene and MeJA (methyl jasmonate) on phenolic compounds profiles and gene expressions in the medicinal plant Catharanthus roseus. In virtue of a widely non-targeted metabolomics method, we identified a total of 34 kinds of phenolic compounds in the leaves, composed by 7 C6C1-, 11 C6C3-, and 16 C6C3C6 compounds. In addition, 7 kinds of intermediates critical for the biosynthesis of phenolic compounds and alkaloids were identified and discussed with phenolic metabolism. The combinational actions of ethylene and MeJA effectively promoted the total phenolic compounds, especially the C6C1 compounds (such as salicylic acid, benzoic acid) and C6C3 ones (such as cinnamic acid, sinapic acid). In contrast, the C6C3C6 compounds displayed a notably inhibitory trend in this case. Subsequently, the gene-to-metabolite networks were drawn up by searching for correlations between the expression profiles of 5 gene tags and the accumulation profiles of 41 metabolite peaks. Generally, we provide an insight into the controlling mode of ethylene-MeJA combination on phenolic metabolism in C. roseus leaves. PMID:27375495

The Combined Effects of Ethylene and MeJA on Metabolic Profiling of Phenolic Compounds in Catharanthus roseus Revealed by Metabolomics Analysis.

PubMed

Liu, Jia; Liu, Yang; Wang, Yu; Zhang, Zhong-Hua; Zu, Yuan-Gang; Efferth, Thomas; Tang, Zhong-Hua

2016-01-01

Phenolic compounds belong to a class of secondary metabolites and are implicated in a wide range of responsive mechanisms in plants triggered by both biotic and abiotic elicitors. In this study, we approached the combinational effects of ethylene and MeJA (methyl jasmonate) on phenolic compounds profiles and gene expressions in the medicinal plant Catharanthus roseus. In virtue of a widely non-targeted metabolomics method, we identified a total of 34 kinds of phenolic compounds in the leaves, composed by 7 C6C1-, 11 C6C3-, and 16 C6C3C6 compounds. In addition, 7 kinds of intermediates critical for the biosynthesis of phenolic compounds and alkaloids were identified and discussed with phenolic metabolism. The combinational actions of ethylene and MeJA effectively promoted the total phenolic compounds, especially the C6C1 compounds (such as salicylic acid, benzoic acid) and C6C3 ones (such as cinnamic acid, sinapic acid). In contrast, the C6C3C6 compounds displayed a notably inhibitory trend in this case. Subsequently, the gene-to-metabolite networks were drawn up by searching for correlations between the expression profiles of 5 gene tags and the accumulation profiles of 41 metabolite peaks. Generally, we provide an insight into the controlling mode of ethylene-MeJA combination on phenolic metabolism in C. roseus leaves.

SH2 Domain Histochemistry.

PubMed

Buhs, Sophia; Nollau, Peter

2017-01-01

Among posttranslational modifications, the phosphorylation of tyrosine residues is a key modification in cell signaling. Because of its biological importance, characterization of the cellular state of tyrosine phosphorylation is of great interest. Based on the unique properties of endogenously expressed SH2 domains recognizing tyrosine phosphorylated signaling proteins with high specificity we have developed an alternative approach, coined SH2 profiling, enabling us to decipher complex patterns of tyrosine phosphorylation in various normal and cancerous tissues. So far, SH2 profiling has largely been applied for the analysis of protein extracts with the limitation that information on spatial distribution and intensity of tyrosine phosphorylation within a tissue is lost. Here, we describe a novel SH2 domain based strategy for differential characterization of the state of tyrosine phosphorylation in formaldehyde-fixed and paraffin-embedded tissues. This approach demonstrates that SH2 domains may serve as very valuable tools for the analysis of the differential state of tyrosine phosphorylation in primary tissues fixed and processed under conditions frequently applied by routine pathology laboratories.

Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation

PubMed Central

Xu, Yaomin; Guo, Xingyi; Sun, Jiayang; Zhao, Zhongming

2015-01-01

Motivation: Large-scale cancer genomic studies, such as The Cancer Genome Atlas (TCGA), have profiled multidimensional genomic data, including mutation and expression profiles on a variety of cancer cell types, to uncover the molecular mechanism of cancerogenesis. More than a hundred driver mutations have been characterized that confer the advantage of cell growth. However, how driver mutations regulate the transcriptome to affect cellular functions remains largely unexplored. Differential analysis of gene expression relative to a driver mutation on patient samples could provide us with new insights in understanding driver mutation dysregulation in tumor genome and developing personalized treatment strategies. Results: Here, we introduce the Snowball approach as a highly sensitive statistical analysis method to identify transcriptional signatures that are affected by a recurrent driver mutation. Snowball utilizes a resampling-based approach and combines a distance-based regression framework to assign a robust ranking index of genes based on their aggregated association with the presence of the mutation, and further selects the top significant genes for downstream data analyses or experiments. In our application of the Snowball approach to both synthesized and TCGA data, we demonstrated that it outperforms the standard methods and provides more accurate inferences to the functional effects and transcriptional dysregulation of driver mutations. Availability and implementation: R package and source code are available from CRAN at http://cran.r-project.org/web/packages/DESnowball, and also available at http://bioinfo.mc.vanderbilt.edu/DESnowball/. Contact: zhongming.zhao@vanderbilt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25192743

Overview of research on Bombyx mori microRNA

PubMed Central

Wang, Xin; Tang, Shun-ming; Shen, Xing-jia

2014-01-01

Abstract MicroRNAs (miRNAs) constitute some of the most significant regulatory factors involved at the post-transcriptional level after gene expression, contributing to the modulation of a large number of physiological processes such as development, metabolism, and disease occurrence. This review comprehensively and retrospectively explores the literature investigating silkworm, Bombyx mori L. (Lepidoptera: Bombicidae), miRNAs published to date, including discovery, identification, expression profiling analysis, target gene prediction, and the functional analysis of both miRNAs and their targets. It may provide experimental considerations and approaches for future study of miRNAs and benefit elucidation of the mechanisms of miRNAs involved in silkworm developmental processes and intracellular activities of other unknown non-coding RNAs. PMID:25368077

Aureolib — A Proteome Signature Library: Towards an Understanding of Staphylococcus aureus Pathophysiology

PubMed Central

Pané-Farré, Jan; Kusch, Harald; Wolf, Carmen; Reiß, Swantje; Binh, Le Thi Nguyen; Albrecht, Dirk; Riedel, Katharina; Hecker, Michael; Engelmann, Susanne

2013-01-01

Gel-based proteomics is a powerful approach to study the physiology of Staphylococcus aureus under various growth restricting conditions. We analyzed 679 protein spots from a reference 2-dimensional gel of cytosolic proteins of S. aureus COL by mass spectrometry resulting in 521 different proteins. 4,692 time dependent protein synthesis profiles were generated by exposing S. aureus to nine infection-related stress and starvation stimuli (H2O2, diamide, paraquat, NO, fermentation, nitrate respiration, heat shock, puromycin, mupirocin). These expression profiles are stored in an online resource called Aureolib (http://www.aureolib.de). Moreover, information on target genes of 75 regulators and regulatory elements were included in the database. Cross-comparisons of this extensive data collection of protein synthesis profiles using the tools implemented in Aureolib lead to the identification of stress and starvation specific marker proteins. Altogether, 226 protein synthesis profiles showed induction ratios of 2.5-fold or higher under at least one of the tested conditions with 157 protein synthesis profiles specifically induced in response to a single stimulus. The respective proteins might serve as marker proteins for the corresponding stimulus. By contrast, proteins whose synthesis was increased or repressed in response to more than four stimuli are rather exceptional. The only protein that was induced by six stimuli is the universal stress protein SACOL1759. Most strikingly, cluster analyses of synthesis profiles of proteins differentially synthesized under at least one condition revealed only in rare cases a grouping that correlated with known regulon structures. The most prominent examples are the GapR, Rex, and CtsR regulon. In contrast, protein synthesis profiles of proteins belonging to the CodY and σB regulon are widely distributed. In summary, Aureolib is by far the most comprehensive protein expression database for S. aureus and provides an essential tool to decipher more complex adaptation processes in S. aureus during host pathogen interaction. PMID:23967085