Sample records for expression profiling based
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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.
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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.
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Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena
2004-01-01
Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086
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Gene expression inference with deep learning.
Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui
2016-06-15
Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu 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.
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Gene expression inference with deep learning
Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui
2016-01-01
Motivation: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. Results: We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929
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Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David
2001-01-01
Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681
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iPcc: a novel feature extraction method for accurate disease class discovery and prediction
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
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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.
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Analyzing gene expression time-courses based on multi-resolution shape mixture model.
Li, Ying; He, Ye; Zhang, Yu
2016-11-01
Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.
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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
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Activity-based protein profiling for biochemical pathway discovery in cancer
Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.
2011-01-01
Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252
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Zhang, Ao; Tian, Suyan
2018-05-01
Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis
Dinalankara, Wikum; Bravo, Héctor Corrada
2015-01-01
Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586
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Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies.
Haimon, Zhana; Volaski, Alon; Orthgiess, Johannes; Boura-Halfon, Sigalit; Varol, Diana; Shemer, Anat; Yona, Simon; Zuckerman, Binyamin; David, Eyal; Chappell-Maor, Louise; Bechmann, Ingo; Gericke, Martin; Ulitsky, Igor; Jung, Steffen
2018-06-01
Transcriptome profiling is widely used to infer functional states of specific cell types, as well as their responses to stimuli, to define contributions to physiology and pathophysiology. Focusing on microglia, the brain's macrophages, we report here a side-by-side comparison of classical cell-sorting-based transcriptome sequencing and the 'RiboTag' method, which avoids cell retrieval from tissue context and yields translatome sequencing information. Conventional whole-cell microglial transcriptomes were found to be significantly tainted by artifacts introduced by tissue dissociation, cargo contamination and transcripts sequestered from ribosomes. Conversely, our data highlight the added value of RiboTag profiling for assessing the lineage accuracy of Cre recombinase expression in transgenic mice. Collectively, this study indicates method-based biases, reveals observer effects and establishes RiboTag-based translatome profiling as a valuable complement to standard sorting-based profiling strategies.
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Debey-Pascher, Svenja; Hofmann, Andrea; Kreusch, Fatima; Schuler, Gerold; Schuler-Thurner, Beatrice; Schultze, Joachim L.; Staratschek-Jox, Andrea
2011-01-01
Microarray-based transcriptome analysis of peripheral blood as surrogate tissue has become an important approach in clinical implementations. However, application of gene expression profiling in routine clinical settings requires careful consideration of the influence of sample handling and RNA isolation methods on gene expression profile outcome. We evaluated the effect of different sample preservation strategies (eg, cryopreservation of peripheral blood mononuclear cells or freezing of PAXgene-stabilized whole blood samples) on gene expression profiles. Expression profiles obtained from cryopreserved peripheral blood mononuclear cells differed substantially from those of their nonfrozen counterpart samples. Furthermore, expression profiles in cryopreserved peripheral blood mononuclear cell samples were found to undergo significant alterations with increasing storage period, whereas long-term freezing of PAXgene RNA stabilized whole blood samples did not significantly affect stability of gene expression profiles. This report describes important technical aspects contributing toward the establishment of robust and reliable guidance for gene expression studies using peripheral blood and provides a promising strategy for reliable implementation in routine handling for diagnostic purposes. PMID:21704280
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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
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Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T
2017-10-01
Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.
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Discovering functional modules by topic modeling RNA-Seq based toxicogenomic data.
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.
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Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko
2016-06-01
Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.
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Malinowski, Douglas P
2007-05-01
In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.
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Kayano, Mitsunori; Matsui, Hidetoshi; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru
2016-04-01
High-throughput time course expression profiles have been available in the last decade due to developments in measurement techniques and devices. Functional data analysis, which treats smoothed curves instead of originally observed discrete data, is effective for the time course expression profiles in terms of dimension reduction, robustness, and applicability to data measured at small and irregularly spaced time points. However, the statistical method of differential analysis for time course expression profiles has not been well established. We propose a functional logistic model based on elastic net regularization (F-Logistic) in order to identify the genes with dynamic alterations in case/control study. We employ a mixed model as a smoothing method to obtain functional data; then F-Logistic is applied to time course profiles measured at small and irregularly spaced time points. We evaluate the performance of F-Logistic in comparison with another functional data approach, i.e. functional ANOVA test (F-ANOVA), by applying the methods to real and synthetic time course data sets. The real data sets consist of the time course gene expression profiles for long-term effects of recombinant interferon β on disease progression in multiple sclerosis. F-Logistic distinguishes dynamic alterations, which cannot be found by competitive approaches such as F-ANOVA, in case/control study based on time course expression profiles. F-Logistic is effective for time-dependent biomarker detection, diagnosis, and therapy. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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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
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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.
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Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che
2013-01-01
Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826
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MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype.
Blenkiron, Cherie; Goldstein, Leonard D; Thorne, Natalie P; Spiteri, Inmaculada; Chin, Suet-Feung; Dunning, Mark J; Barbosa-Morais, Nuno L; Teschendorff, Andrew E; Green, Andrew R; Ellis, Ian O; Tavaré, Simon; Caldas, Carlos; Miska, Eric A
2007-01-01
MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression. Here we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed. This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.
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Zhan, Siyuan; Zhao, Wei; Song, Tianzeng; Dong, Yao; Guo, Jiazhong; Cao, Jiaxue; Zhong, Tao; Wang, Linjie; Li, Li; Zhang, Hongping
2018-01-01
Muscle growth and development from fetal to neonatal stages consist of a series of delicately regulated and orchestrated changes in expression of genes. In this study, we performed whole transcriptome profiling based on RNA-Seq of caprine longissimus dorsi muscle tissue obtained from prenatal stages (days 45, 60, and 105 of gestation) and neonatal stage (the 3-day-old newborn) to identify genes that are differentially expressed and investigate their temporal expression profiles. A total of 3276 differentially expressed genes (DEGs) were identified (Q value < 0.01). Time-series expression profile clustering analysis indicated that DEGs were significantly clustered into eight clusters which can be divided into two classes (Q value < 0.05), class I profiles with downregulated patterns and class II profiles with upregulated patterns. Based on cluster analysis, GO enrichment analysis found that 75, 25, and 8 terms to be significantly enriched in biological process (BP), cellular component (CC), and molecular function (MF) categories in class I profiles, while 35, 21, and 8 terms to be significantly enriched in BP, CC, and MF in class II profiles. KEGG pathway analysis revealed that DEGs from class I profiles were significantly enriched in 22 pathways and the most enriched pathway was Rap1 signaling pathway. DEGs from class II profiles were significantly enriched in 17 pathways and the mainly enriched pathway was AMPK signaling pathway. Finally, six selected DEGs from our sequencing results were confirmed by qPCR. Our study provides a comprehensive understanding of the molecular mechanisms during goat skeletal muscle development from fetal to neonatal stages and valuable information for future studies of muscle development in goats.
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Lung tumor diagnosis and subtype discovery by gene expression profiling.
Wang, Lu-yong; Tu, Zhuowen
2006-01-01
The optimal treatment of patients with complex diseases, such as cancers, depends on the accurate diagnosis by using a combination of clinical and histopathological data. In many scenarios, it becomes tremendously difficult because of the limitations in clinical presentation and histopathology. To accurate diagnose complex diseases, the molecular classification based on gene or protein expression profiles are indispensable for modern medicine. Moreover, many heterogeneous diseases consist of various potential subtypes in molecular basis and differ remarkably in their response to therapies. It is critical to accurate predict subgroup on disease gene expression profiles. More fundamental knowledge of the molecular basis and classification of disease could aid in the prediction of patient outcome, the informed selection of therapies, and identification of novel molecular targets for therapy. In this paper, we propose a new disease diagnostic method, probabilistic boosting tree (PB tree) method, on gene expression profiles of lung tumors. It enables accurate disease classification and subtype discovery in disease. It automatically constructs a tree in which each node combines a number of weak classifiers into a strong classifier. Also, subtype discovery is naturally embedded in the learning process. Our algorithm achieves excellent diagnostic performance, and meanwhile it is capable of detecting the disease subtype based on gene expression profile.
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Obermeier, Christian; Hosseini, Bashir; Friedt, Wolfgang; Snowdon, Rod
2009-01-01
Background Serial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species. PMID:19575793
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ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.
Dvorak, Pavel; Pesta, Martin; Soucek, Pavel
2017-05-01
Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various cancers. Graphical abstract.
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Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.
2012-01-01
The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245
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Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.
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.
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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.
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Barat, Ana; Ruskin, Heather J; Byrne, Annette T; Prehn, Jochen H M
2015-11-23
Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.
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Barat, Ana; Ruskin, Heather J.; Byrne, Annette T.; Prehn, Jochen H. M.
2015-01-01
Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype. PMID:27600244
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Vrahatis, Aristidis G; Dimitrakopoulos, Georgios N; Tsakalidis, Athanasios K; Bezerianos, Anastasios
2015-01-01
In the road for network medicine the newly emerged systems-level subpathway-based analysis methods offer new disease genes, drug targets and network-based biomarkers. In parallel, paired miRNA/mRNA expression data enable simultaneously monitoring of the micronome effect upon the signaling pathways. Towards this orientation, we present a methodological pipeline for the identification of differentially expressed subpathways along with their miRNA regulators by using KEGG signaling pathway maps, miRNA-target interactions and expression profiles from paired miRNA/mRNA experiments. Our pipeline offered new biological insights on a real application of paired miRNA/mRNA expression profiles with respect to the dynamic changes from colostrum to mature milk whey; several literature supported genes and miRNAs were recontextualized through miRNA-mediated differentially expressed subpathways.
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Discriminating Down Syndrome and Fragile X Syndrome Based on Language Ability
ERIC Educational Resources Information Center
Finestack, Lizbeth H.; Sterling, Audra M.; Abbeduto, Leonard
2013-01-01
This study compared the receptive and expressive language profiles of verbally expressive children and adolescents with Down Syndrome (DS) and those with Fragile X syndrome (FXS) and examined the extent to which these profiles reliably differentiate the diagnostic groups. A total of twenty-four verbal participants with DS (mean age: 12 years),…
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ERIC Educational Resources Information Center
McDuffie, Andrea; Kover, Sara; Abbeduto, Leonard; Lewis, Pamela; Brown, Ted
2012-01-01
The authors examined receptive and expressive language profiles for a group of verbal male children and adolescents who had fragile X syndrome along with varying degrees of autism symptoms. A categorical approach for assigning autism diagnostic classification, based on the combined use of the Autism Diagnostic Interview--Revised and the Autism…
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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.
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Zhou, Wei; Song, Xiang-gang; Chen, Chao; Wang, Shu-mei; Liang, Sheng-wang
2015-08-01
Action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis were discussed based on gene expression profile and molecular fingerprint in this paper. First, gene expression profiles of atherosclerotic carotid artery tissues and histologically normal tissues in human body were collected, and were screened using significance analysis of microarray (SAM) to screen out differential gene expressions; then differential genes were analyzed by Gene Ontology (GO) analysis and KEGG pathway analysis; to avoid some genes with non-outstanding differential expression but biologically importance, Gene Set Enrichment Analysis (GSEA) were performed, and 7 chemical ingredients with higher negative enrichment score were obtained by Cmap method, implying that they could reversely regulate the gene expression profiles of pathological tissues; and last, based on the hypotheses that similar structures have similar activities, 336 ingredients of compound Danshen dripping pills were compared with 7 drug molecules in 2D molecular fingerprints method. The results showed that 147 differential genes including 60 up-regulated genes and 87 down regulated genes were screened out by SAM. And in GO analysis, Biological Process ( BP) is mainly concerned with biological adhesion, response to wounding and inflammatory response; Cellular Component (CC) is mainly concerned with extracellular region, extracellular space and plasma membrane; while Molecular Function (MF) is mainly concerned with antigen binding, metalloendopeptidase activity and peptide binding. KEGG pathway analysis is mainly concerned with JAK-STAT, RIG-I like receptor and PPAR signaling pathway. There were 10 compounds, such as hexadecane, with Tanimoto coefficients greater than 0.85, which implied that they may be the active ingredients (AIs) of compound Danshen dripping pills in treatment of carotid atherosclerosis (CAs). The present method can be applied to the research on material base and molecular action mechanism of TCM.
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A high-throughput microRNA expression profiling system.
Guo, Yanwen; Mastriano, Stephen; Lu, Jun
2014-01-01
As small noncoding RNAs, microRNAs (miRNAs) regulate diverse biological functions, including physiological and pathological processes. The expression and deregulation of miRNA levels contain rich information with diagnostic and prognostic relevance and can reflect pharmacological responses. The increasing interest in miRNA-related research demands global miRNA expression profiling on large numbers of samples. We describe here a robust protocol that supports high-throughput sample labeling and detection on hundreds of samples simultaneously. This method employs 96-well-based miRNA capturing from total RNA samples and on-site biochemical reactions, coupled with bead-based detection in 96-well format for hundreds of miRNAs per sample. With low-cost, high-throughput, high detection specificity, and flexibility to profile both small and large numbers of samples, this protocol can be adapted in a wide range of laboratory settings.
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microRNA Expression Profiling: Technologies, Insights, and Prospects.
Roden, Christine; Mastriano, Stephen; Wang, Nayi; Lu, Jun
2015-01-01
Since the early days of microRNA (miRNA) research, miRNA expression profiling technologies have provided important tools toward both better understanding of the biological functions of miRNAs and using miRNA expression as potential diagnostics. Multiple technologies, such as microarrays, next-generation sequencing, bead-based detection system, single-molecule measurements, and quantitative RT-PCR, have enabled accurate quantification of miRNAs and the subsequent derivation of key insights into diverse biological processes. As a class of ~22 nt long small noncoding RNAs, miRNAs present unique challenges in expression profiling that require careful experimental design and data analyses. We will particularly discuss how normalization and the presence of miRNA isoforms can impact data interpretation. We will present one example in which the consideration in data normalization has provided insights that helped to establish the global miRNA expression as a tumor suppressor. Finally, we discuss two future prospects of using miRNA profiling technologies to understand single cell variability and derive new rules for the functions of miRNA isoforms.
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PmiRExAt: plant miRNA expression atlas database and web applications
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
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Quinn, Michael C J; Wilson, Daniel J; Young, Fiona; Dempsey, Adam A; Arcand, Suzanna L; Birch, Ashley H; Wojnarowicz, Paulina M; Provencher, Diane; Mes-Masson, Anne-Marie; Englert, David; Tonin, Patricia N
2009-07-06
As gene expression signatures may serve as biomarkers, there is a need to develop technologies based on mRNA expression patterns that are adaptable for translational research. Xceed Molecular has recently developed a Ziplex technology, that can assay for gene expression of a discrete number of genes as a focused array. The present study has evaluated the reproducibility of the Ziplex system as applied to ovarian cancer research of genes shown to exhibit distinct expression profiles initially assessed by Affymetrix GeneChip analyses. The new chemiluminescence-based Ziplex gene expression array technology was evaluated for the expression of 93 genes selected based on their Affymetrix GeneChip profiles as applied to ovarian cancer research. Probe design was based on the Affymetrix target sequence that favors the 3' UTR of transcripts in order to maximize reproducibility across platforms. Gene expression analysis was performed using the Ziplex Automated Workstation. Statistical analyses were performed to evaluate reproducibility of both the magnitude of expression and differences between normal and tumor samples by correlation analyses, fold change differences and statistical significance testing. Expressions of 82 of 93 (88.2%) genes were highly correlated (p < 0.01) in a comparison of the two platforms. Overall, 75 of 93 (80.6%) genes exhibited consistent results in normal versus tumor tissue comparisons for both platforms (p < 0.001). The fold change differences were concordant for 87 of 93 (94%) genes, where there was agreement between the platforms regarding statistical significance for 71 (76%) of 87 genes. There was a strong agreement between the two platforms as shown by comparisons of log2 fold differences of gene expression between tumor versus normal samples (R = 0.93) and by Bland-Altman analysis, where greater than 90% of expression values fell within the 95% limits of agreement. Overall concordance of gene expression patterns based on correlations, statistical significance between tumor and normal ovary data, and fold changes was consistent between the Ziplex and Affymetrix platforms. The reproducibility and ease-of-use of the technology suggests that the Ziplex array is a suitable platform for translational research.
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Automated Protocol for Large-Scale Modeling of Gene Expression Data.
Hall, Michelle Lynn; Calkins, David; Sherman, Woody
2016-11-28
With the continued rise of phenotypic- and genotypic-based screening projects, computational methods to analyze, process, and ultimately make predictions in this field take on growing importance. Here we show how automated machine learning workflows can produce models that are predictive of differential gene expression as a function of a compound structure using data from A673 cells as a proof of principle. In particular, we present predictive models with an average accuracy of greater than 70% across a highly diverse ∼1000 gene expression profile. In contrast to the usual in silico design paradigm, where one interrogates a particular target-based response, this work opens the opportunity for virtual screening and lead optimization for desired multitarget gene expression profiles.
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Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.
Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin
2005-01-01
DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.
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Ahn, Suzie E.; Lim, Chul-Hong; Lee, Jin-Young; Bae, Seung-Min; Kim, Jinyoung; Bazer, Fuller W.; Song, Gwonhwa
2013-01-01
The reproductive system of chickens undergoes dynamic morphological and functional tissue remodeling during the molting period. The present study identified global gene expression profiles following oviductal tissue regression and regeneration in laying hens in which molting was induced by feeding high levels of zinc in the diet. During the molting and recrudescence processes, progressive morphological and physiological changes included regression and re-growth of reproductive organs and fluctuations in concentrations of testosterone, progesterone, estradiol and corticosterone in blood. The cDNA microarray analysis of oviductal tissues revealed the biological significance of gene expression-based modulation in oviductal tissue during its remodeling. Based on the gene expression profiles, expression patterns of selected genes such as, TF, ANGPTL3, p20K, PTN, AvBD11 and SERPINB3 exhibited similar patterns in expression with gradual decreases during regression of the oviduct and sequential increases during resurrection of the functional oviduct. Also, miR-1689* inhibited expression of Sp1, while miR-17-3p, miR-22* and miR-1764 inhibited expression of STAT1. Similarly, chicken miR-1562 and miR-138 reduced the expression of ANGPTL3 and p20K, respectively. These results suggest that these differentially regulated genes are closely correlated with the molecular mechanism(s) for development and tissue remodeling of the avian female reproductive tract, and that miRNA-mediated regulation of key genes likely contributes to remodeling of the avian reproductive tract by controlling expression of those genes post-transcriptionally. The discovered global gene profiles provide new molecular candidates responsible for regulating morphological and functional recrudescence of the avian reproductive tract, and provide novel insights into understanding the remodeling process at the genomic and epigenomic levels. PMID:24098561
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Gene expression profiling of single cells on large-scale oligonucleotide arrays
Hartmann, Claudia H.; Klein, Christoph A.
2006-01-01
Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717
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Tran, Frances; Penniket, Carolyn; Patel, Rohan V; Provart, Nicholas J; Laroche, André; Rowland, Owen; Robert, Laurian S
2013-06-01
Despite their importance, there remains a paucity of large-scale gene expression-based studies of reproductive development in species belonging to the Triticeae. As a first step to address this deficiency, a gene expression atlas of triticale reproductive development was generated using the 55K Affymetrix GeneChip(®) wheat genome array. The global transcriptional profiles of the anther/pollen, ovary and stigma were analyzed at concurrent developmental stages, and co-expressed as well as preferentially expressed genes were identified. Data analysis revealed both novel and conserved regulatory factors underlying Triticeae floral development and function. This comprehensive resource rests upon detailed gene annotations, and the expression profiles are readily accessible via a web browser. © 2013 Her Majesty the Queen in Right of Canada as represented by the Minister of Agriculture and Agri-Food Canada.
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Katagiri, Fumiaki; Glazebrook, Jane
2003-01-01
A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data. PMID:12960373
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Gene Expression Profiling Predicts the Development of Oral Cancer
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
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A gene expression resource generated by genome-wide lacZ profiling in the mouse
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
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A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*
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
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Cross-wind profiling based on the scattered wave scintillation in a telescope focus.
Banakh, V A; Marakasov, D A; Vorontsov, M A
2007-11-20
The problem of wind profile reconstruction from scintillation of an optical wave scattered off a rough surface in a telescope focus plane is considered. Both the expression for the spatiotemporal correlation function and the algorithm of cross-wind velocity and direction profiles reconstruction based on the spatiotemporal spectrum of intensity of an optical wave scattered by a diffuse target in a turbulent atmosphere are presented. Computer simulations performed under conditions of weak optical turbulence show wind profiles reconstruction by the developed algorithm.
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Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).
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Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485
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Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data
Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.
2003-01-01
Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292
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Introducing Cytology-Based Theranostics in Oral Squamous Cell Carcinoma: A Pilot Program.
Patrikidou, Anna; Valeri, Rosalia Maria; Kitikidou, Kyriaki; Destouni, Charikleia; Vahtsevanos, Konstantinos
2016-04-01
We aimed to evaluate the feasibility and reliability of brush cytology in the biomarker expression profiling of oral squamous cell carcinomas within the concept of theranostics, and to correlate this biomarker profile with patient measurable outcomes. Markers representative of prognostic gene expression changes in oral squamous cell carcinoma was selected. These markers were also selected to involve pathways for which commercially available or investigational agents exist for clinical application. A set of 7 markers were analysed by immunocytochemistry on the archival primary tumour material of 99 oral squamous cell carcinoma patients. We confirmed the feasibility of the technique for the expression profiling of oral squamous cell carcinomas. Furthermore, our results affirm the prognostic significance of the epidermal growth factor receptor (EGFR) family and the angiogenic pathway in oral squamous cell carcinoma, confirming their interest for targeted therapy. Brush cytology appears feasible and applicable for the expression profiling of oral squamous cell carcinoma within the concept of theranostics, according to sample availability.
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Krönig, Malte; Walter, Max; Drendel, Vanessa; Werner, Martin; Jilg, Cordula A.; Richter, Andreas S.; Backofen, Rolf; McGarry, David; Follo, Marie; Schultze-Seemann, Wolfgang; Schüle, Roland
2015-01-01
A lack of cell surface markers for the specific identification, isolation and subsequent analysis of living prostate tumor cells hampers progress in the field. Specific characterization of tumor cells and their microenvironment in a multi-parameter molecular assay could significantly improve prognostic accuracy for the heterogeneous prostate tumor tissue. Novel functionalized gold-nano particles allow fluorescence-based detection of absolute mRNA expression levels in living cells by fluorescent activated flow cytometry (FACS). We use of this technique to separate prostate tumor and benign cells in human prostate needle biopsies based on the expression levels of the tumor marker alpha-methylacyl-CoA racemase (AMACR). We combined RNA and protein detection of living cells by FACS to gate for epithelial cell adhesion molecule (EPCAM) positive tumor and benign cells, EPCAM/CD45 double negative mesenchymal cells and CD45 positive infiltrating lymphocytes. EPCAM positive epithelial cells were further sub-gated into AMACR high and low expressing cells. Two hundred cells from each population and several biopsies from the same patient were analyzed using a multiplexed gene expression profile to generate a cell type resolved profile of the specimen. This technique provides the basis for the clinical evaluation of cell type resolved gene expression profiles as pre-therapeutic prognostic markers for prostate cancer. PMID:25514598
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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
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Expression and secretory profile of buffalo fetal fibroblasts and Wharton's jelly feeder layers.
Parmar, Mehtab S; Mishra, Smruti Ranjan; Somal, Anjali; Pandey, Sriti; Kumar, G Sai; Sarkar, Mihir; Chandra, Vikash; Sharma, G Taru
2017-05-01
The present study examined the comparative expression and secretory profile of vital signaling molecules in buffalo fetal fibroblasts (BFF) and Wharton's jelly (BWJ) feeder layers at different passages. Both feeder layers were expanded up to 8th passage. Signaling molecules viz. bone morphogenetic protein 4 (BMP4), fibroblast growth factor 2 (FGF2), leukemia inhibitory factor (LIF) and transforming growth factor beta 1 (TGFB1) and pluripotency-associated transcriptional factors (POU5F1, SOX2, NANOG, KLF4, MYC and FOXD3) were immunolocalized in the both feeder types. A clear variation in the expression pattern of key signaling molecules with passaging was registered in both feeders compared to primary culture (0 passage). The conditioned media (CM) was collected from different passages (2, 4, 6, 8) of both the feeder layers and was quantified using enzyme-linked immunosorbent assay (ELISA). Concomitant to expression profile, protein quantification also revealed differences in the concentration of signaling molecules at different time points. Conjointly, expression and secretory profile revealed that 2nd passage of BFF and 6th passage of BWJ exhibit optimal levels of key signaling molecules thus may be selected as best passages for embryonic stem cells (ESCs) propagation. Further, the effect of mitomycin-C (MMC) treatment on the expression profile of signaling molecules in the selected passages of BFF and BWJ revealed that MMC modulates the expression profile of these molecules. In conclusion, the results indicate that feeder layers vary in expression and secretory pattern of vital signaling molecules with passaging. Based on these findings, the appropriate feeder passages may be selected for the quality propagation of buffalo ESCs. Copyright © 2017 Elsevier B.V. All rights reserved.
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Lv, Yufeng; Wei, Wenhao; Huang, Zhong; Chen, Zhichao; Fang, Yuan; Pan, Lili; Han, Xueqiong; Xu, Zihai
2018-06-20
The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection. Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) group and non-early recurrence (non-ER) group of HCC. Least absolute shrinkage and selection operator (LASSO) for logistic regression models were used to develop a lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validated the predictive value of this classifier. Futhermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were performed. We identified 10 differentially expressed lncRNAs, including 3 that were upregulated and 7 that were downregulated in ER group. The lncRNA-based classifier was constructed based on 7 lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861 and LINC02084), and its accuracy was 0.83 in training set, 0.87 in test set and 0.84 in total set. And ROC curve analysis showed the AUROC was 0.741 in training set, 0.824 in the test set and 0.765 in total set. A functional enrichment analysis suggested that the genes of which is highly related to 4 lncRNAs were involved in immune system. This 7-lncRNA expression profile can effectively predict the early recurrence after surgical resection for HCC. This article is protected by copyright. All rights reserved.
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Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T
2014-02-06
Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.
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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.
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A proof of the DBRF-MEGN method, an algorithm for deducing minimum equivalent gene networks
2011-01-01
Background We previously developed the DBRF-MEGN (difference-based regulation finding-minimum equivalent gene network) method, which deduces the most parsimonious signed directed graphs (SDGs) consistent with expression profiles of single-gene deletion mutants. However, until the present study, we have not presented the details of the method's algorithm or a proof of the algorithm. Results We describe in detail the algorithm of the DBRF-MEGN method and prove that the algorithm deduces all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants. Conclusions The DBRF-MEGN method provides all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants. PMID:21699737
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Modelling gene expression profiles related to prostate tumor progression using binary states
2013-01-01
Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350
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Mucin profiles in signet-ring cell carcinoma.
Nguyen, Minh D; Plasil, Brian; Wen, Ping; Frankel, Wendy L
2006-06-01
Signet-ring cell carcinoma (SRCC) is a poorly differentiated mucin-producing adenocarcinoma that may arise from many different organs, but all SRCCs share identical morphology. It is not possible to differentiate sites of origin for metastatic SRCC based on morphology alone. Mucins are high-molecular-weight glycoproteins differentially expressed in glandular epithelia and in adenocarcinomas. To identify mucin profiles of primary and metastatic SRCCs using immunohistochemistry to determine whether mucin staining could help distinguish sites of origin. Forty-seven SRCCs, including 38 primary (21 stomach, 11 colorectum, and 6 breast) and 9 metastases from these primary sites were retrieved from archival files. Consecutive tissue sections were immunostained with monoclonal antibodies against MUC1, MUC2, MUC4, MUC5AC (MUC5), and MUC6 on separate slides. Cytoplasmic staining was scored based on proportion of positive tumor cells as follows: 0+ (<5%), 1+ (5%-25%), 2+ (26%-50%), and 3+ (>50%). Mucin profiles were recorded as MUC+, MUCv, and MUC- for consistent, variable, and negative expression, respectively. The mucin profiles for gastric, colorectum, and breast SRCCs are MUC1.2.4.5.6v, MUC2.4+/MUC5v/ MUC1.6-, and MUC1+/MUC2.5.6v/MUC4-, respectively. Mucin profiles of metastatic cases shared profiles with their respective primaries. Signet-ring cell carcinomas of the stomach, colorectum, and breast have distinct mucin expression patterns that are maintained in metastases. Mucin profiling may be useful to identify the origin of a metastatic SRCC of unknown primary.
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Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David
2007-07-23
Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.
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Mäurer, André P; Mehlitz, Adrian; Mollenkopf, Hans J; Meyer, Thomas F
2007-01-01
The obligate intracellular, gram-negative bacterium Chlamydophila pneumoniae (Cpn) has impact as a human pathogen. Little is known about changes in the Cpn transcriptome during its biphasic developmental cycle (the acute infection) and persistence. The latter stage has been linked to chronic diseases. To analyze Cpn CWL029 gene expression, we designed a pathogen-specific oligo microarray and optimized the extraction method for pathogen RNA. Throughout the acute infection, ratio expression profiles for each gene were generated using 48 h post infection as a reference. Based on these profiles, significantly expressed genes were separated into 12 expression clusters using self-organizing map clustering and manual sorting into the “early”, “mid”, “late”, and “tardy” cluster classes. The latter two were differentiated because the “tardy” class showed steadily increasing expression at the end of the cycle. The transcriptome of the Cpn elementary body (EB) and published EB proteomics data were compared to the cluster profile of the acute infection. We found an intriguing association between “late” genes and genes coding for EB proteins, whereas “tardy” genes were mainly associated with genes coding for EB mRNA. It has been published that iron depletion leads to Cpn persistence. We compared the gene expression profiles during iron depletion–mediated persistence with the expression clusters of the acute infection. This led to the finding that establishment of iron depletion–mediated persistence is more likely a mid-cycle arrest in development rather than a completely distinct gene expression pattern. Here, we describe the Cpn transcriptome during the acute infection, differentiating “late” genes, which correlate to EB proteins, and “tardy” genes, which lead to EB mRNA. Expression profiles during iron mediated–persistence led us to propose the hypothesis that the transcriptomic “clock” is arrested during acute mid-cycle. PMID:17590080
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Microarray profiling of gene expression in human adipocytes in response to anthocyanins.
Tsuda, Takanori; Ueno, Yuki; Yoshikawa, Toshikazu; Kojo, Hitoshi; Osawa, Toshihiko
2006-04-14
Adipocyte dysfunction is strongly associated with the development of obesity and insulin resistance. It is accepted that the regulation of adipocytokine secretion or the adipocyte specific gene expression is one of the most important targets for the prevention of obesity and amelioration of insulin sensitivity. Recently, we demonstrated that anthocyanins, which are pigments widespread in the plant kingdom, have the potency of anti-obesity in mice and the enhancement adipocytokine secretion and its gene expression in adipocytes. In this study, we have shown the gene expression profile in human adipocytes treated with anthocyanins (cyanidin 3-glucoside; C3G or cyanidin; Cy). The human adipocytes were treated with 100 microM C3G, Cy or vehicle for 24 h. The total RNA from the adipocytes was isolated and carried out GeneChip microarray analysis. Based on the gene expression profile, we demonstrated the significant changes of adipocytokine expression (up-regulation of adiponectin and down-regulation of plasminogen activator inhibitor-1 and interleukin-6). Some of lipid metabolism related genes (uncoupling protein2, acylCoA oxidase1 and perilipin) also significantly induced in both common the C3G or Cy treatment groups. These studies have provided an overview of the gene expression profiles in human adipocytes treated with anthocyanins and demonstrated that anthocyanins can regulate adipocytokine gene expression to ameliorate adipocyte function related with obesity and diabetes that merit further investigation.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya
Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less
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Reprogramming Methods Do Not Affect Gene Expression Profile of Human Induced Pluripotent Stem Cells.
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.
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O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik
2015-01-01
To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329
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TrackEtching - A Java based code for etched track profile calculations in SSNTDs
NASA Astrophysics Data System (ADS)
Muraleedhara Varier, K.; Sankar, V.; Gangadathan, M. P.
2017-09-01
A java code incorporating a user friendly GUI has been developed to calculate the parameters of chemically etched track profiles of ion-irradiated solid state nuclear track detectors. Huygen's construction of wavefronts based on secondary wavelets has been used to numerically calculate the etched track profile as a function of the etching time. Provision for normal incidence and oblique incidence on the detector surface has been incorporated. Results in typical cases are presented and compared with experimental data. Different expressions for the variation of track etch rate as a function of the ion energy have been utilized. The best set of values of the parameters in the expressions can be obtained by comparing with available experimental data. Critical angle for track development can also be calculated using the present code.
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Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles
NASA Technical Reports Server (NTRS)
Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.
2003-01-01
Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.
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We propose the use of gene expression profiling to complement the chemical characterization currently based on HTS assay data and present a case study relevant to the Endocrine Disruptor Screening Program. We have developed computational methods to identify estrogen receptor &alp...
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Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer.
Hannemann, Juliane; Oosterkamp, Hendrika M; Bosch, Cathy A J; Velds, Arno; Wessels, Lodewyk F A; Loo, Claudette; Rutgers, Emiel J; Rodenhuis, Sjoerd; van de Vijver, Marc J
2005-05-20
At present, clinically useful markers predicting response of primary breast carcinomas to either doxorubicin-cyclophosphamide (AC) or doxorubicin-docetaxel (AD) are lacking. We investigated whether gene expression profiles of the primary tumor could be used to predict treatment response to either of those chemotherapy regimens. Within a single-institution, randomized, phase II trial, patients with locally advanced breast cancer received six courses of either AC (n = 24) or AD (n = 24) neoadjuvant chemotherapy. Gene expression profiles were generated from core-needle biopsies obtained before treatment and correlated with the response of the primary tumor to the chemotherapy administered. Additionally, pretreatment gene expression profiles were compared with those in tumors remaining after chemotherapy. Ten (20%) of 48 patients showed a (near) pathologic complete remission of the primary tumor after treatment. No gene expression pattern correlating with response could be identified for all patients or for the AC or AD groups separately. The comparison of the pretreatment biopsy and the tumor excised after chemotherapy revealed differences in gene expression in tumors that showed a partial remission but not in tumors that did not respond to chemotherapy. No gene expression profile predicting the response of primary breast carcinomas to AC- or AD-based neoadjuvant chemotherapy could be detected in this interim analysis. More subtle differences in gene expression are likely to be present but can only be reliably identified by studying a larger group of patients. Response of a breast tumor to neoadjuvant chemotherapy results in alterations in gene expression.
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Expression signature as a biomarker for prenatal diagnosis of trisomy 21.
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.
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A transcriptome-based examination of blood group expression
Noh, S.-J.; Lee, Y.T.; Byrnes, C.; Miller, J.L.
2011-01-01
Over the last two decades, red cell biologists witnessed a vast expansion of genetic-based information pertaining to blood group antigens and their carrier molecules. Genetic progress has led to a better comprehension of the associated antigens. To assist with studies concerning the integrated regulation and function of blood groups, transcript levels for each of the 36 associated genes were studied. Profiles using mRNA from directly sampled reticulocytes and cultured primary erythroblasts are summarized in this report. Transcriptome profiles suggest a highly regulated pattern of blood group gene expression during erythroid differentiation and ontogeny. Approximately one-third of the blood group carrier genes are transcribed in an erythroid-specific fashion. Low-level and indistinct expression was noted for most of the carbohydrate-associated genes. Methods are now being developed to further explore and manipulate expression of the blood group genes at all stages of human erythropoiesis. PMID:20685146
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Bayesian median regression for temporal gene expression data
NASA Astrophysics Data System (ADS)
Yu, Keming; Vinciotti, Veronica; Liu, Xiaohui; 't Hoen, Peter A. C.
2007-09-01
Most of the existing methods for the identification of biologically interesting genes in a temporal expression profiling dataset do not fully exploit the temporal ordering in the dataset and are based on normality assumptions for the gene expression. In this paper, we introduce a Bayesian median regression model to detect genes whose temporal profile is significantly different across a number of biological conditions. The regression model is defined by a polynomial function where both time and condition effects as well as interactions between the two are included. MCMC-based inference returns the posterior distribution of the polynomial coefficients. From this a simple Bayes factor test is proposed to test for significance. The estimation of the median rather than the mean, and within a Bayesian framework, increases the robustness of the method compared to a Hotelling T2-test previously suggested. This is shown on simulated data and on muscular dystrophy gene expression data.
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DMirNet: Inferring direct microRNA-mRNA association networks.
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.
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Saeliw, Thanit; Tangsuwansri, Chayanin; Thongkorn, Surangrat; Chonchaiya, Weerasak; Suphapeetiporn, Kanya; Mutirangura, Apiwat; Tencomnao, Tewin; Hu, Valerie W; Sarachana, Tewarit
2018-01-01
Alu elements are a group of repetitive elements that can influence gene expression through CpG residues and transcription factor binding. Altered gene expression and methylation profiles have been reported in various tissues and cell lines from individuals with autism spectrum disorder (ASD). However, the role of Alu elements in ASD remains unclear. We thus investigated whether Alu elements are associated with altered gene expression profiles in ASD. We obtained five blood-based gene expression profiles from the Gene Expression Omnibus database and human Alu-inserted gene lists from the TranspoGene database. Differentially expressed genes (DEGs) in ASD were identified from each study and overlapped with the human Alu-inserted genes. The biological functions and networks of Alu-inserted DEGs were then predicted by Ingenuity Pathway Analysis (IPA). A combined bisulfite restriction analysis of lymphoblastoid cell lines (LCLs) derived from 36 ASD and 20 sex- and age-matched unaffected individuals was performed to assess the global DNA methylation levels within Alu elements, and the Alu expression levels were determined by quantitative RT-PCR. In ASD blood or blood-derived cells, 320 Alu-inserted genes were reproducibly differentially expressed. Biological function and pathway analysis showed that these genes were significantly associated with neurodevelopmental disorders and neurological functions involved in ASD etiology. Interestingly, estrogen receptor and androgen signaling pathways implicated in the sex bias of ASD, as well as IL-6 signaling and neuroinflammation signaling pathways, were also highlighted. Alu methylation was not significantly different between the ASD and sex- and age-matched control groups. However, significantly altered Alu methylation patterns were observed in ASD cases sub-grouped based on Autism Diagnostic Interview-Revised scores compared with matched controls. Quantitative RT-PCR analysis of Alu expression also showed significant differences between ASD subgroups. Interestingly, Alu expression was correlated with methylation status in one phenotypic ASD subgroup. Alu methylation and expression were altered in LCLs from ASD subgroups. Our findings highlight the association of Alu elements with gene dysregulation in ASD blood samples and warrant further investigation. Moreover, the classification of ASD individuals into subgroups based on phenotypes may be beneficial and could provide insights into the still unknown etiology and the underlying mechanisms of ASD.
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Lopez-Gomollon, Sara; Mohorianu, Irina; Szittya, Gyorgy; Moulton, Vincent; Dalmay, Tamas
2012-12-01
MicroRNAs negatively regulate the accumulation of mRNAs therefore when they are expressed in the same cells their expression profiles show an inverse correlation. We previously described one positively correlated miRNA/target pair, but it is not known how widespread this phenomenon is. Here, we investigated the correlation between the expression profiles of differentially expressed miRNAs and their targets during tomato fruit development using deep sequencing, Northern blot and RT-qPCR. We found an equal number of positively and negatively correlated miRNA/target pairs indicating that positive correlation is more frequent than previously thought. We also found that the correlation between microRNA and target expression profiles can vary between mRNAs belonging to the same gene family and even for the same target mRNA at different developmental stages. Since microRNAs always negatively regulate their targets, the high number of positively correlated microRNA/target pairs suggests that mutual exclusion could be as widespread as temporal regulation. The change of correlation during development suggests that the type of regulatory circuit directed by a microRNA can change over time and can be different for individual gene family members. Our results also highlight potential problems for expression profiling-based microRNA target identification/validation.
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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
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Gene expression profiling of intestinal regeneration in the sea cucumber
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
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Marques, Márcia M C; Junta, Cristina M; Zárate-Blades, Carlos R; Sakamoto-Hojo, Elza Tiemi; Donadi, Eduardo A; Passos, Geraldo A S
2009-07-01
Since circulating leukocytes, mainly B and T cells, continuously maintain vigilant and comprehensive immune surveillance, these cells could be used as reporters for signs of infection or other pathologies, including cancer. Activated lymphocyte clones trigger a sensitive transcriptional response, which could be identified by gene expression profiling. To assess this hypothesis, we conducted microarray analysis of the gene expression profile of lymphocytes isolated from immunocompetent BALB/c mice subcutaneously injected with different numbers of tumorigenic B61 fibrosarcoma cells. Flow cytometry demonstrated that the number of circulating T (CD3(+)CD4(+) or CD3(+)CD8(+)) or B (CD19(+)) cells did not change. However, the lymphocytes isolated from tumor cell-injected animals expressed a unique transcriptional profile that was identifiable before the development of a palpable tumor mass. This finding demonstrates that the transcriptional response appears before alterations in the main lymphocyte subsets and that the gene expression profile of peripheral lymphocytes can serve as a sensitive and accurate method for the early detection of cancer.
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Rubel, Cory A; Wu, San-Pin; Lin, Lin; Wang, Tianyuan; Lanz, Rainer B; Li, Xilong; Kommagani, Ramakrishna; Franco, Heather L; Camper, Sally A; Tong, Qiang; Jeong, Jae-Wook; Lydon, John P; DeMayo, Francesco J
2016-10-25
Altered progesterone responsiveness leads to female infertility and cancer, but underlying mechanisms remain unclear. Mice with uterine-specific ablation of GATA binding protein 2 (Gata2) are infertile, showing failures in embryo implantation, endometrial decidualization, and uninhibited estrogen signaling. Gata2 deficiency results in reduced progesterone receptor (PGR) expression and attenuated progesterone signaling, as evidenced by genome-wide expression profiling and chromatin immunoprecipitation. GATA2 not only occupies at and promotes expression of the Pgr gene but also regulates downstream progesterone responsive genes in conjunction with the PGR. Additionally, Gata2 knockout uteri exhibit abnormal luminal epithelia with ectopic TRP63 expressing squamous cells and a cancer-related molecular profile in a progesterone-independent manner. Lastly, we found a conserved GATA2-PGR regulatory network in both human and mice based on gene signature and path analyses using gene expression profiles of human endometrial tissues. In conclusion, uterine Gata2 regulates a key regulatory network of gene expression for progesterone signaling at the early pregnancy stage. Published by Elsevier Inc.
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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
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Proteomic and Epigenetic Analysis of Rice after Seed Spaceflight and Ground-Base Ion Radiations
NASA Astrophysics Data System (ADS)
Wang, Wei; Sun, Yeqing; Peng, Yuming; Zhao, Qian; Wen, Bin; Yang, Jun
Highly ionizing radiation (HZE) in space is considered as main factor causing biological effects to plant seeds. In previous work, we compared the proteomic profiles of rice plants growing after seed spaceflights to ground controls by two-dimensional difference gel electrophoresis (2-D DIGE) with mass spectrometry and found that the protein expression profiles were changed and differentially expressed proteins participated in most of the biological processes of rice. To further evaluate the dosage effects of space radiation and compare between low- and high-dose ion effects, we carried out three independent ground-base ionizing radiation experiments with different cumulative doses (low-dose range: 2~1000mGy, high-dose range: 2000~20000mGy) to rice seeds and performed proteomic analysis of seedlings. We found that protein expression profiles showed obvious boundaries between low- and high-dose radiation groups. Rates of differentially expressed proteins presented a dose-dependent effect, it reached the highest value at 2000mGy dosage point in all three radiation experiments coincidently; while proteins responded to low-dose radiations preferred to change their expressions at the minimum dosage (2mGy). Proteins participating in rice biological processes also responded differently between low- and high-dose radiations: proteins involved in energy metabolism and photosynthesis tended to be regulated after low-dose radiations while stress responding, protein folding and cell redox homeostasis related proteins preferred to change their expressions after high-dose radiations. By comparing the proteomic profiles between ground-base radiations and spaceflights, it was worth noting that ground-base low-dose ion radiation effects shared similar biological effects as space environment. In addition, we discovered that protein nucleoside diphosphate kinase 1 (NDPK1) showed obvious increased regulation after spaceflights and ion radiations. NDPK1 catalyzes nucleotide metabolism and is reported to be involved in DNA repair process. Its expression sensitivity and specificity were confirmed by RT-PCR and western blot analysis, indicating its potential to be used as space radiation biomarker. Space radiations might induce epigenetic effects on rice plants, especially changes of DNA methylation. Early results suggested that there were correlations between DNA methylation polymorphic and genomic mutation rates. In addition, the 5-methylcytosine located in coding gene’s promoter and exon regions could regulate gene expressions thus influence protein expressions. So whether there is correlation between genome DNA methylation changes and protein expression profile alterations caused by space radiation is worth for further investigation. Therefore we used the same rice samples treated by carbon ion radiation with different doses (0, 10, 20,100, 200, 1000, 2000, 5000, 20000mGy) and applied methylation sensitive amplification polymorphism (MSAP) for scanning genome DNA methylation changes. Interestingly, DNA methylation polymorphism rates also presented a dose-dependent effect and showed the same changing trend as rates of differentially expressed proteins. Whether there are correlations between epigenetic and proteomic effects of space radiation is worth for further investigation.
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Gene expression analysis predicts insect venom anaphylaxis in indolent systemic mastocytosis.
Niedoszytko, M; Bruinenberg, M; van Doormaal, J J; de Monchy, J G R; Nedoszytko, B; Koppelman, G H; Nawijn, M C; Wijmenga, C; Jassem, E; Elberink, J N G Oude
2011-05-01
Anaphylaxis to insect venom (Hymenoptera) is most severe in patients with mastocytosis and may even lead to death. However, not all patients with mastocytosis suffer from anaphylaxis. The aim of the study was to analyze differences in gene expression between patients with indolent systemic mastocytosis (ISM) and a history of insect venom anaphylaxis (IVA) compared to those patients without a history of anaphylaxis, and to determine the predictive use of gene expression profiling. Whole-genome gene expression analysis was performed in peripheral blood cells. Twenty-two adults with ISM were included: 12 with a history of IVA and 10 without a history of anaphylaxis of any kind. Significant differences in single gene expression corrected for multiple testing were found for 104 transcripts (P < 0.05). Gene ontology analysis revealed that the differentially expressed genes were involved in pathways responsible for the development of cancer and focal and cell adhesion suggesting that the expression of genes related to the differentiation state of cells is higher in patients with a history of anaphylaxis. Based on the gene expression profiles, a naïve Bayes prediction model was built identifying patients with IVA. In ISM, gene expression profiles are different between patients with a history of IVA and those without. These findings might reflect a more pronounced mast cells dysfunction in patients without a history of anaphylaxis. Gene expression profiling might be a useful tool to predict the risk of anaphylaxis on insect venom in patients with ISM. Prospective studies are needed to substantiate any conclusions. © 2010 John Wiley & Sons A/S.
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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.
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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...
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Gene expression profiles of auxin metabolism in maturing apple fruit
USDA-ARS?s Scientific Manuscript database
Variation exists among apple genotypes in fruit maturation and ripening patterns that influences at-harvest fruit firmness and postharvest storability. Based on the results from our previous large-scale transcriptome profiling on apple fruit maturation and well-documented auxin-ethylene crosstalk, t...
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mirEX: a platform for comparative exploration of plant pri-miRNA expression data.
Bielewicz, Dawid; Dolata, Jakub; Zielezinski, Andrzej; Alaba, Sylwia; Szarzynska, Bogna; Szczesniak, Michal W; Jarmolowski, Artur; Szweykowska-Kulinska, Zofia; Karlowski, Wojciech M
2012-01-01
mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. RT-qPCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. A web-based mirEX interface can be accessed at http://bioinfo.amu.edu.pl/mirex.
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Genome-wide expression profiling in pediatric septic shock
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
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Merlaen, Britt; De Keyser, Ellen; Van Labeke, Marie-Christine
2018-01-01
The newly identified aquaporin coding sequences presented here pave the way for further insights into the plant-water relations in the commercial strawberry ( Fragaria x ananassa ). Aquaporins are water channel proteins that allow water to cross (intra)cellular membranes. In Fragaria x ananassa , few of them have been identified hitherto, hampering the exploration of the water transport regulation at cellular level. Here, we present new aquaporin coding sequences belonging to different subclasses: plasma membrane intrinsic proteins subtype 1 and subtype 2 (PIP1 and PIP2) and tonoplast intrinsic proteins (TIP). The classification is based on phylogenetic analysis and is confirmed by the presence of conserved residues. Substrate-specific signature sequences (SSSSs) and specificity-determining positions (SDPs) predict the substrate specificity of each new aquaporin. Expression profiling in leaves, petioles and developing fruits reveals distinct patterns, even within the same (sub)class. Expression profiles range from leaf-specific expression over constitutive expression to fruit-specific expression. Both upregulation and downregulation during fruit ripening occur. Substrate specificity and expression profiles suggest that functional specialization exists among aquaporins belonging to a different but also to the same (sub)class.
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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.
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Rajarapu, Swapna Priya; Shreve, Jacob T; Bhide, Ketaki P; Thimmapuram, Jyothi; Scharf, Michael E
2015-04-22
Second generation lignocellulosic feedstocks are being considered as an alternative to first generation biofuels that are derived from grain starches and sugars. However, the current pre-treatment methods for second generation biofuel production are inefficient and expensive due to the recalcitrant nature of lignocellulose. In this study, we used the lower termite Reticulitermes flavipes (Kollar), as a model to identify potential pretreatment genes/enzymes specifically adapted for use against agricultural feedstocks. Metatranscriptomic profiling was performed on worker termite guts after feeding on corn stover (CS), soybean residue (SR), or 98% pure cellulose (paper) to identify (i) microbial community, (ii) pathway level and (iii) gene-level responses. Microbial community profiles after CS and SR feeding were different from the paper feeding profile, and protist symbiont abundance decreased significantly in termites feeding on SR and CS relative to paper. Functional profiles after CS feeding were similar to paper and SR; whereas paper and SR showed different profiles. Amino acid and carbohydrate metabolism pathways were downregulated in termites feeding on SR relative to paper and CS. Gene expression analyses showed more significant down regulation of genes after SR feeding relative to paper and CS. Stereotypical lignocellulase genes/enzymes were not differentially expressed, but rather were among the most abundant/constitutively-expressed genes. These results suggest that the effect of CS and SR feeding on termite gut lignocellulase composition is minimal and thus, the most abundantly expressed enzymes appear to encode the best candidate catalysts for use in saccharification of these and related second-generation feedstocks. Further, based on these findings we hypothesize that the most abundantly expressed lignocellulases, rather than those that are differentially expressed have the best potential as pretreatment enzymes for CS and SR feedstocks.
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Pathway-Based Concentration Response Profiles from Toxicogenomics Data
Microarray analysis of gene expression of in vitro systems could be a powerful tool for assessing chemical hazard. Differentially expressed genes specific to cells, chemicals, and concentrations can be organized into molecular pathways that inform mode of action. An important par...
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Dynamic association rules for gene expression data analysis.
Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung
2015-10-14
The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.
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[New methods of patient selection for improved anticholinergic therapy].
Neuhaus, J; Schwalenberg, T; Schlichting, N; Schulze, M; Horn, L-C; Stolzenburg, J-U
2007-09-01
M3-specific inhibitors are currently preferred for anticholinergic therapy of OAB. However, not all of the patients profit from this regimen. This might reflect a heterogeneity of the patient group. The aim of this work is to define subgroups of patients with specific alterations of receptor expression and to profile the receptor expression individually. These receptor profiles might be used for the development of evidence-based "tailored" therapies. Detrusor probes from bladder carcinoma patients (BCa, n=9 F, n=7 male) and interstitial cystitis patients (IC, n=9 female) were examined using confocal immunofluorescence and PCR. M2, M3, P2X1-3, and H1-3 mRNAs were demonstrated in detrusor tissue. As revealed by immunofluorescence, the M2 receptor expression was significantly higher in female compared to male BCa tissues. In addition, the M2 receptor was further upregulated in IC vs BCa in female detrusor. IC patients showed specific alterations of their receptor profile. Individual receptor profiles might be used to optimize medicinal therapies.
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Dakshinamurthy, Amirtha Ganesh; Ramesar, Rajkumar; Goldberg, Paul; Blackburn, Jonathan M
2008-11-01
Cancer-testis (CT) antigens are a group of tumor antigens that are expressed in the testis and aberrantly in cancerous tissue but not in somatic tissues. The testis is an immune-privileged site because of the presence of a blood-testis barrier; as a result, CT antigens are considered to be essentially tumor specific and are attractive targets for immunotherapy. CT antigens are classified as the CT-X and the non-X CT antigens depending on the chromosomal location to which the genes are mapped. CT-X antigens are typically highly immunogenic and hence the first step towards tailored immunotherapy is to elucidate the expression profile of CT-X antigens in the respective tumors. In this study we investigated the expression profile of 16 CT-X antigen genes in 34 colorectal cancer (CRC) patients using reverse transcription-polymerase chain reaction. We observed that 12 of the 16 CT-X antigen genes studied did not show expression in any of the CRC samples analyzed. The other 4 CT-X antigen genes showed low frequency of expression and exhibited a highly variable expression profile when compared to other populations. Thus, our study forms the first report on the expression profile of CT-X antigen genes among CRC patients in the genetically diverse South African population. The results of our study suggest that genetic and ethnic variations in population might have a role in the expression of the CT-X antigen genes. Thus our results have significant implications for anti-CT antigen-based immunotherapy trials in this population.
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Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.
Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina
2015-01-01
Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.
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Transcriptome assembly and digital gene expression atlas of the rainbow trout
USDA-ARS?s Scientific Manuscript database
Background: Transcriptome analysis is a preferred method for gene discovery, marker development and gene expression profiling in non-model organisms. Previously, we sequenced a transcriptome reference using Sanger-based and 454-pyrosequencing, however, a transcriptome assembly is still incomplete an...
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The dark cube: dark and light character profiles.
Garcia, Danilo; Rosenberg, Patricia
2016-01-01
Background. Research addressing distinctions and similarities between people's malevolent character traits (i.e., the Dark Triad: Machiavellianism, narcissism, and psychopathy) has detected inconsistent linear associations to temperament traits. Additionally, these dark traits seem to have a common core expressed as uncooperativeness. Hence, some researchers suggest that the dark traits are best represented as one global construct (i.e., the unification argument) rather than as ternary construct (i.e., the uniqueness argument). We put forward the dark cube (cf. Cloninger's character cube) comprising eight dark profiles that can be used to compare individuals who differ in one dark character trait while holding the other two constant. Our aim was to investigate in which circumstances individuals who are high in each one of the dark character traits differ in Cloninger's "light" character traits: self-directedness, cooperativeness, and self-transcendence. We also investigated if people's dark character profiles were associated to their light character profiles. Method. A total of 997 participants recruited from Amazon's Mechanical Turk (MTurk) responded to the Short Dark Triad and the Short Character Inventory. Participants were allocated to eight different dark profiles and eight light profiles based on their scores in each of the traits and any possible combination of high and low scores. We used three-way interaction regression analyses and t-tests to investigate differences in light character traits between individuals with different dark profiles. As a second step, we compared the individuals' dark profile with her/his character profile using an exact cell-wise analysis conducted in the ROPstat software (http://www.ropstat.com). Results. Individuals who expressed high levels of Machiavellianism and those who expressed high levels of psychopathy also expressed low self-directedness and low cooperativeness. Individuals with high levels of narcissism, in contrast, scored high in self-directedness. Moreover, individuals with a profile low in the dark traits were more likely to end up with a profile high in cooperativeness. The opposite was true for those individuals with a profile high in the dark traits. The rest of the cross-comparisons revealed some of the characteristics of human personality as a non-linear complex dynamic system. Conclusions. Our study suggests that individuals who are high in Machiavellianism and psychopathy share a unified non-agentic and uncooperative character (i.e., irresponsible, low in self-control, unempathetic, unhelpful, untolerant), while individuals high in narcissism have a more unique character configuration expressed as high agency and, when the other dark traits are high, highly spiritual but uncooperative. In other words, based on differences in their associations to the light side of character, the Dark Triad seems to be a dyad rather than a triad.
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The dark cube: dark and light character profiles
2016-01-01
Background. Research addressing distinctions and similarities between people’s malevolent character traits (i.e., the Dark Triad: Machiavellianism, narcissism, and psychopathy) has detected inconsistent linear associations to temperament traits. Additionally, these dark traits seem to have a common core expressed as uncooperativeness. Hence, some researchers suggest that the dark traits are best represented as one global construct (i.e., the unification argument) rather than as ternary construct (i.e., the uniqueness argument). We put forward the dark cube (cf. Cloninger’s character cube) comprising eight dark profiles that can be used to compare individuals who differ in one dark character trait while holding the other two constant. Our aim was to investigate in which circumstances individuals who are high in each one of the dark character traits differ in Cloninger’s “light” character traits: self-directedness, cooperativeness, and self-transcendence. We also investigated if people’s dark character profiles were associated to their light character profiles. Method. A total of 997 participants recruited from Amazon’s Mechanical Turk (MTurk) responded to the Short Dark Triad and the Short Character Inventory. Participants were allocated to eight different dark profiles and eight light profiles based on their scores in each of the traits and any possible combination of high and low scores. We used three-way interaction regression analyses and t-tests to investigate differences in light character traits between individuals with different dark profiles. As a second step, we compared the individuals’ dark profile with her/his character profile using an exact cell-wise analysis conducted in the ROPstat software (http://www.ropstat.com). Results. Individuals who expressed high levels of Machiavellianism and those who expressed high levels of psychopathy also expressed low self-directedness and low cooperativeness. Individuals with high levels of narcissism, in contrast, scored high in self-directedness. Moreover, individuals with a profile low in the dark traits were more likely to end up with a profile high in cooperativeness. The opposite was true for those individuals with a profile high in the dark traits. The rest of the cross-comparisons revealed some of the characteristics of human personality as a non-linear complex dynamic system. Conclusions. Our study suggests that individuals who are high in Machiavellianism and psychopathy share a unified non-agentic and uncooperative character (i.e., irresponsible, low in self-control, unempathetic, unhelpful, untolerant), while individuals high in narcissism have a more unique character configuration expressed as high agency and, when the other dark traits are high, highly spiritual but uncooperative. In other words, based on differences in their associations to the light side of character, the Dark Triad seems to be a dyad rather than a triad. PMID:26966650
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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
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Logotheti, Marianthi; Papadodima, Olga; Venizelos, Nikolaos; Chatziioannou, Aristotelis; Kolisis, Fragiskos
2013-01-01
Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets. PMID:23554570
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Genome-wide analysis and expression profiling of the Solanum tuberosum aquaporins.
Venkatesh, Jelli; Yu, Jae-Woong; Park, Se Won
2013-12-01
Aquaporins belongs to the major intrinsic proteins involved in the transcellular membrane transport of water and other small solutes. A comprehensive genome-wide search for the homologues of Solanum tuberosum major intrinsic protein (MIP) revealed 41 full-length potato aquaporin genes. All potato aquaporins are grouped into five subfamilies; plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), NOD26-like intrinsic proteins (NIPs), small basic intrinsic proteins (SIPs) and x-intrinsic proteins (XIPs). Functional predictions based on the aromatic/arginine (ar/R) selectivity filters and Froger's positions showed a remarkable difference in substrate transport specificity among subfamilies. The expression pattern of potato aquaporins, examined by qPCR analysis, showed distinct expression profiles in various organs and tuber developmental stages. Furthermore, qPCR analysis of potato plantlets, subjected to various abiotic stresses revealed the marked effect of stresses on expression levels of aquaporins. Taken together, the expression profiles of aquaporins imply that aquaporins play important roles in plant growth and development, in addition to maintaining water homeostasis in response to environmental stresses. Copyright © 2013 Elsevier Masson SAS. All rights reserved.
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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.
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Benzoate-mediated changes on expression profile of soluble proteins in Serratia sp. DS001.
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.
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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.
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Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.
Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L
2016-10-10
Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.
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Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
Wang, Liming; Zhu, L.; Luan, R.; Wang, L.; Fu, J.; Wang, X.; Sui, L.
2016-01-01
Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM. PMID:27737314
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Gao, Haiyan; Yang, Mei; Zhang, Xiaolan
2018-04-01
The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.
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Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.
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.
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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.
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Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae
2011-07-01
Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.
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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...
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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.
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Jung, Seung-Hyun; Shin, Seung-Hun; Yim, Seon-Hee; Choi, Hye-Sun; Lee, Sug-Hyung; Chung, Yeun-Jun
2009-07-31
Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.
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Immunomediator expression profiling in two beluga whale (delphinapterus leucas) clinical cases
USDA-ARS?s Scientific Manuscript database
Cytokines and other immunomediators can be biomarkers of inflammation. Quantitative real-time PCR (qPCR) has been used to examine cytokine gene expression in beluga whale (Delphinapterus leucas) peripheral blood mononuclear cells (PBMC). Thus, qPCR-based immunomediator assays could supplement clinic...
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Lockyer, Anne E; Noble, Leslie R; Rollinson, David; Jones, Catherine S
2004-01-01
The freshwater tropical snail Biomphalaria glabrata is an intermediate host for Schistosoma mansoni, the causative agent of human intestinal schistosomiasis, and strains differ in their susceptibility to parasite infection. Changes in gene expression in response to parasite infection have been simultaneously examined in a susceptible strain (NHM1742) and a resistant strain (NHM1981) using a newly developed fluorescent-based differential display method. Such RNA profiling techniques allow the examination of changes in gene expression in response to parasite infection, without requiring previous sequence knowledge, or selecting candidate genes that may be involved in the complex neuroendocrine or defence systems of the snail. Thus, novel genes may be identified. Ten transcripts were initially identified, present only in the profiles derived from snails of the resistant strain when exposed to infection. The differential expression of five of these genes, including HSP70 and several novel transcripts with one containing at least two globin-like domains, has been confirmed by semi-quantitative RT-PCR.
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Cendoya, Eugenia; Pinson-Gadais, Laetitia; Farnochi, María C; Ramirez, María L; Chéreau, Sylvain; Marcheguay, Giselè; Ducos, Christine; Barreau, Christian; Richard-Forget, Florence
2017-07-17
Fusarium proliferatum produces fumonisins B not only on maize but also on diverse crops including wheat. Using a wheat-based medium, the effects of abiotic factors, temperature and water activity (a W ), on growth, fumonisin biosynthesis, and expression of FUM genes were compared for three F. proliferatum strains isolated from durum wheat in Argentina. Although all isolates showed similar profiles of growth, the fumonisin production profiles were slightly different. Regarding FUM gene transcriptional control, both FUM8 and FUM19 expression showed similar behavior in all tested conditions. For both genes, expression at 25°C correlated with fumonisin production, regardless of the a w conditions. However, at 15°C, these two genes were as highly expressed as at 25°C although the amounts of toxin were very weak, suggesting that the kinetics of fumonisin production was slowed at 15°C. This study provides useful baseline data on conditions representing a low or a high risk for contamination of wheat kernels with fumonisins. Copyright © 2017 Elsevier B.V. All rights reserved.
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The Human Pancreas Proteome Defined by Transcriptomics and Antibody-Based Profiling
Fagerberg, Linn; Hallström, Björn M.; Schwenk, Jochen M.; Uhlén, Mathias; Korsgren, Olle; Lindskog, Cecilia
2014-01-01
The pancreas is composed of both exocrine glands and intermingled endocrine cells to execute its diverse functions, including enzyme production for digestion of nutrients and hormone secretion for regulation of blood glucose levels. To define the molecular constituents with elevated expression in the human pancreas, we employed a genome-wide RNA sequencing analysis of the human transcriptome to identify genes with elevated expression in the human pancreas. This quantitative transcriptomics data was combined with immunohistochemistry-based protein profiling to allow mapping of the corresponding proteins to different compartments and specific cell types within the pancreas down to the single cell level. Analysis of whole pancreas identified 146 genes with elevated expression levels, of which 47 revealed a particular higher expression as compared to the other analyzed tissue types, thus termed pancreas enriched. Extended analysis of in vitro isolated endocrine islets identified an additional set of 42 genes with elevated expression in these specialized cells. Although only 0.7% of all genes showed an elevated expression level in the pancreas, this fraction of transcripts, in most cases encoding secreted proteins, constituted 68% of the total mRNA in pancreas. This demonstrates the extreme specialization of the pancreas for production of secreted proteins. Among the elevated expression profiles, several previously not described proteins were identified, both in endocrine cells (CFC1, FAM159B, RBPJL and RGS9) and exocrine glandular cells (AQP12A, DPEP1, GATM and ERP27). In summary, we provide a global analysis of the pancreas transcriptome and proteome with a comprehensive list of genes and proteins with elevated expression in pancreas. This list represents an important starting point for further studies of the molecular repertoire of pancreatic cells and their relation to disease states or treatment effects. PMID:25546435
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Bøhn, Siv K; Myhrstad, Mari C; Thoresen, Magne; Holden, Marit; Karlsen, Anette; Tunheim, Siv Haugen; Erlund, Iris; Svendsen, Mette; Seljeflot, Ingebjørg; Moskaug, Jan O; Duttaroy, Asim K; Laake, Petter; Arnesen, Harald; Tonstad, Serena; Collins, Andrew; Drevon, Christan A; Blomhoff, Rune
2010-09-16
Plant-based diets rich in fruit and vegetables can prevent development of several chronic age-related diseases. However, the mechanisms behind this protective effect are not elucidated. We have tested the hypothesis that intake of antioxidant-rich foods can affect groups of genes associated with cellular stress defence in human blood cells. NCT00520819 http://clinicaltrials.gov. In an 8-week dietary intervention study, 102 healthy male smokers were randomised to either a diet rich in various antioxidant-rich foods, a kiwifruit diet (three kiwifruits/d added to the regular diet) or a control group. Blood cell gene expression profiles were obtained from 10 randomly selected individuals of each group. Diet-induced changes on gene expression were compared to controls using a novel application of the gene set enrichment analysis (GSEA) on transcription profiles obtained using Affymetrix HG-U133-Plus 2.0 whole genome arrays. Changes were observed in the blood cell gene expression profiles in both intervention groups when compared to the control group. Groups of genes involved in regulation of cellular stress defence, such as DNA repair, apoptosis and hypoxia, were significantly upregulated (GSEA, FDR q-values < 5%) by both diets compared to the control group. Genes with common regulatory motifs for aryl hydrocarbon receptor (AhR) and AhR nuclear translocator (AhR/ARNT) were upregulated by both interventions (FDR q-values < 5%). Plasma antioxidant biomarkers (polyphenols/carotenoids) increased in both groups. The observed changes in the blood cell gene expression profiles suggest that the beneficial effects of a plant-based diet on human health may be mediated through optimization of defence processes.
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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.
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Understanding development and stem cells using single cell-based analyses of gene expression
Kumar, Pavithra; Tan, Yuqi
2017-01-01
In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells. PMID:28049689
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USDA-ARS?s Scientific Manuscript database
Mounting evidence shows microRNAs (miRNAs) directly regulate gene expression post-transcriptionally through base-pairing with regions in the 3’-untranslated sequences of target gene mRNAs, which results in dysregulation of gene expression/translation and subsequently modulates cellular processes. We...
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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.
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Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang
2017-08-23
Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.
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Bencurova, Petra; Baloun, Jiri; Musilova, Katerina; Radova, Lenka; Tichy, Boris; Pail, Martin; Zeman, Martin; Brichtova, Eva; Hermanova, Marketa; Pospisilova, Sarka; Mraz, Marek; Brazdil, Milan
2017-10-01
Mesial temporal lobe epilepsy (mTLE) is a severe neurological disorder characterized by recurrent seizures. mTLE is frequently accompanied by neurodegeneration in the hippocampus resulting in hippocampal sclerosis (HS), the most common morphological correlate of drug resistance in mTLE patients. Incomplete knowledge of pathological changes in mTLE+HS complicates its therapy. The pathological mechanism underlying mTLE+HS may involve abnormal gene expression regulation, including posttranscriptional networks involving microRNAs (miRNAs). miRNA expression deregulation has been reported in various disorders, including epilepsy. However, the miRNA profile of mTLE+HS is not completely known and needs to be addressed. Here, we have focused on hippocampal miRNA profiling in 33 mTLE+HS patients and nine postmortem controls to reveal abnormally expressed miRNAs. In this study, we significantly reduced technology-related bias (the most common source of false positivity in miRNA profiling data) by combining two different miRNA profiling methods, namely next generation sequencing and miRNA-specific quantitative real-time polymerase chain reaction. These methods combined have identified and validated 20 miRNAs with altered expression in the human epileptic hippocampus; 19 miRNAs were up-regulated and one down-regulated in mTLE+HS patients. Nine of these miRNAs have not been previously associated with epilepsy, and 19 aberrantly expressed miRNAs potentially regulate the targets and pathways linked with epilepsy (such as potassium channels, γ-aminobutyric acid, neurotrophin signaling, and axon guidance). This study extends current knowledge of miRNA-mediated gene expression regulation in mTLE+HS by identifying miRNAs with altered expression in mTLE+HS, including nine novel abnormally expressed miRNAs and their putative targets. These observations further encourage the potential of microRNA-based biomarkers or therapies. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.
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Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE
Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.
2009-01-01
Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438
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Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.
Bowes Rickman, Catherine; Ebright, Jessica N; Zavodni, Zachary J; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P; Wistow, Graeme; Boon, Kathy; Hauser, Michael A
2006-06-01
To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. The EyeSAGE database, combining three different gene-profiling platforms including the authors' multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.
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Weigt, S Samuel; Wang, Xiaoyan; Palchevskiy, Vyacheslav; Patel, Naman; Derhovanessian, Ariss; Shino, Michael Y; Sayah, David M; Lynch, Joseph P; Saggar, Rajan; Ross, David J; Kubak, Bernie M; Ardehali, Abbas; Palmer, Scott; Husain, Shahid; Belperio, John A
2018-06-01
Aspergillus colonization after lung transplant is associated with an increased risk of chronic lung allograft dysfunction (CLAD). We hypothesized that gene expression during Aspergillus colonization could provide clues to CLAD pathogenesis. We examined transcriptional profiles in 3- or 6-month surveillance bronchoalveolar lavage fluid cell pellets from recipients with Aspergillus fumigatus colonization (n = 12) and without colonization (n = 10). Among the Aspergillus colonized, we also explored profiles in those who developed CLAD (n = 6) or remained CLAD-free (n = 6). Transcription profiles were assayed with the HG-U133 Plus 2.0 microarray (Affymetrix). Differential gene expression was based on an absolute fold difference of 2.0 or greater and unadjusted P value less than 0.05. We used NIH Database for Annotation, Visualization and Integrated Discovery for functional analyses, with false discovery rates less than 5% considered significant. Aspergillus colonization was associated with differential expression of 489 probe sets, representing 404 unique genes. "Defense response" genes and genes in the "cytokine-cytokine receptor" Kyoto Encyclopedia of Genes and Genomes pathway were notably enriched in this list. Among Aspergillus colonized patients, CLAD development was associated with differential expression of 69 probe sets, representing 64 unique genes. This list was enriched for genes involved in "immune response" and "response to wounding", among others. Notably, both chitinase 3-like-1 and chitotriosidase were associated with progression to CLAD. Aspergillus colonization is associated with gene expression profiles related to defense responses including cytokine signaling. Epithelial wounding, as well as the innate immune response to chitin that is present in the fungal cell wall, may be key in the link between Aspergillus colonization and CLAD.
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Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic
2006-04-27
Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.
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Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic
2006-01-01
Background Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. Results The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. Conclusion RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts. PMID:16643667
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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
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RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.
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.
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Ketterer, Caroline; Zeiger, Ulrike; Budak, Murat T.; Rubinstein, Neal A.; Khurana, Tejvir S.
2010-01-01
Purpose. To examine and characterize the profile of genes expressed at the synapses or neuromuscular junctions (NMJs) of extraocular muscles (EOMs) compared with those expressed at the tibialis anterior (TA). Methods. Adult rat eyeballs with rectus EOMs attached and TAs were dissected, snap frozen, serially sectioned, and stained for acetylcholinesterase (AChE) to identify the NMJs. Approximately 6000 NMJs for rectus EOM (EOMsyn), 6000 NMJs for TA (TAsyn), equal amounts of NMJ-free fiber regions (EOMfib, TAfib), and underlying myonuclei and RNAs were captured by laser capture microdissection (LCM). RNA was processed for microarray-based expression profiling. Expression profiles and interaction lists were generated for genes differentially expressed at synaptic and nonsynaptic regions of EOM (EOMsyn versus EOMfib) and TA (TAsyn versus TAfib). Profiles were validated by using real-time quantitative polymerase chain reaction (qPCR). Results. The regional transcriptomes associated with NMJs of EOMs and TAs were identified. Two hundred seventy-five genes were preferentially expressed in EOMsyn (compared with EOMfib), 230 in TAsyn (compared with TAfib), and 288 additional transcripts expressed in both synapses. Identified genes included novel genes as well as well-known, evolutionarily conserved synaptic markers (e.g., nicotinic acetylcholine receptor (AChR) alpha (Chrna) and epsilon (Chrne) subunits and nestin (Nes). Conclusions. Transcriptome level differences exist between EOM synaptic regions and TA synaptic regions. The definition of the synaptic transcriptome provides insight into the mechanism of formation and functioning of the unique synapses of EOM and their differential involvement in diseases noted in the EOM allotype. PMID:20393109
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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. ...
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Transcriptional profiling of murine osteoblast differentiation based on RNA-seq expression analyses.
Khayal, Layal Abo; Grünhagen, Johannes; Provazník, Ivo; Mundlos, Stefan; Kornak, Uwe; Robinson, Peter N; Ott, Claus-Eric
2018-04-11
Osteoblastic differentiation is a multistep process characterized by osteogenic induction of mesenchymal stem cells, which then differentiate into proliferative pre-osteoblasts that produce copious amounts of extracellular matrix, followed by stiffening of the extracellular matrix, and matrix mineralization by hydroxylapatite deposition. Although these processes have been well characterized biologically, a detailed transcriptional analysis of murine primary calvaria osteoblast differentiation based on RNA sequencing (RNA-seq) analyses has not previously been reported. Here, we used RNA-seq to obtain expression values of 29,148 genes at four time points as murine primary calvaria osteoblasts differentiate in vitro until onset of mineralization was clearly detectable by microscopic inspection. Expression of marker genes confirmed osteogenic differentiation. We explored differential expression of 1386 protein-coding genes using unsupervised clustering and GO analyses. 100 differentially expressed lncRNAs were investigated by co-expression with protein-coding genes that are localized within the same topologically associated domain. Additionally, we monitored expression of 237 genes that are silent or active at distinct time points and compared differential exon usage. Our data represent an in-depth profiling of murine primary calvaria osteoblast differentiation by RNA-seq and contribute to our understanding of genetic regulation of this key process in osteoblast biology. Copyright © 2018 Elsevier Inc. All rights reserved.
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Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E
2007-12-01
We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.
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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
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Pasricha, Shivani; Payne, Michael; Canovas, David; Pase, Luke; Ngaosuwankul, Nathamon; Beard, Sally; Oshlack, Alicia; Smyth, Gordon K.; Chaiyaroj, Sansanee C.; Boyce, Kylie J.; Andrianopoulos, Alex
2013-01-01
Penicillium marneffei is an opportunistic human pathogen endemic to Southeast Asia. At 25° P. marneffei grows in a filamentous hyphal form and can undergo asexual development (conidiation) to produce spores (conidia), the infectious agent. At 37° P. marneffei grows in the pathogenic yeast cell form that replicates by fission. Switching between these growth forms, known as dimorphic switching, is dependent on temperature. To understand the process of dimorphic switching and the physiological capacity of the different cell types, two microarray-based profiling experiments covering approximately 42% of the genome were performed. The first experiment compared cells from the hyphal, yeast, and conidiation phases to identify “phase or cell-state–specific” gene expression. The second experiment examined gene expression during the dimorphic switch from one morphological state to another. The data identified a variety of differentially expressed genes that have been organized into metabolic clusters based on predicted function and expression patterns. In particular, C-14 sterol reductase–encoding gene ergM of the ergosterol biosynthesis pathway showed high-level expression throughout yeast morphogenesis compared to hyphal. Deletion of ergM resulted in severe growth defects with increased sensitivity to azole-type antifungal agents but not amphotericin B. The data defined gene classes based on spatio-temporal expression such as those expressed early in the dimorphic switch but not in the terminal cell types and those expressed late. Such classifications have been helpful in linking a given gene of interest to its expression pattern throughout the P. marneffei dimorphic life cycle and its likely role in pathogenicity. PMID:24062530
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Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.
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.
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Zhang, Shu-Dong; Gant, Timothy W
2009-07-31
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.
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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.
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Two-pass imputation algorithm for missing value estimation in gene expression time series.
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.
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Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru
2012-01-01
Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls. PMID:22348066
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Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun
2018-01-01
The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.
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Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling
2018-01-01
The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components. PMID:29692857
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Knapp, Dunja; Schulz, Herbert; Rascon, Cynthia Alexander; Volkmer, Michael; Scholz, Juliane; Nacu, Eugen; Le, Mu; Novozhilov, Sergey; Tazaki, Akira; Protze, Stephanie; Jacob, Tina; Hubner, Norbert; Habermann, Bianca; Tanaka, Elly M.
2013-01-01
Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression – early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation. PMID:23658691
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A multiplex branched DNA assay for parallel quantitative gene expression profiling.
Flagella, Michael; Bui, Son; Zheng, Zhi; Nguyen, Cung Tuong; Zhang, Aiguo; Pastor, Larry; Ma, Yunqing; Yang, Wen; Crawford, Kimberly L; McMaster, Gary K; Witney, Frank; Luo, Yuling
2006-05-01
We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.
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Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz
2009-08-25
Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.
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Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz
2009-01-01
Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156
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Xin, Chengqi; Liu, Wanfei; Lin, Qiang; Zhang, Xiaowei; Cui, Peng; Li, Fusen; Zhang, Guangyu; Pan, Linlin; Al-Amer, Ali; Mei, Hailiang; Al-Mssallem, Ibrahim S; Hu, Songnian; Al-Johi, Hasan Awad; Yu, Jun
2015-04-01
MicroRNAs (miRNAs) play crucial roles in multiple stages of plant development and regulate gene expression at posttranscriptional and translational levels. In this study, we first identified 238 conserved miRNAs in date palm (Phoenix dactylifera) based on a high-quality genome assembly and defined 78 fruit-development-associated (FDA) miRNAs, whose expression profiles are variable at different fruit development stages. Using experimental data, we subsequently detected 276 novel P. dactylifera-specific FDA miRNAs and predicted their targets. We also revealed that FDA miRNAs function mainly in regulating genes involved in starch/sucrose metabolisms and other carbon metabolic pathways; among them, 221 FDA miRNAs exhibit negative correlation with their corresponding targets, which suggests their direct regulatory roles on mRNA targets. Our data define a comprehensive set of conserved and novel FDA miRNAs along with their expression profiles, which provide a basis for further experimentation in assigning discrete functions of these miRNAs in P. dactylifera fruit development. Copyright © 2015. Published by Elsevier Inc.
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Generation of miniaturized planar ecombinant antibody arrays using a microcantilever-based printer
NASA Astrophysics Data System (ADS)
Petersson, Linn; Berthet Duroure, Nathalie; Auger, Angèle; Dexlin-Mellby, Linda; Borrebaeck, Carl AK; Ait Ikhlef, Ali; Wingren, Christer
2014-07-01
Miniaturized (Ø 10 μm), multiplexed (>5-plex), and high-density (>100 000 spots cm-2) antibody arrays will play a key role in generating protein expression profiles in health and disease. However, producing such antibody arrays is challenging, and it is the type and range of available spotters which set the stage. This pilot study explored the use of a novel microspotting tool, BioplumeTM—consisting of an array of micromachined silicon cantilevers with integrated microfluidic channels—to produce miniaturized, multiplexed, and high-density planar recombinant antibody arrays for protein expression profiling which targets crude, directly labelled serum. The results demonstrated that 16-plex recombinant antibody arrays could be produced—based on miniaturized spot features (78.5 um2, Ø 10 μm) at a 7-125-times increased spot density (250 000 spots cm-2), interfaced with a fluorescent-based read-out. This prototype platform was found to display adequate reproducibility (spot-to-spot) and an assay sensitivity in the pM range. The feasibility of the array platform for serum protein profiling was outlined.
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Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.
Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio
2017-10-06
Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.
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Comparative transcriptional profiling identifies takeout as a gene that regulates life span
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
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Technical variables in high-throughput miRNA expression profiling: much work remains to be done.
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.
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Ma, Siming; Upneja, Akhil; Galecki, Andrzej; Tsai, Yi-Miau; Burant, Charles F; Raskind, Sasha; Zhang, Quanwei; Zhang, Zhengdong D; Seluanov, Andrei; Gorbunova, Vera; Clish, Clary B; Miller, Richard A; Gladyshev, Vadim N
2016-11-22
Mammalian lifespan differs by >100 fold, but the mechanisms associated with such longevity differences are not understood. Here, we conducted a study on primary skin fibroblasts isolated from 16 species of mammals and maintained under identical cell culture conditions. We developed a pipeline for obtaining species-specific ortholog sequences, profiled gene expression by RNA-seq and small molecules by metabolite profiling, and identified genes and metabolites correlating with species longevity. Cells from longer lived species up-regulated genes involved in DNA repair and glucose metabolism, down-regulated proteolysis and protein transport, and showed high levels of amino acids but low levels of lysophosphatidylcholine and lysophosphatidylethanolamine. The amino acid patterns were recapitulated by further analyses of primate and bird fibroblasts. The study suggests that fibroblast profiling captures differences in longevity across mammals at the level of global gene expression and metabolite levels and reveals pathways that define these differences.
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GTA: a game theoretic approach to identifying cancer subnetwork markers.
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.
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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
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A stochastic model for optimizing composite predictors based on gene expression profiles.
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.
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Quality Assurance of RNA Expression Profiling in Clinical Laboratories
Tang, Weihua; Hu, Zhiyuan; Muallem, Hind; Gulley, Margaret L.
2012-01-01
RNA expression profiles are increasingly used to diagnose and classify disease, based on expression patterns of as many as several thousand RNAs. To ensure quality of expression profiling services in clinical settings, a standard operating procedure incorporates multiple quality indicators and controls, beginning with preanalytic specimen preparation and proceeding thorough analysis, interpretation, and reporting. Before testing, histopathological examination of each cellular specimen, along with optional cell enrichment procedures, ensures adequacy of the input tissue. Other tactics include endogenous controls to evaluate adequacy of RNA and exogenous or spiked controls to evaluate run- and patient-specific performance of the test system, respectively. Unique aspects of quality assurance for array-based tests include controls for the pertinent outcome signatures that often supersede controls for each individual analyte, built-in redundancy for critical analytes or biochemical pathways, and software-supported scrutiny of abundant data by a laboratory physician who interprets the findings in a manner facilitating appropriate medical intervention. Access to high-quality reagents, instruments, and software from commercial sources promotes standardization and adoption in clinical settings, once an assay is vetted in validation studies as being analytically sound and clinically useful. Careful attention to the well-honed principles of laboratory medicine, along with guidance from government and professional groups on strategies to preserve RNA and manage large data sets, promotes clinical-grade assay performance. PMID:22020152
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Comparison of gene expression and fatty acid profiles in concentrate and forage finished beef.
Buchanan, J W; Garmyn, A J; Hilton, G G; VanOverbeke, D L; Duan, Q; Beitz, D C; Mateescu, R G
2013-01-01
Fatty acid profiles and intramuscular expression of genes involved in fatty acid metabolism were characterized in concentrate- (CO) and forage- (FO) based finishing systems. Intramuscular samples from the adductor were taken at slaughter from 99 heifers finished on a CO diet and 58 heifers finished on a FO diet. Strip loins were obtained at fabrication to evaluate fatty acid profiles of LM muscle for all 157 heifers by using gas chromatography fatty acid methyl ester analysis. Composition was analyzed for differences by using the General Linear Model (GLM) procedure in SAS. Differences in fatty acid profile included a greater atherogenic index, greater percentage total MUFA, decreased omega-3 to omega-6 ratio, decreased percentage total PUFA, and decreased percentage omega-3 fatty acids in CO- compared with FO-finished heifers (P<0.05). Fatty acid profiles from intramuscular samples were ranked by the atherogenic index, and 20 heifers with either a high (HAI; n=10) or low (LAI; n=10) atherogenic index were selected for gene expression analysis using real-time PCR (RT-PCR). Gene expression data for the 20 individuals were analyzed as a 2 by 2 factorial arrangement of treatments using the GLM procedure in SAS. There was no significant diet × atherogenic index interaction identified for any gene (P>0.05). Upregulation was observed for PPARγ, fatty acid synthase (FASN), and fatty acid binding protein 4 (FABP4) in FO-finished compared with CO-finished heifers in both atherogenic index categories (P<0.05). Upregulation of diglyceride acyl transferase 2 (DGAT2) was observed in FO-finished heifers with a HAI (P<0.05). Expression of steroyl Co-A desaturase (SCD) was upregulated in CO-finished heifers with a LAI, and downregulated in FO-finished heifers with a HAI (P<0.05). Expression of adiponectin (ADIPOQ) was significantly downregulated in CO-finished heifers with a HAI compared with all other categories (P<0.05). The genes identified in this study which exhibit differential regulation in response to diet or in animals with extreme fatty acid profiles may provide genetic markers for selecting desirable fatty acid profiles in future selection programs.
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Unsupervised Outlier Profile Analysis
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
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Understanding development and stem cells using single cell-based analyses of gene expression.
Kumar, Pavithra; Tan, Yuqi; Cahan, Patrick
2017-01-01
In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells. © 2017. Published by The Company of Biologists Ltd.
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Bone-related gene profiles in developing calvaria.
Cho, Je-Yoel; Lee, Won-Bong; Kim, Hyun-Jung; Mi Woo, Kyung; Baek, Jeong-Hwa; Choi, Je-Yong; Hur, Cheol-Gu; Ryoo, Hyun-Mo
2006-05-10
Generating a comprehensive understanding of osteogenesis-related gene profiles is very important in the development of new treatments for osteopenic conditions. Developing calvaria undergoes a typical intramembranous bone-forming process. To identify genes associated with osteoblast differentiation, we isolated total RNAs from parietal bones, that represent active osteoblasts, and sutural mesenchyme, that represents osteoprogenitor cells, and comprehensively analyzed their gene expression profiles using an oligo-based Affymetrix microarray chip containing 22,690 probes. About 2100 genes with "Present" calls had more than 2-fold higher expression in bone compared to sutures while 73 of these genes had more than 8-fold expression. Some of these genes are already known to be bone-related biomarkers: VitD receptor, bone sialoprotein, osteocalcin, osteopontin, MMP13, etc. Eight genes were selected and subjected to confirmation by quantitative real-time RT-PCR analyses. All the genes tested showed higher expression in bones, ranging from 5- to 140-fold. Several of these genes are ESTs while others are already known but their functions in osteogenesis were not previously known. Most genes of the BMP and FGF families probed in the Genechip analysis were more highly expressed in bone tissues compared to suture. All differentially-expressed Runx and Dlx family genes also showed higher expression in bone. These results imply that our data is valid and can be used as a good standard for the mining of osteogenesis-related genes.
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Shang, Haihong; Li, Wei; Zou, Changsong; Yuan, Youlu
2013-07-01
NAC domain proteins are plant-specific transcription factors known to play diverse roles in various plant developmental processes. In the present study, we performed the first comprehensive study of the NAC gene family in Gossypium raimondii Ulbr., incorporating phylogenetic, chromosomal location, gene structure, conserved motif, and expression profiling analyses. We identified 145 NAC transcription factor (NAC-TF) genes that were phylogenetically clustered into 18 distinct subfamilies. Of these, 127 NAC-TF genes were distributed across the 13 chromosomes, 80 (55%) were preferentially retained duplicates located in both duplicated regions and six were located in triplicated chromosomal regions. The majority of NAC-TF genes showed temporal-, spatial-, and tissue-specific expression patterns based on transcriptomic and qRT-PCR analyses. However, the expression patterns of several duplicate genes were partially redundant, suggesting the occurrence of sub-functionalization during their evolution. Based on their genomic organization, we concluded that genomic duplications contributed significantly to the expansion of the NAC-TF gene family in G. raimondii. Comprehensive analysis of their expression profiles could provide novel insights into the functional divergence among members of the NAC gene family in G. raimondii. © 2013 Institute of Botany, Chinese Academy of Sciences.
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Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J
2015-07-01
Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
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Higashiyama, Hiroyuki; Billin, Andrew N; Okamoto, Yuji; Kinoshita, Mine; Asano, Satoshi
2007-05-01
Peroxisome proliferator-activated receptor-delta (PPAR-delta) is known as a transcription factor involved in the regulation of fatty acid oxidation and mitochondrial biogenesis in several tissues, such as skeletal muscle, liver and adipose tissues. In this study, to elucidate systemic physiological functions of PPAR-delta, we examined the tissue distribution and localization of PPAR-delta in adult mouse tissues using tissue microarray (TMA)-based immunohistochemistry. PPAR-delta positive signals were observed on variety of tissues/cells in multiple systems including cardiovascular, urinary, respiratory, digestive, endocrine, nervous, hematopoietic, immune, musculoskeletal, sensory and reproductive organ systems. In these organs, PPAR-delta immunoreactivity was generally localized on the nucleus, although cytoplasmic localization was observed on several cell types including neurons in the nervous system and cells of the islet of Langerhans. These expression profiling data implicate various physiological roles of PPAR-delta in multiple organ systems. TMA-based immunohistochemistry enables to profile comprehensive protein localization and distribution in a high-throughput manner.
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Takahashi, Junko; Waki, Shiori; Matsumoto, Rena; Odake, Junji; Miyaji, Takayuki; Tottori, Junichi; Iwanaga, Takehiro; Iwahashi, Hitoshi
2012-01-01
Background Hyperlipidemia animal models have been established, but complete gene expression profiles of the transition from normal lipid levels have not been obtained. Miniature pigs are useful model animals for gene expression studies on dietary-induced hyperlipidemia because they have a similar anatomy and digestive physiology to humans, and blood samples can be obtained from them repeatedly. Methodology Two typical dietary treatments were used for dietary-induced hyperlipidemia models, by using specific pathogen-free (SPF) Clawn miniature pigs. One was a high-fat and high-cholesterol diet (HFCD) and the other was a high-fat, high-cholesterol, and high-sucrose diet (HFCSD). Microarray analyses were conducted from whole blood samples during the dietary period and from white blood cells at the end of the dietary period to evaluate the transition of expression profiles of the two dietary models. Principal Findings Variations in whole blood gene expression intensity within the HFCD or the HFCSD group were in the same range as the controls provide with normal diet at all periods. This indicates uniformity of dietary-induced hyperlipidemia for our dietary protocols. Gene ontology- (GO) based functional analyses revealed that characteristics of the common changes between HFCD and HFCSD were involved in inflammatory responses and reproduction. The correlation coefficient between whole blood and white blood cell expression profiles at 27 weeks with the HFCSD diet was significantly lower than that of the control and HFCD diet groups. This may be due to the effects of RNA originating from the tissues and/or organs. Conclusions No statistically significant differences in fasting plasma lipids and glucose levels between the HFCD and HFCSD groups were observed. However, blood RNA analyses revealed different characteristics corresponding to the dietary protocols. In this study, whole blood RNA analyses proved to be a useful tool to evaluate transitions in dietary-induced hyperlipidemia gene expression profiles in miniature pigs. PMID:22662175
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Peterson, Leif E
2002-01-01
CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816
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Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213
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
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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.
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Leaphart, Adam B.; Thompson, Dorothea K.; Huang, Katherine; Alm, Eric; Wan, Xiu-Feng; Arkin, Adam; Brown, Steven D.; Wu, Liyou; Yan, Tingfen; Liu, Xueduan; Wickham, Gene S.; Zhou, Jizhong
2006-01-01
The molecular response of Shewanella oneidensis MR-1 to variations in extracellular pH was investigated based on genomewide gene expression profiling. Microarray analysis revealed that cells elicited both general and specific transcriptome responses when challenged with environmental acid (pH 4) or base (pH 10) conditions over a 60-min period. Global responses included the differential expression of genes functionally linked to amino acid metabolism, transcriptional regulation and signal transduction, transport, cell membrane structure, and oxidative stress protection. Response to acid stress included the elevated expression of genes encoding glycogen biosynthetic enzymes, phosphate transporters, and the RNA polymerase sigma-38 factor (rpoS), whereas the molecular response to alkaline pH was characterized by upregulation of nhaA and nhaR, which are predicted to encode an Na+/H+ antiporter and transcriptional activator, respectively, as well as sulfate transport and sulfur metabolism genes. Collectively, these results suggest that S. oneidensis modulates multiple transporters, cell envelope components, and pathways of amino acid consumption and central intermediary metabolism as part of its transcriptome response to changing external pH conditions. PMID:16452448
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Bautista-Herrera, L A; De la Cruz-Mosso, U; Morales-Zambrano, R; Villanueva-Quintero, G D; Hernández-Bello, J; Ramírez-Dueñas, M G; Martínez-López, E; Brennan-Bourdon, L M; Baños-Hernández, C J; Muñoz-Valle, J F
2018-05-01
Psoriatic arthritis (PsA) is an autoimmune inflammatory disease associated with psoriasis. The cause of this pathology is still unknown, but research suggests the diseases are caused by a deregulated cytokine production. MIF is a cytokine associated with immunomodulation of Th1, Th2, and Th17 cytokine profiles in inflammatory diseases. Based on this knowledge, the aim of this study was to determine the association of MIF and TNFA expression with Th1, Th2, and Th17 cytokine profiles in serum levels of PsA patients. A cross-sectional study was performed in 50 PsA patients and 30 control subjects (CS). The cytokine profiles were quantified by BioPlex MagPix system and the mRNA expression levels by real-time PCR. TNFA mRNA expression was 138.81-folds higher in PsA patients than CS (p < 0.001). Regarding MIF mRNA expression, no significant differences were observed; however, a positive correlation was identified between MIF mRNA expression and PsA time of evolution (r = - 0.53, p = 0.009). An increase of Th1 (IFNγ: PsA = 37.1 pg/mL vs. CS = 17 pg/mL, p < 0.05; TNFα: PsA = 24.6 pg/mL vs. CS = 9.8 pg/mL, p < 0.0001) and Th17 cytokine profiles (IL-17: PsA = 6.4 pg/mL vs. CS = 2.7 pg/mL, p < 0.05; IL-22: PsA = 8.4 pg/mL vs. CS = 1.8 pg/mL, p < 0.001), were found in PsA patients. Th2 cytokines were not significantly different in both groups. In conclusion, a high expression of TNFA mRNA, as well as an increase of Th1 and Th17 cytokine profiles evaluated by IFNγ, TNFα, IL-17, and IL-22 cytokines, was observed in PsA patients.
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The Role of Vitamin D in the Transcriptional Program of Human Pregnancy
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
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Rani, Lata; Mathur, Nitin; Gupta, Ritu; Gogia, Ajay; Kaur, Gurvinder; Dhanjal, Jaspreet Kaur; Sundar, Durai; Kumar, Lalit; Sharma, Atul
2017-01-01
In chronic lymphocytic leukemia (CLL), epigenomic and genomic studies have expanded the existing knowledge about the disease biology and led to the identification of potential biomarkers relevant for implementation of personalized medicine. In this study, an attempt has been made to examine and integrate the global DNA methylation changes with gene expression profile and their impact on clinical outcome in early stage CLL patients. The integration of DNA methylation profile ( n = 14) with the gene expression profile ( n = 21) revealed 142 genes as hypermethylated-downregulated and; 62 genes as hypomethylated-upregulated in early stage CLL patients compared to CD19+ B-cells from healthy individuals. The mRNA expression levels of 17 genes identified to be differentially methylated and/or differentially expressed was further examined in early stage CLL patients ( n = 93) by quantitative real time PCR (RQ-PCR). Significant differences were observed in the mRNA expression of MEIS1 , PMEPA1 , SOX7 , SPRY1 , CDK6 , TBX2 , and SPRY2 genes in CLL cells as compared to B-cells from healthy individuals. The analysis in the IGHV mutation based categories (Unmutated = 39, Mutated = 54) revealed significantly higher mRNA expression of CRY1 and PAX9 genes in the IGHV unmutated subgroup ( p < 0.001). The relative risk of treatment initiation was significantly higher among patients with high expression of CRY1 (RR = 1.91, p = 0.005) or PAX9 (RR = 1.87, p = 0.001). High expression of CRY1 (HR: 3.53, p < 0.001) or PAX9 (HR: 3.14, p < 0.001) gene was significantly associated with shorter time to first treatment. The high expression of PAX9 gene (HR: 3.29, 95% CI 1.172-9.272, p = 0.016) was also predictive of shorter overall survival in CLL. The DNA methylation changes associated with mRNA expression of CRY1 and PAX9 genes allow risk stratification of early stage CLL patients. This comprehensive analysis supports the concept that the epigenetic changes along with the altered expression of genes have the potential to predict clinical outcome in early stage CLL patients.
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Zhang, Xiao; Chen, Jiamin; Radcliffe, Tom; LeBrun, Dave P.; Tron, Victor A.; Feilotter, Harriet
2008-01-01
MicroRNAs (miRNAs) are small, noncoding RNAs that suppress gene expression at the posttranscriptional level via an antisense RNA-RNA interaction. miRNAs used for array-based profiling are generally purified from either snap-frozen or fresh samples. Because tissues found in most pathology departments are available only in formalin-fixed and paraffin-embedded (FFPE) states, we sought to evaluate miRNA derived from FFPE samples for microarray analysis. In this study, miRNAs extracted from matched snap-frozen and FFPE samples were profiled using the Agilent miRNA array platform (Agilent, Santa Clara, CA). Each miRNA sample was hybridized to arrays containing probes interrogating 470 human miRNAs. Seven cases were compared in either duplicate or triplicate. Intrachip and interchip analyses demonstrated that the processes of miRNA extraction, labeling, and hybridization from both frozen and FFPE samples are highly reproducible and add little variation to the results; technical replicates showed high correlations with one another (Kendall tau, 0.722 to 0.853; Spearman rank correlation coefficient, 0.891 to 0.954). Our results showed consistent high correlations between matched frozen and FFPE samples (Kendall tau, 0.669 to 0.815; Spearman rank correlation coefficient, 0.847 to 0.948), supporting the use of FFPE-derived miRNAs for array-based, gene expression profiling. PMID:18832457
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Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.
2015-01-01
Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735
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Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M
2015-01-01
Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.
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Analysis of blood-based gene expression in idiopathic Parkinson disease.
Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri
2017-10-17
To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.
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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
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Pei, Haixia; Ma, Nan; Chen, Jiwei; Zheng, Yi; Tian, Ji; Li, Jing; Zhang, Shuai; Fei, Zhangjun; Gao, Junping
2013-01-01
MicroRNAs play an important role in plant development and plant responses to various biotic and abiotic stimuli. As one of the most important ornamental crops, rose (Rosa hybrida) possesses several specific morphological and physiological features, including recurrent flowering, highly divergent flower shapes, colors and volatiles. Ethylene plays an important role in regulating petal cell expansion during rose flower opening. Here, we report the population and expression profiles of miRNAs in rose petals during flower opening and in response to ethylene based on high throughput sequencing. We identified a total of 33 conserved miRNAs, as well as 47 putative novel miRNAs were identified from rose petals. The conserved and novel targets to those miRNAs were predicted using the rose floral transcriptome database. Expression profiling revealed that expression of 28 known (84.8% of known miRNAs) and 39 novel (83.0% of novel miRNAs) miRNAs was substantially changed in rose petals during the earlier opening period. We also found that 28 known and 22 novel miRNAs showed expression changes in response to ethylene treatment. Furthermore, we performed integrative analysis of expression profiles of miRNAs and their targets. We found that ethylene-caused expression changes of five miRNAs (miR156, miR164, miR166, miR5139 and rhy-miRC1) were inversely correlated to those of their seven target genes. These results indicate that these miRNA/target modules might be regulated by ethylene and were involved in ethylene-regulated petal growth. PMID:23696879
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Gene expression profile of isolated rat adipocytes treated with anthocyanins.
Tsuda, Takanori; Ueno, Yuki; Kojo, Hitoshi; Yoshikawa, Toshikazu; Osawa, Toshihiko
2005-04-15
Adipocyte dysfunction is strongly associated with the development of obesity and insulin resistance. It is accepted that the regulation of adipocytokine secretion or the adipocyte specific gene expression is one of the most important targets for the prevention of obesity and amelioration of insulin sensitivity. Recently, we demonstrated that anthocyanins, which are pigments widespread in the plant kingdom, have the potency of anti-obesity in mice and the enhancement adipocytokine secretion and adipocyte gene expression in adipocytes. In this study, we have shown for the first time the gene expression profile in isolated rat adipocytes treated with anthocyanins (cyanidin 3-glucoside; C3G or cyanidin; Cy). The rat adipocytes were treated with 100 muM C3G, Cy or vehicle for 24 h. The total RNA from the adipocytes was isolated and carried out GeneChip microarray analysis. A total of 633 or 427 genes was up-regulated (>1.5-fold) by the treatment of adipocytes with C3G or Cy, respectively. The up-regulated genes include lipid metabolism and signal transduction-related genes, however, the altered genes were partly different between the C3G- and Cy-treated groups. Based on the gene expression profile, we demonstrated the up-regulation of hormone sensitive lipase and enhancement of the lipolytic activity by the treatment of adipocytes with C3G or Cy. These data have provided an overview of the gene expression profiles in adipocytes treated with anthocyanins and identified new responsive genes with potentially important functions in adipocytes related with obesity and diabetes that merit further investigation.
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Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.
Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P
2017-11-23
The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In addition, the data provides additional evidence in favor of and against the similarity-based functions assigned to uncharacterized genes.
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Sweeney, Torres; Lejeune, Alex; Moloney, Aidan P; Monahan, Frank J; Gettigan, Paul Mc; Downey, Gerard; Park, Stephen D E; Ryan, Marion T
2016-09-21
Differences between cattle production systems can influence the nutritional and sensory characteristics of beef, in particular its fatty acid (FA) composition. As beef products derived from pasture-based systems can demand a higher premium from consumers, there is a need to understand the biological characteristics of pasture produced meat and subsequently to develop methods of authentication for these products. Here, we describe an approach to authentication that focuses on differences in the transcriptomic profile of muscle from animals finished in different systems of production of practical relevance to the Irish beef industry. The objectives of this study were to identify a panel of differentially expressed (DE) genes/networks in the muscle of cattle raised outdoors on pasture compared to animals raised indoors on a concentrate based diet and to subsequently identify an optimum panel which can classify the meat based on a production system. A comparison of the muscle transcriptome of outdoor/pasture-fed and Indoor/concentrate-fed cattle resulted in the identification of 26 DE genes. Functional analysis of these genes identified two significant networks (1: Energy Production, Lipid Metabolism, Small Molecule Biochemistry; and 2: Lipid Metabolism, Molecular Transport, Small Molecule Biochemistry), both of which are involved in FA metabolism. The expression of selected up-regulated genes in the outdoor/pasture-fed animals correlated positively with the total n-3 FA content of the muscle. The pathway and network analysis of the DE genes indicate that peroxisome proliferator-activated receptor (PPAR) and FYN/AMPK could be implicit in the regulation of these alterations to the lipid profile. In terms of authentication, the expression profile of three DE genes (ALAD, EIF4EBP1 and NPNT) could almost completely separate the samples based on production system (95 % authentication for animals on pasture-based and 100 % for animals on concentrate- based diet) in this context. The majority of DE genes between muscle of the outdoor/pasture-fed and concentrate-fed cattle were related to lipid metabolism and in particular β-oxidation. In this experiment the combined expression profiles of ALAD, EIF4EBP1 and NPNT were optimal in classifying the muscle transcriptome based on production system. Given the overall lack of comparable studies and variable concordance with those that do exist, the use of transcriptomic data in authenticating production systems requires more exploration across a range of contexts and breeds.
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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.
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Li, Yong-Fang; Mahalingam, Ramamurthy; Sunkar, Ramanjulu
2017-01-01
Alteration of gene expression is an essential mechanism, which allows plants to respond and adapt to adverse environmental conditions. Transcriptome and proteome analyses in plants exposed to abiotic stresses revealed that protein levels are not correlated with the changes in corresponding mRNAs, indicating regulation at translational level is another major regulator for gene expression. Analysis of translatome, which refers to all mRNAs associated with ribosomes, thus has the potential to bridge the gap between transcriptome and proteome. Polysomal RNA profiling and recently developed ribosome profiling (Ribo-seq) are two main methods for translatome analysis at global level. Here, we describe the classical procedure for polysomal RNA isolation by sucrose gradient ultracentrifugation followed by highthroughput RNA-seq to identify genes regulated at translational level. Polysomal RNA can be further used for a variety of downstream applications including Northern blot analysis, qRT-PCR, RNase protection assay, and microarray-based gene expression profiling.
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Single cell gene expression profiling in Alzheimer's disease.
Ginsberg, Stephen D; Che, Shaoli; Counts, Scott E; Mufson, Elliott J
2006-07-01
Development and implementation of microarray techniques to quantify expression levels of dozens to hundreds to thousands of transcripts simultaneously within select tissue samples from normal control subjects and neurodegenerative diseased brains has enabled scientists to create molecular fingerprints of vulnerable neuronal populations in Alzheimer's disease (AD) and related disorders. A goal is to sample gene expression from homogeneous cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and nonneuronal cells. The precise resolution afforded by single cell and population cell RNA analysis in combination with microarrays and real-time quantitative polymerase chain reaction (qPCR)-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease progression. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models of neurodegeneration as well as postmortem human brain tissues. Gene expression analysis in postmortem AD brain regions including the hippocampal formation and neocortex reveals selectively vulnerable cell types share putative pathogenetic alterations in common classes of transcripts, for example, markers of glutamatergic neurotransmission, synaptic-related markers, protein phosphatases and kinases, and neurotrophins/neurotrophin receptors. Expression profiles of vulnerable regions and neurons may reveal important clues toward the understanding of the molecular pathogenesis of various neurological diseases and aid in identifying rational targets toward pharmacotherapeutic interventions for progressive, late-onset neurodegenerative disorders such as mild cognitive impairment (MCI) and AD.
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Wei, Xiaoyu; Liu, Fengli; Chen, Cheng; Ma, Fengwang; Li, Mingjun
2014-01-01
In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of “Gala” apple. Genes for sugar alcohol [including 17 sorbitol transporters (SOTs)], sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs). Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties. PMID:25414708
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Wei, Xiaoyu; Liu, Fengli; Chen, Cheng; Ma, Fengwang; Li, Mingjun
2014-01-01
In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of "Gala" apple. Genes for sugar alcohol [including 17 sorbitol transporters (SOTs)], sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs). Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties.
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Comparative Expression Profiling of Distinct T Cell Subsets Undergoing Oxidative Stress
Lichtenfels, Rudolf; Mougiakakos, Dimitrios; Johansson, C. Christian; Dressler, Sven P.; Recktenwald, Christian V.; Kiessling, Rolf; Seliger, Barbara
2012-01-01
The clinical outcome of adoptive T cell transfer-based immunotherapies is often limited due to different escape mechanisms established by tumors in order to evade the hosts' immune system. The establishment of an immunosuppressive micromilieu by tumor cells along with distinct subsets of tumor-infiltrating lymphocytes is often associated with oxidative stress that can affect antigen-specific memory/effector cytotoxic T cells thereby substantially reducing their frequency and functional activation. Therefore, protection of tumor-reactive cytotoxic T lymphocytes from oxidative stress may enhance the anti-tumor-directed immune response. In order to better define the key pathways/proteins involved in the response to oxidative stress a comparative 2-DE-based proteome analysis of naïve CD45RA+ and their memory/effector CD45RO+ T cell counterparts in the presence and absence of low dose hydrogen peroxide (H2O2) was performed in this pilot study. Based on the profiling data of these T cell subpopulations under the various conditions, a series of differentially expressed spots were defined, members thereof identified by mass spectrometry and subsequently classified according to their cellular function and localization. Representative targets responding to oxidative stress including proteins involved in signaling pathways, in regulating the cellular redox status as well as in shaping/maintaining the structural cell integrity were independently verified at the transcript and protein level under the same conditions in both T cell subsets. In conclusion the resulting profiling data describe complex, oxidative stress-induced, but not strictly concordant changes within the respective expression profiles of CD45RA+ and CD45RO+ T cells. Some of the differentially expressed genes/proteins might be further exploited as potential targets toward modulating the redox capacity of the distinct lymphocyte subsets thereby providing the basis for further studies aiming at rendering them more resistant to tumor micromilieu-induced oxidative stress. PMID:22911781
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Digital sorting of complex tissues for cell type-specific gene expression profiles.
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.
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Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui
2014-01-01
Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.
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Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui
2014-01-01
Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection. PMID:25664019
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Gene expression profiling of breast cancer cell lines treated with proton and electron radiations.
Bravatà, Valentina; Minafra, Luigi; Cammarata, Francesco Paolo; Pisciotta, Pietro; Lamia, Debora; Marchese, Valentina; Manti, Lorenzo; Cirrone, Giuseppe Ap; Gilardi, Maria Carla; Cuttone, Giacomo; Forte, Giusi Irma; Russo, Giorgio
2018-06-11
Technological advances in radiation therapy are evolving with the use of hadrons, such as protons, indicated for tumors where conventional radiotherapy does not give significant advantages or for tumors located in sensitive regions, which need the maximum of dose-saving of the surrounding healthy tissues. The genomic response to conventional and non conventional Linear Energy Transfer exposure is a poor investigated topic and became an issue of radiobiological interest. The aim of this work was to analyze and compare molecular responses in term of gene expression profiles, induced by electron and proton irradiation in breast cancer cell lines. We studied the gene expression profiling differences by cDNA microarray activated in response to electron and proton irradiation with different Linear Energy Transfer values, among three breast cell lines (the tumorigenic MCF7 and MDA-MB-231 and the non tumorigenic MCF10A), exposed to the same sub-lethal dose of 9 Gy. Gene expression profiling pathway analyses showed the activation of different signaling and molecular networks in a cell line and radiation type-dependent manner. MCF10A and MDA-MB-231 cell lines were found to induce factors and pathways involved in the immunological process control. Here we describe in a detailed way the gene expression profiling and pathways activated after electron and proton irradiation in breast cancer cells. Summarizing, although specific pathways are activated in a radiation type-dependent manner, each cell line activates overall similar molecular networks in response to both these two types of ionizing radiation. Advances in knowledge: In the era of personalized medicine and breast cancer target-directed intervention, we trust that this study could drive radiation therapy towards personalized treatments, evaluating possible combined treatments, based on the molecular characterization.
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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.
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Xiao, Yinghua; van Hijum, Sacha A F T; Abee, Tjakko; Wells-Bennik, Marjon H J
2015-01-01
The formation of bacterial spores is a highly regulated process and the ultimate properties of the spores are determined during sporulation and subsequent maturation. A wide variety of genes that are expressed during sporulation determine spore properties such as resistance to heat and other adverse environmental conditions, dormancy and germination responses. In this study we characterized the sporulation phases of C. perfringens enterotoxic strain SM101 based on morphological characteristics, biomass accumulation (OD600), the total viable counts of cells plus spores, the viable count of heat resistant spores alone, the pH of the supernatant, enterotoxin production and dipicolinic acid accumulation. Subsequently, whole-genome expression profiling during key phases of the sporulation process was performed using DNA microarrays, and genes were clustered based on their time-course expression profiles during sporulation. The majority of previously characterized C. perfringens germination genes showed upregulated expression profiles in time during sporulation and belonged to two main clusters of genes. These clusters with up-regulated genes contained a large number of C. perfringens genes which are homologs of Bacillus genes with roles in sporulation and germination; this study therefore suggests that those homologs are functional in C. perfringens. A comprehensive homology search revealed that approximately half of the upregulated genes in the two clusters are conserved within a broad range of sporeforming Firmicutes. Another 30% of upregulated genes in the two clusters were found only in Clostridium species, while the remaining 20% appeared to be specific for C. perfringens. These newly identified genes may add to the repertoire of genes with roles in sporulation and determining spore properties including germination behavior. Their exact roles remain to be elucidated in future studies.
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Xiao, Yinghua; van Hijum, Sacha A. F. T.; Abee, Tjakko; Wells-Bennik, Marjon H. J.
2015-01-01
The formation of bacterial spores is a highly regulated process and the ultimate properties of the spores are determined during sporulation and subsequent maturation. A wide variety of genes that are expressed during sporulation determine spore properties such as resistance to heat and other adverse environmental conditions, dormancy and germination responses. In this study we characterized the sporulation phases of C. perfringens enterotoxic strain SM101 based on morphological characteristics, biomass accumulation (OD600), the total viable counts of cells plus spores, the viable count of heat resistant spores alone, the pH of the supernatant, enterotoxin production and dipicolinic acid accumulation. Subsequently, whole-genome expression profiling during key phases of the sporulation process was performed using DNA microarrays, and genes were clustered based on their time-course expression profiles during sporulation. The majority of previously characterized C. perfringens germination genes showed upregulated expression profiles in time during sporulation and belonged to two main clusters of genes. These clusters with up-regulated genes contained a large number of C. perfringens genes which are homologs of Bacillus genes with roles in sporulation and germination; this study therefore suggests that those homologs are functional in C. perfringens. A comprehensive homology search revealed that approximately half of the upregulated genes in the two clusters are conserved within a broad range of sporeforming Firmicutes. Another 30% of upregulated genes in the two clusters were found only in Clostridium species, while the remaining 20% appeared to be specific for C. perfringens. These newly identified genes may add to the repertoire of genes with roles in sporulation and determining spore properties including germination behavior. Their exact roles remain to be elucidated in future studies. PMID:25978838
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Small RNA-based prediction of hybrid performance in maize.
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.
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Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.
Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias
2015-06-25
Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.
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Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; van den Hondel, Cees A.; Ram, Arthur F.; Meyer, Vera
2016-01-01
Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes. PMID:27835655
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Paege, Norman; Jung, Sascha; Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; Nitsche, Benjamin M; van den Hondel, Cees A; Ram, Arthur F; Meyer, Vera
2016-01-01
Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes.
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Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...
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Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...
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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.
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Dalgard, Clifton L; Polston, Keith F; Sukumar, Gauthaman; Mallon, Col Timothy M; Wilkerson, Matthew D; Pollard, Harvey B
2016-08-01
The aim of this study was to identify serum microRNA (miRNA) biomarkers that indicate deployment-associated exposures in service members at military installations with open burn pits. Another objective was to determine detection rates of miRNAs in Department of Defense Serum Repository (DoDSR) samples with a high-throughput methodology. Low-volume serum samples (n = 800) were profiled by miRNA-capture isolation, pre-amplification, and measurement by a quantitative PCR-based OpenArray platform. Normalized quantitative cycle values were used for differential expression analysis between groups. Assay specificity, dynamic range, reproducibility, and detection rates by OpenArray passed target desired specifications. Serum abundant miRNAs were consistently measured in study specimens. Four miRNAs were differentially expressed in the case deployment group subjects. miRNAs are suitable RNA species for biomarker discovery in the DoDSR serum specimens. Serum miRNAs are candidate biomarkers for deployment and environmental exposure in military service members.
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Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?
Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David
2014-04-01
Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.
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Beleut, Manfred; Soeldner, Robert; Egorov, Mark; Guenther, Rolf; Dehler, Silvia; Morys-Wortmann, Corinna; Moch, Holger; Henco, Karsten; Schraml, Peter
2016-01-01
Despite the individually different molecular alterations in tumors, the malignancy associated biological traits are strikingly similar. Results of a previous study using renal cell carcinoma (RCC) as a model pointed towards cancer-related features, which could be visualized as three groups by microarray based gene expression analysis. In this study, we used a mathematic model to verify the presence of these groups in RCC as well as in other cancer types. We developed an algorithm for gene-expression deviation profiling for analyzing gene expression data of a total of 8397 patients with 13 different cancer types and normal tissues. We revealed three common Cancer Transcriptomic Profiles (CTPs) which recurred in all investigated tumors. Additionally, CTPs remained robust regardless of the functions or numbers of genes analyzed. CTPs may represent common genetic fingerprints, which potentially reflect the closely related biological traits of human cancers.
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DNA Methylation Profiles of Selected Pro-Inflammatory Cytokines in Alzheimer Disease.
Nicolia, Vincenzina; Cavallaro, Rosaria A; López-González, Irene; Maccarrone, Mauro; Scarpa, Sigfrido; Ferrer, Isidre; Fuso, Andrea
2017-01-01
By means of functional genomics analysis, we recently described the mRNA expression profiles of various genes involved in the neuroinflammatory response in the brains of subjects with late-onset Alzheimer Disease (LOAD). Some of these genes, namely interleukin (IL)-1β and IL-6, showed distinct expression profiles with peak expression during the first stages of the disease and control-like levels at later stages. IL-1β and IL-6 genes are modulated by DNA methylation in different chronic and degenerative diseases; it is also well known that LOAD may have an epigenetic basis. Indeed, we and others have previously reported gene-specific DNA methylation alterations in LOAD and in related animal models. Based on these data, we studied the DNA methylation profiles, at single cytosine resolution, of IL-1β and IL-6 5'-flanking region by bisulphite modification in the cortex of healthy controls and LOAD patients at 2 different disease stages: Braak I-II/A and Braak V-VI/C. Our analysis provides evidence that neuroinflammation in LOAD is associated with (and possibly mediated by) epigenetic modifications. © 2017 American Association of Neuropathologists, Inc. All rights reserved.
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A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.
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.
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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.
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Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R
2007-01-01
We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561
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Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo; ...
2017-10-07
We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo
We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less
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Hook, Sharon E; Lampi, Mark A; Febbo, Eric J; Ward, Jeff A; Parkerton, Thomas F
2010-09-01
Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 h. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including cytochrome P4501A (CYP1A) and glutathione-S-transferase (GST) with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments that used a diverse suite of toxicants. Clustering algorithms successfully identified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils. Copyright 2010 SETAC.
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Alternative life histories shape brain gene expression profiles in males of the same population
Aubin-Horth, N.; Landry, C.R.; Letcher, B.H.; Hofmann, H.A.
2005-01-01
Atlantic salmon (Salmo salar) undergo spectacular marine migrations before homing to spawn in natal rivers. However, males that grow fastest early in life can adopt an alternative 'sneaker' tactic by maturing earlier at greatly reduced size without leaving freshwater. While the ultimate evolutionary causes have been well studied, virtually nothing is known about the molecular bases of this developmental plasticity. We investigate the nature and extent of coordinated molecular changes that accompany such a fundamental transformation by comparing the brain transcription profiles of wild mature sneaker males to age-matched immature males (future large anadromous males) and immature females. Of the ca. 3000 genes surveyed, 15% are differentially expressed in the brains of the two male types. These genes are involved in a wide range of processes, including growth, reproduction and neural plasticity. Interestingly, despite the potential for wide variation in gene expression profiles among individuals sampled in nature, consistent patterns of gene expression were found for individuals of the same reproductive tactic. Notably, gene expression patterns in immature males were different both from immature females and sneakers, indicating that delayed maturation and sea migration by immature males, the 'default' life cycle, may actually result from an active inhibition of development into a sneaker. ?? 2005 The Royal Society.
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Alternative life histories shape brain gene expression profiles in males of the same population
Aubin-Horth, Nadia; Landry, Christian R; Letcher, Benjamin H; Hofmann, Hans A
2005-01-01
Atlantic salmon (Salmo salar) undergo spectacular marine migrations before homing to spawn in natal rivers. However, males that grow fastest early in life can adopt an alternative ‘sneaker’ tactic by maturing earlier at greatly reduced size without leaving freshwater. While the ultimate evolutionary causes have been well studied, virtually nothing is known about the molecular bases of this developmental plasticity. We investigate the nature and extent of coordinated molecular changes that accompany such a fundamental transformation by comparing the brain transcription profiles of wild mature sneaker males to age-matched immature males (future large anadromous males) and immature females. Of the ca. 3000 genes surveyed, 15% are differentially expressed in the brains of the two male types. These genes are involved in a wide range of processes, including growth, reproduction and neural plasticity. Interestingly, despite the potential for wide variation in gene expression profiles among individuals sampled in nature, consistent patterns of gene expression were found for individuals of the same reproductive tactic. Notably, gene expression patterns in immature males were different both from immature females and sneakers, indicating that delayed maturation and sea migration by immature males, the ‘default’ life cycle, may actually result from an active inhibition of development into a sneaker. PMID:16087419
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Alternative life histories shape brain gene expression profiles in males of the same population.
Aubin-Horth, Nadia; Landry, Christian R; Letcher, Benjamin H; Hofmann, Hans A
2005-08-22
Atlantic salmon (Salmo salar) undergo spectacular marine migrations before homing to spawn in natal rivers. However, males that grow fastest early in life can adopt an alternative 'sneaker' tactic by maturing earlier at greatly reduced size without leaving freshwater. While the ultimate evolutionary causes have been well studied, virtually nothing is known about the molecular bases of this developmental plasticity. We investigate the nature and extent of coordinated molecular changes that accompany such a fundamental transformation by comparing the brain transcription profiles of wild mature sneaker males to age-matched immature males (future large anadromous males) and immature females. Of the ca. 3000 genes surveyed, 15% are differentially expressed in the brains of the two male types. These genes are involved in a wide range of processes, including growth, reproduction and neural plasticity. Interestingly, despite the potential for wide variation in gene expression profiles among individuals sampled in nature, consistent patterns of gene expression were found for individuals of the same reproductive tactic. Notably, gene expression patterns in immature males were different both from immature females and sneakers, indicating that delayed maturation and sea migration by immature males, the 'default' life cycle, may actually result from an active inhibition of development into a sneaker.
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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.
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Zou, Ying-Min; Ni, Ke; Yang, Zhuo-Ya; Li, Ying; Cai, Xin-Lu; Xie, Dong-Jie; Zhang, Rui-Ting; Zhou, Fu-Chun; Li, Wen-Xiu; Lui, Simon S Y; Shum, David H K; Cheung, Eric F C; Chan, Raymond C K
2018-05-01
Emotion deficits may be the basis of negative symptoms in schizophrenia patients and they are prevalent in these patients. However, inconsistent findings about emotion deficits in schizophrenia suggest that there may be subtypes. The present study aimed to examine and profile experiential pleasure, emotional regulation and expression in patients with schizophrenia. A set of checklists specifically capturing experiential pleasure, emotional regulation, emotion expression, depressive symptoms and anhedonia were administered to 146 in-patients with schizophrenia and 73 demographically-matched healthy controls. Psychiatric symptoms and negative symptoms were also evaluated by a trained psychiatrist for patients with schizophrenia. Two-stage cluster analysis and discriminant function analysis were used to analyze the profile of these measures in patients with schizophrenia. We found a three-cluster solution. Cluster 1 (n=41) was characterized by a deficit in experiential pleasure and emotional regulation, Cluster 2 (n=47) was characterized by a general deficit in experiential pleasure, emotional regulation and emotion expression, and Cluster 3 (n=57) was characterized by a deficit in emotion expression. Results of a discriminant function analysis indicated that the three groups were reasonably discrete. The present findings suggest that schizophrenia patients can be classified into three subtypes based on experiential pleasure, emotional regulation and emotion expression, which are characterized by distinct clinical representations. Copyright © 2017 Elsevier B.V. All rights reserved.
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Guo, D; Li, H L; Tang, X; Peng, S Q
2014-12-18
In plants, homeodomain proteins play a critical role in regulating various aspects of plant growth and development. KNOX proteins are members of the homeodomain protein family. The KNOX transcription factors have been reported from Arabidopsis, rice, and other higher plants. The recent publication of the draft genome sequence of cassava (Manihot esculenta Krantz) has allowed a genome-wide search for M. esculenta KNOX (MeKNOX) transcription factors and the comparison of these positively identified proteins with their homologs in model plants. In the present study, we identified 12 MeKNOX genes in the cassava genome and grouped them into two distinct subfamilies based on their domain composition and phylogenetic analysis. Furthermore, semi-quantitative reverse transcription polymerase chain reaction analysis was performed to elucidate the expression profiles of these genes in different tissues and during various stages of root development. The analysis of MeKNOX expression profiles of indicated that 12 MeKNOX genes display differential expressions either in their transcript abundance or expression patterns.
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Oishi, M; Gohma, H; Lejukole, H Y; Taniguchi, Y; Yamada, T; Suzuki, K; Shinkai, H; Uenishi, H; Yasue, H; Sasaki, Y
2004-05-01
Expressed sequence tags (ESTs) generated based on characterization of clones isolated randomly from cDNA libraries are used to study gene expression profiles in specific tissues and to provide useful information for characterizing tissue physiology. In this study, two directionally cloned cDNA libraries were constructed from 60 day-old bovine whole fetus and fetal placenta. We have characterized 5357 and 1126 clones, and then identified 3464 and 795 unique sequences for the fetus and placenta cDNA libraries: 1851 and 504 showed homology to already identified genes, and 1613 and 291 showed no significant matches to any of the sequences in DNA databases, respectively. Further, we found 94 unique sequences overlapping in both the fetus and the placenta, leading to a catalog of 4165 genes expressed in 60 day-old fetus and placenta. The catalog is used to examine expression profile of genes in 60 day-old bovine fetus and placenta.
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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.
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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.
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Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong
2007-01-01
With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083
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Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong
2007-10-06
With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.
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Paper-Based MicroRNA Expression Profiling from Plasma and Circulating Tumor Cells.
Leong, Sai Mun; Tan, Karen Mei-Ling; Chua, Hui Wen; Huang, Mo-Chao; Cheong, Wai Chye; Li, Mo-Huang; Tucker, Steven; Koay, Evelyn Siew-Chuan
2017-03-01
Molecular characterization of circulating tumor cells (CTCs) holds great promise for monitoring metastatic progression and characterizing metastatic disease. However, leukocyte and red blood cell contamination of routinely isolated CTCs makes CTC-specific molecular characterization extremely challenging. Here we report the use of a paper-based medium for efficient extraction of microRNAs (miRNAs) from limited amounts of biological samples such as rare CTCs harvested from cancer patient blood. Specifically, we devised a workflow involving the use of Flinders Technology Associates (FTA) ® Elute Card with a digital PCR-inspired "partitioning" method to extract and purify miRNAs from plasma and CTCs. We demonstrated the sensitivity of this method to detect miRNA expression from as few as 3 cancer cells spiked into human blood. Using this method, background miRNA expression was excluded from contaminating blood cells, and CTC-specific miRNA expression profiles were derived from breast and colorectal cancer patients. Plasma separated out during purification of CTCs could likewise be processed using the same paper-based method for miRNA detection, thereby maximizing the amount of patient-specific information that can be derived from a single blood draw. Overall, this paper-based extraction method enables an efficient, cost-effective workflow for maximized recovery of small RNAs from limited biological samples for downstream molecular analyses. © 2016 American Association for Clinical Chemistry.
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Li, Jingyun; Chen, Ling; Li, Qian; Cao, Jing; Gao, Yanli; Li, Jun
2018-08-01
Endogenous peptides recently attract increasing attention for their participation in various biological processes. Their roles in the pathogenesis of human hypertrophic scar remains poorly understood. In this study, we used liquid chromatography-tandem mass spectrometry to construct a comparative peptidomic profiling between human hypertrophic scar tissue and matched normal skin. A total of 179 peptides were significantly differentially expressed in human hypertrophic scar tissue, with 95 upregulated and 84 downregulated peptides between hypertrophic scar tissue and matched normal skin. Further bioinformatics analysis (Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis) indicated that precursor proteins of these differentially expressed peptides correlate with cellular process, biological regulation, cell part, binding and structural molecule activity ribosome, and PPAR signaling pathway occurring during pathological changes of hypertrophic scar. Based on prediction database, we found that 78 differentially expressed peptides shared homology with antimicrobial peptides and five matched known immunomodulatory peptides. In conclusion, our results show significantly altered expression profiles of peptides in human hypertrophic scar tissue. These peptides may participate in the etiology of hypertrophic scar and provide beneficial scheme for scar evaluation and treatments. © 2017 Wiley Periodicals, Inc.
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Socioscience and ethics in science classrooms: Teacher perspectives and strategies
NASA Astrophysics Data System (ADS)
Sadler, Troy D.; Amirshokoohi, Aidin; Kazempour, Mahsa; Allspaw, Kathleen M.
2006-04-01
This study explored teacher perspectives on the use of socioscientific issues (SSI) and on dealing with ethics in the context of science instruction. Twenty-two middle and high school science teachers from three US states participated in semi-structured interviews, and researchers employed inductive analyses to explore emergent patterns relative to the following two questions. (1) How do science teachers conceptualize the place of ethics in science and science education? (2) How do science teachers handle topics with ethical implications and expression of their own values in their classrooms? Profiles were developed to capture the views and reported practices, relative to the place of ethics in science and science classrooms, of participants. Profile A comprising teachers who embraced the notion of infusing science curricula with SSI and cited examples of using controversial topics in their classes. Profile B participants supported SSI curricula in theory but reported significant constraints which prohibited them from actualizing these goals. Profile C described teachers who were non-committal with respect to focusing instruction on SSI and ethics. Profile D was based on the position that science and science education should be value-free. Profile E transcended the question of ethics in science education; these teachers felt very strongly that all education should contribute to their students' ethical development. Participants also expressed a wide range of perspectives regarding the expression of their own values in the classroom. Implications of this research for science education are discussed.
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Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens
2014-10-15
To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.
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2014-01-01
Background While microRNA (miRNA) expression is known to be altered in a variety of human malignancies contributing to cancer development and progression, the potential role of miRNA dysregulation in malignant mast cell disease has not been previously explored. The purpose of this study was to investigate the potential contribution of miRNA dysregulation to the biology of canine mast cell tumors (MCTs), a well-established spontaneous model of malignant mast cell disease. Methods We evaluated the miRNA expression profiles from biologically low-grade and biologically high-grade primary canine MCTs using real-time PCR-based TaqMan Low Density miRNA Arrays and performed real-time PCR to evaluate miR-9 expression in primary canine MCTs, malignant mast cell lines, and normal bone marrow-derived mast cells (BMMCs). Mouse mast cell lines and BMMCs were transduced with empty or pre-miR-9 expressing lentiviral constructs and cell proliferation, caspase 3/7 activity, and invasion were assessed. Transcriptional profiling of cells overexpressing miR-9 was performed using Affymetrix GeneChip Mouse Gene 2.0 ST arrays and real-time PCR was performed to validate changes in mRNA expression. Results Our data demonstrate that unique miRNA expression profiles correlate with the biological behavior of primary canine MCTs and that miR-9 expression is increased in biologically high grade canine MCTs and malignant cell lines compared to biologically low grade tumors and normal canine BMMCs. In transformed mouse malignant mast cell lines expressing either wild-type (C57) or activating (P815) KIT mutations and mouse BMMCs, miR-9 overexpression significantly enhanced invasion but had no effect on cell proliferation or apoptosis. Transcriptional profiling of normal mouse BMMCs and P815 cells possessing enforced miR-9 expression demonstrated dysregulation of several genes, including upregulation of CMA1, a protease involved in activation of matrix metalloproteases and extracellular matrix remodeling. Conclusions Our findings demonstrate that unique miRNA expression profiles correlate with the biological behavior of canine MCTs. Furthermore, dysregulation of miR-9 is associated with MCT metastasis potentially through the induction of an invasive phenotype, identifying a potentially novel pathway for therapeutic intervention. PMID:24517413
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Expression profiling of various genes during the fruit development and ripening of mango.
Pandit, Sagar S; Kulkarni, Ram S; Giri, Ashok P; Köllner, Tobias G; Degenhardt, Jörg; Gershenzon, Jonathan; Gupta, Vidya S
2010-06-01
Mango (Mangifera indica L. cv. Alphonso) development and ripening are the programmed processes; conventional indices and volatile markers help to determine agronomically important stages of fruit life (fruit-setting, harvesting maturity and ripening climacteric). However, more and precise markers are required to understand this programming; apparently, fruit's transcriptome can be a good source of such markers. Therefore, we isolated 18 genes related to the physiology and biochemistry of the fruit and profiled their expression in developing and ripening fruits, flowers and leaves of mango using relative quantitation PCR. In most of the tissues, genes related to primary metabolism, abiotic stress, ethylene response and protein turnover showed high expression as compared to that of the genes related to flavor production. Metallothionin and/or ethylene-response transcription factor showed highest level of transcript abundance in all the tissues. Expressions of mono- and sesquiterpene synthases and 14-3-3 lowered during ripening; whereas, that of lipoxygenase, ethylene-response factor and ubiquitin-protein ligase increased during ripening. Based on these expression profiles, flower showed better positive correlation with developing and ripening fruits than leaf. Most of the genes showed their least expression on the second day of harvest, suggesting that harvesting signals significantly affect the fruit metabolism. Important stages in the fruit life were clearly indicated by the significant changes in the expression levels of various genes. These indications complemented those from the previous analyses of fruit development, ripening and volatile emission, revealing the harmony between physiological, biochemical and molecular activities of the fruit.
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Ye, Bingyuan; Wang, Ruihua; Wang, Jianbo
2016-01-01
Raphanobrassica is an allopolyploid species derived from inter-generic hybridization that combines the R genome from R. sativus and the C genome from B. oleracea var. alboglabra. In the present study, we used a high-throughput sequencing method to identify the mRNA and miRNA profiles in Raphanobrassica and its parents. A total of 33,561 mRNAs and 283 miRNAs were detected, 9,209 mRNAs and 134 miRNAs were differentially expressed respectively, 7,633 mRNAs and 39 miRNAs showed ELD expression, 5,219 mRNAs and 57 miRNAs were non-additively expressed in Raphanobrassica. Remarkably, differentially expressed genes (DEGs) were up-regulated and maternal bias was detected in Raphanobrassica. In addition, a miRNA-mRNA interaction network was constructed based on reverse regulated miRNA-mRNAs, which included 75 miRNAs and 178 mRNAs, 31 miRNAs were non-additively expressed target by 13 miRNAs. The related target genes were significantly enriched in the GO term ‘metabolic processes’. Non-additive related target genes regulation is involved in a range of biological pathways, like providing a driving force for variation and adaption in this allopolyploid. The integrative analysis of mRNA and miRNA profiling provides more information to elucidate gene expression mechanism and may supply a comprehensive and corresponding method to study genetic and transcription variation of allopolyploid. PMID:27874043
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Sweasy, Joann B.
2012-01-01
Maintenance of genomic stability is essential for cellular survival. The base excision repair (BER) pathway is critical for resolution of abasic sites and damaged bases, estimated to occur 20,000 times in cells daily. DNA polymerase β (Pol β) participates in BER by filling DNA gaps that result from excision of damaged bases. Approximately 30% of human tumours express Pol β variants, many of which have altered fidelity and activity in vitro and when expressed, induce cellular transformation. The prostate tumour variant Ile260Met transforms cells and is a sequence-context-dependent mutator. To test the hypothesis that mutations induced in vivo by Ile260Met lead to cellular transformation, we characterized the genome-wide expression profile of a clone expressing Ile260Met as compared with its non-induced counterpart. Using a 1.5-fold minimum cut-off with a false discovery rate (FDR) of <0.05, 912 genes exhibit altered expression. Microarray results were confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) and revealed unique expression profiles in other clones. Gene Ontology (GO) clusters were analyzed using Ingenuity Pathways Analysis to identify altered gene networks and associated nodes. We determined three nodes of interest that exhibited dysfunctional regulation of downstream gene products without themselves having altered expression. One node, peroxisome proliferator-activated protein γ (PPARG), was sequenced and found to contain a coding region mutation in PPARG2 only in transformed cells. Further analysis suggests that this mutation leads to dominant negative activity of PPARG2. PPARG is a transcription factor implicated to have tumour suppressor function. This suggests that the PPARG2 mutant may have played a role in driving cellular transformation. We conclude that PPARG induces cellular transformation by a mutational mechanism. PMID:22914675
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Exploring of the molecular mechanism of rhinitis via bioinformatics methods
Song, Yufen; Yan, Zhaohui
2018-01-01
The aim of this study was to analyze gene expression profiles for exploring the function and regulatory network of differentially expressed genes (DEGs) in pathogenesis of rhinitis by a bioinformatics method. The gene expression profile of GSE43523 was downloaded from the Gene Expression Omnibus database. The dataset contained 7 seasonal allergic rhinitis samples and 5 non-allergic normal samples. DEGs between rhinitis samples and normal samples were identified via the limma package of R. The webGestal database was used to identify enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs. The differentially co-expressed pairs of the DEGs were identified via the DCGL package in R, and the differential co-expression network was constructed based on these pairs. A protein-protein interaction (PPI) network of the DEGs was constructed based on the Search Tool for the Retrieval of Interacting Genes database. A total of 263 DEGs were identified in rhinitis samples compared with normal samples, including 125 downregulated ones and 138 upregulated ones. The DEGs were enriched in 7 KEGG pathways. 308 differential co-expression gene pairs were obtained. A differential co-expression network was constructed, containing 212 nodes. In total, 148 PPI pairs of the DEGs were identified, and a PPI network was constructed based on these pairs. Bioinformatics methods could help us identify significant genes and pathways related to the pathogenesis of rhinitis. Steroid biosynthesis pathway and metabolic pathways might play important roles in the development of allergic rhinitis (AR). Genes such as CDC42 effector protein 5, solute carrier family 39 member A11 and PR/SET domain 10 might be also associated with the pathogenesis of AR, which provided references for the molecular mechanisms of AR. PMID:29257233
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Gorden, Brandi H.; Kim, Jong-Hyuk; Sarver, Aaron L.; Frantz, Aric M.; Breen, Matthew; Lindblad-Toh, Kerstin; O'Brien, Timothy D.; Sharkey, Leslie C.; Modiano, Jaime F.; Dickerson, Erin B.
2015-01-01
Canine hemangiosarcomas have been ascribed to an endothelial origin based on histologic appearance; however, recent findings suggest that these tumors may arise instead from hematopoietic progenitor cells. To clarify this ontogenetic dilemma, we used genome-wide expression profiling of primary hemangiosarcomas and identified three distinct tumor subtypes associated with angiogenesis (group 1), inflammation (group 2), and adipogenesis (group 3). Based on these findings, we hypothesized that a common progenitor may differentiate into the three tumor subtypes observed in our gene profiling experiment. To investigate this possibility, we cultured hemangiosarcoma cell lines under normal and sphere-forming culture conditions to enrich for tumor cell progenitors. Cells from sphere-forming cultures displayed a robust self-renewal capacity and exhibited genotypic, phenotypic, and functional properties consistent with each of the three molecular subtypes seen in primary tumors, including expression of endothelial progenitor cell (CD133 and CD34) and endothelial cell (CD105, CD146, and αvβ3 integrin) markers, expression of early hematopoietic (CD133, CD117, and CD34) and myeloid (CD115 and CD14) differentiation markers in parallel with increased phagocytic capacity, and acquisition of adipogenic potential. Collectively, these results suggest that canine hemangiosarcomas arise from multipotent progenitors that differentiate into distinct subtypes. Improved understanding of the mechanisms that determine the molecular and phenotypic differentiation of tumor cells in vivo could change paradigms regarding the origin and progression of endothelial sarcomas. PMID:24525151
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Altered Hippocampal Transcript Profile Accompanies an Age-Related Spatial Memory Deficit in Mice
ERIC Educational Resources Information Center
Verbitsky, Miguel; Yonan, Amanda L.; Malleret, Gael; Kandel, Eric R.; Gilliam, T. Conrad; Pavlidis, Paul
2004-01-01
We have carried out a global survey of age-related changes in mRNA levels in the 57BL/6NIA mouse hippocampus and found a difference in the hippocampal gene expression profile between 2-month-old young mice and 15-month-old middle-aged mice correlated with an age-related cognitive deficit in hippocampal-based explicit memory formation. Middle-aged…
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Automated Video Based Facial Expression Analysis of Neuropsychiatric Disorders
Wang, Peng; Barrett, Frederick; Martin, Elizabeth; Milanova, Marina; Gur, Raquel E.; Gur, Ruben C.; Kohler, Christian; Verma, Ragini
2008-01-01
Deficits in emotional expression are prominent in several neuropsychiatric disorders, including schizophrenia. Available clinical facial expression evaluations provide subjective and qualitative measurements, which are based on static 2D images that do not capture the temporal dynamics and subtleties of expression changes. Therefore, there is a need for automated, objective and quantitative measurements of facial expressions captured using videos. This paper presents a computational framework that creates probabilistic expression profiles for video data and can potentially help to automatically quantify emotional expression differences between patients with neuropsychiatric disorders and healthy controls. Our method automatically detects and tracks facial landmarks in videos, and then extracts geometric features to characterize facial expression changes. To analyze temporal facial expression changes, we employ probabilistic classifiers that analyze facial expressions in individual frames, and then propagate the probabilities throughout the video to capture the temporal characteristics of facial expressions. The applications of our method to healthy controls and case studies of patients with schizophrenia and Asperger’s syndrome demonstrate the capability of the video-based expression analysis method in capturing subtleties of facial expression. Such results can pave the way for a video based method for quantitative analysis of facial expressions in clinical research of disorders that cause affective deficits. PMID:18045693
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Freeman, J; Baglino, S; Friborg, J; Kraft, Z; Gray, T; Hill, M; McPhee, F; Hillson, J; Lopez-Talavera, J C; Wind-Rotolo, M
2014-06-01
Pegylated interferon-lambda-1a (Lambda), a type III interferon (IFN) in clinical development for the treatment of chronic HCV infection, has shown comparable efficacy and an improved safety profile to a regimen based on pegylated IFN alfa-2a (alfa). To establish a mechanistic context for this improved profile, we investigated the ex vivo effects of Lambda and alfa on cytokine and chemokine release, and on expression of IFN-stimulated genes (ISGs) in primary human hepatocytes and peripheral blood mononuclear cells (PBMCs) from healthy subjects. Our findings were further compared with changes observed in blood analysed from HCV-infected patients treated with Lambda or alfa in clinical studies. mRNA transcript and protein expression of the IFN-λ-limiting receptor subunit was lower compared with IFN-α receptor subunits in all cell types. Upon stimulation, alfa and Lambda induced ISG expression in hepatocytes and PBMCs, although in PBMCs Lambda-induced ISG expression was modest. Furthermore, alfa and Lambda induced release of cytokines and chemokines from hepatocytes and PBMCs, although differences in their kinetics of induction were observed. In HCV-infected patients, alfa treatment induced ISG expression in whole blood after single and repeat dosing. Lambda treatment induced modest ISG expression after single dosing and showed no induction after repeat dosing. Alfa and Lambda treatment increased IP-10, iTAC, IL-6, MCP-1 and MIP-1β levels in serum, with alfa inducing higher levels of all mediators compared with Lambda. Overall, ex vivo and in vivo induction profiles reported in this analysis strongly correlate with clinical observations of fewer related adverse events for Lambda vs those typically associated with alfa. © 2014 John Wiley & Sons Ltd.
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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
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2009-01-01
Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286
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Rotational temperatures of Venus upper atmosphere as measured by SOIR on board Venus Express
NASA Astrophysics Data System (ADS)
Mahieux, A.; Vandaele, A. C.; Robert, S.; Wilquet, V.; Drummond, R.; López Valverde, M. A.; López Puertas, M.; Funke, B.; Bertaux, J. L.
2015-08-01
SOIR is a powerful infrared spectrometer flying on board the Venus Express spacecraft since mid-2006. It sounds the Venus atmosphere above the cloud layer using the solar occultation technique. In the recorded spectra, absorption structures from many species are observed, among them carbon dioxide, the main constituent of the Venus atmosphere. Previously, temperature vertical profiles were derived from the carbon dioxide density retrieved from the SOIR spectra by assuming hydrostatic equilibrium. These profiles show a permanent cold layer at 125 km with temperatures of ~100 K, surrounded by two warmer layers at 90 and 140 km, reaching temperatures of ~200 K and 250-300 K, respectively. In this work, temperature profiles are derived from the SOIR spectra using another technique based on the ro-vibrational structure of carbon dioxide observed in the spectra. The error budget is extensively investigated. Temperature profiles obtained by both techniques are comparable within their respective uncertainties and they confirm the vertical structure previously determined from SOIR spectra.
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Guardado, Pedro; Olivera, Anlys; Rusch, Heather L; Roy, Michael; Martin, Christiana; Lejbman, Natasha; Lee, Hwyunhwa; Gill, Jessica M
2016-03-01
Whole transcriptome analysis provides an unbiased examination of biological activity, and likely, unique insight into the mechanisms underlying posttraumatic stress disorder (PTSD) and comorbid depression and traumatic brain injury. This study compared gene-expression profiles in military personnel with PTSD (n=28) and matched controls without PTSD (n=27) using HG-U133 Plus 2.0 microarrays (Affymetrix), which contain 54,675 probe sets representing more than 38,500 genes. Analysis of expression profiles revealed 203 differentially expressed genes in PTSD, of which 72% were upregulated. Using Partek Genomics Suite 6.6, differentially expressed transcription clusters were filtered based on a selection criterion of ≥1.5 relative fold change at a false discovery rate of ≤5%. Ingenuity Pathway Analysis (Qiagen) of the differentially expressed genes indicated a dysregulation of genes associated with the innate immune, neuroendocrine, and NF-κB systems. These findings provide novel insights that may lead to new pharmaceutical agents for PTSD treatments and help mitigate mental and physical comorbidity risk. Copyright © 2016. Published by Elsevier Ltd.
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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
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Flechner, Stuart M.; Kurian, Sunil M.; Head, Steven R.; Sharp, Starlette M.; Whisenant, Thomas C.; Zhang, Jie; Chismar, Jeffrey D.; Horvath, Steve; Mondala, Tony; Gilmartin, Timothy; Cook, Daniel J.; Kay, Steven A.; Walker, John R.; Salomon, Daniel R.
2007-01-01
A major challenge for kidney transplantation is balancing the need for immunosuppression to prevent rejection, while minimizing drug-induced toxicities. We used DNA microarrays (HG-U95Av2 GeneChips, Affymetrix) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients including normal donor kidneys, well-functioning transplants without rejection, kidneys undergoing acute rejection, and transplants with renal dysfunction without rejection. We developed a data analysis schema based on expression signal determination, class comparison and prediction, hierarchical clustering, statistical power analysis and real-time quantitative PCR validation. We identified distinct gene expression signatures for both biopsies and PBLs that correlated significantly with each of the different classes of transplant patients. This is the most complete report to date using commercial arrays to identify unique expression signatures in transplant biopsies distinguishing acute rejection, acute dysfunction without rejection and well-functioning transplants with no rejection history. We demonstrate for the first time the successful application of high density DNA chip analysis of PBL as a diagnostic tool for transplantation. The significance of these results, if validated in a multicenter prospective trial, would be the establishment of a metric based on gene expression signatures for monitoring the immune status and immunosuppression of transplanted patients. PMID:15307835
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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.
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Schueuermann, C; Bremer, P; Silcock, P
2017-09-01
This study investigated the effect of vineyard site on the volatile profiles of Pinot Noir wines using proton-transfer reaction mass spectrometry with prior headspace dilution. The ANOVA and PCA enabled discrimination of wine based on vineyard site. Sample separation was due to differences in the ratios of a mixture of compounds, including higher alcohols, ethyl, and acetate esters. Proton-transfer reaction mass spectrometry appears to be a useful technique for rapidly discriminating wines based on vineyard site. The similarities and differences expressed in the wines' volatile profiles may help winemakers to reveal the potential of individual vineyard sites to produce wines of certain character. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
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Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone
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
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Aberrant Promoter Methylation and Expression of UTF1 during Cervical Carcinogenesis
Deplus, Rachel; Lampe, Xavier; Krusy, Nathalie; Calonne, Emilie; Delbecque, Katty; Kridelka, Frederic; Fuks, François; Ennaji, My Mustapha; Delvenne, Philippe
2012-01-01
Promoter methylation profiles are proposed as potential prognosis and/or diagnosis biomarkers in cervical cancer. Up to now, little is known about the promoter methylation profile and expression pattern of stem cell (SC) markers during tumor development. In this study, we were interested to identify SC genes methylation profiles during cervical carcinogenesis. A genome-wide promoter methylation screening revealed a strong hypermethylation of Undifferentiated cell Transcription Factor 1 (UTF1) promoter in cervical cancer in comparison with normal ectocervix. By direct bisulfite pyrosequencing of DNA isolated from liquid-based cytological samples, we showed that UTF1 promoter methylation increases with lesion severity, the highest level of methylation being found in carcinoma. This hypermethylation was associated with increased UTF1 mRNA and protein expression. By using quantitative RT-PCR and Western Blot, we showed that both UTF1 mRNA and protein are present in epithelial cancer cell lines, even in the absence of its two main described regulators Oct4A and Sox2. Moreover, by immunofluorescence, we confirmed the nuclear localisation of UTF1 in cell lines. Surprisingly, direct bisulfite pyrosequencing revealed that the inhibition of DNA methyltransferase by 5-aza-2′-deoxycytidine was associated with decreased UTF1 gene methylation and expression in two cervical cancer cell lines of the four tested. These findings strongly suggest that UTF1 promoter methylation profile might be a useful biomarker for cervical cancer diagnosis and raise the questions of its role during epithelial carcinogenesis and of the mechanisms regulating its expression. PMID:22880087
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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
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2015-11-20
between tweets and profiles as follow, • TFIDF Score, which calculates the cosine similarity between a tweet and a profile in vector space model with...TFIDF weight of terms. Vector space model is a model which represents a document as a vector. Tweets and profiles can be expressed as vectors, ~ T = (t...gain(Tr i ) (13) where Tr is the returned tweet sets, gain() is the score func- tion for a tweet. Not interesting, spam/ junk tweets receive a gain of 0
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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
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Bagot, Rosemary C; Cates, Hannah M; Purushothaman, Immanuel; Vialou, Vincent; Heller, Elizabeth A; Yieh, Lynn; LaBonté, Benoit; Peña, Catherine J; Shen, Li; Wittenberg, Gayle M; Nestler, Eric J
2017-02-15
Examining transcriptional regulation by antidepressants in key neural circuits implicated in depression and understanding the relation to transcriptional mechanisms of susceptibility and natural resilience may help in the search for new therapeutic agents. Given the heterogeneity of treatment response in human populations, examining both treatment response and nonresponse is critical. We compared the effects of a conventional monoamine-based tricyclic antidepressant, imipramine, and a rapidly acting, non-monoamine-based antidepressant, ketamine, in mice subjected to chronic social defeat stress, a validated depression model, and used RNA sequencing to analyze transcriptional profiles associated with susceptibility, resilience, and antidepressant response and nonresponse in the prefrontal cortex (PFC), nucleus accumbens, hippocampus, and amygdala. We identified similar numbers of responders and nonresponders after ketamine or imipramine treatment. Ketamine induced more expression changes in the hippocampus; imipramine induced more expression changes in the nucleus accumbens and amygdala. Transcriptional profiles in treatment responders were most similar in the PFC. Nonresponse reflected both the lack of response-associated gene expression changes and unique gene regulation. In responders, both drugs reversed susceptibility-associated transcriptional changes and induced resilience-associated transcription in the PFC. We generated a uniquely large resource of gene expression data in four interconnected limbic brain regions implicated in depression and its treatment with imipramine or ketamine. Our analyses highlight the PFC as a key site of common transcriptional regulation by antidepressant drugs and in both reversing susceptibility- and inducing resilience-associated molecular adaptations. In addition, we found region-specific effects of each drug, suggesting both common and unique effects of imipramine versus ketamine. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
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Lončar-Brzak, Božana; Klobučar, Marko; Veliki-Dalić, Irena; Sabol, Ivan; Kraljević Pavelić, Sandra; Krušlin, Božo; Mravak-Stipetić, Marinka
2018-03-01
The aim of this study was to examine molecular alterations on the protein level in lesions of oral lichen planus (OLP), oral squamous cell carcinoma (OSCC) and healthy mucosa. Global protein profiling methods based on liquid chromatography coupled to mass spectrometry (LC-MS) were used, with a special emphasis on evaluation of deregulated extracellular matrix molecules expression, as well as on analyses of IG2F and IGFR2 expression in healthy mucosa, OLP and OSCC tissues by comparative semi-quantitative immunohistochemistry. Mass spectrometry-based proteomics profiling of healthy mucosa, OLP and OSCC tissues (and accompanied histologically unaltered tissues, respectively) identified 55 extracellular matrix proteins. Twenty among identified proteins were common to all groups of samples. Expression of small leucine-rich extracellular matrix proteoglycans lumican and biglycan was found both in OSCC and OLP and they were validated by Western blot analysis as putative biomarkers. A significant increase (p < 0.05) of biglycan expression in OLP-AT group was determined in comparison with OLP-T group, while lumican showed significant up-regulation (p < 0.05) in OLP-T and OSCC-T groups vs. adjacent and control tissue groups. Biglycan expression was only determined in OSCC-AT group. Immunohistochemical analysis of IGF2 and IG2FR expression revealed no significant difference among groups of samples. Biglycan and lumican were identified as important pathogenesis biomarkers of OLP that point to its malignant potential.
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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.
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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
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Functional clustering of time series gene expression data by Granger causality
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
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Selecting the most appropriate time points to profile in high-throughput studies
Kleyman, Michael; Sefer, Emre; Nicola, Teodora; Espinoza, Celia; Chhabra, Divya; Hagood, James S; Kaminski, Naftali; Ambalavanan, Namasivayam; Bar-Joseph, Ziv
2017-01-01
Biological systems are increasingly being studied by high throughput profiling of molecular data over time. Determining the set of time points to sample in studies that profile several different types of molecular data is still challenging. Here we present the Time Point Selection (TPS) method that solves this combinatorial problem in a principled and practical way. TPS utilizes expression data from a small set of genes sampled at a high rate. As we show by applying TPS to study mouse lung development, the points selected by TPS can be used to reconstruct an accurate representation for the expression values of the non selected points. Further, even though the selection is only based on gene expression, these points are also appropriate for representing a much larger set of protein, miRNA and DNA methylation changes over time. TPS can thus serve as a key design strategy for high throughput time series experiments. Supporting Website: www.sb.cs.cmu.edu/TPS DOI: http://dx.doi.org/10.7554/eLife.18541.001 PMID:28124972
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SARS-CoV Regulates Immune Function-Related Gene Expression in Human Monocytic Cells
Hu, Wanchung; Yen, Yu-Ting; Singh, Sher; Kao, Chuan-Liang
2012-01-01
Abstract Severe acute respiratory syndrome (SARS) is characterized by acute respiratory distress syndrome (ARDS) and pulmonary fibrosis, and monocytes/macrophages are the key players in the pathogenesis of SARS. In this study, we compared the transcriptional profiles of SARS coronavirus (SARS-CoV)-infected monocytic cells against that infected by coronavirus 229E (CoV-229E). Total RNA was extracted from infected DC-SIGN-transfected monocytes (THP-1-DC-SIGN) at 6 and 24 h after infection, and the gene expression was profiled in oligonucleotide-based microarrays. Analysis of immune-related gene expression profiles showed that at 24 h after SARS-CoV infection: (1) IFN-α/β-inducible and cathepsin/proteasome genes were downregulated; (2) hypoxia/hyperoxia-related genes were upregulated; and (3) TLR/TLR-signaling, cytokine/cytokine receptor-related, chemokine/chemokine receptor-related, lysosome-related, MHC/chaperon-related, and fibrosis-related genes were differentially regulated. These results elucidate that SARS-CoV infection regulates immune-related genes in monocytes/macrophages, which may be important to the pathogenesis of SARS. PMID:22876772
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SARS-CoV regulates immune function-related gene expression in human monocytic cells.
Hu, Wanchung; Yen, Yu-Ting; Singh, Sher; Kao, Chuan-Liang; Wu-Hsieh, Betty A
2012-08-01
Severe acute respiratory syndrome (SARS) is characterized by acute respiratory distress syndrome (ARDS) and pulmonary fibrosis, and monocytes/macrophages are the key players in the pathogenesis of SARS. In this study, we compared the transcriptional profiles of SARS coronavirus (SARS-CoV)-infected monocytic cells against that infected by coronavirus 229E (CoV-229E). Total RNA was extracted from infected DC-SIGN-transfected monocytes (THP-1-DC-SIGN) at 6 and 24 h after infection, and the gene expression was profiled in oligonucleotide-based microarrays. Analysis of immune-related gene expression profiles showed that at 24 h after SARS-CoV infection: (1) IFN-α/β-inducible and cathepsin/proteasome genes were downregulated; (2) hypoxia/hyperoxia-related genes were upregulated; and (3) TLR/TLR-signaling, cytokine/cytokine receptor-related, chemokine/chemokine receptor-related, lysosome-related, MHC/chaperon-related, and fibrosis-related genes were differentially regulated. These results elucidate that SARS-CoV infection regulates immune-related genes in monocytes/macrophages, which may be important to the pathogenesis of SARS.
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Cancer survival classification using integrated data sets and intermediate information.
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.
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Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
Yang, Fang; Wang, Yumei
2018-01-01
Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480
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A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.
Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang
2014-04-15
Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.
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Li, Changning; Nong, Qian; Solanki, Manoj Kumar; Liang, Qiang; Xie, Jinlan; Liu, Xiaoyan; Li, Yijie; Wang, Weizan; Yang, Litao; Li, Yangrui
2016-01-01
Water stress causes considerable yield losses in sugarcane. To investigate differentially expressed genes under water stress, a pot experiment was performed with the sugarcane variety GT21 at three water-deficit levels (mild, moderate, and severe) during the elongation stage and gene expression was analyzed using microarray technology. Physiological parameters of sugarcane showed significant alterations in response to drought stress. Based on the expression profile of 15,593 sugarcane genes, 1,501 (9.6%) genes were differentially expressed under different water-level treatments; 821 genes were upregulated and 680 genes were downregulated. A gene similarity analysis showed that approximately 62.6% of the differentially expressed genes shared homology with functional proteins. In a Gene Ontology (GO) analysis, 901 differentially expressed genes were assigned to 36 GO categories. Moreover, 325 differentially expressed genes were classified into 101 pathway categories involved in various processes, such as the biosynthesis of secondary metabolites, ribosomes, carbon metabolism, etc. In addition, some unannotated genes were detected; these may provide a basis for studies of water-deficit tolerance. The reliability of the observed expression patterns was confirmed by RT-PCR. The results of this study may help identify useful genes for improving drought tolerance in sugarcane. PMID:27170459
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Mass Spectrometric Quantification of N-Linked Glycans by Reference to Exogenous Standards.
Mehta, Nickita; Porterfield, Mindy; Struwe, Weston B; Heiss, Christian; Azadi, Parastoo; Rudd, Pauline M; Tiemeyer, Michael; Aoki, Kazuhiro
2016-09-02
Environmental and metabolic processes shape the profile of glycoprotein glycans expressed by cells, whether in culture, developing tissues, or mature organisms. Quantitative characterization of glycomic changes associated with these conditions has been achieved historically by reductive coupling of oligosaccharides to various fluorophores following release from glycoprotein and subsequent HPLC or capillary electrophoretic separation. Such labeling-based approaches provide a robust means of quantifying glycan amount based on fluorescence yield. Mass spectrometry, on the other hand, has generally been limited to relative quantification in which the contribution of the signal intensity for an individual glycan is expressed as a percent of the signal intensity summed over the total profile. Relative quantification has been valuable for highlighting changes in glycan expression between samples; sensitivity is high, and structural information can be derived by fragmentation. We have investigated whether MS-based glycomics is amenable to absolute quantification by referencing signal intensities to well-characterized oligosaccharide standards. We report the qualification of a set of N-linked oligosaccharide standards by NMR, HPLC, and MS. We also demonstrate the dynamic range, sensitivity, and recovery from complex biological matrices for these standards in their permethylated form. Our results indicate that absolute quantification for MS-based glycomic analysis is reproducible and robust utilizing currently available glycan standards.
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Simon, Matthew J; Murchison, Charles; Iliff, Jeffrey J
2018-02-01
Astrocytes play a critical role in regulating the interface between the cerebral vasculature and the central nervous system. Contributing to this is the astrocytic endfoot domain, a specialized structure that ensheathes the entirety of the vasculature and mediates signaling between endothelial cells, pericytes, and neurons. The astrocytic endfoot has been implicated as a critical element of the glymphatic pathway, and changes in protein expression profiles in this cellular domain are linked to Alzheimer's disease pathology. Despite this, basic physiological properties of this structure remain poorly understood including the developmental timing of its formation, and the protein components that localize there to mediate its functions. Here we use human transcriptome data from male and female subjects across several developmental stages and brain regions to characterize the gene expression profile of the dystrophin-associated complex (DAC), a known structural component of the astrocytic endfoot that supports perivascular localization of the astroglial water channel aquaporin-4. Transcriptomic profiling is also used to define genes exhibiting parallel expression profiles to DAC elements, generating a pool of candidate genes that encode gene products that may contribute to the physiological function of the perivascular astrocytic endfoot domain. We found that several genes encoding transporter proteins are transcriptionally associated with DAC genes. © 2017 Wiley Periodicals, Inc.
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Distinct types of primary cutaneous large B-cell lymphoma identified by gene expression profiling.
Hoefnagel, Juliette J; Dijkman, Remco; Basso, Katia; Jansen, Patty M; Hallermann, Christian; Willemze, Rein; Tensen, Cornelis P; Vermeer, Maarten H
2005-05-01
In the European Organization for Research and Treatment of Cancer (EORTC) classification 2 types of primary cutaneous large B-cell lymphoma (PCLBCL) are distinguished: primary cutaneous follicle center cell lymphomas (PCFCCL) and PCLBCL of the leg (PCLBCL-leg). Distinction between both groups is considered important because of differences in prognosis (5-year survival > 95% and 52%, respectively) and the first choice of treatment (radiotherapy or systemic chemotherapy, respectively), but is not generally accepted. To establish a molecular basis for this subdivision in the EORTC classification, we investigated the gene expression profiles of 21 PCLBCLs by oligonucleotide microarray analysis. Hierarchical clustering based on a B-cell signature (7450 genes) classified PCLBCL into 2 distinct subgroups consisting of, respectively, 8 PCFCCLs and 13 PCLBCLsleg. PCLBCLs-leg showed increased expression of genes associated with cell proliferation; the proto-oncogenes Pim-1, Pim-2, and c-Myc; and the transcription factors Mum1/IRF4 and Oct-2. In the group of PCFCCL high expression of SPINK2 was observed. Further analysis suggested that PCFCCLs and PCLBCLs-leg have expression profiles similar to that of germinal center B-cell-like and activated B-cell-like diffuse large B-cell lymphoma, respectively. The results of this study suggest that different pathogenetic mechanisms are involved in the development of PCFCCLs and PCLBCLs-leg and provide molecular support for the subdivision used in the EORTC classification.
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A biomarker-based screen of a gene expression compendium ...
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
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Marklund, Ulrika; Lacerda, Francisco; Persson, Anna; Lohmander, Anette
2018-04-10
This paper describes the development of a vocabulary for Profiles of Early Expressive Phonological Skills for Swedish (PEEPS-SE), a tool for assessment of expressive phonology in Swedish-learning children in the age range of 18-36 months. PEEPS-SE is the Swedish version of the original PEEPS, Profiles of Early Expressive Phonological Skills, which uses two age-adequate word lists-a basic word list (BWL) for the assessment of 18-24-month-old children, to which an expanded word list (EWL) is added for assessment of 24-36-month-old children, or children with more than 250 words in their expressive vocabulary. The selection of words in PEEPS-SE is based on two types of criteria: age of acquisition and phonological complexity. The words also need to be easy to elicit in a natural way in test situations. Vocabulary data previously collected with the Swedish Early Communicative Development Inventory are used for selection of age-adequate words, where the BWL contains words acquired earlier compared to the additional words in the EWL. The latter also contains words that are more phonologically complex compared to those in the BWL. Word complexity was determined by the Swedish version of word complexity measure. PEEPS-SE has made an attempt to match the original version of PEEPS in terms of both assessment method and word selection.
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2010-01-01
Background Molecular chaperones have been shown to be important in the growth of the malaria parasite Plasmodium falciparum and inhibition of chaperone function by pharmacological agents has been shown to abrogate parasite growth. A recent study has demonstrated that clinical isolates of the parasite have distinct physiological states, one of which resembles environmental stress response showing up-regulation of specific molecular chaperones. Methods Chaperone networks operational in the distinct physiological clusters in clinical malaria parasites were constructed using cytoscape by utilizing their clinical expression profiles. Results Molecular chaperones show distinct profiles in the previously defined physiologically distinct states. Further, expression profiles of the chaperones from different cellular compartments correlate with specific patient clusters. While cluster 1 parasites, representing a starvation response, show up-regulation of organellar chaperones, cluster 2 parasites, which resemble active growth based on glycolysis, show up-regulation of cytoplasmic chaperones. Interestingly, cytoplasmic Hsp90 and its co-chaperones, previously implicated as drug targets in malaria, cluster in the same group. Detailed analysis of chaperone expression in the patient cluster 2 reveals up-regulation of the entire Hsp90-dependent pro-survival circuitries. In addition, cluster 2 also shows up-regulation of Plasmodium export element (PEXEL)-containing Hsp40s thought to have regulatory and host remodeling roles in the infected erythrocyte. Conclusion In all, this study demonstrates an intimate involvement of parasite-encoded chaperones, PfHsp90 in particular, in defining pathogenesis of malaria. PMID:20719001
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Estimation of the uncertainty of analyte concentration from the measurement uncertainty.
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.
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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.
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Single cell gene expression profiling of cortical osteoblast lineage cells.
Flynn, James M; Spusta, Steven C; Rosen, Clifford J; Melov, Simon
2013-03-01
In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states. Copyright © 2012 Elsevier Inc. All rights reserved.
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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
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Guillot, Flora; Garcia, Alexandra; Salou, Marion; Brouard, Sophie; Laplaud, David A; Nicot, Arnaud B
2015-07-04
Astrocytes, the most abundant cell population in mammal central nervous system (CNS), contribute to a variety of functions including homeostasis, metabolism, synapse formation, and myelin maintenance. White matter (WM) reactive astrocytes are important players in amplifying autoimmune demyelination and may exhibit different changes in transcriptome profiles and cell function in a disease-context dependent manner. However, their transcriptomic profile has not yet been defined because they are difficult to purify, compared to gray matter astrocytes. Here, we isolated WM astrocytes by laser capture microdissection (LCM) in a murine model of multiple sclerosis to better define their molecular profile focusing on selected genes related to inflammation. Based on previous data indicating anti-inflammatory effects of estrogen only at high nanomolar doses, we also examined mRNA expression for enzymes involved in steroid inactivation. Experimental autoimmune encephalomyelitis (EAE) was induced in female C57BL6 mice with MOG35-55 immunization. Fluorescence activated cell sorting (FACS) analysis of a portion of individual spinal cords at peak disease was used to assess the composition of immune cell infiltrates. Using custom Taqman low-density-array (TLDA), we analyzed mRNA expression of 40 selected genes from immuno-labeled laser-microdissected WM astrocytes from lumbar spinal cord sections of EAE and control mice. Immunohistochemistry and double immunofluorescence on control and EAE mouse spinal cord sections were used to confirm protein expression in astrocytes. The spinal cords of EAE mice were infiltrated mostly by effector/memory T CD4+ cells and macrophages. TLDA-based profiling of LCM-astrocytes identified EAE-induced gene expression of cytokines and chemokines as well as inflammatory mediators recently described in gray matter reactive astrocytes in other murine CNS disease models. Strikingly, SULT1A1, but not other members of the sulfotransferase family, was expressed in WM spinal cord astrocytes. Moreover, its expression was further increased in EAE. Immunohistochemistry on spinal cord tissues confirmed preferential expression of this enzyme in WM astrocytic processes but not in gray matter astrocytes. We described here for the first time the mRNA expression of several genes in WM astrocytes in a mouse model of multiple sclerosis. Besides expected pro-inflammatory chemokines and specific inflammatory mediators increased during EAE, we evidenced relative high astrocytic expression of the cytoplasmic enzyme SULT1A1. As the sulfonation activity of SULT1A1 inactivates estradiol among other phenolic substrates, its high astrocytic expression may account for the relative resistance of this cell population to the anti-neuroinflammatory effects of estradiol. Blocking the activity of this enzyme during neuroinflammation may thus help the injured CNS to maintain the anti-inflammatory activity of endogenous estrogens or limit the dose of estrogen co-regimens for therapeutical purposes.
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Cell-of-Origin in Diffuse Large B-Cell Lymphoma: Are the Assays Ready for the Clinic?
Scott, David W
2015-01-01
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma worldwide and consists of a heterogeneous group of cancers classified together on the basis of shared morphology, immunophenotype, and aggressive clinical behavior. It is now recognized that this malignancy comprises at least two distinct molecular subtypes identified by gene expression profiling: the activated B-cell-like (ABC) and the germinal center B-cell-like (GCB) groups-the cell-of-origin (COO) classification. These two groups have different genetic mutation landscapes, pathobiology, and outcomes following treatment. Evidence is accumulating that novel agents have selective activity in one or the other COO group, making COO a predictive biomarker. Thus, there is now a pressing need for accurate and robust methods to assign COO, to support clinical trials, and ultimately guide treatment decisions for patients. The "gold standard" methods for COO are based on gene expression profiling (GEP) of RNA from fresh frozen tissue using microarray technology, which is an impractical solution when formalin-fixed paraffin-embedded tissue (FFPET) biopsies are the standard diagnostic material. This review outlines the history of the COO classification before examining the practical implementation of COO assays applicable to FFPET biopsies. The immunohistochemistry (IHC)-based algorithms and gene expression-based assays suitable for the highly degraded RNA from FFPET are discussed. Finally, the technical and practical challenges that still need to be addressed are outlined before robust gene expression-based assays are used in the routine management of patients with DLBCL.
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Challenges in projecting clustering results across gene expression-profiling datasets.
Lusa, Lara; McShane, Lisa M; Reid, James F; De Cecco, Loris; Ambrogi, Federico; Biganzoli, Elia; Gariboldi, Manuela; Pierotti, Marco A
2007-11-21
Gene expression microarray studies for several types of cancer have been reported to identify previously unknown subtypes of tumors. For breast cancer, a molecular classification consisting of five subtypes based on gene expression microarray data has been proposed. These subtypes have been reported to exist across several breast cancer microarray studies, and they have demonstrated some association with clinical outcome. A classification rule based on the method of centroids has been proposed for identifying the subtypes in new collections of breast cancer samples; the method is based on the similarity of the new profiles to the mean expression profile of the previously identified subtypes. Previously identified centroids of five breast cancer subtypes were used to assign 99 breast cancer samples, including a subset of 65 estrogen receptor-positive (ER+) samples, to five breast cancer subtypes based on microarray data for the samples. The effect of mean centering the genes (i.e., transforming the expression of each gene so that its mean expression is equal to 0) on subtype assignment by method of centroids was assessed. Further studies of the effect of mean centering and of class prevalence in the test set on the accuracy of method of centroids classifications of ER status were carried out using training and test sets for which ER status had been independently determined by ligand-binding assay and for which the proportion of ER+ and ER- samples were systematically varied. When all 99 samples were considered, mean centering before application of the method of centroids appeared to be helpful for correctly assigning samples to subtypes, as evidenced by the expression of genes that had previously been used as markers to identify the subtypes. However, when only the 65 ER+ samples were considered for classification, many samples appeared to be misclassified, as evidenced by an unexpected distribution of ER+ samples among the resultant subtypes. When genes were mean centered before classification of samples for ER status, the accuracy of the ER subgroup assignments was highly dependent on the proportion of ER+ samples in the test set; this effect of subtype prevalence was not seen when gene expression data were not mean centered. Simple corrections such as mean centering of genes aimed at microarray platform or batch effect correction can have undesirable consequences because patient population effects can easily be confused with these assay-related effects. Careful thought should be given to the comparability of the patient populations before attempting to force data comparability for purposes of assigning subtypes to independent subjects.
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Zhang, Wensheng; Edwards, Andrea; Fan, Wei; Zhu, Dongxiao; Zhang, Kun
2010-06-22
Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering. svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.
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Rendo-Urteaga, Tara; García-Calzón, Sonia; González-Muniesa, Pedro; Milagro, Fermín I; Chueca, María; Oyarzabal, Mirentxu; Azcona-Sanjulián, M Cristina; Martínez, J Alfredo; Marti, Amelia
2015-01-28
The present study analyses the gene expression profile of peripheral blood mononuclear cells (PBMC) from obese boys. The aims of the present study were to identify baseline differences between low responders (LR) and high responders (HR) after 10 weeks of a moderate energy-restricted dietary intervention, and to compare the gene expression profile between the baseline and the endpoint of the nutritional intervention. Spanish obese boys (age 10-14 years) were advised to follow a 10-week moderate energy-restricted diet. Participants were classified into two groups based on the association between the response to the nutritional intervention and the changes in BMI standard deviation score (BMI-SDS): HR group (n 6), who had a more decreased BMI-SDS; LR group (n 6), who either maintained or had an even increased BMI-SDS. The expression of 28,869 genes was analysed in PBMC from both groups at baseline and after the nutritional intervention, using the Affymetrix Human Gene 1.1 ST 24-Array plate microarray. At baseline, the HR group showed a lower expression of inflammation and immune response-related pathways, which suggests that the LR group could have a more developed pro-inflammatory phenotype. Concomitantly, LEPR and SIRPB1 genes were highly expressed in the LR group, indicating a tendency towards an impaired immune response and leptin resistance. Moreover, the moderate energy-restricted diet was able to down-regulate the inflammatory 'mitogen-activated protein kinase signalling pathway' in the HR group, as well as some inflammatory genes (AREG and TNFAIP3). The present study confirms that changes in the gene expression profile of PBMC in obese boys may help to understand the weight-loss response. However, further research is required to confirm these findings.
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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.
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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
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Reyes-Bermudez, Alejandro; Villar-Briones, Alejandro; Ramirez-Portilla, Catalina; Hidaka, Michio; Mikheyev, Alexander S.
2016-01-01
Corals belong to the most basal class of the Phylum Cnidaria, which is considered the sister group of bilaterian animals, and thus have become an emerging model to study the evolution of developmental mechanisms. Although cell renewal, differentiation, and maintenance of pluripotency are cellular events shared by multicellular animals, the cellular basis of these fundamental biological processes are still poorly understood. To understand how changes in gene expression regulate morphogenetic transitions at the base of the eumetazoa, we performed quantitative RNA-seq analysis during Acropora digitifera’s development. We collected embryonic, larval, and adult samples to characterize stage-specific transcription profiles, as well as broad expression patterns. Transcription profiles reconstructed development revealing two main expression clusters. The first cluster grouped blastula and gastrula and the second grouped subsequent developmental time points. Consistently, we observed clear differences in gene expression between early and late developmental transitions, with higher numbers of differentially expressed genes and fold changes around gastrulation. Furthermore, we identified three coexpression clusters that represented discrete gene expression patterns. During early transitions, transcriptional networks seemed to regulate cellular fate and morphogenesis of the larval body. In late transitions, these networks seemed to play important roles preparing planulae for switch in lifestyle and regulation of adult processes. Although developmental progression in A. digitifera is regulated to some extent by differential coexpression of well-defined gene networks, stage-specific transcription profiles appear to be independent entities. While negative regulation of transcription is predominant in early development, cell differentiation was upregulated in larval and adult stages. PMID:26941230
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Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi
2017-09-01
Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.
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Gene Discovery in Bladder Cancer Progression using cDNA Microarrays
Sanchez-Carbayo, Marta; Socci, Nicholas D.; Lozano, Juan Jose; Li, Wentian; Charytonowicz, Elizabeth; Belbin, Thomas J.; Prystowsky, Michael B.; Ortiz, Angel R.; Childs, Geoffrey; Cordon-Cardo, Carlos
2003-01-01
To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression. PMID:12875971
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The Cross-Entropy Based Multi-Filter Ensemble Method for Gene Selection.
Sun, Yingqiang; Lu, Chengbo; Li, Xiaobo
2018-05-17
The gene expression profile has the characteristics of a high dimension, low sample, and continuous type, and it is a great challenge to use gene expression profile data for the classification of tumor samples. This paper proposes a cross-entropy based multi-filter ensemble (CEMFE) method for microarray data classification. Firstly, multiple filters are used to select the microarray data in order to obtain a plurality of the pre-selected feature subsets with a different classification ability. The top N genes with the highest rank of each subset are integrated so as to form a new data set. Secondly, the cross-entropy algorithm is used to remove the redundant data in the data set. Finally, the wrapper method, which is based on forward feature selection, is used to select the best feature subset. The experimental results show that the proposed method is more efficient than other gene selection methods and that it can achieve a higher classification accuracy under fewer characteristic genes.
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NASA Astrophysics Data System (ADS)
Pätzold, M.; Bird, M. K.; Häusler, B.; Peter, K.; Tellmann, S.; Tyler, G. L.
2016-10-01
In their recent paper, Grandin et al. (2014) claim to have developed a novel approach, principally a ray tracing method, to analyze radio sounding data from occulted spacecraft signals by planetary atmospheres without the usual assumptions of the radio occultation inversion method of a stratified, layered, symmetric atmosphere. They apply their "new approach" to observations of the Mars Express Radio Science (MaRS) experiment and compare their resulting temperature, neutral number density, and electron density profiles with those from MaRS, claiming that there is good agreement with the observations. The fact is, however, that there are serious disagreements in the most important altitude ranges. Their temperature profile shows a 30 K shift or a 300σ (1σ standard deviation = 0.1 K for the MaRS profile near the surface) difference toward warmer temperatures at the surface when compared with MaRS, while the MaRS profile is in best agreement with the profile from the Mars Climate Data Base V5.0 (MCD V5.0). Their full temperature profile from the surface to 250 km altitude deviates significantly from the MCD V5.0 profile. Their ionospheric electron density profile is considerably different from that derived from the MaRs observations. Although Grandin et al. (2014) claim to derive the neutral number density and temperature profiles above 200 km, including the asymptotic exosphere temperature, it is simply not possible to derive this information from what is essentially noise.
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Massively parallel nanowell-based single-cell gene expression profiling.
Goldstein, Leonard D; Chen, Ying-Jiun Jasmine; Dunne, Jude; Mir, Alain; Hubschle, Hermann; Guillory, Joseph; Yuan, Wenlin; Zhang, Jingli; Stinson, Jeremy; Jaiswal, Bijay; Pahuja, Kanika Bajaj; Mann, Ishminder; Schaal, Thomas; Chan, Leo; Anandakrishnan, Sangeetha; Lin, Chun-Wah; Espinoza, Patricio; Husain, Syed; Shapiro, Harris; Swaminathan, Karthikeyan; Wei, Sherry; Srinivasan, Maithreyan; Seshagiri, Somasekar; Modrusan, Zora
2017-07-07
Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.
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The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in
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Cross-Platform Toxicogenomics for the Prediction of Non-Genotoxic Hepatocarcinogenesis in Rat
Metzger, Ute; Templin, Markus F.; Plummer, Simon; Ellinger-Ziegelbauer, Heidrun; Zell, Andreas
2014-01-01
In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens. PMID:24830643
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Patil, Rajreddy; Kumar, B. Mohana; Lee, Won-Jae
Dental tissues provide an alternative autologous source of mesenchymal stem cells (MSCs) for regenerative medicine. In this study, we isolated human dental MSCs of follicle, pulp and papilla tissue from a single donor tooth after impacted third molar extraction by excluding the individual differences. We then compared the morphology, proliferation rate, expression of MSC-specific and pluripotency markers, and in vitro differentiation ability into osteoblasts, adipocytes, chondrocytes and functional hepatocyte-like cells (HLCs). Finally, we analyzed the protein expression profiles of undifferentiated dental MSCs using 2DE coupled with MALDI-TOF-MS. Three types of dental MSCs largely shared similar morphology, proliferation potential, expression ofmore » surface markers and pluripotent transcription factors, and differentiation ability into osteoblasts, adipocytes, and chondrocytes. Upon hepatogenic induction, all MSCs were transdifferentiated into functional HLCs, and acquired hepatocyte functions by showing their ability for glycogen storage and urea production. Based on the proteome profiling results, we identified nineteen proteins either found commonly or differentially expressed among the three types of dental MSCs. In conclusion, three kinds of dental MSCs from a single donor tooth possessed largely similar cellular properties and multilineage potential. Further, these dental MSCs had similar proteomic profiles, suggesting their interchangeable applications for basic research and call therapy. - Highlights: • Isolated and characterized three types of human dental MSCs from a single donor. • MSCs of dental follicle, pulp and papilla had largely similar biological properties. • All MSCs were capable of transdifferentiating into functional hepatocyte-like cells. • 2DE proteomics with MALDI-TOF/MS identified 19 proteins in three types of MSCs. • Similar proteomic profiles suggest interchangeable applications of dental MSCs.« less
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Wu, Zhifeng; Ding, Nannan; Yu, Mengxi; Wang, Ke; Luo, Shasha; Zou, Wenjun; Zhou, Ying; Yan, Biao; Jiang, Qin
2016-01-01
Rhegmatogenous retinal detachment associated with choroidal detachment (RRDCD) is a complicated and serious type of rhegmatogenous retinal detachment (RRD). In this study, we identified differentially expressed proteins in the vitreous humors of RRDCD and RRD using isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano-liquid chromatography-electrospray ion trap-mass spectrometry-mass spectrometry (nano-LC-ESI-MS/MS) and bioinformatic analysis. Our result shows that 103 differentially expressed proteins, including 54 up-regulated and 49 down-regulated proteins were identified in RRDCD. Gene ontology (GO) analysis suggested that most of the differentially expressed proteins were extracellular．The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis suggested that proteins related to complement and coagulation cascades were significantly enriched. iTRAQ-based proteomic profiling reveals that complement and coagulation cascades and inflammation may play important roles in the pathogenesis of RRDCD. This study may provide novel insights into the pathogenesis of RRDCD and offer potential opportunities for the diagnosis and treatment of RRDCD. PMID:27941623
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Analysis of high-throughput biological data using their rank values.
Dembélé, Doulaye
2018-01-01
High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .
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Yu, Tonghu; Zhang, Huaping; Qi, Hong
2018-01-01
The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer. PMID:29928385
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Gorden, Brandi H; Kim, Jong-Hyuk; Sarver, Aaron L; Frantz, Aric M; Breen, Matthew; Lindblad-Toh, Kerstin; O'Brien, Timothy D; Sharkey, Leslie C; Modiano, Jaime F; Dickerson, Erin B
2014-04-01
Canine hemangiosarcomas have been ascribed to an endothelial origin based on histologic appearance; however, recent findings suggest that these tumors may arise instead from hematopoietic progenitor cells. To clarify this ontogenetic dilemma, we used genome-wide expression profiling of primary hemangiosarcomas and identified three distinct tumor subtypes associated with angiogenesis (group 1), inflammation (group 2), and adipogenesis (group 3). Based on these findings, we hypothesized that a common progenitor may differentiate into the three tumor subtypes observed in our gene profiling experiment. To investigate this possibility, we cultured hemangiosarcoma cell lines under normal and sphere-forming culture conditions to enrich for tumor cell progenitors. Cells from sphere-forming cultures displayed a robust self-renewal capacity and exhibited genotypic, phenotypic, and functional properties consistent with each of the three molecular subtypes seen in primary tumors, including expression of endothelial progenitor cell (CD133 and CD34) and endothelial cell (CD105, CD146, and αvβ3 integrin) markers, expression of early hematopoietic (CD133, CD117, and CD34) and myeloid (CD115 and CD14) differentiation markers in parallel with increased phagocytic capacity, and acquisition of adipogenic potential. Collectively, these results suggest that canine hemangiosarcomas arise from multipotent progenitors that differentiate into distinct subtypes. Improved understanding of the mechanisms that determine the molecular and phenotypic differentiation of tumor cells in vivo could change paradigms regarding the origin and progression of endothelial sarcomas. Copyright © 2014 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
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Persic, Martina; Mikulic-Petkovsek, Maja; Halbwirth, Heidi; Solar, Anita; Veberic, Robert; Slatnar, Ana
2018-03-21
A rare walnut variant with a red seed coat (pellicle) was examined for alterations in its phenolic profile during development. The red-walnut (RW) pellicle was compared with two commonly colored walnut varieties: 'Lara' (brown) and 'Fernor' (light brown). Furthermore, the activities of selected enzymes of the phenylpropanoid- and flavonoid-related pathways and the relative expressions of the structural genes phenylalanine ammonia lyase ( PAL) and anthocyanidin synthase ( ANS) were examined in the pellicles of the three varieties. In the pellicles of the RWs, phenylalanine ammonia lyase (PAL) activity and related PAL expression was most pronounced in August, about one month before commercial maturity, suggesting a high synthesis rate of phenolic compounds at this development stage. The most pronounced differences between the red and light- and dark-brown varieties were the increased PAL activity, PAL expression, and ANS expression in RWs in August. The vibrant color of the RW pellicle is based on the presence of four derivatives of cyanidin- and delphinidin-hexosides.
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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.
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Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao
2012-03-01
High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.
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Xia, Xiaofeng; Yu, Liying; Xue, Minqian; Yu, Xiaoqiang; Vasseur, Liette; Gurr, Geoff M.; Baxter, Simon W.; Lin, Hailan; Lin, Junhan; You, Minsheng
2015-01-01
The diamondback moth, Plutella xylostella (L.), is a destructive pest that attacks cruciferous crops worldwide. Immune responses are important for interactions between insects and pathogens and information on these underpins the development of strategies for biocontrol-based pest management. Little, however, is known about immune genes and their regulation patterns in P. xylostella. A total of 149 immune-related genes in 20 gene families were identified through comparison of P. xylostella genome with the genomes of other insects. Complete and conserved Toll, IMD and JAK-STAT signaling pathways were found in P. xylostella. Genes involved in pathogen recognition were expanded and more diversified than genes associated with intracellular signal transduction. Gene expression profiles showed that the IMD pathway may regulate expression of antimicrobial peptide (AMP) genes in the midgut, and be related to an observed down-regulation of AMPs in experimental lines of insecticide-resistant P. xylostella. A bacterial feeding study demonstrated that P. xylostella could activate different AMPs in response to bacterial infection. This study has established a framework of comprehensive expression profiles that highlight cues for immune regulation in a major pest. Our work provides a foundation for further studies on the functions of P. xylostella immune genes and mechanisms of innate immunity. PMID:25943446
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Xia, Xiaofeng; Yu, Liying; Xue, Minqian; Yu, Xiaoqiang; Vasseur, Liette; Gurr, Geoff M; Baxter, Simon W; Lin, Hailan; Lin, Junhan; You, Minsheng
2015-05-06
The diamondback moth, Plutella xylostella (L.), is a destructive pest that attacks cruciferous crops worldwide. Immune responses are important for interactions between insects and pathogens and information on these underpins the development of strategies for biocontrol-based pest management. Little, however, is known about immune genes and their regulation patterns in P. xylostella. A total of 149 immune-related genes in 20 gene families were identified through comparison of P. xylostella genome with the genomes of other insects. Complete and conserved Toll, IMD and JAK-STAT signaling pathways were found in P. xylostella. Genes involved in pathogen recognition were expanded and more diversified than genes associated with intracellular signal transduction. Gene expression profiles showed that the IMD pathway may regulate expression of antimicrobial peptide (AMP) genes in the midgut, and be related to an observed down-regulation of AMPs in experimental lines of insecticide-resistant P. xylostella. A bacterial feeding study demonstrated that P. xylostella could activate different AMPs in response to bacterial infection. This study has established a framework of comprehensive expression profiles that highlight cues for immune regulation in a major pest. Our work provides a foundation for further studies on the functions of P. xylostella immune genes and mechanisms of innate immunity.
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Go, Eden P; Moon, Hee-Jung; Mure, Minae; Desaire, Heather
2018-05-04
Human lysyl oxidase-like 2 (hLOXL2), a glycoprotein implicated in tumor progression and organ fibrosis, is a molecular target for anticancer and antifibrosis treatment. This glycoprotein contains three predicted N-linked glycosylation sites; one is near the protein's active site, and at least one more is known to facilitate the protein's secretion. Because the glycosylation impacts the protein's biology, we sought to characterize the native, mammalian glycosylation profile and to determine how closely this profile is recapitulated when the protein is expressed in insect cells. All three glycosylation sites on the protein, expressed in human embryonic kidney (HEK) cells, were characterized individually using a mass spectrometry-based glycopeptide analysis workflow. These data were compared to the glycosylation profile of the same protein expressed in insect cells. We found that the producer cell type imparts a substantial influence on the glycosylation of this important protein. The more-relevant version, expressed in HEK cells, contains large, acidic glycoforms; these glycans are not generated in insect cells. The glycosylation differences likely have structural and functional consequences, and these data should be considered when generating protein for functional studies or for high-throughput screening campaigns.
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JCDSA: a joint covariate detection tool for survival analysis on tumor expression profiles.
Wu, Yiming; Liu, Yanan; Wang, Yueming; Shi, Yan; Zhao, Xudong
2018-05-29
Survival analysis on tumor expression profiles has always been a key issue for subsequent biological experimental validation. It is crucial how to select features which closely correspond to survival time. Furthermore, it is important how to select features which best discriminate between low-risk and high-risk group of patients. Common features derived from the two aspects may provide variable candidates for prognosis of cancer. Based on the provided two-step feature selection strategy, we develop a joint covariate detection tool for survival analysis on tumor expression profiles. Significant features, which are not only consistent with survival time but also associated with the categories of patients with different survival risks, are chosen. Using the miRNA expression data (Level 3) of 548 patients with glioblastoma multiforme (GBM) as an example, miRNA candidates for prognosis of cancer are selected. The reliability of selected miRNAs using this tool is demonstrated by 100 simulations. Furthermore, It is discovered that significant covariates are not directly composed of individually significant variables. Joint covariate detection provides a viewpoint for selecting variables which are not individually but jointly significant. Besides, it helps to select features which are not only consistent with survival time but also associated with prognosis risk. The software is available at http://bio-nefu.com/resource/jcdsa .
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Pena-Castillo, Lourdes; Mercer, Ryan; Gurinovich, Anastasia
2014-08-28
The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigatedmore » preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.« less
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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
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2011-01-01
Background Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Methods Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. Results EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Conclusions Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series. PMID:21266046
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Peraldo-Neia, Caterina; Migliardi, Giorgia; Mello-Grand, Maurizia; Montemurro, Filippo; Segir, Raffaella; Pignochino, Ymera; Cavalloni, Giuliana; Torchio, Bruno; Mosso, Luciano; Chiorino, Giovanna; Aglietta, Massimo
2011-01-25
Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series.
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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... -
Behçet's: A Disease or a Syndrome? Answer from an Expression Profiling Study.
Oğuz, Ali Kemal; Yılmaz, Seda Taşır; Oygür, Çağdaş Şahap; Çandar, Tuba; Sayın, Irmak; Kılıçoğlu, Sibel Serin; Ergün, İhsan; Ateş, Aşkın; Özdağ, Hilal; Akar, Nejat
2016-01-01
Behçet's disease (BD) is a chronic, relapsing, multisystemic inflammatory disorder with unanswered questions regarding its etiology/pathogenesis and classification. Distinct manifestation based subsets, pronounced geographical variations in expression, and discrepant immunological abnormalities raised the question whether Behçet's is "a disease or a syndrome". To answer the preceding question we aimed to display and compare the molecular mechanisms underlying distinct subsets of BD. For this purpose, the expression data of the gene expression profiling and association study on BD by Xavier et al (2013) was retrieved from GEO database and reanalysed by gene expression data analysis/visualization and bioinformatics enrichment tools. There were 15 BD patients (B) and 14 controls (C). Three subsets of BD patients were generated: MB (isolated mucocutaneous manifestations, n = 7), OB (ocular involvement, n = 4), and VB (large vein thrombosis, n = 4). Class comparison analyses yielded the following numbers of differentially expressed genes (DEGs); B vs C: 4, MB vs C: 5, OB vs C: 151, VB vs C: 274, MB vs OB: 215, MB vs VB: 760, OB vs VB: 984. Venn diagram analysis showed that there were no common DEGs in the intersection "MB vs C" ∩ "OB vs C" ∩ "VB vs C". Cluster analyses successfully clustered distinct expressions of BD. During gene ontology term enrichment analyses, categories with relevance to IL-8 production (MB vs C) and immune response to microorganisms (OB vs C) were differentially enriched. Distinct subsets of BD display distinct expression profiles and different disease associated pathways. Based on these clear discrepancies, the designation as "Behçet's syndrome" (BS) should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS subsets. Four gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis.
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L1000CDS2: LINCS L1000 characteristic direction signatures search engine.
Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi
2016-01-01
The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.
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Doumatey, Ayo P; Xu, Huichun; Huang, Hanxia; Trivedi, Niraj S; Lei, Lin; Elkahloun, Abdel; Adeyemo, Adebowale; Rotimi, Charles N
2015-06-01
Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D. Twenty morbidly obese (mean BMI: about 54 kg/m 2 ) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals. At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase ( HNRNPA1, TNKS2 ), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified. This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.
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Tan, Guo-Wei; Lan, Fo-Lin; Gao, Jian-Guo; Jiang, Cai-Mou; Zhang, Yi; Huang, Xiao-Hong; Ma, Yue-Hong; Shao, He-Dui; He, Xue-Yang; Chen, Jin-Long; Long, Jian-Wu; Xiao, Hui-Sheng; Guo, Zhi-Tong; Diao, Yi
2012-08-01
Previously, we developed an orthotopic xenograft model of human glioblastoma multiforme (GBM) with high EGFR expression and invasiveness in Balb/c nu/nu nude mice. Now we also developed the same orthotopic xenograft model in transgenic nude mice with green fluorescent protein (GFP) expression. The present orthotopic xenografts labeled by phycoerythrin fluorescing red showed high EGFR expression profile, and invasive behavior under a bright green-red dual-color fluorescence background. A striking advantage in the present human GBM model is that the change of tumor growth can be observed visually instead of sacrificing animals in our further antitumor therapy studies.
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DNA methylation-based reclassification of olfactory neuroblastoma.
Capper, David; Engel, Nils W; Stichel, Damian; Lechner, Matt; Glöss, Stefanie; Schmid, Simone; Koelsche, Christian; Schrimpf, Daniel; Niesen, Judith; Wefers, Annika K; Jones, David T W; Sill, Martin; Weigert, Oliver; Ligon, Keith L; Olar, Adriana; Koch, Arend; Forster, Martin; Moran, Sebastian; Tirado, Oscar M; Sáinz-Japeado, Miguel; Mora, Jaume; Esteller, Manel; Alonso, Javier; Del Muro, Xavier Garcia; Paulus, Werner; Felsberg, Jörg; Reifenberger, Guido; Glatzel, Markus; Frank, Stephan; Monoranu, Camelia M; Lund, Valerie J; von Deimling, Andreas; Pfister, Stefan; Buslei, Rolf; Ribbat-Idel, Julika; Perner, Sven; Gudziol, Volker; Meinhardt, Matthias; Schüller, Ulrich
2018-05-05
Olfactory neuroblastoma/esthesioneuroblastoma (ONB) is an uncommon neuroectodermal neoplasm thought to arise from the olfactory epithelium. Little is known about its molecular pathogenesis. For this study, a retrospective cohort of n = 66 tumor samples with the institutional diagnosis of ONB was analyzed by immunohistochemistry, genome-wide DNA methylation profiling, copy number analysis, and in a subset, next-generation panel sequencing of 560 tumor-associated genes. DNA methylation profiles were compared to those of relevant differential diagnoses of ONB. Unsupervised hierarchical clustering analysis of DNA methylation data revealed four subgroups among institutionally diagnosed ONB. The largest group (n = 42, 64%, Core ONB) presented with classical ONB histology and no overlap with other classes upon methylation profiling-based t-distributed stochastic neighbor embedding (t-SNE) analysis. A second DNA methylation group (n = 7, 11%) with CpG island methylator phenotype (CIMP) consisted of cases with strong expression of cytokeratin, no or scarce chromogranin A expression and IDH2 hotspot mutation in all cases. T-SNE analysis clustered these cases together with sinonasal carcinoma with IDH2 mutation. Four cases (6%) formed a small group characterized by an overall high level of DNA methylation, but without CIMP. The fourth group consisted of 13 cases that had heterogeneous DNA methylation profiles and strong cytokeratin expression in most cases. In t-SNE analysis, these cases mostly grouped among sinonasal adenocarcinoma, squamous cell carcinoma, and undifferentiated carcinoma. Copy number analysis indicated highly recurrent chromosomal changes among Core ONB with a high frequency of combined loss of chromosome 1-4, 8-10, and 12. NGS sequencing did not reveal highly recurrent mutations in ONB, with the only recurrently mutated genes being TP53 and DNMT3A. In conclusion, we demonstrate that institutionally diagnosed ONB are a heterogeneous group of tumors. Expression of cytokeratin, chromogranin A, the mutational status of IDH2 as well as DNA methylation patterns may greatly aid in the precise classification of ONB.
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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
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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
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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.
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Very Low Abundance Single-Cell Transcript Quantification with 5-Plex ddPCRTM Assays.
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.
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Peyravian, Noshad; Larki, Pegah; Gharib, Ehsan; Nazemalhosseini-Mojarad, Ehsan; Anaraki, Fakhrosadate; Young, Chris; McClellan, James; Ashrafian Bonab, Maziar; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza
2018-01-01
A key factor in determining the likely outcome for a patient with colorectal cancer is whether or not the tumour has metastasised to the lymph nodes—information which is also important in assessing any possibilities of lymph node resection so as to improve survival. In this review we perform a wide-range assessment of literature relating to recent developments in gene expression profiling (GEP) of the primary tumour, to determine their utility in assessing node status. A set of characteristic genes seems to be involved in the prediction of lymph node metastasis (LNM) in colorectal patients. Hence, GEP is applicable in personalised/individualised/tailored therapies and provides insights into developing novel therapeutic targets. Not only is GEP useful in prediction of LNM, but it also allows classification based on differences such as sample size, target gene expression, and examination method. PMID:29498671
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Shu, Xianghua; Liu, Yonggang; Yang, Liangyu; Song, Chunlian; Hou, Jiafa
2008-01-01
The complete coding sequences of 3 porcine genes - ASPA, NAGA, and HEXA - were amplified by the reverse transcriptase polymerase chain reaction (RT-PCR) based on the conserved sequence information of the mouse or other mammals and referenced pig ESTs. These 3 novel porcine genes were then deposited in the NCBI database and assigned GeneIDs: 100142661, 100142664 and 100142667. The phylogenetic tree analysis revealed that the porcine ASPA, NAGA, and HEXA all have closer genetic relationships with the ASPA, NAGA, and HEXA of cattle. Tissue expression profile analysis was also carried out and results revealed that swine ASPA, NAGA, and HEXA genes were differentially expressed in various organs, including skeletal muscle, the heart, liver, fat, kidney, lung, and small and large intestines. Our experiment is the first one to establish the foundation for further research on these 3 swine genes.
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Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray
2012-01-01
Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600
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2013-01-01
Background High-throughput RNA sequencing (RNA-seq) offers unprecedented power to capture the real dynamics of gene expression. Experimental designs with extensive biological replication present a unique opportunity to exploit this feature and distinguish expression profiles with higher resolution. RNA-seq data analysis methods so far have been mostly applied to data sets with few replicates and their default settings try to provide the best performance under this constraint. These methods are based on two well-known count data distributions: the Poisson and the negative binomial. The way to properly calibrate them with large RNA-seq data sets is not trivial for the non-expert bioinformatics user. Results Here we show that expression profiles produced by extensively-replicated RNA-seq experiments lead to a rich diversity of count data distributions beyond the Poisson and the negative binomial, such as Poisson-Inverse Gaussian or Pólya-Aeppli, which can be captured by a more general family of count data distributions called the Poisson-Tweedie. The flexibility of the Poisson-Tweedie family enables a direct fitting of emerging features of large expression profiles, such as heavy-tails or zero-inflation, without the need to alter a single configuration parameter. We provide a software package for R called tweeDEseq implementing a new test for differential expression based on the Poisson-Tweedie family. Using simulations on synthetic and real RNA-seq data we show that tweeDEseq yields P-values that are equally or more accurate than competing methods under different configuration parameters. By surveying the tiny fraction of sex-specific gene expression changes in human lymphoblastoid cell lines, we also show that tweeDEseq accurately detects differentially expressed genes in a real large RNA-seq data set with improved performance and reproducibility over the previously compared methodologies. Finally, we compared the results with those obtained from microarrays in order to check for reproducibility. Conclusions RNA-seq data with many replicates leads to a handful of count data distributions which can be accurately estimated with the statistical model illustrated in this paper. This method provides a better fit to the underlying biological variability; this may be critical when comparing groups of RNA-seq samples with markedly different count data distributions. The tweeDEseq package forms part of the Bioconductor project and it is available for download at http://www.bioconductor.org. PMID:23965047
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Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro
2007-05-01
Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.
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Distinct Protein Expression Profiles of Solid-Pseudopapillary Neoplasms of the Pancreas.
Park, Minhee; Lim, Jong-Sun; Lee, Hyoung-Joo; Na, Keun; Lee, Min Jung; Kang, Chang Moo; Paik, Young-Ki; Kim, Hoguen
2015-08-07
Solid-pseudopapillary neoplasm (SPN) is an uncommon pancreatic tumor with mutation in CTNNB1 and distinct clinical and pathological features. We compared the proteomic profiles of SPN to mRNA expression. Pooled SPNs and pooled non-neoplastic pancreatic tissues were examined with high-resolution mass spectrometry. We identified 329 (150 up-regulated and 179 down-regulated) differentially expressed proteins in SPN. We identified 191 proteins (58.1% of the 329 dysregulated proteins) with the same expression tendencies in SPN based on mRNA data. Many overexpressed proteins were related to signaling pathways known to be activated in SPNs. We found that several proteins involved in Wnt signaling, including DKK4 and β-catenin, and proteins that bind β-catenin, such as FUS and NONO, were up-regulated in SPNs. Molecules involved in glycolysis, including PKM2, ENO2, and HK1, were overexpressed in accordance to their mRNA levels. In summary, SPN showed (1) distinct protein expression changes that correlated with mRNA expression, (2) overexpression of Wnt signaling proteins and proteins that bind directly to β-catenin, and (3) overexpression of proteins involved in metabolism. These findings may help develop early diagnostic biomarkers and molecular targets.
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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.
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Chen, Hao; Sun, Wei; Zhang, Xian Sheng
2013-01-01
Pollination is the first crucial step of sexual reproduction in flowering plants, and it requires communication and coordination between the pollen and the stigma. Maize (Zea mays) is a model monocot with extraordinarily long silks, and a fully sequenced genome, but little is known about the mechanism of its pollen–stigma interactions. In this study, the dynamic gene expression of silks at four different stages before and after pollination was analyzed. The expression profiles of immature silks (IMS), mature silks (MS), and silks at 20 minutes and 3 hours after pollination (20MAP and 3HAP, respectively) were compared. In total, we identified 6,337 differentially expressed genes in silks (SDEG) at the four stages. Among them, the expression of 172 genes were induced upon pollination, most of which participated in RNA binding, processing and transcription, signal transduction, and lipid metabolism processes. Genes in the SDEG dataset could be divided into 12 time-course clusters according to their expression patterns. Gene Ontology (GO) enrichment analysis revealed that many genes involved in microtubule-based movement, ubiquitin-mediated protein degradation, and transport were predominantly expressed at specific stages, indicating that they might play important roles in the pollination process of maize. These results add to current knowledge about the pollination process of grasses and provide a foundation for future studies on key genes involved in the pollen–silk interaction in maize. PMID:23301084
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Zhang, Min; Zhou, Yuwen; Wang, Hui; Jones, Huw; Gao, Qiang; Wang, Dahai; Ma, Youzhi; Xia, Lanqin
2013-08-16
The grain aphid (Sitobion avenae F.) is a major agricultural pest which causes significant yield losses of wheat in China, Europe and North America annually. Transcriptome profiling of the grain aphid alimentary canal after feeding on wheat plants could provide comprehensive gene expression information involved in feeding, ingestion and digestion. Furthermore, selection of aphid-specific RNAi target genes would be essential for utilizing a plant-mediated RNAi strategy to control aphids via a non-toxic mode of action. However, due to the tiny size of the alimentary canal and lack of genomic information on grain aphid as a whole, selection of the RNAi targets is a challenging task that as far as we are aware, has never been documented previously. In this study, we performed de novo transcriptome assembly and gene expression analyses of the alimentary canals of grain aphids before and after feeding on wheat plants using Illumina RNA sequencing. The transcriptome profiling generated 30,427 unigenes with an average length of 664 bp. Furthermore, comparison of the transcriptomes of alimentary canals of pre- and post feeding grain aphids indicated that 5490 unigenes were differentially expressed, among which, diverse genes and/or pathways were identified and annotated. Based on the RPKM values of these unigenes, 16 of them that were significantly up or down-regulated upon feeding were selected for dsRNA artificial feeding assay. Of these, 5 unigenes led to higher mortality and developmental stunting in an artificial feeding assay due to the down-regulation of the target gene expression. Finally, by adding fluorescently labelled dsRNA into the artificial diet, the spread of fluorescence signal in the whole body tissues of grain aphid was observed. Comparison of the transcriptome profiles of the alimentary canals of pre- and post-feeding grain aphids on wheat plants provided comprehensive gene expression information that could facilitate our understanding of the molecular mechanisms underlying feeding, ingestion and digestion. Furthermore, five novel and effective potential RNAi target genes were identified in grain aphid for the first time. This finding would provide a fundamental basis for aphid control in wheat through plant mediated RNAi strategy.
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Liu, Haibo; Cadaneanu, Radu M; Lai, Kevin; Zhang, Baohui; Huo, Lihong; An, Dong Sun; Li, Xinmin; Lewis, Michael S; Garraway, Isla P
2015-01-01
BACKGROUND Human fetal prostate buds appear in the 10th gestational week as solid cords, which branch and form lumens in response to androgen 1. Previous in vivo analysis of prostate epithelia isolated from benign prostatectomy specimens indicated that Epcam+CD44−CD49fHi basal cells possess efficient tubule initiation capability relative to other subpopulations 2. Stromal interactions and branching morphogenesis displayed by adult tubule-initiating cells (TIC) are reminiscent of fetal prostate development. In the current study, we evaluated in vivo tubule initiation by human fetal prostate cells and determined expression profiles of fetal and adult epithelial subpopulations in an effort to identify pathways used by TIC. METHODS Immunostaining and FACS analysis based on Epcam, CD44, and CD49f expression demonstrated the majority (99.9%) of fetal prostate epithelial cells (FC) were Epcam+CD44− with variable levels of CD49f expression. Fetal populations isolated via cell sorting were implanted into immunocompromised mice. Total RNA isolation from Epcam+CD44−CD49fHi FC, adult Epcam+CD44−CD49fHi TIC, Epcam+CD44+CD49fHi basal cells (BC), and Epcam+CD44−CD49fLo luminal cells (LC) was performed, followed by microarray analysis of 19 samples using the Affymetrix Gene Chip Human U133 Plus 2.0 Array. Data was analyzed using Partek Genomics Suite Version 6.4. Genes selected showed >2-fold difference in expression and P < 5.00E-2. Results were validated with RT-PCR. RESULTS Grafts retrieved from Epcam+CD44− fetal cell implants displayed tubule formation with differentiation into basal and luminal compartments, while only stromal outgrowths were recovered from Epcam- fetal cell implants. Hierarchical clustering revealed four distinct groups determined by antigenic profile (TIC, BC, LC) and developmental stage (FC). TIC and BC displayed basal gene expression profiles, while LC expressed secretory genes. FC had a unique profile with the most similarities to adult TIC. Functional, network, and canonical pathway identification using Ingenuity Pathway Analysis Version 7.6 compiled genes with the highest differential expression (TIC relative to BC or LC). Many of these genes were found to be significantly associated with prostate tumorigenesis. CONCLUSIONS Our results demonstrate clustering gene expression profiles of FC and adult TIC. Pathways associated with TIC are known to be deregulated in cancer, suggesting a cell-of-origin role for TIC versus re-emergence of pathways common to these cells in tumorigenesis. Prostate 75: 764–776, 2015. © The Authors. The Prostate, published by Wiley Periodicals, Inc. PMID:25663004
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Liu, Haibo; Cadaneanu, Radu M; Lai, Kevin; Zhang, Baohui; Huo, Lihong; An, Dong Sun; Li, Xinmin; Lewis, Michael S; Garraway, Isla P
2015-05-01
Human fetal prostate buds appear in the 10th gestational week as solid cords, which branch and form lumens in response to androgen 1. Previous in vivo analysis of prostate epithelia isolated from benign prostatectomy specimens indicated that Epcam⁺ CD44⁻ CD49f(Hi) basal cells possess efficient tubule initiation capability relative to other subpopulations 2. Stromal interactions and branching morphogenesis displayed by adult tubule-initiating cells (TIC) are reminiscent of fetal prostate development. In the current study, we evaluated in vivo tubule initiation by human fetal prostate cells and determined expression profiles of fetal and adult epithelial subpopulations in an effort to identify pathways used by TIC. Immunostaining and FACS analysis based on Epcam, CD44, and CD49f expression demonstrated the majority (99.9%) of fetal prostate epithelial cells (FC) were Epcam⁺ CD44⁻ with variable levels of CD49f expression. Fetal populations isolated via cell sorting were implanted into immunocompromised mice. Total RNA isolation from Epcam⁺ CD44⁻ CD49f(Hi) FC, adult Epcam⁺ CD44⁻ CD49f(Hi) TIC, Epcam⁺ CD44⁺ CD49f(Hi) basal cells (BC), and Epcam⁺ CD44⁻ CD49f(Lo) luminal cells (LC) was performed, followed by microarray analysis of 19 samples using the Affymetrix Gene Chip Human U133 Plus 2.0 Array. Data was analyzed using Partek Genomics Suite Version 6.4. Genes selected showed >2-fold difference in expression and P < 5.00E-2. Results were validated with RT-PCR. Grafts retrieved from Epcam⁺ CD44⁻ fetal cell implants displayed tubule formation with differentiation into basal and luminal compartments, while only stromal outgrowths were recovered from Epcam- fetal cell implants. Hierarchical clustering revealed four distinct groups determined by antigenic profile (TIC, BC, LC) and developmental stage (FC). TIC and BC displayed basal gene expression profiles, while LC expressed secretory genes. FC had a unique profile with the most similarities to adult TIC. Functional, network, and canonical pathway identification using Ingenuity Pathway Analysis Version 7.6 compiled genes with the highest differential expression (TIC relative to BC or LC). Many of these genes were found to be significantly associated with prostate tumorigenesis. Our results demonstrate clustering gene expression profiles of FC and adult TIC. Pathways associated with TIC are known to be deregulated in cancer, suggesting a cell-of-origin role for TIC versus re-emergence of pathways common to these cells in tumorigenesis. © 2015 The Authors. The Prostate, published by Wiley Periodicals, Inc.
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IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH
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...
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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)
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Andrade, Fábia de Oliveira; de Assis, Sonia; Jin, Lu; Fontelles, Camile Castilho; Barbisan, Luís Fernando; Purgatto, Eduardo; Hilakivi-Clarke, Leena; Ong, Thomas Prates
2015-09-05
The persistent effects of animal fat consumption during pregnancy and nursing on the programming of breast cancer risk among female offspring were studied here. We have previously found that female offspring of rat dams that consumed a lard-based high-fat (HF) diet (60% fat-derived energy) during pregnancy, or during pregnancy and lactation, were at a reduced risk of developing mammary cancer. To better understand the unexpected protective effects of early life lard exposure, we have applied lipidomics and nutrigenomics approaches to investigate the fatty acid profile and global gene expression patterns in the mammary tissue of the female offspring. Consumption of this HF diet during gestation had few effects on the mammary tissue fatty acids profile of young adult offspring, while exposure from gestation throughout nursing promoted significant alterations in the fatty acids profile. Major differences were related to decreases in saturated fatty acids (SFA) and increases in omega-6 polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs) and conjugated linolenic acid (CLA) concentrations. In addition several differences in gene expression patterns by microarray analysis between the control and in utero or in utero and during lactation HF exposed offspring were identified. Differential dependency network (DDN) analysis indicated that many of the genes exhibited unique connections to other genes only in the HF offspring. These unique connections included Hrh1-Ythdf1 and Repin1-Elavl2 in the in utero HF offspring, and Rnf213-Htr3b and Klf5-Chrna4 in the in utero and lactation HF offspring, compared with the control offspring. We conclude that an exposure to a lard-based HF diet during early life changes the fatty acid profile and transcriptional network in mammary gland in young adult rats, and these changes appear to be consistent with reduced mammary cancer risk observed in our previous study. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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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.
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Das, Sayan; Ehlers, Jeffrey D; Close, Timothy J; Roberts, Philip A
2010-08-19
The locus Rk confers resistance against several species of root-knot nematodes (Meloidogyne spp., RKN) in cowpea (Vigna unguiculata). Based on histological and reactive oxygen species (ROS) profiles, Rk confers a delayed but strong resistance mechanism without a hypersensitive reaction-mediated cell death process, which allows nematode development but blocks reproduction. Responses to M. incognita infection in roots of resistant genotype CB46 and a susceptible near-isogenic line (null-Rk) were investigated using a soybean Affymetrix GeneChip expression array at 3 and 9 days post-inoculation (dpi). At 9 dpi 552 genes were differentially expressed in incompatible interactions (infected resistant tissue compared with non-infected resistant tissue) and 1,060 genes were differentially expressed in compatible interactions (infected susceptible tissue compared with non-infected susceptible tissue). At 3 dpi the differentially expressed genes were 746 for the incompatible and 623 for the compatible interactions. When expression between infected resistant and susceptible genotypes was compared, 638 and 197 genes were differentially expressed at 9 and 3 dpi, respectively. In comparing the differentially expressed genes in response to nematode infection, a greater number and proportion of genes were down-regulated in the resistant than in the susceptible genotype, whereas more genes were up-regulated in the susceptible than in the resistant genotype. Gene ontology based functional categorization revealed that the typical defense response was partially suppressed in resistant roots, even at 9 dpi, allowing nematode juvenile development. Differences in ROS concentrations, induction of toxins and other defense related genes seem to play a role in this unique resistance mechanism.
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High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike
2010-01-01
We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139
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Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.
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.
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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... -
NASA Astrophysics Data System (ADS)
Lee, Young Eun; Saharia, Aditya
With the rapid growth of computer mediated communication technologies in the last two decades, various types of virtual communities have emerged. Some communities provide a role playing arena, enabled by avatars, while others provide an arena for expressing and promoting detailed personal profiles to enhance their offline social networks. Due to different focus of these virtual communities, different factors motivate members to participate in these communities. In this study, we examine differences in members’ motivations to participate in role-playing versus self-expression based virtual communities. To achieve this goal, we apply the Wang and Fesenmaier (2004) framework, which explains members’ participation in terms of their functional, social, psychological, and hedonic needs. The primary contributions of this study are two folds: First, it demonstrates differences between role-playing and self-expression based communities. Second, it provides a comprehensive framework describing members’ motivation to participate in virtual communities.
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Wang, Hung-Ming; Cheng, Nai-Ming; Lee, Li-Yu; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Liao, Chun-Ta; Yang, Lan-Yan; Yen, Tzu-Chen
2016-02-01
The Ang's risk profile (based on p16, smoking and cancer stage) is a well-known prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC). Whether heterogeneity in (18)F-fluorodeoxyglucose (FDG) positron emission tomographic (PET) images and epidermal growth factor receptor (EGFR) expression could provide additional information on clinical outcomes in advanced-stage OPSCC was investigated. Patients with stage III-IV OPSCC who completed primary therapy were eligible. Zone-size nonuniformity (ZSNU) extracted from pretreatment FDG PET scans was used as an index of image heterogeneity. EGFR and p16 expression were examined by immunohistochemistry. Disease-specific survival (DSS) and overall survival (OS) served as outcome measures. Kaplan-Meier estimates and Cox proportional hazards regression models were used for survival analysis. A bootstrap resampling technique was applied to investigate the stability of outcomes. Finally, a recursive partitioning analysis (RPA)-based model was constructed. A total of 113 patients were included, of which 28 were p16-positive. Multivariate analysis identified the Ang's profile, EGFR and ZSNU as independent predictors of both DSS and OS. Using RPA, the three risk factors were used to devise a prognostic scoring system that successfully predicted DSS in both p16-positive and -negative cases. The c-statistic of the prognostic index for DSS was 0.81, a value which was significantly superior to both AJCC stage (0.60) and the Ang's risk profile (0.68). In patients showing an Ang's high-risk profile (N = 77), the use of our scoring system clearly identified three distinct prognostic subgroups. It was concluded that a novel index may improve the prognostic stratification of patients with advanced-stage OPSCC. © 2015 UICC.
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Quality Evaluation of Human Bone Marrow Mesenchymal Stem Cells for Cartilage Repair
Shiraishi, Katsunori; Takeuchi, Shunsuke; Yanada, Shinobu; Mera, Hisashi; Wakitani, Shigeyuki; Adachi, Nobuo
2017-01-01
Quality evaluation of mesenchymal stem cells (MSCs) based on efficacy would be helpful for their clinical application. In this study, we aimed to find the factors of human bone marrow MSCs relating to cartilage repair. The expression profiles of humoral factors, messenger RNAs (mRNAs), and microRNAs (miRNAs) were analyzed in human bone marrow MSCs from five different donors. We investigated the correlations of these expression profiles with the capacity of the MSCs for proliferation, chondrogenic differentiation, and cartilage repair in vivo. The mRNA expression of MYBL1 was positively correlated with proliferation and cartilage differentiation. By contrast, the mRNA expression of RCAN2 and the protein expression of TIMP-1 and VEGF were negatively correlated with proliferation and cartilage differentiation. However, MSCs from all five donors had the capacity to promote cartilage repair in vivo regardless of their capacity for proliferation and cartilage differentiation. The mRNA expression of HLA-DRB1 was positively correlated with cartilage repair in vivo. Meanwhile, the mRNA expression of TMEM155 and expression of miR-486-3p, miR-148b, miR-93, and miR-320B were negatively correlated with cartilage repair. The expression analysis of these factors might help to predict the ability of bone marrow MSCs to promote cartilage repair. PMID:28835756
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Chen, Yan-Ni; Du, Hui-Ying; Shi, Zhuo-Yue; He, Li; He, Yu-Ying; Wang, Duan
2018-01-24
The pathogenesis of autism spectrum disorders remains elusive and currently there are no diagnostic or predictive biomarkers in autism available. Proteomic profiling has been used in a wide range of neurodevelopmental disorder studies, which could produce deeper perceptions of the molecular bases behind certain disease and potentially becomes useful in discovering biomarkers in autism spectrum disorders. Serum samples were collected from autistic children about 3 years old in age (n = 32) and healthy controls (n = 20) in similar age and gender. The samples were identified specific proteins that are differentially expressed by magnetic bead-based pre-fractionation and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS). Eight protein peaks were significantly different in autistic children from the healthy controls (P < 0.0001). The two peaks with the most significant differences were 6428 and 7758 Da in size. According to differences in serum protein profiles between the autistic children and healthy controls, this study identified a set of differentially expressed proteins those are significant for further evaluation and might function as biomarkers in autism.
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Dysregulation of miRNAs in bladder cancer: altered expression with aberrant biogenesis procedure
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
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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.
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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
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Zhao, Junliang; Zhang, Shaohong; Yang, Tifeng; Zeng, Zichong; Huang, Zhanghui; Liu, Qing; Wang, Xiaofei; Leach, Jan; Leung, Hei; Liu, Bin
2015-07-01
Gene expression profiling under severe cold stress (4°C) has been conducted in plants including rice. However, rice seedlings are frequently exposed to milder cold stresses under natural environments. To understand the responses of rice to milder cold stress, a moderately low temperature (8°C) was used for cold treatment prior to genome-wide profiling of gene expression in a cold-tolerant japonica variety, Lijiangxintuanheigu (LTH). A total of 5557 differentially expressed genes (DEGs) were found at four time points during moderate cold stress. Both the DEGs and differentially expressed transcription factor genes were clustered into two groups based on their expression, suggesting a two-phase response to cold stress and a determinative role of transcription factors in the regulation of stress response. The induction of OsDREB2A under cold stress is reported for the first time in this study. Among the anti-oxidant enzyme genes, glutathione peroxidase (GPX) and glutathione S-transferase (GST) were upregulated, suggesting that the glutathione system may serve as the main reactive oxygen species (ROS) scavenger in LTH. Changes in expression of genes in signal transduction pathways for auxin, abscisic acid (ABA) and salicylic acid (SA) imply their involvement in cold stress responses. The induction of ABA response genes and detection of enriched cis-elements in DEGs suggest that ABA signaling pathway plays a dominant role in the cold stress response. Our results suggest that rice responses to cold stress vary with the specific temperature imposed and the rice genotype. © 2014 Scandinavian Plant Physiology Society.
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Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.
Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L
2008-08-15
The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.
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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
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Huang, Jianyan; Zhao, Xiaobo; Weng, Xiaoyu; Wang, Lei; Xie, Weibo
2012-01-01
Background The B-box (BBX) -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX) gene family until now. Methodology/Principal Findings In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97). In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. Conclusions/Significance The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the OsBBX genes. PMID:23118960
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Transcriptome Analysis of ABA/JA-Dual Responsive Genes in Rice Shoot and Root.
Kim, Jin-Ae; Bhatnagar, Nikita; Kwon, Soon Jae; Min, Myung Ki; Moon, Seok-Jun; Yoon, In Sun; Kwon, Taek-Ryoun; Kim, Sun Tae; Kim, Beom-Gi
2018-01-01
The phytohormone abscisic acid (ABA) enables plants to adapt to adverse environmental conditions through the modulation of metabolic pathways and of growth and developmental programs. We used comparative microarray analysis to identify genes exhibiting ABA-dependent expression and other hormone-dependent expression among them in Oryza sativa shoot and root. We identified 854 genes as significantly up- or down-regulated in root or shoot under ABA treatment condition. Most of these genes had similar expression profiles in root and shoot under ABA treatment condition, whereas 86 genes displayed opposite expression responses in root and shoot. To examine the crosstalk between ABA and other hormones, we compared the expression profiles of the ABA-dependently regulated genes under several different hormone treatment conditions. Interestingly, around half of the ABA-dependently expressed genes were also regulated by jasmonic acid based on microarray data analysis. We searched the promoter regions of these genes for cis-elements that could be responsible for their responsiveness to both hormones, and found that ABRE and MYC2 elements, among others, were common to the promoters of genes that were regulated by both ABA and JA. These results show that ABA and JA might have common gene expression regulation system and might explain why the JA could function for both abiotic and biotic stress tolerance.
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Expression profiles of antimicrobial peptides (AMPs) and their regulation by Relish
NASA Astrophysics Data System (ADS)
Wang, Dongdong; Li, Fuhua; Li, Shihao; Wen, Rong; Xiang, Jianhai
2012-07-01
Antimicrobial peptides (AMPs), as key immune effectors, play important roles in the innate immune system of invertebrates. Different types of AMPs, including Penaeidin, Crustin, ALF (antilipopolysaccharide factor) have been identified in different penaeid shrimp; however, systematic analyses on the function of different AMPs in shrimp responsive to different types of bacteria are very limited. In this study, we analyzed the expression profiles of AMPs in the Chinese shrimps, Fenneropenaeus chinensis, simultaneously by real-time RT-PCR (reverse transcription-polymerase chain reaction) when shrimp were challenged with Micrococcus lysodeikticus (Gram-positive, G+) or Vibrio anguillarium (Gram-negative, G-). Different AMPs showed different expression profiles when shrimp were injected with one type of bacterium, and one AMP also showed different expression profiles when shrimp were challenged with different bacteria. Furthermore, the expression of these AMPs showed temporal expression profiles, suggesting that different AMPs function coordinately in bacteria-infected shrimp. An RNA interference approach was used to study the function of the Relish transcription factor in regulating the transcription of different AMPs. The current study showed that Relish could regulate the transcription of different AMPs in shrimp. Differential expression profiles of AMPs in shrimp injected with different types of bacteria indicated that a complicated antimicrobial response network existed in shrimp. These data contribute to our understanding of immunity in shrimp and may provide a strategy for the control of disease in shrimp.
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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...
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Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks
Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi
2014-01-01
Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481
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Statistical use of argonaute expression and RISC assembly in microRNA target identification.
Stanhope, Stephen A; Sengupta, Srikumar; den Boon, Johan; Ahlquist, Paul; Newton, Michael A
2009-09-01
MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address the problem of detecting m/miRNA targeting relationships in homo sapiens from microarray data by developing statistical models that are motivated by the biological mechanisms used by miRNAs. The focus of our modeling is the construction, activity, and mediation of RNA-induced silencing complexes (RISCs) competent for targeted mRNA cleavage. We demonstrate that regression models accommodating RISC abundance and controlling for other mediating factors fit the expression profiles of known target pairs substantially better than models based on m/miRNA expressions alone, and lead to verifications of computational target pair predictions that are more sensitive than those based on marginal expression levels. Because our models are fully independent of exogenous results from sequence-based computational methods, they are appropriate for use as either a primary or secondary source of information regarding m/miRNA target pair relationships, especially in conjunction with high-throughput expression studies.
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Ma, W; Zhang, T-F; Lu, P; Lu, S H
2014-01-01
Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.
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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
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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
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Extended diagnostic criteria for plasmacytoid dendritic cell leukaemia.
Garnache-Ottou, Francine; Feuillard, Jean; Ferrand, Christophe; Biichle, Sabeha; Trimoreau, Franck; Seilles, Estelle; Salaun, Véronique; Garand, Richard; Lepelley, Pascale; Maynadié, Marc; Kuhlein, Emilienne; Deconinck, Eric; Daliphard, Sylvie; Chaperot, Laurence; Beseggio, Lucille; Foisseaud, Vincent; Macintyre, Elizabeth; Bene, Marie-Christine; Saas, Philippe; Jacob, Marie-Christine
2009-06-01
The diagnosis of plasmacytoid dendritic cell leukaemia (pDCL) is based on the immunophenotypic profile: CD4(+) CD56(+) lineage(neg) CD45RA(+)/RO(neg) CD11c(neg) CD116(low) CD123(+) CD34(neg) CD36(+) HLA-DR(+). Several studies have reported pDCL cases that do not express this exact profile or expressing some lineage antigens that could thus be misdiagnosed. This study aimed to validate pDCL-specific markers for diagnosis by flow-cytometry or quantitative reverse transcription polymerase chain reaction on bone marrow samples. Expression of markers previously found in normal pDC was analysed in 16 pDCL, four pDCL presenting an atypical phenotype (apDCL) and 113 non-pDC - lymphoid or myeloid - acute leukaemia. CD123 was expressed at significantly higher levels in pDCL and apDCL. BDCA-2 was expressed on 12/16 pDCL and on 2/4 apDCL, but was never detected in the 113 non-pDC acute leukaemia cases. BDCA-4 expression was found on 13/16 pDCL, but also in 12% of non-pDC acute leukaemia. High levels of LILRA4 and TCL1A transcripts distinguished pDCL and apDCL from all other acute leukaemia (except B-cell acute lymphoblastic leukaemia for TCL1A). We thus propose a diagnosis strategy, scoring first the CD4(+) CD56(+/-) MPO(neg) cCD3(neg) cCD79a(neg) CD11c(neg) profile and then the CD123(high), BDCA-2 and BDCA-4 expression. Atypical pDCL can be also identified this way and non-pDC acute leukaemia excluded: this scoring strategy is useful for diagnosing pDCL and apDCL.
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Zhang, R; Li, R; Zhi, L; Xu, Y; Lin, Y; Chen, L
2018-02-01
1. Muscle regulatory factors (MRFs), including Myf5, Myf6 (MRF4/herculin), MyoD and MyoG (myogenin), play pivotal roles in muscle growth and development. Therefore, they are considered as candidate genes for meat production traits in livestock and poultry. 2. The objective of this study was to investigate the expression profiles of these genes in skeletal muscles (breast muscle and thigh muscle) at 5 developmental stages (0, 81, 119, 154 and 210 d old) of Tibetan chickens. Relationships between expressions of these genes and growth and carcass traits in these chickens were also estimated. 3. The expression profiles showed that in the breast muscle of both genders the mRNA levels of MRF genes were highest on the day of hatching, then declined significantly from d 0 to d 81, and fluctuated in a certain range from d 81 to d 210. However, the expression of Myf5, Myf6 and MyoG reached peaks in the thigh muscle in 118-d-old females and for MyoD in 154-d-old females, whereas the mRNA amounts of MRF genes in the male thigh muscle were in a narrow range from d 0 to d 210. 4. Correlation analysis suggested that gender had an influence on the relationships of MRF gene expression with growth traits. The RNA levels of MyoD, Myf5 genes in male breast muscle were positively related with several growth traits of Tibetan chickens (P < 0.05). No correlation was found between expressions of MRF genes and carcass traits of the chickens. 5. These results will provide a base for functional studies of MRF genes on growth and development of Tibetan chickens, as well as selective breeding and resource exploration.
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Sliwinska, Agnieszka; Sitarek, Przemysław; Toma, Monika; Czarny, Piotr; Synowiec, Ewelina; Krupa, Renata; Wigner, Paulina; Bialek, Katarzyna; Kwiatkowski, Dominik; Korycinska, Anna; Majsterek, Ireneusz; Szemraj, Janusz; Galecki, Piotr; Sliwinski, Tomasz
2017-10-03
Neurodegeneration in Alzheimer's disease can be caused by accumulation of oxidative DNA damage resulting from altered expression of genes involved in the base excision repair system (BER). Promoter methylation can affect the profile of BER genes expression. Decreased expression of BER genes was observed in the brains of AD patients. The aim of our study was to compare the expression and methylation profiles of six genes coding for proteins involved in BER, namely: hOGG1, APE1, MUTYH, NEIL1, PARP1 and XRCC1, in the peripheral blood cells of AD patients and healthy volunteers. The study consisted of 100 persons diagnosed with Alzheimer's disease according to DSM-IV criteria, and 110 healthy volunteers. DNA and total RNA were isolated from venous blood cells. Promoter methylation profiles were obtained by High Resolution Melting (HRM) analysis of bisulfide converted DNA samples. Real-time PCR with TaqMan probes was employed for gene expression analysis. APE1, hOGG1, MUTYH, PARP1 and NEIL1 were significantly (p<0.001) down-regulated in the lymphocytes of AD patients, as compared to healthy volunteers. Expression of XRCC1 didn't differ significantly between both groups. We did not find any differences in the methylation pattern of any of the investigated BER genes. The methylation status of promoters is not associated with downregulation of BER genes. Our results show that downregulation of BER genes detected in peripheral blood samples could reflect the changes occurring in the brain of patients with AD, and may be a useful biomarker of this disease. Copyright © 2017 Elsevier Inc. All rights reserved.
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Chen, Xue; Chen, Zhu; Zhao, Hualin; Zhao, Yang; Cheng, Beijiu; Xiang, Yan
2014-01-01
Homeodomain-leucine zipper (HD-Zip) proteins, a group of homeobox transcription factors, participate in various aspects of normal plant growth and developmental processes as well as environmental responses. To date, no overall analysis or expression profiling of the HD-Zip gene family in soybean (Glycine max) has been reported. An investigation of the soybean genome revealed 88 putative HD-Zip genes. These genes were classified into four subfamilies, I to IV, based on phylogenetic analysis. In each subfamily, the constituent parts of gene structure and motif were relatively conserved. A total of 87 out of 88 genes were distributed unequally on 20 chromosomes with 36 segmental duplication events, indicating that segmental duplication is important for the expansion of the HD-Zip family. Analysis of the Ka/Ks ratios showed that the duplicated genes of the HD-Zip family basically underwent purifying selection with restrictive functional divergence after the duplication events. Analysis of expression profiles showed that 80 genes differentially expressed across 14 tissues, and 59 HD-Zip genes are differentially expressed under salinity and drought stress, with 20 paralogous pairs showing nearly identical expression patterns and three paralogous pairs diversifying significantly under drought stress. Quantitative real-time RT-PCR (qRT-PCR) analysis of six paralogous pairs of 12 selected soybean HD-Zip genes under both drought and salinity stress confirmed their stress-inducible expression patterns. This study presents a thorough overview of the soybean HD-Zip gene family and provides a new perspective on the evolution of this gene family. The results indicate that HD-Zip family genes may be involved in many plant responses to stress conditions. Additionally, this study provides a solid foundation for uncovering the biological roles of HD-Zip genes in soybean growth and development.
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Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis. PMID:25635858
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Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.
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Sasaki, Eita; Momose, Haruka; Hiradate, Yuki; Furuhata, Keiko; Takai, Mamiko; Asanuma, Hideki; Ishii, Ken J.
2018-01-01
Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development. PMID:29408882
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Identification of Candidate B-Lymphoma Genes by Cross-Species Gene Expression Profiling
Tompkins, Van S.; Han, Seong-Su; Olivier, Alicia; Syrbu, Sergei; Bair, Thomas; Button, Anna; Jacobus, Laura; Wang, Zebin; Lifton, Samuel; Raychaudhuri, Pradip; Morse, Herbert C.; Weiner, George; Link, Brian; Smith, Brian J.; Janz, Siegfried
2013-01-01
Comparative genome-wide expression profiling of malignant tumor counterparts across the human-mouse species barrier has a successful track record as a gene discovery tool in liver, breast, lung, prostate and other cancers, but has been largely neglected in studies on neoplasms of mature B-lymphocytes such as diffuse large B cell lymphoma (DLBCL) and Burkitt lymphoma (BL). We used global gene expression profiles of DLBCL-like tumors that arose spontaneously in Myc-transgenic C57BL/6 mice as a phylogenetically conserved filter for analyzing the human DLBCL transcriptome. The human and mouse lymphomas were found to have 60 concordantly deregulated genes in common, including 8 genes that Cox hazard regression analysis associated with overall survival in a published landmark dataset of DLBCL. Genetic network analysis of the 60 genes followed by biological validation studies indicate FOXM1 as a candidate DLBCL and BL gene, supporting a number of studies contending that FOXM1 is a therapeutic target in mature B cell tumors. Our findings demonstrate the value of the “mouse filter” for genomic studies of human B-lineage neoplasms for which a vast knowledge base already exists. PMID:24130802
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Dissecting modes of action of non-genotoxic carcinogens in primary mouse hepatocytes.
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.
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Ni, Ming; Ye, Fuqiang; Zhu, Juanjuan; Li, Zongwei; Yang, Shuai; Yang, Bite; Han, Lu; Wu, Yongge; Chen, Ying; Li, Fei; Wang, Shengqi; Bo, Xiaochen
2014-12-01
Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users' own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved. ExpTreeDB is a database that allows for queries on human and mouse microarray experiments from Gene Expression Omnibus with gene signatures or profiles. Compared with similar applications, ExpTreeDB pays more attention to dataset annotations and result visualization. We introduced a multiple-level annotation system to depict and organize original experiments. For example, a tamoxifen-treated cell line experiment is hierarchically annotated as 'agent→drug→estrogen receptor antagonist→tamoxifen'. Consequently, retrieved results are exhibited by an interactive tree-structured graphics, which provide an overview for related experiments and might enlighten users on key items of interest. The database is freely available at http://biotech.bmi.ac.cn/ExpTreeDB. Web site is implemented in Perl, PHP, R, MySQL and Apache. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Comparative analyses of industrial-scale human platelet lysate preparations.
Pierce, Jan; Benedetti, Eric; Preslar, Amber; Jacobson, Pam; Jin, Ping; Stroncek, David F; Reems, Jo-Anna
2017-12-01
Efforts are underway to eliminate fetal bovine serum from mammalian cell cultures for clinical use. An emerging, viable replacement option for fetal bovine serum is human platelet lysate (PL) as either a plasma-based or serum-based product. Nine industrial-scale, serum-based PL manufacturing runs (i.e., lots) were performed, consisting of an average ± standard deviation volume of 24.6 ± 2.2 liters of pooled, platelet-rich plasma units that were obtained from apheresis donors. Manufactured lots were compared by evaluating various biochemical and functional test results. Comprehensive cytokine profiles of PL lots and product stability tests were performed. Global gene expression profiles of mesenchymal stromal cells (MSCs) cultured with plasma-based or serum-based PL were compared to MSCs cultured with fetal bovine serum. Electrolyte and protein levels were relatively consistent among all serum-based PL lots, with only slight variations in glucose and calcium levels. All nine lots were as good as or better than fetal bovine serum in expanding MSCs. Serum-based PL stored at -80°C remained stable over 2 years. Quantitative cytokine arrays showed similarities as well as dissimilarities in the proteins present in serum-based PL. Greater differences in MSC gene expression profiles were attributable to the starting cell source rather than with the use of either PL or fetal bovine serum as a culture supplement. Using a large-scale, standardized method, lot-to-lot variations were noted for industrial-scale preparations of serum-based PL products. However, all lots performed as well as or better than fetal bovine serum in supporting MSC growth. Together, these data indicate that off-the-shelf PL is a feasible substitute for fetal bovine serum in MSC cultures. © 2017 AABB.
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Sen Sarma, Moushumi; Whitfield, Charles W; Robinson, Gene E
2007-06-29
Honey bees are known for several striking social behaviors, including a complex pattern of behavioral maturation that gives rise to an age-related colony division of labor and a symbolic dance language, by which successful foragers communicate the location of attractive food sources to their nestmates. Our understanding of honey bees is mostly based on studies of the Western honey bee, Apis mellifera, even though there are 9-10 other members of genus Apis, showing interesting variations in social behavior relative to A. mellifera. To facilitate future in-depth genomic and molecular level comparisons of behavior across the genus, we performed a microarray analysis of brain gene expression for A. mellifera and three key species found in Asia, A. cerana, A. florea and A. dorsata. For each species we compared brain gene expression patterns between foragers and adult one-day-old bees on an A. mellifera cDNA microarray and calculated within-species gene expression ratios to facilitate cross-species analysis. The number of cDNA spots showing hybridization fluorescence intensities above the experimental threshold was reduced by an average of 16% in the Asian species compared to A. mellifera, but an average of 71% of genes on the microarray were available for analysis. Brain gene expression profiles between foragers and one-day-olds showed differences that are consistent with a previous study on A. mellifera and were comparable across species. Although 1772 genes showed significant differences in expression between foragers and one-day-olds, only 218 genes showed differences in forager/one-day-old expression between species (p < 0.001). Principal Components Analysis revealed dominant patterns of expression that clearly distinguished between the four species but did not reflect known differences in behavior and ecology. There were species differences in brain expression profiles for functionally related groups of genes. We conclude that the A. mellifera cDNA microarray can be used effectively for cross-species comparisons within the genus. Our results indicate that there is a widespread conservation of the molecular processes in the honey bee brain underlying behavioral maturation. Species differences in brain expression profiles for functionally related groups of genes provide possible clues to the basis of behavioral variation in the genus.
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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.
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NASA Astrophysics Data System (ADS)
Chen, Dongquan; Stueckle, Todd A.; Luanpitpong, Sudjit; Rojanasakul, Yon; Lu, Yongju; Wang, Liying
2015-01-01
A rapid increase in utility of engineered nanomaterials, including carbon nanotubes (CNTs), has raised a concern over their safety. Based on recent evidence from animal studies, pulmonary exposure of CNTs may lead to nanoparticle accumulation in the deep lung without effective clearance which could interact with local lung cells for a long period of time. Physicochemical similarities of CNTs to asbestos fibers may contribute to their asbestos-like carcinogenic potential after long-term exposure, which has not been well addressed. More studies are needed to identify and predict the carcinogenic potential and mechanisms for promoting their safe use. Our previous study reported a long-term in vitro exposure model for CNT carcinogenicity and showed that 6-month sub-chronic exposure of single-walled carbon nanotubes (SWCNT) causes malignant transformation of human lung epithelial cells. In addition, the transformed cells induced tumor formation in mice and exhibited an apoptosis resistant phenotype, a key characteristic of cancer cells. Although the potential role of p53 in the transformation process was identified, the underlying mechanisms of oncogenesis remain largely undefined. Here, we further examined the gene expression profile by using genome microarrays to profile molecular mechanisms of SWCNT oncogenesis. Based on differentially expressed genes, possible mechanisms of SWCNT-associated apoptosis resistance and oncogenesis were identified, which included activation of pAkt/p53/Bcl-2 signaling axis, increased gene expression of Ras family for cell cycle control, Dsh-mediated Notch 1, and downregulation of apoptotic genes BAX and Noxa. Activated immune responses were among the major changes of biological function. Our findings shed light on potential molecular mechanisms and signaling pathways involved in SWCNT oncogenic potential.
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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
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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.
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Petrov, Anja; Beer, Martin; Blome, Sandra
2014-01-01
Dysregulation of cytokine responses plays a major role in the pathogenesis of severe and life-threatening infectious diseases like septicemia or viral hemorrhagic fevers. In pigs, diseases like African and classical swine fever are known to show exaggerated cytokine releases. To study these responses and their impact on disease severity and outcome in detail, reliable, highly specific and sensitive methods are needed. For cytokine research on the molecular level, real-time RT-PCRs have been proven to be suitable. Yet, the currently available and most commonly used SYBR Green I assays or heterogeneous gel-based RT-PCRs for swine show a significant lack of specificity and sensitivity. The latter is however absolutely essential for an accurate quantification of rare cytokine transcripts as well as for detection of small changes in gene expressions. For this reason, a harmonized TaqMan-based triplex real-time RT-PCR protocol for the quantitative detection of normalized gene expression profiles of seven porcine cytokines was designed and validated within the presented study. Cytokines were chosen to represent different immunological pathways and targets known to be involved in the pathogenesis of the above mentioned porcine diseases, namely interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, tumor necrosis factor (TNF)-α and interferon (IFN)-α. Beta-Actin and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as reference genes for normalization. For absolute quantification a synthetic standard plasmid was constructed comprising all target cytokines and reference genes within a single molecule allowing the generation of positive control RNA. The standard as well as positive RNAs from samples, and additionally more than 400 clinical samples, which were collected from animal trials, were included in the validation process to assess analytical sensitivity and applicability under routine conditions. The resulting assay allows the reliable assessment of gene expression profiles and provides a broad applicability to any kind of immunological research in swine.
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Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu
2018-03-01
The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.
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Vivanti, Alexandre; Soheili, Tayebeh S.; Cuccuini, Wendy; Luce, Sonia; Mandelbrot, Laurent; Lechenadec, Jerome; Cordier, Anne-Gael; Azria, Elie; Soulier, Jean; Cavazzana, Marina; Blanche, Stéphane; André-Schmutz, Isabelle
2015-01-01
Objectives: Zidovudine and tenofovir are the two main nucleos(t)ide analogs used to prevent mother-to-child transmission of HIV. In vitro, both drugs bind to and integrate into human DNA and inhibit telomerase. The objective of the present study was to assess the genotoxic effects of either zidovudine or tenofovir-based combination therapies on cord blood cells in newborns exposed in utero. Design: We compared the aneuploid rate and the gene expression profiles in cord blood samples from newborns exposed either to zidovudine or tenofovir-based combination therapies during pregnancy and from unexposed controls (n = 8, 9, and 8, respectively). Methods: The aneuploidy rate was measured on the cord blood T-cell karyotype. Gene expression profiles of cord blood T cells and hematopoietic stem and progenitor cells were determined with microarrays, analyzed in a gene set enrichment analysis and confirmed by real-time quantitative PCRs. Results: Aneuploidy was more frequent in the zidovudine-exposed group (26.3%) than in the tenofovir-exposed group (14.2%) or in controls (13.3%; P < 0.05 for both). The transcription of genes involved in DNA repair, telomere maintenance, nucleotide metabolism, DNA/RNA synthesis, and the cell cycle was deregulated in samples from both the zidovudine and the tenofovir-exposed groups. Conclusion: Although tenofovir has a lower clastogenic impact than zidovudine, gene expression profiling showed that both drugs alter the transcription of DNA repair and telomere maintenance genes. PMID:25513819
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Vivanti, Alexandre; Soheili, Tayebeh S; Cuccuini, Wendy; Luce, Sonia; Mandelbrot, Laurent; Lechenadec, Jerome; Cordier, Anne-Gael; Azria, Elie; Soulier, Jean; Cavazzana, Marina; Blanche, Stéphane; André-Schmutz, Isabelle
2015-07-17
Zidovudine and tenofovir are the two main nucleos(t)ide analogs used to prevent mother-to-child transmission of HIV. In vitro, both drugs bind to and integrate into human DNA and inhibit telomerase. The objective of the present study was to assess the genotoxic effects of either zidovudine or tenofovir-based combination therapies on cord blood cells in newborns exposed in utero. We compared the aneuploid rate and the gene expression profiles in cord blood samples from newborns exposed either to zidovudine or tenofovir-based combination therapies during pregnancy and from unexposed controls (n = 8, 9, and 8, respectively). The aneuploidy rate was measured on the cord blood T-cell karyotype. Gene expression profiles of cord blood T cells and hematopoietic stem and progenitor cells were determined with microarrays, analyzed in a gene set enrichment analysis and confirmed by real-time quantitative PCRs. Aneuploidy was more frequent in the zidovudine-exposed group (26.3%) than in the tenofovir-exposed group (14.2%) or in controls (13.3%; P < 0.05 for both). The transcription of genes involved in DNA repair, telomere maintenance, nucleotide metabolism, DNA/RNA synthesis, and the cell cycle was deregulated in samples from both the zidovudine and the tenofovir-exposed groups. Although tenofovir has a lower clastogenic impact than zidovudine, gene expression profiling showed that both drugs alter the transcription of DNA repair and telomere maintenance genes.
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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
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Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.
Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong
2017-03-01
The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC in the future. ii) Differentially expressed genes may be involved in the occurrence of GC via a variety of mechanisms. iii) CD44, CXXC5, MYH9, MALAT1 and other genes may have important implications for the occurrence and development of GC through the regulation, interaction, and mutual influence of circRNA-miRNA-mRNA via different mechanisms.
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Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi
2013-01-01
Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.
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Lamberts, Laetitia E; de Groot, Derk Jan A; Bense, Rico D; de Vries, Elisabeth G E; Fehrmann, Rudolf S N
2015-09-29
The membrane bound glycoprotein mesothelin (MSLN) is a highly specific tumor marker, which is currently exploited as target for drugs. There are only limited data available on MSLN expression by human tumors. Therefore we determined overexpression of MSLN across different tumor types with Functional Genomic mRNA (FGM) profiling of a large cancer database. Results were compared with data in articles reporting immunohistochemical (IHC) MSLN tumor expression. FGM profiling is a technique that allows prediction of biologically relevant overexpression of proteins from a robust data set of mRNA microarrays. This technique was used in a database comprising 19,746 tumors to identify for 41 tumor types the percentage of samples with an overexpression of MSLN compared to a normal background. A literature search was performed to compare the FGM profiling data with studies reporting IHC MSLN tumor expression. FGM profiling showed MSLN overexpression in gastrointestinal (12-36%) and gynecological tumors (20-66%), non-small cell lung cancer (21%) and synovial sarcomas (30%). The overexpression found in thyroid cancers (5%) and renal cell cancers (10%) was not yet reported with IHC analyses. We observed that MSLN amplification rate within esophageal cancer depends on the histotype (31% for adenocarcinomas versus 3% for squamous-cell carcinomas). Subset analysis in breast cancer showed MSLN amplification rates of 28% in triple-negative breast cancer (TNBC) and 33% in basal-like breast cancer. Further subtype analysis of TNBCs showed the highest amplification rate (42%) in the basal-like 1 subtype and the lowest amplification rate (9%) in the luminal androgen receptor subtype.
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Face in profile view reduces perceived facial expression intensity: an eye-tracking study.
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.
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Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey
2018-04-01
Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.
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MicroRNA signature of the human developing pancreas.
Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L
2010-09-22
MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas.
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MicroRNA signature of the human developing pancreas
2010-01-01
Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas. PMID:20860821
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Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing.
Jäger, Marten; Ott, Claus-Eric; Grünhagen, Johannes; Hecht, Jochen; Schell, Hanna; Mundlos, Stefan; Duda, Georg N; Robinson, Peter N; Lienau, Jasmin
2011-03-24
The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism.
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Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing
2011-01-01
Background The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Results Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Conclusions Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism. PMID:21435219
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GEMINI: a computationally-efficient search engine for large gene expression datasets.
DeFreitas, Timothy; Saddiki, Hachem; Flaherty, Patrick
2016-02-24
Low-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query - a text-based string - is mismatched with the form of the target - a genomic profile. To improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an [Formula: see text] expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 10(5) samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec. GEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information.
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Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.
Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong
2015-01-01
In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.
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Yang, Cheng-Han; Liu, En-Jung; Chen, Yi-Ling; Ou-Yang, Fan-Yu; Li, Si-Yu
2016-08-02
In our previous study, the feasibility of Rubisco-based engineered E. coli (that contains heterologous phosphoribulokinase (PrkA) and Rubisco) for in situ CO2 recycling during the fermentation of pentoses or hexoses was demonstrated. Nevertheless, it is perplexing to see that only roughly 70 % of the carbon fed to the bacterial culture could be accounted for in the standard metabolic products. This low carbon recovery during fermentation occurred even though CO2 emission was effectively reduced by Rubisco-based engineered pathway. In this study, the heterologous expression of form I Rubisco was found to enhance the accumulation of pyruvate in Escherichia coli MZLF [E. coli BL21(DE3) Δzwf, Δldh, Δfrd]. This may be attributed to the enhanced glycolytic reaction supported by the increased biomass and the ethanol/acetate ratio. Besides, it was found that the transcription of arcA (encodes the redox-dependent transcriptional activators ArcA that positively regulates the transcription of pyruvate formate-lyase) was down-regulated in the presence of Rubisco. The enhanced accumulation of pyruvate also occurs when PrkA is co-expressed with Rubisco in E. coli MZLF. Furthermore, E. coli containing Rubisco-based engineered pathway has a distinct profile of the fermentation products, indicating CO2 was converted into fermentation products. By analyzing the ratio of total C-2 (2-carbon fermentation products) to total C-1 (1-carbon fermentation product) of MZLFB (MZLF containing Rubisco-based engineered pathway), it is estimated that 9 % of carbon is directed into Rubisco-based engineered pathway. Here, we report for the first time the complete profile of fermentation products using E. coli MZLF and its derived strains. It has been shown that the expression of Rubisco alone in MZLF enhances the accumulation of pyruvate. By including the contribution of pyruvate accumulation, the perplexing problem of low carbon recovery during fermentation by E. coli containing Rubisco-based engineered pathway has been solved. 9 % of glucose consumption is directed from glycolysis to Rubisco-based engineered pathway in MZLFB. The principle characteristics of mixotroph MZLFB are the high bacterial growth and the low CO2 emission.
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Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang
2018-06-15
Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.
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Radio Sounding of the Martian and Venusian Ionospheres
NASA Astrophysics Data System (ADS)
Paetzold, M.; Haeusler, B.; Bird, M. K.; Peter, K.; Tellmann, S.; Tyler, G. L.; Withers, P.
2011-12-01
The Mars Express Radio Science Experiment MaRS and the radio science experiment Vera on Venus Express sound the ionospheres of Mars and Venus, respectively, at two frequencies in the microwave band and cover altitudes from the base of the ionosphere at 80 km (100 km at Venus) to the ionopause at altitudes between 300 km and 600 km. In general, both ionospheres consists of a lower layer M1 (V1 at Venus) at about 110 km (115 km), and the main layer M2 (V2) at about 135 km (145 km) altitude, both formed mainly by solar radiation at X-ray and EUV, respectively. The specific derivation and interpretation of the vertical electron density profiles at two radio frequencies from radio sounding is demonstrated in detail. Cases of quiet and disturbed ionospheric electron density profiles and cases of potential misinterpretations are presented. The behavior of the peak densities and peak altitudes of both ionospheres as a function of solar zenith angle and phase of the solar cycle as seen with Mars Express and Venus Express will be compared with past observations, models and conclusions.
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Heterogeneity of proteins expressed by Brazilian Sporothrix schenckii isolates.
Fernandes, Geisa Ferreira; Do Amaral, Cristiane Candida; Sasaki, Alexandre; Godoy, Patrício Martinez; De Camargo, Zoilo Pires
2009-12-01
The profiles of proteins present in the exoantigens of Brazilian Sporothrix schenckii isolates were studied and compared by electrophoresis (SDS-PAGE). Thirteen isolates from five different regions of Brazil (1,000 to 2,000 km apart) and ten from a more limited region (200 to 400 km apart within the state of São Paulo) were cultured in Sabouraud, M199 and minimum (MM) media. Qualitative and quantitative differences in the expression of proteins, which varied according to the medium and the isolate, were observed. Fractions with the same MW but varying in intensity were detected, as well as fractions present in 1 isolate but absent in others. Dendrograms were constructed and isolates grouped based on the fractions obtained, irrespective of the intensity. The results showed that Brazilian S. schenckii isolates express different protein profiles, a feature also present in isolates from a more restricted region. The exoantigens were found to have a maximum of 15 protein fractions, ranging in MW from 19-220 KDaltons depending on the medium used for the cultures. These data show the great heterogeneity of Brazilian S. schenckii protein expression.
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A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
Yu, Ying; Fuscoe, James C.; Zhao, Chen; Guo, Chao; Jia, Meiwen; Qing, Tao; Bannon, Desmond I.; Lancashire, Lee; Bao, Wenjun; Du, Tingting; Luo, Heng; Su, Zhenqiang; Jones, Wendell D.; Moland, Carrie L.; Branham, William S.; Qian, Feng; Ning, Baitang; Li, Yan; Hong, Huixiao; Guo, Lei; Mei, Nan; Shi, Tieliu; Wang, Kevin Y.; Wolfinger, Russell D.; Nikolsky, Yuri; Walker, Stephen J.; Duerksen-Hughes, Penelope; Mason, Christopher E.; Tong, Weida; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Shi, Leming; Wang, Charles
2014-01-01
The rat has been used extensively as a model for evaluating chemical toxicities and for understanding drug mechanisms. However, its transcriptome across multiple organs, or developmental stages, has not yet been reported. Here we show, as part of the SEQC consortium efforts, a comprehensive rat transcriptomic BodyMap created by performing RNA-Seq on 320 samples from 11 organs of both sexes of juvenile, adolescent, adult and aged Fischer 344 rats. We catalogue the expression profiles of 40,064 genes, 65,167 transcripts, 31,909 alternatively spliced transcript variants and 2,367 non-coding genes/non-coding RNAs (ncRNAs) annotated in AceView. We find that organ-enriched, differentially expressed genes reflect the known organ-specific biological activities. A large number of transcripts show organ-specific, age-dependent or sex-specific differential expression patterns. We create a web-based, open-access rat BodyMap database of expression profiles with crosslinks to other widely used databases, anticipating that it will serve as a primary resource for biomedical research using the rat model. PMID:24510058
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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
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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.
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Dense module enumeration in biological networks
NASA Astrophysics Data System (ADS)
Tsuda, Koji; Georgii, Elisabeth
2009-12-01
Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.
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Optimal consistency in microRNA expression analysis using reference-gene-based normalization.
Wang, Xi; Gardiner, Erin J; Cairns, Murray J
2015-05-01
Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.
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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.
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Li, Weiwei; Zhao, Lei; Meng, Fei; Wang, Yunsheng; Tan, Huarong; Yang, Hua; Wei, Chaoling; Wan, Xiaochun; Gao, Liping; Xia, Tao
2013-01-01
Phenolic compounds in tea plant [Camellia sinensis (L.)] play a crucial role in dominating tea flavor and possess a number of key pharmacological benefits on human health. The present research aimed to study the profile of tissue-specific, development-dependent accumulation pattern of phenolic compounds in tea plant. A total of 50 phenolic compounds were identified qualitatively using liquid chromatography in tandem mass spectrometry technology. Of which 29 phenolic compounds were quantified based on their fragmentation behaviors. Most of the phenolic compounds were higher in the younger leaves than that in the stem and root, whereas the total amount of proanthocyanidins were unexpectedly higher in the root. The expression patterns of 63 structural and regulator genes involved in the shikimic acid, phenylpropanoid, and flavonoid pathways were analyzed by quantitative real-time polymerase chain reaction and cluster analysis. Based on the similarity of their expression patterns, the genes were classified into two main groups: C1 and C2; and the genes in group C1 had high relative expression level in the root or low in the bud and leaves. The expression patterns of genes in C2-2-1 and C2-2-2-1 groups were probably responsible for the development-dependent accumulation of phenolic compounds in the leaves. Enzymatic analysis suggested that the accumulation of catechins was influenced simultaneously by catabolism and anabolism. Further research is recommended to know the expression patterns of various genes and the reason for the variation in contents of different compounds in different growth stages and also in different organs. PMID:23646127
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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.
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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...
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Lan, Jiaqi; Rahman, Sheikh Mokhlesur; Gou, Na; Jiang, Tao; Plewa, Micheal J; Alshawabkeh, Akram; Gu, April Z
2018-06-05
Genotoxicity is considered a major concern for drinking water disinfection byproducts (DBPs). Of over 700 DBPs identified to date, only a small number has been assessed with limited information for DBP genotoxicity mechanism(s). In this study, we evaluated genotoxicity of 20 regulated and unregulated DBPs applying a quantitative toxicogenomics approach. We used GFP-fused yeast strains that examine protein expression profiling of 38 proteins indicative of all known DNA damage and repair pathways. The toxicogenomics assay detected genotoxicity potential of these DBPs that is consistent with conventional genotoxicity assays end points. Furthermore, the high-resolution, real-time pathway activation and protein expression profiling, in combination with clustering analysis, revealed molecular level details in the genotoxicity mechanisms among different DBPs and enabled classification of DBPs based on their distinct DNA damage effects and repair mechanisms. Oxidative DNA damage and base alkylation were confirmed to be the main molecular mechanisms of DBP genotoxicity. Initial exploration of QSAR modeling using moleular genotoxicity end points (PELI) suggested that genotoxicity of DBPs in this study was correlated with topological and quantum chemical descriptors. This study presents a toxicogenomics-based assay for fast and efficient mechanistic genotoxicity screening and assessment of a large number of DBPs. The results help to fill in the knowledge gap in the understanding of the molecular mechanisms of DBP genotoxicity.
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Geng, Haijiang; Li, Zhihui; Li, Jiabing; Lu, Tao; Yan, Fangrong
2015-01-01
BACKGROUND Personalized cancer treatments depend on the determination of a patient's genetic status according to known genetic profiles for which targeted treatments exist. Such genetic profiles must be scientifically validated before they is applied to general patient population. Reproducibility of findings that support such genetic profiles is a fundamental challenge in validation studies. The percentage of overlapping genes (POG) criterion and derivative methods produce unstable and misleading results. Furthermore, in a complex disease, comparisons between different tumor subtypes can produce high POG scores that do not capture the consistencies in the functions. RESULTS We focused on the quality rather than the quantity of the overlapping genes. We defined the rank value of each gene according to importance or quality by PageRank on basis of a particular topological structure. Then, we used the p-value of the rank-sum of the overlapping genes (PRSOG) to evaluate the quality of reproducibility. Though the POG scores were low in different studies of the same disease, the PRSOG was statistically significant, which suggests that sets of differentially expressed genes might be highly reproducible. CONCLUSIONS Evaluations of eight datasets from breast cancer, lung cancer and four other disorders indicate that quality-based PRSOG method performs better than a quantity-based method. Our analysis of the components of the sets of overlapping genes supports the utility of the PRSOG method. PMID:26556852
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Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.
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.
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Core Canonical Pathways Involved in Developing Human Glioblastoma Multiforme (GBM).
Ghosh, Somiranjan; Dutta, Sisir; Thorne, Gabriel; Boston, Ava; Barfield, Alexis; Banerjee, Narendra; Walker, Rayshawn; Banerjee, Hirendra Nath
2017-02-01
Glioblastoma multiforme (GBM) is the most common and aggressive type of the primary brain tumors with pathologic hallmarks of necrosis and vascular proliferation. The diagnosis of GBM is currently mostly based on histological examination of brain tumor tissues, after radiological characterization and surgical biopsy. The ability to characterize tumors comprehensively at the molecular level raises the possibility that diagnosis can be made based on molecular profiling with or without histological examination, rather than solely on histological phenotype. The development of novel genomic and proteomic techniques will foster in the identification of such diagnostic and prognostic molecular markers. We analyzed the global differential gene expression of a GBM cell line HTB15 in comparison to normal human Astrocytes, and established a few canonical pathways that are important in determining the molecular mechanisms of cancer using global gene expression microarray, coupled with the Ingenuity Pathway Analysis ( IPA ®). Overall, we revealed a discrete gene expression profile in the experimental model that resembled progression of GBM cancer. The canonical pathway analysis showed the involvement of genes that differentially expressed in such a disease condition that included Inositol pathway, Polo like kinases, nNOS signaling , and Tetrapyrrole biosynthesis . Our findings established that the gene expression pattern of this dreaded brain cancer will probably help the cancer research community by finding out newer therapeutic strategies to combat this dreaded cancer type that leads to the identification of high-risk population in this category, with almost hundred percent mortality rate.
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Pullagurla, Swathi R; Witek, Małgorzata A; Jackson, Joshua M; Lindell, Maria A M; Hupert, Mateusz L; Nesterova, Irina V; Baird, Alison E; Soper, Steven A
2014-04-15
We report the design and performance of a polymer microfluidic device that can affinity select multiple types of biological cells simultaneously with sufficient recovery and purity to allow for the expression profiling of mRNA isolated from these cells. The microfluidic device consisted of four independent selection beds with curvilinear channels that were 25 μm wide and 80 μm deep and were modified with antibodies targeting antigens specifically expressed by two different cell types. Bifurcated and Z-configured device geometries were evaluated for cell selection. As an example of the performance of these devices, CD4+ T-cells and neutrophils were selected from whole blood as these cells are known to express genes found in stroke-related expression profiles that can be used for the diagnosis of this disease. CD4+ T-cells and neutrophils were simultaneously isolated with purities >90% using affinity-based capture in cyclic olefin copolymer (COC) devices with a processing time of ∼3 min. In addition, sufficient quantities of the cells could be recovered from a 50 μL whole blood input to allow for reverse transcription-polymerase chain reaction (RT-PCR) following cell lysis. The expression of genes from isolated T-cells and neutrophils, such as S100A9, TCRB, and FPR1, was evaluated using RT-PCR. The modification and isolation procedures demonstrated here can also be used to analyze other cell types as well where multiple subsets must be interrogated.
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Mian, Omar Y; Khattab, Mohamed H; Hedayati, Mohammad; Coulter, Jonathan; Abubaker-Sharif, Budri; Schwaninger, Julie M; Veeraswamy, Ravi K; Brooks, James D; Hopkins, Lisa; Shinohara, Debika Biswal; Cornblatt, Brian; Nelson, William G; Yegnasubramanian, Srinivasan; DeWeese, Theodore L
2016-02-01
Epigenetic silencing of glutathione S-transferase π (GSTP1) is a hallmark of transformation from normal prostatic epithelium to adenocarcinoma of the prostate. The functional significance of this loss is incompletely understood. The present study explores the effects of restored GSTP1 expression on glutathione levels, accumulation of oxidative DNA damage, and prostate cancer cell survival following oxidative stress induced by protracted, low dose rate ionizing radiation (LDR). GSTP1 protein expression was stably restored in LNCaP prostate cancer cells. The effect of GSTP1 restoration on protracted LDR-induced oxidative DNA damage was measured by GC-MS quantitation of modified bases. Reduced and oxidized glutathione levels were measured in control and GSTP1 expressing populations. Clonogenic survival studies of GSTP1- transfected LNCaP cells after exposure to protracted LDR were performed. Global gene expression profiling and pathway analysis were performed. GSTP1 expressing cells accumulated less oxidized DNA base damage and exhibited decreased survival compared to control LNCaP-Neo cells following oxidative injury induced by protracted LDR. Restoration of GSTP1 expression resulted in changes in modified glutathione levels that correlated with GSTP1 protein levels in response to protracted LDR-induced oxidative stress. Survival differences were not attributable to depletion of cellular glutathione stores. Gene expression profiling and pathway analysis following GSTP1 restoration suggests this protein plays a key role in regulating prostate cancer cell survival. The ubiquitous epigenetic silencing of GSTP1 in prostate cancer results in enhanced survival and accumulation of potentially promutagenic DNA adducts following exposure of cells to protracted oxidative injury suggesting a protective, anti-neoplastic function of GSTP1. The present work provides mechanistic backing to the tumor suppressor function of GSTP1 and its role in prostate carcinogenesis. © 2015 Wiley Periodicals, Inc.
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Mian, Omar Y.; Khattab, Mohamed H.; Hedayati, Mohammad; Coulter, Jonathan; Abubaker-Sharif, Budri; Schwaninger, Julie M.; Veeraswamy, Ravi K.; Brooks, James D.; Hopkins, Lisa; Shinohara, Debika Biswal; Cornblatt, Brian; Nelson, William G.; Yegnasubramanian, Srinivasan; DeWeese, Theodore L.
2016-01-01
BACKGROUND Epigenetic silencing of glutathione S-transferase π (GSTP1) is a hallmark of transformation from normal prostatic epithelium to adenocarcinoma of the prostate. The functional significance of this loss is incompletely understood. The present study explores the effects of restored GSTP1 expression on glutathione levels, accumulation of oxidative DNA damage, and prostate cancer cell survival following oxidative stress induced by protracted, low dose rate ionizing radiation (LDR). METHODS GSTP1 protein expression was stably restored in LNCaP prostate cancer cells. The effect of GSTP1 restoration on protracted LDR-induced oxidative DNA damage was measured by GC-MS quantitation of modified bases. Reduced and oxidized glutathione levels were measured in control and GSTP1 expressing populations. Clonogenic survival studies of GSTP1-transfected LNCaP cells after exposure to protracted LDR were performed. Global gene expression profiling and pathway analysis were performed. RESULTS GSTP1 expressing cells accumulated less oxidized DNA base damage and exhibited decreased survival compared to control LNCaP-Neo cells following oxidative injury induced by protracted LDR. Restoration of GSTP1 expression resulted in changes in modified glutathione levels that correlated with GSTP1 protein levels in response to protracted LDR-induced oxidative stress. Survival differences were not attributable to depletion of cellular glutathione stores. Gene expression profiling and pathway analysis following GSTP1 restoration suggests this protein plays a key role in regulating prostate cancer cell survival. CONCLUSIONS The ubiquitous epigenetic silencing of GSTP1 in prostate cancer results in enhanced survival and accumulation of potentially promutagenic DNA adducts following exposure of cells to protracted oxidative injury suggesting a protective, anti-neoplastic function of GSTP1. The present work provides mechanistic backing to the tumor suppressor function of GSTP1 and its role in prostate carcinogenesis. PMID:26447830
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GEM-TREND: a web tool for gene expression data mining toward relevant network discovery
Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi
2009-01-01
Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865
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GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.
Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi
2009-09-03
DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.
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De Laere, Bram; van Dam, Pieter-Jan; Whitington, Tom; Mayrhofer, Markus; Diaz, Emanuela Henao; Van den Eynden, Gert; Vandebroek, Jean; Del-Favero, Jurgen; Van Laere, Steven; Dirix, Luc; Grönberg, Henrik; Lindberg, Johan
2017-08-01
Expression of the androgen receptor splice variant 7 (AR-V7) is associated with poor response to second-line endocrine therapy in castration-resistant prostate cancer (CRPC). However, a large fraction of nonresponding patients are AR-V7-negative. To investigate if a comprehensive liquid biopsy-based AR profile may improve patient stratification in the context of second-line endocrine therapy. Peripheral blood was collected from patients with CRPC (n=30) before initiation of a new line of systemic therapy. We performed profiling of circulating tumour DNA via low-pass whole-genome sequencing and targeted sequencing of the entire AR gene, including introns. Targeted RNA sequencing was performed on enriched circulating tumour cell fractions to assess the expression levels of seven AR splice variants (ARVs). Somatic AR variations, including copy-number alterations, structural variations, and point mutations, were combined with ARV expression patterns and correlated to clinicopathologic parameters. Collectively, any AR perturbation, including ARV, was detected in 25/30 patients. Surprisingly, intra-AR structural variation was present in 15/30 patients, of whom 14 expressed ARVs. The majority of ARV-positive patients expressed multiple ARVs, with AR-V3 the most abundantly expressed. The presence of any ARV was associated with progression-free survival after second-line endocrine treatment (hazard ratio 4.53, 95% confidence interval 1.424-14.41; p=0.0105). Six out of 17 poor responders were AR-V7-negative, but four carried other AR perturbations. Comprehensive AR profiling, which is feasible using liquid biopsies, is necessary to increase our understanding of the mechanisms underpinning resistance to endocrine treatment. Alterations in the androgen receptor are associated with endocrine treatment outcomes. This study demonstrates that it is possible to identify different types of alterations via simple blood draws. Follow-up studies are needed to determine the effect of such alterations on hormonal therapy. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ren, Xuefeng, E-mail: xuefengr@buffalo.edu; Department of Pharmacology and Toxicology, School of Biomedical Sciences, The State University of New York, Buffalo, NY 14214; Gaile, Daniel P.
Arsenic exposure is postulated to modify microRNA (miRNA) expression, leading to changes of gene expression and toxicities, but studies relating the responses of miRNAs to arsenic exposure are lacking, especially with respect to in vivo studies. We utilized high-throughput sequencing technology and generated miRNA expression profiles of liver tissues from Sprague Dawley (SD) rats exposed to various concentrations of sodium arsenite (0, 0.1, 1, 10 and 100 mg/L) for 60 days. Unsupervised hierarchical clustering analysis of the miRNA expression profiles clustered the SD rats into different groups based on the arsenic exposure status, indicating a highly significant association between arsenicmore » exposure and cluster membership (p-value of 0.0012). Multiple miRNA expressions were altered by arsenic in an exposure concentration-dependent manner. Among the identified arsenic-responsive miRNAs, several are predicted to target Nfe2l2-regulated antioxidant genes, including glutamate–cysteine ligase (GCL) catalytic subunit (GCLC) and modifier subunit (GCLM) which are involved in glutathione (GSH) synthesis. Exposure to low concentrations of arsenic increased mRNA expression for Gclc and Gclm, while high concentrations significantly reduced their expression, which were correlated to changes in hepatic GCL activity and GSH level. Moreover, our data suggested that other mechanisms, e.g., miRNAs, rather than Nfe2l2-signaling pathway, could be involved in the regulation of mRNA expression of Gclc and Gclm post-arsenic exposure in vivo. Together, our findings show that arsenic exposure disrupts the genome-wide expression of miRNAs in vivo, which could lead to the biological consequence, such as an altered balance of antioxidant defense and oxidative stress. - Highlights: • Chronic arsenic exposure induces changes of hepatic miRNA expression profiles. • Hepatic GCL activity and GSH level in rats are altered following arsenic exposure. • Arsenic induced GCL expression change is independent to Nfe2l2-signaling pathway. • Expression of several miRNAs predicted to target GCL changed after arsenic exposure.« less
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oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes
Ho Sui, Shannan J.; Mortimer, James R.; Arenillas, David J.; Brumm, Jochen; Walsh, Christopher J.; Kennedy, Brian P.; Wasserman, Wyeth W.
2005-01-01
Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes. PMID:15933209
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eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.
Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen
2014-01-01
Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.
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eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes
Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen
2014-01-01
Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455
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Functional expression of dental plaque microbiota.
Peterson, Scott N; Meissner, Tobias; Su, Andrew I; Snesrud, Erik; Ong, Ana C; Schork, Nicholas J; Bretz, Walter A
2014-01-01
Dental caries remains a significant public health problem and is considered pandemic worldwide. The prediction of dental caries based on profiling of microbial species involved in disease and equally important, the identification of species conferring dental health has proven more difficult than anticipated due to high interpersonal and geographical variability of dental plaque microbiota. We have used RNA-Seq to perform global gene expression analysis of dental plaque microbiota derived from 19 twin pairs that were either concordant (caries-active or caries-free) or discordant for dental caries. The transcription profiling allowed us to define a functional core microbiota consisting of nearly 60 species. Similarities in gene expression patterns allowed a preliminary assessment of the relative contribution of human genetics, environmental factors and caries phenotype on the microbiota's transcriptome. Correlation analysis of transcription allowed the identification of numerous functional networks, suggesting that inter-personal environmental variables may co-select for groups of genera and species. Analysis of functional role categories allowed the identification of dominant functions expressed by dental plaque biofilm communities, that highlight the biochemical priorities of dental plaque microbes to metabolize diverse sugars and cope with the acid and oxidative stress resulting from sugar fermentation. The wealth of data generated by deep sequencing of expressed transcripts enables a greatly expanded perspective concerning the functional expression of dental plaque microbiota.
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Functional expression of dental plaque microbiota
Peterson, Scott N.; Meissner, Tobias; Su, Andrew I.; Snesrud, Erik; Ong, Ana C.; Schork, Nicholas J.; Bretz, Walter A.
2014-01-01
Dental caries remains a significant public health problem and is considered pandemic worldwide. The prediction of dental caries based on profiling of microbial species involved in disease and equally important, the identification of species conferring dental health has proven more difficult than anticipated due to high interpersonal and geographical variability of dental plaque microbiota. We have used RNA-Seq to perform global gene expression analysis of dental plaque microbiota derived from 19 twin pairs that were either concordant (caries-active or caries-free) or discordant for dental caries. The transcription profiling allowed us to define a functional core microbiota consisting of nearly 60 species. Similarities in gene expression patterns allowed a preliminary assessment of the relative contribution of human genetics, environmental factors and caries phenotype on the microbiota's transcriptome. Correlation analysis of transcription allowed the identification of numerous functional networks, suggesting that inter-personal environmental variables may co-select for groups of genera and species. Analysis of functional role categories allowed the identification of dominant functions expressed by dental plaque biofilm communities, that highlight the biochemical priorities of dental plaque microbes to metabolize diverse sugars and cope with the acid and oxidative stress resulting from sugar fermentation. The wealth of data generated by deep sequencing of expressed transcripts enables a greatly expanded perspective concerning the functional expression of dental plaque microbiota. PMID:25177549
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Awazu, Akinori; Tanabe, Takahiro; Kamitani, Mari; Tezuka, Ayumi; Nagano, Atsushi J
2018-05-29
Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed. For A. thaliana and Saccharomyces cerevisiae, various types of ePDF of gene expression levels were obtained that were classified as Gaussian, power law-like containing a long tail, or intermediate. These ePDF profiles were well fitted with a Gauss-power mixing distribution function derived from a simple model of a stochastic transcriptional network containing a feedback loop. The fitting function suggested that gene expression levels with long-tailed ePDFs would be strongly influenced by feedback regulation. Furthermore, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian-like ePDF while those of genes encoding nucleic acid-binding proteins and transcription factors exhibit long-tailed ePDF.
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Meissner, Tobias; Seckinger, Anja; Rème, Thierry; Hielscher, Thomas; Möhler, Thomas; Neben, Kai; Goldschmidt, Hartmut; Klein, Bernard; Hose, Dirk
2011-12-01
Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification. The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore). The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively. GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities. ©2011 AACR.
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Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.
Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S
2012-01-01
RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.
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Multiplex cDNA quantification method that facilitates the standardization of gene expression data
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
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Functional proteomics outlines the complexity of breast cancer molecular subtypes.
Gámez-Pozo, Angelo; Trilla-Fuertes, Lucía; Berges-Soria, Julia; Selevsek, Nathalie; López-Vacas, Rocío; Díaz-Almirón, Mariana; Nanni, Paolo; Arevalillo, Jorge M; Navarro, Hilario; Grossmann, Jonas; Gayá Moreno, Francisco; Gómez Rioja, Rubén; Prado-Vázquez, Guillermo; Zapater-Moros, Andrea; Main, Paloma; Feliú, Jaime; Martínez Del Prado, Purificación; Zamora, Pilar; Ciruelos, Eva; Espinosa, Enrique; Fresno Vara, Juan Ángel
2017-08-30
Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.
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Odierna, Donna H; Afable-Munsuz, Aimee; Ikediobi, Ogechi; Beattie, Mary; Knight, Sara; Ko, Michelle; Wilson, Adrienne; Ponce, Ninez A
2011-11-01
New prognostic tests, such as gene-expression profiling (GEP) of breast tumors, are expected to prolong survival and improve the quality of life for many breast cancer patients. In this article, we argue that GEP has not been adequately validated in minority populations, and that both biological and social factors might affect the broad utility of these tests in diverse populations. We suggest that the widespread use of this technology could potentially lead to suboptimal treatment for black women, resulting in a further increase in black-white patient disparities in treatment response, morbidity and mortality rates. We argue for the need to build a large and diverse evidence base for GEP and other emerging technologies in personalized medicine.
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Biocompatibility of a bicarbonate-buffered amino-acid-based solution for peritoneal dialysis.
Bender, Thorsten O; Witowski, Janusz; Aufricht, Christoph; Endemann, Michaela; Frei, Ulrich; Passlick-Deetjen, Jutta; Jörres, Achim
2008-09-01
Amino-acid-based peritoneal dialysis (PD) fluids have been developed to improve the nutritional status of PD patients. As they may potentially exacerbate acidosis, an amino-acid-containing solution buffered with bicarbonate (Aminobic) has been proposed to effectively maintain acid-base balance. The aim of this study was to evaluate the mesothelial biocompatibility profile of this solution in comparison with a conventional low-glucose-based fluid. Omentum-derived human peritoneal mesothelial cells (HPMC) were preexposed to test PD solutions for up to 120 min, then allowed to recover in control medium for 24 h, and assessed for heat-shock response, viability, and basal and stimulated cytokine [interleukin (IL)-6] and prostaglandin (PGE(2)) release. Acute exposure of HPMC to conventional low-glucose-based PD solution resulted in a time-dependent increase in heat-shock protein (HSP-72) expression, impaired viability, and reduced ability to release IL-6 in response to stimulation. In contrast, in cells treated with Aminobic, the expression of HSP-72 was significantly lower, and viability and cytokine-producing capacity were preserved and did not differ from those seen in control cells. In addition, exposure to Aminobic increased basal release of IL-6 and PGE(2). These data point to a favorable biocompatibility profile of the amino-acid-based bicarbonate-buffered PD solution toward HPMC.
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Variation-preserving normalization unveils blind spots in gene expression profiling
Roca, Carlos P.; Gomes, Susana I. L.; Amorim, Mónica J. B.; Scott-Fordsmand, Janeck J.
2017-01-01
RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression. PMID:28276435
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Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro
2007-01-01
Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074
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Homuth, Georg; Wahl, Simone; Müller, Christian; Schurmann, Claudia; Mäder, Ulrike; Blankenberg, Stefan; Carstensen, Maren; Dörr, Marcus; Endlich, Karlhans; Englbrecht, Christian; Felix, Stephan B; Gieger, Christian; Grallert, Harald; Herder, Christian; Illig, Thomas; Kruppa, Jochen; Marzi, Carola S; Mayerle, Julia; Meitinger, Thomas; Metspalu, Andres; Nauck, Matthias; Peters, Annette; Rathmann, Wolfgang; Reinmaa, Eva; Rettig, Rainer; Roden, Michael; Schillert, Arne; Schramm, Katharina; Steil, Leif; Strauch, Konstantin; Teumer, Alexander; Völzke, Henry; Wallaschofski, Henri; Wild, Philipp S; Ziegler, Andreas; Völker, Uwe; Prokisch, Holger; Zeller, Tanja
2015-10-15
Obesity, defined as pathologically increased body mass index (BMI), is strongly related to an increased risk for numerous common cardiovascular and metabolic diseases. It is particularly associated with insulin resistance, hyperglycemia, and systemic oxidative stress and represents the most important risk factor for type 2 diabetes (T2D). However, the pathophysiological mechanisms underlying these associations are still not completely understood. Therefore, in order to identify potentially disease-relevant BMI-associated gene expression signatures, a transcriptome-wide association study (TWAS) on BMI was performed. Whole-blood mRNA levels determined by array-based transcriptional profiling were correlated with BMI in two large independent population-based cohort studies (KORA F4 and SHIP-TREND) comprising a total of 1977 individuals. Extensive alterations of the whole-blood transcriptome were associated with BMI: More than 3500 transcripts exhibited significant positive or negative BMI-correlation. Three major whole-blood gene expression signatures associated with increased BMI were identified. The three signatures suggested: i) a ratio shift from mature erythrocytes towards reticulocytes, ii) decreased expression of several genes essentially involved in the transmission and amplification of the insulin signal, and iii) reduced expression of several key genes involved in the defence against reactive oxygen species (ROS). Whereas the first signature confirms published results, the other two provide possible mechanistic explanations for well-known epidemiological findings under conditions of increased BMI, namely attenuated insulin signaling and increased oxidative stress. The putatively causative BMI-dependent down-regulation of the expression of numerous genes on the mRNA level represents a novel finding. BMI-associated negative transcriptional regulation of insulin signaling and oxidative stress management provide new insights into the pathogenesis of metabolic syndrome and T2D.
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Zhao, Hongjuan; Hastie, Trevor; Whitfield, Michael L; Børresen-Dale, Anne-Lise; Jeffrey, Stefanie S
2002-01-01
Background T7 based linear amplification of RNA is used to obtain sufficient antisense RNA for microarray expression profiling. We optimized and systematically evaluated the fidelity and reproducibility of different amplification protocols using total RNA obtained from primary human breast carcinomas and high-density cDNA microarrays. Results Using an optimized protocol, the average correlation coefficient of gene expression of 11,123 cDNA clones between amplified and unamplified samples is 0.82 (0.85 when a virtual array was created using repeatedly amplified samples to minimize experimental variation). Less than 4% of genes show changes in expression level by 2-fold or greater after amplification compared to unamplified samples. Most changes due to amplification are not systematic both within one tumor sample and between different tumors. Amplification appears to dampen the variation of gene expression for some genes when compared to unamplified poly(A)+ RNA. The reproducibility between repeatedly amplified samples is 0.97 when performed on the same day, but drops to 0.90 when performed weeks apart. The fidelity and reproducibility of amplification is not affected by decreasing the amount of input total RNA in the 0.3–3 micrograms range. Adding template-switching primer, DNA ligase, or column purification of double-stranded cDNA does not improve the fidelity of amplification. The correlation coefficient between amplified and unamplified samples is higher when total RNA is used as template for both experimental and reference RNA amplification. Conclusion T7 based linear amplification reproducibly generates amplified RNA that closely approximates original sample for gene expression profiling using cDNA microarrays. PMID:12445333
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Diffraction peak profiles of surface relaxed spherical nanocrystals
NASA Astrophysics Data System (ADS)
Perez-Demydenko, C.; Scardi, P.
2017-09-01
A model is proposed for surface relaxation of spherical nanocrystals. Besides reproducing the primary effect of changing the average unit cell parameter, the model accounts for the inhomogeneous atomic displacement caused by surface relaxation and its effect on the diffraction line profiles. Based on three parameters with clear physical meanings - extension of the sub-coordination effect, maximum radial displacement due to sub-coordination, and effective hydrostatic pressure - the model also considers elastic anisotropy and provides parametric expressions of the diffraction line profiles directly applicable in data analysis. The model was tested on spherical nanocrystals of several fcc metals, matching atomic positions with those provided by Molecular Dynamics (MD) simulations based on embedded atom potentials. Agreement was also verified between powder diffraction patterns generated by the Debye scattering equation, using atomic positions from MD and the proposed model.
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Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W
2012-09-10
Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.
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Kim, Soung Min; Jeong, Dasul; Kim, Min Keun; Lee, Sang Shin; Lee, Suk Keun
2017-08-08
Oral squamous cell carcinoma (OSCC) is one of the most dangerous cancers in the body, producing serious complications with individual behaviors. Many different pathogenetic factors are involved in the carcinogenesis of OSCC. Cancer cells derived from oral keratinocytes can produce different carcinogenic signaling pathways through differences in protein expression, but their protein expression profiles cannot be easily explored with ordinary detection methods. The present study compared the protein expression profiles between two different types of OSCCs, which were analyzed through immunoprecipitation high-performance liquid chromatography (IP-HPLC). Two types of squamous cell carcinoma (SCC) occurred in a mandibular (SCC-1) and maxillary gingiva (SCC-2), but their clinical features and progression were quite different from each other. SCC-1 showed a large gingival ulceration with severe halitosis and extensive bony destruction, while SCC-2 showed a relatively small papillary gingival swelling but rapidly grew to form a large submucosal mass, followed by early cervical lymph node metastasis. In the histological observation, SCC-1 was relatively well differentiated with a severe inflammatory reaction, while SCC-2 showed severely infiltrative growth of each cancer islets accompanied with a mild inflammatory reaction. IP-HPLC analysis revealed contrary protein expression profiles analyzed by 72 different oncogenic proteins. SCC-1 showed more cellular apoptosis and invasive growth than SCC-2 through increased expression of caspases, MMPs, p53 signaling, FAS signaling, TGF-β1 signaling, and angiogenesis factors, while SCC-2 showed more cellular growth and survival than SCC-1 through the increased expression of proliferating factors, RAS signaling, eIF5A signaling, WNT signaling, and survivin. The increased trends of cellular apoptosis and invasiveness in the protein expression profiles of SCC-1 were implicative of its extensive gingival ulceration and bony destruction, while the increased trends of cellular proliferation and survival in the protein profile of SCC-2 were implicative of its rapid growing tumor mass and early lymph node metastasis. These analyses of the essential oncogenic protein expression profiles in OSCC provide important information for genetic counseling or customized gene therapy in cancer treatment. Therefore, protein expression profile analysis through IP-HPLC is helpful not only for the molecular genetic diagnosis of cancer but also in identifying target molecules for customized gene therapy in near future.
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Santuario-Facio, Sandra K; Cardona-Huerta, Servando; Perez-Paramo, Yadira X; Trevino, Victor; Hernandez-Cabrera, Francisco; Rojas-Martinez, Augusto; Uscanga-Perales, Grecia; Martinez-Rodriguez, Jorge L; Martinez-Jacobo, Lizeth; Padilla-Rivas, Gerardo; Muñoz-Maldonado, Gerardo; Gonzalez-Guerrero, Juan Francisco; Valero-Gomez, Javier; Vazquez-Guerrero, Ana L; Martinez-Rodriguez, Herminia G; Barboza-Quintana, Alvaro; Barboza-Quintana, Oralia; Garza-Guajardo, Raquel; Ortiz-Lopez, Rocio
2017-01-01
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer tumors. Comparisons between TNBC and non–triple-negative breast cancer (nTNBC) may help to differentiate key components involved in TNBC neoplasms. The purpose of the study was to analyze the expression profile of TNBC versus nTNBC tumors in a homogeneous population from northeastern Mexico. A prospective study of 50 patients (25 TNBC and 25 nTNBC) was conducted. Clinic parameters were equally distributed for TNBC and nTNBC: age at diagnosis (51 versus 47 years, p = 0.1), glucose level (107 mg/dl versus 104 mg/dl, p = 0.64), and body mass index (28 versus 29, p = 0.14). Core biopsies were collected for histopathological diagnosis and gene expression analysis. Total RNA was isolated and expression profiling was performed. Forty genes showed differential expression pattern in TNBC tumors. Among these, nine overexpressed genes (PRKX/PRKY, UGT8, HMGA1, LPIN1, HAPLN3, FAM171A1, BCL141A, FOXC1, and ANKRD11), and one underexpressed gene (ANX9) are involved in general metabolism. Based on this biochemical peculiarity and the overexpression of BCL11A and FOXC1 (involved in tumor growth and metastasis, respectively), we validated by quantitative polymerase chain reaction the expression profiles of seven genes out of the signature. In this report, a new gene signature for TNBC is proposed. To our knowledge, this is the first TNBC signature that describes genes involved in general metabolism. The findings may be pertinent for Mexican patients and require evaluation in other ethnic groups and populations. PMID:28474731
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Wang, Yumei; Yin, Xiaoling; Yang, Fang
2018-02-01
Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.
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Zivicova, Veronika; Gal, Peter; Mifkova, Alzbeta; Novak, Stepan; Kaltner, Herbert; Kolar, Michal; Strnad, Hynek; Sachova, Jana; Hradilova, Miluse; Chovanec, Martin; Gabius, Hans-Joachim; Smetana, Karel; Fik, Zdenek
2018-03-01
Having previously initiated genome-wide expression profiling in head and neck squamous cell carcinoma (HNSCC) for regions of the tumor, the margin of surgical resecate (MSR) and normal mucosa (NM), we here proceed with respective analysis of cases after stratification according to the expression status of tenascin (Ten). Tissue specimens of each anatomical site were analyzed by immunofluorescent detection of Ten, fibronectin (Fn) and galectin-1 (Gal-1) as well as by microarrays. Histopathological examination demonstrated that Ten + Fn + Gal-1 + co-expression occurs more frequently in samples of HNSCC (55%) than in NM (9%; p<0.01). Contrary, the Ten - Fn + Gal-1 - (45%) and Ten - Fn - Gal-1 - (39%) status occurred with significantly (p<0.01) higher frequency than in HNSCC (3% and 4%, respectively). In MSRs, different immunophenotypes were distributed rather equally (Ten + Fn + Gal-1 + =24%; Ten - Fn + Gal-1 - =36%; Ten - Fn - Gal-1 - =33%), differing to the results in tumors (p<0.05). Absence/presence of Ten was used for stratification of patients into cohorts without a difference in prognosis, to comparatively examine gene-activity signatures. Microarray analysis revealed i) expression of several tumor progression-associated genes in Ten + HNSCC tumors and ii) a strong up-regulation of gene expression assigned to lipid metabolism in MSRs of Ten - tumors, while NM profiles remained similar. The presented data reveal marked and specific changes in tumors and MSR specimens of HNSCC without a separation based on prognosis. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
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Neuronal DNA Methylation Profiling of Blast-Related Traumatic Brain Injury.
Haghighi, Fatemeh; Ge, Yongchao; Chen, Sean; Xin, Yurong; Umali, Michelle U; De Gasperi, Rita; Gama Sosa, Miguel A; Ahlers, Stephen T; Elder, Gregory A
2015-08-15
Long-term molecular changes in the brain resulting from blast exposure may be mediated by epigenetic changes, such as deoxyribonucleic acid (DNA) methylation, that regulate gene expression. Aberrant regulation of gene expression is associated with behavioral abnormalities, where DNA methylation bridges environmental signals to sustained changes in gene expression. We assessed DNA methylation changes in the brains of rats exposed to three 74.5 kPa blast overpressure events, conditions that have been associated with long-term anxiogenic manifestations weeks or months following the initial exposures. Rat frontal cortex eight months post-exposure was used for cell sorting of whole brain tissue into neurons and glia. We interrogated DNA methylation profiles in these cells using Expanded Reduced Representation Bisulfite Sequencing. We obtained data for millions of cytosines, showing distinct methylation profiles for neurons and glia and an increase in global methylation in neuronal versus glial cells (p<10(-7)). We detected DNA methylation perturbations in blast overpressure-exposed animals, compared with sham blast controls, within 458 and 379 genes in neurons and glia, respectively. Differentially methylated neuronal genes showed enrichment in cell death and survival and nervous system development and function, including genes involved in transforming growth factor β and nitric oxide signaling. Functional validation via gene expression analysis of 30 differentially methylated neuronal and glial genes showed a 1.2 fold change in gene expression of the serotonin N-acetyltransferase gene (Aanat) in blast animals (p<0.05). These data provide the first genome-based evidence for changes in DNA methylation induced in response to multiple blast overpressure exposures. In particular, increased methylation and decreased gene expression were observed in the Aanat gene, which is involved in converting serotonin to the circadian hormone melatonin and is implicated in sleep disturbance and depression associated with traumatic brain injury.
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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.
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Behçet's: A Disease or a Syndrome? Answer from an Expression Profiling Study
Oğuz, Ali Kemal; Yılmaz, Seda Taşır; Oygür, Çağdaş Şahap; Çandar, Tuba; Sayın, Irmak; Kılıçoğlu, Sibel Serin; Ergün, İhsan; Ateş, Aşkın; Özdağ, Hilal; Akar, Nejat
2016-01-01
Behçet’s disease (BD) is a chronic, relapsing, multisystemic inflammatory disorder with unanswered questions regarding its etiology/pathogenesis and classification. Distinct manifestation based subsets, pronounced geographical variations in expression, and discrepant immunological abnormalities raised the question whether Behçet’s is “a disease or a syndrome”. To answer the preceding question we aimed to display and compare the molecular mechanisms underlying distinct subsets of BD. For this purpose, the expression data of the gene expression profiling and association study on BD by Xavier et al (2013) was retrieved from GEO database and reanalysed by gene expression data analysis/visualization and bioinformatics enrichment tools. There were 15 BD patients (B) and 14 controls (C). Three subsets of BD patients were generated: MB (isolated mucocutaneous manifestations, n = 7), OB (ocular involvement, n = 4), and VB (large vein thrombosis, n = 4). Class comparison analyses yielded the following numbers of differentially expressed genes (DEGs); B vs C: 4, MB vs C: 5, OB vs C: 151, VB vs C: 274, MB vs OB: 215, MB vs VB: 760, OB vs VB: 984. Venn diagram analysis showed that there were no common DEGs in the intersection “MB vs C” ∩ “OB vs C” ∩ “VB vs C”. Cluster analyses successfully clustered distinct expressions of BD. During gene ontology term enrichment analyses, categories with relevance to IL-8 production (MB vs C) and immune response to microorganisms (OB vs C) were differentially enriched. Distinct subsets of BD display distinct expression profiles and different disease associated pathways. Based on these clear discrepancies, the designation as “Behçet’s syndrome” (BS) should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS subsets. Four gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis. PMID:26890122
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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.
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Integrative functional genomics of salt acclimatization in the model legume Lotus japonicus.
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.
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Wei, Dahai; Zhang, Xiaobo
2010-01-01
The virus-host interaction is essential to understanding the role that viruses play in ecological and geochemical processes in deep-sea vent ecosystems. Virus-induced changes in cellular gene expression and host physiology have been studied extensively. However, the molecular mechanism of interaction between a bacteriophage and its host at high temperature remains poorly understood. In the present study, the virus-induced gene expression profile of Geobacillus sp. E263, a thermophile isolated from a deep-sea hydrothermal ecosystem, was characterized. Based on proteomic analysis and random arbitrarily primed PCR (RAP-PCR) of Geobacillus sp. E263 cultured under non-bacteriophage GVE2 infection and GVE2 infection conditions, there were two types of protein/gene profiles in response to GVE2 infection. Twenty differentially expressed genes and proteins were revealed that could be grouped into 3 different categories based on cellular function, suggesting a coordinated response to infection. These differentially expressed genes and proteins were further confirmed by Northern blot analysis. To characterize the host proteins in response to virus infection, aspartate aminotransferase (AST) was inactivated to construct the AST mutant of Geobacillus sp. E263. The results showed that the AST protein was essential in virus infection. Thus, transcriptional and proteomic analyses and functional analysis revealed previously unknown host responses to deep-sea thermophilic virus infection. PMID:20015994
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Schwaenen, Carsten; Viardot, Andreas; Berger, Hilmar; Barth, Thomas F E; Bentink, Stefan; Döhner, Hartmut; Enz, Martina; Feller, Alfred C; Hansmann, Martin-Leo; Hummel, Michael; Kestler, Hans A; Klapper, Wolfram; Kreuz, Markus; Lenze, Dido; Loeffler, Markus; Möller, Peter; Müller-Hermelink, Hans-Konrad; Ott, German; Rosolowski, Maciej; Rosenwald, Andreas; Ruf, Sandra; Siebert, Reiner; Spang, Rainer; Stein, Harald; Truemper, Lorenz; Lichter, Peter; Bentz, Martin; Wessendorf, Swen
2009-01-01
Follicular lymphoma (FL) is characterized by a large number of chromosomal aberrations. However, their exact genomic extension and involved target genes remain to be determined. For this purpose, we used array-based intermediate-high resolution genomic profiling in combination with Affymetrix gene expression analysis. Tumor specimens from 128 FL patients were analyzed for the presence of genomic aberrations and the results were correlated to clinical data sets and mRNA expression levels. In 114 (89%) of the 128 analyzed cases, a total of 688 genomic aberrations (384 gains/amplifications and 304 losses) were detected. Frequent genomic aberrations were: -1p36 (18%), +2p15 (24%), -3q (14%), -6q (25%), +7p (19%), +7q (23%), +8q (14%), -9p (16%), -11q (15%), +12q (20%), -13q (11%), -17p (16%), +18p (18%), and +18q (28%). Critical segments of these imbalances were delineated to genomic fragments with a minimum size down to 0.2 Mb. By comparison of these with mRNA gene expression data, putative candidate genes were identified. Moreover, we found that deletions affecting the tumor suppressor gene CDKN2A/B on 9p21 were detected in nontransformed FL grade I-II. For this aberration as well as for -6q25 and -6q26, an association with inferior survival was observed.
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NASA Astrophysics Data System (ADS)
Bai, Man; Sun, Limin; Zhao, Jia; Xiang, Lujie; Cheng, Xiaoyin; Li, Jiarong; Jia, Chao; Jiang, Huaizhi
2017-10-01
Testis development and spermatogenesis are vital factors that influence male animal fertility. In order to identify spermatogenesis-related genes and further provide a theory basis for finding biomarkers related to male sheep fertility, 2-, 6-, and 12-month-old Small Tail Han Sheep testes were selected to investigate the dynamic changes of sheep testis development. Hematoxylin-eosin routine staining and RNA-Seq technique were used to perform histological and transcriptome analysis for these testes. The results showed that 630, 102, and 322 differentially expressed genes (DEGs) were identified in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes, respectively. GO and KEGG analysis showed the following: DEGs in 2- vs 6-month-old testes were mainly related to the GO terms of sexual maturation and the pathways of multiple metabolism and biosynthesis; in 6- vs 12-month-old testes, most of the GO terms that DEGs involved in were related to metabolism and translation processes; the most significantly enriched pathway is the ribosome pathway. The union of DEGs in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes was categorized into eight profiles by series cluster. Subsequently, the eight profiles were classified into four model profiles and four co-expression networks were constructed based on the DEGs in these model profiles. Finally, 29 key regulatory genes related to spermatogenesis were identified in the four co-expression networks. The expression of 13 DEGs (CA3, APOH, MYOC, CATSPER4, SYT6, SERPINA10, DAZL, ADIPOR2, RAB13, CEP41, SPAG4, ODF1, and FRG1) was validated by RT-PCR.
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21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.
Code of Federal Regulations, 2010 CFR
2010-04-01
... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...
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21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.
Code of Federal Regulations, 2012 CFR
2012-04-01
... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...
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21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.
Code of Federal Regulations, 2011 CFR
2011-04-01
... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...
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21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.
Code of Federal Regulations, 2013 CFR
2013-04-01
... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...
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Abruzzi, Katharine C; Zadina, Abigail; Luo, Weifei; Wiyanto, Evelyn; Rahman, Reazur; Guo, Fang; Shafer, Orie; Rosbash, Michael
2017-02-01
Locomotor activity rhythms are controlled by a network of ~150 circadian neurons within the adult Drosophila brain. They are subdivided based on their anatomical locations and properties. We profiled transcripts "around the clock" from three key groups of circadian neurons with different functions. We also profiled a non-circadian outgroup, dopaminergic (TH) neurons. They have cycling transcripts but fewer than clock neurons as well as low expression and poor cycling of clock gene transcripts. This suggests that TH neurons do not have a canonical circadian clock and that their gene expression cycling is driven by brain systemic cues. The three circadian groups are surprisingly diverse in their cycling transcripts and overall gene expression patterns, which include known and putative novel neuropeptides. Even the overall phase distributions of cycling transcripts are distinct, indicating that different regulatory principles govern transcript oscillations. This surprising cell-type diversity parallels the functional heterogeneity of the different neurons.
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A simple approach for human recombinant apolipoprotein E4 expression and purification.
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.
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Transcriptome and Gene Expression Analysis of the Rice Leaf Folder, Cnaphalocrosis medinalis
Li, Shang-Wei; Yang, Hong; Liu, Yue-Feng; Liao, Qi-Rong; Du, Juan; Jin, Dao-Chao
2012-01-01
Background The rice leaf folder (RLF), Cnaphalocrocis medinalis (Guenee) (Lepidoptera: Pyralidae), is one of the most destructive pests affecting rice in Asia. Although several studies have been performed on the ecological and physiological aspects of this species, the molecular mechanisms underlying its developmental regulation, behavior, and insecticide resistance remain largely unknown. Presently, there is a lack of genomic information for RLF; therefore, studies aimed at profiling the RLF transcriptome expression would provide a better understanding of its biological function at the molecular level. Principal Findings De novo assembly of the RLF transcriptome was performed via the short read sequencing technology (Illumina). In a single run, we produced more than 23 million sequencing reads that were assembled into 44,941 unigenes (mean size = 474 bp) by Trinity. Through a similarity search, 25,281 (56.82%) unigenes matched known proteins in the NCBI Nr protein database. The transcriptome sequences were annotated with gene ontology (GO), cluster of orthologous groups of proteins (COG), and KEGG orthology (KO). Additionally, we profiled gene expression during RLF development using a tag-based digital gene expression (DGE) system. Five DGE libraries were constructed, and variations in gene expression were compared between collected samples: eggs vs. 3rd instar larvae, 3rd instar larvae vs. pupae, pupae vs. adults. The results demonstrated that thousands of genes were significantly differentially expressed during various developmental stages. A number of the differentially expressed genes were confirmed by quantitative real-time PCR (qRT-PCR). Conclusions The RLF transcriptome and DGE data provide a comprehensive and global gene expression profile that would further promote our understanding of the molecular mechanisms underlying various biological characteristics, including development, elevated fecundity, flight, sex differentiation, olfactory behavior, and insecticide resistance in RLF. Therefore, these findings could help elucidate the intrinsic factors involved in the RLF-mediated destruction of rice and offer sustainable insect pest management. PMID:23185238
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Wichmann, Gunnar; Rosolowski, Maciej; Krohn, Knut; Kreuz, Markus; Boehm, Andreas; Reiche, Anett; Scharrer, Ulrike; Halama, Dirk; Bertolini, Julia; Bauer, Ulrike; Holzinger, Dana; Pawlita, Michael; Hess, Jochen; Engel, Christoph; Hasenclever, Dirk; Scholz, Markus; Ahnert, Peter; Kirsten, Holger; Hemprich, Alexander; Wittekind, Christian; Herbarth, Olf; Horn, Friedemann; Dietz, Andreas; Loeffler, Markus
2015-12-15
Stratification of head and neck squamous cell carcinomas (HNSCC) based on HPV16 DNA and RNA status, gene expression patterns, and mutated candidate genes may facilitate patient treatment decision. We characterize head and neck squamous cell carcinomas (HNSCC) with different HPV16 DNA and RNA (E6*I) status from 290 consecutively recruited patients by gene expression profiling and targeted sequencing of 50 genes. We show that tumors with transcriptionally inactive HPV16 (DNA+ RNA-) are similar to HPV-negative (DNA-) tumors regarding gene expression and frequency of TP53 mutations (47%, 8/17 and 43%, 72/167, respectively). We also find that an immune response-related gene expression cluster is associated with lymph node metastasis, independent of HPV16 status and that disruptive TP53 mutations are associated with lymph node metastasis in HPV16 DNA- tumors. We validate each of these associations in another large data set. Four gene expression clusters which we identify differ moderately but significantly in overall survival. Our findings underscore the importance of measuring the HPV16 RNA (E6*I) and TP53-mutation status for patient stratification and identify associations of an immune response-related gene expression cluster and TP53 mutations with lymph node metastasis in HNSCC. © 2015 UICC.
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Nakatani, Yuki; Iwamitsu, Yumi; Kuranami, Masaru; Okazaki, Shigemi; Shikanai, Hiroe; Yamamoto, Kenji; Watanabe, Masahiko; Miyaoka, Hitoshi
2014-09-01
The purpose of this study was to examine the relationship between emotional suppression and psychological distress in breast cancer patients after surgery. We examined this relationship using questionnaires at the first visit to the breast cancer outpatient clinic at our hospital and after surgery, as well as interviews after surgery. A total of 31 breast cancer patients were asked to complete the Courtauld Emotional Control Scale and the Profile of Mood States at their first visit to the outpatient clinic. Patients were also asked to complete the Profile of Mood States between 1 and 6 months after surgery. Trained clinical psychologists conducted the interviews, asking patients to speak freely about their current anxieties, worries and thoughts. Based on the median Courtauld Emotional Control Scale score of 42 points, participants were divided into emotional suppression and emotional expression groups. The Total Mood Disturbance score, as well as each of the subscale (except vigor) scores of the Profile of Mood States, were significantly higher in the emotional suppression group than the emotional expression group. The emotional suppression group expressed significantly more negative emotions and fewer positive emotions than the emotional expression group. Patients with emotional suppression felt and expressed more psychological distress after surgery. This finding highlights the need for medical staff to comprehend the psychological traits of breast cancer patients, including emotional suppression, in the early stages of breast cancer in order to provide adequate psychological support. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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2014-01-01
Background Polycomb group proteins form multicomponent complexes that are important for establishing lineage-specific patterns of gene expression. Mammalian cells encode multiple permutations of the prototypic Polycomb repressive complex 1 (PRC1) with little evidence for functional specialization. An aim of this study is to determine whether the multiple orthologs that are co-expressed in human fibroblasts act on different target genes and whether their genomic location changes during cellular senescence. Results Deep sequencing of chromatin immunoprecipitated with antibodies against CBX6, CBX7, CBX8, RING1 and RING2 reveals that the orthologs co-localize at multiple sites. PCR-based validation at representative loci suggests that a further six PRC1 proteins have similar binding patterns. Importantly, sequential chromatin immunoprecipitation with antibodies against different orthologs implies that multiple variants of PRC1 associate with the same DNA. At many loci, the binding profiles have a distinctive architecture that is preserved in two different types of fibroblast. Conversely, there are several hundred loci at which PRC1 binding is cell type-specific and, contrary to expectations, the presence of PRC1 does not necessarily equate with transcriptional silencing. Interestingly, the PRC1 binding profiles are preserved in senescent cells despite changes in gene expression. Conclusions The multiple permutations of PRC1 in human fibroblasts congregate at common rather than specific sites in the genome and with overlapping but distinctive binding profiles in different fibroblasts. The data imply that the effects of PRC1 complexes on gene expression are more subtle than simply repressing the loci at which they bind. PMID:24485159
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Gene expression profiling of mesenteric lymph nodes from sheep with natural scrapie
2014-01-01
Background Prion diseases are characterized by the accumulation of the pathogenic PrPSc protein, mainly in the brain and the lymphoreticular system. Although prions multiply/accumulate in the lymph nodes without any detectable pathology, transcriptional changes in this tissue may reflect biological processes that contribute to the molecular pathogenesis of prion diseases. Little is known about the molecular processes that occur in the lymphoreticular system in early and late stages of prion disease. We performed a microarray-based study to identify genes that are differentially expressed at different disease stages in the mesenteric lymph node of sheep naturally infected with scrapie. Oligo DNA microarrays were used to identify gene-expression profiles in the early/middle (preclinical) and late (clinical) stages of the disease. Results In the clinical stage of the disease, we detected 105 genes that were differentially expressed (≥2-fold change in expression). Of these, 43 were upregulated and 62 downregulated as compared with age-matched negative controls. Fewer genes (50) were differentially expressed in the preclinical stage of the disease. Gene Ontology enrichment analysis revealed that the differentially expressed genes were largely associated with the following terms: glycoprotein, extracellular region, disulfide bond, cell cycle and extracellular matrix. Moreover, some of the annotated genes could be grouped into 3 specific signaling pathways: focal adhesion, PPAR signaling and ECM-receptor interaction. We discuss the relationship between the observed gene expression profiles and PrPSc deposition and the potential involvement in the pathogenesis of scrapie of 7 specific differentially expressed genes whose expression levels were confirmed by real time-PCR. Conclusions The present findings identify new genes that may be involved in the pathogenesis of natural scrapie infection in the lymphoreticular system, and confirm previous reports describing scrapie-induced alterations in the expression of genes involved in protein misfolding, angiogenesis and the oxidative stress response. Further studies will be necessary to determine the role of these genes in prion replication, dissemination and in the response of the organism to this disease. PMID:24450868
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2015-10-01
1 Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors 5a. CONTRACT NUMBER W81XWH...BRCAlike, i.e. not HR deficient and are resistant to PARPis but are sensitive to platinum . These tumors exhibit alterations in another DNA repair
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Genomic profiling of CHEK2*1100delC-mutated breast carcinomas.
Massink, Maarten P G; Kooi, Irsan E; Martens, John W M; Waisfisz, Quinten; Meijers-Heijboer, Hanne
2015-11-09
CHEK2*1100delC is a moderate-risk breast cancer susceptibility allele with a high prevalence in the Netherlands. We performed copy number and gene expression profiling to investigate whether CHEK2*1100delC breast cancers harbor characteristic genomic aberrations, as seen for BRCA1 mutated breast cancers. We performed high-resolution SNP array and gene expression profiling of 120 familial breast carcinomas selected from a larger cohort of 155 familial breast tumors, including BRCA1, BRCA2, and CHEK2 mutant tumors. Gene expression analyses based on a mRNA immune signature was used to identify samples with relative low amounts of tumor infiltrating lymphocytes (TILs), which were previously found to disturb tumor copy number and LOH (loss of heterozygosity) profiling. We specifically compared the genomic and gene expression profiles of CHEK2*1100delC breast cancers (n = 14) with BRCAX (familial non-BRCA1/BRCA2/CHEK2*1100delC mutated) breast cancers (n = 34) of the luminal intrinsic subtypes for which both SNP-array and gene expression data is available. High amounts of TILs were found in a relatively small number of luminal breast cancers as compared to breast cancers of the basal-like subtype. As expected, these samples mostly have very few copy number aberrations and no detectable regions of LOH. By unsupervised hierarchical clustering of copy number data we observed a great degree of heterogeneity amongst the CHEK2*1100delC breast cancers, comparable to the BRCAX breast cancers. Furthermore, copy number aberrations were mostly seen at low frequencies in both the CHEK2*1100delC and BRCAX group of breast cancers. However, supervised class comparison identified copy number loss of chromosomal arm 1p to be associated with CHEK2*1100delC status. In conclusion, in contrast to basal-like BRCA1 mutated breast cancers, no apparent specific somatic copy number aberration (CNA) profile for CHEK2*1100delC breast cancers was found. With the possible exception of copy number loss of chromosomal arm 1p in a subset of tumors, which might be involved in CHEK2 tumorigenesis. This difference in CNAs profiles might be explained by the need for BRCA1-deficient tumor cells to acquire survival factors, by for example specific copy number aberrations, to expand. Such factors may not be needed for breast tumors with a defect in a non-essential gene such as CHEK2.
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Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D
2002-02-01
Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.
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L1000CDS2: LINCS L1000 characteristic direction signatures search engine
Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi
2016-01-01
The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689
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RECOVERING FILTER-BASED MICROARRAY DATA FOR PATHWAYS ANALYSIS USING A MULTIPOINT ALIGNMENT STRATEGY
The use of commercial microarrays are rapidly becoming the method of choice for profiling gene expression and assessing various disease states. Research Genetics has provided a series of well defined biological and software tools to the research community for these analyses. Th...
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Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane
2018-05-15
By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.
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Ijssennagger, Noortje; Janssen, Aafke W F; Milona, Alexandra; Ramos Pittol, José M; Hollman, Danielle A A; Mokry, Michal; Betzel, Bark; Berends, Frits J; Janssen, Ignace M; van Mil, Saskia W C; Kersten, Sander
2016-05-01
The bile acid-activated farnesoid X receptor (FXR) is a nuclear receptor regulating bile acid, glucose and cholesterol homeostasis. Obeticholic acid (OCA), a promising drug for the treatment of non-alcoholic steatohepatitis (NASH) and type 2 diabetes, activates FXR. Mouse studies demonstrated that FXR activation by OCA alters hepatic expression of many genes. However, no data are available on the effects of OCA in the human liver. Here we generated gene expression profiles in human precision cut liver slices (hPCLS) after treatment with OCA. hPCLS were incubated with OCA for 24 h. Wild-type or FXR(-/-) mice received OCA or vehicle by oral gavage for 7 days. Transcriptomic analysis showed that well-known FXR target genes, including NR0B2 (SHP), ABCB11 (BSEP), SLC51A (OSTα) and SLC51B (OSTβ), and ABCB4 (MDR3) are regulated by OCA in hPCLS. Ingenuity pathway analysis confirmed that 'FXR/RXR activation' is the most significantly changed pathway upon OCA treatment. Comparison of gene expression profiles in hPCLS and mouse livers identified 18 common potential FXR targets. ChIP-sequencing in mouse liver confirmed FXR binding to IR1 sequences of Akap13, Cgnl1, Dyrk3, Pdia5, Ppp1r3b and Tbx6. Our study shows that hPCLS respond to OCA treatment by upregulating well-known FXR target genes, demonstrating its suitability to study FXR-mediated gene regulation. We identified six novel bona-fide FXR target genes in both mouse and human liver. Finally, we discuss a possible explanation for changes in high or low density lipoprotein observed in NASH and primary biliary cholangitis patients treated with OCA based on the genomic expression profile in hPCLS. Copyright © 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
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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
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Brooks, Matthew J.; Rajasimha, Harsha K.; Roger, Jerome E.
2011-01-01
Purpose Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. PMID:22162623
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2013-01-01
Background The grain aphid (Sitobion avenae F.) is a major agricultural pest which causes significant yield losses of wheat in China, Europe and North America annually. Transcriptome profiling of the grain aphid alimentary canal after feeding on wheat plants could provide comprehensive gene expression information involved in feeding, ingestion and digestion. Furthermore, selection of aphid-specific RNAi target genes would be essential for utilizing a plant-mediated RNAi strategy to control aphids via a non-toxic mode of action. However, due to the tiny size of the alimentary canal and lack of genomic information on grain aphid as a whole, selection of the RNAi targets is a challenging task that as far as we are aware, has never been documented previously. Results In this study, we performed de novo transcriptome assembly and gene expression analyses of the alimentary canals of grain aphids before and after feeding on wheat plants using Illumina RNA sequencing. The transcriptome profiling generated 30,427 unigenes with an average length of 664 bp. Furthermore, comparison of the transcriptomes of alimentary canals of pre- and post feeding grain aphids indicated that 5490 unigenes were differentially expressed, among which, diverse genes and/or pathways were identified and annotated. Based on the RPKM values of these unigenes, 16 of them that were significantly up or down-regulated upon feeding were selected for dsRNA artificial feeding assay. Of these, 5 unigenes led to higher mortality and developmental stunting in an artificial feeding assay due to the down-regulation of the target gene expression. Finally, by adding fluorescently labelled dsRNA into the artificial diet, the spread of fluorescence signal in the whole body tissues of grain aphid was observed. Conclusions Comparison of the transcriptome profiles of the alimentary canals of pre- and post-feeding grain aphids on wheat plants provided comprehensive gene expression information that could facilitate our understanding of the molecular mechanisms underlying feeding, ingestion and digestion. Furthermore, five novel and effective potential RNAi target genes were identified in grain aphid for the first time. This finding would provide a fundamental basis for aphid control in wheat through plant mediated RNAi strategy. PMID:23957588
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NASA Technical Reports Server (NTRS)
Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki
2013-01-01
The shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low-level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.
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Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun
2015-01-01
There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.
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A statistical method for measuring activation of gene regulatory networks.
Esteves, Gustavo H; Reis, Luiz F L
2018-06-13
Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation. The real probability distribution for the test statistic is evaluated by a permutation based study. To illustrate the functionality of the proposed methodology, we also present a simple example based on a small hypothetical network and the activation measuring of two KEGG networks, both based on gene expression data collected from gastric and esophageal samples. The two KEGG networks were also analyzed for a public database, available through NCBI-GEO, presented as Supplementary Material. This method was implemented in an R package that is available at the BioConductor project website under the name maigesPack.
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NCBI GEO: mining millions of expression profiles--database and tools.
Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron
2005-01-01
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
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Zajaczkowski, Esmi L; Zhao, Qiong-Yi; Zhang, Zong Hong; Li, Xiang; Wei, Wei; Marshall, Paul R; Leighton, Laura J; Nainar, Sarah; Feng, Chao; Spitale, Robert C; Bredy, Timothy W
2018-06-15
Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.
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Glud, Martin; Klausen, Mikkel; Gniadecki, Robert; Rossing, Maria; Hastrup, Nina; Nielsen, Finn C; Drzewiecki, Krzysztof T
2009-05-01
MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate cellular differentiation, proliferation, and apoptosis. MiRNAs are expressed in a developmentally regulated and tissue-specific manner. Aberrant expression may contribute to pathological processes such as cancer, and miRNA may therefore serve as biomarkers that may be useful in a clinical environment for diagnosis of various diseases. Most miRNA profiling studies have used fresh tissue samples. However, in some types of cancer, including malignant melanoma, fresh material is difficult to obtain from primary tumors, and most surgical specimens are formalin fixed and paraffin embedded (FFPE). To explore whether FFPE material would be suitable for miRNA profiling in melanocytic lesions, we compared miRNA expression patterns in FFPE versus fresh frozen samples, obtained from 15 human melanocytic nevi. Out of microarray data, we identified 84 miRNAs that were expressed in both types of samples and represented an miRNA profile of melanocytic nevi. Our results showed a high correlation in miRNA expression (Spearman r-value of 0.80) between paired FFPE and fresh frozen material. The data were further validated by quantitative RT-PCR. In conclusion, FFPE specimens of melanocytic lesions are suitable as a source for miRNA microarray profiling.
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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.
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Differential expression profiling of serum proteins and metabolites for biomarker discovery
NASA Astrophysics Data System (ADS)
Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.
2004-11-01
A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.
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Nordström, Henrik; Laukka, Petri; Thingujam, Nutankumar S; Schubert, Emery; Elfenbein, Hillary Anger
2017-11-01
This study explored the perception of emotion appraisal dimensions on the basis of speech prosody in a cross-cultural setting. Professional actors from Australia and India vocally portrayed different emotions (anger, fear, happiness, pride, relief, sadness, serenity and shame) by enacting emotion-eliciting situations. In a balanced design, participants from Australia and India then inferred aspects of the emotion-eliciting situation from the vocal expressions, described in terms of appraisal dimensions (novelty, intrinsic pleasantness, goal conduciveness, urgency, power and norm compatibility). Bayesian analyses showed that the perceived appraisal profiles for the vocally expressed emotions were generally consistent with predictions based on appraisal theories. Few group differences emerged, which suggests that the perceived appraisal profiles are largely universal. However, some differences between Australian and Indian participants were also evident, mainly for ratings of norm compatibility. The appraisal ratings were further correlated with a variety of acoustic measures in exploratory analyses, and inspection of the acoustic profiles suggested similarity across groups. In summary, results showed that listeners may infer several aspects of emotion-eliciting situations from the non-verbal aspects of a speaker's voice. These appraisal inferences also seem to be relatively independent of the cultural background of the listener and the speaker.
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Thingujam, Nutankumar S.; Schubert, Emery
2017-01-01
This study explored the perception of emotion appraisal dimensions on the basis of speech prosody in a cross-cultural setting. Professional actors from Australia and India vocally portrayed different emotions (anger, fear, happiness, pride, relief, sadness, serenity and shame) by enacting emotion-eliciting situations. In a balanced design, participants from Australia and India then inferred aspects of the emotion-eliciting situation from the vocal expressions, described in terms of appraisal dimensions (novelty, intrinsic pleasantness, goal conduciveness, urgency, power and norm compatibility). Bayesian analyses showed that the perceived appraisal profiles for the vocally expressed emotions were generally consistent with predictions based on appraisal theories. Few group differences emerged, which suggests that the perceived appraisal profiles are largely universal. However, some differences between Australian and Indian participants were also evident, mainly for ratings of norm compatibility. The appraisal ratings were further correlated with a variety of acoustic measures in exploratory analyses, and inspection of the acoustic profiles suggested similarity across groups. In summary, results showed that listeners may infer several aspects of emotion-eliciting situations from the non-verbal aspects of a speaker's voice. These appraisal inferences also seem to be relatively independent of the cultural background of the listener and the speaker. PMID:29291085
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Statistical Use of Argonaute Expression and RISC Assembly in microRNA Target Identification
Stanhope, Stephen A.; Sengupta, Srikumar; den Boon, Johan; Ahlquist, Paul; Newton, Michael A.
2009-01-01
MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address the problem of detecting m/miRNA targeting relationships in homo sapiens from microarray data by developing statistical models that are motivated by the biological mechanisms used by miRNAs. The focus of our modeling is the construction, activity, and mediation of RNA-induced silencing complexes (RISCs) competent for targeted mRNA cleavage. We demonstrate that regression models accommodating RISC abundance and controlling for other mediating factors fit the expression profiles of known target pairs substantially better than models based on m/miRNA expressions alone, and lead to verifications of computational target pair predictions that are more sensitive than those based on marginal expression levels. Because our models are fully independent of exogenous results from sequence-based computational methods, they are appropriate for use as either a primary or secondary source of information regarding m/miRNA target pair relationships, especially in conjunction with high-throughput expression studies. PMID:19779550
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Let-7b regulates the expression of the growth hormone receptor gene in deletion-type dwarf chickens.
Lin, Shumao; Li, Hongmei; Mu, Heping; Luo, Wen; Li, Ying; Jia, Xinzheng; Wang, Sibing; Jia, Xiaolu; Nie, Qinghua; Li, Yugu; Zhang, Xiquan
2012-07-10
A deletion mutation in the growth hormone receptor (GHR) gene results in the inhibition of skeletal muscle growth and fat deposition in dwarf chickens. We used microarray techniques to determine microRNA (miRNA) and mRNA expression profiles of GHR in the skeletal muscles of 14-day-old embryos as well as 7-week-old deletion-type dwarf and normal-type chickens. Our aim was to elucidate the miRNA regulation of GHR expression with respect to growth inhibition and fat deposition. At the same developmental stages, different expression profiles in skeletal muscles of dwarf and normal chickens occurred for four miRNAs (miR-1623, miR-181b, let-7b, and miR-128). At different developmental stages, there was a significant difference in the expression profiles of a greater number of miRNAs. Eleven miRNAs were up-regulated and 18 down-regulated in the 7-week-old dwarf chickens when compared with profiles in 14-day-old embryos. In 7-week-old normal chickens, seven miRNAs were up-regulated and nine down-regulated compared with those in 14-day-old embryos. In skeletal muscles, 22 genes were up-regulated and 33 down-regulated in 14-day-old embryos compared with 7-week-old dwarf chickens. Sixty-five mRNAs were up-regulated and 108 down-regulated in 14-day-old embryos as compared with 7-week-old normal chickens. Thirty-four differentially expressed miRNAs were grouped into 18 categories based on overlapping seed and target sequences. Only let-7b was found to be complementary to its target in the 3' untranslated region of GHR, and was able to inhibit its expression. Kyoto Encyclopedia of Genes and Genomes pathway analysis and quantitative polymerase chain reactions indicated there were three main signaling pathways regulating skeletal muscle growth and fat deposition of chickens. These were influenced by let-7b-regulated GHR. Suppression of the cytokine signaling 3 (SOCS3) gene was found to be involved in the signaling pathway of adipocytokines. There is a critical miRNA, let-7b, involved in the regulation of GHR. SOCS3 plays a critical role in regulating skeletal muscle growth and fat deposition via let-7b-mediated GHR expression.
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Let-7b regulates the expression of the growth hormone receptor gene in deletion-type dwarf chickens
2012-01-01
Background A deletion mutation in the growth hormone receptor (GHR) gene results in the inhibition of skeletal muscle growth and fat deposition in dwarf chickens. We used microarray techniques to determine microRNA (miRNA) and mRNA expression profiles of GHR in the skeletal muscles of 14-day-old embryos as well as 7-week-old deletion-type dwarf and normal-type chickens. Our aim was to elucidate the miRNA regulation of GHR expression with respect to growth inhibition and fat deposition. Results At the same developmental stages, different expression profiles in skeletal muscles of dwarf and normal chickens occurred for four miRNAs (miR-1623, miR-181b, let-7b, and miR-128). At different developmental stages, there was a significant difference in the expression profiles of a greater number of miRNAs. Eleven miRNAs were up-regulated and 18 down-regulated in the 7-week-old dwarf chickens when compared with profiles in 14-day-old embryos. In 7-week-old normal chickens, seven miRNAs were up-regulated and nine down-regulated compared with those in 14-day-old embryos. In skeletal muscles, 22 genes were up-regulated and 33 down-regulated in 14-day-old embryos compared with 7-week-old dwarf chickens. Sixty-five mRNAs were up-regulated and 108 down-regulated in 14-day-old embryos as compared with 7-week-old normal chickens. Thirty-four differentially expressed miRNAs were grouped into 18 categories based on overlapping seed and target sequences. Only let-7b was found to be complementary to its target in the 3′ untranslated region of GHR, and was able to inhibit its expression. Kyoto Encyclopedia of Genes and Genomes pathway analysis and quantitative polymerase chain reactions indicated there were three main signaling pathways regulating skeletal muscle growth and fat deposition of chickens. These were influenced by let-7b-regulated GHR. Suppression of the cytokine signaling 3 (SOCS3) gene was found to be involved in the signaling pathway of adipocytokines. Conclusions There is a critical miRNA, let-7b, involved in the regulation of GHR. SOCS3 plays a critical role in regulating skeletal muscle growth and fat deposition via let-7b-mediated GHR expression. PMID:22781587
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Kusaka, M; Okamoto, M; Takenaka, M; Sasaki, H; Fukami, N; Kataoka, K; Ito, T; Kenmochi, T; Hoshinaga, K; Shiroki, R
2017-06-01
Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract). Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm. The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period. The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system. Copyright © 2017 Elsevier Inc. All rights reserved.
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Zhu, Yan; Wang, Bo; Phillips, Jonathan; Zhang, Zhen-Nan; Du, Hong; Xu, Tao; Huang, Lian-Cheng; Zhang, Xiao-Fei; Xu, Guang-Hui; Li, Wen-Long; Wang, Zhi; Wang, Ling; Liu, Yong-Xiu; Deng, Xin
2015-07-01
Boea hygrometrica resurrection plants require a period of acclimation by slow soil-drying in order to survive a subsequent period of rapid desiccation. The molecular basis of this observation was investigated by comparing gene expression profiles under different degrees of water deprivation. Transcripts were clustered according to the expression profiles in plants that were air-dried (rapid desiccation), soil-dried (gradual desiccation), rehydrated (acclimated) and air-dried after acclimation. Although phenotypically indistinguishable, it was shown by principal component analysis that the gene expression profiles in rehydrated, acclimated plants resemble those of desiccated plants more closely than those of hydrated acclimated plants. Enrichment analysis based on gene ontology was performed to deconvolute the processes that accompanied desiccation tolerance. Transcripts associated with autophagy and α-tocopherol accumulation were found to be activated in both air-dried, acclimated plants and soil-dried non-acclimated plants. Furthermore, transcripts associated with biosynthesis of ascorbic acid, cell wall catabolism, chaperone-assisted protein folding, respiration and macromolecule catabolism were activated and maintained during soil-drying and rehydration. Based on these findings, we hypothesize that activation of these processes leads to the establishment of an optimal physiological and cellular state that enables tolerance during rapid air-drying. Our study provides a novel insight into the transcriptional regulation of critical priming responses to enable survival following rapid dehydration in B. hygrometrica. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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Ienasescu, Hans; Li, Kang; Andersson, Robin; Vitezic, Morana; Rennie, Sarah; Chen, Yun; Vitting-Seerup, Kristoffer; Lagoni, Emil; Boyd, Mette; Bornholdt, Jette; de Hoon, Michiel J. L.; Kawaji, Hideya; Lassmann, Timo; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Carninci, Piero; Sandelin, Albin
2016-01-01
Genomics consortia have produced large datasets profiling the expression of genes, micro-RNAs, enhancers and more across human tissues or cells. There is a need for intuitive tools to select subsets of such data that is the most relevant for specific studies. To this end, we present SlideBase, a web tool which offers a new way of selecting genes, promoters, enhancers and microRNAs that are preferentially expressed/used in a specified set of cells/tissues, based on the use of interactive sliders. With the help of sliders, SlideBase enables users to define custom expression thresholds for individual cell types/tissues, producing sets of genes, enhancers etc. which satisfy these constraints. Changes in slider settings result in simultaneous changes in the selected sets, updated in real time. SlideBase is linked to major databases from genomics consortia, including FANTOM, GTEx, The Human Protein Atlas and BioGPS. Database URL: http://slidebase.binf.ku.dk PMID:28025337
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Kaneko, Kunihiko
2011-06-01
Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. Copyright © 2011 WILEY Periodicals, Inc.
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Halfon, Sibel; Çavdar, Alev; Orsucci, Franco; Schiepek, Gunter K; Andreassi, Silvia; Giuliani, Alessandro; de Felice, Giulio
2016-01-01
Aim: Even though there is substantial evidence that play based therapies produce significant change, the specific play processes in treatment remain unexamined. For that purpose, processes of change in long-term psychodynamic play therapy are assessed through a repeated systematic assessment of three children's "play profiles," which reflect patterns of organization among play variables that contribute to play activity in therapy, indicative of the children's coping strategies, and an expression of their internal world. The main aims of the study are to investigate the kinds of play profiles expressed in treatment, and to test whether there is emergence of new and more adaptive play profiles using dynamic systems theory as a methodological framework. Methods and Procedures: Each session from the long-term psychodynamic treatment (mean number of sessions = 55) of three 6-year-old good outcome cases presenting with Separation Anxiety were recorded, transcribed and coded using items from the Children's Play Therapy Instrument (CPTI), created to assess the play activity of children in psychotherapy, generating discrete and measurable units of play activity arranged along a continuum of four play profiles: "Adaptive," "Inhibited," "Impulsive," and "Disorganized." The play profiles were clustered through K -means Algorithm, generating seven discrete states characterizing the course of treatment and the transitions between these states were analyzed by Markov Transition Matrix, Recurrence Quantification Analysis (RQA) and odds ratios comparing the first and second halves of psychotherapy. Results: The Markov Transitions between the states scaled almost perfectly and also showed the ergodicity of the system, meaning that the child can reach any state or shift to another one in play. The RQA and odds ratios showed two trends of change, first concerning the decrease in the use of "less adaptive" strategies, second regarding the reduction of play interruptions. Conclusion: The results support that these children express different psychic states in play, which can be captured through the lens of play profiles, and begin to modify less dysfunctional profiles over the course of treatment. The methodology employed showed the productivity of treating psychodynamic play therapy as a complex system, taking advantage of non-linear methods to study psychotherapeutic play activity.
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Talar, Urszula; Kiełbowicz-Matuk, Agnieszka; Czarnecka, Jagoda; Rorat, Tadeusz
2017-01-01
Plant B-box domain proteins (BBX) mediate many light-influenced developmental processes including seedling photomorphogenesis, seed germination, shade avoidance and photoperiodic regulation of flowering. Despite the wide range of potential functions, the current knowledge regarding BBX proteins in major crop plants is scarce. In this study, we identify and characterize the StBBX gene family in potato, which is composed of 30 members, with regard to structural properties and expression profiles under diurnal cycle, etiolation and de-etiolations. Based on domain organization and phylogenetic relationships, StBBX genes have been classified into five groups. Using real-time quantitative PCR, we found that expression of most of them oscillates following a 24-h rhythm; however, large differences in expression profiles were observed between the genes regarding amplitude and position of the maximal and minimal expression levels in the day/night cycle. On the basis of the time-of-day/time-of-night, we distinguished three expression groups specifically expressed during the light and two during the dark phase. In addition, we showed that the expression of several StBBX genes is under the control of the circadian clock and that some others are specifically associated with the etiolation and de-etiolation conditions. Thus, we concluded that StBBX proteins are likely key players involved in the complex diurnal and circadian networks regulating plant development as a function of light conditions and day duration.
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Younossi, Zobair M; Baranova, Ancha; Afendy, Arian; Collantes, Rochelle; Stepanova, Maria; Manyam, Ganiraju; Bakshi, Anita; Sigua, Christopher L; Chan, Joanne P; Iverson, Ayuko A; Santini, Christopher D; Chang, Sheng-Yung P
2009-03-01
Responsiveness to hepatitis C virus (HCV) therapy depends on viral and host factors. Our aim was to assess sustained virologic response (SVR)-associated early gene expression in patients with HCV receiving pegylated interferon-alpha2a (PEG-IFN-alpha2a) or PEG-IFN-alpha2b and ribavirin with the duration based on genotypes. Blood samples were collected into PAXgene tubes prior to treatment as well as 1, 7, 28, and 56 days after treatment. From the peripheral blood cells, total RNA was extracted, quantified, and used for one-step reverse transcription polymerase chain reaction to profile 154 messenger RNAs. Expression levels of messenger RNAs were normalized with six "housekeeping" genes and a reference RNA. Multiple regression and stepwise selection were performed to assess differences in gene expression at different time points, and predictive performance was evaluated for each model. A total of 68 patients were enrolled in the study and treated with combination therapy. The results of gene expression showed that SVR could be predicted by the gene expression of signal transducer and activator of transcription-6 (STAT-6) and suppressor of cytokine signaling-1 in the pretreatment samples. After 24 hours, SVR was predicted by the expression of interferon-dependent genes, and this dependence continued to be prominent throughout the treatment. Early gene expression during anti-HCV therapy may elucidate important molecular pathways that may be influencing the probability of achieving virologic response.
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Sheh, Alexander; Chaturvedi, Rupesh; Merrell, D Scott; Correa, Pelayo; Wilson, Keith T; Fox, James G
2013-07-01
While Helicobacter pylori infects over 50% of the world's population, the mechanisms involved in the development of gastric disease are not fully understood. Bacterial, host, and environmental factors play a role in disease outcome. To investigate the role of bacterial factors in H. pylori pathogenesis, global gene expression of six H. pylori isolates was analyzed during coculture with gastric epithelial cells. Clustering analysis of six Colombian clinical isolates from a region with low gastric cancer risk and a region with high gastric cancer risk segregated strains based on their phylogeographic origin. One hundred forty-six genes had increased expression in European strains, while 350 genes had increased expression in African strains. Differential expression was observed in genes associated with motility, pathogenicity, and other adaptations to the host environment. European strains had greater expression of the virulence factors cagA, vacA, and babB and were associated with increased gastric histologic lesions in patients. In AGS cells, European strains promoted significantly higher interleukin-8 (IL-8) expression than did African strains. African strains significantly induced apoptosis, whereas only one European strain significantly induced apoptosis. Our data suggest that gene expression profiles of clinical isolates can discriminate strains by phylogeographic origin and that these profiles are associated with changes in expression of the proinflammatory and protumorigenic cytokine IL-8 and levels of apoptosis in host epithelial cells. These findings support the hypothesis that bacterial factors determined by the phylogeographic origin of H. pylori strains may promote increased gastric disease.
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Karthik, Govindasamy-Muralidharan; Rantalainen, Mattias; Stålhammar, Gustav; Lövrot, John; Ullah, Ikram; Alkodsi, Amjad; Ma, Ran; Wedlund, Lena; Lindberg, Johan; Frisell, Jan; Bergh, Jonas; Hartman, Johan
2017-11-29
Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.
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Strajhar, Petra; Tonoli, David; Jeanneret, Fabienne; Imhof, Raphaella M; Malagnino, Vanessa; Patt, Melanie; Kratschmar, Denise V; Boccard, Julien; Rudaz, Serge; Odermatt, Alex
2017-04-15
The validated OECD test guideline 456 based on human adrenal H295R cells promotes measurement of testosterone and estradiol production as read-out to identify potential endocrine disrupting chemicals. This study aimed to establish optimal conditions for using H295R cells to detect chemicals interfering with the production of key adrenal steroids. H295R cells' supernatants were characterized by liquid chromatography-mass spectrometry (LC-MS)-based steroid profiling, and the influence of experimental conditions including time and serum content was assessed. Steroid profiles were determined before and after incubation with reference compounds and chemicals to be tested for potential disruption of adrenal steroidogenesis. The H295R cells cultivated according to the OECD test guideline produced progestins, glucocorticoids, mineralocorticoids and adrenal androgens but only very low amounts of testosterone. However, testosterone contained in Nu-serum was metabolized during the 48h incubation. Thus, inclusion of positive and negative controls and a steroid profile of the complete medium prior to the experiment (t=0h) was necessary to characterize H295R cells' steroid production and indicate alterations caused by exposure to chemicals. Among the tested chemicals, octyl methoxycinnamate and acetyl tributylcitrate resembled the corticosteroid induction pattern of the positive control torcetrapib. Gene expression analysis revealed that octyl methoxycinnamate and acetyl tributylcitrate enhanced CYP11B2 expression, although less pronounced than torcetrapib. Further experiments need to assess the toxicological relevance of octyl methoxycinnamate- and acetyl tributylcitrate-induced corticosteroid production. In conclusion, the extended profiling and appropriate controls allow detecting chemicals that act on steroidogenesis and provide initial mechanistic evidence for prioritizing chemicals for further investigations. Copyright © 2017 Elsevier B.V. All rights reserved.
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G-cimp status prediction of glioblastoma samples using mRNA expression data.
Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K; Stevenson, Holly; Meltzer, Paul; Fine, Howard A
2012-01-01
Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.
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G-Cimp Status Prediction Of Glioblastoma Samples Using mRNA Expression Data
Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C.; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K.; Stevenson, Holly; Meltzer, Paul; Fine, Howard A.
2012-01-01
Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data. PMID:23139755
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Kent, Clement; Azanchi, Reza; Smith, Ben; Chu, Adrienne; Levine, Joel
2007-01-01
Drosophila Cuticular Hydrocarbons (CH) influence courtship behaviour, mating, aggregation, oviposition, and resistance to desiccation. We measured levels of 24 different CH compounds of individual male D. melanogaster hourly under a variety of environmental (LD/DD) conditions. Using a model-based analysis of CH variation, we developed an improved normalization method for CH data, and show that CH compounds have reproducible cyclic within-day temporal patterns of expression which differ between LD and DD conditions. Multivariate clustering of expression patterns identified 5 clusters of co-expressed compounds with common chemical characteristics. Turnover rate estimates suggest CH production may be a significant metabolic cost. Male cuticular hydrocarbon expression is a dynamic trait influenced by light and time of day; since abundant hydrocarbons affect male sexual behavior, males may present different pheromonal profiles at different times and under different conditions. PMID:17896002
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Analysis of microRNA and gene expression profiling in triazole fungicide-treated HepG2 cell line.
An, Yu Ri; Kim, Seung Jun; Oh, Moon-Ju; Kim, Hyun-Mi; Shim, Il-Seob; Kim, Pil-Je; Choi, Kyunghee; Hwang, Seung Yong
2013-01-07
MicroRNA (miRNA) plays an important role in various diseases and in cellular and molecular responses to toxicants. In the present study, we investigated differential expression of miRNAs in response to three triazole fungicides (myclobutanil, propiconazole, and triadimefon). The human hepatoma cell line (HepG2) was treated with the above triazoles for 3 h or 48 h. miRNA-based microarray experiments were carried out using the Agilent human miRNA v13 array. At early exposure (3h), six miRNAs were differentially expressed and at late exposure (48 h), three miRNAs were significantly expressed. Overall, this study provides an array of potential biomarkers for the above triazole fungicides. Furthermore, these miRNAs induced by triazoles could be the foundation for the development of a miRNA-based toxic biomarker library that can predict environmental toxicity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
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Case-based retrieval framework for gene expression data.
Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J
2015-01-01
The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.
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NASA Astrophysics Data System (ADS)
Parkinson, Christopher D.; Gao, Peter; Schulte, Rick; Bougher, Stephen W.; Yung, Yuk L.; Bardeen, Charles G.; Wilquet, Valérie; Vandaele, Ann Carine; Mahieux, Arnaud; Tellmann, Silvia; Pätzold, Martin
2015-08-01
Observations from Pioneer Venus and from SPICAV/SOIR aboard Venus Express (VEx) have shown the upper haze (UH) of Venus to be highly spatially and temporally variable, and populated by multiple particle size modes. Previous models of this system (e.g., Gao et al., 2014. Icarus 231, 83-98), using a typical temperature profile representative of the atmosphere (viz., equatorial VIRA profile), did not investigate the effect of temperature on the UH particle distributions. We show that the inclusion of latitude-dependent temperature profiles for both the morning and evening terminators of Venus helps to explain how the atmospheric aerosol distributions vary spatially. In this work we use temperature profiles obtained by two instruments onboard VEx, VeRa and SPICAV/SOIR, to represent the latitudinal temperature dependence. We find that there are no significant differences between results for the morning and evening terminators at any latitude and that the cloud base moves downwards as the latitude increases due to decreasing temperatures. The UH is not affected much by varying the temperature profiles; however, the haze does show some periodic differences, and is slightly thicker at the poles than at the equator. We also find that the sulphuric acid "rain" seen in previous models may be restricted to the equatorial regions of Venus, such that the particle size distribution is relatively stable at higher latitudes and at the poles.
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The altered liver microRNA profile in hepatotoxicity induced by rhizome Dioscorea bulbifera in mice.
Yang, Rui; Bai, Qingyun; Zhang, Jiaqi; Sheng, Yuchen; Ji, Lili
2017-08-01
MicroRNA (miRNA) has been reported to play important roles in regulating drug-induced liver injury. Ethyl acetate extract isolated from rhizoma Dioscoreae bulbifera (EF) has been reported to induce hepatotoxicity in our previous studies. This study aims to observe the altered liver miRNA profile and its related signalling pathway involved in EF-induced hepatotoxicity. Serum alanine/aspartate aminotransferase assay showed that EF (450 mg/kg)-induced hepatotoxicity in mice. Results of miRNA chip analysis showed that the expression of eight miRNAs was up-regulated and of other nine miRNAs was down-regulated in livers from EF-treated mice. Further, the altered expression of miR-200a-3p, miR-5132-5p and miR-5130 was validated using real-time polymerase chain reaction (PCR) assay. There were total seven predicted target genes of miR-200a-3p, miR-5132-5p and miR-5130. Only one kyoto encyclopedia genes and genomes pathway was annotated using those target genes, which is protein processing in endoplasmic reticulum (ER). Furthermore, liver expression of DnaJ subfamily A member 1, a key gene involved in protein processing in ER based on the altered miRNAs, was increased in EF-treated mice. In conclusion, the results demonstrated that EF altered the expression of liver miRNA profile and its related signalling pathway, which may be involved in EF-induced hepatotoxicity.
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Qi, Yanxiang; Liu, Xiaomei; Pu, Jinji
2018-01-01
The NAC transcription factors involved plant development and response to various stress stimuli. However, little information is available concerning the NAC family in the woodland strawberry. Herein, 37 NAC genes were identified from the woodland strawberry genome and were classified into 13 groups based on phylogenetic analysis. And further analyses of gene structure and conserved motifs showed closer relationship of them in every subgroup. Quantitative real-time PCR evaluation different tissues revealed distinct spatial expression profiles of the FvNAC genes. The comprehensive expression of FvNAC genes revealed under abiotic stress (cold, heat, drought, salt), signal molecule treatments (H2O2, ABA, melatonin, rapamycin), biotic stress (Colletotrichum gloeosporioides and Ralstonia solanacearum). Expression profiles derived from quantitative real-time PCR suggested that 5 FvNAC genes responded dramatically to the various abiotic and biotic stresses, indicating their contribution to abiotic and biotic stresses resistance in woodland strawberry. Interestingly, FvNAC genes showed greater extent responded to the cold treatment than other abiotic stress, and H2O2 exhibited a greater response than ABA, melatonin, and rapamycin. For biotic stresses, 3 FvNAC genes were up-regulated during infection with C. gloeosporioides, while 6 FvNAC genes were down-regulated during infection with R. solanacearum. In conclusion, this study identified candidate FvNAC genes to be used for the genetic improvement of abiotic and biotic stress tolerance in woodland strawberry. PMID:29897926
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Bushman, B Shaun; Amundsen, Keenan L; Warnke, Scott E; Robins, Joseph G; Johnson, Paul G
2016-01-13
Kentucky bluegrass (Poa pratensis L.) is a prominent turfgrass in the cool-season regions, but it is sensitive to salt stress. Previously, a relatively salt tolerant Kentucky bluegrass accession was identified that maintained green colour under consistent salt applications. In this study, a transcriptome study between the tolerant (PI 372742) accession and a salt susceptible (PI 368233) accession was conducted, under control and salt treatments, and in shoot and root tissues. Sample replicates grouped tightly by tissue and treatment, and fewer differentially expressed transcripts were detected in the tolerant PI 372742 samples compared to the susceptible PI 368233 samples, and in root tissues compared to shoot tissues. A de novo assembly resulted in 388,764 transcripts, with 36,587 detected as differentially expressed. Approximately 75 % of transcripts had homology based annotations, with several differences in GO terms enriched between the PI 368233 and PI 372742 samples. Gene expression profiling identified salt-responsive gene families that were consistently down-regulated in PI 372742 and unlikely to contribute to salt tolerance in Kentucky bluegrass. Gene expression profiling also identified sets of transcripts relating to transcription factors, ion and water transport genes, and oxidation-reduction process genes with likely roles in salt tolerance. The transcript assembly represents the first such assembly in the highly polyploidy, facultative apomictic Kentucky bluegrass. The transcripts identified provide genetic information on how this plant responds to and tolerates salt stress in both shoot and root tissues, and can be used for further genetic testing and introgression.
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Depth profile of a time-reversal focus in an elastic solid
Remillieux, Marcel C.; Anderson, Brian E.; Ulrich, T. J.; ...
2015-04-01
The out-of-plane velocity component is focused on the flat surface of an isotropic solid sample using the principle of time reversal. This experiment is often reproduced in the context of nondestructive testing for imaging features near the surface of the sample. However, it is not clear how deep the focus extends into the bulk of the sample and what its profile is. In this paper, this question is answered using both numerical simulations and experimental data. The profiles of the foci are expressed in terms of the wavelengths of the dominant waves, based on the interpretation of the Lamb’s problemmore » and the use of the diffraction limit.« less
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Expression profiling of the mouse early embryo: Reflections and Perspectives
Ko, Minoru S. H.
2008-01-01
Laboratory mouse plays important role in our understanding of early mammalian development and provides invaluable model for human early embryos, which are difficult to study for ethical and technical reasons. Comprehensive collection of cDNA clones, their sequences, and complete genome sequence information, which have been accumulated over last two decades, have provided even more advantages to mouse models. Here the progress in global gene expression profiling in early mouse embryos and, to some extent, stem cells are reviewed and the future directions and challenges are discussed. The discussions include the restatement of global gene expression profiles as snapshot of cellular status, and subsequent distinction between the differentiation state and physiological state of the cells. The discussions then extend to the biological problems that can be addressed only through global expression profiling, which include: bird’s-eye view of global gene expression changes, molecular index for developmental potency, cell lineage trajectory, microarray-guided cell manipulation, and the possibility of delineating gene regulatory cascades and networks. PMID:16739220
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2014-11-14
problem. Modification of the PLOS ONE | www.plosone.org 1 November 2014 | Volume 9 | Issue 11 | e112524 Report Documentation Page Form ApprovedOMB No. 0704... Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 FBA algorithm to incorporate additional biological information from gene expression profiles is...We set the maximization of biomass production as the objective of FBA and implemented it in two different forms : without flux minimization (or