Multivariate analysis of flow cytometric data using decision trees.

PubMed

Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

2012-01-01

Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

Identification of the transcriptional regulators by expression profiling infected with hepatitis B virus.

PubMed

Chai, Xiaoqiang; Han, Yanan; Yang, Jian; Zhao, Xianxian; Liu, Yewang; Hou, Xugang; Tang, Yiheng; Zhao, Shirong; Li, Xiao

2016-02-01

The molecular pathogenesis of infection by hepatitis B virus with human is extremely complex and heterogeneous. To date the molecular information is not clearly defined despite intensive research efforts. Thus, studies aimed at transcription and regulation during virus infection or combined researches of those already known to be beneficial are needed. With the purpose of identifying the transcriptional regulators related to infection of hepatitis B virus in gene level, the gene expression profiles from some normal individuals and hepatitis B patients were analyzed in our study. In this work, the differential expressed genes were selected primarily. The several genes among those were validated in an independent set by qRT-PCR. Then the differentially co-expression analysis was conducted to identify differentially co-expressed links and differential co-expressed genes. Next, the analysis of the regulatory impact factors was performed through mapping the links and regulatory data. In order to give a further insight to these regulators, the co-expression gene modules were identified using a threshold-based hierarchical clustering method. Incidentally, the construction of the regulatory network was generated using the computer software. A total of 137,284 differentially co-expressed links and 780 differential co-expressed genes were identified. These co-expressed genes were significantly enriched inflammatory response. The results of regulatory impact factors revealed several crucial regulators related to hepatocellular carcinoma and other high-rank regulators. Meanwhile, more than one hundred co-expression gene modules were identified using clustering method. In our study, some important transcriptional regulators were identified using a computational method, which may enhance the understanding of disease mechanisms and lead to an improved treatment of hepatitis B. However, further experimental studies are required to confirm these findings. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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

PubMed

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

2011-04-11

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

Annotation of gene function in citrus using gene expression information and co-expression networks

PubMed Central

2014-01-01

Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. Results We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Conclusions Integration of citrus gene co-expression networks, functional enrichment analysis and gene expression information provide opportunities to infer gene function in citrus. We present a publicly accessible tool, Network Inference for Citrus Co-Expression (NICCE, http://citrus.adelaide.edu.au/nicce/home.aspx), for the gene co-expression analysis in citrus. PMID:25023870

Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge

PubMed Central

2012-01-01

Background Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a method's ability to find regulators. Results We present a simple data-driven method, Correlation Set Analysis (CSA), for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and a specific type of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their regulatees, we focus on coherence of regulatees of a regulator. Using simulated datasets we show that our method performs very well at recovering even weak regulatory relationships with a low false discovery rate. Using three separate real biological datasets we were able to recover well known and as yet undescribed, active regulators for each disease population. The results are represented as a rank-ordered list of regulators, and reveals both single and higher-order regulatory relationships. Conclusions CSA is an intuitive data-driven way of selecting directed perturbation experiments that are relevant to a disease population of interest and represent a starting point for further investigation. Our findings demonstrate that combining co-expression analysis on regulatee sets with a literature-derived network can successfully identify causal regulators and help develop possible hypothesis to explain disease progression. PMID:22443377

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

PubMed

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.

Comparative modular analysis of gene expression in vertebrate organs.

PubMed

Piasecka, Barbara; Kutalik, Zoltán; Roux, Julien; Bergmann, Sven; Robinson-Rechavi, Marc

2012-03-29

The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

PubMed

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

Gasdermin B expression predicts poor clinical outcome in HER2-positive breast cancer

PubMed Central

Hergueta-Redondo, Marta; Sarrio, David; Molina-Crespo, Ángela; Vicario, Rocío; Bernadó-Morales, Cristina; Martínez, Lidia; Rojo-Sebastián, Alejandro; Serra-Musach, Jordi; Mota, Alba; Martínez-Ramírez, Ángel; Castilla, Maria Ángeles; González-Martin, Antonio; Pernas, Sonia; Cano, Amparo; Cortes, Javier; Nuciforo, Paolo G.; Peg, Vicente; Palacios, José; Pujana, Miguel Ángel; Arribas, Joaquín; Moreno-Bueno, Gema

2016-01-01

Around, 30–40% of HER2-positive breast cancers do not show substantial clinical benefit from the targeted therapy and, thus, the mechanisms underlying resistance remain partially unknown. Interestingly, ERBB2 is frequently co-amplified and co-expressed with neighbour genes that may play a relevant role in this cancer subtype. Here, using an in silico analysis of data from 2,096 breast tumours, we reveal a significant correlation between Gasdermin B (GSDMB) gene (located 175 kilo bases distal from ERBB2) expression and the pathological and clinical parameters of poor prognosis in HER2-positive breast cancer. Next, the analysis of three independent cohorts (totalizing 286 tumours) showed that approximately 65% of the HER2-positive cases have GSDMB gene amplification and protein over-expression. Moreover, GSDMB expression was also linked to poor therapeutic responses in terms of lower relapse free survival and pathologic complete response as well as positive lymph node status and the development of distant metastasis under neoadjuvant and adjuvant treatment settings, respectively. Importantly, GSDMB expression promotes survival to trastuzumab in different HER2-positive breast carcinoma cells, and is associated with trastuzumab resistance phenotype in vivo in Patient Derived Xenografts. In summary, our data identifies the ERBB2 co-amplified and co-expressed gene GSDMB as a critical determinant of poor prognosis and therapeutic response in HER2-positive breast cancer. PMID:27462779

Gasdermin B expression predicts poor clinical outcome in HER2-positive breast cancer.

PubMed

Hergueta-Redondo, Marta; Sarrio, David; Molina-Crespo, Ángela; Vicario, Rocío; Bernadó-Morales, Cristina; Martínez, Lidia; Rojo-Sebastián, Alejandro; Serra-Musach, Jordi; Mota, Alba; Martínez-Ramírez, Ángel; Castilla, Mª Ángeles; González-Martin, Antonio; Pernas, Sonia; Cano, Amparo; Cortes, Javier; Nuciforo, Paolo G; Peg, Vicente; Palacios, José; Pujana, Miguel Ángel; Arribas, Joaquín; Moreno-Bueno, Gema

2016-08-30

Around, 30-40% of HER2-positive breast cancers do not show substantial clinical benefit from the targeted therapy and, thus, the mechanisms underlying resistance remain partially unknown. Interestingly, ERBB2 is frequently co-amplified and co-expressed with neighbour genes that may play a relevant role in this cancer subtype. Here, using an in silico analysis of data from 2,096 breast tumours, we reveal a significant correlation between Gasdermin B (GSDMB) gene (located 175 kilo bases distal from ERBB2) expression and the pathological and clinical parameters of poor prognosis in HER2-positive breast cancer. Next, the analysis of three independent cohorts (totalizing 286 tumours) showed that approximately 65% of the HER2-positive cases have GSDMB gene amplification and protein over-expression. Moreover, GSDMB expression was also linked to poor therapeutic responses in terms of lower relapse free survival and pathologic complete response as well as positive lymph node status and the development of distant metastasis under neoadjuvant and adjuvant treatment settings, respectively. Importantly, GSDMB expression promotes survival to trastuzumab in different HER2-positive breast carcinoma cells, and is associated with trastuzumab resistance phenotype in vivo in Patient Derived Xenografts. In summary, our data identifies the ERBB2 co-amplified and co-expressed gene GSDMB as a critical determinant of poor prognosis and therapeutic response in HER2-positive breast cancer.

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease.

PubMed

Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K

2016-11-30

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer's disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer's disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer's disease brains. The biological pathways associated with Alzheimer's disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature.

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer’s Disease

PubMed Central

Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K.

2016-01-01

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer’s disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer’s disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer’s disease brains. The biological pathways associated with Alzheimer’s disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature. PMID:27901073

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

PubMed

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different networks. By simultaneously exploring these networks and metadata, we gained insights into regulatory mechanisms in M. tuberculosis that could not be obtained through the separate analysis of each data type.

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

PubMed Central

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

2016-01-01

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

Transformation and model choice for RNA-seq co-expression analysis.

PubMed

Rau, Andrea; Maugis-Rabusseau, Cathy

2018-05-01

Although a large number of clustering algorithms have been proposed to identify groups of co-expressed genes from microarray data, the question of if and how such methods may be applied to RNA sequencing (RNA-seq) data remains unaddressed. In this work, we investigate the use of data transformations in conjunction with Gaussian mixture models for RNA-seq co-expression analyses, as well as a penalized model selection criterion to select both an appropriate transformation and number of clusters present in the data. This approach has the advantage of accounting for per-cluster correlation structures among samples, which can be strong in RNA-seq data. In addition, it provides a rigorous statistical framework for parameter estimation, an objective assessment of data transformations and number of clusters and the possibility of performing diagnostic checks on the quality and homogeneity of the identified clusters. We analyze four varied RNA-seq data sets to illustrate the use of transformations and model selection in conjunction with Gaussian mixture models. Finally, we propose a Bioconductor package coseq (co-expression of RNA-seq data) to facilitate implementation and visualization of the recommended RNA-seq co-expression analyses.

Identification of differential pathways in papillary thyroid carcinoma utilizing pathway co-expression analysis.

PubMed

Qiu, Wei-Hai; Chen, Gui-Yan; Cui, Lu; Zhang, Ting-Ming; Wei, Feng; Yang, Yong

2016-01-01

To identify differential pathways between papillary thyroid carcinoma (PTC) patients and normal controls utilizing a novel method which combined pathway with co-expression network. The proposed method included three steps. In the first step, we conducted pretreatments for background pathways and gained representative pathways in PTC. Subsequently, a co-expression network for representative pathways was constructed using empirical Bayes (EB) approach to assign a weight value for each pathway. Finally, random model was extracted to set the thresholds of identifying differential pathways. We obtained 1267 representative pathways and their weight values based on the co-expressed pathway network, and then by meeting the criterion (Weight > 0.0296), 87 differential pathways in total across PTC patients and normal controls were identified. The top three ranked differential pathways were CREB phosphorylation, attachment of GPI anchor to urokinase plasminogen activator receptor (uPAR) and loss of function of SMAD2/3 in cancer. In conclusion, we successfully identified differential pathways (such as CREB phosphorylation, attachment of GPI anchor to uPAR and post-translational modification: synthesis of GPI-anchored proteins) for PTC using the proposed pathway co-expression method, and these pathways might be potential biomarkers for target therapy and detection of PTC.

Discretization provides a conceptually simple tool to build expression networks.

PubMed

Vass, J Keith; Higham, Desmond J; Mudaliar, Manikhandan A V; Mao, Xuerong; Crowther, Daniel J

2011-04-18

Biomarker identification, using network methods, depends on finding regular co-expression patterns; the overall connectivity is of greater importance than any single relationship. A second requirement is a simple algorithm for ranking patients on how relevant a gene-set is. For both of these requirements discretized data helps to first identify gene cliques, and then to stratify patients.We explore a biologically intuitive discretization technique which codes genes as up- or down-regulated, with values close to the mean set as unchanged; this allows a richer description of relationships between genes than can be achieved by positive and negative correlation. We find a close agreement between our results and the template gene-interactions used to build synthetic microarray-like data by SynTReN, which synthesizes "microarray" data using known relationships which are successfully identified by our method.We are able to split positive co-regulation into up-together and down-together and negative co-regulation is considered as directed up-down relationships. In some cases these exist in only one direction, with real data, but not with the synthetic data. We illustrate our approach using two studies on white blood cells and derived immortalized cell lines and compare the approach with standard correlation-based computations. No attempt is made to distinguish possible causal links as the search for biomarkers would be crippled by losing highly significant co-expression relationships. This contrasts with approaches like ARACNE and IRIS.The method is illustrated with an analysis of gene-expression for energy metabolism pathways. For each discovered relationship we are able to identify the samples on which this is based in the discretized sample-gene matrix, along with a simplified view of the patterns of gene expression; this helps to dissect the gene-sample relevant to a research topic--identifying sets of co-regulated and anti-regulated genes and the samples or patients in which this relationship occurs.

Development of the Verona coding definitions of emotional sequences to code health providers' responses (VR-CoDES-P) to patient cues and concerns.

PubMed

Del Piccolo, Lidia; de Haes, Hanneke; Heaven, Cathy; Jansen, Jesse; Verheul, William; Bensing, Jozien; Bergvik, Svein; Deveugele, Myriam; Eide, Hilde; Fletcher, Ian; Goss, Claudia; Humphris, Gerry; Kim, Young-Mi; Langewitz, Wolf; Mazzi, Maria Angela; Mjaaland, Trond; Moretti, Francesca; Nübling, Matthias; Rimondini, Michela; Salmon, Peter; Sibbern, Tonje; Skre, Ingunn; van Dulmen, Sandra; Wissow, Larry; Young, Bridget; Zandbelt, Linda; Zimmermann, Christa; Finset, Arnstein

2011-02-01

To present a method to classify health provider responses to patient cues and concerns according to the VR-CoDES-CC (Del Piccolo et al. (2009) [2] and Zimmermann et al. (submitted for publication) [3]). The system permits sequence analysis and a detailed description of how providers handle patient's expressions of emotion. The Verona-CoDES-P system has been developed based on consensus views within the "Verona Network of Sequence Analysis". The different phases of the creation process are described in detail. A reliability study has been conducted on 20 interviews from a convenience sample of 104 psychiatric consultations. The VR-CoDES-P has two main classes of provider responses, corresponding to the degree of explicitness (yes/no) and space (yes/no) that is given by the health provider to each cue/concern expressed by the patient. The system can be further subdivided into 17 individual categories. Statistical analyses showed that the VR-CoDES-P is reliable (agreement 92.86%, Cohen's kappa 0.90 (±0.04) p<0.0001). Once validity and reliability are tested in different settings, the system should be applied to investigate the relationship between provider responses to patients' expression of emotions and outcome variables. Research employing the VR-CoDES-P should be applied to develop research-based approaches to maximize appropriate responses to patients' indirect and overt expressions of emotional needs. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets

PubMed Central

Kwon, Andrew T.; Arenillas, David J.; Hunt, Rebecca Worsley; Wasserman, Wyeth W.

2012-01-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca. PMID:22973536

oPOSSUM-3: advanced analysis of regulatory motif over-representation across genes or ChIP-Seq datasets.

PubMed

Kwon, Andrew T; Arenillas, David J; Worsley Hunt, Rebecca; Wasserman, Wyeth W

2012-09-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

A long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection.

PubMed

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.

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis

PubMed Central

2013-01-01

Background Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions. Results We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/. Conclusions Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods. PMID:24373308

Genes associated with thermosensitive genic male sterility in rice identified by comparative expression profiling.

PubMed

Pan, Yufang; Li, Qiaofeng; Wang, Zhizheng; Wang, Yang; Ma, Rui; Zhu, Lili; He, Guangcun; Chen, Rongzhi

2014-12-16

Thermosensitive genic male sterile (TGMS) lines and photoperiod-sensitive genic male sterile (PGMS) lines have been successfully used in hybridization to improve rice yields. However, the molecular mechanisms underlying male sterility transitions in most PGMS/TGMS rice lines are unclear. In the recently developed TGMS-Co27 line, the male sterility is based on co-suppression of a UDP-glucose pyrophosphorylase gene (Ugp1), but further study is needed to fully elucidate the molecular mechanisms involved. Microarray-based transcriptome profiling of TGMS-Co27 and wild-type Hejiang 19 (H1493) plants grown at high and low temperatures revealed that 15462 probe sets representing 8303 genes were differentially expressed in the two lines, under the two conditions, or both. Environmental factors strongly affected global gene expression. Some genes important for pollen development were strongly repressed in TGMS-Co27 at high temperature. More significantly, series-cluster analysis of differentially expressed genes (DEGs) between TGMS-Co27 plants grown under the two conditions showed that low temperature induced the expression of a gene cluster. This cluster was found to be essential for sterility transition. It includes many meiosis stage-related genes that are probably important for thermosensitive male sterility in TGMS-Co27, inter alia: Arg/Ser-rich domain (RS)-containing zinc finger proteins, polypyrimidine tract-binding proteins (PTBs), DEAD/DEAH box RNA helicases, ZOS (C2H2 zinc finger proteins of Oryza sativa), at least one polyadenylate-binding protein and some other RNA recognition motif (RRM) domain-containing proteins involved in post-transcriptional processes, eukaryotic initiation factor 5B (eIF5B), ribosomal proteins (L37, L1p/L10e, L27 and L24), aminoacyl-tRNA synthetases (ARSs), eukaryotic elongation factor Tu (eEF-Tu) and a peptide chain release factor protein involved in translation. The differential expression of 12 DEGs that are important for pollen development, low temperature responses or TGMS was validated by quantitative RT-PCR (qRT-PCR). Temperature strongly affects global gene expression and may be the common regulator of fertility in PGMS/TGMS rice lines. The identified expression changes reflect perturbations in the transcriptomic regulation of pollen development networks in TGMS-Co27. Findings from this and previous studies indicate that sets of genes involved in post-transcriptional and translation processes are involved in thermosensitive male sterility transitions in TGMS-Co27.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

PubMed

Mallik, Saurav; Zhao, Zhongming

2017-12-28

For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation

PubMed Central

Kavak, Erşen; Ünlü, Mustafa; Nistér, Monica; Koman, Ahmet

2010-01-01

Cancer is among the major causes of human death and its mechanism(s) are not fully understood. We applied a novel meta-analysis approach to multiple sets of merged serial analysis of gene expression and microarray cancer data in order to analyze transcriptome alterations in human cancer. Our methodology, which we denote ‘COgnate Gene Expression patterNing in tumours’ (COGENT), unmasked numerous genes that were differentially expressed in multiple cancers. COGENT detected well-known tumor-associated (TA) genes such as TP53, EGFR and VEGF, as well as many multi-cancer, but not-yet-tumor-associated genes. In addition, we identified 81 co-regulated regions on the human genome (RIDGEs) by using expression data from all cancers. Some RIDGEs (28%) consist of paralog genes while another subset (30%) are specifically dysregulated in tumors but not in normal tissues. Furthermore, a significant number of RIDGEs are associated with GC-rich regions on the genome. All assembled data is freely available online (www.oncoreveal.org) as a tool implementing COGENT analysis of multi-cancer genes and RIDGEs. These findings engender a deeper understanding of cancer biology by demonstrating the existence of a pool of under-studied multi-cancer genes and by highlighting the cancer-specificity of some TA-RIDGEs. PMID:20621981

Expression Atlas: gene and protein expression across multiple studies and organisms

PubMed Central

Tang, Y Amy; Bazant, Wojciech; Burke, Melissa; Fuentes, Alfonso Muñoz-Pomer; George, Nancy; Koskinen, Satu; Mohammed, Suhaib; Geniza, Matthew; Preece, Justin; Jarnuczak, Andrew F; Huber, Wolfgang; Stegle, Oliver; Brazma, Alvis; Petryszak, Robert

2018-01-01

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions. PMID:29165655

Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

PubMed Central

Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

2015-01-01

Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

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

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

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

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

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

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

Expression profiling of nuclear receptors in breast cancer identifies TLX as a mediator of growth and invasion in triple-negative breast cancer.

PubMed

Lin, Meng-Lay; Patel, Hetal; Remenyi, Judit; Banerji, Christopher R S; Lai, Chun-Fui; Periyasamy, Manikandan; Lombardo, Ylenia; Busonero, Claudia; Ottaviani, Silvia; Passey, Alun; Quinlan, Philip R; Purdie, Colin A; Jordan, Lee B; Thompson, Alastair M; Finn, Richard S; Rueda, Oscar M; Caldas, Carlos; Gil, Jesus; Coombes, R Charles; Fuller-Pace, Frances V; Teschendorff, Andrew E; Buluwela, Laki; Ali, Simak

2015-08-28

The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells.

Identifying osteosarcoma metastasis associated genes by weighted gene co-expression network analysis (WGCNA).

PubMed

Tian, Honglai; Guan, Donghui; Li, Jianmin

2018-06-01

Osteosarcoma (OS), the most common malignant bone tumor, accounts for the heavy healthy threat in the period of children and adolescents. OS occurrence usually correlates with early metastasis and high death rate. This study aimed to better understand the mechanism of OS metastasis.Based on Gene Expression Omnibus (GEO) database, we downloaded 4 expression profile data sets associated with OS metastasis, and selected differential expressed genes. Weighted gene co-expression network analysis (WGCNA) approach allowed us to investigate the most OS metastasis-correlated module. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to give annotation of selected OS metastasis-associated genes.We select 897 differential expressed genes from OS metastasis and OS non-metastasis groups. Based on these selected genes, WGCNA further explored 142 genes included in the most OS metastasis-correlated module. Gene Ontology functional and KEGG pathway enrichment analyses showed that significantly OS metastasis-associated genes were involved in pathway correlated with insulin-like growth factor binding.Our research figured out several potential molecules participating in metastasis process and factors acting as biomarker. With this study, we could better explore the mechanism of OS metastasis and further discover more therapy targets.

CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets

PubMed Central

Li, Yang; Liu, Jun S.; Mootha, Vamsi K.

2017-01-01

In recent years, there has been a huge rise in the number of publicly available transcriptional profiling datasets. These massive compendia comprise billions of measurements and provide a special opportunity to predict the function of unstudied genes based on co-expression to well-studied pathways. Such analyses can be very challenging, however, since biological pathways are modular and may exhibit co-expression only in specific contexts. To overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression. CLIC accepts as input a pathway consisting of two or more genes. It then uses a Bayesian partition model to simultaneously partition the input gene set into coherent co-expressed modules (CEMs), while assigning the posterior probability for each dataset in support of each CEM. CLIC then expands each CEM by scanning the transcriptome for additional co-expressed genes, quantified by an integrated log-likelihood ratio (LLR) score weighted for each dataset. As a byproduct, CLIC automatically learns the conditions (datasets) within which a CEM is operative. We implemented CLIC using a compendium of 1774 mouse microarray datasets (28628 microarrays) or 1887 human microarray datasets (45158 microarrays). CLIC analysis reveals that of 910 canonical biological pathways, 30% consist of strongly co-expressed gene modules for which new members are predicted. For example, CLIC predicts a functional connection between protein C7orf55 (FMC1) and the mitochondrial ATP synthase complex that we have experimentally validated. CLIC is freely available at www.gene-clic.org. We anticipate that CLIC will be valuable both for revealing new components of biological pathways as well as the conditions in which they are active. PMID:28719601

DiRE: identifying distant regulatory elements of co-expressed genes

PubMed Central

Gotea, Valer; Ovcharenko, Ivan

2008-01-01

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org. PMID:18487623

Comparative evaluation of different extraction and quantification methods for forensic RNA analysis.

PubMed

Grabmüller, Melanie; Madea, Burkhard; Courts, Cornelius

2015-05-01

Since about 2005, there is increasing interest in forensic RNA analysis whose versatility may very favorably complement traditional DNA profiling in forensic casework. There is, however, no method available specifically dedicated for extraction of RNA from forensically relevant sample material. In this study we compared five commercially available and commonly used RNA extraction kits and methods (mirVana™ miRNA Isolation Kit Ambion; Trizol® Reagent, Invitrogen; NucleoSpin® miRNA Kit Macherey-Nagel; AllPrep DNA/RNA Mini Kit and RNeasy® Mini Kit both Qiagen) to assess their relative effectiveness of yielding RNA of good quality and their compatibility with co-extraction of DNA amenable to STR profiling. We set up samples of small amounts of dried blood, liquid saliva, semen and buccal mucosa that were aged for different time intervals for co-extraction of RNA and DNA. RNA quality was assessed by determination of 'RNA integrity number' (RIN) and quantitative PCR based expression analysis. DNA quality was assessed via monitoring STR typing success rates. By comparison, the different methods exhibited considerable differences between RNA and DNA yields, RNA quality values and expression levels, and STR profiling success, with the AllPrep DNA/RNA Mini Kit and the NucleoSpin® miRNA Kit excelling at DNA co-extraction and RNA results, respectively. Overall, there was no 'best' method to satisfy all demands of comprehensible co-analysis of RNA and DNA and it appears that each method has specific merits and flaws. We recommend to cautiously choose from available methods and align its characteristics with the needs of the experimental setting at hand. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The structure of a gene co-expression network reveals biological functions underlying eQTLs.

PubMed

Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali

2013-01-01

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network. PMID:22369639

Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

PubMed

Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

2009-02-01

Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

Parallel gene analysis with allele-specific padlock probes and tag microarrays

PubMed Central

Banér, Johan; Isaksson, Anders; Waldenström, Erik; Jarvius, Jonas; Landegren, Ulf; Nilsson, Mats

2003-01-01

Parallel, highly specific analysis methods are required to take advantage of the extensive information about DNA sequence variation and of expressed sequences. We present a scalable laboratory technique suitable to analyze numerous target sequences in multiplexed assays. Sets of padlock probes were applied to analyze single nucleotide variation directly in total genomic DNA or cDNA for parallel genotyping or gene expression analysis. All reacted probes were then co-amplified and identified by hybridization to a standard tag oligonucleotide array. The technique was illustrated by analyzing normal and pathogenic variation within the Wilson disease-related ATP7B gene, both at the level of DNA and RNA, using allele-specific padlock probes. PMID:12930977

Application of the verona coding definitions of emotional sequences (VR-CoDES) on a pediatric data set.

PubMed

Vatne, Torun M; Finset, Arnstein; Ørnes, Knut; Ruland, Cornelia M

2010-09-01

Adult patients present concerns as defined in the Verona Coding Definitions of Emotional Sequences (VR-CoDES), but we do not know how children express their concerns during medical consultations. This study aimed to evaluate the applicability of VR-CoDES to pediatric oncology consultations. Twenty-eight pediatric consultations were coded with the Verona Coding Definitions of Emotional Sequences (VR-CoDES), and the material was also qualitatively analyzed for descriptive purposes. Five consultations were randomly selected for reliability testing and descriptive statistics were computed. Perfect inter-rater reliability for concerns and moderate reliability for cues were obtained. Cues and/or concerns were present in over half of the consultations. Cues were more frequent than concerns, with the majority of cues being verbal hints to hidden concerns or non-verbal cues. Intensity of expressions, limitations in vocabulary, commonality of statements, and complexity of the setting complicated the use of VR-CoDES. Child-specific cues; use of the imperative, cues about past experiences, and use of onomatopoeia were observed. Children with cancer express concerns during medical consultations. VR-CoDES is a reliable tool for coding concerns in pediatric data sets. For future applications in pediatric settings an appendix should be developed to incorporate the child-specific traits. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

CO 2 Sequestration and Enhanced Oil Recovery at Depleted Oil/Gas Reservoirs

DOE PAGES

Dai, Zhenxue; Viswanathan, Hari; Xiao, Ting; ...

2017-08-18

This study presents a quantitative evaluation of the operational and technical risks of an active CO 2-EOR project. A set of risk factor metrics is defined to post-process the Monte Carlo (MC) simulations for statistical analysis. The risk factors are expressed as measurable quantities that can be used to gain insight into project risk (e.g. environmental and economic risks) without the need to generate a rigorous consequence structure, which include (a) CO 2 injection rate, (b) net CO 2 injection rate, (c) cumulative CO 2 storage, (d) cumulative water injection, (e) oil production rate, (f) cumulative oil production, (g) cumulativemore » CH 4 production, and (h) CO 2 breakthrough time. The Morrow reservoir at the Farnsworth Unit (FWU) site, Texas, is used as an example for studying the multi-scale statistical approach for CO 2 accounting and risk analysis. A set of geostatistical-based MC simulations of CO 2-oil/gas-water flow and transport in the Morrow formation are conducted for evaluating the risk metrics. A response-surface-based economic model has been derived to calculate the CO 2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO 2 capture and operating expenses reduce, more realizations would be profitable.« less

CO 2 Sequestration and Enhanced Oil Recovery at Depleted Oil/Gas Reservoirs

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

Dai, Zhenxue; Viswanathan, Hari; Xiao, Ting

This study presents a quantitative evaluation of the operational and technical risks of an active CO 2-EOR project. A set of risk factor metrics is defined to post-process the Monte Carlo (MC) simulations for statistical analysis. The risk factors are expressed as measurable quantities that can be used to gain insight into project risk (e.g. environmental and economic risks) without the need to generate a rigorous consequence structure, which include (a) CO 2 injection rate, (b) net CO 2 injection rate, (c) cumulative CO 2 storage, (d) cumulative water injection, (e) oil production rate, (f) cumulative oil production, (g) cumulativemore » CH 4 production, and (h) CO 2 breakthrough time. The Morrow reservoir at the Farnsworth Unit (FWU) site, Texas, is used as an example for studying the multi-scale statistical approach for CO 2 accounting and risk analysis. A set of geostatistical-based MC simulations of CO 2-oil/gas-water flow and transport in the Morrow formation are conducted for evaluating the risk metrics. A response-surface-based economic model has been derived to calculate the CO 2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO 2 capture and operating expenses reduce, more realizations would be profitable.« less

Expression profiling of nuclear receptors in breast cancer identifies TLX as a mediator of growth and invasion in triple-negative breast cancer

PubMed Central

Remenyi, Judit; Banerji, Christopher R.S.; Lai, Chun-Fui; Periyasamy, Manikandan; Lombardo, Ylenia; Busonero, Claudia; Ottaviani, Silvia; Passey, Alun; Quinlan, Philip R.; Purdie, Colin A.; Jordan, Lee B.; Thompson, Alastair M.; Finn, Richard S.; Rueda, Oscar M.; Caldas, Carlos; Gil, Jesus; Coombes, R. Charles; Fuller-Pace, Frances V.; Teschendorff, Andrew E.; Buluwela, Laki; Ali, Simak

2015-01-01

The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells. PMID:26280373

Identification of rice genes associated with cosmic-ray response via co-expression gene network analysis.

PubMed

Hwang, Sun-Goo; Kim, Dong Sub; Hwang, Jung Eun; Han, A-Reum; Jang, Cheol Seong

2014-05-15

In order to better understand the biological systems that are affected in response to cosmic ray (CR), we conducted weighted gene co-expression network analysis using the module detection method. By using the Pearson's correlation coefficient (PCC) value, we evaluated complex gene-gene functional interactions between 680 CR-responsive probes from integrated microarray data sets, which included large-scale transcriptional profiling of 1000 microarray samples. These probes were divided into 6 distinct modules that contained 20 enriched gene ontology (GO) functions, such as oxidoreductase activity, hydrolase activity, and response to stimulus and stress. In particular, modules 1 and 2 commonly showed enriched annotation categories such as oxidoreductase activity, including enriched cis-regulatory elements known as ROS-specific regulators. These results suggest that the ROS-mediated irradiation response pathway is affected by CR in modules 1 and 2. We found 243 ionizing radiation (IR)-responsive probes that exhibited similarities in expression patterns in various irradiation microarray data sets. The expression patterns of 6 randomly selected IR-responsive genes were evaluated by quantitative reverse transcription polymerase chain reaction following treatment with CR, gamma rays (GR), and ion beam (IB); similar patterns were observed among these genes under these 3 treatments. Moreover, we constructed subnetworks of IR-responsive genes and evaluated the expression levels of their neighboring genes following GR treatment; similar patterns were observed among them. These results of network-based analyses might provide a clue to understanding the complex biological system related to the CR response in plants. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

Whole transcriptome analysis of the coral Acropora millepora reveals complex responses to CO₂-driven acidification during the initiation of calcification.

PubMed

Moya, A; Huisman, L; Ball, E E; Hayward, D C; Grasso, L C; Chua, C M; Woo, H N; Gattuso, J-P; Forêt, S; Miller, D J

2012-05-01

The impact of ocean acidification (OA) on coral calcification, a subject of intense current interest, is poorly understood in part because of the presence of symbionts in adult corals. Early life history stages of Acropora spp. provide an opportunity to study the effects of elevated CO(2) on coral calcification without the complication of symbiont metabolism. Therefore, we used the Illumina RNAseq approach to study the effects of acute exposure to elevated CO(2) on gene expression in primary polyps of Acropora millepora, using as reference a novel comprehensive transcriptome assembly developed for this study. Gene ontology analysis of this whole transcriptome data set indicated that CO(2) -driven acidification strongly suppressed metabolism but enhanced extracellular organic matrix synthesis, whereas targeted analyses revealed complex effects on genes implicated in calcification. Unexpectedly, expression of most ion transport proteins was unaffected, while many membrane-associated or secreted carbonic anhydrases were expressed at lower levels. The most dramatic effect of CO(2) -driven acidification, however, was on genes encoding candidate and known components of the skeletal organic matrix that controls CaCO(3) deposition. The skeletal organic matrix effects included elevated expression of adult-type galaxins and some secreted acidic proteins, but down-regulation of other galaxins, secreted acidic proteins, SCRiPs and other coral-specific genes, suggesting specialized roles for the members of these protein families and complex impacts of OA on mineral deposition. This study is the first exhaustive exploration of the transcriptomic response of a scleractinian coral to acidification and provides an unbiased perspective on its effects during the early stages of calcification. © 2012 Blackwell Publishing Ltd.

Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

PubMed

Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

2013-12-01

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Whole-genome transcriptomic insights into protective molecular mechanisms in metabolically healthy obese African Americans.

PubMed

Gaye, Amadou; Doumatey, Ayo P; Davis, Sharon K; Rotimi, Charles N; Gibbons, Gary H

2018-01-01

Several clinical guidelines have been proposed to distinguish metabolically healthy obesity (MHO) from other subgroups of obesity but the molecular mechanisms by which MHO individuals remain metabolically healthy despite having a high fat mass are yet to be elucidated. We conducted the first whole blood transcriptomic study designed to identify specific sets of genes that might shed novel insights into the molecular mechanisms that protect or delay the occurrence of obesity-related co-morbidities in MHO. The study included 29 African-American obese individuals, 8 MHO and 21 metabolically abnormal obese (MAO). Unbiased transcriptome-wide network analysis was carried out to identify molecular modules of co-expressed genes that are collectively associated with MHO. Network analysis identified a group of 23 co-expressed genes, including ribosomal protein genes (RPs), which were significantly downregulated in MHO subjects. The three pathways enriched in the group of co-expressed genes are EIF2 signaling, regulation of eIF4 and p70S6K signaling, and mTOR signaling. The expression of ten of the RPs collectively predicted MHO status with an area under the curve of 0.81. Triglycerides/HDL (TG/HDL) ratio, an index of insulin resistance, was the best predictor of the expression of genes in the MHO group. The higher TG/HDL values observed in the MAO subjects may underlie the activation of endoplasmic reticulum (ER) and related-stress pathways that lead to a chronic inflammatory state. In summary, these findings suggest that controlling ER stress and/or ribosomal stress by downregulating RPs or controlling TG/HDL ratio may represent effective strategies to prevent or delay the occurrence of metabolic disorders in obese individuals.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model

PubMed Central

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O.; Eijlander, Robyn T.; Kuipers, Oscar P.

2018-01-01

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes. PMID:29424683

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

PubMed

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O; Eijlander, Robyn T; Kuipers, Oscar P

2018-02-09

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

Analysis of protein function in clinical C. albicans isolates

PubMed Central

Gerami-Nejad, Maryam; Forche, Anja; McClellan, Mark; Berman, Judith

2012-01-01

Clinical isolates are prototrophic and hence are not amenable to genetic manipulation using nutritional markers. Here we describe a new set of plasmids carrying the NAT1 (nourseothricin) drug resistance marker (Shen et al., 2005) that can be used both in clinical isolates and in laboratory strains. We constructed novel plasmids containing HA-NAT1 or MYC-NAT1 cassettes to facilitate PCR-mediated construction of strains with C-terminal epitope-tagged proteins and a NAT1-pMet3-GFP plasmid to enable conditional expression of proteins with or without the green fluorescent protein fused at the N-terminus. Furthermore, for proteins that require both the endogenous N- and C-termini for function, we have constructed a GF-NAT1-FP cassette carrying truncated alleles that facilitate insertion of an intact, single copy of GFP internal to the coding sequence. In addition, GFP-NAT1, RFP-NAT1, and M-Cherry-NAT1 plasmids were constructed expressing two differently labeled gene products for the study of protein co-expression and co-localization in vivo. Together, these vectors provide a useful set of genetic tools for studying diverse aspects of gene function in C. albicans clinical as well as laboratory strains. PMID:22777821

Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

PubMed

Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

2016-11-04

Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types, duplication ages and co-expression consequences.

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

PubMed

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.

Extended Poisson process modelling and analysis of grouped binary data.

PubMed

Faddy, Malcolm J; Smith, David M

2012-05-01

A simple extension of the Poisson process results in binomially distributed counts of events in a time interval. A further extension generalises this to probability distributions under- or over-dispersed relative to the binomial distribution. Substantial levels of under-dispersion are possible with this modelling, but only modest levels of over-dispersion - up to Poisson-like variation. Although simple analytical expressions for the moments of these probability distributions are not available, approximate expressions for the mean and variance are derived, and used to re-parameterise the models. The modelling is applied in the analysis of two published data sets, one showing under-dispersion and the other over-dispersion. More appropriate assessment of the precision of estimated parameters and reliable model checking diagnostics follow from this more general modelling of these data sets. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis.

PubMed

Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John

2016-02-24

In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

PubMed Central

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants. PMID:29692794

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana.

PubMed

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

CoPub: a literature-based keyword enrichment tool for microarray data analysis.

PubMed

Frijters, Raoul; Heupers, Bart; van Beek, Pieter; Bouwhuis, Maurice; van Schaik, René; de Vlieg, Jacob; Polman, Jan; Alkema, Wynand

2008-07-01

Medline is a rich information source, from which links between genes and keywords describing biological processes, pathways, drugs, pathologies and diseases can be extracted. We developed a publicly available tool called CoPub that uses the information in the Medline database for the biological interpretation of microarray data. CoPub allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl.

Downregulation of acetyl-CoA synthetase 2 is a metabolic hallmark of tumor progression and aggressiveness in colorectal carcinoma.

PubMed

Bae, Jeong Mo; Kim, Jung Ho; Oh, Hyeon Jeong; Park, Hye Eun; Lee, Tae Hun; Cho, Nam-Yun; Kang, Gyeong Hoon

2017-02-01

Acetyl-CoA synthetase-2 is an emerging key enzyme for cancer metabolism, which supplies acetyl-CoA for tumor cells by capturing acetate as a carbon source under stressed conditions. However, implications of acetyl-CoA synthetase-2 in colorectal carcinoma may differ from other malignancies, because normal colonocytes use short-chain fatty acids as an energy source, which are supplied by fermentation of the intestinal flora. Here we analyzed acetyl-CoA synthetase-2 mRNA expression by reverse-transcription quantitative PCR in paired normal mucosa and tumor tissues of 12 colorectal carcinomas, and subsequently evaluated acetyl-CoA synthetase-2 protein expression by immunohistochemistry in 157 premalignant colorectal lesions, including 60 conventional adenomas and 97 serrated polyps, 1,106 surgically resected primary colorectal carcinomas, and 23 metastatic colorectal carcinomas in the liver. In reverse-transcription quantitative PCR analysis, acetyl-CoA synthetase-2 mRNA expression was significantly decreased in tumor tissues compared with corresponding normal mucosa tissues. In acetyl-CoA synthetase-2 immunohistochemistry analysis, all 157 colorectal polyps showed moderate-to-strong expression of acetyl-CoA synthetase-2. However, cytoplasmic acetyl-CoA synthetase-2 expression was downregulated (acetyl-CoA synthetase-2 low expression) in 771 (69.7%) of 1,106 colorectal carcinomas and 21 (91.3%) of 23 metastatic lesions. The colorectal carcinomas with acetyl-CoA synthetase-2-low expression were significantly associated with advanced TNM stage, poor differentiation, and frequent tumor budding. Regarding the molecular aspect, acetyl-CoA synthetase-2-low expression exhibited a tendency of frequent KRT7 expression and decreased KRT20 and CDX2 expression. In survival analysis, acetyl-CoA synthetase-2-low expression was an independent prognostic factor for poor 5-year progression-free survival (hazard ratio, 1.39; 95% confidence interval, 1.08-1.79; P=0.01). In conclusion, these findings suggest that downregulation of acetyl-CoA synthetase-2 expression is a metabolic hallmark of tumor progression and aggressive behavior in colorectal carcinoma.

CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses.

PubMed

Proost, Sebastian; Mutwil, Marek

2018-05-01

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

PubMed

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Interplay of Noisy Gene Expression and Dynamics Explains Patterns of Bacterial Operon Organization

NASA Astrophysics Data System (ADS)

Igoshin, Oleg

2011-03-01

Bacterial chromosomes are organized into operons -- sets of genes co-transcribed into polycistronic messenger RNA. Hypotheses explaining the emergence and maintenance of operons include proportional co-regulation, horizontal transfer of intact ``selfish'' operons, emergence via gene duplication, and co-production of physically interacting proteins to speed their association. We hypothesized an alternative: operons can reduce or increase intrinsic gene expression noise in a manner dependent on the post-translational interactions, thereby resulting in selection for or against operons in depending on the network architecture. We devised five classes of two-gene network modules and show that the effects of operons on intrinsic noise depend on class membership. Two classes exhibit decreased noise with co-transcription, two others reveal increased noise, and the remaining one does not show a significant difference. To test our modeling predictions we employed bioinformatic analysis to determine the relationship gene expression noise and operon organization. The results confirm the overrepresentation of noise-minimizing operon architectures and provide evidence against other hypotheses. Our results thereby suggest a central role for gene expression noise in selecting for or maintaining operons in bacterial chromosomes. This demonstrates how post-translational network dynamics may provide selective pressure for organizing bacterial chromosomes, and has practical consequences for designing synthetic gene networks. This work is supported by National Institutes of Health grant 1R01GM096189-01.

Employing conservation of co-expression to improve functional inference

PubMed Central

Daub, Carsten O; Sonnhammer, Erik LL

2008-01-01

Background Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species. Results We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method. Conclusion To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results. PMID:18808668

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

Tumour-specific HMG-CoAR is an independent predictor of recurrence free survival in epithelial ovarian cancer.

PubMed

Brennan, Donal J; Brändstedt, Jenny; Rexhepaj, Elton; Foley, Michael; Pontén, Fredrik; Uhlén, Mathias; Gallagher, William M; O'Connor, Darran P; O'Herlihy, Colm; Jirstrom, Karin

2010-04-01

Our group previously reported that tumour-specific expression of the rate-limiting enzyme in the mevalonate pathway, 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) is associated with more favourable tumour parameters and a good prognosis in breast cancer. In the present study, the prognostic value of HMG-CoAR expression was examined in tumours from a cohort of patients with primary epithelial ovarian cancer. HMG-CoAR expression was assessed using immunohistochemistry (IHC) on tissue microarrays (TMA) consisting of 76 ovarian cancer cases, analysed using automated algorithms to develop a quantitative scoring model. Kaplan Meier analysis and Cox proportional hazards modelling were used to estimate the risk of recurrence free survival (RFS). Seventy-two tumours were suitable for analysis. Cytoplasmic HMG-CoAR expression was present in 65% (n = 46) of tumours. No relationship was seen between HMG-CoAR and age, histological subtype, grade, disease stage, estrogen receptor or Ki-67 status. Patients with tumours expressing HMG-CoAR had a significantly prolonged RFS (p = 0.012). Multivariate Cox regression analysis revealed that HMG-CoAR expression was an independent predictor of improved RFS (RR = 0.49, 95% CI (0.25-0.93); p = 0.03) when adjusted for established prognostic factors such as residual disease, tumour stage and grade. HMG-CoAR expression is an independent predictor of prolonged RFS in primary ovarian cancer. As HMG-CoAR inhibitors, also known as statins, have demonstrated anti-neoplastic effects in vitro, further studies are required to evaluate HMG-CoAR expression as a surrogate marker of response to statin treatment, especially in conjunction with current chemotherapeutic regimens.

Tumour-specific HMG-CoAR is an independent predictor of recurrence free survival in epithelial ovarian cancer

PubMed Central

2010-01-01

Background Our group previously reported that tumour-specific expression of the rate-limiting enzyme in the mevalonate pathway, 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) is associated with more favourable tumour parameters and a good prognosis in breast cancer. In the present study, the prognostic value of HMG-CoAR expression was examined in tumours from a cohort of patients with primary epithelial ovarian cancer. Methods HMG-CoAR expression was assessed using immunohistochemistry (IHC) on tissue microarrays (TMA) consisting of 76 ovarian cancer cases, analysed using automated algorithms to develop a quantitative scoring model. Kaplan Meier analysis and Cox proportional hazards modelling were used to estimate the risk of recurrence free survival (RFS). Results Seventy-two tumours were suitable for analysis. Cytoplasmic HMG-CoAR expression was present in 65% (n = 46) of tumours. No relationship was seen between HMG-CoAR and age, histological subtype, grade, disease stage, estrogen receptor or Ki-67 status. Patients with tumours expressing HMG-CoAR had a significantly prolonged RFS (p = 0.012). Multivariate Cox regression analysis revealed that HMG-CoAR expression was an independent predictor of improved RFS (RR = 0.49, 95% CI (0.25-0.93); p = 0.03) when adjusted for established prognostic factors such as residual disease, tumour stage and grade. Conclusion HMG-CoAR expression is an independent predictor of prolonged RFS in primary ovarian cancer. As HMG-CoAR inhibitors, also known as statins, have demonstrated anti-neoplastic effects in vitro, further studies are required to evaluate HMG-CoAR expression as a surrogate marker of response to statin treatment, especially in conjunction with current chemotherapeutic regimens. PMID:20359358

Summary report on the evaluation of a 1977--1985 edited sorption data base for isotherm modeling

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

Polzer, W.L.; Beckman, R.J.; Fuentes, H.R.

1993-09-01

Sorption data bases collected by Los Alamos National Laboratory (LANL) from 1977 to 1985 for the Yucca Mountain Project.(YMP) have been inventoried and fitted with isotherm expressions. Effects of variables (e.g., particle size) on the isotherm were also evaluated. The sorption data are from laboratory batch measurements which were not designed specifically for isotherm modeling. However a limited number of data sets permitted such modeling. The analysis of those isotherm data can aid in the design of future sorption experiments and can provide expressions to be used in radionuclide transport modeling. Over 1200 experimental observations were inventoried for their adequacymore » to be modeled b isotherms and to evaluate the effects of variables on isotherms. About 15% of the observations provided suitable data sets for modeling. The data sets were obtained under conditions that include ambient temperature and two atmospheres, air and CO{sub 2}.« less

When is hub gene selection better than standard meta-analysis?

PubMed

Langfelder, Peter; Mischel, Paul S; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis.

An Integrated Cell Purification and Genomics Strategy Reveals Multiple Regulators of Pancreas Development

PubMed Central

Benitez, Cecil M.; Qu, Kun; Sugiyama, Takuya; Pauerstein, Philip T.; Liu, Yinghua; Tsai, Jennifer; Gu, Xueying; Ghodasara, Amar; Arda, H. Efsun; Zhang, Jiajing; Dekker, Joseph D.; Tucker, Haley O.; Chang, Howard Y.; Kim, Seung K.

2014-01-01

The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus. PMID:25330008

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

Skin Transcriptomes of common bottlenose dolphins (Tursiops truncatus) from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts.

PubMed

Neely, Marion G; Morey, Jeanine S; Anderson, Paul; Balmer, Brian C; Ylitalo, Gina M; Zolman, Eric S; Speakman, Todd R; Sinclair, Carrie; Bachman, Melannie J; Huncik, Kevin; Kucklick, John; Rosel, Patricia E; Mullin, Keith D; Rowles, Teri K; Schwacke, Lori H; Van Dolah, Frances M

2018-04-01

Common bottlenose dolphins serve as sentinels for the health of their coastal environments as they are susceptible to health impacts from anthropogenic inputs through both direct exposure and food web magnification. Remote biopsy samples have been widely used to reveal contaminant burdens in free-ranging bottlenose dolphins, but do not address the health consequences of this exposure. To gain insight into whether remote biopsies can also identify health impacts associated with contaminant burdens, we employed RNA sequencing (RNA-seq) to interrogate the transcriptomes of remote skin biopsies from 116 bottlenose dolphins from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts. Gene expression was analyzed using principal component analysis, differential expression testing, and gene co-expression networks, and the results correlated to season, location, and contaminant burden. Season had a significant impact, with over 60% of genes differentially expressed between spring/summer and winter months. Geographic location exhibited lesser effects on the transcriptome, with 23.5% of genes differentially expressed between the northern Gulf of Mexico and the southeastern U.S. Atlantic locations. Despite a large overlap between the seasonal and geographical gene sets, the pathways altered in the observed gene expression profiles were somewhat distinct. Co-regulated gene modules and differential expression analysis both identified epidermal development and cellular architecture pathways to be expressed at lower levels in animals from the northern Gulf of Mexico. Although contaminant burdens measured were not significantly different between regions, some correlation with contaminant loads in individuals was observed among co-expressed gene modules, but these did not include classical detoxification pathways. Instead, this study identified other, possibly downstream pathways, including those involved in cellular architecture, immune response, and oxidative stress, that may prove to be contaminant responsive markers in bottlenose dolphin skin. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Use of Co-occurrences for Temporal Expressions Annotation

NASA Astrophysics Data System (ADS)

Craveiro, Olga; Macedo, Joaquim; Madeira, Henrique

The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora.

Co-expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

PubMed

Mukund, Kavitha; Ward, Samuel R; Lieber, Richard L; Subramaniam, Shankar

2017-10-16

Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous workBotulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.

Blood gene expression profiles suggest altered immune function associated with symptoms of generalized anxiety disorder.

PubMed

Wingo, Aliza P; Gibson, Greg

2015-01-01

Prospective epidemiological studies found that generalized anxiety disorder (GAD) can impair immune function and increase risk for cardiovascular disease or events. Mechanisms underlying the physiological reverberations of anxiety, however, are still elusive. Hence, we aimed to investigate molecular processes mediating effects of anxiety on physical health using blood gene expression profiles of 336 community participants (157 anxious and 179 control). We examined genome-wide differential gene expression in anxiety, as well as associations between nine major modules of co-regulated transcripts in blood gene expression and anxiety. No significant differential expression was observed in women, but 631 genes were differentially expressed between anxious and control men at the false discovery rate of 0.1 after controlling for age, body mass index, race, and batch effect. Gene set enrichment analysis (GSEA) revealed that genes with altered expression levels in anxious men were involved in response of various immune cells to vaccination and to acute viral and bacterial infection, and in a metabolic network affecting traits of metabolic syndrome. Further, we found one set of 260 co-regulated genes to be significantly associated with anxiety in men after controlling for the relevant covariates, and demonstrate its equivalence to a component of the stress-related conserved transcriptional response to adversity profile. Taken together, our results suggest potential molecular pathways that can explain negative effects of GAD observed in epidemiological studies. Remarkably, even mild anxiety, which most of our participants had, was associated with observable changes in immune-related gene expression levels. Our findings generate hypotheses and provide incremental insights into molecular mechanisms mediating negative physiological effects of GAD. Published by Elsevier Inc.

Improved high-dimensional prediction with Random Forests by the use of co-data.

PubMed

Te Beest, Dennis E; Mes, Steven W; Wilting, Saskia M; Brakenhoff, Ruud H; van de Wiel, Mark A

2017-12-28

Prediction in high dimensional settings is difficult due to the large number of variables relative to the sample size. We demonstrate how auxiliary 'co-data' can be used to improve the performance of a Random Forest in such a setting. Co-data are incorporated in the Random Forest by replacing the uniform sampling probabilities that are used to draw candidate variables by co-data moderated sampling probabilities. Co-data here are defined as any type information that is available on the variables of the primary data, but does not use its response labels. These moderated sampling probabilities are, inspired by empirical Bayes, learned from the data at hand. We demonstrate the co-data moderated Random Forest (CoRF) with two examples. In the first example we aim to predict the presence of a lymph node metastasis with gene expression data. We demonstrate how a set of external p-values, a gene signature, and the correlation between gene expression and DNA copy number can improve the predictive performance. In the second example we demonstrate how the prediction of cervical (pre-)cancer with methylation data can be improved by including the location of the probe relative to the known CpG islands, the number of CpG sites targeted by a probe, and a set of p-values from a related study. The proposed method is able to utilize auxiliary co-data to improve the performance of a Random Forest.

Pinoresinol reductase 1 impacts lignin distribution during secondary cell wall biosynthesis in Arabidopsis

DOE PAGES

Zhao, Qiao; Zeng, Yining; Yin, Yanbin; ...

2014-08-05

In this paper, pinoresinol reductase (PrR) catalyzes the conversion of the lignan (-)-pinoresinol to (-)-lariciresinol in Arabidopsis thaliana, where it is encoded by two genes, PrR1 and PrR2, that appear to act redundantly. PrR1 is highly expressed in lignified inflorescence stem tissue, whereas PrR2 expression is barely detectable in stems. Co-expression analysis has indicated that PrR1 is co-expressed with many characterized genes involved in secondary cell wall biosynthesis, whereas PrR2 expression clusters with a different set of genes. The promoter of the PrR1 gene is regulated by the secondary cell wall related transcription factors SND1 and MYB46. The loss-of-function mutantmore » of PrR1 shows, in addition to elevated levels of pinoresinol, significantly decreased lignin content and a slightly altered lignin structure with lower abundance of cinnamyl alcohol end groups. Stimulated Raman scattering (SRS) microscopy analysis indicated that the lignin content of the prr1-1 loss-of-function mutant is similar to that of wild-type plants in xylem cells, which exhibit a normal phenotype, but is reduced in the fiber cells. Finally, together, these data suggest an association of the lignan biosynthetic enzyme encoded by PrR1 with secondary cell wall biosynthesis in fiber cells.« less

Identification of a set of genes showing regionally enriched expression in the mouse brain

PubMed Central

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa LC; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven JM

2008-01-01

Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression. PMID:18625066

Identification of a set of genes showing regionally enriched expression in the mouse brain.

PubMed

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa L C; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven J M

2008-07-14

The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

Identification of a core set of rhizobial infection genes using data from single cell-types.

PubMed

Chen, Da-Song; Liu, Cheng-Wu; Roy, Sonali; Cousins, Donna; Stacey, Nicola; Murray, Jeremy D

2015-01-01

Genome-wide expression studies on nodulation have varied in their scale from entire root systems to dissected nodules or root sections containing nodule primordia (NP). More recently efforts have focused on developing methods for isolation of root hairs from infected plants and the application of laser-capture microdissection technology to nodules. Here we analyze two published data sets to identify a core set of infection genes that are expressed in the nodule and in root hairs during infection. Among the genes identified were those encoding phenylpropanoid biosynthesis enzymes including Chalcone-O-Methyltransferase which is required for the production of the potent Nod gene inducer 4',4-dihydroxy-2-methoxychalcone. A promoter-GUS analysis in transgenic hairy roots for two genes encoding Chalcone-O-Methyltransferase isoforms revealed their expression in rhizobially infected root hairs and the nodule infection zone but not in the nitrogen fixation zone. We also describe a group of Rhizobially Induced Peroxidases whose expression overlaps with the production of superoxide in rhizobially infected root hairs and in nodules and roots. Finally, we identify a cohort of co-regulated transcription factors as candidate regulators of these processes.

Immunohistochemical and Image Analysis-Based Study Shows That Several Immune Checkpoints are Co-expressed in Non-Small Cell Lung Carcinoma Tumors.

PubMed

Parra, Edwin Roger; Villalobos, Pamela; Zhang, Jiexin; Behrens, Carmen; Mino, Barbara; Swisher, Stephen; Sepesi, Boris; Weissferdt, Annika; Kalhor, Neda; Heymach, John Victor; Moran, Cesar; Zhang, Jianjun; Lee, Jack; Rodriguez-Canales, Jaime; Gibbons, Don; Wistuba, Ignacio I

2018-06-01

The understanding of immune checkpoint molecules' co-expression in non-small cell lung carcinoma (NCLC) is important to potentially design combinatorial immunotherapy approaches. We studied 225 formalin-fixed, paraffin-embedded tumor tissues from stage I-III NCLCs - 142 adenocarcinomas (ADCs) and 83 squamous cell carcinomas (SCCs) - placed in tissue microarrays. Nine immune checkpoint markers were evaluated; four (programmed death ligand 1 [PD-L1], B7-H3, B7-H4, and indoleamine 2,3-dioxygenase 1 [IDO-1]) expressed predominantly in malignant cells (MCs) and five (inducible T cell costimulator, V-set immunoregulatory receptor, T-cell immunoglobulin mucin family member 3, lymphocyte activating 3, and OX40) expressed mostly in stromal tumor-associated inflammatory cells (TAICs). All markers were examined using a quantitative image analysis and correlated with clinicopathologic features, TAICs, and molecular characteristics. Using above the median value as positive expression in MCs and high density of TAICs expressing those markers, we identified higher expression of immune checkpoints in SCC than ADC. Common simultaneous expression by MCs was PD-L1 + B7-H3 + IDO-1 in ADC and PD-L1 + B7-H3, or B7-H3 + B7-H4, in SCC. TAICs expressing checkpoint were significantly higher in current smokers than in never smokers. Almost all the immune checkpoint markers showed positive correlation with TAICs expressing inflammatory cell markers. KRAS-mutant ADC specimens showed higher expression of PD-L1 in MCs and of B7-H3, T-cell immunoglobulin mucin family member 3, and IDO-1 in TAICs than wild type. Kaplan-Meier survival curves showed worse prognosis in ADC patients with higher B7-H4 expression by MCs. We found frequent immunohistochemical co-expression of immune checkpoints in surgically resected NCLC tumors and correlated with tumor histology, smoking history, tumor size, and the density of inflammatory cells and tumor mutational status. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome.

PubMed

Bush, Stephen J; Muriuki, Charity; McCulloch, Mary E B; Farquhar, Iseabail L; Clark, Emily L; Hume, David A

2018-04-24

mRNA-like long non-coding RNAs (lncRNAs) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. Thus, in many cases lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNAs, we compared de novo assembled lncRNAs derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNAs assembled in cattle and human. We then combined the novel lncRNAs with the sheep transcriptional atlas to identify co-regulated sets of protein-coding and non-coding loci. Few lncRNAs could be reproducibly assembled from a single dataset, even with deep sequencing of the same tissues from multiple animals. Furthermore, there was little sequence overlap between lncRNAs that were assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNAs to identify a consensus set of ruminant lncRNAs and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. In sheep, 20 to 30% of lncRNAs were located close to protein-coding genes with which they are strongly co-expressed, which is consistent with the evolutionary origin of some ncRNAs in enhancer sequences. Nevertheless, most of the lncRNAs are not co-expressed with neighbouring protein-coding genes. Alongside substantially expanding the ruminant lncRNA repertoire, the outcomes of our analysis demonstrate that stochastic sampling can be partly overcome by combining RNA-seq datasets from related species. This has practical implications for the future discovery of lncRNAs in other species.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

PubMed Central

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.

2016-01-01

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857

A Top-Down Performance Analysis of a Pegasus-Based Space Strike System

DTIC Science & Technology

1991-12-01

284): AP 1 O. coCO 4., cos 2 =~ +I Q ( QbO - 2) cos2 Cbo 28 This equation is useful for determining free-flight range for any set of burnout con...it may therefore be expressed in the manner given by Eq (26): cot1 - Qbo cos 2 Obo2 Qbo cos ¢ bo1 - cos2 kbo (27) Since \\/f1-cos7 Obo = sin Obo and...in general, cos a sin a = 1/2 x sin 2a, then Eq (27) can be further simplified to ’’ 2 cot - = 2csc20b, - cot Obo (28) 2 Qbo Rearranging tcrms results

Integrated analysis of long non-coding RNAs in human gastric cancer: An in silico study.

PubMed

Han, Weiwei; Zhang, Zhenyu; He, Bangshun; Xu, Yijun; Zhang, Jun; Cao, Weijun

2017-01-01

Accumulating evidence highlights the important role of long non-coding RNAs (lncRNAs) in a large number of biological processes. However, the knowledge of genome scale expression of lncRNAs and their potential biological function in gastric cancer is still lacking. Using RNA-seq data from 420 gastric cancer patients in The Cancer Genome Atlas (TCGA), we identified 1,294 lncRNAs differentially expressed in gastric cancer compared with adjacent normal tissues. We also found 247 lncRNAs differentially expressed between intestinal subtype and diffuse subtype. Survival analysis revealed 33 lncRNAs independently associated with patient overall survival, of which 6 lncRNAs were validated in the internal validation set. There were 181 differentially expressed lncRNAs located in the recurrent somatic copy number alterations (SCNAs) regions and their correlations between copy number and RNA expression level were also analyzed. In addition, we inferred the function of lncRNAs by construction of a co-expression network for mRNAs and lncRNAs. Together, this study presented an integrative analysis of lncRNAs in gastric cancer and provided a valuable resource for further functional research of lncRNAs in gastric cancer.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles.

PubMed

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.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles

PubMed Central

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

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

PubMed

Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

2014-07-01

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

The common transcriptional subnetworks of the grape berry skin in the late stages of ripening.

PubMed

Ghan, Ryan; Petereit, Juli; Tillett, Richard L; Schlauch, Karen A; Toubiana, David; Fait, Aaron; Cramer, Grant R

2017-05-30

Wine grapes are important economically in many countries around the world. Defining the optimum time for grape harvest is a major challenge to the grower and winemaker. Berry skins are an important source of flavor, color and other quality traits in the ripening stage. Senescent-like processes such as chloroplast disorganization and cell death characterize the late ripening stage. To better understand the molecular and physiological processes involved in the late stages of berry ripening, RNA-seq analysis of the skins of seven wine grape cultivars (Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay, Sauvignon Blanc and Semillon) was performed. RNA-seq analysis identified approximately 2000 common differentially expressed genes for all seven cultivars across four different berry sugar levels (20 to 26 °Brix). Network analyses, both a posteriori (standard) and a priori (gene co-expression network analysis), were used to elucidate transcriptional subnetworks and hub genes associated with traits in the berry skins of the late stages of berry ripening. These independent approaches revealed genes involved in photosynthesis, catabolism, and nucleotide metabolism. The transcript abundance of most photosynthetic genes declined with increasing sugar levels in the berries. The transcript abundance of other processes increased such as nucleic acid metabolism, chromosome organization and lipid catabolism. Weighted gene co-expression network analysis (WGCNA) identified 64 gene modules that were organized into 12 subnetworks of three modules or more and six higher order gene subnetworks. Some gene subnetworks were highly correlated with sugar levels and some subnetworks were highly enriched in the chloroplast and nucleus. The petal R package was utilized independently to construct a true small-world and scale-free complex gene co-expression network model. A subnetwork of 216 genes with the highest connectivity was elucidated, consistent with the module results from WGCNA. Hub genes in these subnetworks were identified including numerous members of the core circadian clock, RNA splicing, proteolysis and chromosome organization. An integrated model was constructed linking light sensing with alternative splicing, chromosome remodeling and the circadian clock. A common set of differentially expressed genes and gene subnetworks from seven different cultivars were examined in the skin of the late stages of grapevine berry ripening. A densely connected gene subnetwork was elucidated involving a complex interaction of berry senescent processes (autophagy), catabolism, the circadian clock, RNA splicing, proteolysis and epigenetic regulation. Hypotheses were induced from these data sets involving sugar accumulation, light, autophagy, epigenetic regulation, and fruit development. This work provides a better understanding of berry development and the transcriptional processes involved in the late stages of ripening.

Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells

PubMed Central

Mason, Mike J; Fan, Guoping; Plath, Kathrin; Zhou, Qing; Horvath, Steve

2009-01-01

Background Recent work has revealed that a core group of transcription factors (TFs) regulates the key characteristics of embryonic stem (ES) cells: pluripotency and self-renewal. Current efforts focus on identifying genes that play important roles in maintaining pluripotency and self-renewal in ES cells and aim to understand the interactions among these genes. To that end, we investigated the use of unsigned and signed network analysis to identify pluripotency and differentiation related genes. Results We show that signed networks provide a better systems level understanding of the regulatory mechanisms of ES cells than unsigned networks, using two independent murine ES cell expression data sets. Specifically, using signed weighted gene co-expression network analysis (WGCNA), we found a pluripotency module and a differentiation module, which are not identified in unsigned networks. We confirmed the importance of these modules by incorporating genome-wide TF binding data for key ES cell regulators. Interestingly, we find that the pluripotency module is enriched with genes related to DNA damage repair and mitochondrial function in addition to transcriptional regulation. Using a connectivity measure of module membership, we not only identify known regulators of ES cells but also show that Mrpl15, Msh6, Nrf1, Nup133, Ppif, Rbpj, Sh3gl2, and Zfp39, among other genes, have important roles in maintaining ES cell pluripotency and self-renewal. We also report highly significant relationships between module membership and epigenetic modifications (histone modifications and promoter CpG methylation status), which are known to play a role in controlling gene expression during ES cell self-renewal and differentiation. Conclusion Our systems biologic re-analysis of gene expression, transcription factor binding, epigenetic and gene ontology data provides a novel integrative view of ES cell biology. PMID:19619308

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

PubMed

Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan; Kim, Hoon; Barthel, Floris; Jiang, Tao; Hess, Kenneth R; Verhaak, Roel G W

2017-06-01

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Resolving stem and progenitor cells in the adult mouse incisor through gene co-expression analysis

PubMed Central

Seidel, Kerstin; Marangoni, Pauline; Tang, Cynthia; Houshmand, Bahar; Du, Wen; Maas, Richard L; Murray, Steven; Oldham, Michael C; Klein, Ophir D

2017-01-01

Investigations into stem cell-fueled renewal of an organ benefit from an inventory of cell type-specific markers and a deep understanding of the cellular diversity within stem cell niches. Using the adult mouse incisor as a model for a continuously renewing organ, we performed an unbiased analysis of gene co-expression relationships to identify modules of co-expressed genes that represent differentiated cells, transit-amplifying cells, and residents of stem cell niches. Through in vivo lineage tracing, we demonstrated the power of this approach by showing that co-expression module members Lrig1 and Igfbp5 define populations of incisor epithelial and mesenchymal stem cells. We further discovered that two adjacent mesenchymal tissues, the periodontium and dental pulp, are maintained by distinct pools of stem cells. These findings reveal novel mechanisms of incisor renewal and illustrate how gene co-expression analysis of intact biological systems can provide insights into the transcriptional basis of cellular identity. DOI: http://dx.doi.org/10.7554/eLife.24712.001 PMID:28475038

Overexpression of OsSAP16 Regulates Photosynthesis and the Expression of a Broad Range of Stress Response Genes in Rice (Oryza sativa L.).

PubMed

Wang, Fei; Coe, Robert A; Karki, Shanta; Wanchana, Samart; Thakur, Vivek; Henry, Amelia; Lin, Hsiang-Chun; Huang, Jianliang; Peng, Shaobing; Quick, William Paul

2016-01-01

This study set out to identify and characterize transcription factors regulating photosynthesis in rice. Screening populations of rice T-DNA activation lines led to the identification of a T-DNA mutant with an increase in intrinsic water use efficiency (iWUE) under well-watered conditions. Flanking sequence analysis showed that the T-DNA construct was located upstream of LOC_Os07g38240 (OsSAP16) encoding for a stress-associated protein (SAP). A second mutant identified with activation in the same gene exhibited the same phenotype; expression of OsSAP16 was shown to be enhanced in both lines. There were no differences in stomatal development or morphology in either of these mutants, although overexpression of OsSAP16 reduced stomatal conductance. This phenotype limited CO2 uptake and the rate of photosynthesis, which resulted in the accumulation of less biomass in the two mutants. Whole transcriptome analysis showed that overexpression of OsSAP16 led to global changes in gene expression consistent with the function of zinc-finger transcription factors. These results show that the gene is involved in modulating the response of rice to drought stress through regulation of the expression of a set of stress-associated genes.

Overexpression of OsSAP16 Regulates Photosynthesis and the Expression of a Broad Range of Stress Response Genes in Rice (Oryza sativa L.)

PubMed Central

Wang, Fei; Coe, Robert A.; Karki, Shanta; Wanchana, Samart; Thakur, Vivek; Henry, Amelia; Lin, Hsiang-Chun; Huang, Jianliang; Peng, Shaobing; Quick, William Paul

2016-01-01

This study set out to identify and characterize transcription factors regulating photosynthesis in rice. Screening populations of rice T-DNA activation lines led to the identification of a T-DNA mutant with an increase in intrinsic water use efficiency (iWUE) under well-watered conditions. Flanking sequence analysis showed that the T-DNA construct was located upstream of LOC_Os07g38240 (OsSAP16) encoding for a stress-associated protein (SAP). A second mutant identified with activation in the same gene exhibited the same phenotype; expression of OsSAP16 was shown to be enhanced in both lines. There were no differences in stomatal development or morphology in either of these mutants, although overexpression of OsSAP16 reduced stomatal conductance. This phenotype limited CO2 uptake and the rate of photosynthesis, which resulted in the accumulation of less biomass in the two mutants. Whole transcriptome analysis showed that overexpression of OsSAP16 led to global changes in gene expression consistent with the function of zinc-finger transcription factors. These results show that the gene is involved in modulating the response of rice to drought stress through regulation of the expression of a set of stress-associated genes. PMID:27303811

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

Methyl green and nitrotetrazolium blue chloride co-expression in colon tissue: A hyperspectral microscopic imaging analysis

NASA Astrophysics Data System (ADS)

Li, Qingli; Liu, Hongying; Wang, Yiting; Sun, Zhen; Guo, Fangmin; Zhu, Jianzhong

2014-12-01

Histological observation of dual-stained colon sections is usually performed by visual observation under a light microscope, or by viewing on a computer screen with the assistance of image processing software in both research and clinical settings. These traditional methods are usually not sufficient to reliably differentiate spatially overlapping chromogens generated by different dyes. Hyperspectral microscopic imaging technology offers a solution for these constraints as the hyperspectral microscopic images contain information that allows differentiation between spatially co-located chromogens with similar but different spectra. In this paper, a hyperspectral microscopic imaging (HMI) system is used to identify methyl green and nitrotetrazolium blue chloride in dual-stained colon sections. Hyperspectral microscopic images are captured and the normalized score algorithm is proposed to identify the stains and generate the co-expression results. Experimental results show that the proposed normalized score algorithm can generate more accurate co-localization results than the spectral angle mapper algorithm. The hyperspectral microscopic imaging technology can enhance the visualization of dual-stained colon sections, improve the contrast and legibility of each stain using their spectral signatures, which is helpful for pathologist performing histological analyses.

Analysis of co-occurrence toponyms in web pages based on complex networks

NASA Astrophysics Data System (ADS)

Zhong, Xiang; Liu, Jiajun; Gao, Yong; Wu, Lun

2017-01-01

A large number of geographical toponyms exist in web pages and other documents, providing abundant geographical resources for GIS. It is very common for toponyms to co-occur in the same documents. To investigate these relations associated with geographic entities, a novel complex network model for co-occurrence toponyms is proposed. Then, 12 toponym co-occurrence networks are constructed from the toponym sets extracted from the People's Daily Paper documents of 2010. It is found that two toponyms have a high co-occurrence probability if they are at the same administrative level or if they possess a part-whole relationship. By applying complex network analysis methods to toponym co-occurrence networks, we find the following characteristics. (1) The navigation vertices of the co-occurrence networks can be found by degree centrality analysis. (2) The networks express strong cluster characteristics, and it takes only several steps to reach one vertex from another one, implying that the networks are small-world graphs. (3) The degree distribution satisfies the power law with an exponent of 1.7, so the networks are free-scale. (4) The networks are disassortative and have similar assortative modes, with assortative exponents of approximately 0.18 and assortative indexes less than 0. (5) The frequency of toponym co-occurrence is weakly negatively correlated with geographic distance, but more strongly negatively correlated with administrative hierarchical distance. Considering the toponym frequencies and co-occurrence relationships, a novel method based on link analysis is presented to extract the core toponyms from web pages. This method is suitable and effective for geographical information retrieval.

Study on γH2AX Expression of Lymphocytes as a Biomarker In Radiation Biodosimetry

PubMed Central

Pan, Yan; Gao, Gang; Ruan, Jian Lei; Liu, Jian Xiang

2016-01-01

Flow cytometry analysis was used to detect the changes of γH2AX protein expression in human peripheral blood lymphocytes. In the dose-effect study, the expression of γH2AX was detected 1 h after irradiation with 60Co γ-rays at doses of 0, 0.5, 1, 2, 4, and 6 Gy. Blood was cultivated for 0, 1, 2, 4, 6, 12, and 24 h after 4 Gy 60Co γ-rays irradiation for the time-effect study. At the same time, the blood was divided into four treatment groups (ultraviolet [UV] irradiation, 60Co γ-rays irradiation, UV plus 60Co γ-rays irradiation, and control group) to detect the changes of protein expression of γH2AX. The results showed that the γH2AX protein expression was in dose-effect and time-effect relationship with 60Co γ-rays. The peak expression of γH2AX was at 1 h after 60Co γ-ray irradiation and began to decrease quickly. Compared to irradiation with 60Co γ-rays alone, the expression of γH2AX was not significantly changed after irradiation with 60Co γ-rays plus UV. Dose rate did not significantly change the expression of γH2AX. The expression of γH2AX induced by 60Co γ-rays was basically consistent with the mice in vivo and in vitro. The results revealed that the detection of γH2AX protein expression changes in peripheral blood lymphocyte by flow cytometry analysis is reasonable and may be useful for biodosimetry. PMID:28217286

Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design.

PubMed

Li, Jianqiang; Zhou, Doudou; Qiu, Weiliang; Shi, Yuliang; Yang, Ji-Jiang; Chen, Shi; Wang, Qing; Pan, Hui

2018-01-12

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer.

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

DOE PAGES

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey; ...

2017-01-21

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

Co-Option and De Novo Gene Evolution Underlie Molluscan Shell Diversity

PubMed Central

Aguilera, Felipe; McDougall, Carmel

2017-01-01

Abstract Molluscs fabricate shells of incredible diversity and complexity by localized secretions from the dorsal epithelium of the mantle. Although distantly related molluscs express remarkably different secreted gene products, it remains unclear if the evolution of shell structure and pattern is underpinned by the differential co-option of conserved genes or the integration of lineage-specific genes into the mantle regulatory program. To address this, we compare the mantle transcriptomes of 11 bivalves and gastropods of varying relatedness. We find that each species, including four Pinctada (pearl oyster) species that diverged within the last 20 Ma, expresses a unique mantle secretome. Lineage- or species-specific genes comprise a large proportion of each species’ mantle secretome. A majority of these secreted proteins have unique domain architectures that include repetitive, low complexity domains (RLCDs), which evolve rapidly, and have a proclivity to expand, contract and rearrange in the genome. There are also a large number of secretome genes expressed in the mantle that arose before the origin of gastropods and bivalves. Each species expresses a unique set of these more ancient genes consistent with their independent co-option into these mantle gene regulatory networks. From this analysis, we infer lineage-specific secretomes underlie shell diversity, and include both rapidly evolving RLCD-containing proteins, and the continual recruitment and loss of both ancient and recently evolved genes into the periphery of the regulatory network controlling gene expression in the mantle epithelium. PMID:28053006

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

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

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

Three Approaches to Green Computing on Campus

ERIC Educational Resources Information Center

Thompson, John T.

2009-01-01

A "carbon footprint" is the "total set of greenhouse gas emissions caused directly and indirectly by an (individual, event, organization, and product) expressed as CO2" emissions. Since CO2 emissions are indicative of energy use, the higher the associated CO2 emissions, typically the greater the associated costs. A typical desktop PC system…

Exploring the Diagnostic Potential of Immune Biomarker Co-expression in Gulf War Illness.

PubMed

Broderick, Gordon; Fletcher, Mary Ann; Gallagher, Michael; Barnes, Zachary; Vernon, Suzanne D; Klimas, Nancy G

2018-01-01

Complex disorders like Gulf War illness (GWI) often defy diagnosis on the basis of a single biomarker and may only be distinguishable by considering the co-expression of multiple markers measured in response to a challenge. We demonstrate the practical application of such an approach using an example where blood was collected from 26 GWI, 13 healthy control subjects, and 9 unhealthy controls with chronic fatigue at three points during a graded exercise challenge. A 3-way multivariate projection model based on 12 markers of endocrine and immune function was constructed using a training set of n = 10 GWI and n = 11 healthy controls. These groups were separated almost completely on the basis of two co-expression patterns. In a separate test set these same features allowed for discrimination of new GWI subjects (n = 16) from unhealthy (n = 9) and healthy control subjects with a sensitivity of 70% and a specificity of 90%.

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.

PubMed

Yang, Jing; Yu, Hui; Liu, Bao-Hong; Zhao, Zhongming; Liu, Lei; Ma, Liang-Xiao; Li, Yi-Xue; Li, Yuan-Yuan

2013-01-01

Differential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner. To advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named "Differential Regulation Analysis" (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject. With ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical. DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.

mESAdb: microRNA Expression and Sequence Analysis Database

PubMed Central

Kaya, Koray D.; Karakülah, Gökhan; Yakıcıer, Cengiz M.; Acar, Aybar C.; Konu, Özlen

2011-01-01

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data. PMID:21177657

mESAdb: microRNA expression and sequence analysis database.

PubMed

Kaya, Koray D; Karakülah, Gökhan; Yakicier, Cengiz M; Acar, Aybar C; Konu, Ozlen

2011-01-01

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

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

Co-expression of midkine and pleiotrophin predicts poor survival in human glioma.

PubMed

Ma, Jinyang; Lang, Bojuan; Wang, Xiongwei; Wang, Lei; Dong, Yuanxun; Hu, Huojun

2014-11-01

The aim of this study was to investigate whether co-expression of midkine (MK) and pleiotrophin (PTN) has prognostic relevance in human gliomas. Immunohistochemistry was used to investigate the expression of MK and PTN proteins in 168 patients with gliomas. The levels of MK and PTN mRNA in glioma tissues and paratumor tissues were evaluated in 45 paired cases by quantitative real-time polymerase chain reaction (qRT-PCR). Kaplan-Meier survival analysis was performed to assess prognostic significance. The expression levels of MK and PTN proteins in glioma tissue were both significantly higher (both p<0.001) than those in paratumor tissues on immunohistochemistry analysis, which was confirmed by qRT-PCR analysis. Additionally, the overexpression of either MK or PTN was significantly associated with the World Health Organization Grade (p=0.001 and 0.034, respectively), low Karnofsky Performance Status (KPS) score (p=0.022 and 0.001, respectively), time to recurrence (p=0.043 and 0.011, respectively) and poor overall survival (p=0.018 and 0.001, respectively). Multivariate Cox proportional-hazards regression analysis revealed that increased expressions of MK and PTN were both independent prognostic factors for poor overall survival (p=0.030 and 0.022, respectively). Furthermore, the co-expression of MK and PTN was more significantly (p=0.003) associated with adverse prognosis in patients with gliomas than the respective expression of MK or PTN alone. To our knowledge, these findings are the first to indicate that the co-expression of MK and PTN is significantly correlated with prognosis in glioma patients, suggesting that the co-expression of these proteins may be used as both an early diagnostic and independent prognostic marker. Copyright © 2014 Elsevier Ltd. All rights reserved.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.

PubMed

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T

2016-01-04

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Effects of threshold on the topology of gene co-expression networks.

PubMed

Couto, Cynthia Martins Villar; Comin, César Henrique; Costa, Luciano da Fontoura

2017-09-26

Several developments regarding the analysis of gene co-expression profiles using complex network theory have been reported recently. Such approaches usually start with the construction of an unweighted gene co-expression network, therefore requiring the selection of a suitable threshold defining which pairs of vertices will be connected. We aimed at addressing such an important problem by suggesting and comparing five different approaches for threshold selection. Each of the methods considers a respective biologically-motivated criterion for electing a potentially suitable threshold. A set of 21 microarray experiments from different biological groups was used to investigate the effect of applying the five proposed criteria to several biological situations. For each experiment, we used the Pearson correlation coefficient to measure the relationship between each gene pair, and the resulting weight matrices were thresholded considering several values, generating respective adjacency matrices (co-expression networks). Each of the five proposed criteria was then applied in order to select the respective threshold value. The effects of these thresholding approaches on the topology of the resulting networks were compared by using several measurements, and we verified that, depending on the database, the impact on the topological properties can be large. However, a group of databases was verified to be similarly affected by most of the considered criteria. Based on such results, it can be suggested that when the generated networks present similar measurements, the thresholding method can be chosen with greater freedom. If the generated networks are markedly different, the thresholding method that better suits the interests of each specific research study represents a reasonable choice.

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

PubMed

Yu, Hua; Jiao, Bingke; Lu, Lu; Wang, Pengfei; Chen, Shuangcheng; Liang, Chengzhi; Liu, Wei

2018-01-01

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

Investigation of Antigen-Antibody Interactions of Sulfonamides with a Monoclonal Antibody in a Fluorescence Polarization Immunoassay Using 3D-QSAR Models

PubMed Central

Wang, Zhanhui; Kai, Zhenpeng; Beier, Ross C.; Shen, Jianzhong; Yang, Xinling

2012-01-01

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAbSMR) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The affinities of the MAbSMR, expressed as Log10IC50, for 17 sulfonamide analogs were determined by competitive fluorescence polarization immunoassay (FPIA). The results demonstrated that the proposed pharmacophore model containing two hydrogen-bond acceptors, two hydrogen-bond donors and two hydrophobic centers characterized the structural features of the sulfonamides necessary for MAbSMR binding. Removal of two outliers from the initial set of 17 sulfonamide analogs improved the predictability of the models. The 3D-QSAR models of 15 sulfonamides based on CoMFA and CoMSIA resulted in q2 cv values of 0.600 and 0.523, and r2 values of 0.995 and 0.994, respectively, which indicates that both methods have significant predictive capability. Connolly surface analysis, which mainly focused on steric force fields, was performed to complement the results from CoMFA and CoMSIA. This novel study combining FPIA with pharmacophore modeling demonstrates that multidisciplinary research is useful for investigating antigen-antibody interactions and also may provide information required for the design of new haptens. PMID:22754368

Analysis of Pacific oyster larval proteome and its response to high-CO2.

PubMed

Dineshram, R; Wong, Kelvin K W; Xiao, Shu; Yu, Ziniu; Qian, Pei Yuan; Thiyagarajan, Vengatesen

2012-10-01

Most calcifying organisms show depressed metabolic, growth and calcification rates as symptoms to high-CO(2) due to ocean acidification (OA) process. Analysis of the global expression pattern of proteins (proteome analysis) represents a powerful tool to examine these physiological symptoms at molecular level, but its applications are inadequate. To address this knowledge gap, 2-DE coupled with mass spectrophotometer was used to compare the global protein expression pattern of oyster larvae exposed to ambient and to high-CO(2). Exposure to OA resulted in marked reduction of global protein expression with a decrease or loss of 71 proteins (18% of the expressed proteins in control), indicating a wide-spread depression of metabolic genes expression in larvae reared under OA. This is, to our knowledge, the first proteome analysis that provides insights into the link between physiological suppression and protein down-regulation under OA in oyster larvae. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection.

PubMed

Zhang, Jinfeng; Zhao, Wenjuan; Fu, Rong; Fu, Chenglin; Wang, Lingxia; Liu, Huainian; Li, Shuangcheng; Deng, Qiming; Wang, Shiquan; Zhu, Jun; Liang, Yueyang; Li, Ping; Zheng, Aiping

2018-05-05

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.

PubMed

Tintle, Nathan L; Sitarik, Alexandra; Boerema, Benjamin; Young, Kylie; Best, Aaron A; Dejongh, Matthew

2012-08-08

Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

A cross-species bi-clustering approach to identifying conserved co-regulated genes.

PubMed

Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo

2016-06-15

A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes. We propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared to the two-step method and several recent joint clustering methods. We then applied this approach to two real world datasets of gene expression during the pre-implantation embryonic development of the human and mouse. Co-regulated genes consistent between the human and mouse were identified, offering insights into conserved functions, as well as similarities and differences in genome activation timing between the human and mouse embryos. The R package containing the implementation of the proposed method in C ++ is available at: https://github.com/JavonSun/mvbc.git and also at the R platform https://www.r-project.org/ jinbo@engr.uconn.edu. © The Author 2016. Published by Oxford University Press.

Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma.

PubMed

Wan, Qi; Tang, Jing; Han, Yu; Wang, Dan

2018-01-01

Uveal melanoma is an aggressive cancer which has a high percentage recurrence and with a worse prognosis. Identify the potential prognostic markers of uveal melanoma may provide information for early detection of recurrence and treatment. RNA sequence data of uveal melanoma and patient clinic traits were obtained from The Cancer Genome Atlas (TCGA) database. Co-expression modules were built by weighted gene co -expression network analysis (WGCNA) and applied to investigate the relationship underlying modules and clinic traits. Besides, functional enrichment analysis was performed on these co-expression genes from interested modules. First, using WGCNA, identified 21 co-expression modules were constructed by the 10975 genes from the 80 human uveal melanoma samples. The number of genes in these modules ranged from 42 to 5091. Found four co -expression modules significantly correlated with three clinic traits (status, recurrence and recurrence Time). Module red, and purple positively correlated with patient's life status and recurrence Time. Module green positively correlates with recurrence. The result of functional enrichment analysis showed that the module magenta was mainly enriched genetic material assemble processes, the purple module was mainly enriched in tissue homeostasis and melanosome membrane and the module red was mainly enriched metastasis of cell, suggesting its critical role in the recurrence and development of the disease. Additionally, identified the hug gene (top connectivity with other genes) in each module. The hub gene SLC17A7, NTRK2, ABTB1 and ADPRHL1 might play a vital role in recurrence of uveal melanoma. Our findings provided the framework of co-expression gene modules of uveal melanoma and identified some prognostic markers might be detection of recurrence and treatment for uveal melanoma. Copyright © 2017 Elsevier Ltd. All rights reserved.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

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

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

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.

Comparison of co-expression measures: mutual information, correlation, and model based indices.

PubMed

Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI networks can safely be replaced by correlation networks when it comes to measuring co-expression relationships in stationary data.

Genetic transformation of Dichanthium annulatum (Forssk)--an apomictic tropical forage grass.

PubMed

Dalton, S J; Bettany, A J E; Bhat, V; Gupta, M G; Bailey, K; Timms, E; Morris, P

2003-06-01

Eleven Dichanthium annulatum (Forssk) plants were regenerated from embryogenic callus co-transformed with two plasmids encoding either the hygromycin phosphotransferase gene (hph) or the beta-glucuronidase (GUS) gene (uidA). Analysis of these putative transformants showed that three plants were transformed with the hph gene, showed the presence of the hph transcript and expressed hygromycin resistance after transfer to soil. Two of these also contained the uidA gene but did not express GUS and were shown to be the same transformation event. All three of the transformants set seed. Hygromycin resistance varied from 68-100% in the progeny of the three transformants. Transgene transmission appeared to have been mainly through apomixis.

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

PubMed

Rotival, Maxime; Zeller, Tanja; Wild, Philipp S; Maouche, Seraya; Szymczak, Silke; Schillert, Arne; Castagné, Raphaele; Deiseroth, Arne; Proust, Carole; Brocheton, Jessy; Godefroy, Tiphaine; Perret, Claire; Germain, Marine; Eleftheriadis, Medea; Sinning, Christoph R; Schnabel, Renate B; Lubos, Edith; Lackner, Karl J; Rossmann, Heidi; Münzel, Thomas; Rendon, Augusto; Erdmann, Jeanette; Deloukas, Panos; Hengstenberg, Christian; Diemert, Patrick; Montalescot, Gilles; Ouwehand, Willem H; Samani, Nilesh J; Schunkert, Heribert; Tregouet, David-Alexandre; Ziegler, Andreas; Goodall, Alison H; Cambien, François; Tiret, Laurence; Blankenberg, Stefan

2011-12-01

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

PubMed Central

Li, Wenyuan; Liu, Chun-Chi; Zhang, Tong; Li, Haifeng; Waterman, Michael S.; Zhou, Xianghong Jasmine

2011-01-01

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks. PMID:21698123

High-resolution gene expression data from blastoderm embryos of the scuttle fly Megaselia abdita

PubMed Central

Wotton, Karl R; Jiménez-Guri, Eva; Crombach, Anton; Cicin-Sain, Damjan; Jaeger, Johannes

2015-01-01

Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, quantified expression profiles, extracted positions of expression boundaries, and integrated expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution. PMID:25977812

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

Aging-like Changes in the Transcriptome of Irradiated Microglia

PubMed Central

Li, Matthew D.; Burns, Terry C.; Kumar, Sunny; Morgan, Alexander A.; Sloan, Steven A.; Palmer, Theo D.

2014-01-01

Whole brain irradiation remains important in the management of brain tumors. Although necessary for improving survival outcomes, cranial irradiation also results in cognitive decline in long-term survivors. A chronic inflammatory state characterized by microglial activation has been implicated in radiation-induced brain injury. We here provide the first comprehensive transcriptional profile of irradiated microglia. Fluorescence-activated cell sorting (FACS) was used to isolate CD11b+ microglia from the hippocampi of C57BL/6 and Balb/c mice 1 month after 10Gy cranial irradiation. Affymetrix gene expression profiles were evaluated using linear modeling, rank product analyses. One month after irradiation, a conserved irradiation signature across strains was identified, comprising 448 and 85 differentially up- and down-regulated genes, respectively. Gene set enrichment analysis (GSEA) demonstrated enrichment for inflammation, including M1 macrophage-associated genes, but also an unexpected enrichment for extracellular matrix and blood coagulation-related gene sets, in contrast previously described microglial states. Weighted gene co-expression network analysis (WGCNA) confirmed these findings and further revealed alterations in mitochondrial function. The RNA-seq transcriptome of microglia 24h post-radiation proved similar to the 1-month transcriptome, but additionally featured alterations in apoptotic and lysosomal gene expression. Re-analysis of published aging mouse microglia transcriptome data demonstrated striking similarity to the 1 month irradiated microglia transcriptome, suggesting that shared mechanisms may underlie aging and chronic irradiation-induced cognitive decline. PMID:25690519

Gas, dust, stars, star formation, and their evolution in M 33 at giant molecular cloud scales

NASA Astrophysics Data System (ADS)

Komugi, Shinya; Miura, Rie E.; Kuno, Nario; Tosaki, Tomoka

2018-06-01

We report on a multi-parameter analysis of giant molecular clouds (GMCs) in the nearby spiral galaxy M 33. A catalog of GMCs identifed in 12CO(J = 3-2) was used to compile associated 12CO(J = 1-0), dust, stellar mass, and star formation rate. Each of the 58 GMCs are categorized by their evolutionary stage. Applying the principal component analysis on these parameters, we construct two principal components, PC1 and PC2, which retain 75% of the information from the original data set. PC1 is interpreted as expressing the total interstellar matter content, and PC2 as the total activity of star formation. Young (< 10 Myr) GMCs occupy a distinct region in the PC1-PC2 plane, with lower interstellar medium (ISM) content and star formation activity compared to intermediate-age and older clouds. Comparison of average cloud properties in different evolutionary stages imply that GMCs may be heated or grow denser and more massive via aggregation of diffuse material in their first ˜ 10 Myr. The PCA also objectively identified a set of tight relations between ISM and star formation. The ratio of the two CO lines is nearly constant, but weakly modulated by massive star formation. Dust is more strongly correlated with the star formation rate than the CO lines, supporting recent findings that dust may trace molecular gas better than CO. Stellar mass contributes weakly to the star formation rate, reminiscent of an extended form of the Schmidt-Kennicutt relation with the molecular gas term substituted by dust.

Gas, dust, stars, star formation, and their evolution in M 33 at giant molecular cloud scales

NASA Astrophysics Data System (ADS)

Komugi, Shinya; Miura, Rie E.; Kuno, Nario; Tosaki, Tomoka

2018-04-01

We report on a multi-parameter analysis of giant molecular clouds (GMCs) in the nearby spiral galaxy M 33. A catalog of GMCs identifed in 12CO(J = 3-2) was used to compile associated 12CO(J = 1-0), dust, stellar mass, and star formation rate. Each of the 58 GMCs are categorized by their evolutionary stage. Applying the principal component analysis on these parameters, we construct two principal components, PC1 and PC2, which retain 75% of the information from the original data set. PC1 is interpreted as expressing the total interstellar matter content, and PC2 as the total activity of star formation. Young (< 10 Myr) GMCs occupy a distinct region in the PC1-PC2 plane, with lower interstellar medium (ISM) content and star formation activity compared to intermediate-age and older clouds. Comparison of average cloud properties in different evolutionary stages imply that GMCs may be heated or grow denser and more massive via aggregation of diffuse material in their first ˜ 10 Myr. The PCA also objectively identified a set of tight relations between ISM and star formation. The ratio of the two CO lines is nearly constant, but weakly modulated by massive star formation. Dust is more strongly correlated with the star formation rate than the CO lines, supporting recent findings that dust may trace molecular gas better than CO. Stellar mass contributes weakly to the star formation rate, reminiscent of an extended form of the Schmidt-Kennicutt relation with the molecular gas term substituted by dust.

Expression of adhesion and extracellular matrix genes in human blastocysts upon attachment in a 2D co-culture system.

PubMed

Aberkane, A; Essahib, W; Spits, C; De Paepe, C; Sermon, K; Adriaenssens, T; Mackens, S; Tournaye, H; Brosens, J J; Van de, Velde H

2018-05-26

What are the changes in human embryos, in terms of morphology and gene expression, upon attachment to endometrial epithelial cells? Apposition and adhesion of human blastocysts to endometrial epithelial cells are predominantly initiated at the embryonic pole and these steps are associated with changes in expression of adhesion and extracellular matrix (ECM) genes in the embryo. Both human and murine embryos have been co-cultured with Ishikawa cells, although embryonic gene expression associated with attachment has not yet been investigated in an in-vitro implantation model. Vitrified human blastocysts were warmed and co-cultured for up to 48 h with Ishikawa cells, a model cell line for receptive endometrial epithelium. Six-days post fertilisation (6dpf) human embryos were co-cultured with Ishikawa cells for 12 h, 24 h (7dpf) or 48 h (8dpf) and attachment rate and morphological development investigated. Expression of 84 adhesion and ECM genes was analysed by quantitative PCR. Immunofluorescence microscopy was used to assess the expression of three informative genes at the protein level. Data are reported on 115 human embryos. Mann-Whitney U was used for statistical analysis between two groups, with P < 0.05 considered significant. The majority of embryos attached to Ishikawa cells at the level of the polar trophectoderm; 41% of co-cultured embryos were loosely attached after 12 h and 86% firmly attached after 24 h. Outgrowth of hCG-positive embryonic cells at 8dpf indicated differentiation of trophectoderm into invasive syncytiotrophoblast. Gene expression analysis was performed on loosely attached and unattached embryos co-cultured with Ishikawa cells for 12 h. In contrast to unattached embryos, loosely attached embryos expressed THBS1, TNC, COL12A1, CTNND2, ITGA3, ITGAV, and LAMA3 and had significantly higher CD44 and TIMP1 transcript levels (P = 0.014 and P = 0.029, respectively). LAMA3, THBS1 and TNC expression was validated at the protein level in firmly attached 7dpf embryos. Thrombospondin 1 (THBS1) resided in the cytoplasm of embryonic cells whereas laminin subunit alpha 3 (LAMA3) and tenascin C (TNC) were expressed on the cell surface of trophectoderm cells. Incubation with a neutralizing TNC antibody did not affect the rate of embryo attachment or hCG secretion. None. This in-vitro study made use of an endometrial adenocarcinoma cell line to mimic receptive luminal epithelium. Also, the number of embryos was limited. Contamination of recovered embryos with Ishikawa cells was unlikely based on their differential gene expression profiles. Taken together, we provide a 'proof of concept' that initiation of the implantation process coincides with the induction of specific embryonic genes. Genome-wide expression profiling of a larger sample set may provide insights into the molecular embryonic pathways underlying successful or failed implantation. A.A. was supported by a grant from the "Instituut voor Innovatie door Wetenschap en Technologie" (IWT, 121716, Flanders, Belgium). This work was supported by the "Wetenschappelijk Fonds Willy Gepts" (WFWG G142 and G170, Universitair Ziekenhuis Brussel). The authors declare no conflict of interest.

A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

PubMed Central

Snijders, Tom A.B.; Lomi, Alessandro; Torló, Vanina Jasmine

2012-01-01

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency. The empirical value of the model is demonstrated by examining how employment preferences co-evolve with friendship and advice relations in a group of seventy-five MBA students. The analysis shows that activity in the two-mode network, as expressed by number of employment preferences, is related to activity in the friendship network, as expressed by outdegrees. Further, advice ties between students lead to agreement with respect to employment preferences. In addition, considering the multiplexity of advice and friendship ties yields a better understanding of the dynamics of the advice relation: tendencies to reciprocation and homophily in advice relations are mediated to an important extent by friendship relations. The discussion pays attention to the implications of this study in the broader context of current efforts to model the co-evolutionary dynamics of social networks and individual behavior. PMID:23690653

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

DNA microarray analysis of Methanosarcina mazei Gö1 reveals adaptation to different methanogenic substrates.

PubMed

Hovey, Raymond; Lentes, Sabine; Ehrenreich, Armin; Salmon, Kirsty; Saba, Karla; Gottschalk, Gerhard; Gunsalus, Robert P; Deppenmeier, Uwe

2005-05-01

Methansarcina mazei Gö1 DNA arrays were constructed and used to evaluate the genomic expression patterns of cells grown on either of two alternative methanogenic substrates, acetate or methanol, as sole carbon and energy source. Analysis of differential transcription across the genome revealed two functionally grouped sets of genes that parallel the central biochemical pathways in, and reflect many known features of, acetate and methanol metabolism. These include the acetate-induced genes encoding acetate activating enzymes, acetyl-CoA synthase/CO dehydrogenase, and carbonic anhydrase. Interestingly, additional genes expressed at significantly higher levels during growth on acetate included two energy-conserving complexes (the Ech hydrogenase, and the A1A0-type ATP synthase). Many previously unknown features included the induction by acetate of genes coding for ferredoxins and flavoproteins, an aldehyde:ferredoxin oxidoreductase, enzymes for the synthesis of aromatic amino acids, and components of iron, cobalt and oligopeptide uptake systems. In contrast, methanol-grown cells exhibited elevated expression of genes assigned to the methylotrophic pathway of methanogenesis. Expression of genes for components of the translation apparatus was also elevated in cells grown in the methanol medium relative to acetate, and was correlated with the faster growth rate observed on the former substrate. These experiments provide the first comprehensive insight into substrate-dependent gene expression in a methanogenic archaeon. This genome-wide approach, coupled with the complementary molecular and biochemical tools, should greatly accelerate the exploration of Methanosarcina cell physiology, given the present modest level of our knowledge of these large archaeal genomes.

CoMFA, LeapFrog and blind docking studies on sulfonanilide derivatives acting as selective aromatase expression regulators.

PubMed

Gueto, Carlos; Torres, Juan; Vivas-Reyes, Ricardo

2009-09-01

Aromatase, the enzyme responsible for estrogen biosynthesis, is an attractive target in the treatment of hormone-dependent breast cancer. In this manuscript, the structure-based drug design approach of sulfonanilide analogues as potential selective aromatase expression regulators (SAERs) is described. Receptor-independent CoMFA (Comparative Molecular Field Analysis) maps were employed for generating a pseudocavity for LeapFrog calculation. A robust model, using 45 and 10 molecules in the training and test sets, respectively, was developed producing statistically significant results with cross-validated and conventional correlation coefficients of 0.656 and 0.956, respectively. This model was used to predict the activity of newly proposed molecules as SAERs candidates being two magnitude orders more potent than the previously reported compounds. Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme. Future perspectives of the method in the screening of SAERs candidates with no COX-2 inhibitory activity are discussed.

Vectors for co-expression of an unrestricted number of proteins

PubMed Central

Scheich, Christoph; Kümmel, Daniel; Soumailakakis, Dimitri; Heinemann, Udo; Büssow, Konrad

2007-01-01

A vector system is presented that allows generation of E. coli co-expression clones by a standardized, robust cloning procedure. The number of co-expressed proteins is not limited. Five ‘pQLink’ vectors for expression of His-tag and GST-tag fusion proteins as well as untagged proteins and for cloning by restriction enzymes or Gateway cloning were generated. The vectors allow proteins to be expressed individually; to achieve co-expression, two pQLink plasmids are combined by ligation-independent cloning. pQLink co-expression plasmids can accept an unrestricted number of genes. As an example, the co-expression of a heterotetrameric human transport protein particle (TRAPP) complex from a single plasmid, its isolation and analysis of its stoichiometry are shown. pQLink clones can be used directly for pull-down experiments if the proteins are expressed with different tags. We demonstrate pull-down experiments of human valosin-containing protein (VCP) with fragments of the autocrine motility factor receptor (AMFR). The cloning method avoids PCR or gel isolation of restriction fragments, and a single resistance marker and origin of replication are used, allowing over-expression of rare tRNAs from a second plasmid. It is expected that applications are not restricted to bacteria, but could include co-expression in other hosts such as Bacluovirus/insect cells. PMID:17311810

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool

PubMed Central

Clark, Neil R.; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D.; Jones, Matthew R.; Ma’ayan, Avi

2016-01-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community. PMID:26848405

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

PubMed

Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

Comparative transcript profiling of alloplasmic male-sterile lines revealed altered gene expression related to pollen development in rice (Oryza sativa L.).

PubMed

Hu, Jihong; Chen, Guanglong; Zhang, Hongyuan; Qian, Qian; Ding, Yi

2016-08-05

Cytoplasmic male sterility (CMS) is an ideal model for investigating the mitochondrial-nuclear interaction and down-regulated genes in CMS lines which might be the candidate genes for pollen development in rice. In this study, a set of rice alloplasmic sporophytic CMS lines was obtained by successive backcrossing of Meixiang B, with three different cytoplasmic types: D62A (D type), ZS97A (WA type) and XQZ-A (DA type). Using microarray, the anther transcript profiles of the three indica rice CMS lines revealed 622 differentially expressed genes (DEGs) in each of the three CMS lines compared with the maintainer line Meixiang B. GO and MapMan analysis indicated that these DEGs were mainly involved in lipid metabolism and cell wall organization. Compared with the gene expression of sporophytic and gametophytic CMS lines, 303 DEGs were identified and 56 of them were down-regulated in all the CMS lines of rice. These down-regulated DEGs in the CMS lines were found to be involved in tapetum or cell wall formation and their suppressed expression might be related to male sterility. Weighted gene co-expression network analysis (WGCNA) revealed that two modules were significantly associated with male sterility and many hub genes that were differentially expressed in the CMS lines. A large set of putative genes involved in anther development was identified in the present study. The results will give some information for the nuclear gene regulation by different cytoplasmic genotypes and provide a rich resource for further functional research on the pollen development in rice.

Complex Network Analysis of CA3 Transcriptome Reveals Pathogenic and Compensatory Pathways in Refractory Temporal Lobe Epilepsy

PubMed Central

Bando, Silvia Yumi; Silva, Filipi Nascimento; Costa, Luciano da Fontoura; Silva, Alexandre V.; Pimentel-Silva, Luciana R.; Castro, Luiz HM.; Wen, Hung-Tzu; Amaro, Edson; Moreira-Filho, Carlos Alberto

2013-01-01

We previously described – studying transcriptional signatures of hippocampal CA3 explants – that febrile (FS) and afebrile (NFS) forms of refractory mesial temporal lobe epilepsy constitute two distinct genomic phenotypes. That network analysis was based on a limited number (hundreds) of differentially expressed genes (DE networks) among a large set of valid transcripts (close to two tens of thousands). Here we developed a methodology for complex network visualization (3D) and analysis that allows the categorization of network nodes according to distinct hierarchical levels of gene-gene connections (node degree) and of interconnection between node neighbors (concentric node degree). Hubs are highly connected nodes, VIPs have low node degree but connect only with hubs, and high-hubs have VIP status and high overall number of connections. Studying the whole set of CA3 valid transcripts we: i) obtained complete transcriptional networks (CO) for FS and NFS phenotypic groups; ii) examined how CO and DE networks are related; iii) characterized genomic and molecular mechanisms underlying FS and NFS phenotypes, identifying potential novel targets for therapeutic interventions. We found that: i) DE hubs and VIPs are evenly distributed inside the CO networks; ii) most DE hubs and VIPs are related to synaptic transmission and neuronal excitability whereas most CO hubs, VIPs and high hubs are related to neuronal differentiation, homeostasis and neuroprotection, indicating compensatory mechanisms. Complex network visualization and analysis is a useful tool for systems biology approaches to multifactorial diseases. Network centrality observed for hubs, VIPs and high hubs of CO networks, is consistent with the network disease model, where a group of nodes whose perturbation leads to a disease phenotype occupies a central position in the network. Conceivably, the chance for exerting therapeutic effects through the modulation of particular genes will be higher if these genes are highly interconnected in transcriptional networks. PMID:24278214

Insights into the dynamics of hind leg development in honey bee (Apis mellifera L.) queen and worker larvae - A morphology/differential gene expression analysis

PubMed Central

Santos, Carolina Gonçalves; Hartfelder, Klaus

2015-01-01

Phenotypic plasticity is a hallmark of the caste systems of social insects, expressed in their life history and morphological traits. These are best studied in bees. In their co-evolution with angiosperm plants, the females of corbiculate bees have acquired a specialized structure on their hind legs for collecting pollen. In the highly eusocial bees (Apini and Meliponini), this structure is however only present in workers and absent in queens. By means of histological sections and cell proliferation analysis we followed the developmental dynamics of the hind legs of queens and workers in the fourth and fifth larval instars. In parallel, we generated subtractive cDNA libraries for hind leg discs of queen and worker larvae by means of a Representational Difference Analysis (RDA). From the total of 135 unique sequences we selected 19 for RT-qPCR analysis, where six of these were confirmed as differing significantly in their expression between the two castes in the larval spinning stage. The development of complex structures such as the bees’ hind legs, requires diverse patterning mechanisms and signaling modules, as indicated by the set of differentially expressed genes related with cell adhesion and signaling pathways. PMID:26500430

Regulation of gene expression is associated with tolerance of the Arctic copepod Calanus glacialis to CO2-acidified sea water.

PubMed

Bailey, Allison; De Wit, Pierre; Thor, Peter; Browman, Howard I; Bjelland, Reidun; Shema, Steven; Fields, David M; Runge, Jeffrey A; Thompson, Cameron; Hop, Haakon

2017-09-01

Ocean acidification is the increase in seawater p CO 2 due to the uptake of atmospheric anthropogenic CO 2 , with the largest changes predicted to occur in the Arctic seas. For some marine organisms, this change in p CO 2 , and associated decrease in pH, represents a climate change-related stressor. In this study, we investigated the gene expression patterns of nauplii of the Arctic copepod Calanus glacialis cultured at low pH levels. We have previously shown that organismal-level performance (development, growth, respiration) of C. glacialis nauplii is unaffected by low pH. Here, we investigated the molecular-level response to lowered pH in order to elucidate the physiological processes involved in this tolerance. Nauplii from wild-caught C. glacialis were cultured at four pH levels (8.05, 7.9, 7.7, 7.5). At stage N6, mRNA was extracted and sequenced using RNA-seq. The physiological functionality of the proteins identified was categorized using Gene Ontology and KEGG pathways. We found that the expression of 151 contigs varied significantly with pH on a continuous scale (93% downregulated with decreasing pH). Gene set enrichment analysis revealed that, of the processes downregulated, many were components of the universal cellular stress response, including DNA repair, redox regulation, protein folding, and proteolysis. Sodium:proton antiporters were among the processes significantly upregulated, indicating that these ion pumps were involved in maintaining cellular pH homeostasis. C. glacialis significantly alters its gene expression at low pH, although they maintain normal larval development. Understanding what confers tolerance to some species will support our ability to predict the effects of future ocean acidification on marine organisms.

Characterization of Gastric and Neuronal Histaminergic Populations Using a Transgenic Mouse Model

PubMed Central

Walker, Angela K.; Park, Won-Mee; Chuang, Jen-Chieh; Perello, Mario; Sakata, Ichiro; Osborne-Lawrence, Sherri; Zigman, Jeffrey M.

2013-01-01

Histamine is a potent biogenic amine that mediates numerous physiological processes throughout the body, including digestion, sleep, and immunity. It is synthesized by gastric enterochromaffin-like cells, a specific set of hypothalamic neurons, as well as a subset of white blood cells, including mast cells. Much remains to be learned about these varied histamine-producing cell populations. Here, we report the validation of a transgenic mouse line in which Cre recombinase expression has been targeted to cells expressing histidine decarboxylase (HDC), which catalyzes the rate-limiting step in the synthesis of histamine. This was achieved by crossing the HDC-Cre mouse line with Rosa26-tdTomato reporter mice, thus resulting in the expression of the fluorescent Tomato (Tmt) signal in cells containing Cre recombinase activity. As expected, the Tmt signal co-localized with HDC-immunoreactivity within the gastric mucosa and gastric submucosa and also within the tuberomamillary nucleus of the brain. HDC expression within Tmt-positive gastric cells was further confirmed by quantitative PCR analysis of mRNA isolated from highly purified populations of Tmt-positive cells obtained by fluorescent activated cell sorting (FACS). HDC expression within these FACS-separated cells was found to coincide with other markers of both ECL cells and mast cells. Gastrin expression was co-localized with HDC expression in a subset of histaminergic gastric mucosal cells. We suggest that these transgenic mice will facilitate future studies aimed at investigating the function of histamine-producing cells. PMID:23555941

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Castano, Rebecca; Mann, Tobias; Wold, Barbara

2000-01-01

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

PubMed

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Participatory design facilitates Person Centred Nursing in service improvement with older people: a secondary directed content analysis.

PubMed

Wolstenholme, Daniel; Ross, Helen; Cobb, Mark; Bowen, Simon

2017-05-01

To explore, using the example of a project working with older people in an outpatient setting in a large UK NHS Teaching hospital, how the constructs of Person Centred Nursing are reflected in interviews from participants in a Co-design led service improvement project. Person Centred Care and Person Centred Nursing are recognised terms in healthcare. Co-design (sometimes called participatory design) is an approach that seeks to involve all stakeholders in a creative process to deliver the best result, be this a product, technology or in this case a service. Co-design practice shares some of the underpinning philosophy of Person Centred Nursing and potentially has methods to aid in Person Centred Nursing implementation. The research design was a qualitative secondary Directed analysis. Seven interview transcripts from nurses and older people who had participated in a Co-design led improvement project in a large teaching hospital were transcribed and analysed. Two researchers analysed the transcripts for codes derived from McCormack & McCance's Person Centred Nursing Framework. The four most expressed codes were as follows: from the pre-requisites: knowing self; from care processes, engagement, working with patient's beliefs and values and shared Decision-making; and from Expected outcomes, involvement in care. This study describes the Co-design theory and practice that the participants responded to in the interviews and look at how the co-design activity facilitated elements of the Person Centred Nursing framework. This study adds to the rich literature about using emancipatory and transformational approaches to Person Centred Nursing development, and is the first study exploring explicitly the potential contribution of Co-design to this area. Methods from Co-design allow older people to contribute as equals in a practice development project, co-design methods can facilitate nursing staff to engage meaningfully with older participants and develop a shared understanding and goals. The co-produced outputs of Co-design projects embody and value the expressed beliefs and values of staff and older people. © 2016 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Temporal gene expression profiling of the rat knee joint capsule during immobilization-induced joint contractures.

PubMed

Wong, Kayleigh; Sun, Fangui; Trudel, Guy; Sebastiani, Paola; Laneuville, Odette

2015-05-26

Contractures of the knee joint cause disability and handicap. Recovering range of motion is recognized by arthritic patients as their preference for improved health outcome secondary only to pain management. Clinical and experimental studies provide evidence that the posterior knee capsule prevents the knee from achieving full extension. This study was undertaken to investigate the dynamic changes of the joint capsule transcriptome during the progression of knee joint contractures induced by immobilization. We performed a microarray analysis of genes expressed in the posterior knee joint capsule following induction of a flexion contracture by rigidly immobilizing the rat knee joint over a time-course of 16 weeks. Fold changes of expression values were measured and co-expressed genes were identified by clustering based on time-series analysis. Genes associated with immobilization were further analyzed to reveal pathways and biological significance and validated by immunohistochemistry on sagittal sections of knee joints. Changes in expression with a minimum of 1.5 fold changes were dominated by a decrease in expression for 7732 probe sets occurring at week 8 while the expression of 2251 probe sets increased. Clusters of genes with similar profiles of expression included a total of 162 genes displaying at least a 2 fold change compared to week 1. Functional analysis revealed ontology categories corresponding to triglyceride metabolism, extracellular matrix and muscle contraction. The altered expression of selected genes involved in the triglyceride biosynthesis pathway; AGPAT-9, and of the genes P4HB and HSP47, both involved in collagen synthesis, was confirmed by immunohistochemistry. Gene expression in the knee joint capsule was sensitive to joint immobility and provided insights into molecular mechanisms relevant to the pathophysiology of knee flexion contractures. Capsule responses to immobilization was dynamic and characterized by modulation of at least three reaction pathways; down regulation of triglyceride biosynthesis, alteration of extracellular matrix degradation and muscle contraction gene expression. The posterior knee capsule may deploy tissue-specific patterns of mRNA regulatory responses to immobilization. The identification of altered expression of genes and biochemical pathways in the joint capsule provides potential targets for the therapy of knee flexion contractures.

Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle.

PubMed

Gu, Quan; Nagaraj, Shivashankar H; Hudson, Nicholas J; Dalrymple, Brian P; Reverter, Antonio

2011-01-12

Gene regulation by transcription factors (TF) is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information. We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs). We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs) and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively. The pivotal implication of our research is two-fold: (1) there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2) this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.

PubMed

Mirzarezaee, Mitra; Araabi, Babak N; Sadeghi, Mehdi

2010-12-19

It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

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

Differential co-expression analysis reveals a novel prognostic gene module in ovarian cancer.

PubMed

Gov, Esra; Arga, Kazim Yalcin

2017-07-10

Ovarian cancer is one of the most significant disease among gynecological disorders that women suffered from over the centuries. However, disease-specific and effective biomarkers were still not available, since studies have focused on individual genes associated with ovarian cancer, ignoring the interactions and associations among the gene products. Here, ovarian cancer differential co-expression networks were reconstructed via meta-analysis of gene expression data and co-expressed gene modules were identified in epithelial cells from ovarian tumor and healthy ovarian surface epithelial samples to propose ovarian cancer associated genes and their interactions. We propose a novel, highly interconnected, differentially co-expressed, and co-regulated gene module in ovarian cancer consisting of 84 prognostic genes. Furthermore, the specificity of the module to ovarian cancer was shown through analyses of datasets in nine other cancers. These observations underscore the importance of transcriptome based systems biomarkers research in deciphering the elusive pathophysiology of ovarian cancer, and here, we present reciprocal interplay between candidate ovarian cancer genes and their transcriptional regulatory dynamics. The corresponding gene module might provide new insights on ovarian cancer prognosis and treatment strategies that continue to place a significant burden on global health.

Correlated mRNAs and miRNAs from co-expression and regulatory networks affect porcine muscle and finally meat properties.

PubMed

Ponsuksili, Siriluck; Du, Yang; Hadlich, Frieder; Siengdee, Puntita; Murani, Eduard; Schwerin, Manfred; Wimmers, Klaus

2013-08-05

Physiological processes aiding the conversion of muscle to meat involve many genes associated with muscle structure and metabolic processes. MicroRNAs regulate networks of genes to orchestrate cellular functions, in turn regulating phenotypes. We applied weighted gene co-expression network analysis to identify co-expression modules that correlated to meat quality phenotypes and were highly enriched for genes involved in glucose metabolism, response to wounding, mitochondrial ribosome, mitochondrion, and extracellular matrix. Negative correlation of miRNA with mRNA and target prediction were used to select transcripts out of the modules of trait-associated mRNAs to further identify those genes that are correlated with post mortem traits. Porcine muscle co-expression transcript networks that correlated to post mortem traits were identified. The integration of miRNA and mRNA expression analyses, as well as network analysis, enabled us to interpret the differentially-regulated genes from a systems perspective. Linking co-expression networks of transcripts and hierarchically organized pairs of miRNAs and mRNAs to meat properties yields new insight into several biological pathways underlying phenotype differences. These pathways may also be diagnostic for many myopathies, which are accompanied by deficient nutrient and oxygen supply of muscle fibers.

V-set and Ig domain-containing 4 (VSIG4)-expressing hepatic F4/80+ cells regulate oral antigen-specific responses in mouse.

PubMed

Shin, Wonhwa; Jeon, Youkyoung; Choi, Inhak; Kim, Yeon-Jeong

2018-04-01

Oral tolerance can prevent unnecessary immune responses against dietary antigens. Members of the B7 protein family play critical roles in the positive and/or negative regulation of T cell responses to interactions between APCs and T cells. V-set and Ig domain-containing 4 (VSIG4), a B7-related co-signaling molecule, has been known to act as a co-inhibitory ligand and may be critical in establishing immune tolerance. Therefore, we investigated the regulation of VSIG4 signaling in a food allergy and experimental oral tolerance murine models. We analyzed the contributions of the two main sites involved in oral tolerance, the mesenteric lymph node (MLN) and the liver, in VSIG4-mediated oral tolerance induction. Through the comparative analysis of major APCs, dendritic cells (DCs) and macrophages, we found that Kupffer cells play a critical role in inducing regulatory T cells (Tregs) and establishing immune tolerance against oral antigens via VSIG4 signaling. Taken together, these results suggest the possibility of VSIG4 signaling-based regulation of orally administered antigens. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Co-expression analysis reveals key gene modules and pathway of human coronary heart disease.

PubMed

Tang, Yu; Ke, Zun-Ping; Peng, Yi-Gen; Cai, Ping-Tai

2018-02-01

Coronary heart disease is a kind of disease which causes great injury to people world-widely. Although gene expression analyses had been performed previously, to our best knowledge, systemic co-expression analysis for this disease is still lacking to date. Microarray data of coronary heart disease was downloaded from NCBI with the accession number of GSE20681. Co-expression modules were constructed by WGCNA. Besides, the connectivity degree of eigengenes was analyzed. Furthermore, GO and KEGG enrichment analysis was performed on these eigengenes in these constructed modules. A total of 11 co-expression modules were constructed by the 3000 up-regulated genes from the 99 samples with coronary heart disease. The average number of genes in these modules was 270. The interaction analysis indicated the relative independence of gene expression in these modules. The functional enrichment analysis showed that there was a significant difference in the enriched terms and degree among these 11 modules. The results showed that modules 9 and 10 played critical roles in the occurrence of coronary disease. Pathways of hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) were thought to be closely related to the occurrence and development of coronary heart disease. Our result demonstrated that modules 9 and 10 were the most critical modules in the occurrence of coronary heart disease. Pathways as hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) had the potential to serve as the prognostic and predictive marker of coronary heart disease. © 2017 Wiley Periodicals, Inc.

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

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

PubMed Central

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

2007-01-01

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

Suppression subtractive hybridization and comparative expression analysis to identify developmentally regulated genes in filamentous fungi.

PubMed

Gesing, Stefan; Schindler, Daniel; Nowrousian, Minou

2013-09-01

Ascomycetes differentiate four major morphological types of fruiting bodies (apothecia, perithecia, pseudothecia and cleistothecia) that are derived from an ancestral fruiting body. Thus, fruiting body differentiation is most likely controlled by a set of common core genes. One way to identify such genes is to search for genes with evolutionary conserved expression patterns. Using suppression subtractive hybridization (SSH), we selected differentially expressed transcripts in Pyronema confluens (Pezizales) by comparing two cDNA libraries specific for sexual and for vegetative development, respectively. The expression patterns of selected genes from both libraries were verified by quantitative real time PCR. Expression of several corresponding homologous genes was found to be conserved in two members of the Sordariales (Sordaria macrospora and Neurospora crassa), a derived group of ascomycetes that is only distantly related to the Pezizales. Knockout studies with N. crassa orthologues of differentially regulated genes revealed a functional role during fruiting body development for the gene NCU05079, encoding a putative MFS peptide transporter. These data indicate conserved gene expression patterns and a functional role of the corresponding genes during fruiting body development; such genes are candidates of choice for further functional analysis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integrating mRNA and miRNA Weighted Gene Co-Expression Networks with eQTLs in the Nucleus Accumbens of Subjects with Alcohol Dependence

PubMed Central

Blevins, Tana; Aliev, Fazil; Adkins, Amy; Hack, Laura; Bigdeli, Tim; D. van der Vaart, Andrew; Web, Bradley Todd; Bacanu, Silviu-Alin; Kalsi, Gursharan; Kendler, Kenneth S.; Miles, Michael F.; Dick, Danielle; Riley, Brien P.; Dumur, Catherine; Vladimirov, Vladimir I.

2015-01-01

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD. PMID:26381263

Large clusters of co-expressed genes in the Drosophila genome.

PubMed

Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

Co-infection with human polyomavirus BK enhances gene expression and replication of human adenovirus.

PubMed

Bil-Lula, Iwona; Woźniak, Mieczysław

2018-03-26

Immunocompromised patients are susceptible to multiple viral infections. Relevant interactions between co-infecting viruses might result from viral regulatory genes which trans-activate or repress the expression of host cell genes as well as the genes of any co-infecting virus. The aim of the current study was to show that the replication of human adenovirus 5 is enhanced by co-infection with BK polyomavirus and is associated with increased expression of proteins including early region 4 open reading frame 1 and both the large tumor antigen and small tumor antigen. Clinical samples of whole blood and urine from 156 hematopoietic stem cell transplant recipients were tested. We also inoculated adenocarcinomic human alveolar basal epithelial cells with both human adenovirus 5 and BK polyomavirus to evaluate if co-infection of viruses affected their replication. Data showed that adenovirus load was significantly higher in the plasma (mean 7.5 x 10 3  ± 8.5 x 10 2 copies/ml) and urine (mean 1.9 x 10 3  ± 8.0 x 10 2 copies/ml) of samples from patients with co-infections, in comparison to samples from patients with isolated adenovirus infection. In vitro co-infection led to an increased (8.6 times) expression of the adenovirus early region 4 open reading frame gene 48 hours post-inoculation. The expression of the early region 4 open reading frame gene positively correlated with the expression of BK polyomavirus large tumor antigen (r = 0.90, p < 0.0001) and small tumor antigen (r = 0.83, p < 0.001) genes. The enhanced expression of the early region 4 open reading frame gene due to co-infection with BK polyomavirus was associated with enhanced adenovirus, but not BK polyomavirus, replication. The current study provides evidence that co-infection of adenovirus and BK polyomavirus contributes to enhanced adenovirus replication. Data obtained from this study may have significant importance in the clinical setting.

Time-Course Gene Set Analysis for Longitudinal Gene Expression Data

PubMed Central

Hejblum, Boris P.; Skinner, Jason; Thiébaut, Rodolphe

2015-01-01

Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR) measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial), and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA) for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package. PMID:26111374

Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

PubMed

Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

NASA Astrophysics Data System (ADS)

Trifonov, Vladimir; Pasqualucci, Laura; Dalla-Favera, Riccardo; Rabadan, Raul

2011-12-01

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing (HTS), expression profiles, proteomics, and electronic health records (EHR) are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of fractal-like distributions that commonly appear in the analysis of such data. The first set of examples are drawn from a HTS experiment. Here, the distributions appear as part of the evaluation of the error rate of the sequencing and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in EHR. The distributions are also relevant to identification of subclonal populations in tumors and the study of quasi-species and intrahost diversity of viral populations.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

Angiogenic properties of endometrial mesenchymal stromal cells in endothelial co-culture: an in vitro model of endometriosis.

PubMed

Canosa, S; Moggio, A; Brossa, A; Pittatore, G; Marchino, G L; Leoncini, S; Benedetto, C; Revelli, A; Bussolati, B

2017-03-01

Can endometrial mesenchymal stromal cells (E-MSCs) differentiate into endothelial cells in an in vitro co-culture system with human umbilical vein endothelial cells (HUVECs)? E-MSCs can acquire endothelial markers and function in a direct co-culture system with HUVECs. E-MSCs have been identified in the human endometrium as well as in endometriotic lesions. E-MSCs appear to be involved in formation of the endometrial stromal vascular tissue and the support of tissue growth and vascularization. The use of anti-angiogenic drugs appears as a possible therapeutic strategy against endometriosis. This is an in vitro study comprising patients receiving surgical treatment of ovarian endometriosis (n = 9). E-MSCs were isolated from eutopic and ectopic endometrial tissue and were characterized for the expression of mesenchymal and endothelial markers by FACS analysis and Real-Time PCR. CD31 acquisition was evaluated by FACS analysis and immunofluorescence after a 48 h-direct co-culture with green fluorescent protein +-HUVECs. A tube-forming assay was set up in order to analyze the functional potential of their interaction. Finally, co-cultures were treated with the anti-angiogenic agent Cabergoline. A subpopulation of E-MSCs acquired CD31 expression and integrated into tube-like structures when directly in contact with HUVECs, as observed by both FACS analysis and immunofluorescence. The isolation of CD31+ E-MSCs revealed significant increases in CD31, vascular endothelial growth factor receptor 2, TEK receptor tyrosine kinase and vascular endothelial-Cadherin mRNA expression levels with respect to basal and to CD31neg cells (P < 0.05). On the other hand, the expression of mesenchymal genes such as c-Myc, Vimentin, neuronal-Cadherin and sushi domain containing 2 remained unchanged. Cabergoline treatment induced a significant reduction of the E-MSC angiogenic potential (P < 0.05 versus control). Not applicable. Further studies are necessary to investigate the cellular and molecular mechanisms underlying the endothelial cell differentiation. E-MSCs may undergo endothelial differentiation, and be potentially involved in the development of endometriotic implants. Cell culture systems that more closely mimic the cellular complexity typical of endometriotic tissues in vivo are required to develop novel strategies for treatment. This study was supported by the 'Research Fund ex-60%', University of Turin, Turin, Italy. All authors declare that their participation in the study did not involve actual or potential conflicts of interests. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Tissue and cell-type co-expression networks of transcription factors and wood component genes in Populus trichocarpa.

PubMed

Shi, Rui; Wang, Jack P; Lin, Ying-Chung; Li, Quanzi; Sun, Ying-Hsuan; Chen, Hao; Sederoff, Ronald R; Chiang, Vincent L

2017-05-01

Co-expression networks based on transcriptomes of Populus trichocarpa major tissues and specific cell types suggest redundant control of cell wall component biosynthetic genes by transcription factors in wood formation. We analyzed the transcriptomes of five tissues (xylem, phloem, shoot, leaf, and root) and two wood forming cell types (fiber and vessel) of Populus trichocarpa to assemble gene co-expression subnetworks associated with wood formation. We identified 165 transcription factors (TFs) that showed xylem-, fiber-, and vessel-specific expression. Of these 165 TFs, 101 co-expressed (correlation coefficient, r > 0.7) with the 45 secondary cell wall cellulose, hemicellulose, and lignin biosynthetic genes. Each cell wall component gene co-expressed on average with 34 TFs, suggesting redundant control of the cell wall component gene expression. Co-expression analysis showed that the 101 TFs and the 45 cell wall component genes each has two distinct groups (groups 1 and 2), based on their co-expression patterns. The group 1 TFs (44 members) are predominantly xylem and fiber specific, and are all highly positively co-expressed with the group 1 cell wall component genes (30 members), suggesting their roles as major wood formation regulators. Group 1 TFs include a lateral organ boundary domain gene (LBD) that has the highest number of positively correlated cell wall component genes (36) and TFs (47). The group 2 TFs have 57 members, including 14 vessel-specific TFs, and are generally less correlated with the cell wall component genes. An exception is a vessel-specific basic helix-loop-helix (bHLH) gene that negatively correlates with 20 cell wall component genes, and may function as a key transcriptional suppressor. The co-expression networks revealed here suggest a well-structured transcriptional homeostasis for cell wall component biosynthesis during wood formation.

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

PubMed

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Hierarchical cortical transcriptome disorganization in autism.

PubMed

Lombardo, Michael V; Courchesne, Eric; Lewis, Nathan E; Pramparo, Tiziano

2017-01-01

Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation.

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

PubMed

Peng, Youyi; Keenan, Susan M; Zhang, Qiang; Kholodovych, Vladyslav; Welsh, William J

2005-03-10

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.

Functional characterisation of HvCO1, the barley (Hordeum vulgare) flowering time ortholog of CONSTANS.

PubMed

Campoli, Chiara; Drosse, Benedikt; Searle, Iain; Coupland, George; von Korff, Maria

2012-03-01

Variation in photoperiod response is a major factor determining plant development and the agronomic performance of crops. The genetic control of photoperiodic flowering has been elucidated in the model plant Arabidopsis, and many of the identified genes are structurally conserved in the grasses. In this study, HvCO1, the closest barley ortholog of the key photoperiod response gene CONSTANS in Arabidopsis, was over-expressed in the spring barley Golden Promise. Over-expression of HvCO1 accelerated time to flowering in long- and short-day conditions and caused up-regulation of HvFT1 mRNA under long-day conditions. However, the transgenic plants retained a response to photoperiod, suggesting the presence of photoperiod response factors acting downstream of HvCO1 transcription. Analysis of a population segregating for HvCO1 over-expression and natural genetic variation at Ppd-H1 demonstrated that Ppd-H1 acts downstream of HvCO1 transcription on HvFT1 expression and flowering. Furthermore, variation at Ppd-H1 did not affect diurnal expression of HvCO1 or HvCO2. Over-expression of HvCO1 increased transcription of the spring allele of Vrn-H1 in long- and short-day conditions, while genetic variation at Ppd-H1 did not affect Vrn-H1 expression. Over-expression of HvCO1 and natural genetic variation at Ppd-H1 accelerated inflorescence development and stem elongation. Thus, HvCO1 probably induces flowering by activating HvFT1 whilst Ppd-H1 regulates HvFT1 independently of HvCO1 mRNA, and all three genes also appear to have a strong effect in promoting inflorescence development. © 2011 The Authors. The Plant Journal © 2011 Blackwell Publishing Ltd.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

PubMed Central

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N.; Jones, Byron C.; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses. PMID:29674951

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

PubMed Central

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

2014-01-01

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

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets

PubMed Central

Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J.

2017-01-01

Abstract Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. PMID:28472340

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

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

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

Therapeutic targeting of oxidative stress with coenzyme Q10 counteracts exaggerated diabetic cardiomyopathy in a mouse model of diabetes with diminished PI3K(p110α) signaling.

PubMed

De Blasio, Miles J; Huynh, Karina; Qin, Chengxue; Rosli, Sarah; Kiriazis, Helen; Ayer, Anita; Cemerlang, Nelly; Stocker, Roland; Du, Xiao-Jun; McMullen, Julie R; Ritchie, Rebecca H

2015-10-01

Diabetes-induced cardiac complications include left ventricular (LV) dysfunction and heart failure. We previously demonstrated that LV phosphoinositide 3-kinase p110α (PI3K) protects the heart against diabetic cardiomyopathy, associated with reduced NADPH oxidase expression and activity. Conversely, in dominant negative PI3K(p110α) transgenic mice (dnPI3K), reduced cardiac PI3K signaling exaggerated diabetes-induced cardiomyopathy, associated with upregulated NADPH oxidase. The goal was to examine whether chronic supplementation with the antioxidant coenzyme Q(10) (CoQ(10)) could attenuate LV superoxide and diabetic cardiomyopathy in a setting of impaired PI3K signaling. Diabetes was induced in 6-week-old nontransgenic and dnPI3K male mice via streptozotocin. After 4 weeks of diabetes, CoQ(10) supplementation commenced (10 mg/kg ip, 3 times/week, 8 weeks). At study end (12 weeks of diabetes), markers of LV function, cardiomyocyte hypertrophy, collagen deposition, NADPH oxidase, oxidative stress (3-nitrotyrosine), and concentrations of CoQ(9) and CoQ(10) were determined. LV NADPH oxidase (Nox2 gene expression and activity, and lucigenin-enhanced chemiluminescence), as well as oxidative stress, were increased by diabetes, exaggerated in diabetic dnPI3K mice, and attenuated by CoQ(10). Diabetes-induced LV diastolic dysfunction (prolonged deceleration time, elevated end-diastolic pressure, impaired E/A ratio), cardiomyocyte hypertrophy and fibrosis, expression of atrial natriuretic peptide, connective tissue growth factor, and β-myosin heavy chain were all attenuated by CoQ(10). Chronic CoQ(10) supplementation attenuates aspects of diabetic cardiomyopathy, even in a setting of reduced cardiac PI3K protective signaling. Given that CoQ(10) supplementation has been suggested to have positive outcomes in heart failure patients, chronic CoQ(10) supplementation may be an attractive adjunct therapy for diabetic heart failure. Copyright © 2015 Elsevier Inc. All rights reserved.

Co-Workers' Perceptions of an Employee with Severe Disabilities: An Analysis of Social Interactions in a Work Setting.

ERIC Educational Resources Information Center

Yan, Xiaoyan; And Others

1993-01-01

This study explains the methodology of clique analysis and presents a study in which the use of clique analysis demonstrated that an employee with severe disabilities was perceived by co-workers as socially involved in the work setting at levels comparable to others in such areas as greetings and small talk, work-related conversation, and personal…

Translational analysis of mouse and human placental protein and mRNA reveals distinct molecular pathologies in human preeclampsia.

PubMed

Cox, Brian; Sharma, Parveen; Evangelou, Andreas I; Whiteley, Kathie; Ignatchenko, Vladimir; Ignatchenko, Alex; Baczyk, Dora; Czikk, Marie; Kingdom, John; Rossant, Janet; Gramolini, Anthony O; Adamson, S Lee; Kislinger, Thomas

2011-12-01

Preeclampsia (PE) adversely impacts ~5% of pregnancies. Despite extensive research, no consistent biomarkers or cures have emerged, suggesting that different molecular mechanisms may cause clinically similar disease. To address this, we undertook a proteomics study with three main goals: (1) to identify a panel of cell surface markers that distinguish the trophoblast and endothelial cells of the placenta in the mouse; (2) to translate this marker set to human via the Human Protein Atlas database; and (3) to utilize the validated human trophoblast markers to identify subgroups of human preeclampsia. To achieve these goals, plasma membrane proteins at the blood tissue interfaces were extracted from placentas using intravascular silica-bead perfusion, and then identified using shotgun proteomics. We identified 1181 plasma membrane proteins, of which 171 were enriched at the maternal blood-trophoblast interface and 192 at the fetal endothelial interface with a 70% conservation of expression in humans. Three distinct molecular subgroups of human preeclampsia were identified in existing human microarray data by using expression patterns of trophoblast-enriched proteins. Analysis of all misexpressed genes revealed divergent dysfunctions including angiogenesis (subgroup 1), MAPK signaling (subgroup 2), and hormone biosynthesis and metabolism (subgroup 3). Subgroup 2 lacked expected changes in known preeclampsia markers (sFLT1, sENG) and uniquely overexpressed GNA12. In an independent set of 40 banked placental specimens, GNA12 was overexpressed during preeclampsia when co-incident with chronic hypertension. In the current study we used a novel translational analysis to integrate mouse and human trophoblast protein expression with human microarray data. This strategy identified distinct molecular pathologies in human preeclampsia. We conclude that clinically similar preeclampsia patients exhibit divergent placental gene expression profiles thus implicating divergent molecular mechanisms in the origins of this disease.

Genome-wide screening and identification of long noncoding RNAs and their interaction with protein coding RNAs in bladder urothelial cell carcinoma.

PubMed

Wang, Longxin; Fu, Dian; Qiu, Yongbin; Xing, Xiaoxiao; Xu, Feng; Han, Conghui; Xu, Xiaofeng; Wei, Zhifeng; Zhang, Zhengyu; Ge, Jingping; Cheng, Wen; Xie, Hai-Long

2014-07-10

To understand lncRNAs expression profiling and their potential functions in bladder cancer, we investigated the lncRNA and coding RNA expression on human bladder cancer and normal bladder tissues. Bioinformatic analysis revealed thousands of significantly differentially expressed lncRNAs and coding mRNA in bladder cancer relative to normal bladder tissue. Co-expression analysis revealed that 50% of lncRNAs and coding RNAs expressed in the same direction. A subset of lncRNAs might be involved in mTOR signaling, p53 signaling, cancer pathways. Our study provides a large scale of co-expression between lncRNA and coding RNAs in bladder cancer cells and lays biological basis for further investigation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Rapid transcriptional acclimation following transgenerational exposure of oysters to ocean acidification.

PubMed

Goncalves, Priscila; Anderson, Kelli; Thompson, Emma L; Melwani, Aroon; Parker, Laura M; Ross, Pauline M; Raftos, David A

2016-10-01

Marine organisms need to adapt in order to cope with the adverse effects of ocean acidification and warming. Transgenerational exposure to CO2 stress has been shown to enhance resilience to ocean acidification in offspring from a number of species. However, the molecular basis underlying such adaptive responses is currently unknown. Here, we compared the transcriptional profiles of two genetically distinct oyster breeding lines following transgenerational exposure to elevated CO2 in order to explore the molecular basis of acclimation or adaptation to ocean acidification in these organisms. The expression of key target genes associated with antioxidant defence, metabolism and the cytoskeleton was assessed in oysters exposed to elevated CO2 over three consecutive generations. This set of target genes was chosen specifically to test whether altered responsiveness of intracellular stress mechanisms contributes to the differential acclimation of oyster populations to climate stressors. Transgenerational exposure to elevated CO2 resulted in changes to both basal and inducible expression of those key target genes (e.g. ecSOD, catalase and peroxiredoxin 6), particularly in oysters derived from the disease-resistant, fast-growing B2 line. Exposure to CO2 stress over consecutive generations produced opposite and less evident effects on transcription in a second population that was derived from wild-type (nonselected) oysters. The analysis of key target genes revealed that the acute responses of oysters to CO2 stress appear to be affected by population-specific genetic and/or phenotypic traits and by the CO2 conditions to which their parents had been exposed. This supports the contention that the capacity for heritable change in response to ocean acidification varies between oyster breeding lines and is mediated by parental conditioning. © 2016 John Wiley & Sons Ltd.

SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data.

PubMed

Cava, Claudia; Colaprico, Antonio; Bertoli, Gloria; Graudenzi, Alex; Silva, Tiago C; Olsen, Catharina; Noushmehr, Houtan; Bontempi, Gianluca; Mauri, Giancarlo; Castiglioni, Isabella

2017-01-27

Gene Regulatory Networks (GRNs) control many biological systems, but how such network coordination is shaped is still unknown. GRNs can be subdivided into basic connections that describe how the network members interact e.g., co-expression, physical interaction, co-localization, genetic influence, pathways, and shared protein domains. The important regulatory mechanisms of these networks involve miRNAs. We developed an R/Bioconductor package, namely SpidermiR, which offers an easy access to both GRNs and miRNAs to the end user, and integrates this information with differentially expressed genes obtained from The Cancer Genome Atlas. Specifically, SpidermiR allows the users to: (i) query and download GRNs and miRNAs from validated and predicted repositories; (ii) integrate miRNAs with GRNs in order to obtain miRNA-gene-gene and miRNA-protein-protein interactions, and to analyze miRNA GRNs in order to identify miRNA-gene communities; and (iii) graphically visualize the results of the analyses. These analyses can be performed through a single interface and without the need for any downloads. The full data sets are then rapidly integrated and processed locally.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis.

PubMed

Han, Xinxin; Yin, Linlin; Xue, Hongwei

2012-07-01

Fatty acids (FAs) play crucial rules in signal transduction and plant development, however, the regulation of FA metabolism is still poorly understood. To study the relevant regulatory network, fifty-eight FA biosynthesis genes including de novo synthases, desaturases and elongases were selected as "guide genes" to construct the co-expression network. Calculation of the correlation between all Arabidopsis thaliana (L.) genes with each guide gene by Arabidopsis co-expression dating mining tools (ACT) identifies 797 candidate FA-correlated genes. Gene ontology (GO) analysis of these co-expressed genes showed they are tightly correlated to photosynthesis and carbohydrate metabolism, and function in many processes. Interestingly, 63 transcription factors (TFs) were identified as candidate FA biosynthesis regulators and 8 TF families are enriched. Two TF genes, CRC and AP1, both correlating with 8 FA guide genes, were further characterized. Analyses of the ap1 and crc mutant showed the altered total FA composition of mature seeds. The contents of palmitoleic acid, stearic acid, arachidic acid and eicosadienoic acid are decreased, whereas that of oleic acid is increased in ap1 and crc seeds, which is consistent with the qRT-PCR analysis revealing the suppressed expression of the corresponding guide genes. In addition, yeast one-hybrid analysis and electrophoretic mobility shift assay (EMSA) revealed that CRC can bind to the promoter regions of KCS7 and KCS15, indicating that CRC may directly regulate FA biosynthesis. © 2012 Institute of Botany, Chinese Academy of Sciences.

Analysis of Co-Tunneling Current in Fullerene Single-Electron Transistor

NASA Astrophysics Data System (ADS)

KhademHosseini, Vahideh; Dideban, Daryoosh; Ahmadi, MohammadTaghi; Ismail, Razali

2018-05-01

Single-electron transistors (SETs) are nano devices which can be used in low-power electronic systems. They operate based on coulomb blockade effect. This phenomenon controls single-electron tunneling and it switches the current in SET. On the other hand, co-tunneling process increases leakage current, so it reduces main current and reliability of SET. Due to co-tunneling phenomenon, main characteristics of fullerene SET with multiple islands are modelled in this research. Its performance is compared with silicon SET and consequently, research result reports that fullerene SET has lower leakage current and higher reliability than silicon counterpart. Based on the presented model, lower co-tunneling current is achieved by selection of fullerene as SET island material which leads to smaller value of the leakage current. Moreover, island length and the number of islands can affect on co-tunneling and then they tune the current flow in SET.

Fuzzy Energy and Reserve Co-optimization With High Penetration of Renewable Energy

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

Liu, Cong; Botterud, Audun; Zhou, Zhi

In this study, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzymore » mathematical programming formulation into traditional mixed integer linear programming problems.« less

Fuzzy Energy and Reserve Co-optimization With High Penetration of Renewable Energy

DOE PAGES

Liu, Cong; Botterud, Audun; Zhou, Zhi; ...

2016-10-21

In this study, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzymore » mathematical programming formulation into traditional mixed integer linear programming problems.« less

Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation

PubMed Central

2011-01-01

Background To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns. Results We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed. Conclusions The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses. PMID:21672238

Comprehensive analysis of differentially expressed genes reveals the molecular response to elevated CO2 levels in two sea buckthorn cultivars.

PubMed

Zhang, Guoyun; Zhang, Tong; Liu, Juanjuan; Zhang, Jianguo; He, Caiyun

2018-06-20

Atmospheric carbon dioxide (CO 2 ) concentration increases every year. It is critical to understand the elevated CO 2 response molecular mechanisms of plants using genomic techniques. Hippophae rhamnoides L. is a high stress resistance plant species widely distributed in Europe and Asia. However, the molecular mechanism of elevated CO 2 response in H. rhamnoides has been limited. In this study, transcriptomic analysis of two sea buckthorn cultivars under different CO 2 concentrations was performed, based on the next-generation illumina sequencing platform and de novo assembly. We identified 4740 differentially expressed genes in sea buckthorn response to elevated CO 2 concentrations. According to the gene ontology (GO) results, photosystem I, photosynthesis and chloroplast thylakoid membrane were the main enriched terms in 'xiangyang' sea buckthorn. In 'zhongguo' sea buckthorn, photosynthesis was also the main significantly enriched term. However, the number of photosynthesis related differentially expressed genes were different between two sea buckthorn cultivars. Our GO and pathway analyses indicated that the expression levels of the transcription factors WRKY, MYB and NAC were significantly different between the two sea buckthorn cultivars. This study provides a reliable transcriptome sequence resource and is a valuable resource for genetic and genomic researches for plants under high CO 2 concentration in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

Antibacterial and Odontogenesis Efficacy of Mineral Trioxide Aggregate Combined with CO2 Laser Treatment.

PubMed

Hsu, Tuan-Ti; Yeh, Chia-Hung; Kao, Chia-Tze; Chen, Yi-Wen; Huang, Tsui-Hsien; Yang, Jaw-Ji; Shie, Ming-You

2015-07-01

Mineral trioxide aggregate (MTA) has been successfully used in clinical applications in endodontics. Studies show that the antibacterial effects of CO2 laser irradiation are highly efficient when bacteria are embedded in biofilm because of a photothermal mechanism. The aim of this study was to confirm the effects of CO2 laser irradiation on MTA with regard to both material characterization and cell viability. MTA was irradiated with a dental CO2 laser using directly mounted fiber optics in the wound healing mode with a spot area of 0.25 cm(2) and then stored in an incubator at 100% relative humidity and 37°C for 1 day to set. The human dental pulp cells cultured on MTA were analyzed along with their proliferation and odontogenic differentiation behaviors. The results indicate that the setting time of MTA after irradiation by the CO2 laser was significantly reduced to 118 minutes rather than the usual 143 minutes. The maximum diametral tensile strength and x-ray diffraction patterns were similar to those obtained without CO2 laser irradiation. However, the CO2 laser irradiation increased the amount of Ca and Si ions released from the MTA and regulated cell behavior. CO2 laser-irradiated MTA promoted odontogenic differentiation of hDPCs, with the increased formation of mineralized nodules on the substrate's surface. It also up-regulated the protein expression of multiple markers of odontogenic and the expression of dentin sialophosphoprotein protein. The current study provides new and important data about the effects of CO2 laser irradiation on MTA with regard to the decreased setting time and increased ion release. Taking cell functions into account, the Si concentration released from MTA with laser irradiation may be lower than a critical value, and this information could lead to the development of new regenerative therapies for dentin and periodontal tissue. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Seasonality and the Response of the Thecosome Pteropod Limacina retroversa to CO2 in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Maas, A.; Tarrant, A. M.; Bergan, A. J.; Wang, A. Z.; Lawson, G. L.

2016-02-01

Limacina retroversa is a thecosomatous pteropod found year round in the Gulf of Maine. Because carbonate chemistry within this shelf system is spatially variable and exhibits seasonal cycles, pteropods in this region may already be exposed to under-saturated, and hence corrosive, waters during certain seasons. To understand the implications of this variability, we have explored the physiological responses of L. retroversa at four time points over the course of a year to determine whether pteropods vary seasonally in their sensitivity to CO2 exposure on time-scales relevant to acclimation responses. In the laboratory, these animals were exposed to CO2 (ambient, 800, 1200 ppm) for 7-14 days and their response was assessed using an integrated set of metabolic, gene-expression and shell condition metrics. Similar to previous work with this species and others, pronounced changes in shell condition of exposed adults were discernible after less than 3 days of exposure, while changes to respiration rate were not consistently apparent. There were, however, seasonal variations in respiration rate indicative of an acclimation response. Differential expression analyses (RNAseq) revealed pronounced changes in gene expression among seasons, while laboratory CO2 exposure resulted in a lower number of differentially expressed transcripts. These gene expression studies, together with both respiration rate and shell condition metrics provide an integrated picture of the seasonal effect of CO2 on this sentinel species.

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Tumour cells down-regulate CCN2 gene expression in co-cultured fibroblasts in a Smad7- and ERK-dependent manner.

PubMed

van Rooyen, Beverley A; Schäfer, Georgia; Leaner, Virna D; Parker, M Iqbal

2013-10-03

Recent studies have revealed that interactions between tumour cells and the surrounding stroma play an important role in facilitating tumour growth and invasion. Stromal fibroblasts produce most of the extracellular matrix components found in the stroma. The aim of this study was to investigate mechanisms involved in tumour cell-mediated regulation of extracellular matrix and adhesion molecules in co-cultured fibroblasts. To this end, microarray analysis was performed on CCD-1068SK human fibroblast cells after direct co-culture with MDA-MB-231 human breast tumour cells. We found that the expression of both connective tissue growth factor (CTGF/CCN2) and type I collagen was negatively regulated in CCD-1068SK fibroblast cells under direct co-culture conditions. Further analysis revealed that Smad7, a known negative regulator of the Smad signalling pathway involved in CCN2 promoter regulation, was increased in directly co-cultured fibroblasts. Inhibition of Smad7 expression in CCD-1068SK fibroblasts resulted in increased CCN2 expression, while Smad7 overexpression had the opposite effect. Silencing CCN2 gene expression in fibroblasts led, in turn, to a decrease in type I collagen mRNA and protein levels. ERK signalling was also shown to be impaired in CCD-1068SK fibroblasts after direct co-culture with MDA-MB-231 tumour cells, with Smad7 overexpression in fibroblasts leading to a similar decrease in ERK activity. These effects were not, however, seen in fibroblasts that were indirectly co-cultured with tumour cells. We therefore conclude that breast cancer cells require close contact with fibroblasts in order to upregulate Smad7 which, in turn, leads to decreased ERK signalling resulting in diminished expression of the stromal proteins CCN2 and type I collagen.

ARNetMiT R Package: association rules based gene co-expression networks of miRNA targets.

PubMed

Özgür Cingiz, M; Biricik, G; Diri, B

2017-03-31

miRNAs are key regulators that bind to target genes to suppress their gene expression level. The relations between miRNA-target genes enable users to derive co-expressed genes that may be involved in similar biological processes and functions in cells. We hypothesize that target genes of miRNAs are co-expressed, when they are regulated by multiple miRNAs. With the usage of these co-expressed genes, we can theoretically construct co-expression networks (GCNs) related to 152 diseases. In this study, we introduce ARNetMiT that utilize a hash based association rule algorithm in a novel way to infer the GCNs on miRNA-target genes data. We also present R package of ARNetMiT, which infers and visualizes GCNs of diseases that are selected by users. Our approach assumes miRNAs as transactions and target genes as their items. Support and confidence values are used to prune association rules on miRNA-target genes data to construct support based GCNs (sGCNs) along with support and confidence based GCNs (scGCNs). We use overlap analysis and the topological features for the performance analysis of GCNs. We also infer GCNs with popular GNI algorithms for comparison with the GCNs of ARNetMiT. Overlap analysis results show that ARNetMiT outperforms the compared GNI algorithms. We see that using high confidence values in scGCNs increase the ratio of the overlapped gene-gene interactions between the compared methods. According to the evaluation of the topological features of ARNetMiT based GCNs, the degrees of nodes have power-law distribution. The hub genes discovered by ARNetMiT based GCNs are consistent with the literature.

Functional Geno,ic Analysis of Breast Cancer Cell Tumorigenicity Using a Noval Gene Silencing Resource

DTIC Science & Technology

2006-04-01

Fig. 2B). In addition, luciferase assay on cells co-transfected with constructs expressing firefly and renilla luciferase genes showed a significant...positive cells. (C) BT474 cells were co-transfected with pGL3 plasmid expressing firefly luciferase, pRL plasmid expressing renilla luciferase, and...genes Per1 (A) and Bmal1 (B). BT474 cells were transfected with Per1 (A) and Bmal1 (B) firefly luciferase reporters, pRL plasmid expressing renilla

Expression and characterization of an M cell-specific ligand-fused dengue virus tetravalent epitope using Saccharomyces cerevisiae.

PubMed

Nguyen, Ngoc-Luong; So, Kum-Kang; Kim, Jung-Mi; Kim, Sae-Hae; Jang, Yong-Suk; Yang, Moon-Sik; Kim, Dae-Hyuk

2015-01-01

A fusion construct (Tet-EDIII-Co1) consisting of an M cell-specific peptide ligand (Co1) at the C-terminus of a recombinant tetravalent gene encoding the amino acid sequences of dengue envelope domain III (Tet-EDIII) from four serotypes was expressed and tested for binding activity to the mucosal immune inductive site M cells for the development of an oral vaccine. The yeast episomal expression vector, pYEGPD-TER, which was designed to direct gene expression using the glyceraldehyde-3-phosphate dehydrogenase (GPD) promoter, a functional signal peptide of the amylase 1A protein from rice, and the GAL7 terminator, was used to clone the Tet-EDIII-Co1 gene and resultant plasmids were then used to transform Saccharomyces cerevisiae. PCR and back-transformation into Escherichia coli confirmed the presence of the Tet-EDIII-Co1 gene-containing plasmid in transformants. Northern blot analysis of transformed S. cerevisiae identified the presence of the Tet-EDIII-Co1-specific transcript. Western blot analysis indicated that the produced Tet-EDIII-Co1 protein with the expected molecular weight was successfully secreted into the culture medium. Quantitative Western blot analysis and ELISA revealed that the recombinant Tet-EDIII-Co1 protein comprised approximately 0.1-0.2% of cell-free extracts (CFEs). In addition, 0.1-0.2 mg of Tet-EDIII-Co1 protein per liter of culture filtrate was detected on day 1, and this quantity peaked on day 3 after cultivation. In vivo binding assays showed that the Tet-EDIII-Co1 protein was delivered specifically to M cells in Peyer's patches (PPs) while the Tet-EDIII protein lacking the Co1 ligand did not, which demonstrated the efficient targeting of this antigenic protein through the mucosal-specific ligand. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Initial deployment of the cardiogenic gene regulatory network in the basal chordate, Ciona intestinalis.

PubMed

Woznica, Arielle; Haeussler, Maximilian; Starobinska, Ella; Jemmett, Jessica; Li, Younan; Mount, David; Davidson, Brad

2012-08-01

The complex, partially redundant gene regulatory architecture underlying vertebrate heart formation has been difficult to characterize. Here, we dissect the primary cardiac gene regulatory network in the invertebrate chordate, Ciona intestinalis. The Ciona heart progenitor lineage is first specified by Fibroblast Growth Factor/Map Kinase (FGF/MapK) activation of the transcription factor Ets1/2 (Ets). Through microarray analysis of sorted heart progenitor cells, we identified the complete set of primary genes upregulated by FGF/Ets shortly after heart progenitor emergence. Combinatorial sequence analysis of these co-regulated genes generated a hypothetical regulatory code consisting of Ets binding sites associated with a specific co-motif, ATTA. Through extensive reporter analysis, we confirmed the functional importance of the ATTA co-motif in primary heart progenitor gene regulation. We then used the Ets/ATTA combination motif to successfully predict a number of additional heart progenitor gene regulatory elements, including an intronic element driving expression of the core conserved cardiac transcription factor, GATAa. This work significantly advances our understanding of the Ciona heart gene network. Furthermore, this work has begun to elucidate the precise regulatory architecture underlying the conserved, primary role of FGF/Ets in chordate heart lineage specification. Copyright © 2012 Elsevier Inc. All rights reserved.

ExAtlas: An interactive online tool for meta-analysis of gene expression data.

PubMed

Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

2015-12-01

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

The Metastasis Efficiency Modifier Ribosomal RNA Processing 1 Homolog B (RRP1B) Is a Chromatin-associated Factor*

PubMed Central

Crawford, Nigel P. S.; Yang, Hailiu; Mattaini, Katherine R.; Hunter, Kent W.

2009-01-01

There is accumulating evidence for a role of germ line variation in breast cancer metastasis. We have recently identified a novel metastasis susceptibility gene, Rrp1b (ribosomal RNA processing 1 homolog B). Overexpression of Rrp1b in a mouse mammary tumor cell line induces a gene expression signature that predicts survival in breast cancer. Here we extend the analysis of RRP1B function by demonstrating that the Rrp1b activation gene expression signature accurately predicted the outcome in three of four publicly available breast carcinoma gene expression data sets. In addition, we provide insights into the mechanism of RRP1B. Tandem affinity purification demonstrated that RRP1B physically interacts with many nucleosome binding factors, including histone H1X, poly(ADP-ribose) polymerase 1, TRIM28 (tripartite motif-containing 28), and CSDA (cold shock domain protein A). Co-immunofluorescence and co-immunoprecipitation confirmed these interactions and also interactions with heterochromatin protein-1α and acetyl-histone H4 lysine 5. Finally, we investigated the effects of ectopic expression of an RRP1B allelic variant previously associated with improved survival in breast cancer. Gene expression analyses demonstrate that, compared with ectopic expression of wild type RRP1B in HeLa cells, the variant RRP1B differentially modulates various transcription factors controlled by TRIM28 and CSDA. These data suggest that RRP1B, a tumor progression and metastasis susceptibility candidate gene, is potentially a dynamic modulator of transcription and chromatin structure. PMID:19710015

Identification and Analysis of a Gene from Calendula officinalis Encoding a Fatty Acid Conjugase

PubMed Central

Qiu, Xiao; Reed, Darwin W.; Hong, Haiping; MacKenzie, Samuel L.; Covello, Patrick S.

2001-01-01

Two homologous cDNAs, CoFad2 and CoFac2, were isolated from a Calendula officinalis developing seed by a polymerase chain reaction-based cloning strategy. Both sequences share similarity to FAD2 desaturases and FAD2-related enzymes. In C. officinalis plants CoFad2 was expressed in all tissues tested, whereas CoFac2 expression was specific to developing seeds. Expression of CoFad2 cDNA in yeast (Saccharomyces cerevisiae) indicated it encodes a Δ12 desaturase that introduces a double bond at the 12 position of 16:1(9Z) and 18:1(9Z). Expression of CoFac2 in yeast revealed that the encoded enzyme acts as a fatty acid conjugase converting 18:2(9Z, 12Z) to calendic acid 18:3(8E, 10E, 12Z). The enzyme also has weak activity on the mono-unsaturates 16:1(9Z) and 18:1(9Z) producing compounds with the properties of 8,10 conjugated dienes. PMID:11161042

Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

PubMed Central

Isaacson, Sven; Luo, Feng; Feltus, Frank A.; Smith, Melissa C.

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust. PMID:23409071

LncRNA and mRNA expression profiles of glioblastoma multiforme (GBM) reveal the potential roles of lncRNAs in GBM pathogenesis.

PubMed

Li, Qi; Jia, Hongmei; Li, Haowen; Dong, Chengya; Wang, Yajie; Zou, Zhongmei

2016-11-01

Glioblastoma multiforme (GBM) is the most common brain malignancy. Long non-coding RNAs (lncRNAs) are aberrantly expressed in many cancers and are involved in their cell proliferation, apoptosis, angiogenesis, and invasion. The functional roles of lncRNAs in GBM are less known. We analyzed a cohort of exon microarray datasets from The Cancer Genome Atlas. The differently expressed lncRNAs and mRNA were subjected to construct lncRNA-mRNA co-expression network. Probable functions for lncRNAs were predicted according to lncRNA-mRNA network and genomic adjacency by GO and pathway analysis. The expression of lncRNAs and mRNAs in GBM tissues versus normal brain tissues was examined by quantitative reverse transcription polymerase chain reaction. The 398 lncRNAs and 1995 mRNAs were identified as distinctively expressed in GBM. Probable functional roles for 98 lncRNAs were involved in 30 pathways and 32 gene functions related to tumorigenesis, development, and metastasis. The identified sets of key lncRNAs specific to GBM were subsequently verified by experiment in GBM tissues. Our reports predict the biological functions of a multitude of lncRNAs in GBM that could be potential diagnostic and prognostic biomarkers as well as therapeutic targets. Moreover, our research provides a road map for the identification and analysis of lncRNAs in tumors.

Unraveling the oral cancer lncRNAome: Identification of novel lncRNAs associated with malignant progression and HPV infection.

PubMed

Nohata, Nijiro; Abba, Martin C; Gutkind, J Silvio

2016-08-01

The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, we aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival. The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed. Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, we found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, we found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), we found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC. LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Unraveling the Oral Cancer lncRNAome: Identification of Novel lncRNAs Associated with Malignant Progression and HPV Infection

PubMed Central

Nohata, Nijiro; Abba, Martin C.; Gutkind, J. Silvio

2017-01-01

Objectives The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, we aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival. Materials and Methods The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed. Results Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, we found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, we found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), we found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC. Conclusion LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis. PMID:27424183

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

ADGO: analysis of differentially expressed gene sets using composite GO annotation.

PubMed

Nam, Dougu; Kim, Sang-Bae; Kim, Seon-Kyu; Yang, Sungjin; Kim, Seon-Young; Chu, In-Sun

2006-09-15

Genes are typically expressed in modular manners in biological processes. Recent studies reflect such features in analyzing gene expression patterns by directly scoring gene sets. Gene annotations have been used to define the gene sets, which have served to reveal specific biological themes from expression data. However, current annotations have limited analytical power, because they are classified by single categories providing only unary information for the gene sets. Here we propose a method for discovering composite biological themes from expression data. We intersected two annotated gene sets from different categories of Gene Ontology (GO). We then scored the expression changes of all the single and intersected sets. In this way, we were able to uncover, for example, a gene set with the molecular function F and the cellular component C that showed significant expression change, while the changes in individual gene sets were not significant. We provided an exemplary analysis for HIV-1 immune response. In addition, we tested the method on 20 public datasets where we found many 'filtered' composite terms the number of which reached approximately 34% (a strong criterion, 5% significance) of the number of significant unary terms on average. By using composite annotation, we can derive new and improved information about disease and biological processes from expression data. We provide a web application (ADGO: http://array.kobic.re.kr/ADGO) for the analysis of differentially expressed gene sets with composite GO annotations. The user can analyze Affymetrix and dual channel array (spotted cDNA and spotted oligo microarray) data for four species: human, mouse, rat and yeast. chu@kribb.re.kr http://array.kobic.re.kr/ADGO.

Network Analysis Implicates Alpha-Synuclein (Snca) in the Regulation of Ovariectomy-Induced Bone Loss

PubMed Central

Calabrese, Gina; Mesner, Larry D.; Foley, Patricia L.; Rosen, Clifford J.; Farber, Charles R.

2016-01-01

The postmenopausal period in women is associated with decreased circulating estrogen levels, which accelerate bone loss and increase the risk of fracture. Here, we gained novel insight into the molecular mechanisms mediating bone loss in ovariectomized (OVX) mice, a model of human menopause, using co-expression network analysis. Specifically, we generated a co-expression network consisting of 53 gene modules using expression profiles from intact and OVX mice from a panel of inbred strains. The expression of four modules was altered by OVX, including module 23 whose expression was decreased by OVX across all strains. Module 23 was enriched for genes involved in the response to oxidative stress, a process known to be involved in OVX-induced bone loss. Additionally, module 23 homologs were co-expressed in human bone marrow. Alpha synuclein (Snca) was one of the most highly connected “hub” genes in module 23. We characterized mice deficient in Snca and observed a 40% reduction in OVX-induced bone loss. Furthermore, protection was associated with the altered expression of specific network modules, including module 23. In summary, the results of this study suggest that Snca regulates bone network homeostasis and ovariectomy-induced bone loss. PMID:27378017

Co-expression network with protein-protein interaction and transcription regulation in malaria parasite Plasmodium falciparum.

PubMed

Yu, Fu-Dong; Yang, Shao-You; Li, Yuan-Yuan; Hu, Wei

2013-04-10

Malaria continues to be one of the most severe global infectious diseases, as a major threat to human health and economic development. Network-based biological analysis is a promising approach to uncover key genes and biological processes from a network viewpoint, which could not be recognized from individual gene-based signatures. We integrated gene co-expression profile with protein-protein interaction and transcriptional regulation information to construct a comprehensive gene co-expression network of Plasmodium falciparum. Based on this network, we identified 10 core modules by using ICE (Iterative Clique Enumeration) algorithm, which were essential for malaria parasite development in intraerythrocytic developmental cycle (IDC) stages. In each module, all genes were highly correlated probably due to co-regulation or formation of a protein complex. Some of these genes were recognized to be differentially coexpressed among three close-by IDC stages. The gene of prpf8 (PFD0265w) encoding pre-mRNA processing splicing factor 8 product was identified as DCGs (differentially co-expressed genes) among IDC stages, although this gene function was seldom reported in previous researches. Integrating the species-specific gene prediction and differential co-expression gene detection, we found some modules could perform species-specific functions according to some of genes in these modules were species-specific genes, like the module 10. Furthermore, in order to reveal the underlying mechanisms of the erythrocyte invasion by P. falciparum, Steiner Tree algorithm was employed to identify the invasion subnetwork from our gene co-expression network. The subnetwork-based analysis indicated that some important Plasmodium parasite specific genes could corporate with each other and be co-regulated during the parasite invasion process, which including a head-to-head gene pair of PfRH2a (PF13_0198) and PfRH2b (MAL13P1.176). This study based on gene co-expression network could shed new insights on the mechanisms of pathogenesis, even virulence and P. falciparum development. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

EMMPRIN co-expressed with matrix metalloproteinases predicts poor prognosis in patients with osteosarcoma.

PubMed

Futamura, Naohisa; Nishida, Yoshihiro; Urakawa, Hiroshi; Kozawa, Eiji; Ikuta, Kunihiro; Hamada, Shunsuke; Ishiguro, Naoki

2014-06-01

Several studies have focused on the relationships between the expression of extracellular matrix metalloproteinase inducer (EMMPRIN) and the prognosis of patients with malignant tumors. However, few of these have investigated the expression of EMMPRIN in osteosarcoma. We examined expression levels of EMMPRIN immunohistochemically in 53 cases of high-grade osteosarcoma of the extremities and analyzed the correlation of its expression with patient prognosis. The correlation between matrix metalloproteinases (MMPs) and EMMPRIN expression and the prognostic value of co-expression were also analyzed. Staining positivity for EMMPRIN was negative in 7 cases, low in 17, moderate in 19, and strong in 10. The overall and disease-free survivals (OS and DFS) in patients with higher EMMPRIN expression (strong-moderate) were significantly lower than those in the lower (weak-negative) group (0.037 and 0.024, respectively). In multivariate analysis, age (P=0.004), location (P=0.046), and EMMPRIN expression (P=0.038) were significant prognostic factors for overall survival. EMMPRIN expression (P=0.024) was also a significant prognostic factor for disease-free survival. Co-expression analyses of EMMPRIN and MMPs revealed that strong co-expression of EMMPRIN and membrane-type 1 (MT1)-MMP had a poor prognostic value (P=0.056 for DFS, P=0.006 for OS). EMMPRIN expression and co-expression with MMPs well predict the prognosis of patients with extremity osteosarcoma, making EMMPRIN a possible therapeutic target in these patients.

A kinetic model for the synthesis of high-molecular-weight alcohols over a sulfided Co-K-Mo/C catalyst

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

Gunturu, A.K.; Kugler, E.L.; Cropley, J.B.

A statistically designed set of experiments was run in a recycle reactor to evaluate the kinetics of the formation of higher-molecular-weight alcohols (higher alcohols) and total hydrocarbon byproducts from synthesis gas (hydrogen and carbon monoxide) in a range of experimental conditions that mirrors the limits of commercial production. The alkali-promoted, C-supported Co-Mo sulfide catalyst that was employed in this study is well known for its sulfur resistance. The reaction was carried out in a gradientless Berty-type recycle reactor. A two-level fractional-factorial set consisting of 16 experiments was performed. Five independent variables were selected for this study, namely, temperature, partial pressuremore » of carbon monoxide, partial pressure of hydrogen, partial pressure of inerts, and methanol concentration in the feed. The major oxygenated products were linear alcohols up to n-butanol, but alcohols of higher carbon number were also detected, and analysis of the liquid product revealed the presence of trace amounts of ethers also. Yields of hydrocarbons were non-negligible. The alcohol product followed an Anderson-Schultz-Flory distribution. From the results of the factorial experiments, a preliminary power-law model was developed, and the statistically significant variables in the rate expression for the production of each alcohol were found. Based on the results of the power-law models, rate expressions of the Langmuir-Hinshelwood type were fitted. The observed kinetics are consistent with the rate-limiting step for the production of each higher alcohol being a surface reaction of the alcohol of next-lower carbon number. All other steps, including CO-insertion, H{sub 2}-cleavage, and hydrogenation steps, do not appear to affect the rate correlations.« less

Identification of cyclin B1 and Sec62 as biomarkers for recurrence in patients with HBV-related hepatocellular carcinoma after surgical resection.

PubMed

Weng, Li; Du, Juan; Zhou, Qinghui; Cheng, Binbin; Li, Jun; Zhang, Denghai; Ling, Changquan

2012-06-08

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. Frequent tumor recurrence after surgery is related to its poor prognosis. Although gene expression signatures have been associated with outcome, the molecular basis of HCC recurrence is not fully understood, and there is no method to predict recurrence using peripheral blood mononuclear cells (PBMCs), which can be easily obtained for recurrence prediction in the clinical setting. According to the microarray analysis results, we constructed a co-expression network using the k-core algorithm to determine which genes play pivotal roles in the recurrence of HCC associated with the hepatitis B virus (HBV) infection. Furthermore, we evaluated the mRNA and protein expressions in the PBMCs from 80 patients with or without recurrence and 30 healthy subjects. The stability of the signatures was determined in HCC tissues from the same 80 patients. Data analysis included ROC analysis, correlation analysis, log-lank tests, and Cox modeling to identify independent predictors of tumor recurrence. The tumor-associated proteins cyclin B1, Sec62, and Birc3 were highly expressed in a subset of samples of recurrent HCC; cyclin B1, Sec62, and Birc3 positivity was observed in 80%, 65.7%, and 54.2% of the samples, respectively. The Kaplan-Meier analysis revealed that high expression levels of these proteins was associated with significantly reduced recurrence-free survival. Cox proportional hazards model analysis revealed that cyclin B1 (hazard ratio [HR], 4.762; p = 0.002) and Sec62 (HR, 2.674; p = 0.018) were independent predictors of HCC recurrence. These results revealed that cyclin B1 and Sec62 may be candidate biomarkers and potential therapeutic targets for HBV-related HCC recurrence after surgery.

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of results

NASA Astrophysics Data System (ADS)

Asefi-Najafabady, S.; Rayner, P. J.; Gurney, K. R.; McRobert, A.; Song, Y.; Coltin, K.; Huang, J.; Elvidge, C.; Baugh, K.

2014-09-01

High-resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high-resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long-term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long-term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter-term variations reveals the impact of the 2008-2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.

PubMed

Feltus, F Alex; Ficklin, Stephen P; Gibson, Scott M; Smith, Melissa C

2013-06-05

In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study

PubMed Central

2013-01-01

Background In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. Results A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Conclusions Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired. PMID:23738693

Global Analysis of Differentially Expressed Genes and Proteins in the Wheat Callus Infected by Agrobacterium tumefaciens

PubMed Central

Zhou, Xiaohong; Wang, Ke; Lv, Dongwen; Wu, Chengjun; Li, Jiarui; Zhao, Pei; Lin, Zhishan; Du, Lipu; Yan, Yueming; Ye, Xingguo

2013-01-01

Agrobacterium-mediated plant transformation is an extremely complex and evolved process involving genetic determinants of both the bacteria and the host plant cells. However, the mechanism of the determinants remains obscure, especially in some cereal crops such as wheat, which is recalcitrant for Agrobacterium-mediated transformation. In this study, differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) were analyzed in wheat callus cells co-cultured with Agrobacterium by using RNA sequencing (RNA-seq) and two-dimensional electrophoresis (2-DE) in conjunction with mass spectrometry (MS). A set of 4,889 DEGs and 90 DEPs were identified, respectively. Most of them are related to metabolism, chromatin assembly or disassembly and immune defense. After comparative analysis, 24 of the 90 DEPs were detected in RNA-seq and proteomics datasets simultaneously. In addition, real-time RT-PCR experiments were performed to check the differential expression of the 24 genes, and the results were consistent with the RNA-seq data. According to gene ontology (GO) analysis, we found that a big part of these differentially expressed genes were related to the process of stress or immunity response. Several putative determinants and candidate effectors responsive to Agrobacterium mediated transformation of wheat cells were discussed. We speculate that some of these genes are possibly related to Agrobacterium infection. Our results will help to understand the interaction between Agrobacterium and host cells, and may facilitate developing efficient transformation strategies in cereal crops. PMID:24278131

Human primitive brain displays negative mitochondrial-nuclear expression correlation of respiratory genes.

PubMed

Barshad, Gilad; Blumberg, Amit; Cohen, Tal; Mishmar, Dan

2018-06-14

Oxidative phosphorylation (OXPHOS), a fundamental energy source in all human tissues, requires interactions between mitochondrial (mtDNA)- and nuclear (nDNA)-encoded protein subunits. Although such interactions are fundamental to OXPHOS, bi-genomic coregulation is poorly understood. To address this question, we analyzed ∼8500 RNA-seq experiments from 48 human body sites. Despite well-known variation in mitochondrial activity, quantity, and morphology, we found overall positive mtDNA-nDNA OXPHOS genes' co-expression across human tissues. Nevertheless, negative mtDNA-nDNA gene expression correlation was identified in the hypothalamus, basal ganglia, and amygdala (subcortical brain regions, collectively termed the "primitive" brain). Single-cell RNA-seq analysis of mouse and human brains revealed that this phenomenon is evolutionarily conserved, and both are influenced by brain cell types (involving excitatory/inhibitory neurons and nonneuronal cells) and by their spatial brain location. As the "primitive" brain is highly oxidative, we hypothesized that such negative mtDNA-nDNA co-expression likely controls for the high mtDNA transcript levels, which enforce tight OXPHOS regulation, rather than rewiring toward glycolysis. Accordingly, we found "primitive" brain-specific up-regulation of lactate dehydrogenase B ( LDHB ), which associates with high OXPHOS activity, at the expense of LDHA , which promotes glycolysis. Analyses of co-expression, DNase-seq, and ChIP-seq experiments revealed candidate RNA-binding proteins and CEBPB as the best regulatory candidates to explain these phenomena. Finally, cross-tissue expression analysis unearthed tissue-dependent splice variants and OXPHOS subunit paralogs and allowed revising the list of canonical OXPHOS transcripts. Taken together, our analysis provides a comprehensive view of mito-nuclear gene co-expression across human tissues and provides overall insights into the bi-genomic regulation of mitochondrial activities. © 2018 Barshad et al.; Published by Cold Spring Harbor Laboratory Press.

The induction of heme oxygenase-1 suppresses heat shock protein 90 and the proliferation of human breast cancer cells through its byproduct carbon monoxide

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

Lee, Wen-Ying; Department of Pathology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Chen, Yen-Chou

2014-01-01

Heme oxygenase (HO)-1 is an oxidative stress-response enzyme which catalyzes the degradation of heme into bilirubin, ferric ion, and carbon monoxide (CO). Induction of HO-1 was reported to have antitumor activity; the inhibitory mechanism, however, is still unclear. In the present study, we found that treatment with [Ru(CO){sub 3}Cl{sub 2}]{sub 2} (RuCO), a CO-releasing compound, reduced the growth of human MCF7 and MDA-MB-231 breast cancer cells. Analysis of growth-related proteins showed that treatment with RuCO down-regulated cyclinD1, CDK4, and hTERT protein expressions. Interestingly, RuCO treatment resulted in opposite effects on wild-type and mutant p53 proteins. These results were similar tomore » those of cells treated with geldanamycin (a heat shock protein (HSP)90 inhibitor), suggesting that RuCO might affect HSP90 activity. Moreover, RuCO induced mutant p53 protein destabilization accompanied by promotion of ubiquitination and proteasome degradation. The induction of HO-1 by cobalt protoporphyrin IX (CoPP) showed consistent results, while the addition of tin protoporphyrin IX (SnPP), an HO-1 enzymatic inhibitor, diminished the RuCO-mediated effect. RuCO induction of HO-1 expression was reduced by a p38 mitogen-activated protein kinase inhibitor (SB203580). Additionally, treatment with a chemopreventive compound, curcumin, induced HO-1 expression accompanied with reduction of HSP90 client protein expression. The induction of HO-1 by curcumin inhibited 12-O-tetradecanoyl-13-acetate (TPA)-elicited matrix metalloproteinase-9 expression and tumor invasion. In conclusion, we provide novel evidence underlying HO-1's antitumor mechanism. CO, a byproduct of HO-1, suppresses HSP90 protein activity, and the induction of HO-1 may possess potential as a cancer therapeutic. - Highlights: • CO and HO-1 inhibited the growth of human breast cancer cells. • CO and HO-1 attenuated HSP90 and its client proteins expression. • CO induced mutant p53 protein ubiquitination and degradation. • Curcumin induced HO-1 expression and attenuated HSP90's client proteins expression.« less

Gene Expression Profiling in BRAF-Mutated Melanoma Reveals Patient Subgroups with Poor Outcomes to Vemurafenib That May Be Overcome by Cobimetinib Plus Vemurafenib.

PubMed

Wongchenko, Matthew J; McArthur, Grant A; Dréno, Brigitte; Larkin, James; Ascierto, Paolo A; Sosman, Jeffrey; Andries, Luc; Kockx, Mark; Hurst, Stephen D; Caro, Ivor; Rooney, Isabelle; Hegde, Priti S; Molinero, Luciana; Yue, Huibin; Chang, Ilsung; Amler, Lukas; Yan, Yibing; Ribas, Antoni

2017-09-01

Purpose: The association of tumor gene expression profiles with progression-free survival (PFS) outcomes in patients with BRAF V600 -mutated melanoma treated with vemurafenib or cobimetinib combined with vemurafenib was evaluated. Experimental Design: Gene expression of archival tumor samples from patients in four trials (BRIM-2, BRIM-3, BRIM-7, and coBRIM) was evaluated. Genes significantly associated with PFS ( P < 0.05) were identified by univariate Cox proportional hazards modeling, then subjected to unsupervised hierarchical clustering, principal component analysis, and recursive partitioning to develop optimized gene signatures. Results: Forty-six genes were identified as significantly associated with PFS in both BRIM-2 ( n = 63) and the vemurafenib arm of BRIM-3 ( n = 160). Two distinct signatures were identified: cell cycle and immune. Among vemurafenib-treated patients, the cell-cycle signature was associated with shortened PFS compared with the immune signature in the BRIM-2/BRIM-3 training set [hazard ratio (HR) 1.8; 95% confidence interval (CI), 1.3-2.6, P = 0.0001] and in the coBRIM validation set ( n = 101; HR, 1.6; 95% CI, 1.0-2.5; P = 0.08). The adverse impact of the cell-cycle signature on PFS was not observed in patients treated with cobimetinib combined with vemurafenib ( n = 99; HR, 1.1; 95% CI, 0.7-1.8; P = 0.66). Conclusions: In vemurafenib-treated patients, the cell-cycle gene signature was associated with shorter PFS. However, in cobimetinib combined with vemurafenib-treated patients, both cell cycle and immune signature subgroups had comparable PFS. Cobimetinib combined with vemurafenib may abrogate the adverse impact of the cell-cycle signature. Clin Cancer Res; 23(17); 5238-45. ©2017 AACR . ©2017 American Association for Cancer Research.

Random forests-based differential analysis of gene sets for gene expression data.

PubMed

Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

2013-04-10

In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for interpretation of data in complex biological systems. The classifications of biologically defined gene sets can reveal the underlying interactions of gene sets associated with the phenotypes, and provide an insightful complement to conventional gene set analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

8D.07: GENE EXPRESSION ANALYSIS AND BIOINFORMATICS REVEALED POTENTIAL TRANSCRIPTION FACTORS ASSOCIATED WITH RENIN-ANGIOTENSIN-ALDOSTERONE SYSTEM IN ATHEROMA.

PubMed

Nehme, A; Zibara, K; Cerutti, C; Bricca, G

2015-06-01

The implication of the renin-angiotensin-aldosterone system (RAAS) in atheroma development is well described. However, a complete view of the local RAAS in atheroma is still missing. In this study we aimed to reveal the organization of RAAS in atheroma at the transcriptomic level and identify the transcriptional regulators behind it. Extended RAAS (extRAAS) was defined as the set of 37 genes coding for classical and novel RAAS participants (Figure 1). Five microarray datasets containing overall 590 samples representing carotid and peripheral atheroma were downloaded from the GEO database. Correlation-based hierarchical clustering (R software) of extRAAS genes within each dataset allowed the identification of modules of co-expressed genes. Reproducible co-expression modules across datasets were then extracted. Transcription factors (TFs) having common binding sites (TFBSs) in the promoters of coordinated genes were identified using the Genomatix database tools and analyzed for their correlation with extRAAS genes in the microarray datasets. Expression data revealed the expressed extRAAS components and their relative abundance displaying the favored pathways in atheroma. Three co-expression modules with more than 80% reproducibility across datasets were extracted. Two of them (M1 and M2) contained genes coding for angiotensin metabolizing enzymes involved in different pathways: M1 included ACE, MME, RNPEP, and DPP3, in addition to 7 other genes; and M2 included CMA1, CTSG, and CPA3. The third module (M3) contained genes coding for receptors known to be implicated in atheroma (AGTR1, MR, GR, LNPEP, EGFR and GPER). M1 and M3 were negatively correlated in 3 of 5 datasets. We identified 19 TFs that have enriched TFBSs in the promoters of genes of M1, and two for M3, but none was found for M2. Among the extracted TFs, ELF1, MAX, and IRF5 showed significant positive correlations with peptidase-coding genes from M1 and negative correlations with receptors-coding genes from M3 (p < 0.05). The identified co-expression modules display the transcriptional organization of local extRAAS in human carotid atheroma. The identification of several TFs potentially associated to extRAAS genes may provide a frame for the discovery of atheroma-specific modulators of extRAAS activity.(Figure is included in full-text article.).

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants.

PubMed

Chow, Chi-Nga; Zheng, Han-Qin; Wu, Nai-Yun; Chien, Chia-Hung; Huang, Hsien-Da; Lee, Tzong-Yi; Chiang-Hsieh, Yi-Fan; Hou, Ping-Fu; Yang, Tien-Yi; Chang, Wen-Chi

2016-01-04

Transcription factors (TFs) are sequence-specific DNA-binding proteins acting as critical regulators of gene expression. The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN2.itps.ncku.edu.tw) provides an informative resource for detecting transcription factor binding sites (TFBSs), corresponding TFs, and other important regulatory elements (CpG islands and tandem repeats) in a promoter or a set of plant promoters. Additionally, TFBSs, CpG islands, and tandem repeats in the conserve regions between similar gene promoters are also identified. The current PlantPAN release (version 2.0) contains 16 960 TFs and 1143 TF binding site matrices among 76 plant species. In addition to updating of the annotation information, adding experimentally verified TF matrices, and making improvements in the visualization of transcriptional regulatory networks, several new features and functions are incorporated. These features include: (i) comprehensive curation of TF information (response conditions, target genes, and sequence logos of binding motifs, etc.), (ii) co-expression profiles of TFs and their target genes under various conditions, (iii) protein-protein interactions among TFs and their co-factors, (iv) TF-target networks, and (v) downstream promoter elements. Furthermore, a dynamic transcriptional regulatory network under various conditions is provided in PlantPAN 2.0. The PlantPAN 2.0 is a systematic platform for plant promoter analysis and reconstructing transcriptional regulatory networks. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Asymptotic co- and post-seismic displacements in a homogeneous Maxwell sphere

NASA Astrophysics Data System (ADS)

Tang, He; Sun, Wenke

2018-07-01

The deformations of the Earth caused by internal and external forces are usually expressed through Green's functions or the superposition of normal modes, that is, via numerical methods, which are applicable for computing both co- and post-seismic deformations. It is difficult to express these deformations in an analytical form, even for a uniform viscoelastic sphere. In this study, we present a set of asymptotic solutions for computing co- and post-seismic displacements; these solutions can be further applied to solving co- and post-seismic geoid, gravity and strain changes. Expressions are derived for a uniform Maxwell Earth by combining the reciprocity theorem, which links earthquake, tidal, shear and loading deformations, with the asymptotic solutions of these three external forces (tidal, shear and loading) and analytical inverse Laplace transformation formulae. Since the asymptotic solutions are given in a purely analytical form without series summations or extra convergence skills, they can be practically applied in an efficient way, especially when computing post-seismic deformations and glacial isotactic adjustments of the Earth over long timescales.

Asymptotic Co- and Post-seismic displacements in a homogeneous Maxwell sphere

NASA Astrophysics Data System (ADS)

Tang, He; Sun, Wenke

2018-05-01

The deformations of the Earth caused by internal and external forces are usually expressed through Green's functions or the superposition of normal modes, i.e. via numerical methods, which are applicable for computing both co- and post-seismic deformations. It is difficult to express these deformations in an analytical form, even for a uniform viscoelastic sphere. In this study, we present a set of asymptotic solutions for computing co- and post-seismic displacements; these solutions can be further applied to solving co- and post-seismic geoid, gravity, and strain changes. Expressions are derived for a uniform Maxwell Earth by combining the reciprocity theorem, which links earthquake, tidal, shear and loading deformations, with the asymptotic solutions of these three external forces (tidal, shear and loading) and analytical inverse Laplace transformation formulae. Since the asymptotic solutions are given in a purely analytical form without series summations or extra convergence skills, they can be practically applied in an efficient way, especially when computing post-seismic deformations and glacial isotactic adjustments of the Earth over long timescales.

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2017-01-25

With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

Expression of a putative dioxygenase gene adjacent to an insertion mutation is involved in the short internodes of columnar apples (Malus × domestica).

PubMed

Okada, Kazuma; Wada, Masato; Moriya, Shigeki; Katayose, Yuichi; Fujisawa, Hiroko; Wu, Jianzhong; Kanamori, Hiroyuki; Kurita, Kanako; Sasaki, Harumi; Fujii, Hiroshi; Terakami, Shingo; Iwanami, Hiroshi; Yamamoto, Toshiya; Abe, Kazuyuki

2016-11-01

Determining the molecular mechanism of fruit tree architecture is important for tree management and fruit production. An apple mutant 'McIntosh Wijcik', which was discovered as a bud mutation from 'McIntosh', exhibits a columnar growth phenotype that is controlled by a single dominant gene, Co. In this study, the mutation and the Co gene were analyzed. Fine mapping narrowed the Co region to a 101 kb region. Sequence analysis of the Co region and the original wild-type co region identified an insertion mutation of an 8202 bp long terminal repeat (LTR) retroposon in the Co region. Segregation analysis using a DNA marker based on the insertion polymorphism showed that the LTR retroposon was closely associated with the columnar growth phenotype. RNA-seq and RT-PCR analysis identified a promising Co candidate gene (91071-gene) within the Co region that is specifically expressed in 'McIntosh Wijcik' but not in 'McIntosh'. The 91071-gene was located approximately 16 kb downstream of the insertion mutation and is predicted to encode a 2-oxoglutarate-dependent dioxygenase involved in an unknown reaction. Overexpression of the 91071-gene in transgenic tobaccos and apples resulted in phenotypes with short internodes, like columnar apples. These data suggested that the 8202 bp retroposon insertion in 'McIntosh Wijcik' is associated with the short internodes of the columnar growth phenotype via upregulated expression of the adjacent 91071-gene. Furthermore, the DNA marker based on the insertion polymorphism could be useful for the marker-assisted selection of columnar apples.

A computational model-based validation of Guyton's analysis of cardiac output and venous return curves

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.; Mark, R. G.

2002-01-01

Guyton developed a popular approach for understanding the factors responsible for cardiac output (CO) regulation in which 1) the heart-lung unit and systemic circulation are independently characterized via CO and venous return (VR) curves, and 2) average CO and right atrial pressure (RAP) of the intact circulation are predicted by graphically intersecting the curves. However, this approach is virtually impossible to verify experimentally. We theoretically evaluated the approach with respect to a nonlinear, computational model of the pulsatile heart and circulation. We developed two sets of open circulation models to generate CO and VR curves, differing by the manner in which average RAP was varied. One set applied constant RAPs, while the other set applied pulsatile RAPs. Accurate prediction of intact, average CO and RAP was achieved only by intersecting the CO and VR curves generated with pulsatile RAPs because of the pulsatility and nonlinearity (e.g., systemic venous collapse) of the intact model. The CO and VR curves generated with pulsatile RAPs were also practically independent. This theoretical study therefore supports the validity of Guyton's graphical analysis.

Heterogeneity and phenotypic plasticity of glial cells in the mammalian enteric nervous system.

PubMed

Boesmans, Werend; Lasrado, Reena; Vanden Berghe, Pieter; Pachnis, Vassilis

2015-02-01

Enteric glial cells are vital for the autonomic control of gastrointestinal homeostasis by the enteric nervous system. Several different functions have been assigned to enteric glial cells but whether these are performed by specialized subtypes with a distinctive phenotype and function remains elusive. We used Mosaic Analysis with Double Markers and inducible lineage tracing to characterize the morphology and dynamic molecular marker expression of enteric GLIA in the myenteric plexus. Functional analysis in individually identified enteric glia was performed by Ca(2+) imaging. Our experiments have identified four morphologically distinct subpopulations of enteric glia in the gastrointestinal tract of adult mice. Marker expression analysis showed that the majority of glia in the myenteric plexus co-express glial fibrillary acidic protein (GFAP), S100β, and Sox10. However, a considerable fraction (up to 80%) of glia outside the myenteric ganglia, did not label for these markers. Lineage tracing experiments suggest that these alternative combinations of markers reflect dynamic gene regulation rather than lineage restrictions. At the functional level, the three myenteric glia subtypes can be distinguished by their differential response to adenosine triphosphate. Together, our studies reveal extensive heterogeneity and phenotypic plasticity of enteric glial cells and set a framework for further investigations aimed at deciphering their role in digestive function and disease. © 2014 Wiley Periodicals, Inc.

Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite.

PubMed

Peng, Hui; Lan, Chaowang; Zheng, Yi; Hutvagner, Gyorgy; Tao, Dacheng; Li, Jinyan

2017-03-24

MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics. We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs. With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.

Turning publicly available gene expression data into discoveries using gene set context analysis.

PubMed

Ji, Zhicheng; Vokes, Steven A; Dang, Chi V; Ji, Hongkai

2016-01-08

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

PubMed

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

The Dissociative Subtype of Posttraumatic Stress Disorder (PTSD) Among Adolescents: Co-Occurring PTSD, Depersonalization/Derealization, and Other Dissociation Symptoms.

PubMed

Choi, Kristen R; Seng, Julia S; Briggs, Ernestine C; Munro-Kramer, Michelle L; Graham-Bermann, Sandra A; Lee, Robert C; Ford, Julian D

2017-12-01

The purpose of this study was to examine the co-occurrence of posttraumatic stress disorder (PTSD) and dissociation in a clinical sample of trauma-exposed adolescents by evaluating evidence for the depersonalization/derealization dissociative subtype of PTSD as defined by the DSM-5 and then examining a broader set of dissociation symptoms. A sample of treatment-seeking, trauma-exposed adolescents 12 to 16 years old (N = 3,081) from the National Child Traumatic Stress Network Core Data Set was used to meet the study objectives. Two models of PTSD/dissociation co-occurrence were estimated using latent class analysis, one with 2 dissociation symptoms and the other with 10 dissociation symptoms. After model selection, groups within each model were compared on demographics, trauma characteristics, and psychopathology. Model A, the depersonalization/derealization model, had 5 classes: dissociative subtype/high PTSD; high PTSD; anxious arousal; dysphoric arousal; and a low symptom/reference class. Model B, the expanded dissociation model, identified an additional class characterized by dissociative amnesia and detached arousal. These 2 models provide new information about the specific ways PTSD and dissociation co-occur and illuminate some differences between adult and adolescent trauma symptom expression. A dissociative subtype of PTSD can be distinguished from PTSD alone in adolescents, but assessing a wider range of dissociative symptoms is needed to fully characterize adolescent traumatic stress responses. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease

PubMed Central

Romero-Garmendia, Irati; Jauregi-Miguel, Amaia; Plaza-Izurieta, Leticia; Cros, Marie-Pierre; Legarda, Maria; Irastorza, Iñaki; Herceg, Zdenko; Fernandez-Jimenez, Nora

2018-01-01

The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models. PMID:29748492

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease.

PubMed

Romero-Garmendia, Irati; Garcia-Etxebarria, Koldo; Hernandez-Vargas, Hector; Santin, Izortze; Jauregi-Miguel, Amaia; Plaza-Izurieta, Leticia; Cros, Marie-Pierre; Legarda, Maria; Irastorza, Iñaki; Herceg, Zdenko; Fernandez-Jimenez, Nora; Bilbao, Jose Ramon

2018-05-10

The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models.

Isolation of genes negatively or positively co-expressed with human recombination activating gene 1 (RAG1) by differential display PCR (DD RT-PCR).

PubMed

Verkoczy, L K; Berinstein, N L

1998-10-01

Differential display PCR (DD RT-PCR) has been extensively used for analysis of differential gene expression, but continues to be hampered by technical limitations that impair its effectiveness. In order to isolate novel genes co-expressing with human RAG1, we have developed an effective, multi-tiered screening/purification approach which effectively complements the standard DD RT-PCR methodology. In 'primary' screens, standard DD RT-PCR was used, detecting 22 reproducible differentially expressed amplicons between clonally related cell variants with differential constitutive expression of RAG mRNAs. 'Secondary' screens used differential display (DD) amplicons as probes in low and high stringency northern blotting. Eight of 22 independent DD amplicons detected nine independent differentially expressed transcripts. 'Tertiary' screens used reconfirmed amplicons as probes in northern analysis of multiple RAG-and RAG+sources. Reconfirmed DD amplicons detected six independent RAG co-expressing transcripts. All DD amplicons reconfirmed by northern blot were a heterogeneous mixture of cDNAs, necessitating further purification to isolate single cDNAs prior to subcloning and sequencing. To effectively select the appropriate cDNAs from DD amplicons, we excised and eluted the cDNA(s) directly from regions of prior northern blots in which differentially expressed transcripts were detected. Sequences of six purified cDNA clones specifically detecting RAG co-expressing transcripts included matches to portions of the human RAG2 and BSAP regions and to four novel partial cDNAs (three with homologies to human ESTs). Overall, our results also suggest that even when using clonally related variants from the same cell line in addition to all appropriate internal controls previously reported, further screening and purification steps are still required in order to efficiently and specifically isolate differentially expressed genes by DD RT-PCR.

Differential co-expression analysis of rheumatoid arthritis with microarray data.

PubMed

Wang, Kunpeng; Zhao, Liqiang; Liu, Xuefeng; Hao, Zhenyong; Zhou, Yong; Yang, Chuandong; Li, Hongqiang

2014-11-01

The aim of the present study was to investigate the underlying molecular mechanisms of rheumatoid arthritis (RA) using microarray expression profiles from osteoarthritis and RA patients, to improve diagnosis and treatment strategies for the condition. The gene expression profile of GSE27390 was downloaded from Gene Expression Omnibus, including 19 samples from patients with RA (n=9) or osteoarthritis (n=10). Firstly, the differentially expressed genes (DEGs) were obtained with the thresholds of |logFC|>1.0 and P<0.05, using the t‑test method in LIMMA package. Then, differentially co-expressed genes (DCGs) and differentially co-expressed links (DCLs) were screened with q<0.25 by the differential coexpression analysis and differential regulation analysis of gene expression microarray data package. Secondly, pathway enrichment analysis for DCGs was performed by the Database for Annotation, Visualization and Integrated Discovery and the DCLs associated with RA were selected by comparing the obtained DCLs with known transcription factor (TF)-targets in the TRANSFAC database. Finally, the obtained TFs were mapped to the known TF-targets to construct the network using cytoscape software. A total of 1755 DEGs, 457 DCGs and 101988 DCLs were achieved and there were 20 TFs in the obtained six TF-target relations (STAT3-TNF, PBX1‑PLAU, SOCS3-STAT3, GATA1-ETS2, ETS1-ICAM4 and CEBPE‑GATA1) and 457 DCGs. A number of TF-target relations in the constructed network were not within DCLs when the TF and target gene were DCGs. The identified TFs may have an important role in the pathogenesis of RA and have the potential to be used as biomarkers for the development of novel diagnostic and therapeutic strategies for RA.

A network approach of gene co-expression in the zea mays/Aspergillus flavus pathosystem to map host/pathogen interaction pathways

USDA-ARS?s Scientific Manuscript database

A gene co-expression network was generated using a dual RNA-seq study with the fungal pathogen A. flavus and its plant host Z. mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network reveal...

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

PubMed

Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of host transcriptional networks showing concentration-dependent regulation by HPV16 E6 and E7 proteins in basal cervical squamous epithelial cells

PubMed Central

Smith, Stephen P.; Scarpini, Cinzia G.; Groves, Ian J.; Odle, Richard I.; Coleman, Nicholas

2016-01-01

Development of cervical squamous cell carcinoma requires increased expression of the major high-risk human-papillomavirus (HPV) oncogenes E6 and E7 in basal cervical epithelial cells. We used a systems biology approach to identify host transcriptional networks in such cells and study the concentration-dependent changes produced by HPV16-E6 and -E7 oncoproteins. We investigated sample sets derived from the W12 model of cervical neoplastic progression, for which high quality phenotype/genotype data were available. We defined a gene co-expression matrix containing a small number of highly-connected hub nodes that controlled large numbers of downstream genes (regulons), indicating the scale-free nature of host gene co-expression in W12. We identified a small number of ‘master regulators’ for which downstream effector genes were significantly associated with protein levels of HPV16 E6 (n = 7) or HPV16 E7 (n = 5). We validated our data by depleting E6/E7 in relevant cells and by functional analysis of selected genes in vitro. We conclude that the network of transcriptional interactions in HPV16-infected basal-type cervical epithelium is regulated in a concentration-dependent manner by E6/E7, via a limited number of central master-regulators. These effects are likely to be significant in cervical carcinogenesis, where there is competitive selection of cells with elevated expression of virus oncoproteins. PMID:27457222

Co-Expression of Bmi-1 and Podoplanin Predicts Overall Survival in Patients With Squamous Cell Carcinoma of the Head and Neck Treated With Radio(chemo)therapy

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

Vormittag, Laurenz; Thurnher, Dietmar; Geleff, Silvana

2009-03-01

Purpose: This study was conducted to determine the expression of Bmi-1 and podoplanin in healthy oral mucosa and in untreated tumor tissues samples of patients with squamous cell carcinomas of the head and neck. All patients were treated by primary radio(chemo)therapy. Methods and Materials: The expression of Bmi-1 and podoplanin was immunohistochemically evaluated in 12 normal oral mucosa and 63 tumor specimens and correlated with patients' clinical data. Results: In healthy mucosa expression of Bmi-1 and podoplanin was restricted to the basal cell layer. Expression of both proteins was found in 79% and 86% of our tumor samples, respectively. Inmore » 17 and 8 samples, Bmi-1 and podoplanin were co-expressed at the invasive border or diffuse in the bulk of the tumor, respectively. Univariate analysis showed that the co-expression of Bmi-1 and podoplanin correlated to decreased overall survival (p = 0.044). Moreover, multivariate testing identified high expression of podoplanin (p = 0.044), co-expression of Bmi-1 and podoplanin (p = 0.007) and lack of response to therapy (p < 0.0001) as predictors of shortened overall survival in patients treated with primary radio(chemo)therapy. Conclusions: Bmi-1 and podoplanin are expressed at the invasive front of squamous cell carcinomas of the head and neck. Co-expression of Bmi-1 and podoplanin predicts significantly overall survival of patients treated with primary radio(chemo)therapy.« less

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets.

PubMed

Lemieux, Sebastien; Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J; Mader, Sylvie; Sauvageau, Guy

2017-07-27

Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Quantitative Interaction Effects of Carbon Dioxide, Sodium Chloride, and Sodium Nitrite on Neurotoxin Gene Expression in Nonproteolytic Clostridium botulinum Type B

PubMed Central

Lövenklev, Maria; Artin, Ingrid; Hagberg, Oskar; Borch, Elisabeth; Holst, Elisabet; Rådström, Peter

2004-01-01

The effects of carbon dioxide, sodium chloride, and sodium nitrite on type B botulinum neurotoxin (BoNT/B) gene (cntB) expression in nonproteolytic Clostridium botulinum were investigated in a tryptone-peptone-yeast extract (TPY) medium. Various concentrations of these selected food preservatives were studied by using a complete factorial design in order to quantitatively study interaction effects, as well as main effects, on the following responses: lag phase duration (LPD), growth rate, relative cntB expression, and extracellular BoNT/B production. Multiple linear regression was used to set up six statistical models to quantify and predict these responses. All combinations of NaCl and NaNO2 in the growth medium resulted in a prolonged lag phase duration and in a reduction in the specific growth rate. In contrast, the relative BoNT/B gene expression was unchanged, as determined by the cntB-specific quantitative reverse transcription-PCR method. This was confirmed when we measured the extracellular BoNT/B concentration by an enzyme-linked immunosorbent assay. CO2 was found to have a major effect on gene expression when the cntB mRNA levels were monitored in the mid-exponential, late exponential, and late stationary growth phases. The expression of cntB relative to the expression of the 16S rRNA gene was stimulated by an elevated CO2 concentration; the cntB mRNA level was fivefold greater in a 70% CO2 atmosphere than in a 10% CO2 atmosphere. These findings were also confirmed when we analyzed the extracellular BoNT/B concentration; we found that the concentrations were 27 ng · ml−1 · unit of optical density−1 in the 10% CO2 atmosphere and 126 ng · ml−1 · unit of optical density−1 in the 70% CO2 atmosphere. PMID:15128553

Transcriptomic analysis reveals metabolic switches and surface remodeling as key processes for stage transition in Trypanosoma cruzi

PubMed Central

Greif, Gonzalo; Rodriguez, Matias; Alvarez-Valin, Fernando

2017-01-01

American trypanosomiasis is a chronic and endemic disease which affects millions of people. Trypanosoma cruzi, its causative agent, has a life cycle that involves complex morphological and functional transitions, as well as a variety of environmental conditions. This requires a tight regulation of gene expression, which is achieved mainly by post-transcriptional regulation. In this work we conducted an RNAseq analysis of the three major life cycle stages of T. cruzi: amastigotes, epimastigotes and trypomastigotes. This analysis allowed us to delineate specific transcriptomic profiling for each stage, and also to identify those biological processes of major relevance in each state. Stage specific expression profiling evidenced the plasticity of T. cruzi to adapt quickly to different conditions, with particular focus on membrane remodeling and metabolic shifts along the life cycle. Epimastigotes, which replicate in the gut of insect vectors, showed higher expression of genes related to energy metabolism, mainly Krebs cycle, respiratory chain and oxidative phosphorylation related genes, and anabolism related genes associated to nucleotide and steroid biosynthesis; also, a general down-regulation of surface glycoprotein coding genes was seen at this stage. Trypomastigotes, living extracellularly in the bloodstream of mammals, express a plethora of surface proteins and signaling genes involved in invasion and evasion of immune response. Amastigotes mostly express membrane transporters and genes involved in regulation of cell cycle, and also express a specific subset of surface glycoprotein coding genes. In addition, these results allowed us to improve the annotation of the Dm28c genome, identifying new ORFs and set the stage for construction of networks of co-expression, which can give clues about coded proteins of unknown functions. PMID:28286708

Transcriptional responses of Arabidopsis thaliana to chewing and sucking insect herbivores

DOE PAGES

Appel, Heidi M.; Fescemyer, Howard; Ehlting, Juergen; ...

2014-11-14

We tested the hypothesis that Arabidopsis can recognize and respond differentially to insect species at the transcriptional level using a genome wide microarray. Transcriptional reprogramming was characterized using co-expression analysis in damaged and undamaged leaves at two times in response to mechanical wounding and four insect species. In all, 2778 (10.6%) of annotated genes on the array were differentially expressed in at least one treatment. Responses differed mainly between aphid and caterpillar and sampling times. Responses to aphids and caterpillars shared only 10% of up-regulated and 8% of down-regulated genes. Responses to two caterpillars shared 21 and 12% of up-more » and down-regulated genes, whereas responses to the two aphids shared only 7 and 4% of up-regulated and down-regulated genes. Overlap in genes expressed between 6 and 24 h was 3–15%, and depended on the insect species. Responses in attacked and unattacked leaves differed at 6 h but converged by 24 h. Genes responding to the insects are also responsive to many stressors and included primary metabolism. Aphids down-regulated amino acid catabolism; caterpillars stimulated production of amino acids involved in glucosinolate synthesis. Co-expression analysis revealed 17 response networks. Transcription factors were a major portion of differentially expressed genes throughout and responsive genes shared most of the known or postulated binding sites. However, cis-element composition of genes down regulated by the aphid M. persicae was unique, as were those of genes down-regulated by caterpillars. As many as 20 cis-elements were over-represented in one or more treatments, including some from well-characterized classes and others as yet uncharacterized. We suggest that transcriptional changes elicited by wounding and insects are heavily influenced by transcription factors and involve both enrichment of a common set of cis-elements and a unique enrichment of a few cis-elements in responding genes.« less

Transcriptional responses of Arabidopsis thaliana to chewing and sucking insect herbivores

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

Appel, Heidi M.; Fescemyer, Howard; Ehlting, Juergen

We tested the hypothesis that Arabidopsis can recognize and respond differentially to insect species at the transcriptional level using a genome wide microarray. Transcriptional reprogramming was characterized using co-expression analysis in damaged and undamaged leaves at two times in response to mechanical wounding and four insect species. In all, 2778 (10.6%) of annotated genes on the array were differentially expressed in at least one treatment. Responses differed mainly between aphid and caterpillar and sampling times. Responses to aphids and caterpillars shared only 10% of up-regulated and 8% of down-regulated genes. Responses to two caterpillars shared 21 and 12% of up-more » and down-regulated genes, whereas responses to the two aphids shared only 7 and 4% of up-regulated and down-regulated genes. Overlap in genes expressed between 6 and 24 h was 3–15%, and depended on the insect species. Responses in attacked and unattacked leaves differed at 6 h but converged by 24 h. Genes responding to the insects are also responsive to many stressors and included primary metabolism. Aphids down-regulated amino acid catabolism; caterpillars stimulated production of amino acids involved in glucosinolate synthesis. Co-expression analysis revealed 17 response networks. Transcription factors were a major portion of differentially expressed genes throughout and responsive genes shared most of the known or postulated binding sites. However, cis-element composition of genes down regulated by the aphid M. persicae was unique, as were those of genes down-regulated by caterpillars. As many as 20 cis-elements were over-represented in one or more treatments, including some from well-characterized classes and others as yet uncharacterized. We suggest that transcriptional changes elicited by wounding and insects are heavily influenced by transcription factors and involve both enrichment of a common set of cis-elements and a unique enrichment of a few cis-elements in responding genes.« less

Clustered metallothionein genes are co-regulated in rice and ectopic expression of OsMT1e-P confers multiple abiotic stress tolerance in tobacco via ROS scavenging

PubMed Central

2012-01-01

Background Metallothioneins (MT) are low molecular weight, cysteine rich metal binding proteins, found across genera and species, but their function(s) in abiotic stress tolerance are not well documented. Results We have characterized a rice MT gene, OsMT1e-P, isolated from a subtractive library generated from a stressed salinity tolerant rice genotype, Pokkali. Bioinformatics analysis of the rice genome sequence revealed that this gene belongs to a multigenic family, which consists of 13 genes with 15 protein products. OsMT1e-P is located on chromosome XI, away from the majority of other type I genes that are clustered on chromosome XII. Various members of this MT gene cluster showed a tight co-regulation pattern under several abiotic stresses. Sequence analysis revealed the presence of conserved cysteine residues in OsMT1e-P protein. Salinity stress was found to regulate the transcript abundance of OsMT1e-P in a developmental and organ specific manner. Using transgenic approach, we found a positive correlation between ectopic expression of OsMT1e-P and stress tolerance. Our experiments further suggest ROS scavenging to be the possible mechanism for multiple stress tolerance conferred by OsMT1e-P. Conclusion We present an overview of MTs, describing their gene structure, genome localization and expression patterns under salinity and development in rice. We have found that ectopic expression of OsMT1e-P enhances tolerance towards multiple abiotic stresses in transgenic tobacco and the resultant plants could survive and set viable seeds under saline conditions. Taken together, the experiments presented here have indicated that ectopic expression of OsMT1e-P protects against oxidative stress primarily through efficient scavenging of reactive oxygen species. PMID:22780875

Clustered metallothionein genes are co-regulated in rice and ectopic expression of OsMT1e-P confers multiple abiotic stress tolerance in tobacco via ROS scavenging.

PubMed

Kumar, Gautam; Kushwaha, Hemant Ritturaj; Panjabi-Sabharwal, Vaishali; Kumari, Sumita; Joshi, Rohit; Karan, Ratna; Mittal, Shweta; Pareek, Sneh L Singla; Pareek, Ashwani

2012-07-10

Metallothioneins (MT) are low molecular weight, cysteine rich metal binding proteins, found across genera and species, but their function(s) in abiotic stress tolerance are not well documented. We have characterized a rice MT gene, OsMT1e-P, isolated from a subtractive library generated from a stressed salinity tolerant rice genotype, Pokkali. Bioinformatics analysis of the rice genome sequence revealed that this gene belongs to a multigenic family, which consists of 13 genes with 15 protein products. OsMT1e-P is located on chromosome XI, away from the majority of other type I genes that are clustered on chromosome XII. Various members of this MT gene cluster showed a tight co-regulation pattern under several abiotic stresses. Sequence analysis revealed the presence of conserved cysteine residues in OsMT1e-P protein. Salinity stress was found to regulate the transcript abundance of OsMT1e-P in a developmental and organ specific manner. Using transgenic approach, we found a positive correlation between ectopic expression of OsMT1e-P and stress tolerance. Our experiments further suggest ROS scavenging to be the possible mechanism for multiple stress tolerance conferred by OsMT1e-P. We present an overview of MTs, describing their gene structure, genome localization and expression patterns under salinity and development in rice. We have found that ectopic expression of OsMT1e-P enhances tolerance towards multiple abiotic stresses in transgenic tobacco and the resultant plants could survive and set viable seeds under saline conditions. Taken together, the experiments presented here have indicated that ectopic expression of OsMT1e-P protects against oxidative stress primarily through efficient scavenging of reactive oxygen species.

GSCALite: A Web Server for Gene Set Cancer Analysis.

PubMed

Liu, Chun-Jie; Hu, Fei-Fei; Xia, Mengxuan; Han, Leng; Zhang, Qiong; Guo, An-Yuan

2018-05-22

The availability of cancer genomic data makes it possible to analyze genes related to cancer. Cancer is usually the result of a set of genes and the signal of a single gene could be covered by background noise. Here, we present a web server named Gene Set Cancer Analysis (GSCALite) to analyze a set of genes in cancers with the following functional modules. (i) Differential expression in tumor vs normal, and the survival analysis; (ii) Genomic variations and their survival analysis; (iii) Gene expression associated cancer pathway activity; (iv) miRNA regulatory network for genes; (v) Drug sensitivity for genes; (vi) Normal tissue expression and eQTL for genes. GSCALite is a user-friendly web server for dynamic analysis and visualization of gene set in cancer and drug sensitivity correlation, which will be of broad utilities to cancer researchers. GSCALite is available on http://bioinfo.life.hust.edu.cn/web/GSCALite/. guoay@hust.edu.cn or zhangqiong@hust.edu.cn. Supplementary data are available at Bioinformatics online.

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

PubMed

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

2011-01-01

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

Expression map of a complete set of gustatory receptor genes in chemosensory organs of Bombyx mori.

PubMed

Guo, Huizhen; Cheng, Tingcai; Chen, Zhiwei; Jiang, Liang; Guo, Youbing; Liu, Jianqiu; Li, Shenglong; Taniai, Kiyoko; Asaoka, Kiyoshi; Kadono-Okuda, Keiko; Arunkumar, Kallare P; Wu, Jiaqi; Kishino, Hirohisa; Zhang, Huijie; Seth, Rakesh K; Gopinathan, Karumathil P; Montagné, Nicolas; Jacquin-Joly, Emmanuelle; Goldsmith, Marian R; Xia, Qingyou; Mita, Kazuei

2017-03-01

Most lepidopteran species are herbivores, and interaction with host plants affects their gene expression and behavior as well as their genome evolution. Gustatory receptors (Grs) are expected to mediate host plant selection, feeding, oviposition and courtship behavior. However, due to their high diversity, sequence divergence and extremely low level of expression it has been difficult to identify precisely a complete set of Grs in Lepidoptera. By manual annotation and BAC sequencing, we improved annotation of 43 gene sequences compared with previously reported Grs in the most studied lepidopteran model, the silkworm, Bombyx mori, and identified 7 new tandem copies of BmGr30 on chromosome 7, bringing the total number of BmGrs to 76. Among these, we mapped 68 genes to chromosomes in a newly constructed chromosome distribution map and 8 genes to scaffolds; we also found new evidence for large clusters of BmGrs, especially from the bitter receptor family. RNA-seq analysis of diverse BmGr expression patterns in chemosensory organs of larvae and adults enabled us to draw a precise organ specific map of BmGr expression. Interestingly, most of the clustered genes were expressed in the same tissues and more than half of the genes were expressed in larval maxillae, larval thoracic legs and adult legs. For example, BmGr63 showed high expression levels in all organs in both larval and adult stages. By contrast, some genes showed expression limited to specific developmental stages or organs and tissues. BmGr19 was highly expressed in larval chemosensory organs (especially antennae and thoracic legs), the single exon genes BmGr53 and BmGr67 were expressed exclusively in larval tissues, the BmGr27-BmGr31 gene cluster on chr7 displayed a high expression level limited to adult legs and the candidate CO 2 receptor BmGr2 was highly expressed in adult antennae, where few other Grs were expressed. Transcriptional analysis of the Grs in B. mori provides a valuable new reference for finding genes involved in plant-insect interactions in Lepidoptera and establishing correlations between these genes and vital insect behaviors like host plant selection and courtship for mating. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

3D-QSAR modeling and molecular docking studies on a series of 2,5 disubstituted 1,3,4-oxadiazoles

NASA Astrophysics Data System (ADS)

Ghaleb, Adib; Aouidate, Adnane; Ghamali, Mounir; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-10-01

3D-QSAR (comparative molecular field analysis (CoMFA)) and comparative molecular similarity indices analysis (CoMSIA) were performed on novel 2,5 disubstituted 1,3,4-oxadiazoles analogues as anti-fungal agents. The CoMFA and CoMSIA models using 13 compounds in the training set gives Q2 values of 0.52 and 0.51 respectively, while R2 values of 0.92. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to determine a three-dimensional quantitative structure-activity relationship. Based on this study a set of new molecules with high predicted activities were designed. Surflex-docking confirmed the stability of predicted molecules in the receptor.

Extra Large G-Protein Interactome Reveals Multiple Stress Response Function and Partner-Dependent XLG Subcellular Localization

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

Liang, Ying; Gao, Yajun; Jones, Alan M.

The three-member family of Arabidopsis extra-large G proteins (XLG1-3) defines the prototype of an atypical Ga subunit in the heterotrimeric G protein complex. Some recent evidence indicate that XLG subunits operate along with its Gbg dimer in root morphology, stress responsiveness, and cytokinin induced development, however downstream targets of activated XLG proteins in the stress pathways are rarely known. In order to assemble a set of candidate XLG-targeted proteins, a yeast two-hybrid complementation-based screen was performed using XLG protein baits to query interactions between XLG and partner protein found in glucose-treated seedlings, roots, and Arabidopsis cells in culture. Seventy twomore » interactors were identified and >60% of a test set displayed in vivo interaction with XLG proteins. Gene co-expression analysis shows that >70% of the interactors are positively correlated with the corresponding XLG partners. Gene Ontology enrichment for all the candidates indicates stress responses and posits a molecular mechanism involving a specific set of transcription factor partners to XLG. Genes encoding two of these transcription factors, SZF1 and 2, require XLG proteins for full NaCl-induced expression. Furthermore, the subcellular localization of the XLG proteins in the nucleus, endosome, and plasma membrane is dependent on the specific interacting partner.« less

Extra Large G-Protein Interactome Reveals Multiple Stress Response Function and Partner-Dependent XLG Subcellular Localization

DOE PAGES

Liang, Ying; Gao, Yajun; Jones, Alan M.

2017-06-13

The three-member family of Arabidopsis extra-large G proteins (XLG1-3) defines the prototype of an atypical Ga subunit in the heterotrimeric G protein complex. Some recent evidence indicate that XLG subunits operate along with its Gbg dimer in root morphology, stress responsiveness, and cytokinin induced development, however downstream targets of activated XLG proteins in the stress pathways are rarely known. In order to assemble a set of candidate XLG-targeted proteins, a yeast two-hybrid complementation-based screen was performed using XLG protein baits to query interactions between XLG and partner protein found in glucose-treated seedlings, roots, and Arabidopsis cells in culture. Seventy twomore » interactors were identified and >60% of a test set displayed in vivo interaction with XLG proteins. Gene co-expression analysis shows that >70% of the interactors are positively correlated with the corresponding XLG partners. Gene Ontology enrichment for all the candidates indicates stress responses and posits a molecular mechanism involving a specific set of transcription factor partners to XLG. Genes encoding two of these transcription factors, SZF1 and 2, require XLG proteins for full NaCl-induced expression. Furthermore, the subcellular localization of the XLG proteins in the nucleus, endosome, and plasma membrane is dependent on the specific interacting partner.« less

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments.

PubMed

Regier, Mary C; Maccoux, Lindsey J; Weinberger, Emma M; Regehr, Keil J; Berry, Scott M; Beebe, David J; Alarid, Elaine T

2016-08-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture.

Matrine displayed antiviral activity in porcine alveolar macrophages co-infected by porcine reproductive and respiratory syndrome virus and porcine circovirus type 2

PubMed Central

Sun, Na; Sun, Panpan; Lv, Haipeng; Sun, Yaogui; Guo, Jianhua; Wang, Zhirui; Luo, Tiantian; Wang, Shaoyu; Li, Hongquan

2016-01-01

The co-infection of porcine reproductive respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) is quite common in clinical settings and no effective treatment to the co-infection is available. In this study, we established the porcine alveolar macrophages (PAM) cells model co-infected with PRRSV/PCV2 with modification in vitro, and investigated the antiviral activity of Matrine on this cell model and further evaluated the effect of Matrine on virus-induced TLR3,4/NF-κB/TNF-α pathway. The results demonstrated PAM cells inoculated with PRRSV followed by PCV2 2 h later enhanced PRRSV and PCV2 replications. Matrine treatment suppressed both PRRSV and PCV2 infection at 12 h post infection. Furthermore, PRRSV/PCV2 co- infection induced IκBα degradation and phosphorylation as well as the translocation of NF-κB from the cytoplasm to the nucleus indicating that PRRSV/PCV2 co-infection induced NF-κB activation. Matrine treatment significantly down-regulated the expression of TLR3, TLR4 and TNF-α although it, to some extent, suppressed p-IκBα expression, suggesting that TLR3,4/NF-κB/TNF-α pathway play an important role of Matrine in combating PRRSV/PCV2 co-infection. It is concluded that Matrine possesses activity against PRRSV/PCV2 co-infection in vitro and suppression of the TLR3,4/NF-κB/TNF-α pathway as an important underlying molecular mechanism. These findings warrant Matrine to be further explored for its antiviral activity in clinical settings. PMID:27080155

Identification and functional analysis of a core gene module associated with hepatitis C virus-induced human hepatocellular carcinoma progression.

PubMed

Bai, Gaobo; Zheng, Wenling; Ma, Wenli

2018-05-01

Hepatitis C virus (HCV)-induced human hepatocellular carcinoma (HCC) progression may be due to a complex multi-step processes. The developmental mechanism of these processes is worth investigating for the prevention, diagnosis and therapy of HCC. The aim of the present study was to investigate the molecular mechanism underlying the progression of HCV-induced hepatocarcinogenesis. First, the dynamic gene module, consisting of key genes associated with progression between the normal stage and HCC, was identified using the Weighted Gene Co-expression Network Analysis tool from R language. By defining those genes in the module as seeds, the change of co-expression in differentially expressed gene sets in two consecutive stages of pathological progression was examined. Finally, interaction pairs of HCV viral proteins and their directly targeted proteins in the identified module were extracted from the literature and a comprehensive interaction dataset from yeast two-hybrid experiments. By combining the interactions between HCV and their targets, and protein-protein interactions in the Search Tool for the Retrieval of Interacting Genes database (STRING), the HCV-key genes interaction network was constructed and visualized using Cytoscape software 3.2. As a result, a module containing 44 key genes was identified to be associated with HCC progression, due to the dynamic features and functions of those genes in the module. Several important differentially co-expressed gene pairs were identified between non-HCC and HCC stages. In the key genes, cyclin dependent kinase 1 (CDK1), NDC80, cyclin A2 (CCNA2) and rac GTPase activating protein 1 (RACGAP1) were shown to be targeted by the HCV nonstructural proteins NS5A, NS3 and NS5B, respectively. The four genes perform an intermediary role between the HCV viral proteins and the dysfunctional module in the HCV key genes interaction network. These findings provided valuable information for understanding the mechanism of HCV-induced HCC progression and for seeking drug targets for the therapy and prevention of HCC.

Classification of complex information: inference of co-occurring affective states from their expressions in speech.

PubMed

Sobol-Shikler, Tal; Robinson, Peter

2010-07-01

We present a classification algorithm for inferring affective states (emotions, mental states, attitudes, and the like) from their nonverbal expressions in speech. It is based on the observations that affective states can occur simultaneously and different sets of vocal features, such as intonation and speech rate, distinguish between nonverbal expressions of different affective states. The input to the inference system was a large set of vocal features and metrics that were extracted from each utterance. The classification algorithm conducted independent pairwise comparisons between nine affective-state groups. The classifier used various subsets of metrics of the vocal features and various classification algorithms for different pairs of affective-state groups. Average classification accuracy of the 36 pairwise machines was 75 percent, using 10-fold cross validation. The comparison results were consolidated into a single ranked list of the nine affective-state groups. This list was the output of the system and represented the inferred combination of co-occurring affective states for the analyzed utterance. The inference accuracy of the combined machine was 83 percent. The system automatically characterized over 500 affective state concepts from the Mind Reading database. The inference of co-occurring affective states was validated by comparing the inferred combinations to the lexical definitions of the labels of the analyzed sentences. The distinguishing capabilities of the system were comparable to human performance.

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE PAGES

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; ...

2015-03-27

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

Resilient protein co-expression network in male orbitofrontal cortex layer 2/3 during human aging.

PubMed

Pabba, Mohan; Scifo, Enzo; Kapadia, Fenika; Nikolova, Yuliya S; Ma, Tianzhou; Mechawar, Naguib; Tseng, George C; Sibille, Etienne

2017-10-01

The orbitofrontal cortex (OFC) is vulnerable to normal and pathologic aging. Currently, layer resolution large-scale proteomic studies describing "normal" age-related alterations at OFC are not available. Here, we performed a large-scale exploratory high-throughput mass spectrometry-based protein analysis on OFC layer 2/3 from 15 "young" (15-43 years) and 18 "old" (62-88 years) human male subjects. We detected 4193 proteins and identified 127 differentially expressed (DE) proteins (p-value ≤0.05; effect size >20%), including 65 up- and 62 downregulated proteins (e.g., GFAP, CALB1). Using a previously described categorization of biological aging based on somatic tissues, that is, peripheral "hallmarks of aging," and considering overlap in protein function, we show the highest representation of altered cell-cell communication (54%), deregulated nutrient sensing (39%), and loss of proteostasis (35%) in the set of OFC layer 2/3 DE proteins. DE proteins also showed a significant association with several neurologic disorders; for example, Alzheimer's disease and schizophrenia. Notably, despite age-related changes in individual protein levels, protein co-expression modules were remarkably conserved across age groups, suggesting robust functional homeostasis. Collectively, these results provide biological insight into aging and associated homeostatic mechanisms that maintain normal brain function with advancing age. Copyright © 2017 Elsevier Inc. All rights reserved.

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

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

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

Observations of CO on Mars with OMEGA/Mars Express: A Study of Local Variations over the Volcanoes

NASA Astrophysics Data System (ADS)

Encrenaz, T.; Drossart, P.; Fouchet, T.; Melchiorri, R.; Lellouch, E.; Combes, M.; Bibring, J.-P.; Moroz, V.; Ignatiev, N.; Forget, F.; OMEGA Team

Spectra of Mars recorded with the OMEGA/Mars Express experiment have been used to retrieve information on the CO mixing ratio over the planet. By using simultaneously the CO (1-0) band at 4.7 microns and a weak CO2 band at 4.85 microns, we have inferred the CO mixing ratio in all regions where the thermal emission is dominent, i.e. where the surface temperature is maximum. These observations, in particular, indicate a significant depletion of the CO/CO2 ratio over Olympus Mons. This preliminary result seems to confirm the analysis performed by the ISM imaging spectrometer aboard the Phobos mission, which suggested a possible depletion of CO over the volcanoes (Rosenqvist et al., Icarus 98, 254, 1992). Implications of this result will be discussed.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

Identification of a novel CoA synthase isoform, which is primarily expressed in Brain

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

Nemazanyy, Ivan; Panasyuk, Ganna; Breus, Oksana

2006-03-24

CoA and its derivatives Acetyl-CoA and Acyl-CoA are important players in cellular metabolism and signal transduction. CoA synthase is a bifunctional enzyme which mediates the final stages of CoA biosynthesis. In previous studies, we have reported molecular cloning, biochemical characterization, and subcellular localization of CoA synthase (CoASy). Here, we describe the existence of a novel CoA synthase isoform, which is the product of alternative splicing and possesses a 29aa extension at the N-terminus. We termed it CoASy {beta} and originally identified CoA synthase, CoASy {alpha}. The transcript specific for CoASy {beta} was identified by electronic screening and by RT-PCR analysismore » of various rat tissues. The existence of this novel isoform was further confirmed by immunoblot analysis with antibodies directed to the N-terminal peptide of CoASy {beta}. In contrast to CoASy {alpha}, which shows ubiquitous expression, CoASy {beta} is primarily expressed in Brain. Using confocal microscopy, we demonstrated that both isoforms are localized on mitochondria. The N-terminal extension does not affect the activity of CoA synthase, but possesses a proline-rich sequence which can bring the enzyme into complexes with signalling proteins containing SH3 or WW domains. The role of this novel isoform in CoA biosynthesis, especially in Brain, requires further elucidation.« less

Bathing in carbon dioxide-enriched water alters protein expression in keratinocytes of skin tissue in rats.

PubMed

Kälsch, Julia; Pott, Leona L; Takeda, Atsushi; Kumamoto, Hideo; Möllmann, Dorothe; Canbay, Ali; Sitek, Barbara; Baba, Hideo A

2017-04-01

Beneficial effects of balneotherapy using naturally occurring carbonated water (CO 2 enriched) have been known since the Middle Ages. Although this therapy is clinically applied for peripheral artery disease and skin disorder, the underlying mechanisms are not fully elucidated.Under controlled conditions, rats were bathed in either CO 2 -enriched water (CO 2 content 1200 mg/L) or tap water, both at 37 °C, for 10 min daily over 4 weeks. Proliferation activity was assessed by Ki67 immunohistochemistry of the epidermis of the abdomen. The capillary density was assessed by immunodetection of isolectin-positive cells. Using cryo-fixed abdominal skin epidermis, follicle cells and stroma tissue containing capillaries were separately isolated by means of laser microdissection and subjected to proteomic analysis using label-free technique. Differentially expressed proteins were validated by immunohistochemistry.Proliferation activity of keratinocytes was not significantly different in the epidermis after bathing in CO 2 -enriched water, and also, capillary density did not change. Proteomic analysis revealed up to 36 significantly regulated proteins in the analyzed tissue. Based on the best expression profiles, ten proteins were selected for immunohistochemical validation. Only one protein, far upstream element binding protein 2 (FUBP2), was similarly downregulated in the epidermis after bathing in CO 2 -enriched water with both techniques. Low FUBP2 expression was associated with low c-Myc immune-expression in keratinocytes.Long-term bathing in CO 2 -enriched water showed a cellular protein response of epithelial cells in the epidermis which was detectable by two different methods. However, differences in proliferation activity or capillary density were not detected in the normal skin.

Neuroendocrine and immune network re-modeling in chronic fatigue syndrome: an exploratory analysis.

PubMed

Fuite, Jim; Vernon, Suzanne D; Broderick, Gordon

2008-12-01

This work investigates the significance of changes in association patterns linking indicators of neuroendocrine and immune activity in patients with chronic fatigue syndrome (CFS). Gene sets preferentially expressed in specific immune cell isolates were integrated with neuroendocrine data from a large population-based study. Co-expression patterns linking immune cell activity with hypothalamic-pituitary-adrenal (HPA), thyroidal (HPT) and gonadal (HPG) axis status were computed using mutual information criteria. Networks in control and CFS subjects were compared globally in terms of a weighted graph edit distance. Local re-modeling of node connectivity was quantified by node degree and eigenvector centrality measures. Results indicate statistically significant differences between CFS and control networks determined mainly by re-modeling around pituitary and thyroid nodes as well as an emergent immune sub-network. Findings align with known mechanisms of chronic inflammation and support possible immune-mediated loss of thyroid function in CFS exacerbated by blunted HPA axis responsiveness.

Expression of TpNRAMP5, a metal transporter from Polish wheat (Triticum polonicum L.), enhances the accumulation of Cd, Co and Mn in transgenic Arabidopsis plants.

PubMed

Peng, Fan; Wang, Chao; Zhu, Jianshu; Zeng, Jian; Kang, Houyang; Fan, Xing; Sha, Lina; Zhang, Haiqin; Zhou, Yonghong; Wang, Yi

2018-06-01

TpRNAMP5 is mainly expressed in the plasma membrane of roots and basal stems. It functions as a metal transporter for Cd, Mn and Co accumulation. Numerous natural resistance-associated macrophage proteins (NRAMPs) have been functionally identified in various plant species, including Arabidopsis, rice, soybean and tobacco, but no information is available on NRAMP genes in wheat. In this study, we isolated a TpNRAMP5 from dwarf Polish wheat (DPW, Triticum polonicum L.), a species with high tolerance to Cd and Zn. Expression pattern analysis revealed that TpNRAMP5 is mainly expressed in roots and basal stems of DPW. TpNRAMP5 was localized at the plasma membrane of Arabidopsis leaf protoplast. Expression of TpNRAMP5 in yeast significantly increased yeast sensitivity to Cd and Co, but not Zn, and enhanced Cd and Co concentrations. Expression of TpNRAMP5 in Arabidopsis significantly increased Cd, Co and Mn concentrations in roots, shoots and whole plants, but had no effect on Fe and Zn concentrations. These results indicate that TpNRAMP5 is a metal transporter enhancing the accumulation of Cd, Co and Mn, but not Zn and Fe. Genetic manipulation of TpNRAMP5 can be applied in the future to limit the transfer of Cd from soil to wheat grains, thereby protecting human health.

Exploring of the molecular mechanism of rhinitis via bioinformatics methods

PubMed Central

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

Evaluation of bone substitutes for treatment of peri-implant bone defects: biomechanical, histological, and immunohistochemical analyses in the rabbit tibia

PubMed Central

2016-01-01

Purpose We sought to evaluate the effectiveness of bone substitutes in circumferential peri-implant defects created in the rabbit tibia. Methods Thirty rabbits received 45 implants in their left and right tibia. A circumferential bone defect (6.1 mm in diameter/4 mm depth) was created in each rabbit tibia using a trephine bur. A dental implant (4.1 mm × 8.5 mm) was installed after the creation of the defect, providing a 2-mm gap. The bone defect gaps between the implant and the bone were randomly filled according to the following groups: blood clot (CO), particulate Bio-Oss® (BI), and Bio-Oss® Collagen (BC). Ten animals were euthanized after periods of 15, 30, and 60 days. Biomechanical analysis by means of the removal torque of the implants, as well as histologic and immunohistochemical analyses for protein expression of osteocalcin (OC), Runx2, OPG, RANKL, and TRAP were evaluated. Results For biomechanics, BC showed a better biological response (61.00±15.28 Ncm) than CO (31.60±14.38 Ncm) at 30 days. Immunohistochemical analysis showed significantly different OC expression in CO and BC at 15 days, and also between the CO and BI groups, and between the CO and BC groups at 60 days. After 15 days, Runx2 expression was significantly different in the BI group compared to the CO and BC groups. RANKL expression was significantly different in the BI and CO groups and between the BI and BC groups at 15 days, and also between the BI and CO groups at 60 days. OPG expression was significantly higher at 60 days postoperatively in the BI group than the CO group. Conclusions Collectively, our data indicate that, compared to CO and BI, BC offered better bone healing, which was characterized by greater RUNX2, OC, and OPG immunolabeling, and required greater reversal torque for implant removal. Indeed, along with BI, BC presents promising biomechanical and biological properties supporting its possible use in osteoconductive grafts for filling peri-implant gaps. PMID:27382506

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

Identification of PEG-induced water stress responsive transcripts using co-expression network in Eucalyptus grandis.

PubMed

Ghosh Dasgupta, Modhumita; Dharanishanthi, Veeramuthu

2017-09-05

Ecophysiological studies in Eucalyptus have shown that water is the principal factor limiting stem growth. Effect of water deficit conditions on physiological and biochemical parameters has been extensively reported in Eucalyptus. The present study was conducted to identify major polyethylene glycol induced water stress responsive transcripts in Eucalyptus grandis using gene co-expression network. A customized array representing 3359 water stress responsive genes was designed to document their expression in leaves of E. grandis cuttings subjected to -0.225MPa of PEG treatment. The differentially expressed transcripts were documented and significantly co-expressed transcripts were used for construction of network. The co-expression network was constructed with 915 nodes and 3454 edges with degree ranging from 2 to 45. Ninety four GO categories and 117 functional pathways were identified in the network. MCODE analysis generated 27 modules and module 6 with 479 nodes and 1005 edges was identified as the biologically relevant network. The major water responsive transcripts represented in the module included dehydrin, osmotin, LEA protein, expansin, arabinogalactans, heat shock proteins, major facilitator proteins, ARM repeat proteins, raffinose synthase, tonoplast intrinsic protein and transcription factors like DREB2A, ARF9, AGL24, UNE12, WLIM1 and MYB66, MYB70, MYB 55, MYB 16 and MYB 103. The coordinated analysis of gene expression patterns and coexpression networks developed in this study identified an array of transcripts that may regulate PEG induced water stress responses in E. grandis. Copyright © 2017 Elsevier B.V. All rights reserved.

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

PubMed

Xiang, Bo; Yu, Minglan; Liang, Xuemei; Lei, Wei; Huang, Chaohua; Chen, Jing; He, Wenying; Zhang, Tao; Li, Tao; Liu, Kezhi

2017-12-10

To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

PubMed Central

Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D.H.; Jo, Brian; Gao, Chuan; McDowell, Ian C.; Engelhardt, Barbara E.

2017-01-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. PMID:29021288

Comparative sequence analysis of the complete set of 40S ribosomal proteins in the Senegalese sole (Solea senegalensis Kaup) and Atlantic halibut (Hippoglossus hippoglossus L.) (Teleostei: Pleuronectiformes): phylogeny and tissue- and development-specific expression.

PubMed

Manchado, Manuel; Infante, Carlos; Asensio, Esther; Cañavate, Jose Pedro; Douglas, Susan E

2007-07-03

Ribosomal proteins (RPs) are key components of ribosomes, the cellular organelle responsible for protein biosynthesis in cells. Their levels can vary as a function of organism growth and development; however, some RPs have been associated with other cellular processes or extraribosomal functions. Their high representation in cDNA libraries has resulted in the increase of RP sequences available from different organisms and their proposal as appropriate molecular markers for phylogenetic analysis. The development of large-scale genomics of Senegalese sole (Solea senegalensis) and Atlantic halibut (Hippoglossus hippoglossus), two commercially important flatfish species, has made possible the identification and systematic analysis of the complete set of RP sequences for the small (40S) ribosome subunit. Amino acid sequence comparisons showed a high similarity both between these two flatfish species and with respect to other fish and human. EST analysis revealed the existence of two and four RPS27 genes in Senegalese sole and Atlantic halibut, respectively. Phylogenetic analysis clustered RPS27 in two separate clades with their fish and mammalian counterparts. Steady-state transcript levels for eight RPs (RPS2, RPS3a, RPS15, RPS27-1, RPS27-2, RPS27a, RPS28, and RPS29) in sole were quantitated during larval development and in tissues, using a real-time PCR approach. All eight RPs exhibited different expression patterns in tissues with the lowest levels in brain. On the contrary, RP transcripts increased co-ordinately after first larval feeding reducing progressively during the metamorphic process. The genomic resources and knowledge developed in this survey will provide new insights into the evolution of Pleuronectiformes. Expression data will contribute to a better understanding of RP functions in fish, especially the mechanisms that govern growth and development in larvae, with implications in aquaculture.

Molecular effects of fractional carbon dioxide laser resurfacing on photodamaged human skin.

PubMed

Reilly, Michael J; Cohen, Marc; Hokugo, Akishige; Keller, Gregory S

2010-01-01

Objective To elucidate the sequential changes in protein expression that play a role in the clinically beneficial results seen with fractional carbon dioxide (CO(2)) laser resurfacing of the face and neck. Methods Nine healthy volunteers were recruited for participation from the senior author's facial plastic surgery practice. After informed consent was obtained, each volunteer underwent a 2-mm punch biopsy from a discrete area of infra-auricular neck skin prior to laser treatment. Patients then immediately underwent laser resurfacing of photodamaged face and neck skin at a minimal dose (30 W for 0.1 second) with the Pixel Perfect fractional CO(2) laser. On completion of the treatment, another biopsy specimen was taken adjacent to the first site. Additional biopsy specimens were subsequently taken from adjacent skin at 2 of 3 time points (day 7, day 14, or day 21). RNA was extracted from the specimens, and reverse transcriptase-polymerase chain reaction and protein microarray analysis were performed. Comparisons were then made between time points using pairwise comparison testing. Results We found statistically significant changes in the gene expression of several matrix metalloproteinases (MMPs). The data demonstrate a consistent up-regulation of MMPs 1, 3, 9, and 13, all of which have been previously reported for fully ablative CO(2) laser resurfacing. There was also a statistically significant increase in MMP-10 and MMP-11 levels in this data set. Conclusion This study suggests that the molecular mechanisms of action are similar for both fractional and fully ablative CO(2) laser resurfacing.

Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles.

PubMed

Mustafin, Zakhar Sergeevich; Lashin, Sergey Alexandrovich; Matushkin, Yury Georgievich; Gunbin, Konstantin Vladimirovich; Afonnikov, Dmitry Arkadievich

2017-01-27

There are many available software tools for visualization and analysis of biological networks. Among them, Cytoscape ( http://cytoscape.org/ ) is one of the most comprehensive packages, with many plugins and applications which extends its functionality by providing analysis of protein-protein interaction, gene regulatory and gene co-expression networks, metabolic, signaling, neural as well as ecological-type networks including food webs, communities networks etc. Nevertheless, only three plugins tagged 'network evolution' found in Cytoscape official app store and in literature. We have developed a new Cytoscape 3.0 application Orthoscape aimed to facilitate evolutionary analysis of gene networks and visualize the results. Orthoscape aids in analysis of evolutionary information available for gene sets and networks by highlighting: (1) the orthology relationships between genes; (2) the evolutionary origin of gene network components; (3) the evolutionary pressure mode (diversifying or stabilizing, negative or positive selection) of orthologous groups in general and/or branch-oriented mode. The distinctive feature of Orthoscape is the ability to control all data analysis steps via user-friendly interface. Orthoscape allows its users to analyze gene networks or separated gene sets in the context of evolution. At each step of data analysis, Orthoscape also provides for convenient visualization and data manipulation.

Are global warming and ocean acidification conspiring against marine ectotherms? A meta-analysis of the respiratory effects of elevated temperature, high CO2 and their interaction.

PubMed

Lefevre, Sjannie

2016-01-01

With the occurrence of global change, research aimed at estimating the performance of marine ectotherms in a warmer and acidified future has intensified. The concept of oxygen- and capacity-limited thermal tolerance, which is inspired by the Fry paradigm of a bell-shaped increase-optimum-decrease-type response of aerobic scope to increasing temperature, but also includes proposed negative and synergistic effects of elevated CO2 levels, has been suggested as a unifying framework. The objectives of this meta-analysis were to assess the following: (i) the generality of a bell-shaped relationship between absolute aerobic scope (AAS) and temperature; (ii) to what extent elevated CO2 affects resting oxygen uptake MO2rest and AAS; and (iii) whether there is an interaction between elevated temperature and CO2. The behavioural effects of CO2 are also briefly discussed. In 31 out of 73 data sets (both acutely exposed and acclimated), AAS increased and remained above 90% of the maximum, whereas a clear thermal optimum was observed in the remaining 42 data sets. Carbon dioxide caused a significant rise in MO2rest in only 18 out of 125 data sets, and a decrease in 25, whereas it caused a decrease in AAS in four out of 18 data sets and an increase in two. The analysis did not reveal clear evidence for an overall correlation with temperature, CO2 regime or duration of CO2 treatment. When CO2 had an effect, additive rather than synergistic interactions with temperature were most common and, interestingly, they even interacted antagonistically on MO2rest and AAS. The behavioural effects of CO2 could complicate experimental determination of respiratory performance. Overall, this meta-analysis reveals heterogeneity in the responses to elevated temperature and CO2 that is not in accordance with the idea of a single unifying principle and which cannot be ignored in attempts to model and predict the impacts of global warming and ocean acidification on marine ectotherms.

Are global warming and ocean acidification conspiring against marine ectotherms? A meta-analysis of the respiratory effects of elevated temperature, high CO2 and their interaction

PubMed Central

Lefevre, Sjannie

2016-01-01

Abstract With the occurrence of global change, research aimed at estimating the performance of marine ectotherms in a warmer and acidified future has intensified. The concept of oxygen- and capacity-limited thermal tolerance, which is inspired by the Fry paradigm of a bell-shaped increase–optimum–decrease-type response of aerobic scope to increasing temperature, but also includes proposed negative and synergistic effects of elevated CO2 levels, has been suggested as a unifying framework. The objectives of this meta-analysis were to assess the following: (i) the generality of a bell-shaped relationship between absolute aerobic scope (AAS) and temperature; (ii) to what extent elevated CO2 affects resting oxygen uptake MO2rest and AAS; and (iii) whether there is an interaction between elevated temperature and CO2. The behavioural effects of CO2 are also briefly discussed. In 31 out of 73 data sets (both acutely exposed and acclimated), AAS increased and remained above 90% of the maximum, whereas a clear thermal optimum was observed in the remaining 42 data sets. Carbon dioxide caused a significant rise in MO2rest in only 18 out of 125 data sets, and a decrease in 25, whereas it caused a decrease in AAS in four out of 18 data sets and an increase in two. The analysis did not reveal clear evidence for an overall correlation with temperature, CO2 regime or duration of CO2 treatment. When CO2 had an effect, additive rather than synergistic interactions with temperature were most common and, interestingly, they even interacted antagonistically on MO2rest and AAS. The behavioural effects of CO2 could complicate experimental determination of respiratory performance. Overall, this meta-analysis reveals heterogeneity in the responses to elevated temperature and CO2 that is not in accordance with the idea of a single unifying principle and which cannot be ignored in attempts to model and predict the impacts of global warming and ocean acidification on marine ectotherms. PMID:27382472

Sheep skeletal muscle transcriptome analysis reveals muscle growth regulatory lncRNAs.

PubMed

Chao, Tianle; Ji, Zhibin; Hou, Lei; Wang, Jin; Zhang, Chunlan; Wang, Guizhi; Wang, Jianmin

2018-01-01

As widely distributed domestic animals, sheep are an important species and the source of mutton. In this study, we aimed to evaluate the regulatory lncRNAs associated with muscle growth and development between high production mutton sheep (Dorper sheep and Qianhua Mutton Merino sheep) and low production mutton sheep (Small-tailed Han sheep). In total, 39 lncRNAs were found to be differentially expressed. Using co-expression analysis and functional annotation, 1,206 co-expression interactions were found between 32 lncRNAs and 369 genes, and 29 of these lncRNAs were found to be associated with muscle development, metabolism, cell proliferation and apoptosis. lncRNA-mRNA interactions revealed 6 lncRNAs as hub lncRNAs. Moreover, three lncRNAs and their associated co-expressed genes were demonstrated by cis-regulatory gene analyses, and we also found a potential regulatory relationship between the pseudogene lncRNA LOC101121401 and its parent gene FTH1. This study provides a genome-wide resolution of lncRNA and mRNA regulation in muscles from mutton sheep.

Sheep skeletal muscle transcriptome analysis reveals muscle growth regulatory lncRNAs

PubMed Central

Chao, Tianle; Ji, Zhibin; Hou, Lei; Wang, Jin; Zhang, Chunlan

2018-01-01

As widely distributed domestic animals, sheep are an important species and the source of mutton. In this study, we aimed to evaluate the regulatory lncRNAs associated with muscle growth and development between high production mutton sheep (Dorper sheep and Qianhua Mutton Merino sheep) and low production mutton sheep (Small-tailed Han sheep). In total, 39 lncRNAs were found to be differentially expressed. Using co-expression analysis and functional annotation, 1,206 co-expression interactions were found between 32 lncRNAs and 369 genes, and 29 of these lncRNAs were found to be associated with muscle development, metabolism, cell proliferation and apoptosis. lncRNA–mRNA interactions revealed 6 lncRNAs as hub lncRNAs. Moreover, three lncRNAs and their associated co-expressed genes were demonstrated by cis-regulatory gene analyses, and we also found a potential regulatory relationship between the pseudogene lncRNA LOC101121401 and its parent gene FTH1. This study provides a genome-wide resolution of lncRNA and mRNA regulation in muscles from mutton sheep. PMID:29666768

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice.

PubMed

Smita, Shuchi; Katiyar, Amit; Chinnusamy, Viswanathan; Pandey, Dev M; Bansal, Kailash C

2015-01-01

MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by "top-down" and "guide-gene" approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via "top-down" approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by "guide-gene" approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice. Thus, the co-regulatory network analysis facilitated the identification of complex OsMYB regulatory networks, and candidate target regulon genes of selected guide MYB genes. The results contribute to the candidate gene screening, and experimentally testable hypotheses for potential regulatory MYB TFs, and their targets under stress conditions.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models.

PubMed

Chen, Ying; Cai, Xiaoyu; Jiang, Long; Li, Yu

2016-02-01

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs. Copyright © 2015 Elsevier Inc. All rights reserved.

Differential co-expression and regulation analyses reveal different mechanisms underlying major depressive disorder and subsyndromal symptomatic depression.

PubMed

Xu, Fan; Yang, Jing; Chen, Jin; Wu, Qingyuan; Gong, Wei; Zhang, Jianguo; Shao, Weihua; Mu, Jun; Yang, Deyu; Yang, Yongtao; Li, Zhiwei; Xie, Peng

2015-04-03

Recent depression research has revealed a growing awareness of how to best classify depression into depressive subtypes. Appropriately subtyping depression can lead to identification of subtypes that are more responsive to current pharmacological treatment and aid in separating out depressed patients in which current antidepressants are not particularly effective. Differential co-expression analysis (DCEA) and differential regulation analysis (DRA) were applied to compare the transcriptomic profiles of peripheral blood lymphocytes from patients with two depressive subtypes: major depressive disorder (MDD) and subsyndromal symptomatic depression (SSD). Six differentially regulated genes (DRGs) (FOSL1, SRF, JUN, TFAP4, SOX9, and HLF) and 16 transcription factor-to-target differentially co-expressed gene links or pairs (TF2target DCLs) appear to be the key differential factors in MDD; in contrast, one DRG (PATZ1) and eight TF2target DCLs appear to be the key differential factors in SSD. There was no overlap between the MDD target genes and SSD target genes. Venlafaxine (Efexor™, Effexor™) appears to have a significant effect on the gene expression profile of MDD patients but no significant effect on the gene expression profile of SSD patients. DCEA and DRA revealed no apparent similarities between the differential regulatory processes underlying MDD and SSD. This bioinformatic analysis may provide novel insights that can support future antidepressant R&D efforts.

Ischemia and reperfusion induce differential expression of calpastatin and its homologue high molecular weight calmodulin-binding protein in murine cardiomyocytes.

PubMed

Parameswaran, Sreejit; Sharma, Rajendra K

2014-01-01

In the heart, calpastatin (Calp) and its homologue high molecular weight calmodulin-binding protein (HMWCaMBP) regulate calpains (Calpn) by inhibition. A rise in intracellular myocardial Ca2+ during cardiac ischemia activates Calpn thereby causing damage to myocardial proteins, which leads to myocyte death and consequently to loss of myocardial structure and function. The present study aims to elucidate expression of Calp and HMWCaMBP with respect to Calpn during induced ischemia and reperfusion in primary murine cardiomyocyte cultures. Ischemia and subsequently reperfusion was induced in ∼ 80% confluent cultures of neonatal murine cardiomyocytes (NMCC). Flow cytometric analysis (FACS) has been used for analyzing protein expression concurrently with viability. Confocal fluorescent microscopy was used to observe protein localization. We observed that ischemia induces increased expression of Calp, HMWCaMBP and Calpn. Calpn expressing NMCC on co-expressing Calp survived ischemic induction compared to NMCC co-expressing HMWCaMBP. Similarly, living cells expressed Calp in contrast to dead cells which expressed HMWCaMBP following reperfusion. A significant difference in the expression of Calp and its homologue HMWCaMBP was observed in localization studies during ischemia. The current study adds to the existing knowledge that HMWCaMBP could be a putative isoform of Calp. NMCC on co-expressing Calp and Calpn-1 survived ischemic and reperfusion inductions compared to NMCC co-expressing HMWCaMBP and Calpn-1. A significant difference in expression of Calp and HMWCaMBP was observed in localization studies during ischemia.

Genome-wide analysis of drought induced gene expression changes in flax (Linum usitatissimum).

PubMed

Dash, Prasanta K; Cao, Yongguo; Jailani, Abdul K; Gupta, Payal; Venglat, Prakash; Xiang, Daoquan; Rai, Rhitu; Sharma, Rinku; Thirunavukkarasu, Nepolean; Abdin, Malik Z; Yadava, Devendra K; Singh, Nagendra K; Singh, Jas; Selvaraj, Gopalan; Deyholos, Mike; Kumar, Polumetla Ananda; Datla, Raju

2014-01-01

A robust phenotypic plasticity to ward off adverse environmental conditions determines performance and productivity in crop plants. Flax (linseed), is an important cash crop produced for natural textile fiber (linen) or oilseed with many health promoting products. This crop is prone to drought stress and yield losses in many parts of the world. Despite recent advances in drought research in a number of important crops, related progress in flax is very limited. Since, response of this plant to drought stress has not been addressed at the molecular level; we conducted microarray analysis to capture transcriptome associated with induced drought in flax. This study identified 183 differentially expressed genes (DEGs) associated with diverse cellular, biophysical and metabolic programs in flax. The analysis also revealed especially the altered regulation of cellular and metabolic pathways governing photosynthesis. Additionally, comparative transcriptome analysis identified a plethora of genes that displayed differential regulation both spatially and temporally. These results revealed co-regulated expression of 26 genes in both shoot and root tissues with implications for drought stress response. Furthermore, the data also showed that more genes are upregulated in roots compared to shoots, suggesting that roots may play important and additional roles in response to drought in flax. With prolonged drought treatment, the number of DEGs increased in both tissue types. Differential expression of selected genes was confirmed by qRT-PCR, thus supporting the suggested functional association of these intrinsic genes in maintaining growth and homeostasis in response to imminent drought stress in flax. Together the present study has developed foundational and new transcriptome data sets for drought stress in flax.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

Revisiting an old concept: the coupled oscillator model for VCD. Part 1: the generalised coupled oscillator mechanism and its intrinsic connection to the strength of VCD signals.

PubMed

Nicu, Valentin Paul

2016-08-03

Motivated by the renewed interest in the coupled oscillator (CO) model for VCD, in this work a generalised coupled oscillator (GCO) expression is derived by introducing the concept of a coupled oscillator origin. Unlike the standard CO expression, the GCO expression is exact within the harmonic approximation. Using two illustrative example molecules, the theoretical concepts introduced here are demonstrated by performing a GCO decomposition of the rotational strengths computed using DFT. This analysis shows that: (1) the contributions to the rotational strengths that are normally neglected in the standard CO model can be comparable to or larger than the CO contribution, and (2) the GCO mechanism introduced here can affect the VCD intensities of all types of modes in symmetric and asymmetric molecules.

Identification of transcription regulatory relationships in rheumatoid arthritis and osteoarthritis.

PubMed

Li, Guofeng; Han, Ning; Li, Zengchun; Lu, Qingyou

2013-05-01

Rheumatoid arthritis (RA) is recognized as the most crippling or disabling type of arthritis, and osteoarthritis (OA) is the most common form of arthritis. These diseases severely reduce the quality of life, and cause high socioeconomic burdens. However, the molecular mechanisms of RA and OA development remain elusive despite intensive research efforts. In this study, we aimed to identify the potential transcription regulatory relationships between transcription factors (TFs) and differentially co-expressed genes (DCGs) in RA and OA, respectively. We downloaded the gene expression profiles of RA and OA from the Gene Expression Omnibus and analyzed the gene expression using computational methods. We identified a set of 4,076 DCGs in pairwise comparisons between RA and OA patients, RA and normal donors (NDs), or OA and ND. After regulatory network construction and regulatory impact factor analysis, we found that EGR1, NFE2L1, and NFYA were crucial TFs in the regulatory network of RA and NFYA, CBFB, CREB1, YY1 and PATZ1 were crucial TFs in the regulatory network of OA. These TFs could regulate the DCGs expression to involve RA and OA by promoting or inhibiting their expression. Altogether, our work may extend our understanding of disease mechanisms and may lead to an improved diagnosis. However, further experiments are still needed to confirm these observations.

KP-CoT-23 (CCDC83) is a novel immunogenic cancer/testis antigen in colon cancer.

PubMed

Song, Myung-Ha; Ha, Jin-Mok; Shin, Dong-Hoon; Lee, Chang-Hun; Old, Lloyd; Lee, Sang-Yull

2012-11-01

Cancer/testis (CT) antigens are considered target molecules for cancer immunotherapy. To identify novel CT antigens, immunoscreening of a testicular cDNA library was performed using serum obtained from a colon cancer patient who was immunized with a new dendritic cell vaccine. We isolated 64 positive cDNA clones comprised of 40 different genes, designated KP-CoT-1 through KP-CoT-40. Three of these putative antigens, including KP-CoT-23 (CCDC83), had testis-specific expression profiles in the Unigene database. RT-PCR analysis showed that the expression of 2 KP-Cot-23 variants was restricted to the testis in normal adult tissues. In addition, KP-CoT-23 variants were frequently expressed in a variety of tumors and cancer cell lines, including colon cancer. A serological western blot assay showed IgG antibodies to the KP-CoT-23 protein in 26 of 37 colon cancer patients and in 4 of 21 healthy patients. These data suggest that KP-CoT-23 is a novel CT antigen that may be useful for the diagnosis and immunotherapy of cancer.

An immune-related lncRNA signature for patients with anaplastic gliomas.

PubMed

Wang, Wen; Zhao, Zheng; Yang, Fan; Wang, Haoyuan; Wu, Fan; Liang, Tingyu; Yan, Xiaoyan; Li, Jiye; Lan, Qing; Wang, Jiangfei; Zhao, Jizong

2018-01-01

We investigated immune-related long non-coding RNAs (lncRNAs) that may be exploited as potential therapeutic targets in anaplastic gliomas. We obtained 572 lncRNAs and 317 immune genes from the Chinese Glioma Genome Atlas microarray and constructed immune-related lncRNAs co-expression networks to identify immune-related lncRNAs. Two additional datasets (GSE16011, REMBRANDT) were used for validation. Gene set enrichment analysis and principal component analysis were used for functional annotation. Immune-lncRNAs co-expression networks were constructed. Nine immune-related lncRNAs (SNHG8, PGM5-AS1, ST20-AS1, LINC00937, AGAP2-AS1, MIR155HG, TUG1, MAPKAPK5-AS1, and HCG18) signature was identified in patients with anaplastic gliomas. Patients in the low-risk group showed longer overall survival (OS) and progression-free survival than those in the high-risk group (P < 0.0001; P < 0.0001). Additionally, patients in the high-risk group displayed no-deletion of chromosomal arms 1p and/or 19q, isocitrate dehydrogenase wild-type, classical and mesenchymal TCGA subtype, G3 CGGA subtype, and lower Karnofsky performance score (KPS). Moreover, the signature was an independent factor and was significantly associated with the OS (P = 0.000, hazard ratio (HR) = 1.434). These findings were further validated in two additional datasets (GSE16011, REMBRANDT). Low-risk and high-risk groups displayed different immune status based on principal components analysis. Our results showed that the nine immune-related lncRNAs signature has prognostic value for anaplastic gliomas.

Quantitative Analysis of the KSHV Transcriptome Following Primary Infection of Blood and Lymphatic Endothelial Cells

PubMed Central

Bruce, A. Gregory; Barcy, Serge; DiMaio, Terri; Gan, Emilia; Garrigues, H. Jacques; Lagunoff, Michael; Rose, Timothy M.

2017-01-01

The transcriptome of the Kaposi’s sarcoma-associated herpesvirus (KSHV/HHV8) after primary latent infection of human blood (BEC), lymphatic (LEC) and immortalized (TIME) endothelial cells was analyzed using RNAseq, and compared to long-term latency in BCBL-1 lymphoma cells. Naturally expressed transcripts were obtained without artificial induction, and a comprehensive annotation of the KSHV genome was determined. A set of unique coding sequence (UCDS) features and a process to resolve overlapping transcripts were developed to accurately quantitate transcript levels from specific promoters. Similar patterns of KSHV expression were detected in BCBL-1 cells undergoing long-term latent infections and in primary latent infections of both BEC and LEC cultures. High expression levels of poly-adenylated nuclear (PAN) RNA and spliced and unspliced transcripts encoding the K12 Kaposin B/C complex and associated microRNA region were detected, with an elevated expression of a large set of lytic genes in all latently infected cultures. Quantitation of non-overlapping regions of transcripts across the complete KSHV genome enabled for the first time accurate evaluation of the KSHV transcriptome associated with viral latency in different cell types. Hierarchical clustering applied to a gene correlation matrix identified modules of co-regulated genes with similar correlation profiles, which corresponded with biological and functional similarities of the encoded gene products. Gene modules were differentially upregulated during latency in specific cell types indicating a role for cellular factors associated with differentiated and/or proliferative states of the host cell to influence viral gene expression. PMID:28335496

Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

PubMed Central

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

Discovering Condition-Specific Gene Co-Expression Patterns Using Gaussian Mixture Models: A Cancer Case Study.

PubMed

Ficklin, Stephen P; Dunwoodie, Leland J; Poehlman, William L; Watson, Christopher; Roche, Kimberly E; Feltus, F Alex

2017-08-17

A gene co-expression network (GCN) describes associations between genes and points to genetic coordination of biochemical pathways. However, genetic correlations in a GCN are only detectable if they are present in the sampled conditions. With the increasing quantity of gene expression samples available in public repositories, there is greater potential for discovery of genetic correlations from a variety of biologically interesting conditions. However, even if gene correlations are present, their discovery can be masked by noise. Noise is introduced from natural variation (intrinsic and extrinsic), systematic variation (caused by sample measurement protocols and instruments), and algorithmic and statistical variation created by selection of data processing tools. A variety of published studies, approaches and methods attempt to address each of these contributions of variation to reduce noise. Here we describe an approach using Gaussian Mixture Models (GMMs) to address natural extrinsic (condition-specific) variation during network construction from mixed input conditions. To demonstrate utility, we build and analyze a condition-annotated GCN from a compendium of 2,016 mixed gene expression data sets from five tumor subtypes obtained from The Cancer Genome Atlas. Our results show that GMMs help discover tumor subtype specific gene co-expression patterns (modules) that are significantly enriched for clinical attributes.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments

PubMed Central

Weinberger, Emma M.; Regehr, Keil J.; Berry, Scott M.; Beebe, David J.; Alarid, Elaine T.

2016-01-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture. PMID:27432323

CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing data.

PubMed

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-07-01

Small RNAs (sRNAs) are 20-25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci. To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.

Algorithms on Flag Manifolds for Knowledge Discovery in N-way Arrays

DTIC Science & Technology

2015-11-20

that three of 18 subjects will become symptomatic after only 8 hours. Host pathway analysis of a human endotoxin gene expression data set revealed a 14...pathway analysis of a human endotoxin gene expression data set revealed a 14 pathway signature that identified symptomatic subjects within 2-3 hours post

Construction and analysis of lncRNA-lncRNA synergistic networks to reveal clinically relevant lncRNAs in cancer.

PubMed

Li, Yongsheng; Chen, Juan; Zhang, Jinwen; Wang, Zishan; Shao, Tingting; Jiang, Chunjie; Xu, Juan; Li, Xia

2015-09-22

Long non-coding RNAs (lncRNAs) play key roles in diverse biological processes. Moreover, the development and progression of cancer often involves the combined actions of several lncRNAs. Here we propose a multi-step method for constructing lncRNA-lncRNA functional synergistic networks (LFSNs) through co-regulation of functional modules having three features: common coexpressed genes of lncRNA pairs, enrichment in the same functional category and close proximity within protein interaction networks. Applied to three cancers, we constructed cancer-specific LFSNs and found that they exhibit a scale free and modular architecture. In addition, cancer-associated lncRNAs tend to be hubs and are enriched within modules. Although there is little synergistic pairing of lncRNAs across cancers, lncRNA pairs involved in the same cancer hallmarks by regulating same or different biological processes. Finally, we identify prognostic biomarkers within cancer lncRNA expression datasets using modules derived from LFSNs. In summary, this proof-of-principle study indicates synergistic lncRNA pairs can be identified through integrative analysis of genome-wide expression data sets and functional information.

Effects of CO2 and iron availability on rbcL gene expression in Bering Sea diatoms

NASA Astrophysics Data System (ADS)

Endo, H.; Sugie, K.; Yoshimura, T.; Suzuki, K.

2014-12-01

Iron (Fe) can limit phytoplankton productivity in approximately 40% of the global ocean, including high-nutrient, low-chlorophyll (HNLC) waters. However, there is little information available on the impact of CO2-induced seawater acidification on natural phytoplankton assemblages in HNLC regions. We therefore conducted an on-deck experiment manipulating CO2 and Fe using Fe-deficient Bering Sea waters during the summer of 2009. The concentrations of CO2 in the incubation bottles were set at 380 and 600 ppm in the non-Fe-added (control) bottles and 180, 380, 600, and 1000 ppm in the Fe-added bottles. The phytoplankton assemblages were primarily composed of diatoms followed by haptophytes in all incubation bottles as estimated by pigment signatures throughout the 7 day incubation period. At the end of incubation, the relative contributions of diatoms to chlorophyll a biomass decreased significantly with increased CO2 levels in the controls, whereas minimal changes were found in the Fe-added treatments. These results indicate that, under Fe-deficient conditions, the growth of diatoms was negatively affected by the increase in CO2 availability. To confirm this, we estimated the expression and phylogeny of rbcL (which encodes the large subunit of RubisCO) mRNA in diatoms by quantitative reverse transcription PCR and clone library techniques, respectively. Interestingly, regardless of Fe availability, the expression and diversity of rbcL cDNA decreased in the high CO2 treatments (600 and 1000 ppm). The present study suggests that the projected future increase in seawater pCO2 could reduce the RubisCO activity of diatoms, resulting in a decrease in primary productivity and a shift in the food web structure of the Bering Sea.

BeadArray Expression Analysis Using Bioconductor

PubMed Central

Ritchie, Matthew E.; Dunning, Mark J.; Smith, Mike L.; Shi, Wei; Lynch, Andy G.

2011-01-01

Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered. PMID:22144879

Defective eyelid leading edge cell migration in C57BL/6-corneal opacity mice with an "eye open at birth" phenotype.

PubMed

Wu, L C; Liu, C; Jiang, M R; Jiang, Y M; Wang, Q H; Lu, Z Y; Wang, S J; Yang, W L; Shao, Y X

2016-08-26

Development of the eyelid requires coordination of the cellular processes involved in proliferation, cell size alteration, migration, and cell death. C57BL/6J-corneal opacity (B6-Co) mice are mutant mice generated by the administration of N-ethyl-N-nitrosourea (100 mg/kg). They exhibit the eyelids open at birth phenotype, abnormal round cell shape from tightened F-actin bundles in leading edge keratinocytes at E16.5, and gradual corneal opacity with neovessels. The tip of the leading edge in B6-Co mice did not move forward, and demonstrated a sharp peak shape without obvious directionality. Analysis of the biological characteristics of B6-Co mice demonstrated that abnormal migration of keratinocytes could affect eyelid development, but proliferation and apoptosis in B6-Co mice had no effect. Mutant gene mapping and sequence analysis demonstrated that in B6-Co mice, adenosine was inserted into the untranslated regions, between 3030 and 3031, in the mRNA 3'-terminal of Fgf10. In addition, guanine 7112 was substituted by adenine in the Mtap1B mRNA, and an A2333T mutation was identified in Mtap1B. Quantitative real-time polymerase chain reaction analysis showed that expression of the Hbegf gene was significantly down-regulated in the eyelids of B6- Co mice at E16.5, compared to B6 mice. However, the expression of Rock1, Map3k1, and Jnk1 genes did not show any significant changes. Abnormal keratinocyte migration and down-regulated expression of the Hbegf gene might be associated with impaired eyelid development in B6-Co mice.

Human growth is associated with distinct patterns of gene expression in evolutionarily conserved networks

PubMed Central

2013-01-01

Background A co-ordinated tissue-independent gene expression profile associated with growth is present in rodent models and this is hypothesised to extend to all mammals. Growth in humans has similarities to other mammals but the return to active long bone growth in the pubertal growth spurt is a distinctly human growth event. The aim of this study was to describe gene expression and biological pathways associated with stages of growth in children and to assess tissue-independent expression patterns in relation to human growth. Results We conducted gene expression analysis on a library of datasets from normal children with age annotation, collated from the NCBI Gene Expression Omnibus (GEO) and EBI Arrayexpress databases. A primary data set was generated using cells of lymphoid origin from normal children; the expression of 688 genes (ANOVA false discovery rate modified p-value, q < 0.1) was associated with age, and subsets of these genes formed clusters that correlated with the phases of growth – infancy, childhood, puberty and final height. Network analysis on these clusters identified evolutionarily conserved growth pathways (NOTCH, VEGF, TGFB, WNT and glucocorticoid receptor – Hyper-geometric test, q < 0.05). The greatest degree of network ‘connectivity’ and hence functional significance was present in infancy (Wilcoxon test, p < 0.05), which then decreased through to adulthood. These observations were confirmed in a separate validation data set from lymphoid tissue. Similar biological pathways were observed to be associated with development-related gene expression in other tissues (conjunctival epithelia, temporal lobe brain tissue and bone marrow) suggesting the existence of a tissue-independent genetic program for human growth and maturation. Conclusions Similar evolutionarily conserved pathways have been associated with gene expression and child growth in multiple tissues. These expression profiles associate with the developmental phases of growth including the return to active long bone growth in puberty, a distinctly human event. These observations also have direct medical relevance to pathological changes that induce disease in children. Taking into account development-dependent gene expression profiles for normal children will be key to the appropriate selection of genes and pathways as potential biomarkers of disease or as drug targets. PMID:23941278

Pattern identification in time-course gene expression data with the CoGAPS matrix factorization.

PubMed

Fertig, Elana J; Stein-O'Brien, Genevieve; Jaffe, Andrew; Colantuoni, Carlo

2014-01-01

Patterns in time-course gene expression data can represent the biological processes that are active over the measured time period. However, the orthogonality constraint in standard pattern-finding algorithms, including notably principal components analysis (PCA), confounds expression changes resulting from simultaneous, non-orthogonal biological processes. Previously, we have shown that Markov chain Monte Carlo nonnegative matrix factorization algorithms are particularly adept at distinguishing such concurrent patterns. One such matrix factorization is implemented in the software package CoGAPS. We describe the application of this software and several technical considerations for identification of age-related patterns in a public, prefrontal cortex gene expression dataset.

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

Comparative analysis of behavioral and transcriptional variation underlying CO2 sensory neuron function and development in Drosophila.

PubMed

Pan, Jia Wern; McLaughlin, Joi; Yang, Haining; Leo, Charles; Rambarat, Paula; Okuwa, Sumie; Monroy-Eklund, Anaïs; Clark, Sabrina; Jones, Corbin D; Volkan, Pelin Cayirlioglu

2017-10-02

Carbon dioxide is an important environmental cue for many insects, regulating many behaviors including some that have direct human impacts. To further improve our understanding of how this system varies among closely related insect species, we examined both the behavioral response to CO 2 as well as the transcriptional profile of key developmental regulators of CO 2 sensory neurons in the olfactory system across the Drosophila genus. We found that CO 2 generally evokes repulsive behavior across most of the Drosophilids we examined, but this behavior has been lost or reduced in several lineages. Comparisons of transcriptional profiles from the developing and adult antennae for subset these species suggest that behavioral differences in some species may be due to differences in the expression of the CO 2 co-receptor Gr63a. Furthermore, these differences in Gr63a expression are correlated with changes in the expression of a few genes known to be involved in the development of the CO 2 circuit, namely dac, an important regulator of sensilla fate for sensilla that house CO 2 ORNs, and mip120, a member of the MMB/dREAM epigenetic regulatory complex that regulates CO 2 receptor expression. In contrast, most of the other known structural, molecular, and developmental components of the peripheral Drosophila CO 2 olfactory system seem to be well-conserved across all examined lineages. These findings suggest that certain components of CO 2 sensory ORN development may be more evolutionarily labile, and may contribute to differences in CO 2 -evoked behavioral responses across species.

The neuropeptides CCK and NPY and the changing view of cell-to-cell communication in the taste bud.

PubMed

Herness, Scott; Zhao, Fang-Li

2009-07-14

The evolving view of the taste bud increasingly suggests that it operates as a complex signal processing unit. A number of neurotransmitters and neuropeptides and their corresponding receptors are now known to be expressed in subsets of taste receptor cells in the mammalian bud. These expression patterns set up hard-wired cell-to-cell communication pathways whose exact physiological roles still remain obscure. As occurs in other cellular systems, it is likely that neuropeptides are co-expressed with neurotransmitters and function as neuromodulators. Several neuropeptides have been identified in taste receptor cells including cholecystokinin (CCK), neuropeptide Y (NPY), vasoactive intestinal peptide (VIP), and glucagon-like peptide 1 (GLP-1). Of these, CCK and NPY are the best studied. These two peptides are co-expressed in the same presynaptic cells; however, their postsynaptic actions are both divergent and antagonistic. CCK and its receptor, the CCK-1 subtype, are expressed in the same subset of taste receptor cells and the autocrine activation of these cells produces a number of excitatory physiological actions. Further, most of these cells are responsive to bitter stimuli. On the other hand, NPY and its receptor, the NPY-1 subtype, are expressed in different cells. NPY, acting in a paracrine fashion on NPY-1 receptors, results in inhibitory actions on the cell. Preliminary evidence suggests the NPY-1 receptor expressing cell co-expresses T1R3, a member of the T1R family of G-protein coupled receptors thought to be important in detection of sweet and umami stimuli. Thus the neuropeptide expressing cells co-express CCK, NPY, and CCK-1 receptor. Neuropeptides released from these cells during bitter stimulation may work in concert to both modulate the excitation of bitter-sensitive taste receptor cells while concurrently inhibiting sweet-sensitive cells. This modulatory process is similar to the phenomenon of lateral inhibition that occurs in other sensory systems.

The expression of '150-kDa oxygen regulated protein (ORP-150)' in human brain and its relationship with duration time until death.

PubMed

Ikematsu, Kazuya; Tsuda, Ryouichi; Kondo, Toshikazu; Kondo, Hisayoshi; Ozawa, Kentaro; Ogawa, Satoshi; Nakasono, Ichiro

2004-04-01

The expression of oxygen regulated protein 150-kDa (ORP-150) was strongly induced in human brain under the hypoxic conditions. We examined the expression of ORP-150 in the brain samples, and discussed its significance in forensic practice. The cerebral cortexes of 31 cases (asphyxia: 9 cases, hypothermia: 4, exsanguinations: 5, CO intoxication (CO): 6, sudden cardiac death (SCD): 7) were used for this study. Each tissue section was incubated with anti-ORP-150 polyclonal antibody and the number of ORP-150 positive cells were counted. In the multiple linear regression method, the estimated regression coefficient of ORP-150 on age was significant (P=0.039) thus, we could find that the ORP-150 expression level depended on age. Using analysis of covariance, we compared the means of ORP-150, LSMEAN, which means hypothetic average value excluding influence of age, for each cause of death. The LSMEAN+/-SE was 84.74+/-9.03 in hypothermia, 57.52+/-6.34 in asphyxia, 46.68+/-6.70 in CO, 24.84+/-8.05 in exsanguinations, and 16.24+/-7.35 in SCD. As a result of the analysis, the LSMEAN of the ORP-150 expression level was related to the cause of death. There might be differences in the duration of brain ischemia before death. For example, SCD is presumed to be instant death, while brain ischemia continues for several minutes in asphyxia, CO and exsanguinations, and for several hours in hypothermia cases. Therefore, the immunohistochemical and morphometrical analysis of ORP-150 in the brain may be very useful to determine the duration of brain ischemia before death in forensic autopsy cases.

Enhanced peroxisomal β-oxidation metabolism in visceral adipose tissues of high-fat diet-fed obesity-resistant C57BL/6 mice

PubMed Central

XIE, WEI-DONG; WANG, HUA; ZHANG, JIN-FANG; LI, JIAN-NA; CAN, YI; QING, LV; KUNG, HSIANG-FU; ZHANG, YA-OU

2011-01-01

This study aimed to investigate the potential mechanisms of natural resistance to high-fat diet-induced obesity. Four-week-old C57BL/6 mice were fed a high-fat diet for 6 weeks and were then designated as high-fat diet-fed obesity-prone (HOP) and obesity-resistant (HOR) animals. Their blood biochemistry was evaluated, and visceral adipose tissue samples were subjected to proteomic, Western blot and quantitative real-time PCR (q-PCR) analyses. The HOR mice showed reduced visceral fat weight and size, as well as lowered serum lipid and leptin levels. Proteomic analysis showed that enoyl coenzyme A hydratase 1, peroxisomal (Ech1) expression was significantly increased in their visceral adipose tissues. Moreover, other proteins, such as α-tropomyosin, myosin light chain, urine-nucleoside phosphorylase and transgelin, were also significantly increased. Furthermore, q-PCR analysis showed that the expression of acyl-CoA oxidase 1 palmitoyl, enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase and 3-oxoacyl-CoA thiolase responsible for peroxisomal β-oxidation was also up-regulated in the visceral adipose tissues of the HOR mice. The expression of peroxisome proliferator-activated receptor α (PPARα) was increased in the HOR mice as shown by Western blot analysis. Obesity-resistant animals show enhanced peroxisomal β-oxidation metabolism and reduced fat accumulation in visceral adipose tissues by up-regulating the expression of Ech1, peroxisomal or other related peroxisomal β-oxidation marker genes, which may be driven or enhanced by the up-regulation of the expression of PPARα. However, further validation in future studies is required. PMID:22977503

Molecular Cloning, Characterization, and Functional Analysis of Acetyl-CoA C-Acetyltransferase and Mevalonate Kinase Genes Involved in Terpene Trilactone Biosynthesis from Ginkgo biloba.

PubMed

Chen, Qiangwen; Yan, Jiaping; Meng, Xiangxiang; Xu, Feng; Zhang, Weiwei; Liao, Yongling; Qu, Jinwang

2017-01-02

Ginkgolides and bilobalide, collectively termed terpene trilactones (TTLs), are terpenoids that form the main active substance of Ginkgo biloba . Terpenoids in the mevalonate (MVA) biosynthetic pathway include acetyl-CoA C -acetyltransferase (AACT) and mevalonate kinase (MVK) as core enzymes. In this study, two full-length (cDNAs) encoding AACT ( GbAACT , GenBank Accession No. KX904942) and MVK ( GbMVK , GenBank Accession No. KX904944) were cloned from G. biloba . The deduced GbAACT and GbMVK proteins contain 404 and 396 amino acids with the corresponding open-reading frame (ORF) sizes of 1215 bp and 1194 bp, respectively. Tissue expression pattern analysis revealed that GbAACT was highly expressed in ginkgo fruits and leaves, and GbMVK was highly expressed in leaves and roots. The functional complementation of GbAACT in AACT-deficient Saccharomyces cerevisiae strain Δerg10 and GbMVK in MVK-deficient strain Δerg12 confirmed that GbAACT mediated the conversion of mevalonate acetyl-CoA to acetoacetyl-CoA and GbMVK mediated the conversion of mevalonate to mevalonate phosphate. This observation indicated that GbAACT and GbMVK are functional genes in the cytosolic mevalonate (MVA) biosynthesis pathway. After G. biloba seedlings were treated with methyl jasmonate and salicylic acid, the expression levels of GbAACT and GbMVK increased, and TTL production was enhanced. The cloning, characterization, expression and functional analysis of GbAACT and GbMVK will be helpful to understand more about the role of these two genes involved in TTL biosynthesis.

Directions for Optimization of Photosynthetic Carbon Fixation: RuBisCO's Efficiency May Not Be So Constrained After All.

PubMed

Cummins, Peter L; Kannappan, Babu; Gready, Jill E

2018-01-01

The ubiquitous enzyme Ribulose 1,5-bisphosphate carboxylase-oxygenase (RuBisCO) fixes atmospheric carbon dioxide within the Calvin-Benson cycle that is utilized by most photosynthetic organisms. Despite this central role, RuBisCO's efficiency surprisingly struggles, with both a very slow turnover rate to products and also impaired substrate specificity, features that have long been an enigma as it would be assumed that its efficiency was under strong evolutionary pressure. RuBisCO's substrate specificity is compromised as it catalyzes a side-fixation reaction with atmospheric oxygen; empirical kinetic results show a trend to tradeoff between relative specificity and low catalytic turnover rate. Although the dominant hypothesis has been that the active-site chemistry constrains the enzyme's evolution, a more recent study on RuBisCO stability and adaptability has implicated competing selection pressures. Elucidating these constraints is crucial for directing future research on improving photosynthesis, as the current literature casts doubt on the potential effectiveness of site-directed mutagenesis to improve RuBisCO's efficiency. Here we use regression analysis to quantify the relationships between kinetic parameters obtained from empirical data sets spanning a wide evolutionary range of RuBisCOs. Most significantly we found that the rate constant for dissociation of CO 2 from the enzyme complex was much higher than previous estimates and comparable with the corresponding catalytic rate constant. Observed trends between relative specificity and turnover rate can be expressed as the product of negative and positive correlation factors. This provides an explanation in simple kinetic terms of both the natural variation of relative specificity as well as that obtained by reported site-directed mutagenesis results. We demonstrate that the kinetic behaviour shows a lesser rather than more constrained RuBisCO, consistent with growing empirical evidence of higher variability in relative specificity. In summary our analysis supports an explanation for the origin of the tradeoff between specificity and turnover as due to competition between protein stability and activity, rather than constraints between rate constants imposed by the underlying chemistry. Our analysis suggests that simultaneous improvement in both specificity and turnover rate of RuBisCO is possible.

Molecular cloning and sequence analysis of stearoyl-CoA desaturase in milkfish, Chanos chanos.

PubMed

Hsieh, S L; Liao, W L; Kuo, C M

2001-12-01

Stearoyl-CoA desaturase (EC 1.14.99.5) is a key enzyme in the biosynthesis of polyunsaturated fatty acids and the maintenance of the homeoviscous fluidity of biological membranes. The stearoyl-CoA desaturase cDNA in milkfish (Chanos chanos) was cloned by RT-PCR and RACE, and it was compared with the stearoyl-CoA desaturase in cold-tolerant teleosts, common carp and grass carp. Nucleotide sequence analysis revealed that the cDNA clone has a 972-bp open reading frame encoding 323 amino acid residues. Alignments of the deduced amino acid sequence showed that the milkfish stearoyl-CoA desaturase shares 79% and 75% identity with common carp and grass carp, and 63%-64% with other vertebrates such as sheep, hamsters, rats, mice, and humans. Like common carp and grass carp, the deduced amino acid sequence in milkfish well conserves three histidine cluster motifs (one HXXXXH and two HXXHH) that are essential for catalysis of stearoyl-CoA desaturase activity. However, RT-PCR analysis showed that stearoyl-CoA desaturase expression in milkfish is detected in the tissues of liver, muscle, kidney, brain, and gill, and more expression sites were found in milkfish than in common carp and grass carp. Phylogenic relationships among the deduced stearoyl-CoA desaturase amino acid sequence in milkfish and those in other vertebrates showed that the milkfish stearoyl-CoA desaturase amino acid sequence is phylogenetically closer to those of common carp and grass carp than to other higher vertebrates.

Identifying biomarkers of papillary renal cell carcinoma associated with pathological stage by weighted gene co-expression network analysis.

PubMed

He, Zhongshi; Sun, Min; Ke, Yuan; Lin, Rongjie; Xiao, Youde; Zhou, Shuliang; Zhao, Hong; Wang, Yan; Zhou, Fuxiang; Zhou, Yunfeng

2017-04-25

Although papillary renal cell carcinoma (PRCC) accounts for 10%-15% of renal cell carcinoma (RCC), no predictive molecular biomarker is currently applicable to guiding disease stage of PRCC patients. The mRNASeq data of PRCC and adjacent normal tissue in The Cancer Genome Atlas was analyzed to identify 1148 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 11 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = 0.45) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on nuclear division, cell cycle phase, and spindle (all P < 1e-10). All 40 hub genes in blue module can distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) PRCC (P < 0.01). A good molecular biomarker for pathological stage of RCC must be a prognostic gene in clinical practice. Survival analysis was performed to reversely validate if hub genes were associated with pathological stage. Survival analysis unveiled that all hub genes were associated with patient prognosis (P < 0.01).The validation cohort GSE2748 verified that 30 hub genes can differentiate localized from non-localized PRCC (P < 0.01), and 18 hub genes are prognosis-associated (P < 0.01).ROC curve indicated that the 17 hub genes exhibited excellent diagnostic efficiency for localized and non-localized PRCC (AUC > 0.7). These hub genes may serve as a biomarker and help to distinguish different pathological stages for PRCC patients.

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia

PubMed Central

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J. V.; Schulz, Marcel H.; Simon, Martin

2015-01-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. PMID:26231545

Network of proteins, enzymes and genes linked to biomass degradation shared by Trichoderma species.

PubMed

Horta, Maria Augusta Crivelente; Filho, Jaire Alves Ferreira; Murad, Natália Faraj; de Oliveira Santos, Eidy; Dos Santos, Clelton Aparecido; Mendes, Juliano Sales; Brandão, Marcelo Mendes; Azzoni, Sindelia Freitas; de Souza, Anete Pereira

2018-01-22

Understanding relationships between genes responsible for enzymatic hydrolysis of cellulose and synergistic reactions is fundamental for improving biomass biodegradation technologies. To reveal synergistic reactions, the transcriptome, exoproteome, and enzymatic activities of extracts from Trichoderma harzianum, Trichoderma reesei and Trichoderma atroviride under biodegradation conditions were examined. This work revealed co-regulatory networks across carbohydrate-active enzyme (CAZy) genes and secreted proteins in extracts. A set of 80 proteins and respective genes that might correspond to a common system for biodegradation from the studied species were evaluated to elucidate new co-regulated genes. Differences such as one unique base pair between fungal genomes might influence enzyme-substrate binding sites and alter fungal gene expression responses, explaining the enzymatic activities specific to each species observed in the corresponding extracts. These differences are also responsible for the different architectures observed in the co-expression networks.

Comparison of gene expression and fatty acid profiles in concentrate and forage finished beef.

PubMed

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.

Co-expression of mitosis-regulating genes contributes to malignant progression and prognosis in oligodendrogliomas

PubMed Central

Liu, Yanwei; Hu, Huimin; Zhang, Chuanbao; Wang, Haoyuan; Zhang, Wenlong; Wang, Zheng; Li, Mingyang; Zhang, Wei; Zhou, Dabiao; Jiang, Tao

2015-01-01

The clinical prognosis of patients with glioma is determined by tumor grades, but tumors of different subtypes with equal malignancy grade usually have different prognosis that is largely determined by genetic abnormalities. Oligodendrogliomas (ODs) are the second most common type of gliomas. In this study, integrative analyses found that distribution of TCGA transcriptomic subtypes was associated with grade progression in ODs. To identify critical gene(s) associated with tumor grades and TCGA subtypes, we analyzed 34 normal brain tissue (NBT), 146 WHO grade II and 130 grade III ODs by microarray and RNA sequencing, and identified a co-expression network of six genes (AURKA, NDC80,CENPK, KIAA0101, TIMELESS and MELK) that was associated with tumor grades and TCGA subtypes as well as Ki-67 expression. Validation of the six genes was performed by qPCR in additional 28 ODs. Importantly, these genes also were validated in four high-grade recurrent gliomas and the initial lower-grade gliomas resected from the same patients. Finally, the RNA data on two genes with the highest discrimination potential (AURKA and NDC80) and Ki-67 were validated on an independent cohort (5 NBTs and 86 ODs) by immunohistochemistry. Knockdown of AURKA and NDC80 by siRNAs suppressed Ki-67 expression and proliferation of gliomas cells. Survival analysis showed that high expression of the six genes corporately indicated a poor survival outcome. Correlation and protein interaction analysis provided further evidence for this co-expression network. These data suggest that the co-expression of the six mitosis-regulating genes was associated with malignant progression and prognosis in ODs. PMID:26468983

Functional characterization of two new members of the caffeoyl CoA O-methyltransferase-like gene family from Vanilla planifolia reveals a new class of plastid-localized O-methyltransferases.

PubMed

Widiez, Thomas; Hartman, Thomas G; Dudai, Nativ; Yan, Qing; Lawton, Michael; Havkin-Frenkel, Daphna; Belanger, Faith C

2011-08-01

Caffeoyl CoA O-methyltransferases (OMTs) have been characterized from numerous plant species and have been demonstrated to be involved in lignin biosynthesis. Higher plant species are known to have additional caffeoyl CoA OMT-like genes, which have not been well characterized. Here, we identified two new caffeoyl CoA OMT-like genes by screening a cDNA library from specialized hair cells of pods of the orchid Vanilla planifolia. Characterization of the corresponding two enzymes, designated Vp-OMT4 and Vp-OMT5, revealed that in vitro both enzymes preferred as a substrate the flavone tricetin, yet their sequences and phylogenetic relationships to other enzymes are distinct from each other. Quantitative analysis of gene expression indicated a dramatic tissue-specific expression pattern for Vp-OMT4, which was highly expressed in the hair cells of the developing pod, the likely location of vanillin biosynthesis. Although Vp-OMT4 had a lower activity with the proposed vanillin precursor, 3,4-dihydroxybenzaldehyde, than with tricetin, the tissue specificity of expression suggests it may be a candidate for an enzyme involved in vanillin biosynthesis. In contrast, the Vp-OMT5 gene was mainly expressed in leaf tissue and only marginally expressed in pod hair cells. Phylogenetic analysis suggests Vp-OMT5 evolved from a cyanobacterial enzyme and it clustered within a clade in which the sequences from eukaryotic species had predicted chloroplast transit peptides. Transient expression of a GFP-fusion in tobacco demonstrated that Vp-OMT5 was localized in the plastids. This is the first flavonoid OMT demonstrated to be targeted to the plastids.

Co-culture of 3D tumor spheroids with fibroblasts as a model for epithelial–mesenchymal transition in vitro

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

Kim, Sun-Ah, E-mail: j.sarah.k@gmail.com; Lee, Eun Kyung, E-mail: leeek@catholic.ac.kr; Cancer Evolution Research Center, College of Medicine, The Catholic University of Korea, Seoul 137-701

Epithelial–mesenchymal transition (EMT) acts as a facilitator of metastatic dissemination in the invasive margin of malignant tumors where active tumor–stromal crosstalks take place. Co-cultures of cancer cells with cancer-associated fibroblasts (CAFs) are often used as in vitro models of EMT. We established a tumor–fibroblast proximity co-culture using HT-29 tumor spheroids (TSs) with CCD-18co fibroblasts. When co-cultured with TSs, CCD-18co appeared activated, and proliferative activity as well as cell migration increased. Expression of fibronectin increased whereas laminin and type I collagen decreased in TSs co-cultured with fibroblasts compared to TSs alone, closely resembling the margin of in vivo xenograft tissue. Activemore » TGFβ1 in culture media significantly increased in TS co-cultures but not in 2D co-cultures of cancer cells–fibroblasts, indicating that 3D context-associated factors from TSs may be crucial to crosstalks between cancer cells and fibroblasts. We also observed in TSs co-cultured with fibroblasts increased expression of α-SMA, EGFR and CTGF; reduced expression of membranous β-catenin and E-cadherin, together suggesting an EMT-like changes similar to a marginal region of xenograft tissue in vivo. Overall, our in vitro TS–fibroblast proximity co-culture mimics the EMT-state of the invasive margin of in vivo tumors in early metastasis. - Highlights: • An adjacent co-culture of tumor spheroids and fibroblasts is presented as EMT model. • Activation of fibroblasts and increased cell migration were shown in co-culture. • Expression of EMT-related factors in co-culture was similar to that in tumor tissue. • Crosstalk between spheroids and fibroblasts was demonstrated by secretome analysis.« less

Comprehensive analysis of lncRNAs microarray profile and mRNA-lncRNA co-expression in oncogenic HPV-positive cervical cancer cell lines.

PubMed

Yang, LingYun; Yi, Ke; Wang, HongJing; Zhao, YiQi; Xi, MingRong

2016-08-02

Long non-coding RNAs are emerging to be novel regulators in gene expression. In current study, lncRNAs microarray and lncRNA-mRNA co-expression analysis were performed to explore the alternation and function of lncRNAs in cervical cancer cells. We identified that 4750 lncRNAs (15.52%) were differentially expressed in SiHa (HPV-16 positive) (2127 up-regulated and 2623 down-regulated) compared with C-33A (HPV negative), while 5026 lncRNAs (16.43%) were differentially expressed in HeLa (HPV-18 positive) (2218 up-regulated and 2808 down-regulated) respectively. There were 5008 mRNAs differentially expressed in SiHa and 4993 in HeLa, which were all cataloged by GO terms and KEGG pathway. With the help of mRNA-lncRNA co-expression network, we found that ENST00000503812 was significantly negative correlated with RAD51B and IL-28A expression in SiHa, while ENST00000420168, ENST00000564977 and TCONS_00010232 had significant correlation with FOXQ1 and CASP3 expression in HeLa. Up-regulation of ENST00000503812 may inhibit RAD51B and IL-28A expression and result in deficiency of DNA repair pathway and immune responses in HPV-16 positive cervical cancer cell. Up-regulation of ENST00000420168, ENST00000564977 and down-regulation of TCONS_00010232 might stimulate FOXQ1 expression and suppress CASP3 expression in HPV-18 positive cervical cancer cell, which lead to HPV-induced proliferation and deficiency in apoptosis. These results indicate that changes of lncRNAs and related mRNAs might impact on several cellular pathways and involve in HPV-induced proliferation, which enriches our understanding of lncRNAs and coding transcripts anticipated in HPV oncogenesis of cervical cancer.

RNA sequencing analysis reveals new findings of hyperbaric oxygen treatment on rats with acute carbon monoxide poisoning.

PubMed

Wang, Wenlan; Xue, Li; Li, Ya; Li, Rong; Xie, Xiaoping; Bao, Junxiang; Hai, Chunxu; Li, Jinsheng

2016-01-01

To elucidate the altered gene network in the brains of carbon monoxide (CO) poisoned rats after treatment with hyperbaric oxygen (HBO₂). RNA sequencing (RNA-seq) analysis was performed to examine differentially expressed genes (DEGs) in brain tissue samples from nine male rats: a normal control group; a CO poisoning group; and an HBO₂ treatment group (three rats/group). Reverse transcription polymerase chain reaction (RT-PCR) and real-time quantitative PCR were used for validation of the DEGs in another 18 male rats (six rats/group). RNA-seq revealed that two genes were upregulated (4.18 and 8.76 log to the base 2 fold change) (p⟨0.05) in the CO-poisoned rats relative to the control rats; two genes were upregulated (3.88 and 7.69 log to the base 2 fold change); and 23 genes were downregulated (3.49-15.12 log to the base 2 fold change) (p⟨0.05) in the brains of the HBO₂-treated rats relative to the CO-poisoned rats. Target prediction of DEGs by gene network analysis and analysis of pathways affected suggested that regulation of gene expressions of dopamine metabolism and nitric oxide (NO) synthesis were significantly affected by CO poisoning and HBO₂ treatment. Results of RT-PCR and real-time quantitative PCR indicated that four genes (Pomc, GH-1, Pr1 and Fshβ) associated with hormone secretion in the hypothalamic-pituitary system have potential as markers for prognosis of CO. This study is the first RNA-seq analysis profile of HBO₂ treatment on rats with acute CO poisoning. It concludes that changes of hormone secretion in the hypothalamic-pituitary system, dopamine metabolism and NO synthesis involved in brain damage and behavior abnormalities after CO poisoning and HBO₂ therapy may regulate these changes.

Reconstruction of the genome-scale co-expression network for the Hippo signaling pathway in colorectal cancer.

PubMed

Dehghanian, Fariba; Hojati, Zohreh; Hosseinkhan, Nazanin; Mousavian, Zaynab; Masoudi-Nejad, Ali

2018-05-26

The Hippo signaling pathway (HSP) has been identified as an essential and complex signaling pathway for tumor suppression that coordinates proliferation, differentiation, cell death, cell growth and stemness. In the present study, we conducted a genome-scale co-expression analysis to reconstruct the HSP in colorectal cancer (CRC). Five key modules were detected through network clustering, and a detailed discussion of two modules containing respectively 18 and 13 over and down-regulated members of HSP was provided. Our results suggest new potential regulatory factors in the HSP. The detected modules also suggest novel genes contributing to CRC. Moreover, differential expression analysis confirmed the differential expression pattern of HSP members and new suggested regulatory factors between tumor and normal samples. These findings can further reveal the importance of HSP in CRC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Association of HADHA expression with the risk of breast cancer: targeted subset analysis and meta-analysis of microarray data

PubMed Central

2012-01-01

Background The role of n-3 fatty acids in prevention of breast cancer is well recognized, but the underlying molecular mechanisms are still unclear. In view of the growing need for early detection of breast cancer, Graham et al. (2010) studied the microarray gene expression in histologically normal epithelium of subjects with or without breast cancer. We conducted a secondary analysis of this dataset with a focus on the genes (n = 47) involved in fat and lipid metabolism. We used stepwise multivariate logistic regression analyses, volcano plots and false discovery rates for association analyses. We also conducted meta-analyses of other microarray studies using random effects models for three outcomes--risk of breast cancer (380 breast cancer patients and 240 normal subjects), risk of metastasis (430 metastatic compared to 1104 non-metastatic breast cancers) and risk of recurrence (484 recurring versus 890 non-recurring breast cancers). Results The HADHA gene [hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit] was significantly under-expressed in breast cancer; more so in those with estrogen receptor-negative status. Our meta-analysis showed an 18.4%-26% reduction in HADHA expression in breast cancer. Also, there was an inconclusive but consistent under-expression of HADHA in subjects with metastatic and recurring breast cancers. Conclusions Involvement of mitochondria and the mitochondrial trifunctional protein (encoded by HADHA gene) in breast carcinogenesis is known. Our results lend additional support to the possibility of this involvement. Further, our results suggest that targeted subset analysis of large genome-based datasets can provide interesting association signals. PMID:22240105

Mesenchymal stromal cells (MSCs) induce ex vivo proliferation and erythroid commitment of cord blood haematopoietic stem cells (CB-CD34+ cells)

PubMed Central

Perucca, Simone; Di Palma, Andrea; Piccaluga, Pier Paolo; Gemelli, Claudia; Zoratti, Elisa; Bassi, Giulio; Giacopuzzi, Edoardo; Lojacono, Andrea; Borsani, Giuseppe; Tagliafico, Enrico; Scupoli, Maria Teresa; Bernardi, Simona; Zanaglio, Camilla; Cattina, Federica; Cancelli, Valeria; Malagola, Michele; Krampera, Mauro; Marini, Mirella; Almici, Camillo; Ferrari, Sergio; Russo, Domenico

2017-01-01

A human bone marrow-derived mesenchymal stromal cell (MSCs) and cord blood-derived CD34+ stem cell co-culture system was set up in order to evaluate the proliferative and differentiative effects induced by MSCs on CD34+ stem cells, and the reciprocal influences on gene expression profiles. After 10 days of co-culture, non-adherent (SN-fraction) and adherent (AD-fraction) CD34+ stem cells were collected and analysed separately. In the presence of MSCs, a significant increase in CD34+ cell number was observed (fold increase = 14.68), mostly in the SN-fraction (fold increase = 13.20). This was combined with a significant increase in CD34+ cell differentiation towards the BFU-E colonies and with a decrease in the CFU-GM. These observations were confirmed by microarray analysis. Through gene set enrichment analysis (GSEA), we noted a significant enrichment in genes involved in heme metabolism (e.g. LAMP2, CLCN3, BMP2K), mitotic spindle formation and proliferation (e.g. PALLD, SOS1, CCNA1) and TGF-beta signalling (e.g. ID1) and a down-modulation of genes participating in myeloid and lymphoid differentiation (e.g. PCGF2) in the co-cultured CD34+ stem cells. On the other hand, a significant enrichment in genes involved in oxygen-level response (e.g. TNFAIP3, SLC2A3, KLF6) and angiogenesis (e.g. VEGFA, IGF1, ID1) was found in the co-cultured MSCs. Taken together, our results suggest that MSCs can exert a priming effect on CD34+ stem cells, regulating their proliferation and erythroid differentiation. In turn, CD34+ stem cells seem to be able to polarise the BM-niche towards the vascular compartment by modulating molecular pathways related to hypoxia and angiogenesis. PMID:28231331

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

PubMed

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

NOTCH3 is expressed in human apical papilla and in subpopulations of stem cells isolated from the tissue.

PubMed

Jamal, Mohamed; Chogle, Sami M; Karam, Sherif M; Huang, George T-J

2015-09-01

NOTCH plays a role in regulating stem cell function and fate decision. It is involved in tooth development and injury repair. Information regarding NOTCH expression in human dental root apical papilla (AP) and its residing stem cells (SCAP) is limited. Here we investigated the expression of NOTCH3, its ligand JAG1, and mesenchymal stem cell markers CD146 and STRO-1 in the AP or in the primary cultures of SCAP isolated from AP. Our in situ immunostaining showed that in the AP NOTCH3 and CD146 were co-expressed and associated with blood vessels having NOTCH3 located more peripherally. In cultured SCAP, NOTCH3 and JAG1 were co-expressed. Flow cytometry analysis showed that 7%, 16% and 98% of the isolated SCAP were positive for NOTCH3, STRO-1 and CD146, respectively with a rare 1.5% subpopulation of SCAP co-expressing all three markers. The expression level of NOTCH3 reduced when SCAP underwent osteogenic differentiation. Our findings are the first step towards defining the regulatory role of NOTCH3 in SCAP fate decision.

Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis

PubMed Central

Lee, Won Jun; Kim, Sang Cheol; Yoon, Jung-Ho; Yoon, Sang Jun; Lim, Johan; Kim, You-Sun; Kwon, Sung Won; Park, Jeong Hill

2016-01-01

Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of < 0.05, and our network analysis showed high connectivity in five genes. From these results, we established CXCR4, CXCL1 and HMGCS1, the intersecting genes of the datasets with high connectivity and p-value of < 0.05, as significant genes in the identification of cancer stem cells. Additional experiment using quantitative reverse transcription-polymerase chain reaction showed significant up-regulation in MCF-7 derived sphere cells and confirmed the importance of these three genes. Taken together, using meta-analysis that combines gene set and network analysis, we suggested CXCR4, CXCL1 and HMGCS1 as candidates involved in tumor stem-like breast cancer cells. Distinct from other meta-analysis, by using gene set analysis, we selected possible markers which can explain the biological mechanisms and suggested network analysis as an additional criterion for selecting candidates. PMID:26870956

Proteomic analysis to investigate color changes of chilled beef longissimus steaks held under carbon monoxide and high oxygen packaging.

PubMed

Yang, Xiaoyin; Wu, Shuang; Hopkins, David L; Liang, Rongrong; Zhu, Lixian; Zhang, Yimin; Luo, Xin

2018-08-01

This study investigated the proteome basis for color stability variations in beef steaks packaged under two modified atmosphere packaging (MAP) methods: HiOx-MAP (80% O 2 /20% CO 2 ) and CO-MAP (0.4% CO/30% CO 2 /69.6% N 2 ) during 15 days of storage. The color stability, pH, and sarcoplasmic proteome analysis of steaks were evaluated on days 0, 5, 10 and 15 of storage. Proteomic results revealed that the differential expression of the sarcoplasmic proteome during storage contributed to the variations in meat color stability between the two MAP methods. Compared with HiOx-MAP steaks, some glycolytic and energy metabolic enzymes important in NADH regeneration and antioxidant processes, antioxidant peroxiredoxins (thioredoxin-dependent peroxide reductase, peroxiredoxin-2, peroxiredoxin-6) and protein DJ-1 were more abundant in CO-MAP steaks. The over-expression of these proteins could induce CO-MAP steaks to maintain high levels of metmyoglobin reducing activity and oxygen consumption rate, resulting in CO-MAP steaks exhibiting better color stability than HiOx-MAP steaks during storage. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genes and gene networks implicated in aggression related behaviour.

PubMed

Malki, Karim; Pain, Oliver; Du Rietz, Ebba; Tosto, Maria Grazia; Paya-Cano, Jose; Sandnabba, Kenneth N; de Boer, Sietse; Schalkwyk, Leonard C; Sluyter, Frans

2014-10-01

Aggressive behaviour is a major cause of mortality and morbidity. Despite of moderate heritability estimates, progress in identifying the genetic factors underlying aggressive behaviour has been limited. There are currently three genetic mouse models of high and low aggression created using selective breeding. This is the first study to offer a global transcriptomic characterization of the prefrontal cortex across all three genetic mouse models of aggression. A systems biology approach has been applied to transcriptomic data across the three pairs of selected inbred mouse strains (Turku Aggressive (TA) and Turku Non-Aggressive (TNA), Short Attack Latency (SAL) and Long Attack Latency (LAL) mice and North Carolina Aggressive (NC900) and North Carolina Non-Aggressive (NC100)), providing novel insight into the neurobiological mechanisms and genetics underlying aggression. First, weighted gene co-expression network analysis (WGCNA) was performed to identify modules of highly correlated genes associated with aggression. Probe sets belonging to gene modules uncovered by WGCNA were carried forward for network analysis using ingenuity pathway analysis (IPA). The RankProd non-parametric algorithm was then used to statistically evaluate expression differences across the genes belonging to modules significantly associated with aggression. IPA uncovered two pathways, involving NF-kB and MAPKs. The secondary RankProd analysis yielded 14 differentially expressed genes, some of which have previously been implicated in pathways associated with aggressive behaviour, such as Adrbk2. The results highlighted plausible candidate genes and gene networks implicated in aggression-related behaviour.

Genome-Wide Analysis of Long Noncoding RNA (lncRNA) Expression in Hepatoblastoma Tissues

PubMed Central

Xue, Ping; Cui, Ximao; Li, Kai; Zheng, Shan; He, Xianghuo; Dong, Kuiran

2014-01-01

Long noncoding RNAs (lncRNAs) have crucial roles in cancer biology. We performed a genome-wide analysis of lncRNA expression in hepatoblastoma tissues to identify novel targets for further study of hepatoblastoma. Hepatoblastoma and normal liver tissue samples were obtained from hepatoblastoma patients. The genome-wide analysis of lncRNA expression in these tissues was performed using a 4×180 K lncRNA microarray and Sureprint G3 Human lncRNA Chips. Quantitative RT-PCR (qRT-PCR) was performed to confirm these results. The differential expressions of lncRNAs and mRNAs were identified through fold-change filtering. Gene Ontology (GO) and pathway analyses were performed using the standard enrichment computation method. Associations between lncRNAs and adjacent protein-coding genes were determined through complex transcriptional loci analysis. We found that 2736 lncRNAs were differentially expressed in hepatoblastoma tissues. Among these, 1757 lncRNAs were upregulated more than two-fold relative to normal tissues and 979 lncRNAs were downregulated. Moreover, in hepatoblastoma there were 420 matched lncRNA-mRNA pairs for 120 differentially expressed lncRNAs, and 167 differentially expressed mRNAs. The co-expression network analysis predicted 252 network nodes and 420 connections between 120 lncRNAs and 132 coding genes. Within this co-expression network, 369 pairs were positive, and 51 pairs were negative. Lastly, qRT-PCR data verified six upregulated and downregulated lncRNAs in hepatoblastoma, plus endothelial cell-specific molecule 1 (ESM1) mRNA. Our results demonstrated that expression of these aberrant lncRNAs could respond to hepatoblastoma development. Further study of these lncRNAs could provide useful insight into hepatoblastoma biology. PMID:24465615

Dynamics of Metabolite Induction in Fungal Co-cultures by Metabolomics at Both Volatile and Non-volatile Levels

PubMed Central

Azzollini, Antonio; Boggia, Lorenzo; Boccard, Julien; Sgorbini, Barbara; Lecoultre, Nicole; Allard, Pierre-Marie; Rubiolo, Patrizia; Rudaz, Serge; Gindro, Katia; Bicchi, Carlo; Wolfender, Jean-Luc

2018-01-01

Fungal co-cultivation has emerged as a promising way for activating cryptic biosynthetic pathways and discovering novel antimicrobial metabolites. For the success of such studies, a key element remains the development of standardized co-cultivation methods compatible with high-throughput analytical procedures. To efficiently highlight induction processes, it is crucial to acquire a holistic view of intermicrobial communication at the molecular level. To tackle this issue, a strategy was developed based on the miniaturization of fungal cultures that allows for a concomitant survey of induction phenomena in volatile and non-volatile metabolomes. Fungi were directly grown in vials, and each sample was profiled by head space solid phase microextraction gas chromatography mass spectrometry (HS-SPME-GC-MS), while the corresponding solid culture medium was analyzed by liquid chromatography high resolution mass spectrometry (LC-HRMS) after solvent extraction. This strategy was implemented for the screening of volatile and non-volatile metabolite inductions in an ecologically relevant fungal co-culture of Eutypa lata (Pers.) Tul. & C. Tul. (Diatrypaceae) and Botryosphaeria obtusa (Schwein.) Shoemaker (Botryosphaeriaceae), two wood-decaying fungi interacting in the context of esca disease of grapevine. For a comprehensive evaluation of the results, a multivariate data analysis combining Analysis of Variance and Partial Least Squares approaches, namely AMOPLS, was used to explore the complex LC-HRMS and GC-MS datasets and highlight dynamically induced compounds. A time-series study was carried out over 9 days, showing characteristic metabolite induction patterns in both volatile and non-volatile dimensions. Relevant links between the dynamics of expression of specific metabolite production were observed. In addition, the antifungal activity of 2-nonanone, a metabolite incrementally produced over time in the volatile fraction, was assessed against Eutypa lata and Botryosphaeria obtusa in an adapted bioassay set for volatile compounds. This compound has shown antifungal activity on both fungi and was found to be co-expressed with a known antifungal compound, O-methylmellein, induced in solid media. This strategy could help elucidate microbial inter- and intra-species cross-talk at various levels. Moreover, it supports the study of concerted defense/communication mechanisms for efficiently identifying original antimicrobials. PMID:29459851

The kids at Hamilton Elementary School: Purposes and practices for co-opting science

NASA Astrophysics Data System (ADS)

Ortiz, Loaiza

The purpose of this study was to explore youth's purposes and motivations for engaging in science through the lens of science practices. The construct of science practices allowed me to see science in youths' lives in a holistic way, shaped by social, political, historical, economic and cultural forces. The framework for understanding urban youths' science practices is grounded in the intersections of critical and feminist theory, sociocultural learning theories, especially as applied in research in urban science education, and recent work in critical literacy studies. As I explored the answers to my research questions---(1) When 5th grade youth, living in predominantly Latino communities struggling with urban poverty, engage in science how and why do they co-opt science in ways that result in changes in participation in science? (2) What are the science practices that facilitate youths' coopting of science? And how are those practices framed by context (school, out-of-school), content (LiFE curriculum), and funds of knowledge? (3) In what ways are science practices expressions of youths' scientific literacy? And (4) In what ways do youth use science practices as tools for expressing identities and agency?---I engaged in feminist ethnography with embedded case studies. Data were collected in 2004 in school and in out of school settings. I recorded numerous informal conversations, interviews, and observations both during after-school and students' regular science and non-science classes. Findings describe how and why students co-opted science for purposes that make sense for their lives. These purposes included gaining and activating resources, building and maintaining social relationships, bridging home and school knowledge, positioning themselves with authority, and constructing science identities. Findings also explored what practices facilitated youth's co-opting of science. I highlighted three practices: making ideas public, storytelling and prioritizing and using evidence. Finally, I present an in-depth analysis of the science practice of storytelling. Analysis revealed that students engaged in storytelling to facilitate co-opting of science by: allowing them to change the discourse of the science classroom, to seek legitimacy, and to position themselves with authority. I end with implications for urban science education, teacher education and for future research.

Expressed Glycosylphosphatidylinositol-Anchored Horseradish Peroxidase Identifies Co-Clustering Molecules in Individual Lipid Raft Domains

PubMed Central

Miyagawa-Yamaguchi, Arisa; Kotani, Norihiro; Honke, Koichi

2014-01-01

Lipid rafts that are enriched in glycosylphosphatidylinositol (GPI)-anchored proteins serve as a platform for important biological events. To elucidate the molecular mechanisms of these events, identification of co-clustering molecules in individual raft domains is required. Here we describe an approach to this issue using the recently developed method termed enzyme-mediated activation of radical source (EMARS), by which molecules in the vicinity within 300 nm from horseradish peroxidase (HRP) set on the probed molecule are labeled. GPI-anchored HRP fusion proteins (HRP-GPIs), in which the GPI attachment signals derived from human decay accelerating factor and Thy-1 were separately connected to the C-terminus of HRP, were expressed in HeLa S3 cells, and the EMARS reaction was catalyzed by these expressed HRP-GPIs under a living condition. As a result, these different HRP-GPIs had differences in glycosylation and localization and formed distinct clusters. This novel approach distinguished molecular clusters associated with individual GPI-anchored proteins, suggesting that it can identify co-clustering molecules in individual raft domains. PMID:24671047

Stimulation of StAR expression by cAMP is controlled by inhibition of highly inducible SIK1 via CRTC2, a co-activator of CREB.

PubMed

Lee, Jinwoo; Tong, Tiegang; Takemori, Hiroshi; Jefcoate, Colin

2015-06-15

In mouse steroidogenic cells the activation of cholesterol metabolism is mediated by steroidogenic acute regulatory protein (StAR). Here, we visualized a coordinated regulation of StAR transcription, splicing and post-transcriptional processing, which are synchronized by salt inducible kinase (SIK1) and CREB-regulated transcription coactivator (CRTC2). To detect primary RNA (pRNA), spliced primary RNA (Sp-RNA) and mRNA in single cells, we generated probe sets by using fluorescence in situ hybridization (FISH). These methods allowed us to address the nature of StAR gene expression and to visualize protein-nucleic acid interactions through direct detection. We show that SIK1 represses StAR expression in Y1 adrenal and MA10 testis cells through inhibition of processing mediated by CRTC2. Digital image analysis matches qPCR analyses of the total cell culture. Evidence is presented for spatially separate accumulation of StAR pRNA and Sp-RNA at the gene loci in the nucleus. These findings establish that cAMP, SIK and CRTC mediate StAR expression through activation of individual StAR gene loci. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Transcriptional regulation by the Set7 lysine methyltransferase

PubMed Central

Keating, Samuel; El-Osta, Assam

2013-01-01

Posttranslational histone modifications define chromatin structure and function. In recent years, a number of studies have characterized many of the enzymatic activities and diverse regulatory components required for monomethylation of histone H3 lysine 4 (H3K4me1) and the expression of specific genes. The challenge now is to understand how this specific chemical modification is written and the Set7 methyltransferase has emerged as a key regulatory enzyme mediating methylation of lysine residues of histone and non-histone proteins. In this review, we comprehensively explore the regulatory proteins modified by Set7 and highlight mechanisms of specific co-recruitment of the enzyme to activating promoters. With a focus on signaling and transcriptional control in disease we discuss recent experimental data emphasizing specific components of diverse regulatory complexes that mediate chromatin modification and reinterpretation of Set7-mediated gene expression. PMID:23478572

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

PubMed

Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

2016-04-01

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P < 0.05 to maximize discovery. Over-representation of genes associated for nearly all traits was found in a xylem preferential co-expression group developed in independent experiments. A xylem co-expression network was reconstructed with 180 wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

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

PubMed Central

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

1999-01-01

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

Meta-analysis of gene expression patterns in animal models of prenatal alcohol exposure suggests role for protein synthesis inhibition and chromatin remodeling

PubMed Central

Rogic, Sanja; Wong, Albertina; Pavlidis, Paul

2017-01-01

Background Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioural and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models, however there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. Methods We assembled ten microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and post-natal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. Results For each sub-analysis we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute ethanol treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over-representation of genes involved in protein synthesis, mRNA splicing and chromatin organization. Conclusions Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of FASD. PMID:26996386

Functional expression of Ca²⁺ dependent mammalian transmembrane gap junction protein Cx43 in slime mold Dictyostelium discoideum.

PubMed

Kaufmann, Stefan; Weiss, Ingrid M; Eckstein, Volker; Tanaka, Motomu

2012-03-09

In this paper, we expressed murine gap junction protein Cx43 in Dictyostelium discoideum by introducing the specific vector pDXA. In the first step, the successful expression of Cx43 and Cx43-eGFP was verified by (a) Western blot (anti-Cx43, anti-GFP), (b) fluorescence microscopy (eGFP-Cx43 co-expression, Cx43 immunostaining), and (c) flow cytometry analysis (eGFP-Cx43 co-expression). Although the fluorescence signals from cells expressing Cx43-eGFP detected by fluorescence microscopy seem relatively low, analysis by flow cytometry demonstrated that more than 60% of cells expressed Cx43-eGFP. In order to evaluate the function of expressed Cx43 in D. discoideum, we examined the hemi-channel function of Cx43. In this series of experiments, the passive uptake of carboxyfluorescein was monitored using flow cytometric analysis. A significant number of the transfected cells showed a prominent dye uptake in the absence of Ca(2+). The dye uptake by transfected cells in the presence of Ca(2+) was even lower than the non-specific dye uptake by non-transformed Ax3 orf+ cells, confirming that Cx43 expressed in D. discoideum retains its Ca(2+)-dependent, specific gating function. The expression of gap junction proteins expressed in slime molds opens a possibility to the biological significance of intercellular communications in development and maintenance of multicellular organisms. Copyright © 2012 Elsevier Inc. All rights reserved.

Expression Profiling-Based Identification of CO2-Responsive Genes Regulated by CCM1 Controlling a Carbon-Concentrating Mechanism in Chlamydomonas reinhardtii1

PubMed Central

Miura, Kenji; Yamano, Takashi; Yoshioka, Satoshi; Kohinata, Tsutomu; Inoue, Yoshihiro; Taniguchi, Fumiya; Asamizu, Erika; Nakamura, Yasukazu; Tabata, Satoshi; Yamato, Katsuyuki T.; Ohyama, Kanji; Fukuzawa, Hideya

2004-01-01

Photosynthetic acclimation to CO2-limiting stress is associated with control of genetic and physiological responses through a signal transduction pathway, followed by integrated monitoring of the environmental changes. Although several CO2-responsive genes have been previously isolated, genome-wide analysis has not been applied to the isolation of CO2-responsive genes that may function as part of a carbon-concentrating mechanism (CCM) in photosynthetic eukaryotes. By comparing expression profiles of cells grown under CO2-rich conditions with those of cells grown under CO2-limiting conditions using a cDNA membrane array containing 10,368 expressed sequence tags, 51 low-CO2 inducible genes and 32 genes repressed by low CO2 whose mRNA levels were changed more than 2.5-fold in Chlamydomonas reinhardtii Dangeard were detected. The fact that the induction of almost all low-CO2 inducible genes was impaired in the ccm1 mutant suggests that CCM1 is a master regulator of CCM through putative low-CO2 signal transduction pathways. Among low-CO2 inducible genes, two novel genes, LciA and LciB, were identified, which may be involved in inorganic carbon transport. Possible functions of low-CO2 inducible and/or CCM1-regulated genes are discussed in relation to the CCM. PMID:15235119

Cross section data sets for electron collisions with H2, O2, CO, CO2, N2O and H2O

NASA Astrophysics Data System (ADS)

Anzai, K.; Kato, H.; Hoshino, M.; Tanaka, H.; Itikawa, Y.; Campbell, L.; Brunger, M. J.; Buckman, S. J.; Cho, H.; Blanco, F.; Garcia, G.; Limão-Vieira, P.; Ingólfsson, O.

2012-02-01

We review earlier cross section data sets for electron-collisions with H2, O2, CO, CO2, H2O and N2O, updated here by experimental results for their electronic states. Based on our recent measurements of differential cross sections for the electronic states of those molecules, integral cross sections (ICSs) are derived by applying a generalized oscillator strength analysis and then assessed against theory (BE f-scaling [Y.-K. Kim, J. Chem. Phys. 126, 064305 (2007)]). As they now represent benchmark electronic state cross sections, those ICSs for the above molecules are added into the original cross section sets taken from the data reviews for H2, O2, CO2 and H2O (the Itikawa group), and for CO and N2O (the Zecca group).

Simultaneous assimilation of satellite NO2, O3, CO, and HNO3 data for the analysis of the tropospheric chemical composition

NASA Astrophysics Data System (ADS)

Miyazaki, K.; Eskes, H.; Sudo, K.

2012-04-01

Carbon monoxide (CO) and nitrogen oxides (NOx) play an important role in tropospheric chemistry through their influences on the ozone and hydroxyl radical (OH). The simultaneous optimization of various chemical components is expected to improve the emission inversion through the better description of the chemical feedbacks in the NOx- and CO-chemistry. This study aims to reproduce chemical composition distributions in the troposphere by combining information obtained from multiple satellite data sets. The emissions of CO and NOx, together with the 3D concentration fields of all forecasted chemical species in the global CTM CHASER have been simultaneously optimized using the ensemble Kalman filter (EnKF) data assimilation technique, and NO2, O3, CO, and HNO3 data obtained from OMI, TES, MOPITT, and MLS satellite measurements. The performance is evaluated against independent data from ozone sondes, aircraft measurements, GOME-2, and SCIAMACHY satellite data. Observing System Experiments (OSEs) have been carried out. These OSEs quantify the relative importance of each data set on constraining the emissions and concentrations. We confirmed that the simultaneous data assimilation improved the agreement with these independent data sets. The combined analysis of multiple data sets by means of advanced data assimilation system can provide a useful framework for the air quality research.

Co-expression networks reveal the tissue-specific regulation of transcription and splicing.

PubMed

Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H; Jo, Brian; Gao, Chuan; McDowell, Ian C; Engelhardt, Barbara E; Battle, Alexis

2017-11-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. © 2017 Saha et al.; Published by Cold Spring Harbor Laboratory Press.

Severe acute respiratory syndrome (SARS) S protein production in plants: Development of recombinant vaccine

PubMed Central

Pogrebnyak, Natalia; Golovkin, Maxim; Andrianov, Vyacheslav; Spitsin, Sergei; Smirnov, Yuriy; Egolf, Richard; Koprowski, Hilary

2005-01-01

In view of a recent spread of severe acute respiratory syndrome (SARS), there is a high demand for production of a vaccine to prevent this disease. Recent studies indicate that SARS-coronavirus (CoV) spike protein (S protein) and its truncated fragments are considered the best candidates for generation of the recombinant vaccine. Toward the development of a safe, effective, and inexpensive vaccine candidate, we have expressed the N-terminal fragment of SARS-CoV S protein (S1) in tomato and low-nicotine tobacco plants. Incorporation of the S1 fragment into plant genomes as well as its transcription was confirmed by PCR and RT-PCR analyses. High levels of expression of recombinant S1 protein were observed in several transgenic lines by Western blot analysis using specific antibodies. Plant-derived antigen was evaluated to induce the systemic and mucosal immune responses in mice. Mice showed significantly increased levels of SARS-CoV-specific IgA after oral ingestion of tomato fruits expressing S1 protein. Sera of mice parenterally primed with tobacco-derived S1 protein revealed the presence of SARS-CoV-specific IgG as detected by Western blot and ELISA analysis. PMID:15956182

Severe acute respiratory syndrome (SARS) S protein production in plants: development of recombinant vaccine.

PubMed

Pogrebnyak, Natalia; Golovkin, Maxim; Andrianov, Vyacheslav; Spitsin, Sergei; Smirnov, Yuriy; Egolf, Richard; Koprowski, Hilary

2005-06-21

In view of a recent spread of severe acute respiratory syndrome (SARS), there is a high demand for production of a vaccine to prevent this disease. Recent studies indicate that SARS-coronavirus (CoV) spike protein (S protein) and its truncated fragments are considered the best candidates for generation of the recombinant vaccine. Toward the development of a safe, effective, and inexpensive vaccine candidate, we have expressed the N-terminal fragment of SARS-CoV S protein (S1) in tomato and low-nicotine tobacco plants. Incorporation of the S1 fragment into plant genomes as well as its transcription was confirmed by PCR and RT-PCR analyses. High levels of expression of recombinant S1 protein were observed in several transgenic lines by Western blot analysis using specific antibodies. Plant-derived antigen was evaluated to induce the systemic and mucosal immune responses in mice. Mice showed significantly increased levels of SARS-CoV-specific IgA after oral ingestion of tomato fruits expressing S1 protein. Sera of mice parenterally primed with tobacco-derived S1 protein revealed the presence of SARS-CoV-specific IgG as detected by Western blot and ELISA analysis.

Co-regulation analysis of co-expressed modules under cold and pathogen stress conditions in tomato.

PubMed

Abedini, Davar; Rashidi Monfared, Sajad

2018-06-01

A primary mechanism for controlling the development of multicellular organisms is transcriptional regulation, which carried out by transcription factors (TFs) that recognize and bind to their binding sites on promoter region. The distance from translation start site, order, orientation, and spacing between cis elements are key factors in the concentration of active nuclear TFs and transcriptional regulation of target genes. In this study, overrepresented motifs in cold and pathogenesis responsive genes were scanned via Gibbs sampling method, this method is based on detection of overrepresented motifs by means of a stochastic optimization strategy that searches for all possible sets of short DNA segments. Then, identified motifs were checked by TRANSFAC, PLACE and Soft Berry databases in order to identify putative TFs which, interact to the motifs. Several cis/trans regulatory elements were found using these databases. Moreover, cross-talk between cold and pathogenesis responsive genes were confirmed. Statistical analysis was used to determine distribution of identified motifs on promoter region. In addition, co-regulation analysis results, illustrated genes in pathogenesis responsive module are divided into two main groups. Also, promoter region was crunched to six subareas in order to draw the pattern of distribution of motifs in promoter subareas. The result showed the majority of motifs are concentrated on 700 nucleotides upstream of the translational start site (ATG). In contrast, this result isn't true in another group. In other words, there was no difference between total and compartmentalized regions in cold responsive genes.

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

PubMed

Ray, Sumanta; Hossain, Sk Md Mosaddek; Khatun, Lutfunnesa; Mukhopadhyay, Anirban

2017-12-20

Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

PubMed Central

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2018-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications. PMID:29375311

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

PubMed

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2017-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications.

ModuleMiner - improved computational detection of cis-regulatory modules: are there different modes of gene regulation in embryonic development and adult tissues?

PubMed Central

Van Loo, Peter; Aerts, Stein; Thienpont, Bernard; De Moor, Bart; Moreau, Yves; Marynen, Peter

2008-01-01

We present ModuleMiner, a novel algorithm for computationally detecting cis-regulatory modules (CRMs) in a set of co-expressed genes. ModuleMiner outperforms other methods for CRM detection on benchmark data, and successfully detects CRMs in tissue-specific microarray clusters and in embryonic development gene sets. Interestingly, CRM predictions for differentiated tissues exhibit strong enrichment close to the transcription start site, whereas CRM predictions for embryonic development gene sets are depleted in this region. PMID:18394174

Correlation between clinical severity and different non-invasive measurements of carbon monoxide concentration: A population study

PubMed Central

Desseaux, Kristell; Chevret, Sylvie

2017-01-01

Objectives Carbon monoxide (CO) poisoning is a major concern in industrialized countries. Each year, thousands of victims, resulting in approximately 100 fatalities, are encountered in France. The diagnosis of CO poisoning is challenging; while carboxyhemoglobin (COHb) may be useful, it is a weak indicator of the severity of CO poisoning. This weak indicator may be a result of the delay between poisoning occurrence and the blood assay. Two apparatuses, CO oximeters and exhaled CO analyzers, now permit COHb to be determined outside hospitals. Our hypothesis is that these instruments allow the early measurement of COHb concentrations, which are more correlated with the severity of poisoning, expressed using the poisoning severity score (PSS). Design In an observational and retrospective cohort study, the distribution of COHb measurements obtained by CO oximetry or by exhaled CO analyzers was compared between groups of severity expressed using the PSS. Setting Data were collected in the Paris area from January 2006 to December 2010 by the French Surveillance System of CO poisoning. Participants All patients with CO poisoning reported to the French Surveillance System of CO poisoning. Results There was a significant difference in the COHb values obtained by CO oximetry between groups stratified according to PSS (p<0.0001). A significant difference in the values of exhaled CO was also observed between PSS groups (p = 0.006), although the relationship was not linear. Conclusions The COHb concentrations measured using CO oximetry, but not those measured using exhaled CO analyzers, were well correlated with the severity of CO poisoning. PMID:28350859

Long-Range Chromosome Interactions Mediated by Cohesin Shape Circadian Gene Expression

PubMed Central

Xu, Yichi; Guo, Weimin; Li, Ping; Zhang, Yan; Zhao, Meng; Fan, Zenghua; Zhao, Zhihu; Yan, Jun

2016-01-01

Mammalian circadian rhythm is established by the negative feedback loops consisting of a set of clock genes, which lead to the circadian expression of thousands of downstream genes in vivo. As genome-wide transcription is organized under the high-order chromosome structure, it is largely uncharted how circadian gene expression is influenced by chromosome architecture. We focus on the function of chromatin structure proteins cohesin as well as CTCF (CCCTC-binding factor) in circadian rhythm. Using circular chromosome conformation capture sequencing, we systematically examined the interacting loci of a Bmal1-bound super-enhancer upstream of a clock gene Nr1d1 in mouse liver. These interactions are largely stable in the circadian cycle and cohesin binding sites are enriched in the interactome. Global analysis showed that cohesin-CTCF co-binding sites tend to insulate the phases of circadian oscillating genes while cohesin-non-CTCF sites are associated with high circadian rhythmicity of transcription. A model integrating the effects of cohesin and CTCF markedly improved the mechanistic understanding of circadian gene expression. Further experiments in cohesin knockout cells demonstrated that cohesin is required at least in part for driving the circadian gene expression by facilitating the enhancer-promoter looping. This study provided a novel insight into the relationship between circadian transcriptome and the high-order chromosome structure. PMID:27135601

Transcriptional regulation of brain gene expression in response to a territorial intrusion

PubMed Central

Sanogo, Yibayiri O.; Band, Mark; Blatti, Charles; Sinha, Saurabh; Bell, Alison M.

2012-01-01

Aggressive behaviour associated with territorial defence is widespread and has fitness consequences. However, excess aggression can interfere with other important biological functions such as immunity and energy homeostasis. How the expression of complex behaviours such as aggression is regulated in the brain has long intrigued ethologists, but has only recently become amenable for molecular dissection in non-model organisms. We investigated the transcriptomic response to territorial intrusion in four brain regions in breeding male threespined sticklebacks using expression microarrays and quantitative polymerase chain reaction (qPCR). Each region of the brain had a distinct genomic response to a territorial challenge. We identified a set of genes that were upregulated in the diencephalon and downregulated in the cerebellum and the brain stem. Cis-regulatory network analysis suggested transcription factors that regulated or co-regulated genes that were consistently regulated in all brain regions and others that regulated gene expression in opposing directions across brain regions. Our results support the hypothesis that territorial animals respond to social challenges via transcriptional regulation of genes in different brain regions. Finally, we found a remarkably close association between gene expression and aggressive behaviour at the individual level. This study sheds light on the molecular mechanisms in the brain that underlie the response to social challenges. PMID:23097509

A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

PubMed Central

Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

2009-01-01

Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

Progesterone-dependent Regulation of Endometrial Cannabinoid Receptor Type 1 (CB1-R) Expression is Disrupted in Women with Endometriosis and in Isolated Stromal Cells Exposed to TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin)

PubMed Central

Resuehr, David; Glore, Dana R.; Taylor, Hugh S.; Bruner-Tran, Kaylon L.; Osteen, Kevin G.

2012-01-01

Objective To examine the differentiation-related expression of CB1-R mRNA and protein in endometrial tissue obtained from women with and without endometriosis and to determine the impact of acute TCDD exposure on CB1-R gene expression in isolated endometrial stromal cells. Design Laboratory-based study Setting University-affiliated medical center Patients Women with and without endometriosis undergoing volunteer endometrial biopsies after informed consent. Interventions None Main Outcome Measures Analysis of in vivo CB1-R mRNA and protein expression in human endometrial tissues and mRNA expression in isolated stromal cells following exposure to TCDD or a progesterone receptor antagonist (Onapristone). Results CB1-R mRNA and protein expression was highest during the progesterone-dominated secretory phase in control women, while expression was minimal in endometrial tissues acquired from women with endometriosis, regardless of the cycle phase. Although progesterone was found to induce CB1-R mRNA expression in endometrial stromal cells from control donors, steroid-induced expression of this gene was inhibited by co-treatment with either TCDD or Onapristone. Conclusions Our studies reveal a role for the anti-inflammatory actions of progesterone in regulating endometrial cannabinoid signaling, which is disrupted in women with endometriosis. Significantly, our studies demonstrate, for the first time, that acute TCDD exposure disrupts cannabinoid signaling in the human endometrium. PMID:22789143

Genomic Characterization of a Newly Discovered Coronavirus Associated with Acute Respiratory Distress Syndrome in Humans

PubMed Central

van Boheemen, Sander; de Graaf, Miranda; Lauber, Chris; Bestebroer, Theo M.; Raj, V. Stalin; Zaki, Ali Moh; Osterhaus, Albert D. M. E.; Haagmans, Bart L.; Gorbalenya, Alexander E.; Snijder, Eric J.; Fouchier, Ron A. M.

2012-01-01

ABSTRACT A novel human coronavirus (HCoV-EMC/2012) was isolated from a man with acute pneumonia and renal failure in June 2012. This report describes the complete genome sequence, genome organization, and expression strategy of HCoV-EMC/2012 and its relation with known coronaviruses. The genome contains 30,119 nucleotides and contains at least 10 predicted open reading frames, 9 of which are predicted to be expressed from a nested set of seven subgenomic mRNAs. Phylogenetic analysis of the replicase gene of coronaviruses with completely sequenced genomes showed that HCoV-EMC/2012 is most closely related to Tylonycteris bat coronavirus HKU4 (BtCoV-HKU4) and Pipistrellus bat coronavirus HKU5 (BtCoV-HKU5), which prototype two species in lineage C of the genus Betacoronavirus. In accordance with the guidelines of the International Committee on Taxonomy of Viruses, and in view of the 75% and 77% amino acid sequence identity in 7 conserved replicase domains with BtCoV-HKU4 and BtCoV-HKU5, respectively, we propose that HCoV-EMC/2012 prototypes a novel species in the genus Betacoronavirus. HCoV-EMC/2012 may be most closely related to a coronavirus detected in Pipistrellus pipistrellus in The Netherlands, but because only a short sequence from the most conserved part of the RNA-dependent RNA polymerase-encoding region of the genome was reported for this bat virus, its genetic distance from HCoV-EMC remains uncertain. HCoV-EMC/2012 is the sixth coronavirus known to infect humans and the first human virus within betacoronavirus lineage C. PMID:23170002

3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA.

PubMed

Pourbasheer, Eslam; Aalizadeh, Reza; Ebadi, Amin; Ganjali, Mohammad Reza

2015-01-01

Three-dimensional quantitative structure-activity relationship was developed for the series of compounds as malonyl-CoA decarboxylase antagonists (MCD) using the CoMFA and CoMSIA methods. The statistical parameters for CoMFA (q(2)=0.558, r(2)=0.841) and CoMSIA (q(2)= 0.615, r(2) = 0.870) models were derived based on 38 compounds as training set in the basis of the selected alignment. The external predictive abilities of the built models were evaluated by using the test set of nine compounds. From obtained results, the CoMSIA method was found to have highly predictive capability in comparison with CoMFA method. Based on the given results by CoMSIA and CoMFA contour maps, some features that can enhance the activity of compounds as MCD antagonists were introduced and used to design new compounds with better inhibition activity.

Analysis of Bos taurus and Sus scrofa X and Y chromosome transcriptome highlights reproductive driver genes

PubMed Central

Khan, Faheem Ahmed; Liu, Hui; Zhou, Hao; Wang, Kai; Qamar, Muhammad Tahir Ul; Pandupuspitasari, Nuruliarizki Shinta; Shujun, Zhang

2017-01-01

The biology of sperm, its capability of fertilizing an egg and its role in sex ratio are the major biological questions in reproductive biology. To answer these question we integrated X and Y chromosome transcriptome across different species: Bos taurus and Sus scrofa and identified reproductive driver genes based on Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. Our strategy resulted in 11007 and 10445 unique genes consisting of 9 and 11 reproductive modules in Bos taurus and Sus scrofa, respectively. The consensus module calculation yields an overall 167 overlapped genes which were mapped to 846 DEGs in Bos taurus to finally get a list of 67 dual feature genes. We develop gene co-expression network of selected 67 genes that consists of 58 nodes (27 down-regulated and 31 up-regulated genes) enriched to 66 GO biological process (BP) including 6 GO annotations related to reproduction and two KEGG pathways. Moreover, we searched significantly related TF (ISRE, AP1FJ, RP58, CREL) and miRNAs (bta-miR-181a, bta-miR-17-5p, bta-miR-146b, bta-miR-146a) which targeted the genes in co-expression network. In addition we performed genetic analysis including phylogenetic, functional domain identification, epigenetic modifications, mutation analysis of the most important reproductive driver genes PRM1, PPP2R2B and PAFAH1B1 and finally performed a protein docking analysis to visualize their therapeutic and gene expression regulation ability. PMID:28903352

DNA and protein co-administration induces tolerogenic dendritic cells through DC-SIGN mediated negative signals.

PubMed

Li, Jinyao; Geng, Shuang; Liu, Xiuping; Liu, Hu; Jin, Huali; Liu, Chang-Gong; Wang, Bin

2013-10-01

We previously demonstrated that DNA and protein co-administration induced differentiation of immature dendritic cells (iDCs) into CD11c(+)CD40(low)IL-10(+) regulatory DCs (DCregs) via the caveolin-1 (Cav-1) -mediated signal pathway. Here, we demonstrate that production of IL-10 and the low expression of CD40 play a critical role in the subsequent induction of regulatory T cells (Tregs) by the DCregs. We observed that DNA and protein were co-localized with DC-SIGN in caveolae and early lysosomes in the treated DCs, as indicated by co-localization with Cav-1 and EEA-1 compartment markers. DNA and protein also co-localized with LAMP-2. Gene-array analysis of gene expression showed that more than a thousand genes were significantly changed by the DC co-treatment with DNA + protein compared with controls. Notably, the level of DC-SIGN expression was dramatically upregulated in pOVA + OVA co-treated DCs. The expression levels of Rho and Rho GNEF, the down-stream molecules of DC-SIGN mediated signal pathway, were also greatly upregulated. Further, the level of TLR9, the traditional DNA receptor, was significantly downregulated. These results suggest that DC-SIGN as the potential receptor for DNA and protein might trigger the negative pathway to contribute the induction of DCreg combining with Cav-1 mediated negative signal pathway.

DNA and protein co-administration induces tolerogenic dendritic cells through DC-SIGN mediated negative signals

PubMed Central

Li, Jinyao; Geng, Shuang; Liu, Xiuping; Liu, Hu; Jin, Huali; Liu, Chang-Gong; Wang, Bin

2013-01-01

We previously demonstrated that DNA and protein co-administration induced differentiation of immature dendritic cells (iDCs) into CD11c+CD40lowIL-10+ regulatory DCs (DCregs) via the caveolin-1 (Cav-1) -mediated signal pathway. Here, we demonstrate that production of IL-10 and the low expression of CD40 play a critical role in the subsequent induction of regulatory T cells (Tregs) by the DCregs. We observed that DNA and protein were co-localized with DC-SIGN in caveolae and early lysosomes in the treated DCs, as indicated by co-localization with Cav-1 and EEA-1 compartment markers. DNA and protein also co-localized with LAMP-2. Gene-array analysis of gene expression showed that more than a thousand genes were significantly changed by the DC co-treatment with DNA + protein compared with controls. Notably, the level of DC-SIGN expression was dramatically upregulated in pOVA + OVA co-treated DCs. The expression levels of Rho and Rho GNEF, the down-stream molecules of DC-SIGN mediated signal pathway, were also greatly upregulated. Further, the level of TLR9, the traditional DNA receptor, was significantly downregulated. These results suggest that DC-SIGN as the potential receptor for DNA and protein might trigger the negative pathway to contribute the induction of DCreg combining with Cav-1 mediated negative signal pathway. PMID:24051433

Repeated Gestational Exposure of Mice to Chlorpyrifos Oxon Is Associated with Paraoxonase 1 (PON1) Modulated Effects in Maternal and Fetal Tissues

PubMed Central

Co, Aila L.; Hay, Ariel M.; MacDonald, James W.; Bammler, Theo K.; Farin, Federico M.; Costa, Lucio G.; Furlong, Clement E.

2014-01-01

Chlorpyrifos oxon (CPO), the toxic metabolite of the organophosphorus (OP) insecticide chlorpyrifos, causes developmental neurotoxicity in humans and rodents. CPO is hydrolyzed by paraoxonase-1 (PON1), with protection determined by PON1 levels and the human Q192R polymorphism. To examine how the Q192R polymorphism influences fetal toxicity associated with gestational CPO exposure, we measured enzyme inhibition and fetal-brain gene expression in wild-type (PON1+/+), PON1-knockout (PON1−/−), and tgHuPON1R192 and tgHuPON1Q192 transgenic mice. Pregnant mice exposed dermally to 0, 0.50, 0.75, or 0.85 mg/kg/d CPO from gestational day (GD) 6 through 17 were sacrificed on GD18. Biomarkers of CPO exposure inhibited in maternal tissues included brain acetylcholinesterase (AChE), red blood cell acylpeptide hydrolase (APH), and plasma butyrylcholinesterase (BChE) and carboxylesterase (CES). Fetal plasma BChE was inhibited in PON1−/− and tgHuPON1Q192, but not PON1+/+ or tgHuPON1R192 mice. Fetal brain AChE and plasma CES were inhibited in PON1−/− mice, but not in other genotypes. Weighted gene co-expression network analysis identified five gene modules based on clustering of the correlations among their fetal-brain expression values, allowing for correlation of module membership with the phenotypic data on enzyme inhibition. One module that correlated highly with maternal brain AChE activity had a large representation of homeobox genes. Gene set enrichment analysis revealed multiple gene sets affected by gestational CPO exposure in tgHuPON1Q192 but not tgHuPON1R192 mice, including gene sets involved in protein export, lipid metabolism, and neurotransmission. These data indicate that maternal PON1 status modulates the effects of repeated gestational CPO exposure on fetal-brain gene expression and on inhibition of both maternal and fetal biomarker enzymes. PMID:25070982

Repeated exposure to Lutzomyia intermedia sand fly saliva induces local expression of interferon-inducible genes both at the site of injection in mice and in human blood.

PubMed

Weinkopff, Tiffany; de Oliveira, Camila I; de Carvalho, Augusto M; Hauyon-La Torre, Yazmin; Muniz, Aline C; Miranda, Jose Carlos; Barral, Aldina; Tacchini-Cottier, Fabienne

2014-01-01

During a blood meal, Lutzomyia intermedia sand flies transmit Leishmania braziliensis, a parasite causing tegumentary leishmaniasis. In experimental leishmaniasis, pre-exposure to saliva of most blood-feeding sand flies results in parasite establishment in absence of any skin damages in mice challenged with dermotropic Leishmania species together with saliva. In contrast, pre-immunization with Lu. intermedia salivary gland sonicate (SGS) results in enhanced skin inflammatory exacerbation upon co-inoculation of Lu. intermedia SGS and L. braziliensis. These data highlight potential unique features of both L. braziliensis and Lu. intermedia. In this study, we investigated the genes modulated by Lu. intermedia SGS immunization to understand their potential impact on the subsequent cutaneous immune response following inoculation of both SGS and L. braziliensis. The cellular recruitment and global gene expression profile was analyzed in mice repeatedly inoculated or not with Lu. intermedia. Microarray gene analysis revealed the upregulation of a distinct set of IFN-inducible genes, an immune signature not seen to the same extent in control animals. Of note this INF-inducible gene set was not induced in SGS pre-immunized mice subsequently co-inoculated with SGS and L. braziliensis. These data suggest the parasite prevented the upregulation of this Lu. intermedia saliva-related immune signature. The presence of these IFN-inducible genes was further analyzed in peripheral blood mononuclear cells (PBMCs) sampled from uninfected human individuals living in a L. braziliensis-endemic region of Brazil thus regularly exposed to Lu. intermedia bites. PBMCs were cultured in presence or absence of Lu. intermedia SGS. Using qRT-PCR we established that the IFN-inducible genes induced in the skin of SGS pre-immunized mice, were also upregulated by SGS in PBMCs from human individuals regularly exposed to Lu. intermedia bites, but not in PBMCs of control subjects. These data demonstrate that repeated exposure to Lu. intermedia SGS induces the expression of potentially host-protective IFN-inducible genes.

Identification of aberrantly expressed long non-coding RNAs in stomach adenocarcinoma.

PubMed

Gu, Jianbin; Li, Yong; Fan, Liqiao; Zhao, Qun; Tan, Bibo; Hua, Kelei; Wu, Guobin

2017-07-25

Stomach adenocarcinoma (STAD) is a common malignancy worldwide. This study aimed to identify the aberrantly expressed long non-coding RNAs (lncRNAs) in STAD. Total of 74 DElncRNAs and 449 DEmRNAs were identified in STAD compared with paired non-tumor tissues. The DElncRNA/DEmRNA co-expression network was constructed, which covered 519 nodes and 2993 edges. The qRT-PCR validation results of DElncRNAs were consistent with our bioinformatics analysis based on RNA-sequencing. The DEmRNAs co-expressed with DElncRNAs were significantly enriched in gastric acid secretion, complement and coagulation cascades, pancreatic secretion, cytokine-cytokine receptor interaction and Jak-STAT signaling pathway. The expression levels of the nine candidate DElncRNAs in TCGA database were compatible with our RNA-sequencing. FEZF1-AS1, HOTAIR and LINC01234 had the potential diagnosis value for STAD. The lncRNA and mRNA expression profile of 3 STAD tissues and 3 matched adjacent non-tumor tissues was obtained through high-throughput RNA-sequencing. Differentially expressed lncRNAs/mRNAs (DElncRNAs/DEmRNAs) were identified in STAD. DElncRNA/DEmRNA co-expression network construction, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to predict the biological functions of DElncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was subjected to validate the expression levels of DEmRNAs and DElncRNAs. Moreover, the expression of DElncRNAs was validated through The Cancer Genome Atlas (TCGA) database. The diagnosis value of candidate DElncRNAs was accessed by receiver operating characteristic (ROC) analysis. Our work might provide useful information for exploring the tumorigenesis mechanism of STAD and pave the road for identification of diagnostic biomarkers in STAD.

Biochemical and Expression Analyses of the Rice Cinnamoyl-CoA Reductase Gene Family.

PubMed

Park, Hye Lin; Bhoo, Seong Hee; Kwon, Mi; Lee, Sang-Won; Cho, Man-Ho

2017-01-01

Cinnamoyl-CoA reductase (CCR) is the first committed enzyme in the monolignol pathway for lignin biosynthesis and catalyzes the conversion of hydroxycinnamoyl-CoAs into hydroxycinnamaldehydes. In the rice genome, 33 genes are annotated as CCR and CCR-like genes, collectively called OsCCR s. To elucidate the functions of OsCCR s, their phylogenetic relationships, expression patterns at the transcription levels and biochemical characteristics were thoroughly analyzed. Of the 33 OsCCR s, 24 of them encoded polypeptides of lengths similar to those of previously identified plant CCRs. The other nine OsCCRs had much shorter peptide lengths. Phylogenetic tree and sequence similarities suggested OsCCR4, 5, 17, 18, 19, 20, and 21 as likely candidates for functional CCRs in rice. To elucidate biochemical functions, OsCCR1, 5, 17, 19, 20, 21, and 26 were heterologously expressed in Escherichia coli and the resulting recombinant OsCCRs were purified to apparent homogeneity. Activity assays of the recombinant OsCCRs with hydroxycinnamoyl-CoAs revealed that OsCCR17, 19, 20, and 21 were biochemically active CCRs, in which the NAD(P)-binding and NADP-specificity motifs as well as the CCR signature motif were fully conserved. The kinetic parameters of enzyme reactions revealed that feruloyl-CoA, a precursor for the guaiacyl (G)-unit of lignin, is the most preferred substrate of OsCCR20 and 21. This result is consistent with a high content (about 70%) of G-units in rice lignins. Phylogenetic analysis revealed that OsCCR19 and 20 were grouped with other plant CCRs involved in developmental lignification, whereas OsCCR17 and 21 were closely related to stress-responsible CCRs identified from other plant species. In agreement with the phylogenetic analysis, expression analysis demonstrated that OsCCR20 was constitutively expressed throughout the developmental stages of rice, showing particularly high expression levels in actively lignifying tissues, such as roots and stems. These results suggest that OsCCR20 is primarily involved in developmental deposition of lignins in secondary cell walls. As expected, the expressions of OsCCR17 and 21 were induced in response to biotic and abiotic stresses, such as Magnaporthe grisea and Xanthomonas oryzae pv. oryzae ( Xoo ) infections, UV-irradiation and high salinity, suggesting that these genes play a role in defense-related processes in rice.

Chronic Low-Grade Inflammation in Childhood Obesity Is Associated with Decreased IL-10 Expression by Monocyte Subsets.

PubMed

Mattos, Rafael T; Medeiros, Nayara I; Menezes, Carlos A; Fares, Rafaelle C G; Franco, Eliza P; Dutra, Walderez O; Rios-Santos, Fabrício; Correa-Oliveira, Rodrigo; Gomes, Juliana A S

2016-01-01

Chronic low-grade inflammation is related to the development of comorbidities and poor prognosis in obesity. Monocytes are main sources of cytokines and play a pivotal role in inflammation. We evaluated monocyte frequency, phenotype and cytokine profile of monocyte subsets, to determine their association with the pathogenesis of childhood obesity. Children with obesity were evaluated for biochemical and anthropometric parameters. Monocyte subsets were characterized by flow cytometry, considering cytokine production and activation/recognition molecules. Correlation analysis between clinical parameters and immunological data delineated the monocytes contribution for low-grade inflammation. We observed a higher frequency of non-classical monocytes in the childhood obesity group (CO) than normal-weight group (NW). All subsets displayed higher TLR4 expression in CO, but their recognition and antigen presentation functions seem to be diminished due to lower expression of CD40, CD80/86 and HLA-DR. All subsets showed a lower expression of IL-10 in CO and correlation analyses showed changes in IL-10 expression profile. The lower expression of IL-10 may be decisive for the maintenance of the low-grade inflammation status in CO, especially for alterations in non-classical monocytes profile. These cells may contribute to supporting inflammation and loss of regulation in the immune response of children with obesity.

Chronic Low-Grade Inflammation in Childhood Obesity Is Associated with Decreased IL-10 Expression by Monocyte Subsets

PubMed Central

Mattos, Rafael T.; Medeiros, Nayara I.; Menezes, Carlos A.; Fares, Rafaelle C. G.; Franco, Eliza P.; Dutra, Walderez O.; Rios-Santos, Fabrício; Correa-Oliveira, Rodrigo; Gomes, Juliana A. S.

2016-01-01

Chronic low-grade inflammation is related to the development of comorbidities and poor prognosis in obesity. Monocytes are main sources of cytokines and play a pivotal role in inflammation. We evaluated monocyte frequency, phenotype and cytokine profile of monocyte subsets, to determine their association with the pathogenesis of childhood obesity. Children with obesity were evaluated for biochemical and anthropometric parameters. Monocyte subsets were characterized by flow cytometry, considering cytokine production and activation/recognition molecules. Correlation analysis between clinical parameters and immunological data delineated the monocytes contribution for low-grade inflammation. We observed a higher frequency of non-classical monocytes in the childhood obesity group (CO) than normal-weight group (NW). All subsets displayed higher TLR4 expression in CO, but their recognition and antigen presentation functions seem to be diminished due to lower expression of CD40, CD80/86 and HLA-DR. All subsets showed a lower expression of IL-10 in CO and correlation analyses showed changes in IL-10 expression profile. The lower expression of IL-10 may be decisive for the maintenance of the low-grade inflammation status in CO, especially for alterations in non-classical monocytes profile. These cells may contribute to supporting inflammation and loss of regulation in the immune response of children with obesity. PMID:27977792

PAPST, a User Friendly and Powerful Java Platform for ChIP-Seq Peak Co-Localization Analysis and Beyond.

PubMed

Bible, Paul W; Kanno, Yuka; Wei, Lai; Brooks, Stephen R; O'Shea, John J; Morasso, Maria I; Loganantharaj, Rasiah; Sun, Hong-Wei

2015-01-01

Comparative co-localization analysis of transcription factors (TFs) and epigenetic marks (EMs) in specific biological contexts is one of the most critical areas of ChIP-Seq data analysis beyond peak calling. Yet there is a significant lack of user-friendly and powerful tools geared towards co-localization analysis based exploratory research. Most tools currently used for co-localization analysis are command line only and require extensive installation procedures and Linux expertise. Online tools partially address the usability issues of command line tools, but slow response times and few customization features make them unsuitable for rapid data-driven interactive exploratory research. We have developed PAPST: Peak Assignment and Profile Search Tool, a user-friendly yet powerful platform with a unique design, which integrates both gene-centric and peak-centric co-localization analysis into a single package. Most of PAPST's functions can be completed in less than five seconds, allowing quick cycles of data-driven hypothesis generation and testing. With PAPST, a researcher with or without computational expertise can perform sophisticated co-localization pattern analysis of multiple TFs and EMs, either against all known genes or a set of genomic regions obtained from public repositories or prior analysis. PAPST is a versatile, efficient, and customizable tool for genome-wide data-driven exploratory research. Creatively used, PAPST can be quickly applied to any genomic data analysis that involves a comparison of two or more sets of genomic coordinate intervals, making it a powerful tool for a wide range of exploratory genomic research. We first present PAPST's general purpose features then apply it to several public ChIP-Seq data sets to demonstrate its rapid execution and potential for cutting-edge research with a case study in enhancer analysis. To our knowledge, PAPST is the first software of its kind to provide efficient and sophisticated post peak-calling ChIP-Seq data analysis as an easy-to-use interactive application. PAPST is available at https://github.com/paulbible/papst and is a public domain work.

PAPST, a User Friendly and Powerful Java Platform for ChIP-Seq Peak Co-Localization Analysis and Beyond

PubMed Central

Bible, Paul W.; Kanno, Yuka; Wei, Lai; Brooks, Stephen R.; O’Shea, John J.; Morasso, Maria I.; Loganantharaj, Rasiah; Sun, Hong-Wei

2015-01-01

Comparative co-localization analysis of transcription factors (TFs) and epigenetic marks (EMs) in specific biological contexts is one of the most critical areas of ChIP-Seq data analysis beyond peak calling. Yet there is a significant lack of user-friendly and powerful tools geared towards co-localization analysis based exploratory research. Most tools currently used for co-localization analysis are command line only and require extensive installation procedures and Linux expertise. Online tools partially address the usability issues of command line tools, but slow response times and few customization features make them unsuitable for rapid data-driven interactive exploratory research. We have developed PAPST: Peak Assignment and Profile Search Tool, a user-friendly yet powerful platform with a unique design, which integrates both gene-centric and peak-centric co-localization analysis into a single package. Most of PAPST’s functions can be completed in less than five seconds, allowing quick cycles of data-driven hypothesis generation and testing. With PAPST, a researcher with or without computational expertise can perform sophisticated co-localization pattern analysis of multiple TFs and EMs, either against all known genes or a set of genomic regions obtained from public repositories or prior analysis. PAPST is a versatile, efficient, and customizable tool for genome-wide data-driven exploratory research. Creatively used, PAPST can be quickly applied to any genomic data analysis that involves a comparison of two or more sets of genomic coordinate intervals, making it a powerful tool for a wide range of exploratory genomic research. We first present PAPST’s general purpose features then apply it to several public ChIP-Seq data sets to demonstrate its rapid execution and potential for cutting-edge research with a case study in enhancer analysis. To our knowledge, PAPST is the first software of its kind to provide efficient and sophisticated post peak-calling ChIP-Seq data analysis as an easy-to-use interactive application. PAPST is available at https://github.com/paulbible/papst and is a public domain work. PMID:25970601

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

PubMed

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

PubMed

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large-scale datasets. Software and data sets are available at http://www.sfu.ca/~ester/software/DECOB.zip.

Genome-wide DNA methylation analysis in lung fibroblasts co-cultured with silica-exposed alveolar macrophages.

PubMed

Li, Juan; Yao, Wu; Zhang, Lin; Bao, Lei; Chen, Huiting; Wang, Di; Yue, Zhongzheng; Li, Yiping; Zhang, Miao; Hao, Changfu

2017-05-12

Exposure to crystalline silica is considered to increase the risk of lung fibrosis. The primary effector cell, the myofibroblast, plays an important role in the deposition of extracellular matrix (ECM). DNA methylation change is considered to have a potential effect on myofibroblast differentiation. Therefore, the present study was designed to investigate the genome-wide DNA methylation profiles of lung fibroblasts co-cultured with alveolar macrophages exposed to crystalline silica in vitro. AM/fibroblast co-culture system was established. CCK8 was used to assess the toxicity of AMs. mRNA and protein expression of collagen I, α-SMA, MAPK9 and TGF-β1 of fibroblasts after AMs exposed to 100 μg /ml SiO 2 for 0-, 24-, or 48 h were determined by means of quantitative real-time PCR, immunoblotting and immunohistochemistry. Genomic DNA of fibroblasts was isolated using MeDIP-Seq to sequence. R software, GO, KEGG and Cytoscape were used to analyze the data. SiO 2 exposure increased the expression of collagen I and α-SMA in fibroblasts in co-culture system. Analysis of fibroblast methylome identified extensive methylation changes involved in several signaling pathways, such as the MAPK signaling pathway and metabolic pathways. Several candidates, including Tgfb1 and Mapk9, are hubs who can connect the gene clusters. MAPK9 mRNA expression was significantly higher in fibroblast exposed to SiO 2 in co-culture system for 48 h. MAPK9 protein expression was increased at both 24-h and 48-h treatment groups. TGF-β1 mRNA expression of fibroblast has a time-dependent manner, but we didn't observe the TGF-β1 protein expression. Tgfb1 and Mapk9 are helpful to explore the mechanism of myofibroblast differentiation. The genome-wide DNA methylation profiles of fibroblasts in this experimental silicosis model will be useful for future studies on epigenetic gene regulation during myofibroblast differentiation.

Coronavirus Infections in the Central Nervous System and Respiratory Tract Show Distinct Features in Hospitalized Children.

PubMed

Li, Yuanyuan; Li, Haipeng; Fan, Ruyan; Wen, Bo; Zhang, Jian; Cao, Xiaoying; Wang, Chengwu; Song, Zhanyi; Li, Shuochi; Li, Xiaojie; Lv, Xinjun; Qu, Xiaowang; Huang, Renbin; Liu, Wenpei

2016-01-01

Coronavirus (CoV) infections induce respiratory tract illnesses and central nervous system (CNS) diseases. We aimed to explore the cytokine expression profiles in hospitalized children with CoV-CNS and CoV-respiratory tract infections. A total of 183 and 236 hospitalized children with acute encephalitis-like syndrome and respiratory tract infection, respectively, were screened for anti-CoV IgM antibodies. The expression profiles of multiple cytokines were determined in CoV-positive patients. Anti-CoV IgM antibodies were detected in 22/183 (12.02%) and 26/236 (11.02%) patients with acute encephalitis-like syndrome and respiratory tract infection, respectively. Cytokine analysis revealed that the level of serum granulocyte colony-stimulating factor (G-CSF) was significantly higher in both CoV-CNS and CoV-respiratory tract infection compared with healthy controls. Additionally, the serum level of granulocyte macrophage colony-stimulating factor (GM-CSF) was significantly higher in CoV-CNS infection than in CoV-respiratory tract infection. In patients with CoV-CNS infection, the levels of IL-6, IL-8, MCP-1, and GM-CSF were significantly higher in their cerebrospinal fluid samples than in matched serum samples. To the best of our knowledge, this is the first report showing a high incidence of CoV infection in hospitalized children, especially with CNS illness. The characteristic cytokine expression profiles in CoV infection indicate the importance of host immune response in disease progression. © 2017 S. Karger AG, Basel.

Carbon dioxide receptor genes in cotton bollworm Helicoverpa armigera

NASA Astrophysics Data System (ADS)

Xu, Wei; Anderson, Alisha

2015-04-01

Carbon dioxide (CO2) is important in insect ecology, eliciting a range of behaviours across different species. Interestingly, the numbers of CO2 gustatory receptors (GRs) vary among insect species. In the model organism Drosophila melanogaster, two GRs (DmelGR21a and DmelGR63a) have been shown to detect CO2. In the butterfly, moth, beetle and mosquito species studied so far, three CO2 GR genes have been identified, while in tsetse flies, four CO2 GR genes have been identified. In other species including honeybees, pea aphids, ants, locusts and wasps, no CO2 GR genes have been identified from the genome. These genomic differences may suggest different mechanisms for CO2 detection exist in different insects but, with the exception of Drosophila and mosquitoes, limited attention has been paid to the CO2 GRs in insects. Here, we cloned three putative CO2 GR genes from the cotton bollworm Helicoverpa armigera and performed phylogenetic and expression analysis. All three H. armigera CO2 GRs (HarmGR1, HarmGR2 and HarmGR3) are specifically expressed in labial palps, the CO2-sensing tissue of this moth. HarmGR3 is significantly activated by NaHCO3 when expressed in insect Sf9 cells but HarmGR1 and HarmGR2 are not. This is the first report characterizing the function of lepidopteran CO2 receptors, which contributes to our general understanding of the molecular mechanisms of insect CO2 gustatory receptors.

Identifying a gene expression signature of cluster headache in blood

PubMed Central

Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

2017-01-01

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

MicroRNA319-regulated TCPs interact with FBHs and PFT1 to activate CO transcription and control flowering time in Arabidopsis.

PubMed

Liu, Jie; Cheng, Xiliu; Liu, Pan; Li, Dayong; Chen, Tao; Gu, Xiaofeng; Sun, Jiaqiang

2017-05-01

The transcription factor CONSTANS (CO) is a central component that promotes Arabidopsis flowering under long-day conditions (LDs). Here, we show that the microRNA319-regulated TEOSINTE BRANCHED/CYCLOIDEA/PCF (TCP) transcription factors promote photoperiodic flowering through binding to the CO promoter and activating its transcription. Meanwhile, these TCPs directly interact with the flowering activators FLOWERING BHLH (FBHs), but not the flowering repressors CYCLING DOF FACTORs (CDFs), to additively activate CO expression. Furthermore, both the TCPs and FBHs physically interact with the flowering time regulator PHYTOCHROME AND FLOWERING TIME 1 (PFT1) to facilitate CO transcription. Our findings provide evidence that a set of transcriptional activators act directly and additively at the CO promoter to promote CO transcription, and establish a molecular mechanism underlying the regulation of photoperiodic flowering time in Arabidopsis.

MicroRNA319-regulated TCPs interact with FBHs and PFT1 to activate CO transcription and control flowering time in Arabidopsis

PubMed Central

Liu, Pan; Li, Dayong; Chen, Tao; Gu, Xiaofeng; Sun, Jiaqiang

2017-01-01

The transcription factor CONSTANS (CO) is a central component that promotes Arabidopsis flowering under long-day conditions (LDs). Here, we show that the microRNA319-regulated TEOSINTE BRANCHED/CYCLOIDEA/PCF (TCP) transcription factors promote photoperiodic flowering through binding to the CO promoter and activating its transcription. Meanwhile, these TCPs directly interact with the flowering activators FLOWERING BHLH (FBHs), but not the flowering repressors CYCLING DOF FACTORs (CDFs), to additively activate CO expression. Furthermore, both the TCPs and FBHs physically interact with the flowering time regulator PHYTOCHROME AND FLOWERING TIME 1 (PFT1) to facilitate CO transcription. Our findings provide evidence that a set of transcriptional activators act directly and additively at the CO promoter to promote CO transcription, and establish a molecular mechanism underlying the regulation of photoperiodic flowering time in Arabidopsis. PMID:28558040

Baghdadite ceramics modulate the cross talk between human adipose stem cells and osteoblasts for bone regeneration.

PubMed

Lu, Zufu; Wang, Guocheng; Roohani-Esfahani, Iman; Dunstan, Colin R; Zreiqat, Hala

2014-03-01

Understanding interactions among the three elements (cells, scaffolds, and bioactive factors) is critical for successful tissue engineering. This study was aimed to investigate how scaffolds would affect osteogenic gene expression in human adipose tissue-derived stem cells (ASCs) or human primary osteoblasts (HOBs), and their cross talk. Either ASCs or HOBs were seeded on Baghdadite (Ca3ZrSi2O9) and hydroxyapatite/tricalcium phosphate (HA/TCP) scaffolds, and osteogenic gene expression was assessed. To further evaluate how substrate affected HOB and ASC cross talk, an indirect co-culture system with semipermeable inserts placed on the culture plate was set up to co-culture ASCs or HOBs, which were grown in monolayer or seeded on Baghdadite or HA/TCP scaffolds, and osteogenic differentiation of the cells was assessed. We found that Baghdadite scaffolds induced a significantly greater increase in RUNX2, osteopontin, bone sialoprotein, and osteocalcin gene expression in HOBs in comparison to HA/TCP scaffolds; Baghdadite scaffolds also significantly induced RUNX2 and osteopontin, but not bone sialoprotein and osteocalcin gene expression in ASCs. In the co-culture system, the HOBs on Baghdadite scaffolds more markedly promoted osteogenic gene expression in ASCs compared to HOBs in monolayer or the HOBs on HA/TCP scaffolds. In addition, the ASCs seeded on Baghdadite scaffolds more markedly promoted osteogenic gene expression in HOBs than did the ASCs on HA/TCP scaffolds. BMP-2 expression in ASCs or HOBs was increased when they were seeded on Baghdadite scaffolds, and adding Noggin into the co-culture medium largely abrogated Baghdadite scaffold-modulated ASC-HOB cross talk. In summary, Baghdadite scaffolds not only promote the osteogenic differentiation of HOBs or ASCs but also modulate the cross talk between ASCs and HOBs, in part via increasing BMP2 expression, thereby promoting their osteogenic differentiation.

Identification, characterization and expression analysis of lineage-specific genes within sweet orange (Citrus sinensis).

PubMed

Xu, Yuantao; Wu, Guizhi; Hao, Baohai; Chen, Lingling; Deng, Xiuxin; Xu, Qiang

2015-11-23

With the availability of rapidly increasing number of genome and transcriptome sequences, lineage-specific genes (LSGs) can be identified and characterized. Like other conserved functional genes, LSGs play important roles in biological evolution and functions. Two set of citrus LSGs, 296 citrus-specific genes (CSGs) and 1039 orphan genes specific to sweet orange, were identified by comparative analysis between the sweet orange genome sequences and 41 genomes and 273 transcriptomes. With the two sets of genes, gene structure and gene expression pattern were investigated. On average, both the CSGs and orphan genes have fewer exons, shorter gene length and higher GC content when compared with those evolutionarily conserved genes (ECs). Expression profiling indicated that most of the LSGs expressed in various tissues of sweet orange and some of them exhibited distinct temporal and spatial expression patterns. Particularly, the orphan genes were preferentially expressed in callus, which is an important pluripotent tissue of citrus. Besides, part of the CSGs and orphan genes expressed responsive to abiotic stress, indicating their potential functions during interaction with environment. This study identified and characterized two sets of LSGs in citrus, dissected their sequence features and expression patterns, and provided valuable clues for future functional analysis of the LSGs in sweet orange.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

PubMed

Contreras-López, Orlando; Moyano, Tomás C; Soto, Daniela C; Gutiérrez, Rodrigo A

2018-01-01

The rapid increase in the availability of transcriptomics data generated by RNA sequencing represents both a challenge and an opportunity for biologists without bioinformatics training. The challenge is handling, integrating, and interpreting these data sets. The opportunity is to use this information to generate testable hypothesis to understand molecular mechanisms controlling gene expression and biological processes (Fig. 1). A successful strategy to generate tractable hypotheses from transcriptomics data has been to build undirected network graphs based on patterns of gene co-expression. Many examples of new hypothesis derived from network analyses can be found in the literature, spanning different organisms including plants and specific fields such as root developmental biology.In order to make the process of constructing a gene co-expression network more accessible to biologists, here we provide step-by-step instructions using published RNA-seq experimental data obtained from a public database. Similar strategies have been used in previous studies to advance root developmental biology. This guide includes basic instructions for the operation of widely used open source platforms such as Bio-Linux, R, and Cytoscape. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be easily adapted to work with RNA-seq data from any organism.

RNA-Seq Reveals Enhanced Sugar Metabolism in Streptococcus mutans Co-cultured with Candida albicans within Mixed-Species Biofilms

PubMed Central

He, Jinzhi; Kim, Dongyeop; Zhou, Xuedong; Ahn, Sang-Joon; Burne, Robert A.; Richards, Vincent P.; Koo, Hyun

2017-01-01

Early childhood caries (ECC), which can lead to rampant tooth-decay that is painful and costly to treat, is one of the most prevalent infectious diseases affecting children worldwide. Previous studies support that interactions between Streptococcus mutans and Candida albicans are associated with the pathogenesis of ECC. The presence of Candida enhances S. mutans growth, fitness and accumulation within biofilms in vitro, although the molecular basis for these behaviors is undefined. Using an established co-cultivation biofilm model and RNA-Seq, we investigated how C. albicans influences the transcriptome of S. mutans. The presence of C. albicans dramatically altered gene expression in S. mutans in the dual-species biofilm, resulting in 393 genes differentially expressed, compared to mono-species biofilms of S. mutans. By Gene Ontology analysis, the majority of up-regulated genes were related to carbohydrate transport and metabolic/catabolic processes. KEGG pathway impact analysis showed elevated pyruvate and galactose metabolism, suggesting that co-cultivation with C. albicans influences carbohydrate utilization by S. mutans. Analysis of metabolites confirmed the increases in carbohydrate metabolism, with elevated amounts of formate in the culture medium of co-cultured biofilms. Moreover, co-cultivation with C. albicans altered transcription of S. mutans signal transduction (comC and ciaRH) genes associated with fitness and virulence. Interestingly, the expression of genes for mutacins (bacteriocins) and CRISPR were down-regulated. Collectively, the data provide a comprehensive insight into S. mutans transcriptomic changes induced by C. albicans, and offer novel insights into how bacterial–fungal interactions may enhance the severity of dental caries. PMID:28642749

TCP4-dependent induction of CONSTANS transcription requires GIGANTEA in photoperiodic flowering in Arabidopsis

PubMed Central

Shim, Jae Sung; Song, Yong Hun; Laboy Cintrón, Dianne; Koyama, Tomotsugu; Ohme-Takagi, Masaru; Pruneda-Paz, Jose L.; Kay, Steve A.; MacCoss, Michael J.

2017-01-01

Photoperiod is one of the most reliable environmental cues for plants to regulate flowering timing. In Arabidopsis thaliana, CONSTANS (CO) transcription factor plays a central role in regulating photoperiodic flowering. In contrast to posttranslational regulation of CO protein, still little was known about CO transcriptional regulation. Here we show that the CINCINNATA (CIN) clade of class II TEOSINTE BRANCHED 1/ CYCLOIDEA/ PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR (TCP) proteins act as CO activators. Our yeast one-hybrid analysis revealed that class II CIN-TCPs, including TCP4, bind to the CO promoter. TCP4 induces CO expression around dusk by directly associating with the CO promoter in vivo. In addition, TCP4 binds to another flowering regulator, GIGANTEA (GI), in the nucleus, and induces CO expression in a GI-dependent manner. The physical association of TCP4 with the CO promoter was reduced in the gi mutant, suggesting that GI may enhance the DNA-binding ability of TCP4. Our tandem affinity purification coupled with mass spectrometry (TAP-MS) analysis identified all class II CIN-TCPs as the components of the in vivo TCP4 complex, and the gi mutant did not alter the composition of the TCP4 complex. Taken together, our results demonstrate a novel function of CIN-TCPs as photoperiodic flowering regulators, which may contribute to coordinating plant development with flowering regulation. PMID:28628608

TCP4-dependent induction of CONSTANS transcription requires GIGANTEA in photoperiodic flowering in Arabidopsis.

PubMed

Kubota, Akane; Ito, Shogo; Shim, Jae Sung; Johnson, Richard S; Song, Yong Hun; Breton, Ghislain; Goralogia, Greg S; Kwon, Michael S; Laboy Cintrón, Dianne; Koyama, Tomotsugu; Ohme-Takagi, Masaru; Pruneda-Paz, Jose L; Kay, Steve A; MacCoss, Michael J; Imaizumi, Takato

2017-06-01

Photoperiod is one of the most reliable environmental cues for plants to regulate flowering timing. In Arabidopsis thaliana, CONSTANS (CO) transcription factor plays a central role in regulating photoperiodic flowering. In contrast to posttranslational regulation of CO protein, still little was known about CO transcriptional regulation. Here we show that the CINCINNATA (CIN) clade of class II TEOSINTE BRANCHED 1/ CYCLOIDEA/ PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR (TCP) proteins act as CO activators. Our yeast one-hybrid analysis revealed that class II CIN-TCPs, including TCP4, bind to the CO promoter. TCP4 induces CO expression around dusk by directly associating with the CO promoter in vivo. In addition, TCP4 binds to another flowering regulator, GIGANTEA (GI), in the nucleus, and induces CO expression in a GI-dependent manner. The physical association of TCP4 with the CO promoter was reduced in the gi mutant, suggesting that GI may enhance the DNA-binding ability of TCP4. Our tandem affinity purification coupled with mass spectrometry (TAP-MS) analysis identified all class II CIN-TCPs as the components of the in vivo TCP4 complex, and the gi mutant did not alter the composition of the TCP4 complex. Taken together, our results demonstrate a novel function of CIN-TCPs as photoperiodic flowering regulators, which may contribute to coordinating plant development with flowering regulation.

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

Evolving fuzzy rules in a learning classifier system

NASA Technical Reports Server (NTRS)

Valenzuela-Rendon, Manuel

1993-01-01

The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning classifier systems (LCS's). It brings together the expressive powers of fuzzy logic as it has been applied in fuzzy controllers to express relations between continuous variables, and the ability of LCS's to evolve co-adapted sets of rules. The goal of the FCS is to develop a rule-based system capable of learning in a reinforcement regime, and that can potentially be used for process control.

Analysing how negative emotions emerge and are addressed in veterinary consultations, using the Verona Coding Definitions of Emotional Sequences (VR-CoDES).

PubMed

Vijfhuizen, Malou; Bok, Harold; Matthew, Susan M; Del Piccolo, Lidia; McArthur, Michelle

2017-04-01

To explore the applicability, need for modifications and reliability of the VR-CoDES in a veterinary setting while also gaining a deeper understanding of clients' expressions of negative emotion and how they are addressed by veterinarians. The Verona Coding Definitions of Emotional Sequences for client cues and concerns (VR-CoDES-CC) and health provider responses (VR-CoDES-P) were used to analyse 20 audiotaped veterinary consultations. Inter-rater reliability was established. The applicability of definitions of the VR-CoDES was identified, together with the need for specific modifications to suit veterinary consultations. The VR-CoDES-CC and VR-CoDES-P generally applied to veterinary consultations. Cue and concern reliability was found satisfactory for most types of cues, but not for concerns. Response reliability was satisfactory for explicitness, and for providing and reducing space for further disclosure. Modifications to the original coding system were necessary to accurately reflect the veterinary context and included minor additions to the VR-CoDES-CC. Using minor additions to the VR-CoDES including guilt, reassurance and cost discussions it can be reliably adopted to assess clients' implicit expressions of negative emotion and veterinarians' responses. The modified VR-CoDES could be of great value when combined with existing frameworks used for teaching and researching veterinary communication. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

3D QSAR based design of novel oxindole derivative as 5HT7 inhibitors.

PubMed

Chitta, Aparna; Sivan, Sree Kanth; Manga, Vijjulatha

2014-06-01

To understand the structural requirements of 5-hydroxytryptamine (5HT7) receptor inhibitors and to design new ligands against 5HT7 receptor with enhanced inhibitory potency, a three-dimensional quantitative structure-activity relationship study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a data set of 56 molecules consisting of oxindole, tetrahydronaphthalene, aryl ketone substituted arylpiperazinealkylamide derivatives was performed. Derived model showed good statistical reliability in terms of predicting 5HT7 inhibitory activity of the molecules, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like conventional r2 and a cross validated (q2) values of 0.985, 0.743 for CoMFA and 0.970, 0.608 for CoMSIA, respectively. Predictive ability of the models to determine 5HT7 antagonistic activity is validated using a test set of 16 molecules that were not included in the training set. Predictive r2 obtained for the test set was 0.560 and 0.619 for CoMFA and CoMSIA, respectively. Steric, electrostatic fields majorly contributed toward activity which forms the basis for design of new molecules. Absorption, distribution, metabolism and elimination (ADME) calculation using QikProp 2.5 (Schrodinger 2010, Portland, OR) reveals that the molecules confer to Lipinski's rule of five in majority of the cases.

A Split-GFP Gateway Cloning System for Topology Analyses of Membrane Proteins in Plants.

PubMed

Xie, Wenjun; Nielsen, Mads Eggert; Pedersen, Carsten; Thordal-Christensen, Hans

2017-01-01

To understand the function of membrane proteins, it is imperative to know their topology. For such studies, a split green fluorescent protein (GFP) method is useful. GFP is barrel-shaped, consisting of 11 β-sheets. When the first ten β-sheets (GFP1-10) and the 11th β-sheet (GFP11) are expressed from separate genes they will self-assembly and reconstitute a fluorescent GFP protein. However, this will only occur when the two domains co-localize in the same cellular compartment. We have developed an easy-to-use Gateway vector set for determining on which side of the membrane the N- and C-termini are located. Two vectors were designed for making N- and C-terminal fusions between the membrane proteins-of-interest and GFP11, while another three plasmids were designed to express GFP1-10 in either the cytosol, the endoplasmic reticulum (ER) lumen or the apoplast. We tested functionality of the system by applying the vector set for the transmembrane domain, CNXTM, of the ER membrane protein, calnexin, after transient expression in Nicotiana benthamiana leaves. We observed GFP signal from the ER when we reciprocally co-expressed GFP11-CNXTM with GFP1-10-HDEL and CNXTM-GFP with cytosolic GFP1-10. The opposite combinations did not result in GFP signal emission. This test using the calnexin ER-membrane domain demonstrated its C-terminus to be in the cytosol and its N-terminus in the ER lumen. This result confirmed the known topology of calnexin, and we therefore consider this split-GFP system highly useful for ER membrane topology studies. Furthermore, the vector set provided is useful for detecting the topology of proteins on other membranes in the cell, which we confirmed for a plasma membrane syntaxin. The set of five Ti-plasmids are easily and efficiently used for Gateway cloning and transient transformation of N. benthamiana leaves.

ISL1 and BRN3B co-regulate the differentiation of murine retinal ganglion cells

PubMed Central

Pan, Ling; Deng, Min; Xie, Xiaoling; Gan, Lin

2009-01-01

SUMMARY LIM-homeodomain (HD) and POU-HD transcription factors play critical roles in neurogenesis. However, it remains largely unknown how they cooperate in this process and what downstream target genes they regulate. Here we show that ISL1, a LIM-HD protein, is co-expressed with BRN3B, a POU-HD factor, in nascent, post-mitotic retinal ganglion cells (RGCs). Similar to the Brn3b-null retinas, retina-specific deletion of Isl1 results in the apoptosis of a majority of RGCs and in RGC axon guidance defects. The Isl1 and Brn3b double null mice display more severe retinal abnormalities with a near complete loss of RGCs, indicating the synergistic functions of these two factors. Furthermore, we show that both Isl1 and Brn3b function downstream of Math5 to regulate the expression of a common set of RGC-specific genes. Whole retina chromatin immunoprecipitation and in vitro transactivation assays reveal that ISL1 and BRN3B concurrently bind to and synergistically regulate the expression of a common set of RGC-specific genes. Thus, our results uncover a novel regulatory mechanism of BRN3B and ISL1 in RGC differentiation. PMID:18434421

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia.

PubMed

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J V; Schulz, Marcel H; Simon, Martin

2015-08-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1.

PubMed

Fatima, Sabiha; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2012-08-01

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r², q²(loo) and r²(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r²(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.

What chickens would tell you about the evolution of antigen processing and presentation.

PubMed

Kaufman, Jim

2015-06-01

Outside of mammals, antigen processing and presentation have only been investigated in chickens. The chicken MHC is organized differently than mammals, allowing the co-evolution of polymorphic genes, with each MHC haplotype having a set of TAP1, TAP2 and tapasin alleles directed to high expression of a single classical class I molecule. However, the class I alleles vary in the size of peptide-binding repertoire, along with a suite of other properties. The salient features of the chicken MHC are found in many non-mammalian vertebrates, and are likely to have been set at the origin of the adaptive immune system of jawed vertebrates, with unrelated genes co-evolving to set up the original pathways. Half a billion years later, various features of presentation and resistance to disease still reflect this ancestral arrangement. Copyright © 2015 Elsevier Ltd. All rights reserved.

Environment or Development? Lifetime Net CO2 Exchange and Control of the Expression of Crassulacean Acid Metabolism in Mesembryanthemum crystallinum1

PubMed Central

Winter, Klaus; Holtum, Joseph A.M.

2007-01-01

The relative influence of plant age and environmental stress signals in triggering a shift from C3 photosynthesis to Crassulacean acid metabolism (CAM) in the annual halophytic C3-CAM species Mesembryanthemum crystallinum was explored by continuously monitoring net CO2 exchange of whole shoots from the seedling stage until seed set. Plants exposed to high salinity (400 mm NaCl) in hydroponic culture solution or grown in saline-droughted soil acquired between 11% and 24% of their carbon via net dark CO2 uptake involving CAM. In contrast, plants grown under nonsaline, well-watered conditions were capable of completing their life cycle by operating in the C3 mode without ever exhibiting net CO2 uptake at night. These observations are not consistent with the widely expressed view that the induction of CAM by high salinity in M. crystallinum represents an acceleration of preprogrammed developmental processes. Rather, our study demonstrates that the induction of the CAM pathway for carbon acquisition in M. crystallinum is under environmental control. PMID:17056756

Environment or development? Lifetime net CO2 exchange and control of the expression of Crassulacean acid metabolism in Mesembryanthemum crystallinum.

PubMed

Winter, Klaus; Holtum, Joseph A M

2007-01-01

The relative influence of plant age and environmental stress signals in triggering a shift from C(3) photosynthesis to Crassulacean acid metabolism (CAM) in the annual halophytic C(3)-CAM species Mesembryanthemum crystallinum was explored by continuously monitoring net CO(2) exchange of whole shoots from the seedling stage until seed set. Plants exposed to high salinity (400 mm NaCl) in hydroponic culture solution or grown in saline-droughted soil acquired between 11% and 24% of their carbon via net dark CO(2) uptake involving CAM. In contrast, plants grown under nonsaline, well-watered conditions were capable of completing their life cycle by operating in the C(3) mode without ever exhibiting net CO(2) uptake at night. These observations are not consistent with the widely expressed view that the induction of CAM by high salinity in M. crystallinum represents an acceleration of preprogrammed developmental processes. Rather, our study demonstrates that the induction of the CAM pathway for carbon acquisition in M. crystallinum is under environmental control.

Not5-dependent co-translational assembly of Ada2 and Spt20 is essential for functional integrity of SAGA

PubMed Central

Kassem, Sari; Villanyi, Zoltan

2017-01-01

Abstract Acetylation of histones regulates gene expression in eukaryotes. In the yeast Saccharomyces cerevisiae it depends mainly upon the ADA and SAGA histone acetyltransferase complexes for which Gcn5 is the catalytic subunit. Previous screens have determined that global acetylation is reduced in cells lacking subunits of the Ccr4–Not complex, a global regulator of eukaryotic gene expression. In this study we have characterized the functional connection between the Ccr4–Not complex and SAGA. We show that SAGA mRNAs encoding a core set of SAGA subunits are tethered together for co-translational assembly of the encoded proteins. Ccr4–Not subunits bind SAGA mRNAs and promote the co-translational assembly of these subunits. This is needed for integrity of SAGA. In addition, we determine that a glycolytic enzyme, the glyceraldehyde-3-phosphate dehydrogenase Tdh3, a prototypical moonlighting protein, is tethered at this site of Ccr4–Not-dependent co-translational SAGA assembly and functions as a chaperone. PMID:28180299

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench

PubMed Central

Beckers, Matthew; Mohorianu, Irina; Stocks, Matthew; Applegate, Christopher; Dalmay, Tamas; Moulton, Vincent

2017-01-01

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this. PMID:28289155

DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

PubMed

Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

2018-04-01

Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

Expression of leukemia inhibitory factor and leukemia inhibitory factor receptor in the canine pituitary gland and corticotrope adenomas.

PubMed

Hanson, J M; Mol, J A; Meij, B P

2010-05-01

Leukemia inhibitory factor (LIF) is a pleiotropic cytokine of the IL-6 family that activates the hypothalamic-pituitary-adrenal axis and promotes corticotrope cell differentiation during development. The aim of this study was to investigate the expression of LIF and its receptor (LIFR) in the canine pituitary gland and in corticotrope adenomas, and to perform a mutation analysis of LIFR. Using immunohistochemistry, immunofluorescence, and quantitative expression analysis, LIF and LIFR expression were studied in pituitary glands of control dogs and in specimens of corticotrope adenoma tissue collected through hypophysectomy in dogs with pituitary-dependent hypercortisolism (PDH, Cushing's disease). Using sequence analysis, cDNA was screened for mutations in the LIFR. In the control pituitary tissues and corticotrope adenomas, there was a low magnitude of LIF expression. The LIFR, however, was highly expressed and co-localized with ACTH(1-24) expression. Cytoplasmatic immunoreactivity of LIFR was preserved in corticotrope adenomas and adjacent nontumorous cells of pars intermedia. No mutation was found on mutation analysis of the complete LIFR cDNA. Surprisingly, nuclear to perinuclear immunoreactivity for LIFR was present in nontumorous pituitary cells of the pars distalis in 10 of 12 tissue specimens from PDH dogs. These data show that LIFR is highly co-expressed with adrenocorticotropic hormone (ACTH) and alpha-melanocyte-stimulating hormone (alpha-MSH) in the canine pituitary gland and in corticotrope adenomas. Nuclear immunoreactivity for LIFR in nontumorous cells of the pars distalis may indicate the presence of a corticotrope adenoma. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

PubMed

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

SLC9A9 Co-expression modules in autism-associated brain regions.

PubMed

Patak, Jameson; Hess, Jonathan L; Zhang-James, Yanli; Glatt, Stephen J; Faraone, Stephen V

2017-03-01

SLC9A9 is a sodium hydrogen exchanger present in the recycling endosome and highly expressed in the brain. It is implicated in neuropsychiatric disorders, including autism spectrum disorders (ASDs). Little research concerning its gene expression patterns and biological pathways has been conducted. We sought to investigate its possible biological roles in autism-associated brain regions throughout development. We conducted a weighted gene co-expression network analysis on RNA-seq data downloaded from Brainspan. We compared prenatal and postnatal gene expression networks for three ASD-associated brain regions known to have high SLC9A9 gene expression. We also performed an ASD-associated single nucleotide polymorphism enrichment analysis and a cell signature enrichment analysis. The modules showed differences in gene constituents (membership), gene number, and connectivity throughout time. SLC9A9 was highly associated with immune system functions, metabolism, apoptosis, endocytosis, and signaling cascades. Gene list comparison with co-immunoprecipitation data was significant for multiple modules. We found a disproportionately high autism risk signal among genes constituting the prenatal hippocampal module. The modules were enriched with astrocyte and oligodendrocyte markers. SLC9A9 is potentially involved in the pathophysiology of ASDs. Our investigation confirmed proposed functions for SLC9A9, such as endocytosis and immune regulation, while also revealing potential roles in mTOR signaling and cell survival.. By providing a concise molecular map and interactions, evidence of cell type and implicated brain regions we hope this will guide future research on SLC9A9. Autism Res 2017, 10: 414-429. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Network-based co-expression analysis for exploring the potential diagnostic biomarkers of metastatic melanoma.

PubMed

Wang, Li-Xin; Li, Yang; Chen, Guan-Zhi

2018-01-01

Metastatic melanoma is an aggressive skin cancer and is one of the global malignancies with high mortality and morbidity. It is essential to identify and verify diagnostic biomarkers of early metastatic melanoma. Previous studies have systematically assessed protein biomarkers and mRNA-based expression characteristics. However, molecular markers for the early diagnosis of metastatic melanoma have not been identified. To explore potential regulatory targets, we have analyzed the gene microarray expression profiles of malignant melanoma samples by co-expression analysis based on the network approach. The differentially expressed genes (DEGs) were screened by the EdgeR package of R software. A weighted gene co-expression network analysis (WGCNA) was used for the identification of DEGs in the special gene modules and hub genes. Subsequently, a protein-protein interaction network was constructed to extract hub genes associated with gene modules. Finally, twenty-four important hub genes (RASGRP2, IKZF1, CXCR5, LTB, BLK, LINGO3, CCR6, P2RY10, RHOH, JUP, KRT14, PLA2G3, SPRR1A, KRT78, SFN, CLDN4, IL1RN, PKP3, CBLC, KRT16, TMEM79, KLK8, LYPD3 and LYPD5) were treated as valuable factors involved in the immune response and tumor cell development in tumorigenesis. In addition, a transcriptional regulatory network was constructed for these specific modules or hub genes, and a few core transcriptional regulators were found to be mostly associated with our hub genes, including GATA1, STAT1, SP1, and PSG1. In summary, our findings enhance our understanding of the biological process of malignant melanoma metastasis, enabling us to identify specific genes to use for diagnostic and prognostic markers and possibly for targeted therapy.

Leptin reverts pro-apoptotic and antiproliferative effects of α-linolenic acids in BCR-ABL positive leukemic cells: involvement of PI3K pathway.

PubMed

Beaulieu, Aurore; Poncin, Géraldine; Belaid-Choucair, Zakia; Humblet, Chantal; Bogdanovic, Gordana; Lognay, Georges; Boniver, Jacques; Defresne, Marie-Paule

2011-01-01

It is suspected that bone marrow (BM) microenvironmental factors may influence the evolution of chronic myeloid leukaemia (CML). In this study, we postulated that adipocytes and lipids could be involved in the progression of CML. To test this hypothesis, adipocytes were co-cultured with two BCR-ABL positive cell lines (PCMDS and K562). T cell (Jurkat) and stroma cell (HS-5) lines were used as controls. In the second set of experiments, leukemic cell lines were treated with stearic, oleic, linoleic or α-linolenic acids in presence or absence of leptin. Survival, proliferation, leptin production, OB-R isoforms (OB-Ra and OB-Rb), phosphoinositide 3-kinase (PI3k) and BCL-2 expression have been tested after 24h, 48h and 72h of treatment. Our results showed that adipocytes induced a decrease of CML proliferation and an increase in lipid accumulation in leukemic cells. In addition, CML cell lines induced adipocytes cell death. Chromatography analysis showed that BM microenvironment cells were full of saturated (SFA) and monounsaturated (MUFA) fatty acids, fatty acids that protect tumor cells against external agents. Stearic acid increased Bcl-2 expression in PCMDS, whereas oleic and linoleic acids had no effects. In contrast, α-linolenic acid decreased the proliferation and the survival of CML cell lines as well as BCL-2 and OB-R expression. The effect of α-linolenic acids seemed to be due to PI3K pathway and Bcl-2 inhibition. Leptin production was detected in the co-culture medium. In the presence of leptin, the effect of α-linolenic acid on proliferation, survival, OB-R and BCl-2 expression was reduced.

An Iterative Time Windowed Signature Algorithm for Time Dependent Transcription Module Discovery

PubMed Central

Meng, Jia; Gao, Shou-Jiang; Huang, Yufei

2010-01-01

An algorithm for the discovery of time varying modules using genome-wide expression data is present here. When applied to large-scale time serious data, our method is designed to discover not only the transcription modules but also their timing information, which is rarely annotated by the existing approaches. Rather than assuming commonly defined time constant transcription modules, a module is depicted as a set of genes that are co-regulated during a specific period of time, i.e., a time dependent transcription module (TDTM). A rigorous mathematical definition of TDTM is provided, which is serve as an objective function for retrieving modules. Based on the definition, an effective signature algorithm is proposed that iteratively searches the transcription modules from the time series data. The proposed method was tested on the simulated systems and applied to the human time series microarray data during Kaposi's sarcoma-associated herpesvirus (KSHV) infection. The result has been verified by Expression Analysis Systematic Explorer. PMID:21552463

Atmospheric CO2 Concentrations from Aircraft for 1972-1981, CSIRO Monitoring Program

DOE Data Explorer

Beardsmore, David J. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Victoria, Australia; Pearman, Graeme I. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Victoria, Australia

2012-01-01

From 1972 through 1981, air samples were collected in glass flasks from aircraft at a variety of latitudes and altitudes over Australia, New Zealand, and Antarctica. The samples were analyzed for CO2 concentrations with nondispersive infrared gas analysis. The resulting data contain the sampling dates, type of aircraft, flight number, flask identification number, sampling time, geographic sector, distance in kilometers from the listed distance measuring equipment (DME) station, station number of the radio navigation distance measuring equipment, altitude of the aircraft above mean sea level, sample analysis date, flask pressure, tertiary standards used for the analysis, analyzer used, and CO2 concentration. These data represent the first published record of CO2 concentrations in the Southern Hemisphere expressed in the WMO 1981 CO2 Calibration Scale and provide a precise record of atmospheric CO2 concentrations in the troposphere and lower stratosphere over Australia and New Zealand.

Transcriptomic analysis of instinctive and learned reward-related behaviors in honey bees

PubMed Central

Naeger, Nicholas L.

2016-01-01

ABSTRACT We used transcriptomics to compare instinctive and learned, reward-based honey bee behaviors with similar spatio-temporal components: mating flights by males (drones) and time-trained foraging flights by females (workers), respectively. Genome-wide gene expression profiling via RNA sequencing was performed on the mushroom bodies, a region of the brain known for multi-modal sensory integration and responsive to various types of reward. Differentially expressed genes (DEGs) associated with the onset of mating (623 genes) were enriched for the gene ontology (GO) categories of Transcription, Unfolded Protein Binding, Post-embryonic Development, and Neuron Differentiation. DEGs associated with the onset of foraging (473) were enriched for Lipid Transport, Regulation of Programmed Cell Death, and Actin Cytoskeleton Organization. These results demonstrate that there are fundamental molecular differences between similar instinctive and learned behaviors. In addition, there were 166 genes with strong similarities in expression across the two behaviors – a statistically significant overlap in gene expression, also seen in Weighted Gene Co-Expression Network Analysis. This finding indicates that similar instinctive and learned behaviors also share common molecular architecture. This common set of DEGs was enriched for Regulation of RNA Metabolic Process, Transcription Factor Activity, and Response to Ecdysone. These findings provide a starting point for better understanding the relationship between instincts and learned behaviors. In addition, because bees collect food for their colony rather than for themselves, these results also support the idea that altruistic behavior relies, in part, on elements of brain reward systems associated with selfish behavior. PMID:27852762

A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

PubMed

Sethi, Isha; Romano, Rose-Anne; Gluck, Christian; Smalley, Kirsten; Vojtesek, Borivoj; Buck, Michael J; Sinha, Satrajit

2015-08-07

The transcription factor p63 belongs to the p53/p63/p73 family and plays key functional roles during normal epithelial development and differentiation and in pathological states such as squamous cell carcinomas. The human TP63 gene, located on chromosome 3q28 is driven by two promoters that generate the full-length transactivating (TA) and N-terminal truncated (ΔN) isoforms. Furthermore alternative splicing at the C-terminus gives rise to additional α, β, γ and likely several other minor variants. Teasing out the expression and biological function of each p63 variant has been both the focus of, and a cause for contention in the p63 field. Here we have taken advantage of a burgeoning RNA-Seq based genomic data-sets to examine the global expression profiles of p63 isoforms across commonly utilized human cell-lines and major tissues and organs. Consistent with earlier studies, we find ΔNp63 transcripts, primarily that of the ΔNp63α isoforms, to be expressed in most cells of epithelial origin such as those of skin and oral tissues, mammary glands and squamous cell carcinomas. In contrast, TAp63 is not expressed in the majority of normal cell-types and tissues; rather it is selectively expressed at moderate to high levels in a subset of Burkitt's and diffuse large B-cell lymphoma cell lines. We verify this differential expression pattern of p63 isoforms by Western blot analysis, using newly developed ΔN and TA specific antibodies. Furthermore using unsupervised clustering of human cell lines, tissues and organs, we show that ΔNp63 and TAp63 driven transcriptional networks involve very distinct sets of molecular players, which may underlie their different biological functions. In this study we report comprehensive and global expression profiles of p63 isoforms and their relationship to p53/p73 and other potential transcriptional co-regulators. We curate publicly available data generated in part by consortiums such as ENCODE, FANTOM and Human Protein Atlas to delineate the vastly different transcriptomic landscapes of ΔNp63 and TAp63. Our studies help not only in dispelling prevailing myths and controversies on p63 expression in commonly used human cell lines but also augur new isoform- and cell type-specific activities of p63.

SARS-CoV Regulates Immune Function-Related Gene Expression in Human Monocytic Cells

PubMed Central

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

SARS-CoV regulates immune function-related gene expression in human monocytic cells.

PubMed

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.

T cell subtypes and reciprocal inflammatory mediator expression differentiate P. falciparum memory recall responses in asymptomatic and symptomatic malaria patients in southeastern Haiti

PubMed Central

Campo, Joseph J.; Cicéron, Micheline; Raccurt, Christian P.; Beau De Rochars, Valery E. M.

2017-01-01

Asymptomatic Plasmodium falciparum infection is responsible for maintaining malarial disease within human populations in low transmission countries such as Haiti. Investigating differential host immune responses to the parasite as a potential underlying mechanism could help provide insight into this highly complex phenomenon and possibly identify asymptomatic individuals. We performed a cross-sectional analysis of individuals who were diagnosed with malaria in Sud-Est, Haiti by comparing the cellular and humoral responses of both symptomatic and asymptomatic subjects. Plasma samples were analyzed with a P. falciparum protein microarray, which demonstrated serologic reactivity to 3,877 P. falciparum proteins of known serologic reactivity; however, no antigen-antibody reactions delineating asymptomatics from symptomatics were identified. In contrast, differences in cellular responses were observed. Flow cytometric analysis of patient peripheral blood mononuclear cells co-cultured with P. falciparum infected erythrocytes demonstrated a statistically significant increase in the proportion of T regulatory cells (CD4+ CD25+ CD127-), and increases in unique populations of both NKT-like cells (CD3+ CD8+ CD56+) and CD8mid T cells in asymptomatics compared to symptomatics. Also, CD38+/HLA-DR+ expression on γδ T cells, CD8mid (CD56-) T cells, and CD8mid CD56+ NKT-like cells decreased upon exposure to infected erythrocytes in both groups. Cytometric bead analysis of the co-culture supernatants demonstrated an upregulation of monocyte-activating chemokines/cytokines in asymptomatics, while immunomodulatory soluble factors were elevated in symptomatics. Principal component analysis of these expression values revealed a distinct clustering of individual responses within their respective phenotypic groups. This is the first comprehensive investigation of immune responses to P. falciparum in Haiti, and describes unique cell-mediated immune repertoires that delineate individuals into asymptomatic and symptomatic phenotypes. Future investigations using large scale biological data sets analyzing multiple components of adaptive immunity, could collectively define which cellular responses and molecular correlates of disease outcome are malaria region specific, and which are truly generalizable features of asymptomatic Plasmodium immunity, a research goal of critical priority. PMID:28369062

T cell subtypes and reciprocal inflammatory mediator expression differentiate P. falciparum memory recall responses in asymptomatic and symptomatic malaria patients in southeastern Haiti.

PubMed

Lehmann, Jason S; Campo, Joseph J; Cicéron, Micheline; Raccurt, Christian P; Boncy, Jacques; Beau De Rochars, Valery E M; Cannella, Anthony P

2017-01-01

Asymptomatic Plasmodium falciparum infection is responsible for maintaining malarial disease within human populations in low transmission countries such as Haiti. Investigating differential host immune responses to the parasite as a potential underlying mechanism could help provide insight into this highly complex phenomenon and possibly identify asymptomatic individuals. We performed a cross-sectional analysis of individuals who were diagnosed with malaria in Sud-Est, Haiti by comparing the cellular and humoral responses of both symptomatic and asymptomatic subjects. Plasma samples were analyzed with a P. falciparum protein microarray, which demonstrated serologic reactivity to 3,877 P. falciparum proteins of known serologic reactivity; however, no antigen-antibody reactions delineating asymptomatics from symptomatics were identified. In contrast, differences in cellular responses were observed. Flow cytometric analysis of patient peripheral blood mononuclear cells co-cultured with P. falciparum infected erythrocytes demonstrated a statistically significant increase in the proportion of T regulatory cells (CD4+ CD25+ CD127-), and increases in unique populations of both NKT-like cells (CD3+ CD8+ CD56+) and CD8mid T cells in asymptomatics compared to symptomatics. Also, CD38+/HLA-DR+ expression on γδ T cells, CD8mid (CD56-) T cells, and CD8mid CD56+ NKT-like cells decreased upon exposure to infected erythrocytes in both groups. Cytometric bead analysis of the co-culture supernatants demonstrated an upregulation of monocyte-activating chemokines/cytokines in asymptomatics, while immunomodulatory soluble factors were elevated in symptomatics. Principal component analysis of these expression values revealed a distinct clustering of individual responses within their respective phenotypic groups. This is the first comprehensive investigation of immune responses to P. falciparum in Haiti, and describes unique cell-mediated immune repertoires that delineate individuals into asymptomatic and symptomatic phenotypes. Future investigations using large scale biological data sets analyzing multiple components of adaptive immunity, could collectively define which cellular responses and molecular correlates of disease outcome are malaria region specific, and which are truly generalizable features of asymptomatic Plasmodium immunity, a research goal of critical priority.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Carboxydothermus islandicus sp. nov., a thermophilic, hydrogenogenic, carboxydotrophic bacterium isolated from a hot spring.

PubMed

Novikov, Andrey A; Sokolova, Tatyana G; Lebedinsky, Alexander V; Kolganova, Tatyana V; Bonch-Osmolovskaya, Elizaveta A

2011-10-01

An anaerobic, thermophilic bacterium, strain SET IS-9(T), was isolated from an Icelandic hot spring. Cells of strain SET IS-9(T) are short, slightly curved, motile rods. The strain grows chemolithotrophically on CO, producing equimolar quantities of H(2) and CO(2). It also grows fermentatively on lactate or pyruvate in the presence of yeast extract (0.2 g l(-1)). Products of pyruvate fermentation are acetate, CO(2) and H(2). Growth occurs at 50-70 °C, with an optimum at 65 °C, and at pH 5.0-8.0, with an optimum at pH 5.5-6.0. The generation time during chemolithotrophic growth on CO under optimal conditions is 2.0 h. 16S rRNA gene sequence analysis suggested that the organism belongs to the genus Carboxydothermus. On the basis of phenotypic features and phylogenetic analysis, Carboxydothermus islandicus sp. nov. is proposed, with the type strain SET IS-9(T) ( = DSM 21830(T)  = VKM B-2561(T)). An emended description of the genus Carboxydothermus is also given.

β2 Adrenoceptors are underexpressed in peripheral blood mononuclear cells and associated with a better metabolic profile in central obesity.

PubMed

Leite, Fernanda; Lima, Margarida; Marino, Franca; Cosentino, Marco; Ribeiro, Laura

2017-01-01

Background: Central obesity (CO) is an inflammatory disease. Because immune cells and adipocytes are catecholamines(CA)-producing cells, we studied the expression of adrenoceptors (AR) in peripheral blood mononuclear cells (PBMCs) hypothesizing a distinct adrenergic pattern in inflammatory obesity. Methods: AR expression was assessed in blood donors categorized by waist circumference (WC) (CO: WC≥0.80 m in women and ≥0.94 m in men). Following a pilot study for all AR subtypes, we measured β 2 AR expression in fifty-seven individuals and correlated this result with anthropometric, metabolic and inflammatory parameters. A ratio (R) between AR mRNA of CO and non-CO<0.5 was considered under and >2.0 over expression. Results: The pilot study revealed no differences between groups, except for β 2 AR mRNA. CO individuals showed underexpression of β 2 AR relatively to those without CO (R=0.08; p=0.009). β 2 AR expression inversely correlated with triacylglycerol (r=-0.271; p=0.041), very low-density lipoprotein-cholesterol (r=-0.313; p=0.018) and leptin (r=-0.392; p=0.012) and positively with high-density lipoprotein-cholesterol (r=0.310: p=0.045) plasma levels. Multiple logistic regression analysis showed a protective effect of β 2 AR expression (≥2x10-6) [odds ratio (OR) 0.177 with respective confidence interval of 95% (95% CI) (0.040- 0.796)] for the occurrence of CO. A higher association was found for women as compared to men (Ξ9:1) [OR 8.972 (95% CI) (1.679-47.949)]. Conclusion: PBMCs β 2 AR, underexpressed in centrally obese, are associated with a better metabolic profile and showed a protective role for the development of CO. The discovery of β 2 AR as a new molecular marker of obesity subphenotypes in PBMCs might contribute to clarify the adrenergic immunomodulation of inflammatory obesity.

β2 Adrenoceptors are underexpressed in peripheral blood mononuclear cells and associated with a better metabolic profile in central obesity

PubMed Central

Leite, Fernanda; Lima, Margarida; Marino, Franca; Cosentino, Marco; Ribeiro, Laura

2017-01-01

Background: Central obesity (CO) is an inflammatory disease. Because immune cells and adipocytes are catecholamines(CA)-producing cells, we studied the expression of adrenoceptors (AR) in peripheral blood mononuclear cells (PBMCs) hypothesizing a distinct adrenergic pattern in inflammatory obesity. Methods: AR expression was assessed in blood donors categorized by waist circumference (WC) (CO: WC≥0.80 m in women and ≥0.94 m in men). Following a pilot study for all AR subtypes, we measured β2AR expression in fifty-seven individuals and correlated this result with anthropometric, metabolic and inflammatory parameters. A ratio (R) between AR mRNA of CO and non-CO<0.5 was considered under and >2.0 over expression. Results: The pilot study revealed no differences between groups, except for β2AR mRNA. CO individuals showed underexpression of β2AR relatively to those without CO (R=0.08; p=0.009). β2AR expression inversely correlated with triacylglycerol (r=-0.271; p=0.041), very low-density lipoprotein-cholesterol (r=-0.313; p=0.018) and leptin (r=-0.392; p=0.012) and positively with high-density lipoprotein-cholesterol (r=0.310: p=0.045) plasma levels. Multiple logistic regression analysis showed a protective effect of β2AR expression (≥2x10-6) [odds ratio (OR) 0.177 with respective confidence interval of 95% (95% CI) (0.040- 0.796)] for the occurrence of CO. A higher association was found for women as compared to men (Ξ9:1) [OR 8.972 (95% CI) (1.679-47.949)]. Conclusion: PBMCs β2AR, underexpressed in centrally obese, are associated with a better metabolic profile and showed a protective role for the development of CO. The discovery of β2AR as a new molecular marker of obesity subphenotypes in PBMCs might contribute to clarify the adrenergic immunomodulation of inflammatory obesity. PMID:28824322

Mechanisms of glacial-to-future atmospheric CO2 effects on plant immunity.

PubMed

Williams, Alex; Pétriacq, Pierre; Schwarzenbacher, Roland E; Beerling, David J; Ton, Jurriaan

2018-04-01

The impacts of rising atmospheric CO 2 concentrations on plant disease have received increasing attention, but with little consensus emerging on the direct mechanisms by which CO 2 shapes plant immunity. Furthermore, the impact of sub-ambient CO 2 concentrations, which plants have experienced repeatedly over the past 800 000 yr, has been largely overlooked. A combination of gene expression analysis, phenotypic characterisation of mutants and mass spectrometry-based metabolic profiling was used to determine development-independent effects of sub-ambient CO 2 (saCO 2 ) and elevated CO 2 (eCO 2 ) on Arabidopsis immunity. Resistance to the necrotrophic Plectosphaerella cucumerina (Pc) was repressed at saCO 2 and enhanced at eCO 2 . This CO 2 -dependent resistance was associated with priming of jasmonic acid (JA)-dependent gene expression and required intact JA biosynthesis and signalling. Resistance to the biotrophic oomycete Hyaloperonospora arabidopsidis (Hpa) increased at both eCO 2 and saCO 2 . Although eCO 2 primed salicylic acid (SA)-dependent gene expression, mutations affecting SA signalling only partially suppressed Hpa resistance at eCO 2 , suggesting additional mechanisms are involved. Induced production of intracellular reactive oxygen species (ROS) at saCO 2 corresponded to a loss of resistance in glycolate oxidase mutants and increased transcription of the peroxisomal catalase gene CAT2, unveiling a mechanism by which photorespiration-derived ROS determined Hpa resistance at saCO 2 . By separating indirect developmental impacts from direct immunological effects, we uncover distinct mechanisms by which CO 2 shapes plant immunity and discuss their evolutionary significance. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Characterization, Function, and Transcriptional Profiling Analysis of 3-Hydroxy-3-methylglutaryl-CoA Synthase Gene (GbHMGS1) towards Stresses and Exogenous Hormone Treatments in Ginkgo biloba.

PubMed

Meng, Xiangxiang; Song, Qiling; Ye, Jiabao; Wang, Lanlan; Xu, Feng

2017-10-12

3-Hydroxy-3-methylglutaryl-CoA synthase (HMGS) is one of the rate-limiting enzymes in the mevalonate pathway as it catalyzes the condensation of acetoacetyl-CoA to form 3-hydroxy-3-methylglutaryl-CoA. In this study, A HMGS gene (designated as GbHMGS1 ) was cloned from Ginkgo biloba for the first time. GbHMGS1 contained a 1422-bp open-reading frame encoding 474 amino acids. Comparative and bioinformatics analysis revealed that GbHMGS1 was extensively homologous to HMGSs from other plant species. Phylogenetic analysis indicated that the GbHMGS1 belonged to the plant HMGS superfamily, sharing a common evolutionary ancestor with other HMGSs, and had a further relationship with other gymnosperm species. The yeast complement assay of GbHMGS1 in HMGS -deficient Saccharomyces cerevisiae strain YSC6274 demonstrated that GbHMGS1 gene encodes a functional HMGS enzyme. The recombinant protein of GbHMGS1 was successfully expressed in E. coli . The in vitro enzyme activity assay showed that the k cat and K m values of GbHMGS1 were 195.4 min -1 and 689 μM, respectively. GbHMGS1 was constitutively expressed in all tested tissues, including the roots, stems, leaves, female flowers, male flowers and fruits. The transcript accumulation for GbHMGS1 was highest in the leaves. Expression profiling analyses revealed that GbHMGS1 expression was induced by abiotic stresses (ultraviolet B and cold) and hormone treatments (salicylic acid, methyl jasmonate, and ethephon) in G. biloba , indicating that GbHMGS1 gene was involved in the response to environmental stresses and plant hormones.

Testing the Hydrological Coherence of High-Resolution Gridded Precipitation and Temperature Data Sets

NASA Astrophysics Data System (ADS)

Laiti, L.; Mallucci, S.; Piccolroaz, S.; Bellin, A.; Zardi, D.; Fiori, A.; Nikulin, G.; Majone, B.

2018-03-01

Assessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989-2008 and includes five gridded daily meteorological data sets: E-OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E-OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large-scale hydroclimatic studies.

Matrix factorization reveals aging-specific co-expression gene modules in the fat and muscle tissues in nonhuman primates

NASA Astrophysics Data System (ADS)

Wang, Yongcui; Zhao, Weiling; Zhou, Xiaobo

2016-10-01

Accurate identification of coherent transcriptional modules (subnetworks) in adipose and muscle tissues is important for revealing the related mechanisms and co-regulated pathways involved in the development of aging-related diseases. Here, we proposed a systematically computational approach, called ICEGM, to Identify the Co-Expression Gene Modules through a novel mathematical framework of Higher-Order Generalized Singular Value Decomposition (HO-GSVD). ICEGM was applied on the adipose, and heart and skeletal muscle tissues in old and young female African green vervet monkeys. The genes associated with the development of inflammation, cardiovascular and skeletal disorder diseases, and cancer were revealed by the ICEGM. Meanwhile, genes in the ICEGM modules were also enriched in the adipocytes, smooth muscle cells, cardiac myocytes, and immune cells. Comprehensive disease annotation and canonical pathway analysis indicated that immune cells, adipocytes, cardiomyocytes, and smooth muscle cells played a synergistic role in cardiac and physical functions in the aged monkeys by regulation of the biological processes associated with metabolism, inflammation, and atherosclerosis. In conclusion, the ICEGM provides an efficiently systematic framework for decoding the co-expression gene modules in multiple tissues. Analysis of genes in the ICEGM module yielded important insights on the cooperative role of multiple tissues in the development of diseases.

A sensitivity analysis on seismic tomography data with respect to CO2 saturation of a CO2 geological sequestration field

NASA Astrophysics Data System (ADS)

Park, Chanho; Nguyen, Phung K. T.; Nam, Myung Jin; Kim, Jongwook

2013-04-01

Monitoring CO2 migration and storage in geological formations is important not only for the stability of geological sequestration of CO2 but also for efficient management of CO2 injection. Especially, geophysical methods can make in situ observation of CO2 to assess the potential leakage of CO2 and to improve reservoir description as well to monitor development of geologic discontinuity (i.e., fault, crack, joint, etc.). Geophysical monitoring can be based on wireline logging or surface surveys for well-scale monitoring (high resolution and nallow area of investigation) or basin-scale monitoring (low resolution and wide area of investigation). In the meantime, crosswell tomography can make reservoir-scale monitoring to bridge the resolution gap between well logs and surface measurements. This study focuses on reservoir-scale monitoring based on crosswell seismic tomography aiming describe details of reservoir structure and monitoring migration of reservoir fluid (water and CO2). For the monitoring, we first make a sensitivity analysis on crosswell seismic tomography data with respect to CO2 saturation. For the sensitivity analysis, Rock Physics Models (RPMs) are constructed by calculating the values of density and P and S-wave velocities of a virtual CO2 injection reservoir. Since the seismic velocity of the reservoir accordingly changes as CO2 saturation changes when the CO2 saturation is less than about 20%, while when the CO2 saturation is larger than 20%, the seismic velocity is insensitive to the change, sensitivity analysis is mainly made when CO2 saturation is less than 20%. For precise simulation of seismic tomography responses for constructed RPMs, we developed a time-domain 2D elastic modeling based on finite difference method with a staggered grid employing a boundary condition of a convolutional perfectly matched layer. We further make comparison between sensitivities of seismic tomography and surface measurements for RPMs to analysis resolution difference between them. Moreover, assuming a similar reservoir situation to the CO2 storage site in Nagaoka, Japan, we generate time-lapse tomographic data sets for the corresponding CO2 injection process, and make a preliminary interpretation of the data sets.

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

Eckert, C. A.; Sullivan, R.; Johnson, C.

CO2 and H2 are promising feedstocks for production of valuable biocompounds. Ralstonia eutropha utilizes these feedstocks to generate energy (ATP) and reductant (NAD(P)H) via oxidation of H2 by a membrane-bound (MBH) and a soluble hydrogenase (SH) for CO2 fixation by the Calvin-Benson-Bassham (CBB) cycle. Increased expression of the enzyme that fixes CO2 (RubisCO) resulted in 6-fold activity improvement in vitro, while increased expression of the MBH operon or the SH operon plus MBH operon maturation factors necessary for activity resulted in a 10-fold enhancement. Current research involves genetic manipulation of two endogenous cbb operons for increased expression, analysis of expressionmore » and activity of CBB/MBH/SH, cofactor ratios, and downstream products during autotrophic growth in control versus enhanced strains, and development of strategies for long-term, optimal overexpression. These studies will improve our understanding of autotrophic metabolism and provide a chassis strain for autotrophic production of biodiesel and other valuable carbon biocompounds.« less

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

PubMed

Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Plant RuBisCo assembly in E. coli with five chloroplast chaperones including BSD2.

PubMed

Aigner, H; Wilson, R H; Bracher, A; Calisse, L; Bhat, J Y; Hartl, F U; Hayer-Hartl, M

2017-12-08

Plant RuBisCo, a complex of eight large and eight small subunits, catalyzes the fixation of CO 2 in photosynthesis. The low catalytic efficiency of RuBisCo provides strong motivation to reengineer the enzyme with the goal of increasing crop yields. However, genetic manipulation has been hampered by the failure to express plant RuBisCo in a bacterial host. We achieved the functional expression of Arabidopsis thaliana RuBisCo in Escherichia coli by coexpressing multiple chloroplast chaperones. These include the chaperonins Cpn60/Cpn20, RuBisCo accumulation factors 1 and 2, RbcX, and bundle-sheath defective-2 (BSD2). Our structural and functional analysis revealed the role of BSD2 in stabilizing an end-state assembly intermediate of eight RuBisCo large subunits until the small subunits become available. The ability to produce plant RuBisCo recombinantly will facilitate efforts to improve the enzyme through mutagenesis. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Identification of synergistic impacts during anaerobic co-digestion of organic wastes.

PubMed

Astals, S; Batstone, D J; Mata-Alvarez, J; Jensen, P D

2014-10-01

Anaerobic co-digestion has been widely investigated, but there is limited analysis of interaction between substrates. The objective of this work was to assess the role of carbohydrates, protein and lipids in co-digestion behaviour separately, and together. Two sets of batch tests were done, each set consisting of the mono-digestion of three substrates, and the co-digestion of seven mixtures. The first was done with pure substrates--cellulose, casein and olive oil--while in the second slaughterhouse waste--paunch, blood and fat--were used as carbohydrate, protein and lipid sources, respectively. Synergistic effects were mainly improvement of process kinetics without a significant change in biodegradability. Kinetics improvement was linked to the mitigation of inhibitory compounds, particularly fats dilution. The exception was co-digestion of paunch with lipids, which resulted in an improved final yield with model based analysis indicating the presence of paunch improved degradability of the fatty feed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decoding the Long Noncoding RNA During Cardiac Maturation: A Roadmap for Functional Discovery.

PubMed

Touma, Marlin; Kang, Xuedong; Zhao, Yan; Cass, Ashley A; Gao, Fuying; Biniwale, Reshma; Coppola, Giovanni; Xiao, Xinshu; Reemtsen, Brian; Wang, Yibin

2016-10-01

Cardiac maturation during perinatal transition of heart is critical for functional adaptation to hemodynamic load and nutrient environment. Perturbation in this process has major implications in congenital heart defects. Transcriptome programming during perinatal stages is an important information but incomplete in current literature, particularly, the expression profiles of the long noncoding RNAs (lncRNAs) are not fully elucidated. From comprehensive analysis of transcriptomes derived from neonatal mouse heart left and right ventricles, a total of 45 167 unique transcripts were identified, including 21 916 known and 2033 novel lncRNAs. Among these lncRNAs, 196 exhibited significant dynamic regulation along maturation process. By implementing parallel weighted gene co-expression network analysis of mRNA and lncRNA data sets, several lncRNA modules coordinately expressed in a developmental manner similar to protein coding genes, while few lncRNAs revealed chamber-specific patterns. Out of 2262 lncRNAs located within 50 kb of protein coding genes, 5% significantly correlate with the expression of their neighboring genes. The impact of Ppp1r1b-lncRNA on the corresponding partner gene Tcap was validated in cultured myoblasts. This concordant regulation was also conserved in human infantile hearts. Furthermore, the Ppp1r1b-lncRNA/Tcap expression ratio was identified as a molecular signature that differentiated congenital heart defect phenotypes. The study provides the first high-resolution landscape on neonatal cardiac lncRNAs and reveals their potential interaction with mRNA transcriptome during cardiac maturation. Ppp1r1b-lncRNA was identified as a regulator of Tcap expression, with dynamic interaction in postnatal cardiac development and congenital heart defects. © 2016 American Heart Association, Inc.

Estrogen stabilizes hypoxia inducible factor 1 α through G protein coupled estrogen receptor 1 in eutopic endometrium of endometriosis

PubMed Central

Zhang, Ling; Xiong, Wenqian; Li, Na; Liu, Hengwei; He, Haitang; Du, Yu; Zhang, Zhibing; Liu, Yi

2016-01-01

Objective To investigate whether G protein-coupled estrogen receptor (GPER, also known as GPR30 and GPER1) stabilizes Hypoxia inducible factor 1α (HIF-1α) in eutopic endometrium (EuEM) of endometriosis? Design Immunohistochemical analysis and experimental in vitro study. Setting University hospital Patient(s) Patients with or without endometriosis Intervention(s) The EuEM and normal control endometrium (CoEM) were obtained by curettage. Primary cultured endometrial stromal cells (ESCs) were treated with 17β-estrogen (E2), G1 or G15. Main Outcome Measure(s) The EuEM and CoEM were collected for immunohistochemistry. Western blot, PCR, Elisa, and dual luciferase experiments were used to detect expression of GPER, HIF-1α, VEGF, and MMP9 in ESCs. E2 and G1 were used as agonists of GPER while G15 as an antagonist. Migration of ESCs and endothelial tube formation of HUVECs cultured in medium collected from ESCs were measured. Results Protein levels of GPER and HIF-1α were higher in EuEM than in CoEM. HIF-1α protein levels but not HIF-1α mRNA levels increased concurrently with GPER after E2 and G1 treatment. Furthermore, expression and activity of VEGF and MMP9 increased under E2 and G1 stimulation. However these effects disappeared when GPER was blocked. Conclusion GPER stabilizes HIF-1α thus promotes HIF-1α induced vascular endothelial growth factor (VEGF) and matrix metalloproteinase 9 (MMP9) in ESCs, which plays critical roles in endometriosis. PMID:27939762

Integrative analysis identifies targetable CREB1/FoxA1 transcriptional co-regulation as a predictor of prostate cancer recurrence.

PubMed

Sunkel, Benjamin; Wu, Dayong; Chen, Zhong; Wang, Chiou-Miin; Liu, Xiangtao; Ye, Zhenqing; Horning, Aaron M; Liu, Joseph; Mahalingam, Devalingam; Lopez-Nicora, Horacio; Lin, Chun-Lin; Goodfellow, Paul J; Clinton, Steven K; Jin, Victor X; Chen, Chun-Liang; Huang, Tim H-M; Wang, Qianben

2016-05-19

Identifying prostate cancer-driving transcription factors (TFs) in addition to the androgen receptor promises to improve our ability to effectively diagnose and treat this disease. We employed an integrative genomics analysis of master TFs CREB1 and FoxA1 in androgen-dependent prostate cancer (ADPC) and castration-resistant prostate cancer (CRPC) cell lines, primary prostate cancer tissues and circulating tumor cells (CTCs) to investigate their role in defining prostate cancer gene expression profiles. Combining genome-wide binding site and gene expression profiles we define CREB1 as a critical driver of pro-survival, cell cycle and metabolic transcription programs. We show that CREB1 and FoxA1 co-localize and mutually influence each other's binding to define disease-driving transcription profiles associated with advanced prostate cancer. Gene expression analysis in human prostate cancer samples found that CREB1/FoxA1 target gene panels predict prostate cancer recurrence. Finally, we showed that this signaling pathway is sensitive to compounds that inhibit the transcription co-regulatory factor MED1. These findings not only reveal a novel, global transcriptional co-regulatory function of CREB1 and FoxA1, but also suggest CREB1/FoxA1 signaling is a targetable driver of prostate cancer progression and serves as a biomarker of poor clinical outcomes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

PubMed

Deveci, Mehmet; Küçüktunç, Onur; Eren, Kemal; Bozdağ, Doruk; Kaya, Kamer; Çatalyürek, Ümit V

2016-01-01

Rapid development and increasing popularity of gene expression microarrays have resulted in a number of studies on the discovery of co-regulated genes. One important way of discovering such co-regulations is the query-based search since gene co-expressions may indicate a shared role in a biological process. Although there exist promising query-driven search methods adapting clustering, they fail to capture many genes that function in the same biological pathway because microarray datasets are fraught with spurious samples or samples of diverse origin, or the pathways might be regulated under only a subset of samples. On the other hand, a class of clustering algorithms known as biclustering algorithms which simultaneously cluster both the items and their features are useful while analyzing gene expression data, or any data in which items are related in only a subset of their samples. This means that genes need not be related in all samples to be clustered together. Because many genes only interact under specific circumstances, biclustering may recover the relationships that traditional clustering algorithms can easily miss. In this chapter, we briefly summarize the literature using biclustering for querying co-regulated genes. Then we present a novel biclustering approach and evaluate its performance by a thorough experimental analysis.

TCR-pMHC encounter differentially regulates transcriptomes of tissue-resident CD8 T cells.

PubMed

Yoshizawa, Akihiro; Bi, Kevin; Keskin, Derin B; Zhang, Guanglan; Reinhold, Bruce; Reinherz, Ellis L

2018-01-01

To investigate the role of TCR-pMHC interaction in regulating lung CD8 tissue-resident T cell (T R ) differentiation, polyclonal responses were compared against NP 366-374 /D b and PA 224-233 /D b , two immunodominant epitopes that arise during influenza A infection in mice. Memory niches distinct from iBALTs develop within the lamina propria, supporting CD103 + and CD103 - CD8 T R generation and intraepithelial translocation. Gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) identify dominant TCR, adherens junction, RIG-I-like and NOD-like pattern recognition receptor as well as TGF-β signaling pathways and memory signatures among PA 224-233 /D b T cells consistent with T resident memory (T RM ) status. In contrast, NP 366-374 /D b T cells exhibit enrichment of effector signatures, upregulating pro-inflammatory mediators even among T RM . While NP 366-374 /D b T cells manifest transcripts linked to canonical exhaustion pathways, PA 224-233 /D b T cells exploit P2rx7 purinoreceptor attenuation. The NP 366-374 /D b CD103 + subset expresses the antimicrobial lactotransferrin whereas PA 224-233 /D b CD103 + utilizes pore-forming mpeg-1, with <22% of genes correspondingly upregulated in CD103 + (or CD103 - ) subsets of both specificities. Thus, TCR-pMHC interactions among T R and antigen presenting cells in a tissue milieu strongly impact CD8 T cell biology. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From SNP co-association to RNA co-expression: novel insights into gene networks for intramuscular fatty acid composition in porcine.

PubMed

Ramayo-Caldas, Yuliaxis; Ballester, Maria; Fortes, Marina R S; Esteve-Codina, Anna; Castelló, Anna; Noguera, Jose L; Fernández, Ana I; Pérez-Enciso, Miguel; Reverter, Antonio; Folch, Josep M

2014-03-26

Fatty acids (FA) play a critical role in energy homeostasis and metabolic diseases; in the context of livestock species, their profile also impacts on meat quality for healthy human consumption. Molecular pathways controlling lipid metabolism are highly interconnected and are not fully understood. Elucidating these molecular processes will aid technological development towards improvement of pork meat quality and increased knowledge of FA metabolism, underpinning metabolic diseases in humans. The results from genome-wide association studies (GWAS) across 15 phenotypes were subjected to an Association Weight Matrix (AWM) approach to predict a network of 1,096 genes related to intramuscular FA composition in pigs. To identify the key regulators of FA metabolism, we focused on the minimal set of transcription factors (TF) that the explored the majority of the network topology. Pathway and network analyses pointed towards a trio of TF as key regulators of FA metabolism: NCOA2, FHL2 and EP300. Promoter sequence analyses confirmed that these TF have binding sites for some well-know regulators of lipid and carbohydrate metabolism. For the first time in a non-model species, some of the co-associations observed at the genetic level were validated through co-expression at the transcriptomic level based on real-time PCR of 40 genes in adipose tissue, and a further 55 genes in liver. In particular, liver expression of NCOA2 and EP300 differed between pig breeds (Iberian and Landrace) extreme in terms of fat deposition. Highly clustered co-expression networks in both liver and adipose tissues were observed. EP300 and NCOA2 showed centrality parameters above average in the both networks. Over all genes, co-expression analyses confirmed 28.9% of the AWM predicted gene-gene interactions in liver and 33.0% in adipose tissue. The magnitude of this validation varied across genes, with up to 60.8% of the connections of NCOA2 in adipose tissue being validated via co-expression. Our results recapitulate the known transcriptional regulation of FA metabolism, predict gene interactions that can be experimentally validated, and suggest that genetic variants mapped to EP300, FHL2, and NCOA2 modulate lipid metabolism and control energy homeostasis in pigs.

A synthetic system for expression of components of a bacterial microcompartment.

PubMed

Sargent, Frank; Davidson, Fordyce A; Kelly, Ciarán L; Binny, Rachelle; Christodoulides, Natasha; Gibson, David; Johansson, Emelie; Kozyrska, Katarzyna; Lado, Lucia Licandro; Maccallum, Jane; Montague, Rachel; Ortmann, Brian; Owen, Richard; Coulthurst, Sarah J; Dupuy, Lionel; Prescott, Alan R; Palmer, Tracy

2013-11-01

In general, prokaryotes are considered to be single-celled organisms that lack internal membrane-bound organelles. However, many bacteria produce proteinaceous microcompartments that serve a similar purpose, i.e. to concentrate specific enzymic reactions together or to shield the wider cytoplasm from toxic metabolic intermediates. In this paper, a synthetic operon encoding the key structural components of a microcompartment was designed based on the genes for the Salmonella propanediol utilization (Pdu) microcompartment. The genes chosen included pduA, -B, -J, -K, -N, -T and -U, and each was shown to produce protein in an Escherichia coli chassis. In parallel, a set of compatible vectors designed to express non-native cargo proteins was also designed and tested. Engineered hexa-His tags allowed isolation of the components of the microcompartments together with co-expressed, untagged, cargo proteins. Finally, an in vivo protease accessibility assay suggested that a PduD-GFP fusion could be protected from proteolysis when co-expressed with the synthetic microcompartment operon. This work gives encouragement that it may be possible to harness the genes encoding a non-native microcompartment for future biotechnological applications.

A Kinome-Wide Small Interfering RNA Screen Identifies Proviral and Antiviral Host Factors in Severe Acute Respiratory Syndrome Coronavirus Replication, Including Double-Stranded RNA-Activated Protein Kinase and Early Secretory Pathway Proteins

PubMed Central

de Wilde, Adriaan H.; Wannee, Kazimier F.; Scholte, Florine E. M.; Goeman, Jelle J.; ten Dijke, Peter; Snijder, Eric J.

2015-01-01

ABSTRACT To identify host factors relevant for severe acute respiratory syndrome-coronavirus (SARS-CoV) replication, we performed a small interfering RNA (siRNA) library screen targeting the human kinome. Protein kinases are key regulators of many cellular functions, and the systematic knockdown of their expression should provide a broad perspective on factors and pathways promoting or antagonizing coronavirus replication. In addition to 40 proteins that promote SARS-CoV replication, our study identified 90 factors exhibiting an antiviral effect. Pathway analysis grouped subsets of these factors in specific cellular processes, including the innate immune response and the metabolism of complex lipids, which appear to play a role in SARS-CoV infection. Several factors were selected for in-depth validation in follow-up experiments. In cells depleted for the β2 subunit of the coatomer protein complex (COPB2), the strongest proviral hit, we observed reduced SARS-CoV protein expression and a >2-log reduction in virus yield. Knockdown of the COPB2-related proteins COPB1 and Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF1) also suggested that COPI-coated vesicles and/or the early secretory pathway are important for SARS-CoV replication. Depletion of the antiviral double-stranded RNA-activated protein kinase (PKR) enhanced virus replication in the primary screen, and validation experiments confirmed increased SARS-CoV protein expression and virus production upon PKR depletion. In addition, cyclin-dependent kinase 6 (CDK6) was identified as a novel antiviral host factor in SARS-CoV replication. The inventory of pro- and antiviral host factors and pathways described here substantiates and expands our understanding of SARS-CoV replication and may contribute to the identification of novel targets for antiviral therapy. IMPORTANCE Replication of all viruses, including SARS-CoV, depends on and is influenced by cellular pathways. Although substantial progress has been made in dissecting the coronavirus replicative cycle, our understanding of the host factors that stimulate (proviral factors) or restrict (antiviral factors) infection remains far from complete. To study the role of host proteins in SARS-CoV infection, we set out to systematically identify kinase-regulated processes that influence virus replication. Protein kinases are key regulators in signal transduction, controlling a wide variety of cellular processes, and many of them are targets of approved drugs and other compounds. Our screen identified a variety of hits and will form the basis for more detailed follow-up studies that should contribute to a better understanding of SARS-CoV replication and coronavirus-host interactions in general. The identified factors could be interesting targets for the development of host-directed antiviral therapy to treat infections with SARS-CoV or other pathogenic coronaviruses. PMID:26041291

Integration of co-localized glandular morphometry and protein biomarker expression in immunofluorescent images for prostate cancer prognosis

NASA Astrophysics Data System (ADS)

Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

2015-03-01

Immunofluorescent (IF) image analysis of tissue pathology has proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. However, while biomarker and glandular morphometric features have been combined as separate predictors in multivariate models, there is a lack of integrative features for biomarkers co-localized within specific morphological sub-types; for example the evaluation of androgen receptor (AR) expression within Gleason 3 glands only. In this work we propose a novel framework employing multiple techniques to generate integrated metrics of morphology and biomarker expression. We demonstrate the utility of the approaches in predicting clinical disease progression in images from 326 prostate biopsies and 373 prostatectomies. Our proposed integrative approaches yield significant improvements over existing IF image feature metrics. This work presents some of the first algorithms for generating innovative characteristics in tissue diagnostics that integrate co-localized morphometry and protein biomarker expression.

New Tools for Comparing Microscopy Images: Quantitative Analysis of Cell Types in Bacillus subtilis

PubMed Central

van Gestel, Jordi; Vlamakis, Hera

2014-01-01

Fluorescence microscopy is a method commonly used to examine individual differences between bacterial cells, yet many studies still lack a quantitative analysis of fluorescence microscopy data. Here we introduce some simple tools that microbiologists can use to analyze and compare their microscopy images. We show how image data can be converted to distribution data. These data can be subjected to a cluster analysis that makes it possible to objectively compare microscopy images. The distribution data can further be analyzed using distribution fitting. We illustrate our methods by scrutinizing two independently acquired data sets, each containing microscopy images of a doubly labeled Bacillus subtilis strain. For the first data set, we examined the expression of srfA and tapA, two genes which are expressed in surfactin-producing and matrix-producing cells, respectively. For the second data set, we examined the expression of eps and tapA; these genes are expressed in matrix-producing cells. We show that srfA is expressed by all cells in the population, a finding which contrasts with a previously reported bimodal distribution of srfA expression. In addition, we show that eps and tapA do not always have the same expression profiles, despite being expressed in the same cell type: both operons are expressed in cell chains, while single cells mainly express eps. These findings exemplify that the quantification and comparison of microscopy data can yield insights that otherwise would go unnoticed. PMID:25448819

New tools for comparing microscopy images: quantitative analysis of cell types in Bacillus subtilis.

PubMed

van Gestel, Jordi; Vlamakis, Hera; Kolter, Roberto

2015-02-15

Fluorescence microscopy is a method commonly used to examine individual differences between bacterial cells, yet many studies still lack a quantitative analysis of fluorescence microscopy data. Here we introduce some simple tools that microbiologists can use to analyze and compare their microscopy images. We show how image data can be converted to distribution data. These data can be subjected to a cluster analysis that makes it possible to objectively compare microscopy images. The distribution data can further be analyzed using distribution fitting. We illustrate our methods by scrutinizing two independently acquired data sets, each containing microscopy images of a doubly labeled Bacillus subtilis strain. For the first data set, we examined the expression of srfA and tapA, two genes which are expressed in surfactin-producing and matrix-producing cells, respectively. For the second data set, we examined the expression of eps and tapA; these genes are expressed in matrix-producing cells. We show that srfA is expressed by all cells in the population, a finding which contrasts with a previously reported bimodal distribution of srfA expression. In addition, we show that eps and tapA do not always have the same expression profiles, despite being expressed in the same cell type: both operons are expressed in cell chains, while single cells mainly express eps. These findings exemplify that the quantification and comparison of microscopy data can yield insights that otherwise would go unnoticed. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy.

PubMed

O'Reilly, Paul; Ortutay, Csaba; Gernon, Grainne; O'Connell, Enda; Seoighe, Cathal; Boyce, Susan; Serrano, Luis; Szegezdi, Eva

2014-12-19

Identification of differentially expressed genes from transcriptomic studies is one of the most common mechanisms to identify tumor biomarkers. This approach however is not well suited to identify interaction between genes whose protein products potentially influence each other, which limits its power to identify molecular wiring of tumour cells dictating response to a drug. Due to the fact that signal transduction pathways are not linear and highly interlinked, the biological response they drive may be better described by the relative amount of their components and their functional relationships than by their individual, absolute expression. Gene expression microarray data for 109 tumor cell lines with known sensitivity to the death ligand cytokine tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) was used to identify genes with potential functional relationships determining responsiveness to TRAIL-induced apoptosis. The machine learning technique Random Forest in the statistical environment "R" with backward elimination was used to identify the key predictors of TRAIL sensitivity and differentially expressed genes were identified using the software GeneSpring. Gene co-regulation and statistical interaction was assessed with q-order partial correlation analysis and non-rejection rate. Biological (functional) interactions amongst the co-acting genes were studied with Ingenuity network analysis. Prediction accuracy was assessed by calculating the area under the receiver operator curve using an independent dataset. We show that the gene panel identified could predict TRAIL-sensitivity with a very high degree of sensitivity and specificity (AUC=0·84). The genes in the panel are co-regulated and at least 40% of them functionally interact in signal transduction pathways that regulate cell death and cell survival, cellular differentiation and morphogenesis. Importantly, only 12% of the TRAIL-predictor genes were differentially expressed highlighting the importance of functional interactions in predicting the biological response. The advantage of co-acting gene clusters is that this analysis does not depend on differential expression and is able to incorporate direct- and indirect gene interactions as well as tissue- and cell-specific characteristics. This approach (1) identified a descriptor of TRAIL sensitivity which performs significantly better as a predictor of TRAIL sensitivity than any previously reported gene signatures, (2) identified potential novel regulators of TRAIL-responsiveness and (3) provided a systematic view highlighting fundamental differences between the molecular wiring of sensitive and resistant cell types.

Gene expression analysis of colorectal cancer by bioinformatics strategy.

PubMed

Cui, Meng; Yuan, Junhua; Li, Jun; Sun, Bing; Li, Tao; Li, Yuantao; Wu, Guoliang

2014-10-01

We used bioinformatics technology to analyze gene expression profiles involved in colorectal cancer tissue samples and healthy controls. In this paper, we downloaded the gene expression profile GSE4107 from Gene Expression Omnibus (GEO) database, in which a total of 22 chips were available, including normal colonic mucosa tissue from normal healthy donors (n=10), colorectal cancer tissue samples from colorectal patients (n=33). To further understand the biological functions of the screened DGEs, the KEGG pathway enrichment analysis were conducted. Then we built a transcriptome network to study differentially co-expressed links. A total of 3151 DEGs of CRC were selected. Besides, total 164 DCGs (Differentially Coexpressed Gene, DCG) and 29279 DCLs (Differentially Co-expressed Link, DCL) were obtained. Furthermore, the significantly enriched KEGG pathways were Endocytosis, Calcium signaling pathway, Vascular smooth muscle contraction, Linoleic acid metabolism, Arginine and proline metabolism, Inositol phosphate metabolism and MAPK signaling pathway. Our results show that the generation of CRC involves multiple genes, TFs and pathways. Several signal and immune pathways are linked to CRC and give us more clues in the process of CRC. Hence, our work would pave ways for novel diagnosis of CRC, and provided theoretical guidance into cancer therapy.

Effects of lithium on growth, maturation, reproduction and gene expression in the nematode Caenorhabditis elegans.

PubMed

Inokuchi, Ayako; Yamamoto, Ryoko; Morita, Fumiyo; Takumi, Shota; Matsusaki, Hiromi; Ishibashi, Hiroshi; Tominaga, Nobuaki; Arizono, Koji

2015-09-01

Lithium (Li) has been widely used to treat bipolar disorder, and industrial use of Li has been increasing; thus, environmental pollution and ecological impacts of Li have become a concern. This study was conducted to clarify the potential biological effects of LiCl and Li(2)CO(3) on a nematode, Caenorhabditis elegans as a model system for evaluating soil contaminated with Li. Exposure of C. elegans to LiCl and Li(2)CO(3) decreased growth/maturation and reproduction. The lowest observed effect concentrations for growth, maturation and reproduction were 1250, 313 and 10 000 µm, respectively, for LiCl and 750, 750 and 3000 µm, respectively, for Li(2)CO(3). We also investigated the physiological function of LiCl and LiCO(3) in C. elegans using DNA microarray analysis as an eco-toxicogenomic approach. Among approximately 300 unique genes, including metabolic genes, the exposure to 78 µm LiCl downregulated the expression of 36 cytochrome P450, 16 ABC transporter, 10 glutathione S-transferase, 16 lipid metabolism and two vitellogenin genes. On the other hand, exposure to 375 µm Li(2)CO(3) downregulated the expression of 11 cytochrome P450, 13 ABC transporter, 13 lipid metabolism and one vitellogenin genes. No gene was upregulated by LiCl or Li(2)CO(3). These results suggest that LiCl and Li(2)CO(3) potentially affect the biological and physiological function in C. elegans associated with alteration of the gene expression such as metabolic genes. Our data also provide experimental support for the utility of toxicogenomics by integrating gene expression profiling into a toxicological study of an environmentally important organism such as C. elegans. Copyright © 2015 John Wiley & Sons, Ltd.

Ubiquitin ligase ATL31 functions in leaf senescence in response to the balance between atmospheric CO2 and nitrogen availability in Arabidopsis.

PubMed

Aoyama, Shoki; Huarancca Reyes, Thais; Guglielminetti, Lorenzo; Lu, Yu; Morita, Yoshie; Sato, Takeo; Yamaguchi, Junji

2014-02-01

Carbon (C) and nitrogen (N) are essential elements for metabolism, and their availability, called the C/N balance, must be tightly coordinated for optimal growth in plants. Previously, we have identified the ubiquitin ligase CNI1/ATL31 as a novel C/N regulator by screening plants grown on C/N stress medium containing excess sugar and limited N. To elucidate further the effect of C/N balance on plant growth and to determine the physiological function of ATL31, we performed C/N response analysis using an atmospheric CO2 manipulation system. Under conditions of elevated CO2 and sufficient N, plant biomass and total sugar and starch dramatically increased. In contrast, elevated CO2 with limited N did not increase plant biomass but promoted leaf chlorosis, with anthocyanin accumulation and increased senescence-associated gene expression. Similar results were obtained with plants grown in medium containing excess sugar and limited N, suggesting that disruption of the C/N balance affects senescence progression. In ATL31-overexpressing plants, promotion of senescence under disrupted CO2/N conditions was repressed, whereas in the loss-of-function mutant it was enhanced. The ATL31 gene was transcriptionally up-regulated under N deficiency and in senescent leaves, and ATL31 expression was highly correlated with WRKY53 expression, a key regulator of senescence. Furthermore, transient protoplast analysis implicated the direct activation of ATL31 expression by WRKY53, which was in accordance with the results of WRKY53 overexpression experiments. Together, these results demonstrate the importance of C/N balance in leaf senescence and the involvement of ubiquitin ligase ATL31 in the process of senescence in Arabidopsis.

An Ultra-High Fluorescence Enhancement and High Throughput Assay for Revealing Expression and Internalization of Chemokine Receptor CXCR4.

PubMed

He, Hua; Wang, Xiaojuan; Cheng, Tiantian; Xia, Yongqing; Lao, Jun; Ge, Baosheng; Ren, Hao; Khan, Naseer Ullah; Huang, Fang

2016-04-18

Revealing chemokine receptor CXCR4 expression, distribution, and internalization levels in different cancers helps to evaluate cancer progression or prognosis and to set personalized treatment strategy. We here describe a sensitive and high-throughput immunoassay for determining CXCR4 expression and distribution in cancer cells. The assay is accessible to a wide range of users in an ordinary lab only by dip-coating poly(styrene-co-N-isopropylacrylamide) spheres on the glass substrate. The self- assembled spheres form three-dimensional photonic colloidal crystals which enhance the fluorescence of CF647 and Alexa Fluor 647 by a factor of up to 1000. CXCR4 in cells is detected by using the sandwich immunoassay, where the primary antibody recognizes CXCR4 and the secondary antibody is labeled with CF647. With the newly established assay, we quantified the total expression of CXCR4, its distribution on the cell membrane and cytoplasm, and revealed their internalization level upon SDF-1α activation in various cancer cells, even for those with extremely low expression level. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions.

PubMed

Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy

2014-01-16

The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers.

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

PubMed Central

2014-01-01

Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. Conclusions The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers. PMID:24433256

Visual gene-network analysis reveals the cancer gene co-expression in human endometrial cancer

PubMed Central

2014-01-01

Background Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments. Results ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. Conclusions The results of this study provide a powerful biomarker discovery platform to better understand the progression of ECs and to uncover potential therapeutic targets in the treatment of ECs. This information might lead to improved monitoring of ECs and resulting improvement of treatment of ECs, the 4th most common of cancer in women. PMID:24758163

Targeted Integration of RNA-Seq and Metabolite Data to Elucidate Curcuminoid Biosynthesis in Four Curcuma Species.

PubMed

Li, Donghan; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Ohta, Daisaku; Suzuki, Hideyuki; Arita, Masanori; Tanaka, Ken; Ma, Zhiqiang; Kanaya, Shigehiko

2015-05-01

Curcuminoids, namely curcumin and its analogs, are secondary metabolites that act as the primary active constituents of turmeric (Curcuma longa). The contents of these curcuminoids vary among species in the genus Curcuma. For this reason, we compared two wild strains and two cultivars to understand the differences in the synthesis of curcuminoids. Because the fluxes of metabolic reactions depend on the amounts of their substrate and the activity of the catalysts, we analyzed the metabolite concentrations and gene expression of related enzymes. We developed a method based on RNA sequencing (RNA-Seq) analysis that focuses on a specific set of genes to detect expression differences between species in detail. We developed a 'selection-first' method for RNA-Seq analysis in which short reads are mapped to selected enzymes in the target biosynthetic pathways in order to reduce the effect of mapping errors. Using this method, we found that the difference in the contents of curcuminoids among the species, as measured by gas chromatography-mass spectrometry, could be explained by the changes in the expression of genes encoding diketide-CoA synthase, and curcumin synthase at the branching point of the curcuminoid biosynthesis pathway. © 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.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

A caspase-2-RFXANK interaction and its implication for MHC class II expression.

PubMed

Forsberg, Jeremy; Li, Xinge; Akpinar, Birce; Salvatori, Roger; Ott, Martin; Zhivotovsky, Boris; Olsson, Magnus

2018-01-23

Despite recent achievements implicating caspase-2 in tumor suppression, the enzyme stands out from the apoptotic caspase family as a factor whose function requires further clarification. To specify enzyme characteristics through the definition of interacting proteins in apoptotic or non-apoptotic settings, a yeast 2-hybrid (Y2H) screen was performed using the full-length protein as bait. The current report describes the analysis of a captured prey and putative novel caspase-2 interacting factor, the regulatory factor X-associated ankyrin-containing protein (RFXANK), previously associated with CIITA, the transactivator regulating cell-type specificity and inducibility of MHC class II gene expression. The interaction between caspase-2 and RFXANK was verified by co-immunoprecipitations using both exogenous and endogenous proteins, where the latter approach suggested that binding of the components occurs in the cytoplasm. Cellular co-localization was confirmed by transfection of fluorescently conjugated proteins. Enhanced caspase-2 processing in RFXANK-overexpressing HEK293T cells treated with chemotherapeutic agents further supported Y2H data. Yet, no distinct differences with respect to MHC class II expression were observed in plasma membranes of antigen-presenting cells derived from wild type and caspase-2 -/- mice. In contrast, increased levels of the total MHC class II protein was evident in protein lysates from caspase-2 RNAi-silenced leukemia cell lines and B-cells isolated from gene-targeted mice. Together, these data identify a novel caspase-2-interacting factor, RFXANK, and indicate a potential non-apoptotic role for the enzyme in the control of MHC class II gene regulation.

Phenotypic and transcriptional response to selection for alcohol sensitivity in Drosophila melanogaster

PubMed Central

Morozova, Tatiana V; Anholt, Robert RH; Mackay, Trudy FC

2007-01-01

Background Alcoholism is a complex disorder determined by interactions between genetic and environmental risk factors. Drosophila represents a powerful model system to dissect the genetic architecture of alcohol sensitivity, as large numbers of flies can readily be reared in defined genetic backgrounds and under controlled environmental conditions. Furthermore, flies exposed to ethanol undergo physiological and behavioral changes that resemble human alcohol intoxication, including loss of postural control, sedation, and development of tolerance. Results We performed artificial selection for alcohol sensitivity for 35 generations and created duplicate selection lines that are either highly sensitive or resistant to ethanol exposure along with unselected control lines. We used whole genome expression analysis to identify 1,678 probe sets with different expression levels between the divergent lines, pooled across replicates, at a false discovery rate of q < 0.001. We assessed to what extent genes with altered transcriptional regulation might be causally associated with ethanol sensitivity by measuring alcohol sensitivity of 37 co-isogenic P-element insertional mutations in 35 candidate genes, and found that 32 of these mutants differed in sensitivity to ethanol exposure from their co-isogenic controls. Furthermore, 23 of these novel genes have human orthologues. Conclusion Combining whole genome expression profiling with selection for genetically divergent lines is an effective approach for identifying candidate genes that affect complex traits, such as alcohol sensitivity. Because of evolutionary conservation of function, it is likely that human orthologues of genes affecting alcohol sensitivity in Drosophila may contribute to alcohol-associated phenotypes in humans. PMID:17973985

Comparison of upper tropospheric carbon monoxide from MOPITT, ACE-FTS, and HIPPO-QCLS

NASA Astrophysics Data System (ADS)

Martínez-Alonso, Sara; Deeter, Merritt N.; Worden, Helen M.; Gille, John C.; Emmons, Louisa K.; Pan, Laura L.; Park, Mijeong; Manney, Gloria L.; Bernath, Peter F.; Boone, Chris D.; Walker, Kaley A.; Kolonjari, Felicia; Wofsy, Steven C.; Pittman, Jasna; Daube, Bruce C.

2014-12-01

Products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument are regularly validated using in situ airborne measurements. However, few of these measurements reach into the upper troposphere, thus hindering MOPITT validation in that region. Here we evaluate upper tropospheric (~500 hPa to the tropopause) MOPITT CO profiles by comparing them to satellite Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) retrievals and to measurements from the High-performance Instrumented Airborne Platform for Environmental Research Pole to Pole Observations (HIPPO) Quantum Cascade Laser Spectrometer (QCLS). Direct comparison of colocated v5 MOPITT thermal infrared-only retrievals, v3.0 ACE-FTS retrievals, and HIPPO-QCLS measurements shows a slight positive MOPITT CO bias within its 10% accuracy requirement with respect to the other two data sets. Direct comparison of colocated ACE-FTS and HIPPO-QCLS measurements results in a small number of samples due to the large disparity in sampling pattern and density of these data sets. Thus, two additional indirect techniques for comparison of noncoincident data sets have been applied: tracer-tracer (CO-O3) correlation analysis and analysis of profiles in tropopause coordinates. These techniques suggest a negative bias of ACE-FTS with respect to HIPPO-QCLS; this could be caused by differences in resolution (horizontal, vertical) or by deficiencies in the ACE-FTS CO retrievals below ~20 km of altitude, among others. We also investigate the temporal stability of MOPITT and ACE-FTS data, which provide unique global CO records and are thus important in climate analysis. Our results indicate that the relative bias between the two data sets has remained generally stable during the 2004-2010 period.

Primary care patients reporting concerns about their gambling frequently have other co-occurring lifestyle and mental health issues

PubMed Central

Goodyear-Smith, Felicity; Arroll, Bruce; Kerse, Ngaire; Sullivan, Sean; Coupe, Nicole; Tse, Samson; Shepherd, Robin; Rossen, Fiona; Perese, Lana

2006-01-01

Background Problem gambling often goes undetected by family physicians but may be associated with stress-related medical problems as well as mental disorders and substance abuse. Family physicians are often first in line to identify these problems and to provide a proper referral. The aim of this study was to compare a group of primary care patients who identified concerns with their gambling behavior with the total population of screened patients in relation to co-morbidity of other lifestyle risk factors or mental health issues. Methods This is a cross sectional study comparing patients identified as worrying about their gambling behavior with the total screened patient population for co morbidity. The setting was 51 urban and rural New Zealand practices. Participants were consecutive adult patients per practice (N = 2,536) who completed a brief multi-item tool screening primary care patients for lifestyle risk factors and mental health problems (smoking, alcohol and drug misuse, problem gambling, depression, anxiety, abuse, anger). Data analysis used descriptive statistics and non-parametric binomial tests with adjusting for clustering by practitioner using STATA survey analysis. Results Approximately 3/100 (3%) answered yes to the gambling question. Those worried about gambling more likely to be male OR 1.85 (95% CI 1.1 to 3.1). Increasing age reduced likelihood of gambling concerns – logistic regression for complex survey data OR = 0.99 (CI 95% 0.97 to 0.99) p = 0.04 for each year older. Patients concerned about gambling were significantly more likely (all p < 0.0001) to have concerns about their smoking, use of recreational drugs, and alcohol. Similarly there were more likely to indicate problems with depression, anxiety and anger control. No significant relationship with gambling worries was found for abuse, physical inactivity or weight concerns. Patients expressing concerns about gambling were significantly more likely to want help with smoking, other drug use, depression and anxiety. Conclusion Our questionnaire identifies patients who express a need for help with gambling and other lifestyle and mental health issues. Screening for gambling in primary care has the potential to identify individuals with multiple co-occurring disorders. PMID:16606465

Comparison of normalization methods for differential gene expression analysis in RNA-Seq experiments

PubMed Central

Maza, Elie; Frasse, Pierre; Senin, Pavel; Bouzayen, Mondher; Zouine, Mohamed

2013-01-01

In recent years, RNA-Seq technologies became a powerful tool for transcriptome studies. However, computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. In particular, it is known that the choice of a normalization procedure leads to a great variability in results of differential gene expression analysis. The present study compares the most widespread normalization procedures and proposes a novel one aiming at removing an inherent bias of studied transcriptomes related to their relative size. Comparisons of the normalization procedures are performed on real and simulated data sets. Real RNA-Seq data sets analyses, performed with all the different normalization methods, show that only 50% of significantly differentially expressed genes are common. This result highlights the influence of the normalization step on the differential expression analysis. Real and simulated data sets analyses give similar results showing 3 different groups of procedures having the same behavior. The group including the novel method named “Median Ratio Normalization” (MRN) gives the lower number of false discoveries. Within this group the MRN method is less sensitive to the modification of parameters related to the relative size of transcriptomes such as the number of down- and upregulated genes and the gene expression levels. The newly proposed MRN method efficiently deals with intrinsic bias resulting from relative size of studied transcriptomes. Validation with real and simulated data sets confirmed that MRN is more consistent and robust than existing methods. PMID:26442135

The Renilla luciferase gene as a reference gene for normalization of gene expression in transiently transfected cells.

PubMed

Jiwaji, Meesbah; Daly, Rónán; Pansare, Kshama; McLean, Pauline; Yang, Jingli; Kolch, Walter; Pitt, Andrew R

2010-12-31

The importance of appropriate normalization controls in quantitative real-time polymerase chain reaction (qPCR) experiments has become more apparent as the number of biological studies using this methodology has increased. In developing a system to study gene expression from transiently transfected plasmids, it became clear that normalization using chromosomally encoded genes is not ideal, at it does not take into account the transfection efficiency and the significantly lower expression levels of the plasmids. We have developed and validated a normalization method for qPCR using a co-transfected plasmid. The best chromosomal gene for normalization in the presence of the transcriptional activators used in this study, cadmium, dexamethasone, forskolin and phorbol-12-myristate 13-acetate was first identified. qPCR data was analyzed using geNorm, Normfinder and BestKeeper. Each software application was found to rank the normalization controls differently with no clear correlation. Including a co-transfected plasmid encoding the Renilla luciferase gene (Rluc) in this analysis showed that its calculated stability was not as good as the optimised chromosomal genes, most likely as a result of the lower expression levels and transfection variability. Finally, we validated these analyses by testing two chromosomal genes (B2M and ActB) and a co-transfected gene (Rluc) under biological conditions. When analyzing co-transfected plasmids, Rluc normalization gave the smallest errors compared to the chromosomal reference genes. Our data demonstrates that transfected Rluc is the most appropriate normalization reference gene for transient transfection qPCR analysis; it significantly reduces the standard deviation within biological experiments as it takes into account the transfection efficiencies and has easily controllable expression levels. This improves reproducibility, data validity and most importantly, enables accurate interpretation of qPCR data.

The Influence of Plasma-Based Nitriding and Oxidizing Treatments on the Mechanical and Corrosion Properties of CoCrMo Biomedical Alloy

NASA Astrophysics Data System (ADS)

Noli, Fotini; Pichon, Luc; Öztürk, Orhan

2018-04-01

Plasma-based nitriding and/or oxidizing treatments were applied to CoCrMo alloy to improve its surface mechanical properties and corrosion resistance for biomedical applications. Three treatments were performed. A set of CoCrMo samples has been subjected to nitriding at moderate temperatures ( 400 °C). A second set of CoCrMo samples was oxidized at 395 °C in pure O2. The last set of CoCrMo samples was nitrided and subsequently oxidized under the experimental conditions of previous sets (double treatment). The microstructure and morphology of the layers formed on the CoCrMo alloy were investigated by X-ray diffraction, Atomic Force Microscopy, and Scanning Electron Microscopy. In addition, nitrogen and oxygen profiles were determined by Glow Discharge Optical Emission Spectroscopy, Rutherford Backscattering Spectroscopy, Energy-Dispersive X-ray, and Nuclear Reaction Analysis. Significant improvement of the Vickers hardness of the CoCrMo samples after plasma nitriding was observed due to the supersaturated nitrogen solution and the formation of an expanded FCC γ N phase and CrN precipitates. In the case of the oxidized samples, Vickers hardness improvement was minimal. The corrosion behavior of the samples was investigated in simulated body fluid (0.9 pct NaCl solution at 37 °C) using electrochemical techniques (potentiodynamic polarization and cyclic voltammetry). The concentration of metal ions released from the CoCrMo surfaces was determined by Instrumental Neutron Activation Analysis. The experimental results clearly indicate that the CoCrMo surface subjected to the double surface treatment consisting in plasma nitriding and plasma oxidizing exhibited lower deterioration and better resistance to corrosion compared to the nitrided, oxidized, and untreated samples. This enhancement is believed to be due to the formation of a thicker and more stable layer.

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

PubMed

Priest, Henry D; Fox, Samuel E; Rowley, Erik R; Murray, Jessica R; Michael, Todd P; Mockler, Todd C

2014-01-01

Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

Anther-preferential expressing gene PMR is essential for the mitosis of pollen development in rice.

PubMed

Liu, Yaqin; Xu, Ya; Ling, Sheng; Liu, Shasha; Yao, Jialing

2017-06-01

Phenotype identification, expression examination, and function prediction declared that the anther-preferential expressing gene PMR may participate in regulation of male gametophyte development in rice. Male germline development in flowering plants produces the pair of sperm cells for double fertilization and the pollen mitosis is a key process of it. Although the structural features of male gametophyte have been defined, the molecular mechanisms regulating the mitotic cell cycle are not well elucidated in rice. Here, we reported an anther-preferential expressing gene in rice, PMR (Pollen Mitosis Relative), playing an essential role in male gametogenesis. When PMR gene was suppressed via RNAi, the mitosis of microspore was severely damaged, and the plants formed unmatured pollens containing only one or two nucleuses at the anthesis, ultimately leading to serious reduction of pollen fertility and seed-setting. The CRISPR mutants, pmr-1 and pmr-2, both showed the similar defects as the PMR-RNAi lines. Further analysis revealed that PMR together with its co-expressing genes were liable to participate in the regulation of DNA metabolism in the nucleus, and affected the activities of some enzymes related to the cell cycle. We finally discussed that unknown protein PMR contained the PHD, SWIB and Plus-3 domains and they might have coordinating functions in regulation pathway of the pollen mitosis in rice.

Microbial co-culturing systems: butanol production from organic wastes through consolidated bioprocessing.

PubMed

Jiang, Yujia; Zhang, Ting; Lu, Jiasheng; Dürre, Peter; Zhang, Wenming; Dong, Weiliang; Zhou, Jie; Jiang, Min; Xin, Fengxue

2018-05-07

Biobutanol can be indigenously synthesized by solventogenic Clostridium species; however, these microorganisms possess inferior capability of utilizing abundant and renewable organic wastes, such as starch, lignocellulose, and even syngas. The common strategy to achieve direct butanol production from these organic wastes is through genetic modification of wild-type strains. However, due to the complex of butanol synthetic and hydrolytic enzymes expression systems, the recombinants show unsatisfactory results. Recently, setting up microbial co-culturing systems became more attractive, as they could not only perform more complicated tasks, but also endure changeable environments. Hence, this mini-review comprehensively summarized the state-of-the-art biobutanol production from different substrates by using microbial co-culturing systems. Furthermore, strategies regarding establishment principles of microbial co-culturing systems were also analyzed and compared.

Experimental verification of cleavage characteristic stress vs grain size

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

Lei, W.; Li, D.; Yao, M.

Instead of the accepted cleavage fracture stress [sigma][sub f] proposed by Knott et al, a new parameter S[sub co], named as ''cleavage characteristic stress,'' has been recently recommended to characterize the microscopic resistance to cleavage fracture. To give a definition, S[sub co] is the fracture stress at the brittle/ductile transition temperature of steels in plain tension, below which the yield strength approximately equals the true fracture stress combined with an abrupt curtailment of ductility. By considering a single-grain microcrack arrested at a boundary, Huang and Yao set up an expression of S[sub co] as a function of grain size. Themore » present work was arranged to provide an experimental verification of S[sub co] vs grain size.« less

MicroRNA expression profiling in alveolar macrophages of indigenous Chinese Tongcheng pigs infected with PRRSV in vivo.

PubMed

Zhou, Xiang; Michal, Jennifer J; Jiang, Zhihua; Liu, Bang

2017-11-01

Porcine respiratory and reproductive syndrome (PRRS), caused by PRRS virus (PRRSV), is one of the most serious infectious diseases in the swine industry worldwide. Indigenous Chinese Tongcheng (TC) pigs reportedly show strong resistance to PRRSV infection. The miRNA expression profiles of porcine alveolar macrophages (PAMs) of control TC pigs and those infected with PRRSV in vivo were analyzed by high-throughput sequencing to explore changes induced by infection. A total of 182 known miRNAs including 101 miRNA-5p and 81 miRNA-3p were identified with 23 up-regulated differentially expressed miRNAs (DEmiRNAs) and 25 down-regulated DEmiRNAs. Gene Ontology analysis showed that predicted target genes for the DEmiRNAs were enriched in immune response, transcription regulation, and cell death. The integrative analysis of mRNA and miRNA expression revealed that down-regulated methylation-related genes (DNMT1 and DNMT3b) were targeted by five up-regulated DEmiRNAs. Furthermore, 35 pairs of miRNAs (70 miRNAs) were co-expressed after PRRSV infection and six pairs were co-expressed differently. Our results describe miRNA expression profiles of TC pigs in response to PRRSV infection and lay a strong foundation for developing novel therapies to control PRRS in pigs.

An atlas of gene expression and gene co-regulation in the human retina.

PubMed

Pinelli, Michele; Carissimo, Annamaria; Cutillo, Luisa; Lai, Ching-Hung; Mutarelli, Margherita; Moretti, Maria Nicoletta; Singh, Marwah Veer; Karali, Marianthi; Carrella, Diego; Pizzo, Mariateresa; Russo, Francesco; Ferrari, Stefano; Ponzin, Diego; Angelini, Claudia; Banfi, Sandro; di Bernardo, Diego

2016-07-08

The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it). © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Oncoprotein HBXIP enhances HOXB13 acetylation and co-activates HOXB13 to confer tamoxifen resistance in breast cancer.

PubMed

Liu, Bowen; Wang, Tianjiao; Wang, Huawei; Zhang, Lu; Xu, Feifei; Fang, Runping; Li, Leilei; Cai, Xiaoli; Wu, Yue; Zhang, Weiying; Ye, Lihong

2018-02-23

Resistance to tamoxifen (TAM) frequently occurs in the treatment of estrogen receptor positive (ER+) breast cancer. Accumulating evidences indicate that transcription factor HOXB13 is of great significance in TAM resistance. However, the regulation of HOXB13 in TAM-resistant breast cancer remains largely unexplored. Here, we were interested in the potential effect of HBXIP, an oncoprotein involved in the acceleration of cancer progression, on the modulation of HOXB13 in TAM resistance of breast cancer. The Kaplan-Meier plotter cancer database and GEO dataset were used to analyze the association between HBXIP expression and relapse-free survival. The correlation of HBXIP and HOXB13 in ER+ breast cancer was assessed by human tissue microarray. Immunoblotting analysis, qRT-PCR assay, immunofluorescence staining, Co-IP assay, ChIP assay, luciferase reporter gene assay, cell viability assay, and colony formation assay were performed to explore the possible molecular mechanism by which HBXIP modulates HOXB13. Cell viability assay, xenograft assay, and immunohistochemistry staining analysis were utilized to evaluate the effect of the HBXIP/HOXB13 axis on the facilitation of TAM resistance in vitro and in vivo. The analysis of the Kaplan-Meier plotter and the GEO dataset showed that mono-TAM-treated breast cancer patients with higher HBXIP expression levels had shorter relapse-free survivals than patients with lower HBXIP expression levels. Overexpression of HBXIP induced TAM resistance in ER+ breast cancer cells. The tissue microarray analysis revealed a positive association between the expression levels of HBXIP and HOXB13 in ER+ breast cancer patients. HBXIP elevated HOXB13 protein level in breast cancer cells. Mechanistically, HBXIP prevented chaperone-mediated autophagy (CMA)-dependent degradation of HOXB13 via enhancement of HOXB13 acetylation at the lysine 277 residue, causing the accumulation of HOXB13. Moreover, HBXIP was able to act as a co-activator of HOXB13 to stimulate interleukin (IL)-6 transcription in the promotion of TAM resistance. Interestingly, aspirin (ASA) suppressed the HBXIP/HOXB13 axis by decreasing HBXIP expression, overcoming TAM resistance in vitro and in vivo. Our study highlights that HBXIP enhances HOXB13 acetylation to prevent HOXB13 degradation and co-activates HOXB13 in the promotion of TAM resistance of breast cancer. Therapeutically, ASA can serve as a potential candidate for reversing TAM resistance by inhibiting HBXIP expression.

Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis.

PubMed

Tylee, Daniel S; Hess, Jonathan L; Quinn, Thomas P; Barve, Rahul; Huang, Hailiang; Zhang-James, Yanli; Chang, Jeffrey; Stamova, Boryana S; Sharp, Frank R; Hertz-Picciotto, Irva; Faraone, Stephen V; Kong, Sek Won; Glatt, Stephen J

2017-04-01

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Blood Transcriptomic Comparison of Individuals with and without Autism Spectrum Disorder: A Combined-Samples Mega-Analysis

PubMed Central

Tylee, Daniel S.; Hess, Jonathan L.; Quinn, Thomas P.; Barve, Rahul; Huang, Hailiang; Zhang-James, Yanli; Chang, Jeffrey; Stamova, Boryana S.; Sharp, Frank R.; Hertz-Picciotto, Irva; Faraone, Stephen V.; Kong, Sek Won; Glatt, Stephen J.

2017-01-01

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex-vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. PMID:27862943

Genome-Wide Identification of Regulatory Elements and Reconstruction of Gene Regulatory Networks of the Green Alga Chlamydomonas reinhardtii under Carbon Deprivation

PubMed Central

Vischi Winck, Flavia; Arvidsson, Samuel; Riaño-Pachón, Diego Mauricio; Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran; Urbina Gomez, David Alejandro; Rupprecht, Jens; Mueller-Roeber, Bernd

2013-01-01

The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1) and Lcr2 (Low-CO 2 response regulator 2), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas. PMID:24224019

Comparative Bacterial Proteomics: Analysis of the Core Genome Concept

PubMed Central

Callister, Stephen J.; McCue, Lee Ann; Turse, Joshua E.; Monroe, Matthew E.; Auberry, Kenneth J.; Smith, Richard D.; Adkins, Joshua N.; Lipton, Mary S.

2008-01-01

While comparative bacterial genomic studies commonly predict a set of genes indicative of common ancestry, experimental validation of the existence of this core genome requires extensive measurement and is typically not undertaken. Enabled by an extensive proteome database developed over six years, we have experimentally verified the expression of proteins predicted from genomic ortholog comparisons among 17 environmental and pathogenic bacteria. More exclusive relationships were observed among the expressed protein content of phenotypically related bacteria, which is indicative of the specific lifestyles associated with these organisms. Although genomic studies can establish relative orthologous relationships among a set of bacteria and propose a set of ancestral genes, our proteomics study establishes expressed lifestyle differences among conserved genes and proposes a set of expressed ancestral traits. PMID:18253490

A Novel Multifunctional C-23 Oxidase, CYP714E19, is Involved in Asiaticoside Biosynthesis.

PubMed

Kim, Ok Tae; Um, Yurry; Jin, Mei Lan; Kim, Jang Uk; Hegebarth, Daniela; Busta, Lucas; Racovita, Radu C; Jetter, Reinhard

2018-06-01

Centella asiatica is widely used as a medicinal plant due to accumulation of the ursane-type triterpene saponins asiaticoside and madecassoside. The molecular structure of both compounds suggests that they are biosynthesized from α-amyrin via three hydroxylations, and the respective Cyt P450-dependent monooxygenases (P450 enzymes) oxidizing the C-28 and C-2α positions have been reported. However, a third enzyme hydroxylating C-23 remained elusive. We previously identified 40,064 unique sequences in the transcriptome of C. asiatica elicited by methyl jasmonate, and among them we have now found 149 unigenes encoding putative P450 enzymes. In this set, 23 full-length cDNAs were recognized, 13 of which belonged to P450 subfamilies previously implicated in secondary metabolism. Four of these genes were highly expressed in response to jasmonate treatment, especially in leaves, in accordance with the accumulation patterns of asiaticoside. The functions of these candidate genes were tested using heterologous expression in yeast cells. Gas chromatography-mass spectrometry (GC-MS) analysis revealed that yeast expressing only the oxidosqualene synthase CaDDS produced the asiaticoside precursor α-amyrin (along with its isomer β-amyrin), while yeast co-expressing CaDDS and CYP716A83 also contained ursolic acid along with oleanolic acid. This P450 enzyme thus acts as a multifunctional triterpenoid C-28 oxidase converting amyrins into corresponding triterpenoid acids. Finally, yeast strains co-expressing CaDDS, CYP716A83 and CYP714E19 produced hederagenin and 23-hydroxyursolic acid, showing that CYP714E19 is a multifunctional triterpenoid oxidase catalyzing the C-23 hydroxylation of oleanolic acid and ursolic acid. Overall, our results demonstrate that CaDDS, CYP716A83 and CYP714E19 are C. asiatica enzymes catalyzing consecutive steps in asiaticoside biosynthesis.

Ragweed (Ambrosia artemisiifolia) pollen allergenicity: SuperSAGE transcriptomic analysis upon elevated CO2 and drought stress

PubMed Central

2014-01-01

Background Pollen of common ragweed (Ambrosia artemisiifolia) is a main cause of allergic diseases in Northern America. The weed has recently become spreading as a neophyte in Europe, while climate change may also affect the growth of the plant and additionally may also influence pollen allergenicity. To gain better insight in the molecular mechanisms in the development of ragweed pollen and its allergenic proteins under global change scenarios, we generated SuperSAGE libraries to identify differentially expressed transcripts. Results Ragweed plants were grown in a greenhouse under 380 ppm CO2 and under elevated level of CO2 (700 ppm). In addition, drought experiments under both CO2 concentrations were performed. The pollen viability was not altered under elevated CO2, whereas drought stress decreased its viability. Increased levels of individual flavonoid metabolites were found under elevated CO2 and/or drought. Total RNA was isolated from ragweed pollen, exposed to the four mentioned scenarios and four SuperSAGE libraries were constructed. The library dataset included 236,942 unique sequences, showing overlapping as well as clear differently expressed sequence tags (ESTs). The analysis targeted ESTs known in Ambrosia, as well as in pollen of other plants. Among the identified ESTs, those encoding allergenic ragweed proteins (Amb a) increased under elevated CO2 and drought stress. In addition, ESTs encoding allergenic proteins in other plants were also identified. Conclusions The analysis of changes in the transcriptome of ragweed pollen upon CO2 and drought stress using SuperSAGE indicates that under global change scenarios the pollen transcriptome was altered, and impacts the allergenic potential of ragweed pollen. PMID:24972689

Generation of a new Gateway-compatible inducible lentiviral vector platform allowing easy derivation of co-transduced cells.

PubMed

De Groote, Philippe; Grootjans, Sasker; Lippens, Saskia; Eichperger, Chantal; Leurs, Kirsten; Kahr, Irene; Tanghe, Giel; Bruggeman, Inge; De Schamphelaire, Wouter; Urwyler, Corinne; Vandenabeele, Peter; Haustraete, Jurgen; Declercq, Wim

2016-01-01

In contrast to most common gene delivery techniques, lentiviral vectors allow targeting of almost any mammalian cell type, even non-dividing cells, and they stably integrate in the genome. Therefore, these vectors are a very powerful tool for biomedical research. Here we report the generation of a versatile new set of 22 lentiviral vectors with broad applicability in multiple research areas. In contrast to previous systems, our platform provides a choice between constitutive and/or conditional expression and six different C-terminal fusions. Furthermore, two compatible selection markers enable the easy derivation of stable cell lines co-expressing differently tagged transgenes in a constitutive or inducible manner. We show that all of the vector features are functional and that they contribute to transgene overexpression in proof-of-principle experiments.

Gene-expression signatures of Atlantic salmon's plastic life cycle.

PubMed

Aubin-Horth, Nadia; Letcher, Benjamin H; Hofmann, Hans A

2009-09-15

How genomic expression differs as a function of life history variation is largely unknown. Atlantic salmon exhibits extreme alternative life histories. We defined the gene-expression signatures of wild-caught salmon at two different life stages by comparing the brain expression profiles of mature sneaker males and immature males, and early migrants and late migrants. In addition to life-stage-specific signatures, we discovered a surprisingly large gene set that was differentially regulated-at similar magnitudes, yet in opposite direction-in both life history transitions. We suggest that this co-variation is not a consequence of many independent cellular and molecular switches in the same direction but rather represents the molecular equivalent of a physiological shift orchestrated by one or very few master regulators.

Tumor formation of prostate cancer cells influenced by stromal cells from the transitional or peripheral zones of the normal prostate

PubMed Central

Zhao, Fu-Jun; Han, Bang-Min; Yu, Sheng-Qiang; Xia, Shu-Jie

2009-01-01

This study was designed to investigate the different involvements of prostatic stromal cells from the normal transitional zone (TZ) or peripheral zone (PZ) in the carcinogenesis of prostate cancer (PCa) epithelial cells (PC-3) in vitro and in vivo co-culture models. Ultra-structures and gene expression profiles of primary cultures of human prostatic stromal cells from the normal TZ or PZ were analyzed by electron microscopy and microarray analysis. In vitro and in vivo co-culture models composed of normal TZ or PZ stromal cells and human PCa PC-3 cells were established. We assessed tumor growth and weight in the in vivo nude mice model. There are morphological and ultra-structural differences in stromal cells from TZ and PZ of the normal prostate. In all, 514 differentially expressed genes were selected by microarray analysis; 483 genes were more highly expressed in stromal cells from TZ and 31 were more highly expressed in those from PZ. Co-culture with PZ stromal cells and transforming growth factor-β1 (TGF-β1) increased the tumor growth of PC-3 cells in vitro and in vivo, as well as Bcl-2 expression. On the other hand, stromal cells of TZ suppressed PC-3 cell tumor growth in the mouse model. We conclude that ultra-structures and gene expression differ between the stromal cells from TZ or PZ of the normal prostate, and stroma–epithelium interactions from TZ or PZ might be responsible for the distinct zonal localization of prostate tumor formation. PMID:19122679

A novel comparative pattern count analysis reveals a chronic ethanol-induced dynamic shift in immediate early NF-κB genome-wide promoter binding during liver regeneration.

PubMed

Kuttippurathu, Lakshmi; Patra, Biswanath; Hoek, Jan B; Vadigepalli, Rajanikanth

2016-03-01

Liver regeneration after partial hepatectomy is a clinically important process that is impaired by adaptation to chronic alcohol intake. We focused on the initial time points following partial hepatectomy (PHx) to analyze the genome-wide binding activity of NF-κB, a key immediate early regulator. We investigated the effect of chronic alcohol intake on immediate early NF-κB genome-wide localization, in the adapted state as well as in response to partial hepatectomy, using chromatin immunoprecipitation followed by promoter microarray analysis. We found many ethanol-specific NF-κB binding target promoters in the ethanol-adapted state, corresponding to the regulation of biosynthetic processes, oxidation-reduction and apoptosis. Partial hepatectomy induced a diet-independent shift in NF-κB binding loci relative to the transcription start sites. We employed a novel pattern count analysis to exhaustively enumerate and compare the number of promoters corresponding to the temporal binding patterns in ethanol and pair-fed control groups. The highest pattern count corresponded to promoters with NF-κB binding exclusively in the ethanol group at 1 h post PHx. This set was associated with the regulation of cell death, response to oxidative stress, histone modification, mitochondrial function, and metabolic processes. Integration with the global gene expression profiles to identify putative transcriptional consequences of NF-κB binding patterns revealed that several of ethanol-specific 1 h binding targets showed ethanol-specific differential expression through 6 h post PHx. Motif analysis yielded co-incident binding loci for STAT3, AP-1, CREB, C/EBP-β, PPAR-γ and C/EBP-α, likely participating in co-regulatory modules with NF-κB in shaping the immediate early response to PHx. We conclude that adaptation to chronic ethanol intake disrupts the NF-κB promoter binding landscape with consequences for the immediate early gene regulatory response to the acute challenge of PHx.