Sample records for identify differentially coexpressed

  1. Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network.

    PubMed

    Jiang, Xue; Zhang, Han; Quan, Xiongwen

    2016-01-01

    Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

  2. Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection

    PubMed Central

    Jiang, Zhenhong; Dong, Xiaobao; Li, Zhi-Gang; He, Fei; Zhang, Ziding

    2016-01-01

    Plant defense responses to pathogens involve massive transcriptional reprogramming. Recently, differential coexpression analysis has been developed to study the rewiring of gene networks through microarray data, which is becoming an important complement to traditional differential expression analysis. Using time-series microarray data of Arabidopsis thaliana infected with Pseudomonas syringae, we analyzed Arabidopsis defense responses to P. syringae through differential coexpression analysis. Overall, we found that differential coexpression was a common phenomenon of plant immunity. Genes that were frequently involved in differential coexpression tend to be related to plant immune responses. Importantly, many of those genes have similar average expression levels between normal plant growth and pathogen infection but have different coexpression partners. By integrating the Arabidopsis regulatory network into our analysis, we identified several transcription factors that may be regulators of differential coexpression during plant immune responses. We also observed extensive differential coexpression between genes within the same metabolic pathways. Several metabolic pathways, such as photosynthesis light reactions, exhibited significant changes in expression correlation between normal growth and pathogen infection. Taken together, differential coexpression analysis provides a new strategy for analyzing transcriptional data related to plant defense responses and new insights into the understanding of plant-pathogen interactions. PMID:27721457

  3. 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.

  4. 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.

  5. A methodology for the analysis of differential coexpression across the human lifespan.

    PubMed

    Gillis, Jesse; Pavlidis, Paul

    2009-09-22

    Differential coexpression is a change in coexpression between genes that may reflect 'rewiring' of transcriptional networks. It has previously been hypothesized that such changes might be occurring over time in the lifespan of an organism. While both coexpression and differential expression of genes have been previously studied in life stage change or aging, differential coexpression has not. Generalizing differential coexpression analysis to many time points presents a methodological challenge. Here we introduce a method for analyzing changes in coexpression across multiple ordered groups (e.g., over time) and extensively test its validity and usefulness. Our method is based on the use of the Haar basis set to efficiently represent changes in coexpression at multiple time scales, and thus represents a principled and generalizable extension of the idea of differential coexpression to life stage data. We used published microarray studies categorized by age to test the methodology. We validated the methodology by testing our ability to reconstruct Gene Ontology (GO) categories using our measure of differential coexpression and compared this result to using coexpression alone. Our method allows significant improvement in characterizing these groups of genes. Further, we examine the statistical properties of our measure of differential coexpression and establish that the results are significant both statistically and by an improvement in semantic similarity. In addition, we found that our method finds more significant changes in gene relationships compared to several other methods of expressing temporal relationships between genes, such as coexpression over time. Differential coexpression over age generates significant and biologically relevant information about the genes producing it. Our Haar basis methodology for determining age-related differential coexpression performs better than other tested methods. The Haar basis set also lends itself to ready interpretation

  6. 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

  7. 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.

  8. 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.

  9. A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

    PubMed

    Zhang, Qingyang

    2018-05-16

    Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

  10. Differentiation of embryonic stem cells into hepatocytes that coexpress coagulation factors VIII and IX.

    PubMed

    Cao, Jun; Shang, Chang-zhen; Lü, Li-hong; Qiu, De-chuan; Ren, Meng; Chen, Ya-jin; Min, Jun

    2010-11-01

    To establish an efficient culture system to support embryonic stem (ES) cell differentiation into hepatocytes that coexpress F-VIII and F-IX. Mouse E14 ES cells were cultured in differentiation medium containing sodium butyrate (SB), basic fibroblast growth factor (bFGF), and/or bone morphogenetic protein 4 (BMP4) to induce the differentiation of endoderm cells and hepatic progenitor cells. Hepatocyte growth factor, oncostatin M, and dexamethasone were then used to induce the maturation of ES cell-derived hepatocytes. The mRNA expression levels of endoderm-specific genes and hepatocyte-specific genes, including the levels of F-VIII and F-IX, were detected by RT-PCR and real-time PCR during various stages of differentiation. Protein expression was examined by immunofluorescence and Western blot. At the final stage of differentiation, flow cytometry was performed to determine the percentage of cells coexpressing F-VIII and F-IX, and ELISA was used to detect the levels of F-VIII and F-IX protein secreted into the culture medium. The expression of endoderm-specific and hepatocyte-specific markers was upregulated to highest level in response to the combination of SB, bFGF, and BMP4. Treatment with the three inducers during hepatic progenitor differentiation significantly enhanced the mRNA and protein levels of F-VIII and F-IX in ES cell-derived hepatocytes. More importantly, F-VIII and F-IX were coexpressed with high efficiency at the final stage of differentiation, and they were also secreted into the culture medium. We have established a novel in vitro differentiation protocol for ES-derived hepatocytes that coexpress F-VIII and F-IX that may provide a foundation for stem cell replacement therapy for hemophilia.

  11. Network-based expression analyses and experimental validations revealed high co-expression between Yap1 and stem cell markers compared to differentiated cells.

    PubMed

    Dehghanian, Fariba; Hojati, Zohreh; Esmaeili, Fariba; Masoudi-Nejad, Ali

    2018-05-21

    The Hippo signaling pathway is identified as a potential regulatory pathway which plays critical roles in differentiation and stem cell self-renewal. Yap1 is a primary transcriptional effector of this pathway. The importance of Yap1 in embryonic stem cells (ESCs) and differentiation procedure remains a challenging question, since two different observations have been reported. To answer this question we used co-expression network and differential co-expression analyses followed by experimental validations. Our results indicate that Yap1 is highly co-expressed with stem cell markers in ESCs but not in differentiated cells (DCs). The significant Yap1 down-regulation and also translocation of Yap1 into the cytoplasm during P19 differentiation was also detected. Moreover, our results suggest the E2f7, Lin28a and Dppa4 genes as possible regulatory nuclear factors of Hippo pathway in stem cells. The present findings are actively consistent with studies that suggested Yap1 as an essential factor for stem cell self-renewal. Copyright © 2018 Elsevier Inc. All rights reserved.

  12. Analysis of differentially co-expressed genes based on microarray data of hepatocellular carcinoma.

    PubMed

    Wang, Y; Jiang, T; Li, Z; Lu, L; Zhang, R; Zhang, D; Wang, X; Tan, J

    2017-01-01

    Hepatocellular carcinoma (HCC) is the third leading cause of cancer related death worldwide. Although great progress in diagnosis and management of HCC have been made, the exact molecular mechanisms remain poorly understood. The study aims to identify potential biomarkers for HCC progression, mainly at transcription level. In this study, chip data GSE 29721 was utilized, which contains 10 HCC samples and 10 normal adjacent tissue samples. Differentially expressed genes (DEGs) between two sample types were selected by t-test method. Following, the differentially co-expressed genes (DCGs) and differentially co-expressed Links (DCLs) were identified by DCGL package in R with the threshold of q < 0.25. Afterwards, pathway enrichment analysis of the DCGs was carried out by DAVID. Then, DCLs were mapped to TRANSFAC database to reveal associations between relevant transcriptional factors (TFs) and their target genes. Quantitative real-time RT-PCR was performed for TFs or genes of interest. As a result, a total of 388 DCGs and 35,771 DCLs were obtained. The predominant pathways enriched by these genes were Cytokine-cytokine receptor interaction, ECM-receptor interaction and TGF-β signaling pathway. Three TF-target interactions, LEF1-NCAM1, EGR1-FN1 and FOS-MT2A were predicted. Compared with control, expressions of the TF genes EGR1, FOS and ETS2 were all up-regulated in the HCC cell line, HepG2; while LEF1 was down-regulated. Except NCAM1, all the target genes were up-regulated in HepG2. Our findings suggest these TFs and genes might play important roles in the pathogenesis of HCC and may be used as therapeutic targets for HCC management.

  13. 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.

  14. Differentially co-expressed interacting protein pairs discriminate samples under distinct stages of HIV type 1 infection.

    PubMed

    Yoon, Dukyong; Kim, Hyosil; Suh-Kim, Haeyoung; Park, Rae Woong; Lee, KiYoung

    2011-01-01

    Microarray analyses based on differentially expressed genes (DEGs) have been widely used to distinguish samples across different cellular conditions. However, studies based on DEGs have not been able to clearly determine significant differences between samples of pathophysiologically similar HIV-1 stages, e.g., between acute and chronic progressive (or AIDS) or between uninfected and clinically latent stages. We here suggest a novel approach to allow such discrimination based on stage-specific genetic features of HIV-1 infection. Our approach is based on co-expression changes of genes known to interact. The method can identify a genetic signature for a single sample as contrasted with existing protein-protein-based analyses with correlational designs. Our approach distinguishes each sample using differentially co-expressed interacting protein pairs (DEPs) based on co-expression scores of individual interacting pairs within a sample. The co-expression score has positive value if two genes in a sample are simultaneously up-regulated or down-regulated. And the score has higher absolute value if expression-changing ratios are similar between the two genes. We compared characteristics of DEPs with that of DEGs by evaluating their usefulness in separation of HIV-1 stage. And we identified DEP-based network-modules and their gene-ontology enrichment to find out the HIV-1 stage-specific gene signature. Based on the DEP approach, we observed clear separation among samples from distinct HIV-1 stages using clustering and principal component analyses. Moreover, the discrimination power of DEPs on the samples (70-100% accuracy) was much higher than that of DEGs (35-45%) using several well-known classifiers. DEP-based network analysis also revealed the HIV-1 stage-specific network modules; the main biological processes were related to "translation," "RNA splicing," "mRNA, RNA, and nucleic acid transport," and "DNA metabolism." Through the HIV-1 stage-related modules, changing

  15. Identification of Transcriptional Modules and Key Genes in Chickens Infected with Salmonella enterica Serovar Pullorum Using Integrated Coexpression Analyses.

    PubMed

    Liu, Bao-Hong; Cai, Jian-Ping

    2017-01-01

    Salmonella enterica Pullorum is one of the leading causes of mortality in poultry. Understanding the molecular response in chickens in response to the infection by S. enterica is important in revealing the mechanisms of pathogenesis and disease progress. There have been studies on identifying genes associated with Salmonella infection by differential expression analysis, but the relationships among regulated genes have not been investigated. In this study, we employed weighted gene coexpression network analysis (WGCNA) and differential coexpression analysis (DCEA) to identify coexpression modules by exploring microarray data derived from chicken splenic tissues in response to the S. enterica infection. A total of 19 modules from 13,538 genes were associated with the Jak-STAT signaling pathway, the extracellular matrix, cytoskeleton organization, the regulation of the actin cytoskeleton, G-protein coupled receptor activity, Toll-like receptor signaling pathways, and immune system processes; among them, 14 differentially coexpressed modules (DCMs) and 2,856 differentially coexpressed genes (DCGs) were identified. The global expression of module genes between infected and uninfected chickens showed slight differences but considerable changes for global coexpression. Furthermore, DCGs were consistently linked to the hubs of the modules. These results will help prioritize candidate genes for future studies of Salmonella infection.

  16. Identification of Transcriptional Modules and Key Genes in Chickens Infected with Salmonella enterica Serovar Pullorum Using Integrated Coexpression Analyses

    PubMed Central

    2017-01-01

    Salmonella enterica Pullorum is one of the leading causes of mortality in poultry. Understanding the molecular response in chickens in response to the infection by S. enterica is important in revealing the mechanisms of pathogenesis and disease progress. There have been studies on identifying genes associated with Salmonella infection by differential expression analysis, but the relationships among regulated genes have not been investigated. In this study, we employed weighted gene coexpression network analysis (WGCNA) and differential coexpression analysis (DCEA) to identify coexpression modules by exploring microarray data derived from chicken splenic tissues in response to the S. enterica infection. A total of 19 modules from 13,538 genes were associated with the Jak-STAT signaling pathway, the extracellular matrix, cytoskeleton organization, the regulation of the actin cytoskeleton, G-protein coupled receptor activity, Toll-like receptor signaling pathways, and immune system processes; among them, 14 differentially coexpressed modules (DCMs) and 2,856 differentially coexpressed genes (DCGs) were identified. The global expression of module genes between infected and uninfected chickens showed slight differences but considerable changes for global coexpression. Furthermore, DCGs were consistently linked to the hubs of the modules. These results will help prioritize candidate genes for future studies of Salmonella infection. PMID:28529955

  17. Cooperation and coexpression: How coexpression networks shift in response to multiple mutualists.

    PubMed

    Palakurty, Sathvik X; Stinchcombe, John R; Afkhami, Michelle E

    2018-04-01

    A mechanistic understanding of community ecology requires tackling the nonadditive effects of multispecies interactions, a challenge that necessitates integration of ecological and molecular complexity-namely moving beyond pairwise ecological interaction studies and the "gene at a time" approach to mechanism. Here, we investigate the consequences of multispecies mutualisms for the structure and function of genomewide differential coexpression networks for the first time, using the tractable and ecologically important interaction between legume Medicago truncatula, rhizobia and mycorrhizal fungi. First, we found that genes whose expression is affected nonadditively by multiple mutualists are more highly connected in gene networks than expected by chance and had 94% greater network centrality than genes showing additive effects, suggesting that nonadditive genes may be key players in the widespread transcriptomic responses to multispecies symbioses. Second, multispecies mutualisms substantially changed coexpression network structure of 18 modules of host plant genes and 22 modules of the fungal symbionts' genes, indicating that third-party mutualists can cause significant rewiring of plant and fungal molecular networks. Third, we found that 60% of the coexpressed gene sets that explained variation in plant performance had coexpression structures that were altered by interactive effects of rhizobia and fungi. Finally, an "across-symbiosis" approach identified sets of plant and mycorrhizal genes whose coexpression structure was unique to the multiple mutualist context and suggested coupled responses across the plant-mycorrhizal interaction to rhizobial mutualists. Taken together, these results show multispecies mutualisms have substantial effects on the molecular interactions in host plants, microbes and across symbiotic boundaries. © 2018 John Wiley & Sons Ltd.

  18. Muscle-specific gene expression is underscored by differential stressor responses and coexpression changes.

    PubMed

    Moreno-Sánchez, Natalia; Rueda, Julia; Reverter, Antonio; Carabaño, María Jesús; Díaz, Clara

    2012-03-01

    Variations on the transcriptome from one skeletal muscle type to another still remain unknown. The reliable identification of stable gene coexpression networks is essential to unravel gene functions and define biological processes. The differential expression of two distinct muscles, M. flexor digitorum (FD) and M. psoas major (PM), was studied using microarrays in cattle to illustrate muscle-specific transcription patterns and to quantify changes in connectivity regarding the expected gene coexpression pattern. A total of 206 genes were differentially expressed (DE), 94 upregulated in PM and 112 in FD. The distribution of DE genes in pathways and biological functions was explored in the context of system biology. Global interactomes for genes of interest were predicted. Fast/slow twitch genes, genes coding for extracellular matrix, ribosomal and heat shock proteins, and fatty acid uptake centred the specific gene expression patterns per muscle. Genes involved in repairing mechanisms, such as ribosomal and heat shock proteins, suggested a differential ability of muscles to react to similar stressing factors, acting preferentially in slow twitch muscles. Muscle attributes do not seem to be completely explained by the muscle fibre composition. Changes in connectivity accounted for 24% of significant correlations between DE genes. Genes changing their connectivity mostly seem to contribute to the main differential attributes that characterize each specific muscle type. These results underscore the unique flexibility of skeletal muscle where a substantial set of genes are able to change their behavior depending on the circumstances.

  19. 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.

  20. 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.

  1. Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.

    PubMed

    Skinner, Jeff; Kotliarov, Yuri; Varma, Sudhir; Mine, Karina L; Yambartsev, Anatoly; Simon, Richard; Huyen, Yentram; Morgun, Andrey

    2011-07-14

    DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

  2. 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

  3. A gene co-expression network model identifies yield-related vicinity networks in Jatropha curcas shoot system.

    PubMed

    Govender, Nisha; Senan, Siju; Mohamed-Hussein, Zeti-Azura; Wickneswari, Ratnam

    2018-06-15

    The plant shoot system consists of reproductive organs such as inflorescences, buds and fruits, and the vegetative leaves and stems. In this study, the reproductive part of the Jatropha curcas shoot system, which includes the aerial shoots, shoots bearing the inflorescence and inflorescence were investigated in regard to gene-to-gene interactions underpinning yield-related biological processes. An RNA-seq based sequencing of shoot tissues performed on an Illumina HiSeq. 2500 platform generated 18 transcriptomes. Using the reference genome-based mapping approach, a total of 64 361 genes was identified in all samples and the data was annotated against the non-redundant database by the BLAST2GO Pro. Suite. After removing the outlier genes and samples, a total of 12 734 genes across 17 samples were subjected to gene co-expression network construction using petal, an R library. A gene co-expression network model built with scale-free and small-world properties extracted four vicinity networks (VNs) with putative involvement in yield-related biological processes as follow; heat stress tolerance, floral and shoot meristem differentiation, biosynthesis of chlorophyll molecules and laticifers, cell wall metabolism and epigenetic regulations. Our VNs revealed putative key players that could be adapted in breeding strategies for J. curcas shoot system improvements.

  4. 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

  5. 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.

  6. 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.

  7. A Novel Method to Identify Differential Pathways in Hippocampus Alzheimer's Disease.

    PubMed

    Liu, Chun-Han; Liu, Lian

    2017-05-08

    BACKGROUND Alzheimer's disease (AD) is the most common type of dementia. The objective of this paper is to propose a novel method to identify differential pathways in hippocampus AD. MATERIAL AND METHODS We proposed a combined method by merging existed methods. Firstly, pathways were identified by four known methods (DAVID, the neaGUI package, the pathway-based co-expressed method, and the pathway network approach), and differential pathways were evaluated through setting weight thresholds. Subsequently, we combined all pathways by a rank-based algorithm and called the method the combined method. Finally, common differential pathways across two or more of five methods were selected. RESULTS Pathways obtained from different methods were also different. The combined method obtained 1639 pathways and 596 differential pathways, which included all pathways gained from the four existing methods; hence, the novel method solved the problem of inconsistent results. Besides, a total of 13 common pathways were identified, such as metabolism, immune system, and cell cycle. CONCLUSIONS We have proposed a novel method by combining four existing methods based on a rank product algorithm, and identified 13 significant differential pathways based on it. These differential pathways might provide insight into treatment and diagnosis of hippocampus AD.

  8. No3CoGP: non-conserved and conserved coexpressed gene pairs.

    PubMed

    Mal, Chittabrata; Aftabuddin, Md; Kundu, Sudip

    2014-12-08

    Analyzing the microarray data of different conditions, one can identify the conserved and condition-specific genes and gene modules, and thus can infer the underlying cellular activities. All the available tools based on Bioconductor and R packages differ in how they extract differential coexpression and at what level they study. There is a need for a user-friendly, flexible tool which can start analysis using raw or preprocessed microarray data and can report different levels of useful information. We present a GUI software, No3CoGP: Non-Conserved and Conserved Coexpressed Gene Pairs which takes Affymetrix microarray data (.CEL files or log2 normalized.txt files) along with annotation file (.csv file), Chip Definition File (CDF file) and probe file as inputs, utilizes the concept of network density cut-off and Fisher's z-test to extract biologically relevant information. It can identify four possible types of gene pairs based on their coexpression relationships. These are (i) gene pair showing coexpression in one condition but not in the other, (ii) gene pair which is positively coexpressed in one condition but negatively coexpressed in the other condition, (iii) positively and (iv) negatively coexpressed in both the conditions. Further, it can generate modules of coexpressed genes. Easy-to-use GUI interface enables researchers without knowledge in R language to use No3CoGP. Utilization of one or more CPU cores, depending on the availability, speeds up the program. The output files stored in the respective directories under the user-defined project offer the researchers to unravel condition-specific functionalities of gene, gene sets or modules.

  9. Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

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

    Xia, Jing; Rocke, David M.; Perry, George

    In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

  10. Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

    DOE PAGES

    Xia, Jing; Rocke, David M.; Perry, George; ...

    2014-01-01

    In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. Multiscale Embedded Gene Co-expression Network Analysis

    PubMed Central

    Song, Won-Min; Zhang, Bin

    2015-01-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

  16. Multiscale Embedded Gene Co-expression Network Analysis.

    PubMed

    Song, Won-Min; Zhang, Bin

    2015-11-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  17. Opsin co-expression in Limulus photoreceptors: differential regulation by light and a circadian clock

    PubMed Central

    Katti, C.; Kempler, K.; Porter, M. L.; Legg, A.; Gonzalez, R.; Garcia-Rivera, E.; Dugger, D.; Battelle, B.-A.

    2010-01-01

    A long-standing concept in vision science has held that a single photoreceptor expresses a single type of opsin, the protein component of visual pigment. However, the number of examples in the literature of photoreceptors from vertebrates and invertebrates that break this rule is increasing. Here, we describe a newly discovered Limulus opsin, Limulus opsin5, which is significantly different from previously characterized Limulus opsins, opsins1 and 2. We show that opsin5 is co-expressed with opsins1 and 2 in Limulus lateral and ventral eye photoreceptors and provide the first evidence that the expression of co-expressed opsins can be differentially regulated. We show that the relative levels of opsin5 and opsin1 and 2 in the rhabdom change with a diurnal rhythm and that their relative levels are also influenced by the animal's central circadian clock. An analysis of the sequence of opsin5 suggests it is sensitive to visible light (400–700 nm) but that its spectral properties may be different from that of opsins1 and 2. Changes in the relative levels of these opsins may underlie some of the dramatic day–night changes in Limulus photoreceptor function and may produce a diurnal change in their spectral sensitivity. PMID:20639420

  18. Whole genome co-expression analysis of soybean cytochrome P450 genes identifies nodulation-specific P450 monooxygenases

    PubMed Central

    2010-01-01

    Background Cytochrome P450 monooxygenases (P450s) catalyze oxidation of various substrates using oxygen and NAD(P)H. Plant P450s are involved in the biosynthesis of primary and secondary metabolites performing diverse biological functions. The recent availability of the soybean genome sequence allows us to identify and analyze soybean putative P450s at a genome scale. Co-expression analysis using an available soybean microarray and Illumina sequencing data provides clues for functional annotation of these enzymes. This approach is based on the assumption that genes that have similar expression patterns across a set of conditions may have a functional relationship. Results We have identified a total number of 332 full-length P450 genes and 378 pseudogenes from the soybean genome. From the full-length sequences, 195 genes belong to A-type, which could be further divided into 20 families. The remaining 137 genes belong to non-A type P450s and are classified into 28 families. A total of 178 probe sets were found to correspond to P450 genes on the Affymetrix soybean array. Out of these probe sets, 108 represented single genes. Using the 28 publicly available microarray libraries that contain organ-specific information, some tissue-specific P450s were identified. Similarly, stress responsive soybean P450s were retrieved from 99 microarray soybean libraries. We also utilized Illumina transcriptome sequencing technology to analyze the expressions of all 332 soybean P450 genes. This dataset contains total RNAs isolated from nodules, roots, root tips, leaves, flowers, green pods, apical meristem, mock-inoculated and Bradyrhizobium japonicum-infected root hair cells. The tissue-specific expression patterns of these P450 genes were analyzed and the expression of a representative set of genes were confirmed by qRT-PCR. We performed the co-expression analysis on many of the 108 P450 genes on the Affymetrix arrays. First we confirmed that CYP93C5 (an isoflavone synthase gene) is

  19. Chronic Ethanol Exposure Produces Time- and Brain Region-Dependent Changes in Gene Coexpression Networks

    PubMed Central

    Osterndorff-Kahanek, Elizabeth A.; Becker, Howard C.; Lopez, Marcelo F.; Farris, Sean P.; Tiwari, Gayatri R.; Nunez, Yury O.; Harris, R. Adron; Mayfield, R. Dayne

    2015-01-01

    Repeated ethanol exposure and withdrawal in mice increases voluntary drinking and represents an animal model of physical dependence. We examined time- and brain region-dependent changes in gene coexpression networks in amygdala (AMY), nucleus accumbens (NAC), prefrontal cortex (PFC), and liver after four weekly cycles of chronic intermittent ethanol (CIE) vapor exposure in C57BL/6J mice. Microarrays were used to compare gene expression profiles at 0-, 8-, and 120-hours following the last ethanol exposure. Each brain region exhibited a large number of differentially expressed genes (2,000-3,000) at the 0- and 8-hour time points, but fewer changes were detected at the 120-hour time point (400-600). Within each region, there was little gene overlap across time (~20%). All brain regions were significantly enriched with differentially expressed immune-related genes at the 8-hour time point. Weighted gene correlation network analysis identified modules that were highly enriched with differentially expressed genes at the 0- and 8-hour time points with virtually no enrichment at 120 hours. Modules enriched for both ethanol-responsive and cell-specific genes were identified in each brain region. These results indicate that chronic alcohol exposure causes global ‘rewiring‘ of coexpression systems involving glial and immune signaling as well as neuronal genes. PMID:25803291

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets.

    PubMed

    Abu-Jamous, Basel; Fa, Rui; Roberts, David J; Nandi, Asoke K

    2015-06-04

    Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few

  6. 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

  7. 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

  8. Identification of common coexpression modules based on quantitative network comparison.

    PubMed

    Jo, Yousang; Kim, Sanghyeon; Lee, Doheon

    2018-06-13

    Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes. However, there has been no quantitative network comparison method for coexpression networks and we examined previous methods for other networks that cannot be applied to coexpression network. Therefore, we aimed to propose quantitative comparison methods for coexpression networks and to find common biological mechanisms between Huntington's disease and brain aging by the new method. We proposed two similarity measures for quantitative comparison of coexpression networks. Then, we performed experiments using known coexpression networks. We showed the validity of two measures and evaluated threshold values for similar coexpression network pairs from experiments. Using these similarity measures and thresholds, we quantitatively measured the similarity between disease-specific and aging-related coexpression modules and found similar Huntington's disease-aging coexpression module pairs. We identified similar Huntington's disease-aging coexpression module pairs and found that these modules are related to brain development, cell death, and immune response. It suggests that up-regulated cell signalling related cell death and immune/ inflammation response may be the common molecular mechanisms in the pathophysiology of HD and normal brain aging in the frontal cortex.

  9. 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

  10. Evolutionary Conservation and Divergence of Gene Coexpression Networks in Gossypium (Cotton) Seeds.

    PubMed

    Hu, Guanjing; Hovav, Ran; Grover, Corrinne E; Faigenboim-Doron, Adi; Kadmon, Noa; Page, Justin T; Udall, Joshua A; Wendel, Jonathan F

    2016-12-01

    The cotton genus (Gossypium) provides a superior system for the study of diversification, genome evolution, polyploidization, and human-mediated selection. To gain insight into phenotypic diversification in cotton seeds, we conducted coexpression network analysis of developing seeds from diploid and allopolyploid cotton species and explored network properties. Key network modules and functional associations were identified related to seed oil content and seed weight. We compared species-specific networks to reveal topological changes, including rewired edges and differentially coexpressed genes, associated with speciation, polyploidy, and cotton domestication. Network comparisons among species indicate that topologies are altered in addition to gene expression profiles, indicating that changes in transcriptomic coexpression relationships play a role in the developmental architecture of cotton seed development. The global network topology of allopolyploids, especially for domesticated G. hirsutum, resembles the network of the A-genome diploid more than that of the D-genome parent, despite its D-like phenotype in oil content. Expression modifications associated with allopolyploidy include coexpression level dominance and transgressive expression, suggesting that the transcriptomic architecture in polyploids is to some extent a modular combination of that of its progenitor genomes. Among allopolyploids, intermodular relationships are more preserved between two different wild allopolyploid species than they are between wild and domesticated forms of a cultivated cotton, and regulatory connections of oil synthesis-related pathways are denser and more closely clustered in domesticated vs. wild G. hirsutum. These results demonstrate substantial modification of genic coexpression under domestication. Our work demonstrates how network inference informs our understanding of the transcriptomic architecture of phenotypic variation associated with temporal scales ranging from

  11. Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case-control validation study.

    PubMed

    Li, Yiping; Li, Yanhong; Bai, Zhenjiang; Pan, Jian; Wang, Jian; Fang, Fang

    2017-12-13

    Sepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset. Using the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis to identify co-expression modules significantly associated with pediatric sepsis. Functional interpretation (gene ontology and pathway analysis) and enrichment analysis with known transcription factors and microRNAs of the identified candidate modules were then performed. In modules significantly associated with sepsis, the intramodular analysis was further performed and "hub genes" were identified and validated by quantitative real-time PCR (qPCR) in this study. 15 co-expression modules in total were detected, and four modules ("midnight blue", "cyan", "brown", and "tan") were most significantly associated with pediatric sepsis and suggested as potential sepsis-associated modules. Gene ontology analysis and pathway analysis revealed that these four modules strongly associated with immune response. Three of the four sepsis-associated modules were also enriched with known transcription factors (false discovery rate-adjusted P < 0.05). Hub genes were identified in each of the four modules. Four of the identified hub genes (MYB proto-oncogene like 1, killer cell lectin like receptor G1, stomatin, and membrane spanning 4-domains A4A) were further validated to be differentially expressed between septic children and controls by qPCR. Four pediatric sepsis-associated co-expression modules were identified in this study. qPCR results suggest that hub genes in these modules are potential transcriptomic markers for pediatric sepsis diagnosis. These results provide novel insights into the pathogenesis of pediatric sepsis and promote the generation of diagnostic gene sets.

  12. Identifying gene coexpression networks underlying the dynamic regulation of wood-forming tissues in Populus under diverse environmental conditions.

    PubMed

    Zinkgraf, Matthew; Liu, Lijun; Groover, Andrew; Filkov, Vladimir

    2017-06-01

    Trees modify wood formation through integration of environmental and developmental signals in complex but poorly defined transcriptional networks, allowing trees to produce woody tissues appropriate to diverse environmental conditions. In order to identify relationships among genes expressed during wood formation, we integrated data from new and publically available datasets in Populus. These datasets were generated from woody tissue and include transcriptome profiling, transcription factor binding, DNA accessibility and genome-wide association mapping experiments. Coexpression modules were calculated, each of which contains genes showing similar expression patterns across experimental conditions, genotypes and treatments. Conserved gene coexpression modules (four modules totaling 8398 genes) were identified that were highly preserved across diverse environmental conditions and genetic backgrounds. Functional annotations as well as correlations with specific experimental treatments associated individual conserved modules with distinct biological processes underlying wood formation, such as cell-wall biosynthesis, meristem development and epigenetic pathways. Module genes were also enriched for DNase I hypersensitivity footprints and binding from four transcription factors associated with wood formation. The conserved modules are excellent candidates for modeling core developmental pathways common to wood formation in diverse environments and genotypes, and serve as testbeds for hypothesis generation and testing for future studies. No claim to original US government works. New Phytologist © 2017 New Phytologist Trust.

  13. Co-expression network analysis identified six hub genes in association with metastasis risk and prognosis in hepatocellular carcinoma

    PubMed Central

    Feng, Juerong; Zhou, Rui; Chang, Ying; Liu, Jing; Zhao, Qiu

    2017-01-01

    Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, and its carcinogenesis and progression are influenced by a complex network of gene interactions. A weighted gene co-expression network was constructed to identify gene modules associated with the clinical traits in HCC (n = 214). Among the 13 modules, high correlation was only found between the red module and metastasis risk (classified by the HCC metastasis gene signature) (R2 = −0.74). Moreover, in the red module, 34 network hub genes for metastasis risk were identified, six of which (ABAT, AGXT, ALDH6A1, CYP4A11, DAO and EHHADH) were also hub nodes in the protein-protein interaction network of the module genes. Thus, a total of six hub genes were identified. In validation, all hub genes showed a negative correlation with the four-stage HCC progression (P for trend < 0.05) in the test set. Furthermore, in the training set, HCC samples with any hub gene lowly expressed demonstrated a higher recurrence rate and poorer survival rate (hazard ratios with 95% confidence intervals > 1). RNA-sequencing data of 142 HCC samples showed consistent results in the prognosis. Gene set enrichment analysis (GSEA) demonstrated that in the samples with any hub gene highly expressed, a total of 24 functional gene sets were enriched, most of which focused on amino acid metabolism and oxidation. In conclusion, co-expression network analysis identified six hub genes in association with HCC metastasis risk and prognosis, which might improve the prognosis by influencing amino acid metabolism and oxidation. PMID:28430663

  14. Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

    PubMed

    Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

    2014-01-01

    Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed

  15. 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

  16. 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.

  17. Cis-Natural Antisense Transcripts Are Mainly Co-expressed with Their Sense Transcripts and Primarily Related to Energy Metabolic Pathways during Muscle Development.

    PubMed

    Zhao, Yunxia; Hou, Ye; Zhao, Changzhi; Liu, Fei; Luan, Yu; Jing, Lu; Li, Xinyun; Zhu, Mengjin; Zhao, Shuhong

    2016-01-01

    Cis-natural antisense transcripts (cis-NATs) are a new class of RNAs identified in various species. However, the biological functions of cis-NATs are largely unknown. In this study, we investigated the transcriptional characteristics and functions of cis-NATs in the muscle tissue of lean Landrace and indigenous fatty Lantang pigs. In total, 3,306 cis-NATs of 2,469 annotated genes were identified in the muscle tissue of pigs. More than 1,300 cis-NATs correlated with their sense genes at the transcriptional level, and approximately 80% of them were co-expressed in the two breeds. Furthermore, over 1,200 differentially expressed cis-NATs were identified during muscle development. Function annotation showed that the cis-NATs participated in muscle development mainly by co-expressing with genes involved in energy metabolic pathways, including citrate cycle (TCA cycle), glycolysis or gluconeogenesis, mitochondrial activation and so on. Moreover, these cis-NATs and their sense genes abruptly increased at the transition from the late fetal stages to the early postnatal stages and then decreased along with muscle development. In conclusion, the cis-NATs in the muscle tissue of pigs were identified and determined to be mainly co-expressed with their sense genes. The co-expressed cis-NATs and their sense gene were primarily related to energy metabolic pathways during muscle development in pigs. Our results offered novel evidence on the roles of cis-NATs during the muscle development of pigs.

  18. 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.

  19. A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies.

    PubMed

    Chang, Lun-Ching; Jamain, Stephane; Lin, Chien-Wei; Rujescu, Dan; Tseng, George C; Sibille, Etienne

    2014-01-01

    Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules

  20. Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

    PubMed

    Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

    2017-12-01

    Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

  1. 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.

  2. Coexpression network analysis identifies transcriptional modules associated with genomic alterations in neuroblastoma.

    PubMed

    Yang, Liulin; Li, Yun; Wei, Zhi; Chang, Xiao

    2018-06-01

    Neuroblastoma is a highly complex and heterogeneous cancer in children. Acquired genomic alterations including MYCN amplification, 1p deletion and 11q deletion are important risk factors and biomarkers in neuroblastoma. Here, we performed a co-expression-based gene network analysis to study the intrinsic association between specific genomic changes and transcriptome organization. We identified multiple gene coexpression modules which are recurrent in two independent datasets and associated with functional pathways including nervous system development, cell cycle, immune system process and extracellular matrix/space. Our results also indicated that modules involved in nervous system development and cell cycle are highly associated with MYCN amplification and 1p deletion, while modules responding to immune system process are associated with MYCN amplification only. In summary, this integrated analysis provides novel insights into molecular heterogeneity and pathogenesis of neuroblastoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang. Copyright © 2017. Published by Elsevier B.V.

  3. Gene co-expression analysis identifies gene clusters associated with isotropic and polarized growth in Aspergillus fumigatus conidia.

    PubMed

    Baltussen, Tim J H; Coolen, Jordy P M; Zoll, Jan; Verweij, Paul E; Melchers, Willem J G

    2018-04-26

    Aspergillus fumigatus is a saprophytic fungus that extensively produces conidia. These microscopic asexually reproductive structures are small enough to reach the lungs. Germination of conidia followed by hyphal growth inside human lungs is a key step in the establishment of infection in immunocompromised patients. RNA-Seq was used to analyze the transcriptome of dormant and germinating A. fumigatus conidia. Construction of a gene co-expression network revealed four gene clusters (modules) correlated with a growth phase (dormant, isotropic growth, polarized growth). Transcripts levels of genes encoding for secondary metabolites were high in dormant conidia. During isotropic growth, transcript levels of genes involved in cell wall modifications increased. Two modules encoding for growth and cell cycle/DNA processing were associated with polarized growth. In addition, the co-expression network was used to identify highly connected intermodular hub genes. These genes may have a pivotal role in the respective module and could therefore be compelling therapeutic targets. Generally, cell wall remodeling is an important process during isotropic and polarized growth, characterized by an increase of transcripts coding for hyphal growth and cell cycle/DNA processing when polarized growth is initiated. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  4. 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

  5. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model.

    PubMed

    Kogelman, Lisette J A; Cirera, Susanna; Zhernakova, Daria V; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

    2014-09-30

    Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection

  6. oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes

    PubMed Central

    Ho Sui, Shannan J.; Mortimer, James R.; Arenillas, David J.; Brumm, Jochen; Walsh, Christopher J.; Kennedy, Brian P.; Wasserman, Wyeth W.

    2005-01-01

    Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes. PMID:15933209

  7. G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

    USDA-ARS?s Scientific Manuscript database

    In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

  8. 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

  9. 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.

  10. Functional differentiation and spatial-temporal co-expression networks of the NBS-encoding gene family in Jilin ginseng, Panax ginseng C.A. Meyer.

    PubMed

    Yin, Rui; Zhao, Mingzhu; Wang, Kangyu; Lin, Yanping; Wang, Yanfang; Sun, Chunyu; Wang, Yi; Zhang, Meiping

    2017-01-01

    Ginseng, Panax ginseng C.A. Meyer, is one of the most important medicinal plants for human health and medicine. It has been documented that over 80% of genes conferring resistance to bacteria, viruses, fungi and nematodes are contributed by the nucleotide binding site (NBS)-encoding gene family. Therefore, identification and characterization of NBS genes expressed in ginseng are paramount to its genetic improvement and breeding. However, little is known about the NBS-encoding genes in ginseng. Here we report genome-wide identification and systems analysis of the NBS genes actively expressed in ginseng (PgNBS genes). Four hundred twelve PgNBS gene transcripts, derived from 284 gene models, were identified from the transcriptomes of 14 ginseng tissues. These genes were classified into eight types, including TNL, TN, CNL, CN, NL, N, RPW8-NL and RPW8-N. Seven conserved motifs were identified in both the Toll/interleukine-1 receptor (TIR) and coiled-coil (CC) typed genes whereas six were identified in the RPW8 typed genes. Phylogenetic analysis showed that the PgNBS gene family is an ancient family, with a vast majority of its genes originated before ginseng originated. In spite of their belonging to a family, the PgNBS genes have functionally dramatically differentiated and been categorized into numerous functional categories. The expressions of the across tissues, different aged roots and the roots of different genotypes. However, they are coordinating in expression, forming a single co-expression network. These results provide a deeper understanding of the origin, evolution and functional differentiation and expression dynamics of the NBS-encoding gene family in plants in general and in ginseng particularly, and a NBS gene toolkit useful for isolation and characterization of disease resistance genes and for enhanced disease resistance breeding in ginseng and related species.

  11. Functional differentiation and spatial-temporal co-expression networks of the NBS-encoding gene family in Jilin ginseng, Panax ginseng C.A. Meyer

    PubMed Central

    Wang, Kangyu; Lin, Yanping; Wang, Yanfang; Sun, Chunyu; Wang, Yi

    2017-01-01

    Ginseng, Panax ginseng C.A. Meyer, is one of the most important medicinal plants for human health and medicine. It has been documented that over 80% of genes conferring resistance to bacteria, viruses, fungi and nematodes are contributed by the nucleotide binding site (NBS)-encoding gene family. Therefore, identification and characterization of NBS genes expressed in ginseng are paramount to its genetic improvement and breeding. However, little is known about the NBS-encoding genes in ginseng. Here we report genome-wide identification and systems analysis of the NBS genes actively expressed in ginseng (PgNBS genes). Four hundred twelve PgNBS gene transcripts, derived from 284 gene models, were identified from the transcriptomes of 14 ginseng tissues. These genes were classified into eight types, including TNL, TN, CNL, CN, NL, N, RPW8-NL and RPW8-N. Seven conserved motifs were identified in both the Toll/interleukine-1 receptor (TIR) and coiled-coil (CC) typed genes whereas six were identified in the RPW8 typed genes. Phylogenetic analysis showed that the PgNBS gene family is an ancient family, with a vast majority of its genes originated before ginseng originated. In spite of their belonging to a family, the PgNBS genes have functionally dramatically differentiated and been categorized into numerous functional categories. The expressions of the across tissues, different aged roots and the roots of different genotypes. However, they are coordinating in expression, forming a single co-expression network. These results provide a deeper understanding of the origin, evolution and functional differentiation and expression dynamics of the NBS-encoding gene family in plants in general and in ginseng particularly, and a NBS gene toolkit useful for isolation and characterization of disease resistance genes and for enhanced disease resistance breeding in ginseng and related species. PMID:28727829

  12. One-plasmid tunable coexpression for mycobacterial protein–protein interaction studies

    PubMed Central

    Chang, Yong; Mead, David; Dhodda, Vinay; Brumm, Phil; Fox, Brian G

    2009-01-01

    A single plasmid that allows controlled coexpression has been developed for use in mycobacteria. The tetracycline inducible promoter, PtetO, was used to provide tetracycline-dependent induction of one gene, while the Psmyc, Pimyc, or Phsp promoters were used to provide three different levels of constitutive expression of a second gene. The functions of these four individual promoters were established using green fluorescent protein (GFP) and a newly identified red fluorescence inducible protein from Geobacillus sterothermophilus strain G1.13 (RFIP) as reporters. The tandem use of GFP and RFIP as reporter genes allowed optimization of the tunable coexpression in Mycobacterium smegmatis; either time at a fixed inducer concentration or changes in inducer concentration could be used to control the protein:protein ratio. This single vector system was used to coexpress the two-protein Mycobacterium tuberculosis stearoyl-CoA Δ9 desaturase complex (integral membrane desaturase Rv3229c and NADPH oxidoreductase Rv3230c) in M. smegmatis. The catalytic activity was found to increase in a manner corresponding to increasing the level of Rv3230c relative to a fixed level of Rv3229c. This system, which can yield finely tuned coexpression of the fatty acid desaturase complex in mycobacteria, may be useful for study of other multicomponent complexes. Furthermore, the tunable coexpression strategy used herein should also be applicable in other species with minor modifications. PMID:19760663

  13. 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

  14. 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

  15. Retinal specialization through spatially varying cell densities and opsin coexpression in cichlid fish.

    PubMed

    Dalton, Brian E; de Busserolles, Fanny; Marshall, N Justin; Carleton, Karen L

    2017-01-15

    The distinct behaviours of animals and the varied habitats in which animals live place different requirements on their visual systems. A trade-off exists between resolution and sensitivity, with these properties varying across the retina. Spectral sensitivity, which affects both achromatic and chromatic (colour) vision, also varies across the retina, though the function of this inhomogeneity is less clear. We previously demonstrated spatially varying spectral sensitivity of double cones in the cichlid fish Metriaclima zebra owing to coexpression of different opsins. Here, we map the distributions of ganglion cells and cone cells and quantify opsin coexpression in single cones to show these also vary across the retina. We identify an area centralis with peak acuity and infrequent coexpression, which may be suited for tasks such as foraging and detecting male signals. The peripheral retina has reduced ganglion cell densities and increased opsin coexpression. Modeling of cichlid visual tasks indicates that coexpression might hinder colour discrimination of foraging targets and some fish colours. But, coexpression might improve contrast detection of dark objects against bright backgrounds, which might be useful for detecting predators or zooplankton. This suggests a trade-off between acuity and colour discrimination in the central retina versus lower resolution but more sensitive contrast detection in the peripheral retina. Significant variation in the pattern of coexpression among individuals, however, raises interesting questions about the selective forces at work. © 2017. Published by The Company of Biologists Ltd.

  16. 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.

  17. Co-expression analysis and identification of fecundity-related long non-coding RNAs in sheep ovaries

    PubMed Central

    Miao, Xiangyang; Luo, Qingmiao; Zhao, Huijing; Qin, Xiaoyu

    2016-01-01

    Small Tail Han sheep, including the FecBBFecBB (Han BB) and FecB+ FecB+ (Han++) genotypes, and Dorset sheep exhibit different fecundities. To identify novel long non-coding RNAs (lncRNAs) associated with sheep fecundity to better understand their molecular mechanisms, a genome-wide analysis of mRNAs and lncRNAs from Han BB, Han++ and Dorset sheep was performed. After the identification of differentially expressed mRNAs and lncRNAs, 16 significant modules were explored by using weighted gene coexpression network analysis (WGCNA) followed by functional enrichment analysis of the genes and lncRNAs in significant modules. Among these selected modules, the yellow and brown modules were significantly related to sheep fecundity. lncRNAs (e.g., NR0B1, XLOC_041882, and MYH15) in the yellow module were mainly involved in the TGF-β signalling pathway, and NYAP1 and BCORL1 were significantly associated with the oxytocin signalling pathway, which regulates several genes in the coexpression network of the brown module. Overall, we identified several gene modules associated with sheep fecundity, as well as networks consisting of hub genes and lncRNAs that may contribute to sheep prolificacy by regulating the target mRNAs related to the TGF-β and oxytocin signalling pathways. This study provides an alternative strategy for the identification of potential candidate regulatory lncRNAs. PMID:27982099

  18. Co-expression analysis and identification of fecundity-related long non-coding RNAs in sheep ovaries.

    PubMed

    Miao, Xiangyang; Luo, Qingmiao; Zhao, Huijing; Qin, Xiaoyu

    2016-12-16

    Small Tail Han sheep, including the FecB B FecB B (Han BB) and FecB + FecB + (Han++) genotypes, and Dorset sheep exhibit different fecundities. To identify novel long non-coding RNAs (lncRNAs) associated with sheep fecundity to better understand their molecular mechanisms, a genome-wide analysis of mRNAs and lncRNAs from Han BB, Han++ and Dorset sheep was performed. After the identification of differentially expressed mRNAs and lncRNAs, 16 significant modules were explored by using weighted gene coexpression network analysis (WGCNA) followed by functional enrichment analysis of the genes and lncRNAs in significant modules. Among these selected modules, the yellow and brown modules were significantly related to sheep fecundity. lncRNAs (e.g., NR0B1, XLOC_041882, and MYH15) in the yellow module were mainly involved in the TGF-β signalling pathway, and NYAP1 and BCORL1 were significantly associated with the oxytocin signalling pathway, which regulates several genes in the coexpression network of the brown module. Overall, we identified several gene modules associated with sheep fecundity, as well as networks consisting of hub genes and lncRNAs that may contribute to sheep prolificacy by regulating the target mRNAs related to the TGF-β and oxytocin signalling pathways. This study provides an alternative strategy for the identification of potential candidate regulatory lncRNAs.

  19. CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities.

    PubMed

    Manem, Venkata; Adam, George Alexandru; Gruosso, Tina; Gigoux, Mathieu; Bertos, Nicholas; Park, Morag; Haibe-Kains, Benjamin

    2018-04-15

    Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments. Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140-3. ©2018 AACR . ©2018 American Association for Cancer Research.

  20. Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

    PubMed Central

    Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

    2008-01-01

    Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

  1. Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

    PubMed

    Chang, Xiao; Liu, Shuai; Yu, Yong-Tao; Li, Yi-Xue; Li, Yuan-Yuan

    2010-08-12

    The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.

  2. 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.

  3. A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants

    PubMed Central

    Borowsky, Alexander T.

    2017-01-01

    Plants produce diverse specialized metabolites (SMs), but the genes responsible for their production and regulation remain largely unknown, hindering efforts to tap plant pharmacopeia. Given that genes comprising SM pathways exhibit environmentally dependent coregulation, we hypothesized that genes within a SM pathway would form tight associations (modules) with each other in coexpression networks, facilitating their identification. To evaluate this hypothesis, we used 10 global coexpression data sets, each a meta-analysis of hundreds to thousands of experiments, across eight plant species to identify hundreds of coexpressed gene modules per data set. In support of our hypothesis, 15.3 to 52.6% of modules contained two or more known SM biosynthetic genes, and module genes were enriched in SM functions. Moreover, modules recovered many experimentally validated SM pathways, including all six known to form biosynthetic gene clusters (BGCs). In contrast, bioinformatically predicted BGCs (i.e., those lacking an associated metabolite) were no more coexpressed than the null distribution for neighboring genes. These results suggest that most predicted plant BGCs are not genuine SM pathways and argue that BGCs are not a hallmark of plant specialized metabolism. We submit that global gene coexpression is a rich, largely untapped resource for discovering the genetic basis and architecture of plant natural products. PMID:28408660

  4. 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.

  5. Coexpression of multidrug resistance involve proteins: a flow cytometric analysis.

    PubMed

    Boutonnat, J; Bonnefoix, T; Mousseau, M; Seigneurin, D; Ronot, X

    1998-01-01

    Cross resistance to multiple natural cytotoxic products represents a major obstacle in myeloblastic acute leukaemia (AML). Multidrug resistance (MDR) often involves overexpression of plasma membrane drug transporter P-glycoprotein (PGP) or the resistance associated protein (MRP). Recently, a protein overexpressed in a non-PGP MDR lung cancer cell line and termed lung resistance related protein (LRP) was identified. These proteins are known to be associated with a bad prognosis in AML. We have developed a triple indirect labelling analysed by flow cytometry to detect the coexpression of these proteins. Since no cell line expressing all three antigens is known, we mixed K562 cells (resistant to Adriblastine, PGP+, MRP-, LRP-) with GLC4 cells (resistant to Adriblastine, PGP-, MRP+, LRP+) to create a model system to test the method. The antibodies used were UIC2 for PGP, MRPm6 for MRP and LRP56 for LRP. They were revealed by Fab'2 coupled with Fluoresceine-isothiocyanate, Phycoerythrin or Tricolor with isotype specificity. Cells were fixed and permeabilized after PGP labelling because MRPm6 and LRP56 recognize intracellular epitopes. PGP and LRP were easily detected. MRP is expressed at relatively low levels and was more difficult to detect because in the triple labelling the non specific staining was higher than in a single labelling. Despite the increased background in the triple labelling we were able to detect coexpression of PGP, MRP, LRP by flow cytometry. This method appears to be very useful to detect coexpression of markers in AML. Such coexpression could modify the therapeutic approach with revertants.

  6. Polarizing the Neuron through Sustained Co-expression of Alternatively Spliced Isoforms.

    PubMed

    Yap, Karen; Xiao, Yixin; Friedman, Brad A; Je, H Shawn; Makeyev, Eugene V

    2016-05-10

    Alternative splicing (AS) is an important source of proteome diversity in eukaryotes. However, how this affects protein repertoires at a single-cell level remains an open question. Here, we show that many 3'-terminal exons are persistently co-expressed with their alternatives in mammalian neurons. In an important example of this scenario, cell polarity gene Cdc42, a combination of polypyrimidine tract-binding, protein-dependent, and constitutive splicing mechanisms ensures a halfway switch from the general (E7) to the neuron-specific (E6) alternative 3'-terminal exon during neuronal differentiation. Perturbing the nearly equimolar E6/E7 ratio in neurons results in defects in both axonal and dendritic compartments and suggests that Cdc42E7 is involved in axonogenesis, whereas Cdc42E6 is required for normal development of dendritic spines. Thus, co-expression of a precise blend of functionally distinct splice isoforms rather than a complete switch from one isoform to another underlies proper structural and functional polarization of neurons. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  7. 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.

  8. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

    PubMed Central

    Uddin, Raihan; Singh, Shiva M.

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken

  9. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

    PubMed

    Uddin, Raihan; Singh, Shiva M

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

  10. 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

  11. A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants.

    PubMed

    Wisecaver, Jennifer H; Borowsky, Alexander T; Tzin, Vered; Jander, Georg; Kliebenstein, Daniel J; Rokas, Antonis

    2017-05-01

    Plants produce diverse specialized metabolites (SMs), but the genes responsible for their production and regulation remain largely unknown, hindering efforts to tap plant pharmacopeia. Given that genes comprising SM pathways exhibit environmentally dependent coregulation, we hypothesized that genes within a SM pathway would form tight associations (modules) with each other in coexpression networks, facilitating their identification. To evaluate this hypothesis, we used 10 global coexpression data sets, each a meta-analysis of hundreds to thousands of experiments, across eight plant species to identify hundreds of coexpressed gene modules per data set. In support of our hypothesis, 15.3 to 52.6% of modules contained two or more known SM biosynthetic genes, and module genes were enriched in SM functions. Moreover, modules recovered many experimentally validated SM pathways, including all six known to form biosynthetic gene clusters (BGCs). In contrast, bioinformatically predicted BGCs (i.e., those lacking an associated metabolite) were no more coexpressed than the null distribution for neighboring genes. These results suggest that most predicted plant BGCs are not genuine SM pathways and argue that BGCs are not a hallmark of plant specialized metabolism. We submit that global gene coexpression is a rich, largely untapped resource for discovering the genetic basis and architecture of plant natural products. © 2017 American Society of Plant Biologists. All rights reserved.

  12. Modeling the Effects of HER/ErbB1-3 Coexpression on Receptor Dimerization and Biological Response

    PubMed Central

    Shankaran, Harish; Wiley, H. Steven; Resat, Haluk

    2006-01-01

    The human epidermal growth factor receptor (HER/ErbB) system comprises the epidermal growth factor receptor (EGFR/HER1) and three other homologs, namely HERs 2–4. This receptor system plays a critical role in cell proliferation and differentiation and receptor overexpression has been associated with poor prognosis in cancers of the epithelium. Here, we examine the effect of coexpressing varying levels of HERs 1–3 on the receptor dimerization patterns using a detailed kinetic model for HER/ErbB dimerization and trafficking. Our results indicate that coexpression of EGFR with HER2 or HER3 biases signaling to the cell surface and retards signal downregulation. In addition, simultaneous coexpression of HERs 1–3 leads to an abundance of HER2-HER3 heterodimers, which are known to be potent inducers of cell growth and transformation. Our new approach to use parameter dependence analysis in experimental design reveals that measurements of HER3 phosphorylation and HER2 internalization ratio may prove to be especially useful for the estimation of critical model parameters. Further, we examine the effect of receptor dimerization patterns on biological response using a simple phenomenological model. Results indicate that coexpression of EGFR with HER2 and HER3 at low to moderate levels may enable cells to match the response of a high HER2 expresser. PMID:16533841

  13. Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

    PubMed

    Obayashi, Takeshi; Kinoshita, Kengo

    2010-05-01

    Gene coexpression analyses are a powerful method to predict the function of genes and/or to identify genes that are functionally related to query genes. The basic idea of gene coexpression analyses is that genes with similar functions should have similar expression patterns under many different conditions. This approach is now widely used by many experimental researchers, especially in the field of plant biology. In this review, we will summarize recent successful examples obtained by using our gene coexpression database, ATTED-II. Specifically, the examples will describe the identification of new genes, such as the subunits of a complex protein, the enzymes in a metabolic pathway and transporters. In addition, we will discuss the discovery of a new intercellular signaling factor and new regulatory relationships between transcription factors and their target genes. In ATTED-II, we provide two basic views of gene coexpression, a gene list view and a gene network view, which can be used as guide gene approach and narrow-down approach, respectively. In addition, we will discuss the coexpression effectiveness for various types of gene sets.

  14. CXCL4-induced plaque macrophages can be specifically identified by co-expression of MMP7+S100A8+ in vitro and in vivo.

    PubMed

    Erbel, Christian; Tyka, Mirjam; Helmes, Christian M; Akhavanpoor, Mohmmadreza; Rupp, Gregor; Domschke, Gabriele; Linden, Fabian; Wolf, Antonia; Doesch, Andreas; Lasitschka, Felix; Katus, Hugo A; Gleissner, Christian A

    2015-04-01

    Macrophage heterogeneity in human atherosclerotic plaques has been recognized; however, markers for unequivocal identification of some subtypes are lacking. We found that the platelet chemokine CXCL4 induces a unique macrophage phenotype, which we proposed to call 'M4'. Here, we sought to identify suitable markers that identify M4 macrophages in vitro and in vivo. Using a stringent algorithm, we identified a set of potential markers from transcriptomic data derived from polarized macrophages. We specifically focused on matrix metalloproteinase (MMP)7 and S100A8, the co-expression of which has not been described in any macrophage type thus far. We found dose- and time-dependent MMP7 and S100A8 expression in M4 macrophages at the gene and protein levels. CXCL4-induced up-regulation of both MMP7 and S100A8 was curbed in the presence of heparin, which binds to CXCL4 and glycosaminoglycans, most likely representing the macrophage receptor for CXCL4. Immunofluorescence of post-mortem atherosclerotic coronary arteries identified CD68(+)MMP7(+), CD68(+)MMP7(-), CD68(+)S100A8(+) and CD68(+)S100A8(-) macrophages. A small proportion of MMP7(+)S100A8(+) macrophages most likely represent M4 macrophages. In summary, we have identified co-expression of MMP7 and S100A8 to be a marker combination exclusively found in M4 macrophages. This finding may allow further dissection of the role of M4 macrophages in atherosclerosis and other pathologic conditions. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  15. Effect of genomic distance on coexpression of coregulated genes in E. coli

    PubMed Central

    Merino, Enrique; Marchal, Kathleen; Collado-Vides, Julio

    2017-01-01

    In prokaryotes, genomic distance is a feature that in addition to coregulation affects coexpression. Several observations, such as genomic clustering of highly coexpressed small regulons, support the idea that coexpression behavior of coregulated genes is affected by the distance between the coregulated genes. However, the specific contribution of distance in addition to coregulation in determining the degree of coexpression has not yet been studied systematically. In this work, we exploit the rich information in RegulonDB to study how the genomic distance between coregulated genes affects their degree of coexpression, measured by pairwise similarity of expression profiles obtained under a large number of conditions. We observed that, in general, coregulated genes display higher degrees of coexpression as they are more closely located on the genome. This contribution of genomic distance in determining the degree of coexpression was relatively small compared to the degree of coexpression that was determined by the tightness of the coregulation (degree of overlap of regulatory programs) but was shown to be evolutionary constrained. In addition, the distance effect was sufficient to guarantee coexpression of coregulated genes that are located at very short distances, irrespective of their tightness of coregulation. This is partly but definitely not always because the close distance is also the cause of the coregulation. In cases where it is not, we hypothesize that the effect of the distance on coexpression could be caused by the fact that coregulated genes closely located to each other are also relatively more equidistantly located from their common TF and therefore subject to more similar levels of TF molecules. The absolute genomic distance of the coregulated genes to their common TF-coding gene tends to be less important in determining the degree of coexpression. Our results pinpoint the importance of taking into account the combined effect of distance and

  16. 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

  17. Discovery and validation of a glioblastoma co-expressed gene module

    PubMed Central

    Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

    2018-01-01

    Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

  18. Discovery and validation of a glioblastoma co-expressed gene module.

    PubMed

    Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

    2018-02-16

    Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

  19. CD8 single-cell gene coexpression reveals three different effector types present at distinct phases of the immune response

    PubMed Central

    Peixoto, António; Evaristo, César; Munitic, Ivana; Monteiro, Marta; Charbit, Alain; Rocha, Benedita; Veiga-Fernandes, Henrique

    2007-01-01

    To study in vivo CD8 T cell differentiation, we quantified the coexpression of multiple genes in single cells throughout immune responses. After in vitro activation, CD8 T cells rapidly express effector molecules and cease their expression when the antigen is removed. Gene behavior after in vivo activation, in contrast, was quite heterogeneous. Different mRNAs were induced at very different time points of the response, were transcribed during different time periods, and could decline or persist independently of the antigen load. Consequently, distinct gene coexpression patterns/different cell types were generated at the various phases of the immune responses. During primary stimulation, inflammatory molecules were induced and down-regulated shortly after activation, generating early cells that only mediated inflammation. Cytotoxic T cells were generated at the peak of the primary response, when individual cells simultaneously expressed multiple killer molecules, whereas memory cells lost killer capacity because they no longer coexpressed killer genes. Surprisingly, during secondary responses gene transcription became permanent. Secondary cells recovered after antigen elimination were more efficient killers than cytotoxic T cells present at the peak of the primary response. Thus, primary responses produced two transient effector types. However, after boosting, CD8 T cells differentiate into long-lived killer cells that persist in vivo in the absence of antigen. PMID:17485515

  20. 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.

  1. 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

  2. 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.

  3. Coexpression Analysis Identifies Two Oxidoreductases Involved in the Biosynthesis of the Monoterpene Acid Moiety of Natural Pyrethrin Insecticides in Tanacetum cinerariifolium1[OPEN

    PubMed Central

    Moghe, Gaurav D.

    2018-01-01

    Flowers of Tanacetum cinerariifolium produce a set of compounds known collectively as pyrethrins, which are commercially important pesticides that are strongly toxic to flying insects but not to most vertebrates. A pyrethrin molecule is an ester consisting of either trans-chrysanthemic acid or its modified form, pyrethric acid, and one of three alcohols, jasmolone, pyrethrolone, and cinerolone, that appear to be derived from jasmonic acid. Chrysanthemyl diphosphate synthase (CDS), the first enzyme involved in the synthesis of trans-chrysanthemic acid, was characterized previously and its gene isolated. TcCDS produces free trans-chrysanthemol in addition to trans-chrysanthemyl diphosphate, but the enzymes responsible for the conversion of trans-chrysanthemol to the corresponding aldehyde and then to the acid have not been reported. We used an RNA sequencing-based approach and coexpression correlation analysis to identify several candidate genes encoding putative trans-chrysanthemol and trans-chrysanthemal dehydrogenases. We functionally characterized the proteins encoded by these genes using a combination of in vitro biochemical assays and heterologous expression in planta to demonstrate that TcADH2 encodes an enzyme that oxidizes trans-chrysanthemol to trans-chrysanthemal, while TcALDH1 encodes an enzyme that oxidizes trans-chrysanthemal into trans-chrysanthemic acid. Transient coexpression of TcADH2 and TcALDH1 together with TcCDS in Nicotiana benthamiana leaves results in the production of trans-chrysanthemic acid as well as several other side products. The majority (58%) of trans-chrysanthemic acid was glycosylated or otherwise modified. Overall, these data identify key steps in the biosynthesis of pyrethrins and demonstrate the feasibility of metabolic engineering to produce components of these defense compounds in a heterologous host. PMID:29122986

  4. Dissecting nutrient-related co-expression networks in phosphate starved poplars.

    PubMed

    Kavka, Mareike; Polle, Andrea

    2017-01-01

    Phosphorus (P) is an essential plant nutrient, but its availability is often limited in soil. Here, we studied changes in the transcriptome and in nutrient element concentrations in leaves and roots of poplars (Populus × canescens) in response to P deficiency. P starvation resulted in decreased concentrations of S and major cations (K, Mg, Ca), in increased concentrations of N, Zn and Al, while C, Fe and Mn were only little affected. In roots and leaves >4,000 and >9,000 genes were differently expressed upon P starvation. These genes clustered in eleven co-expression modules of which seven were correlated with distinct elements in the plant tissues. One module (4.7% of all differentially expressed genes) was strongly correlated with changes in the P concentration in the plant. In this module the GO term "response to P starvation" was enriched with phosphoenolpyruvate carboxylase kinases, phosphatases and pyrophosphatases as well as regulatory domains such as SPX, but no phosphate transporters. The P-related module was also enriched in genes of the functional category "galactolipid synthesis". Galactolipids substitute phospholipids in membranes under P limitation. Two modules, one correlated with C and N and the other with biomass, S and Mg, were connected with the P-related module by co-expression. In these modules GO terms indicating "DNA modification" and "cell division" as well as "defense" and "RNA modification" and "signaling" were enriched; they contained phosphate transporters. Bark storage proteins were among the most strongly upregulated genes in the growth-related module suggesting that N, which could not be used for growth, accumulated in typical storage compounds. In conclusion, weighted gene coexpression network analysis revealed a hierarchical structure of gene clusters, which separated phosphate starvation responses correlated with P tissue concentrations from other gene modules, which most likely represented transcriptional adjustments related to

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

    PubMed Central

    Kadarmideen, Haja N; Watson-haigh, Nathan S

    2012-01-01

    Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

  12. Evolution, functional differentiation, and co-expression of the RLK gene family revealed in Jilin ginseng, Panax ginseng C.A. Meyer.

    PubMed

    Lin, Yanping; Wang, Kangyu; Li, Xiangyu; Sun, Chunyu; Yin, Rui; Wang, Yanfang; Wang, Yi; Zhang, Meiping

    2018-02-21

    Most genes in a genome exist in the form of a gene family; therefore, it is necessary to have knowledge of how a gene family functions to comprehensively understand organismal biology. The receptor-like kinase (RLK)-encoding gene family is one of the most important gene families in plants. It plays important roles in biotic and abiotic stress tolerances, and growth and development. However, little is known about the functional differentiation and relationships among the gene members within a gene family in plants. This study has isolated 563 RLK genes (designated as PgRLK genes) expressed in Jilin ginseng (Panax ginseng C.A. Meyer), investigated their evolution, and deciphered their functional diversification and relationships. The PgRLK gene family is highly diverged and formed into eight types. The LRR type is the earliest and most prevalent, while only the Lec type originated after P. ginseng evolved. Furthermore, although the members of the PgRLK gene family all encode receptor-like protein kinases and share conservative domains, they are functionally very diverse, participating in numerous biological processes. The expressions of different members of the PgRLK gene family are extremely variable within a tissue, at a developmental stage and in the same cultivar, but most of the genes tend to express correlatively, forming a co-expression network. These results not only provide a deeper and comprehensive understanding of the evolution, functional differentiation and correlation of a gene family in plants, but also an RLK genic resource useful for enhanced ginseng genetic improvement.

  13. Inference for High-dimensional Differential Correlation Matrices *

    PubMed Central

    Cai, T. Tony; Zhang, Anru

    2015-01-01

    Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380

  14. Inference for High-dimensional Differential Correlation Matrices.

    PubMed

    Cai, T Tony; Zhang, Anru

    2016-01-01

    Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

  15. Reconstruction of an Integrated Genome-Scale Co-Expression Network Reveals Key Modules Involved in Lung Adenocarcinoma

    PubMed Central

    Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

    2013-01-01

    Our goal of this study was to reconstruct a “genome-scale co-expression network” and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named “genome-scale co-expression network”. As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules. PMID:23874428

  16. Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma.

    PubMed

    Bidkhori, Gholamreza; Narimani, Zahra; Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

    2013-01-01

    Our goal of this study was to reconstruct a "genome-scale co-expression network" and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named "genome-scale co-expression network". As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules.

  17. 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

  18. Coexpression of α6β4 Integrin and Guanine Nucleotide Exchange Factor Net1 Identifies Node-Positive Breast Cancer Patients at High Risk for Distant Metastasis

    PubMed Central

    Gilcrease, Michael Z.; Kilpatrick, Shannan K.; Woodward, Wendy A.; Zhou, Xiao; Nicolas, Marlo M.; Corley, Lynda J.; Fuller, Gregory N.; Tucker, Susan L.; Diaz, Leslie K.; Buchholz, Thomas A.; Frost, Jeffrey A.

    2009-01-01

    Preclinical data indicate that α6β4 integrin signaling through Ras homolog gene family, member A, plays an important role in tumor cell motility. The objective of this study was to determine whether the combined expression of α6β4 integrin and neuroepithelioma transforming gene 1 (Net1), a guanine nucleotide exchange factor specific for Ras homolog gene family member A, is associated with adverse clinical outcome in breast cancer patients. Immunohistochemical expression of each protein was evaluated in a tumor tissue microarray prepared from the primary tumors of 94 node-positive patients with invasive breast carcinoma treated with total mastectomy and doxorubicin-based chemotherapy without radiation with a median follow-up of 12.5 years. Associations between staining results and multiple clinicopathologic variables were investigated. Although there was no significant association between α6β4 integrin or Net1 expression and clinical outcome when each marker was considered individually, coexpression of α6β4 and Net1 was associated with decreased distant metastasis–free survival (P = 0.030). In the subset of patients with hormone receptor–positive tumors, coexpression of α6β4 and Net1 was associated with a decrease in distant metastasis–free and overall survival (P < 0.001 and P = 0.006, respectively). Although an association between human epidermal growth factor receptor 2 expression and coexpression of α6β4 and Net1 (P = 0.008) was observed, coexpression of α6β4 and Net1 (hazard ratio, 1.63; P = 0.02) and lymphovascular invasion (hazard ratio, 2.35; P = 0.02) were the only factors independently associated with the development of distant metastasis in multivariate analysis. These findings suggest that coexpression of α6β4 integrin and Net1 could be a useful biomarker for aggressive disease in node-positive breast cancer patients. PMID:19124484

  19. Identifying microRNAs that Regulate Neuroblastoma Cell Differentiation

    DTIC Science & Technology

    2015-10-01

    Award Number: W81XWH-13-1-0241 TITLE: Identifying that Regulate Neuroblastoma Cell Differentiation PRINCIPAL INVESTIGATOR: Dr. Liqin Du...inducing miRNA, miR- 449a. We examined the differentiation-inducing function of miR-449a in multiple neuroblastoma cell lines. We have demonstrated that...miR-449a functions as an inducer of cell differentiation in neuroblastoma cell lines with distinct genetic backgrounds, including the MYCN

  20. 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.

  1. Global Landscape of a Co-Expressed Gene Network in Barley and its Application to Gene Discovery in Triticeae Crops

    PubMed Central

    Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

    2011-01-01

    Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/. PMID:21441235

  2. A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

    PubMed Central

    Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

    2013-01-01

    Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

  3. Differential co-expression analysis of a microarray gene expression profiles of pulmonary adenocarcinoma.

    PubMed

    Fu, Shijie; Pan, Xufeng; Fang, Wentao

    2014-08-01

    Lung cancer severely reduces the quality of life worldwide and causes high socioeconomic burdens. However, key genes leading to the generation of pulmonary adenocarcinoma remain elusive despite intensive research efforts. The present study aimed to identify the potential associations between transcription factors (TFs) and differentially co‑expressed genes (DCGs) in the regulation of transcription in pulmonary adenocarcinoma. Gene expression profiles of pulmonary adenocarcinoma were downloaded from the Gene Expression Omnibus, and gene expression was analyzed using a computational method. A total of 37,094 differentially co‑expressed links (DCLs) and 251 DCGs were identified, which were significantly enriched in 10 pathways. The construction of the regulatory network and the analysis of the regulatory impact factors revealed eight crucial TFs in the regulatory network. These TFs regulated the expression of DCGs by promoting or inhibiting their expression. In addition, certain TFs and target genes associated with DCGs did not appear in the DCLs, which indicated that those TFs could be synergistic with other factors. This is likely to provide novel insights for research into pulmonary adenocarcinoma. In conclusion, the present study may enhance the understanding of disease mechanisms and lead to an improved diagnosis of lung cancer. However, further studies are required to confirm these observations.

  4. 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.

  5. Pan- and core- network analysis of co-expression genes in a model plant

    DOE PAGES

    He, Fei; Maslov, Sergei

    2016-12-16

    Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

  6. Pan- and core- network analysis of co-expression genes in a model plant

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

    He, Fei; Maslov, Sergei

    Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

  7. Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

    PubMed Central

    Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S.

    2016-01-01

    Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites. PMID:27588023

  8. Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

    PubMed

    Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

    2016-01-01

    Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

  9. Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

    PubMed Central

    Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

    2015-01-01

    The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

  10. Cooperative transformation and coexpression of bovine papillomavirus type 1 E5 and E7 proteins.

    PubMed

    Bohl, J; Hull, B; Vande Pol, S B

    2001-01-01

    Productively infected bovine fibropapillomas were examined for bovine papillomavirus type 1 (BPV-1) E7 localization. BPV-1 E7 was observed in the cytoplasm of basal and lower spinous epithelial cells, coexpressed in the cytoplasm of basal cells with the E5 oncoprotein. E7 was also observed in nucleoli throughout the basal and spinous layers but not in the granular cell layer. Ectopic expression of E7 in cultured epithelial cells gave rise to localization similar to that seen in productive fibropapillomas, with cytoplasmic and nucleolar expression observed. Consistent with the coexpression of E7 and E5 in basal keratinocytes, BPV-1 E7 cooperated with E5 as well as E6 in an anchorage independence transformation assay. While E5 is expressed in both basal and superficial differentiating keratinocytes, BPV-1 E7 is only observed in basal and lower spinous epithelial cells. Therefore, BPV-1 E7 may serve to modulate the cellular response of basal epithelial cells to E5 expression.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Genomic approaches to identifying transcriptional regulators of osteoblast differentiation

    NASA Technical Reports Server (NTRS)

    Stains, Joseph P.; Civitelli, Roberto

    2003-01-01

    Recent microarray studies of mouse and human osteoblast differentiation in vitro have identified novel transcription factors that may be important in the establishment and maintenance of differentiation. These findings help unravel the pattern of gene-expression changes that underly the complex process of bone formation.

  16. Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis.

    PubMed

    Guo, Sheng-Min; Wang, Jian-Xiong; Li, Jin; Xu, Fang-Yuan; Wei, Quan; Wang, Hai-Ming; Huang, Hou-Qiang; Zheng, Si-Lin; Xie, Yu-Jie; Zhang, Chi

    2018-06-15

    Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA-associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease-related networks based on 21756 gene expression correlation coefficients, hub-genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits-related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA-associated genes. Moreover, 310 OA-associated genes were found, and 34 of them were among hub-genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)-receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway (PI3K-AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA. © 2018 Wiley Periodicals, Inc.

  17. Efficient Production of Active Polyhydroxyalkanoate Synthase in Escherichia coli by Coexpression of Molecular Chaperones

    PubMed Central

    Thomson, Nicholas M.; Saika, Azusa; Ushimaru, Kazunori; Sangiambut, Smith; Tsuge, Takeharu; Summers, David K.

    2013-01-01

    The type I polyhydroxyalkanoate synthase from Cupriavidus necator was heterologously expressed in Escherichia coli with simultaneous overexpression of chaperone proteins. Compared to expression of synthase alone (14.55 mg liter−1), coexpression with chaperones resulted in the production of larger total quantities of enzyme, including a larger proportion in the soluble fraction. The largest increase was seen when the GroEL/GroES system was coexpressed, resulting in approximately 6-fold-greater enzyme yields (82.37 mg liter−1) than in the absence of coexpressed chaperones. The specific activity of the purified enzyme was unaffected by coexpression with chaperones. Therefore, the increase in yield was attributed to an enhanced soluble fraction of synthase. Chaperones were also coexpressed with a polyhydroxyalkanoate production operon, resulting in the production of polymers with generally reduced molecular weights. This suggests a potential use for chaperones to control the physical properties of the polymer. PMID:23335776

  18. 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

  19. Gene coexpression measures in large heterogeneous samples using count statistics.

    PubMed

    Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

    2014-11-18

    With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

  20. A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

    PubMed Central

    2018-01-01

    Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968

  1. Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

    PubMed

    Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

    2016-05-27

    Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and

  2. Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

    PubMed

    Salem, Saeed; Ozcaglar, Cagri

    2014-01-01

    Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

  3. Genome-wide coexpression dynamics: Theory and application

    PubMed Central

    Li, Ker-Chau

    2002-01-01

    High-throughput expression profiling enables the global study of gene activities. Genes with positively correlated expression profiles are likely to encode functionally related proteins. However, all biological processes are interlocked, and each protein may play multiple cellular roles. Thus the coexpression of any two functionally related genes may depend on the constantly varying, yet often-unknown cellular state. To initiate a systematic study on this issue, a theory of coexpression dynamics is presented. This theory is used to rationalize a strategy of conducting a genome-wide search for the most critical cellular players that may affect the coexpression pattern of any two genes. In one example, using a yeast data set, our method reveals how the enzymes associated with the urea cycle are expressed to ensure proper mass flow of the involved metabolites. The correlation between ARG2 and CAR2 is found to change from positive to negative as the expression level of CPA2 increases. This delicate interplay in correlation signifies a remarkable control on the influx and efflux of ornithine and reflects well the intrinsic cellular demand for arginine. In addition to the urea cycle, our examples include SCH9 and CYR1 (both implicated in a recent longevity study), cytochrome c1 (mitochondrial electron transport), calmodulin (main calcium-binding protein), PFK1 and PFK2 (glycolysis), and two genes, ECM1 and YNL101W, the functions of which are newly revealed. The complexity in computation is eased by a new result from mathematical statistics. PMID:12486219

  4. Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets

    PubMed Central

    2014-01-01

    Background Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. Results We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways. PMID:25221624

  5. The Pathway Coexpression Network: Revealing pathway relationships

    PubMed Central

    Tanzi, Rudolph E.

    2018-01-01

    A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of

  6. Transcriptomic profiling in muscle and adipose tissue identifies genes related to growth and lipid deposition

    PubMed Central

    Pang, Jianhui; Zhong, Zhijun; Chen, Xiaohui; Yang, Yuekui; Zeng, Kai; Kang, Runming; Lei, Yunfeng; Ying, Sancheng; Gong, Jianjun; Gu, Yiren

    2017-01-01

    Growth performance and meat quality are important traits for the pig industry and consumers. Adipose tissue is the main site at which fat storage and fatty acid synthesis occur. Therefore, we combined high-throughput transcriptomic sequencing in adipose and muscle tissues with the quantification of corresponding phenotypic features using seven Chinese indigenous pig breeds and one Western commercial breed (Yorkshire). We obtained data on 101 phenotypic traits, from which principal component analysis distinguished two groups: one associated with the Chinese breeds and one with Yorkshire. The numbers of differentially expressed genes between all Chinese breeds and Yorkshire were shown to be 673 and 1056 in adipose and muscle tissues, respectively. Functional enrichment analysis revealed that these genes are associated with biological functions and canonical pathways related to oxidoreductase activity, immune response, and metabolic process. Weighted gene coexpression network analysis found more coexpression modules significantly correlated with the measured phenotypic traits in adipose than in muscle, indicating that adipose regulates meat and carcass quality. Using the combination of differential expression, QTL information, gene significance, and module hub genes, we identified a large number of candidate genes potentially related to economically important traits in pig, which should help us improve meat production and quality. PMID:28877211

  7. Transcriptomic profiling in muscle and adipose tissue identifies genes related to growth and lipid deposition.

    PubMed

    Tao, Xuan; Liang, Yan; Yang, Xuemei; Pang, Jianhui; Zhong, Zhijun; Chen, Xiaohui; Yang, Yuekui; Zeng, Kai; Kang, Runming; Lei, Yunfeng; Ying, Sancheng; Gong, Jianjun; Gu, Yiren; Lv, Xuebin

    2017-01-01

    Growth performance and meat quality are important traits for the pig industry and consumers. Adipose tissue is the main site at which fat storage and fatty acid synthesis occur. Therefore, we combined high-throughput transcriptomic sequencing in adipose and muscle tissues with the quantification of corresponding phenotypic features using seven Chinese indigenous pig breeds and one Western commercial breed (Yorkshire). We obtained data on 101 phenotypic traits, from which principal component analysis distinguished two groups: one associated with the Chinese breeds and one with Yorkshire. The numbers of differentially expressed genes between all Chinese breeds and Yorkshire were shown to be 673 and 1056 in adipose and muscle tissues, respectively. Functional enrichment analysis revealed that these genes are associated with biological functions and canonical pathways related to oxidoreductase activity, immune response, and metabolic process. Weighted gene coexpression network analysis found more coexpression modules significantly correlated with the measured phenotypic traits in adipose than in muscle, indicating that adipose regulates meat and carcass quality. Using the combination of differential expression, QTL information, gene significance, and module hub genes, we identified a large number of candidate genes potentially related to economically important traits in pig, which should help us improve meat production and quality.

  8. 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

  9. Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

    PubMed

    Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

    2011-02-01

    Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

  10. Simultaneous coexpression of memory-related and effector-related genes by individual human CD8 T cells depends on antigen specificity and differentiation.

    PubMed

    Gupta, Bhawna; Iancu, Emanuela M; Gannon, Philippe O; Wieckowski, Sébastien; Baitsch, Lukas; Speiser, Daniel E; Rufer, Nathalie

    2012-07-01

    Phenotypic and functional cell properties are usually analyzed at the level of defined cell populations but not single cells. Yet, large differences between individual cells may have important functional consequences. It is likely that T-cell-mediated immunity depends on the polyfunctionality of individual T cells, rather than the sum of functions of responding T-cell subpopulations. We performed highly sensitive single-cell gene expression profiling, allowing the direct ex vivo characterization of individual virus-specific and tumor-specific T cells from healthy donors and melanoma patients. We have previously shown that vaccination with the natural tumor peptide Melan-A-induced T cells with superior effector functions as compared with vaccination with the analog peptide optimized for enhanced HLA-A*0201 binding. Here we found that natural peptide vaccination induced tumor-reactive CD8 T cells with frequent coexpression of both memory/homing-associated genes (CD27, IL7R, EOMES, CXCR3, and CCR5) and effector-related genes (IFNG, KLRD1, PRF1, and GZMB), comparable with protective Epstein-Barr virus-specific and cytomegalovirus-specific T cells. In contrast, memory/homing-associated and effector-associated genes were less frequently coexpressed after vaccination with the analog peptide. Remarkably, these findings reveal a previously unknown level of gene expression diversity among vaccine-specific and virus-specific T cells with the simultaneous coexpression of multiple memory/homing-related and effector-related genes by the same cell. Such broad functional gene expression signatures within antigen-specific T cells may be critical for mounting efficient responses to pathogens or tumors. In summary, direct ex vivo high-resolution molecular characterization of individual T cells provides key insights into the processes shaping the functional properties of tumor-specific and virus-specific T cells.

  11. Gene co-expression networks shed light into diseases of brain iron accumulation

    PubMed Central

    Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M.; Botía, Juan A.; Collingwood, Joanna F.; Hardy, John; Milward, Elizabeth A.; Ryten, Mina; Houlden, Henry

    2016-01-01

    Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. PMID:26707700

  12. Partial Roc Reveals Superiority of Mutual Rank of Pearson's Correlation Coefficient as a Coexpression Measure to Elucidate Functional Association of Genes

    NASA Astrophysics Data System (ADS)

    Obayashi, Takeshi; Kinoshita, Kengo

    2013-01-01

    Gene coexpression analysis is a powerful approach to elucidate gene function. We have established and developed this approach using vast amount of publicly available gene expression data measured by microarray techniques. The coexpressed genes are used to estimate gene function of the guide gene or to construct gene coexpression networks. In the case to construct gene networks, researchers should introduce an arbitrary threshold of gene coexpression, because gene coexpression value is continuous value. In the viewpoint to introduce common threshold of gene coexpression, we previously reported rank of Pearson's correlation coefficient (PCC) is more useful than the original PCC value. In this manuscript, we re-assessed the measure of gene coexpression to construct gene coexpression network, and found that mutual rank (MR) of PCC showed better performance than rank of PCC and the original PCC in low false positive rate.

  13. Coexpression of Arp2 and WAVE2 predicts poor outcome in invasive breast carcinoma.

    PubMed

    Iwaya, Keiichi; Norio, Kohno; Mukai, Kiyoshi

    2007-03-01

    Breast carcinoma with a high histologic grade is highly invasive and metastatic. One reason for its irregular morphology is the formation of excessive protrusions due to assemblages of branched actin filament networks. In mammalian cells, the actin-related protein 2 and 3 (Arp2/3) complex initiates actin assembly to form lamellipodial protrusions by binding to the Wiskott-Aldrich syndrome (WASP)/WASP family verproline-homologous protein2 (WAVE2), a member of the WASP protein family. In this study, the localization Arp2 and WAVE2 in breast carcinoma was investigated to clarify whether coexpression of the two proteins is associated with histologic grade or patient outcome. Immunohistochemical staining of Arp2 and WAVE2 was performed on mirror specimens of 197 breast carcinomas, and the association between coexpression of the two proteins and clinicopathologic factors was examined. Kaplan-Meier disease-free survival and overall survival curves were analyzed to determine the prognostic significance of Arp2 and WAVE2 coexpression in breast carcinoma. Coexpression of Arp2 and WAVE2 was detected in 64 (36%) of 179 invasive ductal carcinomas and in 2 (11%) of 18 ductal carcinomas in situ, but was not detected in any adjacent non-cancerous tissue. The proportion of cancer cells expressing both Arp2 and WAVE2 was significantly higher in cases with high histologic grade (P<0.0001), and cases with lymph node metastasis (P=0.0150). The patients whose cancer cells showed such coexpression had shorter disease-free (P=0.0002) and overall survival (P=0.0122) than patients whose cancer cells expressed only one or none of Arp2 and WAVE2. Multivariate Cox regression analysis revealed that coexpression of Arp2 and WAVE2 is an independent factor for both tumor recurrence (P=0.0308) and death (P=0.0455). These results indicate that coexpression of Arp2 and WAVE2 is a significant prognostic factor that is closely associated with aggressive morphology of invasive ductal carcinoma of the

  14. Gene coexpression network alignment and conservation of gene modules between two grass species: maize and rice.

    PubMed

    Ficklin, Stephen P; Feltus, F Alex

    2011-07-01

    One major objective for plant biology is the discovery of molecular subsystems underlying complex traits. The use of genetic and genomic resources combined in a systems genetics approach offers a means for approaching this goal. This study describes a maize (Zea mays) gene coexpression network built from publicly available expression arrays. The maize network consisted of 2,071 loci that were divided into 34 distinct modules that contained 1,928 enriched functional annotation terms and 35 cofunctional gene clusters. Of note, 391 maize genes of unknown function were found to be coexpressed within modules along with genes of known function. A global network alignment was made between this maize network and a previously described rice (Oryza sativa) coexpression network. The IsoRankN tool was used, which incorporates both gene homology and network topology for the alignment. A total of 1,173 aligned loci were detected between the two grass networks, which condensed into 154 conserved subgraphs that preserved 4,758 coexpression edges in rice and 6,105 coexpression edges in maize. This study provides an early view into maize coexpression space and provides an initial network-based framework for the translation of functional genomic and genetic information between these two vital agricultural species.

  15. The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

    PubMed

    Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

    2010-09-01

    Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

  16. A null model for Pearson coexpression networks.

    PubMed

    Gobbi, Andrea; Jurman, Giuseppe

    2015-01-01

    Gene coexpression networks inferred by correlation from high-throughput profiling such as microarray data represent simple but effective structures for discovering and interpreting linear gene relationships. In recent years, several approaches have been proposed to tackle the problem of deciding when the resulting correlation values are statistically significant. This is most crucial when the number of samples is small, yielding a non-negligible chance that even high correlation values are due to random effects. Here we introduce a novel hard thresholding solution based on the assumption that a coexpression network inferred by randomly generated data is expected to be empty. The threshold is theoretically derived by means of an analytic approach and, as a deterministic independent null model, it depends only on the dimensions of the starting data matrix, with assumptions on the skewness of the data distribution compatible with the structure of gene expression levels data. We show, on synthetic and array datasets, that the proposed threshold is effective in eliminating all false positive links, with an offsetting cost in terms of false negative detected edges.

  17. A high-content morphological screen identifies novel microRNAs that regulate neuroblastoma cell differentiation

    PubMed Central

    Zhao, Zhenze; Ma, Xiuye; Hsiao, Tzu-Hung; Lin, Gregory; Kosti, Adam; Yu, Xiaojie; Suresh, Uthra; Chen, Yidong; Tomlinson, Gail E.; Pertsemlidis, Alexander; Du, Liqin

    2014-01-01

    Neuroblastoma, the most common extracranial solid tumor of childhood, arises from neural crest cell precursors that fail to differentiate. Inducing cell differentiation is an important therapeutic strategy for neuroblastoma. We developed a direct functional high-content screen to identify differentiation-inducing microRNAs, in order to develop microRNA-based differentiation therapy for neuroblastoma. We discovered novel microRNAs, and more strikingly, three microRNA seed families that induce neuroblastoma cell differentiation. In addition, we showed that microRNA seed families were overrepresented in the identified group of fourteen differentiation-inducing microRNAs, suggesting that microRNA seed families are functionally more important in neuroblastoma differentiation than microRNAs with unique sequences. We further investigated the differentiation-inducing function of the microRNA-506-3p/microRNA-124-3p seed family, which was the most potent inducer of differentiation. We showed that the differentiation-inducing function of microRNA-506-3p/microRNA-124-3p is mediated, at least partially, by down-regulating expression of their targets CDK4 and STAT3. We further showed that expression of miR-506-3p, but not miR-124-3p, is dramatically upregulated in differentiated neuroblastoma cells, suggesting the important role of endogenous miR-506-3p in differentiation and tumorigenesis. Overall, our functional screen on microRNAs provided the first comprehensive analysis on the involvements of microRNA species in neuroblastoma cell differentiation and identified novel differentiation-inducing microRNAs. Further investigations are certainly warranted to fully characterize the function of the identified microRNAs in order to eventually benefit neuroblastoma therapy. PMID:24811707

  18. Male specific genes from dioecious white campion identified by fluorescent differential display.

    PubMed

    Scutt, Charles P; Jenkins, Tom; Furuya, Masaki; Gilmartin, Philip M

    2002-05-01

    Fluorescent differential display (FDD) has been used to screen for cDNAs that are differentially up-regulated in male flowers of the dioecious plant Silene latifolia in which an X/Y chromosome system of sex determination operates. To adapt FDD to the cloning of large numbers of differential cDNAs, a novel method of confirming the differential expression of these has been devised. FDD gels were Southern electro-blotted and probed with mixtures of individual cDNA clones derived from different FDD product ligation reactions. These Southern blots were then stripped and re-probed with further mixtures of individual cloned FDD products to identify the maximum number of recombinant clones carrying the true differential amplification products. Of 135 differential bands identified by FDD, 56 differential amplification products were confirmed; these represent 23 unique differentially expressed genes as determined by virtual Northern analysis and two genes expressed at or below the level of detection by virtual Northern analysis. These two low expressed genes show bands of hybridization on genomic Southern blots that are specific to male plants, indicating that they are derived from, or closely related to, Y chromosome genes.

  19. Lignin, mitochondrial family, and photorespiratory transporter classification as case studies in using co-expression, co-response, and protein locations to aid in identifying transport functions

    PubMed Central

    Tohge, Takayuki; Fernie, Alisdair R.

    2014-01-01

    Whole genome sequencing and the relative ease of transcript profiling have facilitated the collection and data warehousing of immense quantities of expression data. However, a substantial proportion of genes are not yet functionally annotated a problem which is particularly acute for transport proteins. In Arabidopsis, for example, only a minor fraction of the estimated 700 intracellular transporters have been identified at the molecular genetic level. Furthermore it is only within the last couple of years that critical genes such as those encoding the final transport step required for the long distance transport of sucrose and the first transporter of the core photorespiratory pathway have been identified. Here we will describe how transcriptional coordination between genes of known function and non-annotated genes allows the identification of putative transporters on the premise that such co-expressed genes tend to be functionally related. We will additionally extend this to include the expansion of this approach to include phenotypic information from other levels of cellular organization such as proteomic and metabolomic data and provide case studies wherein this approach has successfully been used to fill knowledge gaps in important metabolic pathways and physiological processes. PMID:24672529

  20. 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

  1. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

    PubMed Central

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  2. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

    PubMed

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

  3. Gene co-expression networks shed light into diseases of brain iron accumulation.

    PubMed

    Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M; Botía, Juan A; Collingwood, Joanna F; Hardy, John; Milward, Elizabeth A; Ryten, Mina; Houlden, Henry

    2016-03-01

    Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks

    PubMed Central

    2017-01-01

    Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing—with its unique statistical properties—became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca. PMID:28817636

  5. Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

    PubMed

    Ramachandran, Parameswaran; Sánchez-Taltavull, Daniel; Perkins, Theodore J

    2017-01-01

    Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca.

  6. Weighted gene co-expression network analysis of colorectal cancer liver metastasis genome sequencing data and screening of anti-metastasis drugs.

    PubMed

    Gao, Bo; Shao, Qin; Choudhry, Hani; Marcus, Victoria; Dong, Kung; Ragoussis, Jiannis; Gao, Zu-Hua

    2016-09-01

    Approximately 9% of cancer-related deaths are caused by colorectal cancer (CRC). CRC patients are prone to liver metastasis, which is the most important cause for the high CRC mortality rate. Understanding the molecular mechanism of CRC liver metastasis could help us to find novel targets for the effective treatment of this deadly disease. Using weighted gene co-expression network analysis on the sequencing data of CRC with and with metastasis, we identified 5 colorectal cancer liver metastasis related modules which were labeled as brown, blue, grey, yellow and turquoise. In the brown module, which represents the metastatic tumor in the liver, gene ontology (GO) analysis revealed functions including the G-protein coupled receptor protein signaling pathway, epithelial cell differentiation and cell surface receptor linked signal transduction. In the blue module, which represents the primary CRC that has metastasized, GO analysis showed that the genes were mainly enriched in GO terms including G-protein coupled receptor protein signaling pathway, cell surface receptor linked signal transduction, and negative regulation of cell differentiation. In the yellow and turquoise modules, which represent the primary non-metastatic CRC, 13 downregulated CRC liver metastasis-related candidate miRNAs were identified (e.g. hsa-miR-204, hsa-miR-455, etc.). Furthermore, analyzing the DrugBank database and mining the literature identified 25 and 12 candidate drugs that could potentially block the metastatic processes of the primary tumor and inhibit the progression of metastatic tumors in the liver, respectively. Data generated from this study not only furthers our understanding of the genetic alterations that drive the metastatic process, but also guides the development of molecular-targeted therapy of colorectal cancer liver metastasis.

  7. Systematic identification and comparison of expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in mouse germline stem cells

    PubMed Central

    Wu, Ji

    2017-01-01

    Accumulating evidence indicates that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) involve in germ cell development. However, little is known about the functions and mechanisms of lncRNAs and circRNAs in self-renewal and differentiation of germline stem cells. Therefore, we explored the expression profiles of mRNAs, lncRNAs, and circRNAs in male and female mouse germline stem cells by high-throughput sequencing. We identified 18573 novel lncRNAs and 18822 circRNAs in the germline stem cells and further confirmed the existence of these lncRNAs and circRNAs by RT-PCR. The results showed that male and female germline stem cells had similar GDNF signaling mechanism. Subsequently, 8115 mRNAs, 3996 lncRNAs, and 921 circRNAs exhibited sex-biased expression that may be associated with germline stem cell acquisition of the sex-specific properties required for differentiation into gametes. Gene Ontology (GO) and KEGG pathway enrichment analyses revealed different functions for these sex-biased lncRNAs and circRNAs. We further constructed correlated expression networks including coding–noncoding co-expression and competing endogenous RNAs with bioinformatics. Co-expression analysis showed hundreds of lncRNAs were correlated with sex differences in mouse germline stem cells, including lncRNA Gm11851, lncRNA Gm12840, lncRNA 4930405O22Rik, and lncRNA Atp10d. CeRNA network inferred that lncRNA Meg3 and cirRNA Igf1r could bind competitively with miRNA-15a-5p increasing target gene Inha, Acsl3, Kif21b, and Igfbp2 expressions. These findings provide novel perspectives on lncRNAs and circRNAs and lay a foundation for future research into the regulating mechanisms of lncRNAs and circRNAs in germline stem cells. PMID:28404936

  8. Single-cell RNA sequencing identifies diverse roles of epithelial cells in idiopathic pulmonary fibrosis

    PubMed Central

    Mizuno, Takako; Sridharan, Anusha; Du, Yina; Guo, Minzhe; Wikenheiser-Brokamp, Kathryn A.; Perl, Anne-Karina T.; Funari, Vincent A.; Gokey, Jason J.; Stripp, Barry R.; Whitsett, Jeffrey A.

    2016-01-01

    Idiopathic pulmonary fibrosis (IPF) is a lethal interstitial lung disease characterized by airway remodeling, inflammation, alveolar destruction, and fibrosis. We utilized single-cell RNA sequencing (scRNA-seq) to identify epithelial cell types and associated biological processes involved in the pathogenesis of IPF. Transcriptomic analysis of normal human lung epithelial cells defined gene expression patterns associated with highly differentiated alveolar type 2 (AT2) cells, indicated by enrichment of RNAs critical for surfactant homeostasis. In contrast, scRNA-seq of IPF cells identified 3 distinct subsets of epithelial cell types with characteristics of conducting airway basal and goblet cells and an additional atypical transitional cell that contributes to pathological processes in IPF. Individual IPF cells frequently coexpressed alveolar type 1 (AT1), AT2, and conducting airway selective markers, demonstrating “indeterminate” states of differentiation not seen in normal lung development. Pathway analysis predicted aberrant activation of canonical signaling via TGF-β, HIPPO/YAP, P53, WNT, and AKT/PI3K. Immunofluorescence confocal microscopy identified the disruption of alveolar structure and loss of the normal proximal-peripheral differentiation of pulmonary epithelial cells. scRNA-seq analyses identified loss of normal epithelial cell identities and unique contributions of epithelial cells to the pathogenesis of IPF. The present study provides a rich data source to further explore lung health and disease. PMID:27942595

  9. 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

  10. Loss of Trem2 in microglia leads to widespread disruption of cell coexpression networks in mouse brain.

    PubMed

    Carbajosa, Guillermo; Malki, Karim; Lawless, Nathan; Wang, Hong; Ryder, John W; Wozniak, Eva; Wood, Kristie; Mein, Charles A; Dobson, Richard J B; Collier, David A; O'Neill, Michael J; Hodges, Angela K; Newhouse, Stephen J

    2018-05-17

    Rare heterozygous coding variants in the triggering receptor expressed in myeloid cells 2 (TREM2) gene, conferring increased risk of developing late-onset Alzheimer's disease, have been identified. We examined the transcriptional consequences of the loss of Trem2 in mouse brain to better understand its role in disease using differential expression and coexpression network analysis of Trem2 knockout and wild-type mice. We generated RNA-Seq data from cortex and hippocampus sampled at 4 and 8 months. Using brain cell-type markers and ontology enrichment, we found subnetworks with cell type and/or functional identity. We primarily discovered changes in an endothelial gene-enriched subnetwork at 4 months, including a shift toward a more central role for the amyloid precursor protein gene, coupled with widespread disruption of other cell-type subnetworks, including a subnetwork with neuronal identity. We reveal an unexpected potential role of Trem2 in the homeostasis of endothelial cells that goes beyond its known functions as a microglial receptor and signaling hub, suggesting an underlying link between immune response and vascular disease in dementia. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  11. Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

    PubMed Central

    2012-01-01

    Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

  12. Visual pigment coexpression in all cones of two rodents, the Siberian hamster, and the pouched mouse.

    PubMed

    Lukáts, Akos; Dkhissi-Benyahya, Ouria; Szepessy, Zsuzsanna; Röhlich, Pál; Vígh, Béla; Bennett, Nigel C; Cooper, Howard M; Szél, Agoston

    2002-07-01

    To decide whether the identical topography of short- and middle-wavelength cone photoreceptors in two species of rodents reflects the presence of both opsins in all cone cells. Double-label immunocytochemistry using antibodies directed against short-wavelength (S)-and middle- to long-wavelength (M/L)-sensitive opsin were used to determine the presence of visual pigments in cones of two species of rodents, the Siberian hamster (Phodopus sungorus) and the pouched mouse (Saccostomus campestris) from South Africa. Topographical distribution was determined from retinal whole-mounts, and the colocalization of visual pigments was examined using confocal laser scanning microscopy. Opsin colocalization was also confirmed in consecutive semithin tangential sections. The immunocytochemical results demonstrate that in both the Siberian hamster and the pouched mouse all retinal cones contain two visual pigments. No dorsoventral gradient in the differential expression of the two opsins is observed. The retina of the Siberian hamster and the pouched mouse is the first example to show a uniform coexpression of M and S cone opsins in all cones, without any topographical gradient in opsin expression. This finding makes these two species good models for the study of molecular control mechanisms in opsin coexpression in rodents, and renders them suitable as sources of dual cones for future investigations on the role and neural connections of this cone type.

  13. Bacterial co-expression of human Tau protein with protein kinase A and 14-3-3 for studies of 14-3-3/phospho-Tau interaction

    PubMed Central

    Tugaeva, Kristina V.; Tsvetkov, Philipp O.

    2017-01-01

    Abundant regulatory 14-3-3 proteins have an extremely wide interactome and coordinate multiple cellular events via interaction with specifically phosphorylated partner proteins. Notwithstanding the key role of 14-3-3/phosphotarget interactions in many physiological and pathological processes, they are dramatically underexplored. Here, we focused on the 14-3-3 interaction with human Tau protein associated with the development of several neurodegenerative disorders, including Alzheimer’s and Parkinson’s diseases. Among many known phosphorylation sites within Tau, protein kinase A (PKA) phosphorylates several key residues of Tau and induces its tight interaction with 14-3-3 proteins. However, the stoichiometry and mechanism of 14-3-3 interaction with phosphorylated Tau (pTau) are not clearly elucidated. In this work, we describe a simple bacterial co-expression system aimed to facilitate biochemical and structural studies on the 14-3-3/pTau interaction. We show that dual co-expression of human fetal Tau with PKA in Escherichia coli results in multisite Tau phosphorylation including also naturally occurring sites which were not previously considered in the context of 14-3-3 binding. Tau protein co-expressed with PKA displays tight functional interaction with 14-3-3 isoforms of a different type. Upon triple co-expression with 14-3-3 and PKA, Tau protein could be co-purified with 14-3-3 and demonstrates complex which is similar to that formed in vitro between individual 14-3-3 and pTau obtained from dual co-expression. Although used in this study for the specific case of the previously known 14-3-3/pTau interaction, our co-expression system may be useful to study of other selected 14-3-3/phosphotarget interactions and for validations of 14-3-3 complexes identified by other methods. PMID:28575131

  14. Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

    PubMed Central

    2012-01-01

    Background WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of OsWD40 genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice. Results In this study, we identify and analyze 200 potential OsWD40 genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of OsWD40 were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 OsWD40 genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the OsWD40 genes in rice. The results suggested that OsWD40 genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that OsWD40 genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network. Conclusions All of these analyses suggest that the functions of OsWD40 genes are diversified, which provide useful references for selecting candidate genes for further functional studies. PMID:22429805

  15. Developmental Progression in the Coral Acropora digitifera Is Controlled by Differential Expression of Distinct Regulatory Gene Networks

    PubMed Central

    Reyes-Bermudez, Alejandro; Villar-Briones, Alejandro; Ramirez-Portilla, Catalina; Hidaka, Michio; Mikheyev, Alexander S.

    2016-01-01

    Corals belong to the most basal class of the Phylum Cnidaria, which is considered the sister group of bilaterian animals, and thus have become an emerging model to study the evolution of developmental mechanisms. Although cell renewal, differentiation, and maintenance of pluripotency are cellular events shared by multicellular animals, the cellular basis of these fundamental biological processes are still poorly understood. To understand how changes in gene expression regulate morphogenetic transitions at the base of the eumetazoa, we performed quantitative RNA-seq analysis during Acropora digitifera’s development. We collected embryonic, larval, and adult samples to characterize stage-specific transcription profiles, as well as broad expression patterns. Transcription profiles reconstructed development revealing two main expression clusters. The first cluster grouped blastula and gastrula and the second grouped subsequent developmental time points. Consistently, we observed clear differences in gene expression between early and late developmental transitions, with higher numbers of differentially expressed genes and fold changes around gastrulation. Furthermore, we identified three coexpression clusters that represented discrete gene expression patterns. During early transitions, transcriptional networks seemed to regulate cellular fate and morphogenesis of the larval body. In late transitions, these networks seemed to play important roles preparing planulae for switch in lifestyle and regulation of adult processes. Although developmental progression in A. digitifera is regulated to some extent by differential coexpression of well-defined gene networks, stage-specific transcription profiles appear to be independent entities. While negative regulation of transcription is predominant in early development, cell differentiation was upregulated in larval and adult stages. PMID:26941230

  16. A Dual-Intein Autoprocessing Domain that Directs Synchronized Protein Co-Expression in Both Prokaryotes and Eukaryotes

    PubMed Central

    Zhang, Bei; Rapolu, Madhusudhan; Liang, Zhibin; Han, Zhenlin; Williams, Philip G.; Su, Wei Wen

    2015-01-01

    Being able to coordinate co-expression of multiple proteins is necessary for a variety of important applications such as assembly of protein complexes, trait stacking, and metabolic engineering. Currently only few options are available for multiple recombinant protein co-expression, and most of them are not applicable to both prokaryotic and eukaryotic hosts. Here, we report a new polyprotein vector system that is based on a pair of self-excising mini-inteins fused in tandem, termed the dual-intein (DI) domain, to achieve synchronized co-expression of multiple proteins. The DI domain comprises an Ssp DnaE mini-intein N159A mutant and an Ssp DnaB mini-intein C1A mutant connected in tandem by a peptide linker to mediate efficient release of the flanking proteins via autocatalytic cleavage. Essentially complete release of constituent proteins, GFP and RFP (mCherry), from a polyprotein precursor, in bacterial, mammalian, and plant hosts was demonstrated. In addition, successful co-expression of GFP with chloramphenicol acetyltransferase, and thioredoxin with RFP, respectively, further substantiates the general applicability of the DI polyprotein system. Collectively, our results demonstrate the DI-based polyprotein technology as a highly valuable addition to the molecular toolbox for multi-protein co-expression which finds vast applications in biotechnology, biosciences, and biomedicine. PMID:25712612

  17. Coexpression of Nuclear Receptors and Histone Methylation Modifying Genes in the Testis: Implications for Endocrine Disruptor Modes of Action

    PubMed Central

    Anderson, Alison M.; Carter, Kim W.; Anderson, Denise; Wise, Michael J.

    2012-01-01

    Background Endocrine disruptor chemicals elicit adverse health effects by perturbing nuclear receptor signalling systems. It has been speculated that these compounds may also perturb epigenetic mechanisms and thus contribute to the early origin of adult onset disease. We hypothesised that histone methylation may be a component of the epigenome that is susceptible to perturbation. We used coexpression analysis of publicly available data to investigate the combinatorial actions of nuclear receptors and genes involved in histone methylation in normal testis and when faced with endocrine disruptor compounds. Methodology/Principal Findings The expression patterns of a set of genes were profiled across testis tissue in human, rat and mouse, plus control and exposed samples from four toxicity experiments in the rat. Our results indicate that histone methylation events are a more general component of nuclear receptor mediated transcriptional regulation in the testis than previously appreciated. Coexpression patterns support the role of a gatekeeper mechanism involving the histone methylation modifiers Kdm1, Prdm2, and Ehmt1 and indicate that this mechanism is a common determinant of transcriptional integrity for genes critical to diverse physiological endpoints relevant to endocrine disruption. Coexpression patterns following exposure to vinclozolin and dibutyl phthalate suggest that coactivity of the demethylase Kdm1 in particular warrants further investigation in relation to endocrine disruptor mode of action. Conclusions/Significance This study provides proof of concept that a bioinformatics approach that profiles genes related to a specific hypothesis across multiple biological settings can provide powerful insight into coregulatory activity that would be difficult to discern at an individual experiment level or by traditional differential expression analysis methods. PMID:22496781

  18. 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

  19. Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

    PubMed

    Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-10-01

    The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

  20. FastGCN: A GPU Accelerated Tool for Fast Gene Co-Expression Networks

    PubMed Central

    Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

    2015-01-01

    Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out. PMID:25602758

  1. FastGCN: a GPU accelerated tool for fast gene co-expression networks.

    PubMed

    Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

    2015-01-01

    Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

  2. Co-expression of five genes in E coli for L-phenylalanine in Brevibacterium flavum

    PubMed Central

    Wu, Yong-Qing; Jiang, Pei-Hong; Fan, Chang-Sheng; Wang, Jian-Gang; Shang, Liang; Huang, Wei-Da

    2003-01-01

    AIM: To study the effect of co-expression of ppsA, pckA, aroG, pheA and tyrB genes on the production of L-phenylalanine, and to construct a genetic engineering strain for L-phenylalanine. METHODS: ppsA and pckA genes were amplified from genomic DNA of E. coli by polymerase chain reaction, and then introduced into shuttle vectors between E coli and Brevibacterium flavum to generate constructs pJN2 and pJN5. pJN2 was generated by inserting ppsA and pckA genes into vector pCZ; whereas pJN5 was obtained by introducing ppsA and pckA genes into pCZ-GAB, which was originally constructed for co-expression of aroG, pheA and tyrB genes. The recombinant plasmids were then introduced into B. flavum by electroporation and the transformants were used for L-phenylalanine fermentation. RESULTS: Compared with the original B. flavum cells, all the transformants were showed to have increased five enzyme activities specifically, and have enhanced L-phenylalanine biosynthesis ability variably. pJN5 transformant was observed to have the highest elevation of L-phenylalanine production by a 3.4-fold. Co-expression of ppsA and pckA increased activity of DAHP synthetase significantly. CONCLUSION: Co-expression of ppsA and pckA genes in B. flavum could remarkably increase the expression of DAHP synthetase; Co-expression of ppsA, pckA, aroG, pheA and tyrB of E. coli in B. flavum was a feasible approach to construct a strain for phenylalanine production. PMID:12532463

  3. Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

    PubMed

    Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

    2012-01-01

    Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

  4. Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

    PubMed Central

    Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

    2012-01-01

    Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

  5. Differentiation of a Highly Tumorigenic Basal Cell Compartment in Urothelial Carcinoma

    PubMed Central

    He, Xiaobing; Marchionni, Luigi; Hansel, Donna E.; Yu, Wayne; Sood, Akshay; Yang, Jie; Parmigiani, Giovanni; Matsui, William; Berman, David M.

    2011-01-01

    Highly tumorigenic cancer cell (HTC) populations have been identified for a variety of solid tumors and assigned stem cell properties. Strategies for identifying HTCs in solid tumors have been primarily empirical rather than rational, particularly in epithelial tumors, which are responsible for 80% of cancer deaths. We report evidence for a spatially restricted bladder epithelial (urothelial) differentiation program in primary urothelial cancers (UCs) and in UC xenografts. We identified a highly tumorigenic UC cell compartment that resembles benign urothelial stem cells (basal cells), co-expresses the 67-kDa laminin receptor and the basal cell-specific cytokeratin CK17, and lacks the carcinoembryonic antigen family member CEACAM6 (CD66c). This multipotent compartment resides at the tumor-stroma interface, is easily identified on histologic sections, and possesses most, if not all, of the engraftable tumor-forming ability in the parental xenograft. We analyzed differential expression of genes and pathways in basal-like cells versus more differentiated cells. Among these, we found significant enrichment of pathways comprising “hallmarks” of cancer, and pharmacologically targetable signaling pathways, including Janus kinase-signal transducer and activator of transcription, Notch, focal adhesion, mammalian target of rapamycin, epidermal growth factor receptor (erythroblastic leukemia viral oncogene homolog [ErbB]), and wingless-type MMTV integration site family (Wnt). The basal/HTC gene expression signature was essentially invisible within the context of nontumorigenic cell gene expression and overlapped significantly with genes driving progression and death in primary human UC. The spatially restricted epithelial differentiation program described here represents a conceptual advance in understanding cellular heterogeneity of carcinomas and identifies basal-like HTCs as attractive targets for cancer therapy. PMID:19544456

  6. Modulating secretory pathway pH by proton channel co-expression can increase recombinant protein stability in plants.

    PubMed

    Jutras, Philippe V; D'Aoust, Marc-André; Couture, Manon M-J; Vézina, Louis-Philippe; Goulet, Marie-Claire; Michaud, Dominique; Sainsbury, Frank

    2015-09-01

    Eukaryotic expression systems are used for the production of complex secreted proteins. However, recombinant proteins face considerable biochemical challenges along the secretory pathway, including proteolysis and pH variation between organelles. As the use of synthetic biology matures into solutions for protein production, various host-cell engineering approaches are being developed to ameliorate host-cell factors that can limit recombinant protein quality and yield. We report the potential of the influenza M2 ion channel as a novel tool to neutralize the pH in acidic subcellular compartments. Using transient expression in the plant host, Nicotiana benthamiana, we show that ion channel expression can significantly raise pH in the Golgi apparatus and that this can have a strong stabilizing effect on a fusion protein separated by an acid-susceptible linker peptide. We exemplify the utility of this effect in recombinant protein production using influenza hemagglutinin subtypes differentially stable at low pH; the expression of hemagglutinins prone to conformational change in mildly acidic conditions is considerably enhanced by M2 co-expression. The co-expression of a heterologous ion channel to stabilize acid-labile proteins and peptides represents a novel approach to increasing the yield and quality of secreted recombinant proteins in plants and, possibly, in other eukaryotic expression hosts. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. 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.

  8. Coexpression network based on natural variation in human gene expression reveals gene interactions and functions

    PubMed Central

    Nayak, Renuka R.; Kearns, Michael; Spielman, Richard S.; Cheung, Vivian G.

    2009-01-01

    Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including CHCHD2 and TMEM111, and provided experimental evidence that TMEM111 is part of the endoplasmic reticulum-associated secretory pathway. We also found that IFIH1, a susceptibility gene of type 1 diabetes, interacts with YES1, which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes. PMID:19797678

  9. Gene Coexpression Network Alignment and Conservation of Gene Modules between Two Grass Species: Maize and Rice[C][W][OA

    PubMed Central

    Ficklin, Stephen P.; Feltus, F. Alex

    2011-01-01

    One major objective for plant biology is the discovery of molecular subsystems underlying complex traits. The use of genetic and genomic resources combined in a systems genetics approach offers a means for approaching this goal. This study describes a maize (Zea mays) gene coexpression network built from publicly available expression arrays. The maize network consisted of 2,071 loci that were divided into 34 distinct modules that contained 1,928 enriched functional annotation terms and 35 cofunctional gene clusters. Of note, 391 maize genes of unknown function were found to be coexpressed within modules along with genes of known function. A global network alignment was made between this maize network and a previously described rice (Oryza sativa) coexpression network. The IsoRankN tool was used, which incorporates both gene homology and network topology for the alignment. A total of 1,173 aligned loci were detected between the two grass networks, which condensed into 154 conserved subgraphs that preserved 4,758 coexpression edges in rice and 6,105 coexpression edges in maize. This study provides an early view into maize coexpression space and provides an initial network-based framework for the translation of functional genomic and genetic information between these two vital agricultural species. PMID:21606319

  10. Identifying Differentially Abundant Metabolic Pathways in Metagenomic Datasets

    NASA Astrophysics Data System (ADS)

    Liu, Bo; Pop, Mihai

    Enabled by rapid advances in sequencing technology, metagenomic studies aim to characterize entire communities of microbes bypassing the need for culturing individual bacterial members. One major goal of such studies is to identify specific functional adaptations of microbial communities to their habitats. Here we describe a powerful analytical method (MetaPath) that can identify differentially abundant pathways in metagenomic data-sets, relying on a combination of metagenomic sequence data and prior metabolic pathway knowledge. We show that MetaPath outperforms other common approaches when evaluated on simulated datasets. We also demonstrate the power of our methods in analyzing two, publicly available, metagenomic datasets: a comparison of the gut microbiome of obese and lean twins; and a comparison of the gut microbiome of infant and adult subjects. We demonstrate that the subpathways identified by our method provide valuable insights into the biological activities of the microbiome.

  11. Mini-P-gp and P-gp Co-Expression in Brown Trout Erythrocytes: A Prospective Blood Biomarker of Aquatic Pollution

    PubMed Central

    Valton, Emeline; Amblard, Christian; Desmolles, François; Combourieu, Bruno; Penault-Llorca, Frédérique; Bamdad, Mahchid

    2015-01-01

    In aquatic organisms, such as fish, blood is continually exposed to aquatic contaminants. Multidrug Resistance (MDR) proteins are ubiquitous detoxification membrane pumps, which recognize various xenobiotics. Moreover, their expression is induced by a large class of drugs and pollutants. We have highlighted the co-expression of a mini P-gp of 75 kDa and a P-gp of 140 kDa in the primary culture of brown trout erythrocytes and in the erythrocytes of wild brown trout collected from three rivers in the Auvergne region of France. In vitro experiments showed that benzo[a]pyrene, a highly toxic pollutant model, induced the co-expression of mini-P-gp and P-gp in trout erythrocytes in a dose-dependent manner and relay type response. Similarly, in the erythrocytes of wild brown trout collected from rivers contaminated by a mixture of PAH and other multi-residues of pesticides, mini-P-gp and P-gp were able to modulate their expression, according to the nature of the pollutants. The differential and complementary responses of mini-P-gp and P-gp in trout erythrocytes suggest the existence in blood cells of a real protective network against xenobiotics/drugs. This property could be exploited to develop a blood biomarker of river pollution. PMID:26854141

  12. 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.

  13. Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences.

    PubMed

    Colonna, Vincenza; Ayub, Qasim; Chen, Yuan; Pagani, Luca; Luisi, Pierre; Pybus, Marc; Garrison, Erik; Xue, Yali; Tyler-Smith, Chris; Abecasis, Goncalo R; Auton, Adam; Brooks, Lisa D; DePristo, Mark A; Durbin, Richard M; Handsaker, Robert E; Kang, Hyun Min; Marth, Gabor T; McVean, Gil A

    2014-06-30

    Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes. We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively. We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

  14. Differentiated transcriptional signatures in the maize landraces of Chiapas, Mexico.

    PubMed

    Kost, Matthew A; Perales, Hugo R; Wijeratne, Saranga; Wijeratne, Asela J; Stockinger, Eric; Mercer, Kristin L

    2017-09-08

    Landrace farmers are the keepers of crops locally adapted to the environments where they are cultivated. Patterns of diversity across the genome can provide signals of past evolution in the face of abiotic and biotic change. Understanding this rich genetic resource is imperative especially since diversity can provide agricultural security as climate continues to shift. Here we employ RNA sequencing (RNA-seq) to understand the role that conditions that vary across a landscape may have played in shaping genetic diversity in the maize landraces of Chiapas, Mexico. We collected landraces from three distinct elevational zones and planted them in a midland common garden. Early season leaf tissue was collected for RNA-seq and we performed weighted gene co-expression network analysis (WGCNA). We then used association analysis between landrace co-expression module expression values and environmental parameters of landrace origin to elucidate genes and gene networks potentially shaped by environmental factors along our study gradient. Elevation of landrace origin affected the transcriptome profiles. Two co-expression modules were highly correlated with temperature parameters of landrace origin and queries into their 'hub' genes suggested that temperature may have led to differentiation among landraces in hormone biosynthesis/signaling and abiotic and biotic stress responses. We identified several 'hub' transcription factors and kinases as candidates for the regulation of these responses. These findings indicate that natural selection may influence the transcriptomes of crop landraces along an elevational gradient in a major diversity center, and provide a foundation for exploring the genetic basis of local adaptation. While we cannot rule out the role of neutral evolutionary forces in the patterns we have identified, combining whole transcriptome sequencing technologies, established bioinformatics techniques, and common garden experimentation can powerfully elucidate

  15. 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.

  16. 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.

  17. LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering.

    PubMed

    Specht, Alicia T; Li, Jun

    2017-03-01

    To construct gene co-expression networks based on single-cell RNA-Sequencing data, we present an algorithm called LEAP, which utilizes the estimated pseudotime of the cells to find gene co-expression that involves time delay. R package LEAP available on CRAN. jun.li@nd.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  18. A co-expression gene network associated with developmental regulation of apple fruit acidity.

    PubMed

    Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Xu, Kenong

    2015-08-01

    Apple fruit acidity, which affects the fruit's overall taste and flavor to a large extent, is primarily determined by the concentration of malic acid. Previous studies demonstrated that the major QTL malic acid (Ma) on chromosome 16 is largely responsible for fruit acidity variations in apple. Recent advances suggested that a natural mutation that gives rise to a premature stop codon in one of the two aluminum-activated malate transporter (ALMT)-like genes (called Ma1) is the genetic causal element underlying Ma. However, the natural mutation does not explain the developmental changes of fruit malate levels in a given genotype. Using RNA-seq data from the fruit of 'Golden Delicious' taken at 14 developmental stages from 1 week after full-bloom (WAF01) to harvest (WAF20), we characterized their transcriptomes in groups of high (12.2 ± 1.6 mg/g fw, WAF03-WAF08), mid (7.4 ± 0.5 mg/g fw, WAF01-WAF02 and WAF10-WAF14) and low (5.4 ± 0.4 mg/g fw, WAF16-WAF20) malate concentrations. Detailed analyses showed that a set of 3,066 genes (including Ma1) were expressed not only differentially (P FDR < 0.05) between the high and low malate groups (or between the early and late developmental stages) but also in significant (P < 0.05) correlation with malate concentrations. The 3,066 genes fell in 648 MapMan (sub-) bins or functional classes, and 19 of them were significantly (P FDR < 0.05) co-enriched or co-suppressed in a malate dependent manner. Network inferring using the 363 genes encompassed in the 19 (sub-) bins, identified a major co-expression network of 239 genes. Since the 239 genes were also differentially expressed between the early (WAF03-WAF08) and late (WAF16-WAF20) developmental stages, the major network was considered to be associated with developmental regulation of apple fruit acidity in 'Golden Delicious'.

  19. 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.

  20. Co-expression of HIV-1 virus-like particles and granulocyte-macrophage colony stimulating factor by GEO-D03 DNA vaccine.

    PubMed

    Hellerstein, Michael; Xu, Yongxian; Marino, Tracie; Lu, Shan; Yi, Hong; Wright, Elizabeth R; Robinson, Harriet L

    2012-11-01

    Here, we report on GEO-D03, a DNA vaccine that co-expresses non-infectious HIV-1 virus-like particles (VLPs) and the human cytokine, granulocyte-macrophage colony-stimulating factor (GM-CSF). The virus-like particles display the native gp160 form of the HIV-1 Envelope glycoprotein (Env) and are designed to elicit antibody against the natural form of Env on virus and virus-infected cells. The DNA-expressed HIV Gag, Pol and Env proteins also have the potential to elicit virus-specific CD4 and CD8 T cells. The purpose of the co-expressed GM-CSF is to target a cytokine that recruits, expands and differentiates macrophages and dendritic cells to the site of VLP expression. The GEO-D03 DNA vaccine is currently entered into human trials as a prime for a recombinant modified vaccinia Ankara (MVA) boost. In preclinical studies in macaques using an SIV prototype vaccine, this vaccination regimen elicited both anti-viral T cells and antibody, and provided 70% protection against acquisition during 12 weekly rectal exposures with a heterologous SIV. Higher avidity of the Env-specific Ab for the native form of the Env in the challenge virus correlated with lower likelihood of SIV infection.

  1. The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

    PubMed Central

    Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

    2010-01-01

    Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

  2. 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

  3. Regulation of gap junctional charge selectivity in cells coexpressing connexin 40 and connexin 43.

    PubMed

    Heyman, Nathanael S; Kurjiaka, David T; Ek Vitorin, Jose F; Burt, Janis M

    2009-07-01

    Expression of connexin 40 (Cx40) and Cx43 in cardiovascular tissues varies as a function of age, injury, and development with unknown consequences on the selectivity of junctional communication and its acute regulation. We investigated the PKC-dependent regulation of charge selectivity in junctions composed of Cx43, Cx40, or both by simultaneous assessment of junctional permeance rate constants (B(dye)) for dyes of similar size but opposite charge, N,N,N-trimethyl-2-[methyl-(7-nitro-2,1,3-benzoxadiol-4-yl)amino]ethanaminium (NBD-M-TMA; +1) and Alexa 350 (-1). The ratio of dye rate constants (B(NBD-M-TMA)/B(Alexa 350)) indicated that Cx40 junctions are cation selective (10.7 +/- 0.5), whereas Cx43 junction are nonselective (1.22 +/- 0.14). In coexpressing cells, a broad range of junctional selectivities was observed with mean cation selectivity increasing as the Cx40 to Cx43 expression ratio increased. PKC activation reduced or eliminated dye permeability of Cx43 junctions without altering their charge selectivity, had no effect on either permeability or charge selectivity of Cx40 junctions, and significantly increased the cation selectivity of junctions formed by coexpressing cells (approaching charge selectivity of Cx40 junctions). Junctions composed of Cx43 truncated at residue 257 (Cx43tr) were also not charge selective, but when Cx43tr was coexpressed with Cx40, a broad range of junctional selectivities that was unaffected by PKC activation was observed. Thus, whereas the charge selectivities of homomeric/homotypic Cx43 and Cx40 junctions appear invariant, the selectivities of junctions formed by cells coexpressing Cx40 and Cx43 vary considerably, reflecting both their relative expression levels and phosphorylation-dependent regulation. Such regulation could represent a mechanism by which coexpressing cells such as vascular endothelium and atrial cells regulate acutely the selective intercellular communication mediated by their gap junctions.

  4. 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

  5. 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

  6. Identification of transcript regulatory patterns in cell differentiation.

    PubMed

    Gusnanto, Arief; Gosling, John Paul; Pope, Christopher

    2017-10-15

    Studying transcript regulatory patterns in cell differentiation is critical in understanding its complex nature of the formation and function of different cell types. This is done usually by measuring gene expression at different stages of the cell differentiation. However, if the gene expression data available are only from the mature cells, we have some challenges in identifying transcript regulatory patterns that govern the cell differentiation. We propose to exploit the information of the lineage of cell differentiation in terms of correlation structure between cell types. We assume that two different cell types that are close in the lineage will exhibit many common genes that are co-expressed relative to those that are far in the lineage. Current analysis methods tend to ignore this correlation by testing for differential expression assuming some sort of independence between cell types. We employ a Bayesian approach to estimate the posterior distribution of the mean of expression in each cell type, by taking into account the cell formation path in the lineage. This enables us to infer genes that are specific in each cell type, indicating the genes are involved in directing the cell differentiation to that particular cell type. We illustrate the method using gene expression data from a study of haematopoiesis. R codes to perform the analysis are available in http://www1.maths.leeds.ac.uk/∼arief/R/CellDiff/. a.gusnanto@leeds.ac.uk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  7. CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.

    PubMed

    Wang, Hong-Qiang; Tsai, Chung-Jui

    2013-01-01

    With the rapid increase of omics data, correlation analysis has become an indispensable tool for inferring meaningful associations from a large number of observations. Pearson correlation coefficient (PCC) and its variants are widely used for such purposes. However, it remains challenging to test whether an observed association is reliable both statistically and biologically. We present here a new method, CorSig, for statistical inference of correlation significance. CorSig is based on a biology-informed null hypothesis, i.e., testing whether the true PCC (ρ) between two variables is statistically larger than a user-specified PCC cutoff (τ), as opposed to the simple null hypothesis of ρ = 0 in existing methods, i.e., testing whether an association can be declared without a threshold. CorSig incorporates Fisher's Z transformation of the observed PCC (r), which facilitates use of standard techniques for p-value computation and multiple testing corrections. We compared CorSig against two methods: one uses a minimum PCC cutoff while the other (Zhu's procedure) controls correlation strength and statistical significance in two discrete steps. CorSig consistently outperformed these methods in various simulation data scenarios by balancing between false positives and false negatives. When tested on real-world Populus microarray data, CorSig effectively identified co-expressed genes in the flavonoid pathway, and discriminated between closely related gene family members for their differential association with flavonoid and lignin pathways. The p-values obtained by CorSig can be used as a stand-alone parameter for stratification of co-expressed genes according to their correlation strength in lieu of an arbitrary cutoff. CorSig requires one single tunable parameter, and can be readily extended to other correlation measures. Thus, CorSig should be useful for a wide range of applications, particularly for network analysis of high-dimensional genomic data. A web server for

  8. Estimation of the proteomic cancer co-expression sub networks by using association estimators.

    PubMed

    Erdoğan, Cihat; Kurt, Zeyneb; Diri, Banu

    2017-01-01

    In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

  9. Estimation of the proteomic cancer co-expression sub networks by using association estimators

    PubMed Central

    Kurt, Zeyneb; Diri, Banu

    2017-01-01

    In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators’ performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists. PMID:29145449

  10. 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

  11. 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

  12. Transcriptome display during tilapia sex determination and differentiation as revealed by RNA-Seq analysis.

    PubMed

    Tao, Wenjing; Chen, Jinlin; Tan, Dejie; Yang, Jing; Sun, Lina; Wei, Jing; Conte, Matthew A; Kocher, Thomas D; Wang, Deshou

    2018-05-15

    The factors determining sex in teleosts are diverse. Great efforts have been made to characterize the underlying genetic network in various species. However, only seven master sex-determining genes have been identified in teleosts. While the function of a few genes involved in sex determination and differentiation has been studied, we are far from fully understanding how genes interact to coordinate in this process. To enable systematic insights into fish sexual differentiation, we generated a dynamic co-expression network from tilapia gonadal transcriptomes at 5, 20, 30, 40, 90, and 180 dah (days after hatching), plus 45 and 90 dat (days after treatment) and linked gene expression profiles to both development and sexual differentiation. Transcriptomic profiles of female and male gonads at 5 and 20 dah exhibited high similarities except for a small number of genes that were involved in sex determination, while drastic changes were observed from 90 to 180 dah, with a group of differently expressed genes which were involved in gonadal differentiation and gametogenesis. Weighted gene correlation network analysis identified changes in the expression of Borealin, Gtsf1, tesk1, Zar1, Cdn15, and Rpl that were correlated with the expression of genes previously known to be involved in sex differentiation, such as Foxl2, Cyp19a1a, Gsdf, Dmrt1, and Amh. Global gonadal gene expression kinetics during sex determination and differentiation have been extensively profiled in tilapia. These findings provide insights into the genetic framework underlying sex determination and sexual differentiation, and expand our current understanding of developmental pathways during teleost sex determination.

  13. Uncovering co-expression gene network modules regulating fruit acidity in diverse apples.

    PubMed

    Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

    2015-08-16

    Acidity is a major contributor to fruit quality. Several organic acids are present in apple fruit, but malic acid is predominant and determines fruit acidity. The trait is largely controlled by the Malic acid (Ma) locus, underpinning which Ma1 that putatively encodes a vacuolar aluminum-activated malate transporter1 (ALMT1)-like protein is a strong candidate gene. We hypothesize that fruit acidity is governed by a gene network in which Ma1 is key member. The goal of this study is to identify the gene network and the potential mechanisms through which the network operates. Guided by Ma1, we analyzed the transcriptomes of mature fruit of contrasting acidity from six apple accessions of genotype Ma_ (MaMa or Mama) and four of mama using RNA-seq and identified 1301 fruit acidity associated genes, among which 18 were most significant acidity genes (MSAGs). Network inferring using weighted gene co-expression network analysis (WGCNA) revealed five co-expression gene network modules of significant (P < 0.001) correlation with malate. Of these, the Ma1 containing module (Turquoise) of 336 genes showed the highest correlation (0.79). We also identified 12 intramodular hub genes from each of the five modules and 18 enriched gene ontology (GO) terms and MapMan sub-bines, including two GO terms (GO:0015979 and GO:0009765) and two MapMap sub-bins (1.3.4 and 1.1.1.1) related to photosynthesis in module Turquoise. Using Lemon-Tree algorithms, we identified 12 regulator genes of probabilistic scores 35.5-81.0, including MDP0000525602 (a LLR receptor kinase), MDP0000319170 (an IQD2-like CaM binding protein) and MDP0000190273 (an EIN3-like transcription factor) of greater interest for being one of the 18 MSAGs or one of the 12 intramodular hub genes in Turquoise, and/or a regulator to the cluster containing Ma1. The most relevant finding of this study is the identification of the MSAGs, intramodular hub genes, enriched photosynthesis related processes, and regulator genes in a

  14. Differential coexpression of FoxP1, FoxP2, and FoxP4 in the Zebra Finch (Taeniopygia guttata) song system.

    PubMed

    Mendoza, Ezequiel; Tokarev, Kirill; Düring, Daniel N; Retamosa, Eva Camarillo; Weiss, Michael; Arpenik, Nshdejan; Scharff, Constance

    2015-06-15

    Heterozygous disruptions of the Forkhead transcription factor FoxP2 impair acquisition of speech and language. Experimental downregulation in brain region Area X of the avian ortholog FoxP2 disrupts song learning in juvenile male zebra finches. In vitro, transcriptional activity of FoxP2 requires dimerization with itself or with paralogs FoxP1 and FoxP4. Whether this is the case in vivo is unknown. To provide the means for future functional studies we cloned FoxP4 from zebra finches and compared regional and cellular coexpression of FoxP1, FoxP2, and FoxP4 mRNA and protein in brains of juvenile and adult male zebra finches. In the telencephalic song nuclei HVC, RA, and Area X, the three investigated FoxPs were either expressed alone or occurred in specific combinations with each other, as shown by double in situ hybridization and triple immunohistochemistry. FoxP1 and FoxP4 but not FoxP2 were expressed in RA and in the HVCRA and HVCX projection neurons. In Area X and the surrounding striatum the density of neurons expressing all three FoxPs together or FoxP1 and FoxP4 together was significantly higher than the density of neurons expressing other combinations. Interestingly, the proportions of Area X neurons expressing particular combinations of FoxPs remained constant at all ages. In addition, FoxP-expressing neurons in adult Area X express dopamine receptors 1A, 1B, and 2. Together, these data provide the first evidence that Area X neurons can coexpress all avian FoxP subfamily members, thus allowing for a variety of regulatory possibilities via heterodimerization that could impact song behavior in zebra finches. © 2014 Wiley Periodicals, Inc.

  15. Differential effects of Notch ligands Delta-1 and Jagged-1 in human lymphoid differentiation.

    PubMed

    Jaleco, A C; Neves, H; Hooijberg, E; Gameiro, P; Clode, N; Haury, M; Henrique, D; Parreira, L

    2001-10-01

    Notch signaling is known to differentially affect the development of lymphoid B and T cell lineages, but it remains unclear whether such effects are specifically dependent on distinct Notch ligands. Using a cell coculture assay we observed that the Notch ligand Delta-1 completely inhibits the differentiation of human hematopoietic progenitors into the B cell lineage while promoting the emergence of cells with a phenotype of T cell/natural killer (NK) precursors. In contrast, Jagged-1 did not disturb either B or T cell/NK development. Furthermore, cells cultured in the presence of either Delta-1 or Jagged-1 can acquire a phenotype of NK cells, and Delta-1, but not Jagged-1, permits the emergence of a de novo cell population coexpressing CD4 and CD8. Our results thus indicate that distinct Notch ligands can mediate differential effects of Notch signaling and provide a useful system to further address cell-fate decision processes in lymphopoiesis.

  16. Differential Effects of Notch Ligands Delta-1 and Jagged-1 in Human Lymphoid Differentiation

    PubMed Central

    Jaleco, Ana C.; Neves, Hélia; Hooijberg, Erik; Gameiro, Paula; Clode, Nuno; Haury, Matthias; Henrique, Domingos; Parreira, Leonor

    2001-01-01

    Notch signaling is known to differentially affect the development of lymphoid B and T cell lineages, but it remains unclear whether such effects are specifically dependent on distinct Notch ligands. Using a cell coculture assay we observed that the Notch ligand Delta-1 completely inhibits the differentiation of human hematopoietic progenitors into the B cell lineage while promoting the emergence of cells with a phenotype of T cell/natural killer (NK) precursors. In contrast, Jagged-1 did not disturb either B or T cell/NK development. Furthermore, cells cultured in the presence of either Delta-1 or Jagged-1 can acquire a phenotype of NK cells, and Delta-1, but not Jagged-1, permits the emergence of a de novo cell population coexpressing CD4 and CD8. Our results thus indicate that distinct Notch ligands can mediate differential effects of Notch signaling and provide a useful system to further address cell-fate decision processes in lymphopoiesis. PMID:11581320

  17. 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.

  18. Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy.

    PubMed

    Ilin, Yelena; Choi, Ji Sun; Harley, Brendan A C; Kraft, Mary L

    2015-11-17

    A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that

  19. 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

  20. 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

  1. 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

  2. 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

  3. Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response

    DOE PAGES

    Li, Jiying; Hu, Jianping; Bassham, Diane

    2015-09-14

    Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co-expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Usingmore » microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co-expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their coexpression pattern. Since drought caused expression changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay. Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Lastly, our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to

  4. Transcriptomic Analysis of Paeonia delavayi Wild Population Flowers to Identify Differentially Expressed Genes Involved in Purple-Red and Yellow Petal Pigmentation

    PubMed Central

    Wang, Yan; Li, Kui; Zheng, Baoqiang; Miao, Kun

    2015-01-01

    Tree peony (Paeonia suffruticosa Andrews) is a very famous traditional ornamental plant in China. P. delavayi is a species endemic to Southwest China that has aroused great interest from researchers as a precious genetic resource for flower color breeding. However, the current understanding of the molecular mechanisms of flower pigmentation in this plant is limited, hindering the genetic engineering of novel flower color in tree peonies. In this study, we conducted a large-scale transcriptome analysis based on Illumina HiSeq sequencing of cDNA libraries generated from yellow and purple-red P. delavayi petals. A total of 90,202 unigenes were obtained by de novo assembly, with an average length of 721 nt. Using Blastx, 44,811 unigenes (49.68%) were found to have significant similarity to accessions in the NR, NT, and Swiss-Prot databases. We also examined COG, GO and KEGG annotations to better understand the functions of these unigenes. Further analysis of the two digital transcriptomes revealed that 6,855 unigenes were differentially expressed between yellow and purple-red flower petals, with 3,430 up-regulated and 3,425 down-regulated. According to the RNA-Seq data and qRT-PCR analysis, we proposed that four up-regulated key structural genes, including F3H, DFR, ANS and 3GT, might play an important role in purple-red petal pigmentation, while high co-expression of THC2'GT, CHI and FNS II ensures the accumulation of pigments contributing to the yellow color. We also found 50 differentially expressed transcription factors that might be involved in flavonoid biosynthesis. This study is the first to report genetic information for P. delavayi. The large number of gene sequences produced by transcriptome sequencing and the candidate genes identified using pathway mapping and expression profiles will provide a valuable resource for future association studies aimed at better understanding the molecular mechanisms underlying flower pigmentation in tree peonies. PMID

  5. Lack of cilia and differentiation defects in the liver of human foetuses with the Meckel syndrome.

    PubMed

    Clotman, Frédéric; Libbrecht, Louis; Killingsworth, Murray C; Loo, Christine C K; Roskams, Tania; Lemaigre, Frédéric P

    2008-03-01

    Meckel syndrome is an autosomal-recessive disease characterized by a combination of renal cysts, anomalies of the central nervous system, polydactyly and ductal plate malformations (DPM), which are hepatic anomalies consisting of excessive and abnormal foetal biliary structures. Among the genomic loci associated with Meckel syndrome, mutations in four genes were recently identified. These genes code for proteins associated with primary cilia and are possibly involved in cell differentiation. The aim of the present work was to investigate the formation of the primary cilia and the differentiation of the hepatic cells in foetuses with Meckel syndrome. Sections of livers from human foetuses with Meckel syndrome were analysed by immunofluorescence, immunohistochemistry and electron microscopy. The primary cilia of the biliary cells were absent in some Meckel foetuses, but were present in others. In addition, defects in hepatic differentiation were observed in Meckel livers, as evidenced by the presence of hybrid cells co-expressing hepatocytic and biliary markers. Defects in cilia formation occur in some Meckel livers, and most cases show DPM associated with abnormal hepatic cell differentiation. Because differentiation precedes the formation of the cilia during liver development, we propose that defective differentiation may constitute the initial defect in the liver of Meckel syndrome foetuses.

  6. MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation

    PubMed Central

    Wang, Luman; Mo, Qiaochu; Wang, Jianxin

    2015-01-01

    Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches. PMID:26881263

  7. MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation.

    PubMed

    Wang, Luman; Mo, Qiaochu; Wang, Jianxin

    2015-01-01

    Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.

  8. Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes.

    PubMed

    Wang, Ya-Xuan; Gao, Ying-Lian; Liu, Jin-Xing; Kong, Xiang-Zhen; Li, Hai-Jun

    2017-09-01

    Identifying differentially expressed genes from the thousands of genes is a challenging task. Robust principal component analysis (RPCA) is an efficient method in the identification of differentially expressed genes. RPCA method uses nuclear norm to approximate the rank function. However, theoretical studies showed that the nuclear norm minimizes all singular values, so it may not be the best solution to approximate the rank function. The truncated nuclear norm is defined as the sum of some smaller singular values, which may achieve a better approximation of the rank function than nuclear norm. In this paper, a novel method is proposed by replacing nuclear norm of RPCA with the truncated nuclear norm, which is named robust principal component analysis regularized by truncated nuclear norm (TRPCA). The method decomposes the observation matrix of genomic data into a low-rank matrix and a sparse matrix. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Thus, the differentially expressed genes can be identified according to the sparse matrix. The experimental results on The Cancer Genome Atlas data illustrate that the TRPCA method outperforms other state-of-the-art methods in the identification of differentially expressed genes.

  9. Positive prognostic value of HER2-HER3 co-expression and p-mTOR in gastric cancer patients.

    PubMed

    Cao, Guo-Dong; Chen, Ke; Chen, Bo; Xiong, Mao-Ming

    2017-12-12

    The HER2-HER3 heterodimer significantly decreases survival in breast cancer patients. However, the prognostic value of HER2-HER3 overexpression remains unknown in gastric cancer (GC). The expression levels of HER2, HER3, Akt, p-Akt, mTOR and p-mTOR were examined in specimens from 120 GC patients by immunohistochemistry and quantitative reverse transcription-PCR. The associations of HER proteins, PI3K/Akt/mTOR pathway-related proteins, clinicopathological features of GC, and overall survival (OS) were assessed. To comprehensively evaluate the prognostic values of pathway-related proteins, meta-analyses were conducted with STATA 11.0. HER2 overexpression was significantly associated with HER3 levels (P = 0.02). HER3 was highly expressed in gastric cancer tissues. High HER2 and HER3 levels were associated with elevated p-Akt and p-mTOR amounts (P < 0.05). Furthermore, HER2-HER3 co-expression was associated with high p-Akt and p-mTOR (P < 0.05) levels. Meanwhile, p-mTOR overexpression was tightly associated with differentiation, depth of invasion, lymph node metastasis, TNM stage and OS (P < 0.05). By meta-analyses, Akt, p-Akt, and mTOR levels were unrelated to clinicopathological characters. HER3 overexpression was associated with depth of invasion (OR = 2.39, 95%CI 1.62-3.54, P < 0.001) and lymph node metastasis (OR = 2.35, 95%CI 1.34-4.11, P = 0.003). Further, p-mTOR overexpression was associated with patient age, tumor location, depth of invasion (OR = 1.63, 95%CI 1.08-2.45, P = 0.02) and TNM stage (OR = 1.73, 95%CI 1.29-2.32, P < 0.001). In addition, HER2-HER3 overexpression corresponded to gradually shortened 5-year OS (P < 0.05), and significant relationships were shown among HER3, p-mTOR overexpression, and 1-, 3-, 5-year OS (P < 0.05). HER2-HER3 co-expression may potentially enhance mTOR phosphorylation. HER2-HER3 co-expression and p-mTOR are both related to the prognosis of GC patients.

  10. Mct8 and trh co-expression throughout the hypothalamic paraventricular nucleus is modified by dehydration-induced anorexia in rats.

    PubMed

    Alvarez-Salas, Elena; Mengod, Guadalupe; García-Luna, Cinthia; Soberanes-Chávez, Paulina; Matamoros-Trejo, Gilberto; de Gortari, Patricia

    2016-04-01

    Thyrotropin-releasing hormone (TRH) is a neuropeptide with endocrine and neuromodulatory effects. TRH from the paraventricular hypothalamic nucleus (PVN) participates in the control of energy homeostasis; as a neuromodulator TRH has anorexigenic effects. Negative energy balance decreases PVN TRH expression and TSH concentration; in contrast, a particular model of anorexia (dehydration) induces in rats a paradoxical increase in TRH expression in hypophysiotropic cells from caudal PVN and high TSH serum levels, despite their apparent hypothalamic hyperthyroidism and low body weight. We compared here the mRNA co-expression pattern of one of the brain thyroid hormones' transporters, the monocarboxylate transporter-8 (MCT8) with that of TRH in PVN subdivisions of dehydration-induced anorexic (DIA) and control rats. Our aim was to identify whether a low MCT8 expression in anorexic rats could contribute to their high TRH mRNA content.We registered daily food intake and body weight of 7-day DIA and control rats and analyzed TRH and MCT8 mRNA co-expression throughout the PVN by double in situ hybridization assays. We found that DIA rats showed increased number of TRHergic cells in caudal PVN, as well as a decreased percentage of TRH-expressing neurons that co-expressed MCT8 mRNA signal. Results suggest that the reduced proportion of double TRH/MCT8 expressing cells may be limiting the entry of hypothalamic triiodothyronine to the greater number of TRH-expressing neurons from caudal PVN and be in part responsible for the high TRH expression in anorexia rats and for the lack of adaptation of their hypothalamic-pituitary-thyroid axis to their low food intake.

  11. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism

    PubMed Central

    Willsey, A. Jeremy; Sanders, Stephan J.; Li, Mingfeng; Dong, Shan; Tebbenkamp, Andrew T.; Muhle, Rebecca A.; Reilly, Steven K.; Lin, Leon; Fertuzinhos, Sofia; Miller, Jeremy A.; Murtha, Michael T.; Bichsel, Candace; Niu, Wei; Cotney, Justin; Ercan-Sencicek, A. Gulhan; Gockley, Jake; Gupta, Abha; Han, Wenqi; He, Xin; Hoffman, Ellen; Klei, Lambertus; Lei, Jing; Liu, Wenzhong; Liu, Li; Lu, Cong; Xu, Xuming; Zhu, Ying; Mane, Shrikant M.; Lein, Edward S.; Wei, Liping; Noonan, James P.; Roeder, Kathryn; Devlin, Bernie; Šestan, Nenad; State, Matthew W.

    2013-01-01

    SUMMARY Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD “seed” genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology. PMID:24267886

  12. 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

  13. Dynamic Visualization of Co-expression in Systems Genetics Data

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

    New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

    2008-01-01

    Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

  14. MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

    PubMed

    Gonzalez-Dominguez, Jorge; Martin, Maria J

    2017-10-10

    In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

  15. 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

  16. 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

  17. Using Multiple-Variable Matching to Identify Cultural Sources of Differential Item Functioning

    ERIC Educational Resources Information Center

    Wu, Amery D.; Ercikan, Kadriye

    2006-01-01

    Identifying the sources of differential item functioning (DIF) in international assessments is very challenging, because such sources are often nebulous and intertwined. Even though researchers frequently focus on test translation and content area, few actually go beyond these factors to investigate other cultural sources of DIF. This article…

  18. 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

  19. Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

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

    Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

    2011-01-01

    Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

  20. 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.

  1. 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

  2. Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

    PubMed Central

    Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

    2016-01-01

    Background: Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). Methods: This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. Results: We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA–TF–gene network relevant to SZ, including an EGR1–miR-124-3p–SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Conclusions: Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. PMID:26609121

  3. A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

    PubMed

    Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

    2017-09-01

    The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

  4. 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.

  5. Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma

    PubMed Central

    2013-01-01

    Background Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally. Results In this paper, we develop a gene module based method for differential gene expression analysis, named network-based differential gene expression (nDGE) analysis, a one-step integrative process for prioritizing deregulated genes and grouping them into gene modules. We demonstrate that nDGE outperforms existing methods in prioritizing deregulated genes and discovering deregulated gene modules using simulated data sets. When tested on a series of smoker and non-smoker lung adenocarcinoma data sets, we show that top differentially regulated genes identified by the rank sum test in different sets are not consistent while top ranked genes defined by nDGE in different data sets significantly overlap. nDGE results suggest that a differentially regulated gene module, which is enriched for cell cycle related genes and E2F1 targeted genes, plays a role in the molecular differences between smoker and non-smoker lung adenocarcinoma. Conclusions In this paper, we develop nDGE to prioritize

  6. 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%.

  7. 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.

  8. DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data.

    PubMed

    Gaspar, John M; Hart, Ronald P

    2017-11-29

    DNA methylation is an epigenetic modification that is studied at a single-base resolution with bisulfite treatment followed by high-throughput sequencing. After alignment of the sequence reads to a reference genome, methylation counts are analyzed to determine genomic regions that are differentially methylated between two or more biological conditions. Even though a variety of software packages is available for different aspects of the bioinformatics analysis, they often produce results that are biased or require excessive computational requirements. DMRfinder is a novel computational pipeline that identifies differentially methylated regions efficiently. Following alignment, DMRfinder extracts methylation counts and performs a modified single-linkage clustering of methylation sites into genomic regions. It then compares methylation levels using beta-binomial hierarchical modeling and Wald tests. Among its innovative attributes are the analyses of novel methylation sites and methylation linkage, as well as the simultaneous statistical analysis of multiple sample groups. To demonstrate its efficiency, DMRfinder is benchmarked against other computational approaches using a large published dataset. Contrasting two replicates of the same sample yielded minimal genomic regions with DMRfinder, whereas two alternative software packages reported a substantial number of false positives. Further analyses of biological samples revealed fundamental differences between DMRfinder and another software package, despite the fact that they utilize the same underlying statistical basis. For each step, DMRfinder completed the analysis in a fraction of the time required by other software. Among the computational approaches for identifying differentially methylated regions from high-throughput bisulfite sequencing datasets, DMRfinder is the first that integrates all the post-alignment steps in a single package. Compared to other software, DMRfinder is extremely efficient and unbiased in

  9. Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

    PubMed Central

    Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

    2017-01-01

    Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

  10. Genetic and Chemical Screenings Identify HDAC3 as a Key Regulator in Hepatic Differentiation of Human Pluripotent Stem Cells.

    PubMed

    Li, Shuang; Li, Mushan; Liu, Xiaojian; Yang, Yuanyuan; Wei, Yuda; Chen, Yanhao; Qiu, Yan; Zhou, Tingting; Feng, Zhuanghui; Ma, Danjun; Fang, Jing; Ying, Hao; Wang, Hui; Musunuru, Kiran; Shao, Zhen; Zhao, Yongxu; Ding, Qiurong

    2018-05-24

    Hepatocyte-like cells (HLCs) derived from human pluripotent stem cells (hPSCs) offer a promising cell resource for disease modeling and transplantation. However, differentiated HLCs exhibit an immature phenotype and comprise a heterogeneous population. Thus, a better understanding of HLC differentiation will improve the likelihood of future application. Here, by taking advantage of CRISPR-Cas9-based genome-wide screening technology and a high-throughput hPSC screening platform with a reporter readout, we identified several potential genetic regulators of HLC differentiation. By using a chemical screening approach within our platform, we also identified compounds that can further promote HLC differentiation and preserve the characteristics of in vitro cultured primary hepatocytes. Remarkably, both screenings identified histone deacetylase 3 (HDAC3) as a key regulator in hepatic differentiation. Mechanistically, HDAC3 formed a complex with liver transcriptional factors, e.g., HNF4, and co-regulated the transcriptional program during hepatic differentiation. This study highlights a broadly useful approach for studying and optimizing hPSC differentiation. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  11. Using the 2A Protein Coexpression System: Multicistronic 2A Vectors Expressing Gene(s) of Interest and Reporter Proteins.

    PubMed

    Luke, Garry A; Ryan, Martin D

    2018-01-01

    To date, a huge range of different proteins-many with cotranslational and posttranslational subcellular localization signals-have been coexpressed together with various reporter proteins in vitro and in vivo using 2A peptides. The pros and cons of 2A co-expression technology are considered below, followed by a simple example of a "how to" protocol to concatenate multiple genes of interest, together with a reporter gene, into a single gene linked via 2As for easy identification or selection of transduced cells.

  12. Expression atlas and comparative coexpression network analyses reveal important genes involved in the formation of lignified cell wall in Brachypodium distachyon.

    PubMed

    Sibout, Richard; Proost, Sebastian; Hansen, Bjoern Oest; Vaid, Neha; Giorgi, Federico M; Ho-Yue-Kuang, Severine; Legée, Frédéric; Cézart, Laurent; Bouchabké-Coussa, Oumaya; Soulhat, Camille; Provart, Nicholas; Pasha, Asher; Le Bris, Philippe; Roujol, David; Hofte, Herman; Jamet, Elisabeth; Lapierre, Catherine; Persson, Staffan; Mutwil, Marek

    2017-08-01

    While Brachypodium distachyon (Brachypodium) is an emerging model for grasses, no expression atlas or gene coexpression network is available. Such tools are of high importance to provide insights into the function of Brachypodium genes. We present a detailed Brachypodium expression atlas, capturing gene expression in its major organs at different developmental stages. The data were integrated into a large-scale coexpression database ( www.gene2function.de), enabling identification of duplicated pathways and conserved processes across 10 plant species, thus allowing genome-wide inference of gene function. We highlight the importance of the atlas and the platform through the identification of duplicated cell wall modules, and show that a lignin biosynthesis module is conserved across angiosperms. We identified and functionally characterised a putative ferulate 5-hydroxylase gene through overexpression of it in Brachypodium, which resulted in an increase in lignin syringyl units and reduced lignin content of mature stems, and led to improved saccharification of the stem biomass. Our Brachypodium expression atlas thus provides a powerful resource to reveal functionally related genes, which may advance our understanding of important biological processes in grasses. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  13. Midline thalamic neurons are differentially engaged during hippocampus network oscillations.

    PubMed

    Lara-Vásquez, Ariel; Espinosa, Nelson; Durán, Ernesto; Stockle, Marcelo; Fuentealba, Pablo

    2016-07-14

    The midline thalamus is reciprocally connected with the medial temporal lobe, where neural circuitry essential for spatial navigation and memory formation resides. Yet, little information is available on the dynamic relationship between activity patterns in the midline thalamus and medial temporal lobe. Here, we report on the functional heterogeneity of anatomically-identified thalamic neurons and the differential modulation of their activity with respect to dorsal hippocampal rhythms in the anesthetized mouse. Midline thalamic neurons expressing the calcium-binding protein calretinin, irrespective of their selective co-expression of calbindin, discharged at overall low levels, did not increase their activity during hippocampal theta oscillations, and their firing rates were inhibited during hippocampal sharp wave-ripples. Conversely, thalamic neurons lacking calretinin discharged at higher rates, increased their activity during hippocampal theta waves, but remained unaffected during sharp wave-ripples. Our results indicate that the midline thalamic system comprises at least two different classes of thalamic projection neuron, which can be partly defined by their differential engagement by hippocampal pathways during specific network oscillations that accompany distinct behavioral contexts. Thus, different midline thalamic neuronal populations might be selectively recruited to support distinct stages of memory processing, consistent with the thalamus being pivotal in the dialogue of cortical circuits.

  14. Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia.

    PubMed

    Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

    2016-07-01

    Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA-TF-gene network relevant to SZ, including an EGR1-miR-124-3p-SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  15. 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.

  16. 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

  17. Yeast three-hybrid screen identifies TgBRADIN/GRA24 as a negative regulator of Toxoplasma gondii bradyzoite differentiation.

    PubMed

    Odell, Anahi V; Tran, Fanny; Foderaro, Jenna E; Poupart, Séverine; Pathak, Ravi; Westwood, Nicholas J; Ward, Gary E

    2015-01-01

    Differentiation of the protozoan parasite Toxoplasma gondii into its latent bradyzoite stage is a key event in the parasite's life cycle. Compound 2 is an imidazopyridine that was previously shown to inhibit the parasite lytic cycle, in part through inhibition of parasite cGMP-dependent protein kinase. We show here that Compound 2 can also enhance parasite differentiation, and we use yeast three-hybrid analysis to identify TgBRADIN/GRA24 as a parasite protein that interacts directly or indirectly with the compound. Disruption of the TgBRADIN/GRA24 gene leads to enhanced differentiation of the parasite, and the TgBRADIN/GRA24 knockout parasites show decreased susceptibility to the differentiation-enhancing effects of Compound 2. This study represents the first use of yeast three-hybrid analysis to study small-molecule mechanism of action in any pathogenic microorganism, and it identifies a previously unrecognized inhibitor of differentiation in T. gondii. A better understanding of the proteins and mechanisms regulating T. gondii differentiation will enable new approaches to preventing the establishment of chronic infection in this important human pathogen.

  18. Microarray and differential display identify genes involved in jasmonate-dependent anther development.

    PubMed

    Mandaokar, Ajin; Kumar, V Dinesh; Amway, Matt; Browse, John

    2003-07-01

    Jasmonate (JA) is a signaling compound essential for anther development and pollen fertility in Arabidopsis. Mutations that block the pathway of JA synthesis result into male sterility. To understand the processes of anther and pollen maturation, we used microarray and differential display approaches to compare gene expression pattern in anthers of wild-type Arabidopsis and the male-sterile mutant, opr3. Microarray experiment revealed 25 genes that were up-regulated more than 1.8-fold in wild-type anthers as compared to mutant anthers. Experiments based on differential display identified 13 additional genes up-regulated in wild-type anthers compared to opr3 for a total of 38 differentially expressed genes. Searches of the Arabidopsis and non-redundant databases disclosed known or likely functions for 28 of the 38 genes identified, while 10 genes encode proteins of unknown function. Northern blot analysis of eight representative clones as probes confirmed low expression in opr3 anthers compared with wild-type anthers. JA responsiveness of these same genes was also investigated by northern blot analysis of anther RNA isolated from wild-type and opr3 plants, In these experiments, four genes were induced in opr3 anthers within 0.5-1 h of JA treatment while the remaining genes were up-regulated only 1-8 h after JA application. None of these genes was induced by JA in anthers of the coil mutant that is deficient in JA responsiveness. The four early-induced genes in opr3 encode lipoxygenase, a putative bHLH transcription factor, epithiospecifier protein and an unknown protein. We propose that these and other early components may be involved in JA signaling and in the initiation of developmental processes. The four late genes encode an extensin-like protein, a peptide transporter and two unknown proteins, which may represent components required later in anther and pollen maturation. Transcript profiling has provided a successful approach to identify genes involved in

  19. 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.

  20. Efficient co-expression of a recombinant staphopain A and its inhibitor staphostatin A in Escherichia coli.

    PubMed

    Wladyka, Benedykt; Puzia, Katarzyna; Dubin, Adam

    2005-01-01

    Staphopain A is a staphylococcal cysteine protease. Genes encoding staphopain A and its specific inhibitor, staphostatin A, are localized in an operon. Staphopain A is an important staphylococcal virulence factor. It is difficult to perform studies on its interaction with other proteins due to problems in obtaining a sufficient amount of the enzyme from natural sources. Therefore efforts were made to produce a recombinant staphopain A. Sequences encoding the mature form of staphopain A and staphostatin A were PCR-amplified from Staphylococcus aureus genomic DNA and cloned into different compatible expression vectors. Production of staphopain A was observed only when the enzyme was co-expressed together with its specific inhibitor, staphostatin A. Loss of the function mutations introduced within the active site of staphopain A causes the expression of the inactive enzyme. Mutations within the reactive centre of staphostatin A result in abrogation of production of both the co-expressed proteins. These results support the thesis that the toxicity of recombinant staphopain A to the host is due to its proteolytic activity. The coexpressed proteins are located in the insoluble fraction. Ni2+-nitrilotriacetate immobilized metal-affinity chromatography allows for an efficient and easy purification of staphopain A. Our optimized refolding parameters allow restoration of the native conformation of the enzyme, with yields over 10-fold higher when compared with isolation from natural sources.

  1. An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

    PubMed

    Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

    2017-04-12

    Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

  2. Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism

    PubMed Central

    Pérez-Delgado, Carmen M.; Moyano, Tomás C.; García-Calderón, Margarita; Canales, Javier; Gutiérrez, Rodrigo A.; Márquez, Antonio J.; Betti, Marco

    2016-01-01

    Nitrogen is one of the most important nutrients for plants and, in natural soils, its availability is often a major limiting factor for plant growth. Here we examine the effect of different forms of nitrogen nutrition and of photorespiration on gene expression in the model legume Lotus japonicus with the aim of identifying regulatory candidate genes co-ordinating primary nitrogen assimilation and photorespiration. The transcriptomic changes produced by the use of different nitrogen sources in leaves of L. japonicus plants combined with the transcriptomic changes produced in the same tissue by different photorespiratory conditions were examined. The results obtained provide novel information on the possible role of plastidic glutamine synthetase in the response to different nitrogen sources and in the C/N balance of L. japonicus plants. The use of gene co-expression networks establishes a clear relationship between photorespiration and primary nitrogen assimilation and identifies possible transcription factors connected to the genes of both routes. PMID:27117340

  3. 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

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

    PubMed Central

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

    2017-01-01

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

  5. Construction and comparison of gene co-expression networks shows complex plant immune responses

    PubMed Central

    López, Camilo; López-Kleine, Liliana

    2014-01-01

    Gene co-expression networks (GCNs) are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA). Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses. PMID:25320678

  6. Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

    PubMed

    Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

    2011-10-01

    Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Enhanced Transgene Expression in Sugarcane by Co-Expression of Virus-Encoded RNA Silencing Suppressors

    PubMed Central

    Park, Jong-Won; Beyene, Getu; Buenrostro-Nava, Marco T.; Molina, Joe; Wang, Xiaofeng; Ciomperlik, Jessica J.; Manabayeva, Shuga A.; Alvarado, Veria Y.; Rathore, Keerti S.; Scholthof, Herman B.; Mirkov, T. Erik

    2013-01-01

    Post-transcriptional gene silencing is commonly observed in polyploid species and often poses a major limitation to plant improvement via biotechnology. Five plant viral suppressors of RNA silencing were evaluated for their ability to counteract gene silencing and enhance the expression of the Enhanced Yellow Fluorescent Protein (EYFP) or the β-glucuronidase (GUS) reporter gene in sugarcane, a major sugar and biomass producing polyploid. Functionality of these suppressors was first verified in Nicotiana benthamiana and onion epidermal cells, and later tested by transient expression in sugarcane young leaf segments and protoplasts. In young leaf segments co-expressing a suppressor, EYFP reached its maximum expression at 48–96 h post-DNA introduction and maintained its peak expression for a longer time compared with that in the absence of a suppressor. Among the five suppressors, Tomato bushy stunt virus-encoded P19 and Barley stripe mosaic virus-encoded γb were the most efficient. Co-expression with P19 and γb enhanced EYFP expression 4.6-fold and 3.6-fold in young leaf segments, and GUS activity 2.3-fold and 2.4-fold in protoplasts compared with those in the absence of a suppressor, respectively. In transgenic sugarcane, co-expression of GUS and P19 suppressor showed the highest accumulation of GUS levels with an average of 2.7-fold more than when GUS was expressed alone, with no detrimental phenotypic effects. The two established transient expression assays, based on young leaf segments and protoplasts, and confirmed by stable transgene expression, offer a rapid versatile system to verify the efficiency of RNA silencing suppressors that proved to be valuable in enhancing and stabilizing transgene expression in sugarcane. PMID:23799071

  8. Machine Learning–Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis[W

    PubMed Central

    Ma, Chuang; Xin, Mingming; Feldmann, Kenneth A.; Wang, Xiangfeng

    2014-01-01

    Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via comparison of gene coexpression networks, implemented as an R package called machine learning–based differential network analysis (mlDNA) and apply this method to reanalyze a set of abiotic stress expression data in Arabidopsis thaliana. The mlDNA first used a ML-based filtering process to remove nonexpressed, constitutively expressed, or non-stress-responsive “noninformative” genes prior to network construction, through learning the patterns of 32 expression characteristics of known stress-related genes. The retained “informative” genes were subsequently analyzed by ML-based network comparison to predict candidate stress-related genes showing expression and network differences between control and stress networks, based on 33 network topological characteristics. Comparative evaluation of the network-centric and gene-centric analytic methods showed that mlDNA substantially outperformed traditional statistical testing–based differential expression analysis at identifying stress-related genes, with markedly improved prediction accuracy. To experimentally validate the mlDNA predictions, we selected 89 candidates out of the 1784 predicted salt stress–related genes with available SALK T-DNA mutagenesis lines for phenotypic screening and identified two previously unreported genes, mutants of which showed salt-sensitive phenotypes. PMID:24520154

  9. A high throughput drug screening assay to identify compounds that promote oligodendrocyte differentiation using acutely dissociated and purified oligodendrocyte precursor cells.

    PubMed

    Lariosa-Willingham, Karen D; Rosler, Elen S; Tung, Jay S; Dugas, Jason C; Collins, Tassie L; Leonoudakis, Dmitri

    2016-09-05

    Multiple sclerosis is caused by an autoimmune response resulting in demyelination and neural degeneration. The adult central nervous system has the capacity to remyelinate axons in part through the generation of new oligodendrocytes (OLs). To identify clinical candidate compounds that may promote remyelination, we have developed a high throughput screening (HTS) assay to identify compounds that promote the differentiation of oligodendrocyte precursor cells (OPCs) into OLs. Using acutely dissociated and purified rat OPCs coupled with immunofluorescent image quantification, we have developed an OL differentiation assay. We have validated this assay with a known promoter of differentiation, thyroid hormone, and subsequently used the assay to screen the NIH clinical collection library. We have identified twenty-seven hit compounds which were validated by dose response analysis and the generation of half maximal effective concentration (EC50) values allowed for the ranking of efficacy. The assay identified novel promoters of OL differentiation which we attribute to (1) the incorporation of an OL toxicity pre-screen to allow lowering the concentrations of toxic compounds and (2) the utilization of freshly purified, non-passaged OPCs. These features set our assay apart from other OL differentiation assays used for drug discovery efforts. This acute primary OL-based differentiation assay should be of use to those interested in screening large compound libraries for the identification of drugs for the treatment of MS and other demyelinating diseases.

  10. Coexpression of actin-related protein 2 and Wiskott-Aldrich syndrome family verproline-homologous protein 2 in adenocarcinoma of the lung.

    PubMed

    Semba, Seitaro; Iwaya, Keiichi; Matsubayashi, Jun; Serizawa, Hiromi; Kataba, Hiroaki; Hirano, Takashi; Kato, Harubumi; Matsuoka, Takeshi; Mukai, Kiyoshi

    2006-04-15

    Highly invasive and metastatic cancer cells, such as adenocarcinoma of the lung cells, form irregular protrusions by assembling a branched network of actin filaments. In mammalian cells, the actin-related protein 2 and 3 (Arp2/3) complex initiates actin assembly to form lamellipodial protrusions by binding to Wiskott-Aldrich syndrome (WASP)/WASP family verproline-homologous protein 2 (WAVE2). In this study, colocalization of Arp2 and WAVE2 in adenocarcinoma of the lung was investigated to elucidate its prognostic value. Immunohistochemical staining of Arp2 and WAVE2 was done on mirror sections of 115 adenocarcinomas of the lung from pathologic stage IA to IIIA classes. Kaplan-Meier disease-free survival and overall survival curves were analyzed to determine the prognostic significance of the coexpression of Arp2 and WAVE2. Immunoreactivity for both Arp2 and WAVE2 was detected in the same cancer cells in 78 (67.8%) of the 115 lung cancer specimens. The proportion of cancer cells expressing both Arp2 and WAVE2 was significantly higher in cases with lymph-node metastasis (P = 0.0046), and significantly lower in bronchioloalveolar carcinomas (P < 0.0001). The patients whose cancer cells coexpressed them had a shorter disease-free survival time (P < 0.0001) and overall survival time (P < 0.0001). Multivariate Cox regression analysis revealed that coexpression of Arp2 and WAVE2 is an independent risk factor for tumor recurrence. Coexpression of Arp2 and WAVE2 is correlated with poorer patient outcome, and may be involved in the mechanism of cancer metastasis.

  11. 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

  12. Epigenetic Library Screen Identifies Abexinostat as Novel Regulator of Adipocytic and Osteoblastic Differentiation of Human Skeletal (Mesenchymal) Stem Cells

    PubMed Central

    Ali, Dalia; Hamam, Rimi; Alfayez, Musaed; Kassem, Moustapha; Aldahmash, Abdullah

    2016-01-01

    The epigenetic mechanisms promoting lineage-specific commitment of human skeletal (mesenchymal or stromal) stem cells (hMSCs) into adipocytes or osteoblasts are still not fully understood. Herein, we performed an epigenetic library functional screen and identified several novel compounds, including abexinostat, which promoted adipocytic and osteoblastic differentiation of hMSCs. Using gene expression microarrays, chromatin immunoprecipitation for H3K9Ac combined with high-throughput DNA sequencing (ChIP-seq), and bioinformatics, we identified several key genes involved in regulating stem cell proliferation and differentiation that were targeted by abexinostat. Concordantly, ChIP-quantitative polymerase chain reaction revealed marked increase in H3K9Ac epigenetic mark on the promoter region of AdipoQ, FABP4, PPARγ, KLF15, CEBPA, SP7, and ALPL in abexinostat-treated hMSCs. Pharmacological inhibition of focal adhesion kinase (PF-573228) or insulin-like growth factor-1R/insulin receptor (NVP-AEW51) signaling exhibited significant inhibition of abexinostat-mediated adipocytic differentiation, whereas inhibition of WNT (XAV939) or transforming growth factor-β (SB505124) signaling abrogated abexinostat-mediated osteogenic differentiation of hMSCs. Our findings provide insight into the understanding of the relationship between the epigenetic effect of histone deacetylase inhibitors, transcription factors, and differentiation pathways governing adipocyte and osteoblast differentiation. Manipulating such pathways allows a novel use for epigenetic compounds in hMSC-based therapies and tissue engineering. Significance This unbiased epigenetic library functional screen identified several novel compounds, including abexinostat, that promoted adipocytic and osteoblastic differentiation of human skeletal (mesenchymal or stromal) stem cells (hMSCs). These data provide new insight into the understanding of the relationship between the epigenetic effect of histone deacetylase

  13. Transcriptional profiling of murine osteoblast differentiation based on RNA-seq expression analyses.

    PubMed

    Khayal, Layal Abo; Grünhagen, Johannes; Provazník, Ivo; Mundlos, Stefan; Kornak, Uwe; Robinson, Peter N; Ott, Claus-Eric

    2018-04-11

    Osteoblastic differentiation is a multistep process characterized by osteogenic induction of mesenchymal stem cells, which then differentiate into proliferative pre-osteoblasts that produce copious amounts of extracellular matrix, followed by stiffening of the extracellular matrix, and matrix mineralization by hydroxylapatite deposition. Although these processes have been well characterized biologically, a detailed transcriptional analysis of murine primary calvaria osteoblast differentiation based on RNA sequencing (RNA-seq) analyses has not previously been reported. Here, we used RNA-seq to obtain expression values of 29,148 genes at four time points as murine primary calvaria osteoblasts differentiate in vitro until onset of mineralization was clearly detectable by microscopic inspection. Expression of marker genes confirmed osteogenic differentiation. We explored differential expression of 1386 protein-coding genes using unsupervised clustering and GO analyses. 100 differentially expressed lncRNAs were investigated by co-expression with protein-coding genes that are localized within the same topologically associated domain. Additionally, we monitored expression of 237 genes that are silent or active at distinct time points and compared differential exon usage. Our data represent an in-depth profiling of murine primary calvaria osteoblast differentiation by RNA-seq and contribute to our understanding of genetic regulation of this key process in osteoblast biology. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Age gene expression and coexpression progressive signatures in peripheral blood leukocytes.

    PubMed

    Irizar, Haritz; Goñi, Joaquín; Alzualde, Ainhoa; Castillo-Triviño, Tamara; Olascoaga, Javier; Lopez de Munain, Adolfo; Otaegui, David

    2015-12-01

    Both cellular senescence and organismic aging are known to be dynamic processes that start early in life and progress constantly during the whole life of the individual. In this work, with the objective of identifying signatures of age-related progressive change at the transcriptomic level, we have performed a whole-genome gene expression analysis of peripheral blood leukocytes in a group of healthy individuals with ages ranging from 14 to 93 years. A set of genes with progressively changing gene expression (either increase or decrease with age) has been identified and contextualized in a coexpression network. A modularity analysis has been performed on this network and biological-term and pathway enrichment analyses have been used for biological interpretation of each module. In summary, the results of the present work reveal the existence of a transcriptomic component that shows progressive expression changes associated to age in peripheral blood leukocytes, highlighting both the dynamic nature of the process and the need to complement young vs. elder studies with longitudinal studies that include middle aged individuals. From the transcriptional point of view, immunosenescence seems to be occurring from a relatively early age, at least from the late 20s/early 30s, and the 49-56 year old age-range appears to be critical. In general, the genes that, according to our results, show progressive expression changes with aging are involved in pathogenic/cellular processes that have classically been linked to aging in humans: cancer, immune processes and cellular growth vs. maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Use of multilevel logistic regression to identify the causes of differential item functioning.

    PubMed

    Balluerka, Nekane; Gorostiaga, Arantxa; Gómez-Benito, Juana; Hidalgo, María Dolores

    2010-11-01

    Given that a key function of tests is to serve as evaluation instruments and for decision making in the fields of psychology and education, the possibility that some of their items may show differential behaviour is a major concern for psychometricians. In recent decades, important progress has been made as regards the efficacy of techniques designed to detect this differential item functioning (DIF). However, the findings are scant when it comes to explaining its causes. The present study addresses this problem from the perspective of multilevel analysis. Starting from a case study in the area of transcultural comparisons, multilevel logistic regression is used: 1) to identify the item characteristics associated with the presence of DIF; 2) to estimate the proportion of variation in the DIF coefficients that is explained by these characteristics; and 3) to evaluate alternative explanations of the DIF by comparing the explanatory power or fit of different sequential models. The comparison of these models confirmed one of the two alternatives (familiarity with the stimulus) and rejected the other (the topic area) as being a cause of differential functioning with respect to the compared groups.

  16. Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

    PubMed

    Van Bel, Michiel; Coppens, Frederik

    2017-01-01

    Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

  17. 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

  18. Orbital-differentiated coherence-incoherence crossover identified by photoemission spectroscopy in LiFeAs

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

    Miao, H.; Yin, Z. P.; Wu, S. F.

    In the iron-based superconductors (FeSCs), orbital differentiation is an important phenomenon, whereby correlations stronger on the d xy orbital than on the d xz/d yz orbital yield quasi-particles with d xy orbital character having larger mass renormalization and abnormal temperature evolution. However, the physical origin of this orbital di erentiation is debated between the Hund's coupling induced unbinding of spin and orbital degrees of freedom and the Hubbard interaction instigated orbital selective Mott transition. Here we use angle-resolved photoemission spectroscopy to identify an orbital-dependent correlation-induced quasi-particle (QP) anomaly in LiFeAs. Lastly, the excellent agreement between our photoemission measurements and first-principlesmore » many-body theory calculations shows that the orbital-differentiated QP lifetime anomalies in LiFeAs are controlled by the Hund's coupling.« less

  19. Orbital-differentiated coherence-incoherence crossover identified by photoemission spectroscopy in LiFeAs

    DOE PAGES

    Miao, H.; Yin, Z. P.; Wu, S. F.; ...

    2016-11-14

    In the iron-based superconductors (FeSCs), orbital differentiation is an important phenomenon, whereby correlations stronger on the d xy orbital than on the d xz/d yz orbital yield quasi-particles with d xy orbital character having larger mass renormalization and abnormal temperature evolution. However, the physical origin of this orbital di erentiation is debated between the Hund's coupling induced unbinding of spin and orbital degrees of freedom and the Hubbard interaction instigated orbital selective Mott transition. Here we use angle-resolved photoemission spectroscopy to identify an orbital-dependent correlation-induced quasi-particle (QP) anomaly in LiFeAs. Lastly, the excellent agreement between our photoemission measurements and first-principlesmore » many-body theory calculations shows that the orbital-differentiated QP lifetime anomalies in LiFeAs are controlled by the Hund's coupling.« less

  20. Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish.

    PubMed

    Chen, Wen; Zhang, Xuan; Li, Jing; Huang, Shulan; Xiang, Shuanglin; Hu, Xiang; Liu, Changning

    2018-05-09

    Zebrafish is a full-developed model system for studying development processes and human disease. Recent studies of deep sequencing had discovered a large number of long non-coding RNAs (lncRNAs) in zebrafish. However, only few of them had been functionally characterized. Therefore, how to take advantage of the mature zebrafish system to deeply investigate the lncRNAs' function and conservation is really intriguing. We systematically collected and analyzed a series of zebrafish RNA-seq data, then combined them with resources from known database and literatures. As a result, we obtained by far the most complete dataset of zebrafish lncRNAs, containing 13,604 lncRNA genes (21,128 transcripts) in total. Based on that, a co-expression network upon zebrafish coding and lncRNA genes was constructed and analyzed, and used to predict the Gene Ontology (GO) and the KEGG annotation of lncRNA. Meanwhile, we made a conservation analysis on zebrafish lncRNA, identifying 1828 conserved zebrafish lncRNA genes (1890 transcripts) that have their putative mammalian orthologs. We also found that zebrafish lncRNAs play important roles in regulation of the development and function of nervous system; these conserved lncRNAs present a significant sequential and functional conservation, with their mammalian counterparts. By integrative data analysis and construction of coding-lncRNA gene co-expression network, we gained the most comprehensive dataset of zebrafish lncRNAs up to present, as well as their systematic annotations and comprehensive analyses on function and conservation. Our study provides a reliable zebrafish-based platform to deeply explore lncRNA function and mechanism, as well as the lncRNA commonality between zebrafish and human.

  1. A Rasch Differential Item Functioning Analysis of the Massachusetts Youth Screening Instrument: Identifying Race and Gender Differential Item Functioning among Juvenile Offenders

    ERIC Educational Resources Information Center

    Cauffman, Elizabeth; MacIntosh, Randall

    2006-01-01

    The juvenile justice system needs a tool that can identify and assess mental health problems among youths quickly with validity and reliability. The goal of this article is to evaluate the racial/ethnic and gender differential item functioning (DIF) of the Massachusetts Youth Screening Instrument-Second Version (MAYSI-2) using the Rasch Model.…

  2. Systematic comparison of co-expression of multiple recombinant thermophilic enzymes in Escherichia coli BL21(DE3).

    PubMed

    Chen, Hui; Huang, Rui; Zhang, Y-H Percival

    2017-06-01

    The precise control of multiple heterologous enzyme expression levels in one Escherichia coli strain is important for cascade biocatalysis, metabolic engineering, synthetic biology, natural product synthesis, and studies of complexed proteins. We systematically investigated the co-expression of up to four thermophilic enzymes (i.e., α-glucan phosphorylase (αGP), phosphoglucomutase (PGM), glucose 6-phosphate dehydrogenase (G6PDH), and 6-phosphogluconate dehydrogenase (6PGDH)) in E. coli BL21(DE3) by adding T7 promoter or T7 terminator of each gene for multiple genes in tandem, changing gene alignment, and comparing one or two plasmid systems. It was found that the addition of T7 terminator after each gene was useful to decrease the influence of the upstream gene. The co-expression of the four enzymes in E. coli BL21(DE3) was demonstrated to generate two NADPH molecules from one glucose unit of maltodextrin, where NADPH was oxidized to convert xylose to xylitol. The best four-gene co-expression system was based on two plasmids (pET and pACYC) which harbored two genes. As a result, apparent enzymatic activities of the four enzymes were regulated to be at similar levels and the overall four-enzyme activity was the highest based on the formation of xylitol. This study provides useful information for the precise control of multi-enzyme-coordinated expression in E. coli BL21(DE3).

  3. FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants1

    PubMed Central

    Tohge, Takayuki; Klie, Sebastian; Fernie, Alisdair R.

    2016-01-01

    Gene duplications generate new genes that can acquire similar but often diversified functions. Recent studies of gene coexpression networks have indicated that, not only genes, but also pathways can be multiplied and diversified to perform related functions in different parts of an organism. Identification of such diversified pathways, or modules, is needed to expand our knowledge of biological processes in plants and to understand how biological functions evolve. However, systematic explorations of modules remain scarce, and no user-friendly platform to identify them exists. We have established a statistical framework to identify modules and show that approximately one-third of the genes of a plant’s genome participate in hundreds of multiplied modules. Using this framework as a basis, we implemented a platform that can explore and visualize multiplied modules in coexpression networks of eight plant species. To validate the usefulness of the platform, we identified and functionally characterized pollen- and root-specific cell wall modules that multiplied to confer tip growth in pollen tubes and root hairs, respectively. Furthermore, we identified multiplied modules involved in secondary metabolite synthesis and corroborated them by metabolite profiling of tobacco (Nicotiana tabacum) tissues. The interactive platform, referred to as FamNet, is available at http://www.gene2function.de/famnet.html. PMID:26754669

  4. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    PubMed

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

  5. Coexpression of CdSe and CdSe/CdS quantum dots in live cells using molecular hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

    Li, Qingli; Peng, Hui; Wang, Jing; Wang, Yiting; Guo, Fangmin

    2015-11-01

    A direct spatial and spectral observation of CdSe and CdSe/CdS quantum dots (QDs) as probes in live cells is performed by using a custom molecular hyperspectral imaging (MHI) system. Water-soluble CdSe and CdSe/CdS QDs are synthesized in aqueous solution under the assistance of high-intensity ultrasonic irradiation and incubated with colon cancer cells for bioimaging. Unlike the traditional fluorescence microscopy methods, MHI technology can identify QD probes according to their spectral signatures and generate coexpression and stain titer maps by a clustering method. The experimental results show that the MHI method has potential to unmix biomarkers by their spectral information, which opens up a pathway of optical multiplexing with many different QD probes.

  6. Co-expression of COX-2 and 5-LO in primary glioblastoma is associated with poor prognosis.

    PubMed

    Wang, Xingfu; Chen, Yupeng; Zhang, Sheng; Zhang, Lifeng; Liu, Xueyong; Zhang, Li; Li, Xiaoling; Chen, Dayang

    2015-11-01

    Cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LO) are important factors in tumorigenesis and malignant progression; however, studies of their roles in glioblastoma have produced conflicting results. To define the frequencies of COX-2 and 5-LO expression and their correlation with clinicopathological features and prognosis, tumor tissues from 76 cases of newly diagnosed primary ordinary glioblastoma were examined for COX-2 and 5-LO expression by immunohistochemistry. The expression levels of COX-2 and 5-LO and the relationships between the co-expression of COX-2/5-LO and patient age and gender, edema index (EI), Karnofsky Performance Scale and overall survival (OS) were analyzed. COX-2 and 5-LO were expressed in 73.7 % (56/76) and 92.1 % (70/76) of the samples, respectively. Among the clinicopathological characteristics, only age (>60 years) exhibited a significant association with the high expression of COX-2. No statistically significant correlations were found in the 5-LO cohort. A significant positive correlation was revealed between the COX-2 and 5-LO scores (r = 0.374; p = 0.001). The elevated co-expression of COX-2 and 5-LO was observed primarily in the patients over the age of 60 years. Patients with a high expression of COX-2 had a significantly shorter OS (p < 0.01), whereas the immunoexpression of 5-LO was not associated with the OS of patients with glioblastoma. Survival analysis indicated that simultaneous high levels of COX-2 and 5-LO expression were significantly correlated with poor OS and, conversely, that a low/low expression pattern of these two proteins was significantly associated with better OS (p < 0.05). Moreover, the Cox multivariable proportional hazard model showed that a high expression of COX-2, high co-expression of COX-2 and 5-LO, and a high Ki-67 index were significant predictors of shorter OS in primary glioblastoma, independent of age, gender, EI, 5-LO expression and p53 status. The hazard ratios for OS were 2.347 (95 % CI 1

  7. Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators.

    PubMed

    Silberstein, Lev; Goncalves, Kevin A; Kharchenko, Peter V; Turcotte, Raphael; Kfoury, Youmna; Mercier, Francois; Baryawno, Ninib; Severe, Nicolas; Bachand, Jacqueline; Spencer, Joel A; Papazian, Ani; Lee, Dongjun; Chitteti, Brahmananda Reddy; Srour, Edward F; Hoggatt, Jonathan; Tate, Tiffany; Lo Celso, Cristina; Ono, Noriaki; Nutt, Stephen; Heino, Jyrki; Sipilä, Kalle; Shioda, Toshihiro; Osawa, Masatake; Lin, Charles P; Hu, Guo-Fu; Scadden, David T

    2016-10-06

    Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. 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.

  9. Co-expression of cystatin inhibitors OCI and OCII in transgenic potato plants alters Colorado potato beetle development

    USDA-ARS?s Scientific Manuscript database

    Oryzacystatins I and II (OCI and OCII) show potential for controlling pests that utilize cysteine proteinases for protein digestion. To strengthen individual inhibitory range and achieve an additive effect in the overall efficiency of these proteins against pests, both cystatin genes were co-express...

  10. Co-expression of D-glucose isomerase and D-psicose 3-epimerase: development of an efficient one-step production of D-psicose.

    PubMed

    Men, Yan; Zhu, Yueming; Zeng, Yan; Izumori, Ken; Sun, Yuanxia; Ma, Yanhe

    2014-10-01

    D-Psicose has been attracting attention in recent years because of its alimentary activities and is used as an ingredient in a range of foods and dietary supplements. To develop a one-step enzymatic process of D-psicose production, thermoactive D-glucose isomerase and the D-psicose 3-epimerase obtained from Bacillus sp. and Ruminococcus sp., respectively, were successfully co-expressed in Escherichia coli BL21 strain. The substrate of one-step enzymatic process was D-glucose. The co-expression system exhibited maximum activity at 65 °C and pH 7.0. Mg(2+) could enhance the output of D-psicose by 2.32 fold to 1.6 g/L from 10 g/L of D-glucose. When using high-fructose corn syrup (HFCS) as substrate, 135 g/L D-psicose was produced under optimum conditions. The mass ratio of D-glucose, D-fructose, and D-psicose was almost 3.0:2.7:1.0, when the reaction reached equilibrium after an 8h incubation time. This co-expression system approaching to produce D-psicose has potential application in food and beverage products, especially softdrinks. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Differentiation of V2a interneurons from human pluripotent stem cells

    PubMed Central

    Butts, Jessica C.; McCreedy, Dylan A.; Martinez-Vargas, Jorge Alexis; Mendoza-Camacho, Frederico N.; Hookway, Tracy A.; Gifford, Casey A.; Taneja, Praveen; Noble-Haeusslein, Linda; McDevitt, Todd C.

    2017-01-01

    The spinal cord consists of multiple neuronal cell types that are critical to motor control and arise from distinct progenitor domains in the developing neural tube. Excitatory V2a interneurons in particular are an integral component of central pattern generators that control respiration and locomotion; however, the lack of a robust source of human V2a interneurons limits the ability to molecularly profile these cells and examine their therapeutic potential to treat spinal cord injury (SCI). Here, we report the directed differentiation of CHX10+ V2a interneurons from human pluripotent stem cells (hPSCs). Signaling pathways (retinoic acid, sonic hedgehog, and Notch) that pattern the neural tube were sequentially perturbed to identify an optimized combination of small molecules that yielded ∼25% CHX10+ cells in four hPSC lines. Differentiated cultures expressed much higher levels of V2a phenotypic markers (CHX10 and SOX14) than other neural lineage markers. Over time, CHX10+ cells expressed neuronal markers [neurofilament, NeuN, and vesicular glutamate transporter 2 (VGlut2)], and cultures exhibited increased action potential frequency. Single-cell RNAseq analysis confirmed CHX10+ cells within the differentiated population, which consisted primarily of neurons with some glial and neural progenitor cells. At 2 wk after transplantation into the spinal cord of mice, hPSC-derived V2a cultures survived at the site of injection, coexpressed NeuN and VGlut2, extended neurites >5 mm, and formed putative synapses with host neurons. These results provide a description of V2a interneurons differentiated from hPSCs that may be used to model central nervous system development and serve as a potential cell therapy for SCI. PMID:28438991

  12. 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.

  13. Necdin interacts with the Msx2 homeodomain protein via MAGE-D1 to promote myogenic differentiation of C2C12 cells.

    PubMed

    Kuwajima, Takaaki; Taniura, Hideo; Nishimura, Isao; Yoshikawa, Kazuaki

    2004-09-24

    Necdin is a potent growth suppressor that is expressed predominantly in postmitotic cells such as neurons and skeletal muscle cells. Necdin shows a significant homology to MAGE (melanoma antigen) family proteins, all of which contain a large homology domain. MAGE-D1 (NRAGE, Dlxin-1) interacts with the Dlx/Msx family homeodomain proteins via an interspersed hexapeptide repeat domain distinct from the homology domain. Here we report that necdin associates with the Msx homeodomain proteins via MAGE-D1 to modulate their function. In vitro binding and co-immunoprecipitation analyses revealed that MAGE-D1 directly interacted with necdin via the homology domain and Msx1 (or Msx2) via the repeat domain. A ternary complex of necdin, MAGE-D1, and Msx2 was formed in vitro, and an endogenous complex containing these three proteins was detected in differentiating embryonal carcinoma cells. Co-expression of necdin and MAGE-D1 released Msx-dependent transcriptional repression. C2C12 myoblast cells that were stably transfected with Msx2 cDNA showed a marked reduction in myogenic differentiation, and co-expression of necdin and MAGE-D1 canceled the Msx2-dependent repression. These results suggest that necdin and MAGE-D1 cooperate to modulate the function of Dlx/Msx homeodomain proteins in cellular differentiation. Copyright 2004 American Society for Biochemistry and Molecular Biology, Inc.

  14. 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.

  15. The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

    PubMed Central

    Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

    2006-01-01

    Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In

  16. Structural and metabolic transitions of C4 leaf development and differentiation defined by microscopy and quantitative proteomics in maize.

    PubMed

    Majeran, Wojciech; Friso, Giulia; Ponnala, Lalit; Connolly, Brian; Huang, Mingshu; Reidel, Edwin; Zhang, Cankui; Asakura, Yukari; Bhuiyan, Nazmul H; Sun, Qi; Turgeon, Robert; van Wijk, Klaas J

    2010-11-01

    C(4) grasses, such as maize (Zea mays), have high photosynthetic efficiency through combined biochemical and structural adaptations. C(4) photosynthesis is established along the developmental axis of the leaf blade, leading from an undifferentiated leaf base just above the ligule into highly specialized mesophyll cells (MCs) and bundle sheath cells (BSCs) at the tip. To resolve the kinetics of maize leaf development and C(4) differentiation and to obtain a systems-level understanding of maize leaf formation, the accumulation profiles of proteomes of the leaf and the isolated BSCs with their vascular bundle along the developmental gradient were determined using large-scale mass spectrometry. This was complemented by extensive qualitative and quantitative microscopy analysis of structural features (e.g., Kranz anatomy, plasmodesmata, cell wall, and organelles). More than 4300 proteins were identified and functionally annotated. Developmental protein accumulation profiles and hierarchical cluster analysis then determined the kinetics of organelle biogenesis, formation of cellular structures, metabolism, and coexpression patterns. Two main expression clusters were observed, each divided in subclusters, suggesting that a limited number of developmental regulatory networks organize concerted protein accumulation along the leaf gradient. The coexpression with BSC and MC markers provided strong candidates for further analysis of C(4) specialization, in particular transporters and biogenesis factors. Based on the integrated information, we describe five developmental transitions that provide a conceptual and practical template for further analysis. An online protein expression viewer is provided through the Plant Proteome Database.

  17. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    PubMed

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

  18. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

    PubMed

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  19. CRISPR screen identifies the NCOR/HDAC3 complex as a major suppressor of differentiation in rhabdomyosarcoma

    PubMed Central

    Phelps, Michael P.; Bailey, Jenna N.; Vleeshouwer-Neumann, Terra

    2016-01-01

    Dysregulated gene expression resulting from abnormal epigenetic alterations including histone acetylation and deacetylation has been demonstrated to play an important role in driving tumor growth and progression. However, the mechanisms by which specific histone deacetylases (HDACs) regulate differentiation in solid tumors remains unclear. Using pediatric rhabdomyosarcoma (RMS) as a paradigm to elucidate the mechanism blocking differentiation in solid tumors, we identified HDAC3 as a major suppressor of myogenic differentiation from a high-efficiency Clustered regularly interspaced short palindromic repeats (CRISPR)-based phenotypic screen of class I and II HDAC genes. Detailed characterization of the HDAC3-knockout phenotype in vitro and in vivo using a tamoxifen-inducible CRISPR targeting strategy demonstrated that HDAC3 deacetylase activity and the formation of a functional complex with nuclear receptor corepressors (NCORs) were critical in restricting differentiation in RMS. The NCOR/HDAC3 complex specifically functions by blocking myoblast determination protein 1 (MYOD1)-mediated activation of myogenic differentiation. Interestingly, there was also a transient up-regulation of growth-promoting genes upon initial HDAC3 targeting, revealing a unique cancer-specific response to the forced transition from a neoplastic state to terminal differentiation. Our study applied modifications of CRISPR/CRISPR-associated endonuclease 9 (Cas9) technology to interrogate the function of essential cancer genes and pathways and has provided insights into cancer cell adaptation in response to altered differentiation status. Because current pan-HDAC inhibitors have shown disappointing results in clinical trials of solid tumors, therapeutic targets specific to HDAC3 function represent a promising option for differentiation therapy in malignant tumors with dysregulated HDAC3 activity. PMID:27956629

  20. CRISPR screen identifies the NCOR/HDAC3 complex as a major suppressor of differentiation in rhabdomyosarcoma.

    PubMed

    Phelps, Michael P; Bailey, Jenna N; Vleeshouwer-Neumann, Terra; Chen, Eleanor Y

    2016-12-27

    Dysregulated gene expression resulting from abnormal epigenetic alterations including histone acetylation and deacetylation has been demonstrated to play an important role in driving tumor growth and progression. However, the mechanisms by which specific histone deacetylases (HDACs) regulate differentiation in solid tumors remains unclear. Using pediatric rhabdomyosarcoma (RMS) as a paradigm to elucidate the mechanism blocking differentiation in solid tumors, we identified HDAC3 as a major suppressor of myogenic differentiation from a high-efficiency Clustered regularly interspaced short palindromic repeats (CRISPR)-based phenotypic screen of class I and II HDAC genes. Detailed characterization of the HDAC3-knockout phenotype in vitro and in vivo using a tamoxifen-inducible CRISPR targeting strategy demonstrated that HDAC3 deacetylase activity and the formation of a functional complex with nuclear receptor corepressors (NCORs) were critical in restricting differentiation in RMS. The NCOR/HDAC3 complex specifically functions by blocking myoblast determination protein 1 (MYOD1)-mediated activation of myogenic differentiation. Interestingly, there was also a transient up-regulation of growth-promoting genes upon initial HDAC3 targeting, revealing a unique cancer-specific response to the forced transition from a neoplastic state to terminal differentiation. Our study applied modifications of CRISPR/CRISPR-associated endonuclease 9 (Cas9) technology to interrogate the function of essential cancer genes and pathways and has provided insights into cancer cell adaptation in response to altered differentiation status. Because current pan-HDAC inhibitors have shown disappointing results in clinical trials of solid tumors, therapeutic targets specific to HDAC3 function represent a promising option for differentiation therapy in malignant tumors with dysregulated HDAC3 activity.

  1. Autocrine CSF-1 and CSF-1 Receptor Co-expression Promotes Renal Cell Carcinoma Growth

    PubMed Central

    Menke, Julia; Kriegsmann, Jörg; Schimanski, Carl Christoph; Schwartz, Melvin M.; Schwarting, Andreas; Kelley, Vicki R.

    2011-01-01

    Renal cell carcinoma is increasing in incidence but the molecular mechanisms regulating its growth remain elusive. Co-expression of the monocytic growth factor CSF-1 and its receptor CSF-1R on renal tubular epithelial cells (TEC) will promote proliferation and anti-apoptosis during regeneration of renal tubules. Here we show that a CSF-1-dependent autocrine pathway is also responsible for the growth of renal cell carcinoma (RCC). CSF-1 and CSF-1R were co-expressed in RCC and TEC proximally adjacent to RCC. CSF-1 engagement of CSF-1R promoted RCC survival and proliferation and reduced apoptosis, in support of the likelihood that CSF-1R effector signals mediate RCC growth. In vivo CSF-1R blockade using a CSF-1R tyrosine kinase inhibitor decreased RCC proliferation and macrophage infiltration in a manner associated with a dramatic reduction in tumor mass. Further mechanistic investigations linked CSF-1 and EGF signaling in RCC. Taken together, our results suggest that budding RCC stimulates the proximal adjacent microenvironment in the kidney to release mediators of CSF-1, CSF-1R and EGF expression in RCC. Further, our findings imply that targeting CSF-1/CSF-1R signaling may be therapeutically effective in RCC. PMID:22052465

  2. Proteomics-based approach identified differentially expressed proteins with potential roles in endometrial carcinoma.

    PubMed

    Li, Zhengyu; Min, Wenjiao; Huang, Canhua; Bai, Shujun; Tang, Minghai; Zhao, Xia

    2010-01-01

    We used proteomic approaches to identify altered expressed proteins in endometrial carcinoma, with the aim of discovering potential biomarkers or therapeutic targets for endometrial carcinoma. The global proteins extracted from endometrial carcinoma and normal endometrial tissues were separated by 2-dimensional electrophoresis and analyzed with PDQuest (Bio-Rad, Hercules, Calif) software. The differentially expressed spots were identified by mass spectrometry and searched against NCBInr protein database. Those proteins with potential roles were confirmed by Western blotting and immunohistochemical assays. Ninety-nine proteins were identified by mass spectrometry, and a cluster diagram analysis indicated that these proteins were involved in metabolism, cell transformation, protein folding, translation and modification, proliferation and apoptosis, signal transduction, cytoskeleton, and so on. In confirmatory immunoblotting and immunohistochemical analyses, overexpressions of epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A were also observed in endometrial carcinoma tissues, which were consistent with the proteomic results. Our results suggested that these identified proteins, including epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A, might be of potential values in the studies of endometrial carcinogenesis or investigations of diagnostic biomarkers or treatment targets for endometrial carcinoma.

  3. 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

  4. DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

    PubMed Central

    Peng, Hao; Yang, Yifan; Zhe, Shandian; Wang, Jian; Gribskov, Michael; Qi, Yuan

    2017-01-01

    Abstract Motivation High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy. Results We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature. Availability and implementation The software is available at https

  5. Production of d-allulose from d-glucose by Escherichia coli transformant cells co-expressing d-glucose isomerase and d-psicose 3-epimerase genes.

    PubMed

    Zhang, Wenli; Li, Hao; Jiang, Bo; Zhang, Tao; Mu, Wanmeng

    2017-08-01

    d-Allulose is a novel and low-calorie rare monosaccharide that is a C-3 epimer of d-fructose. Because of its excellent physiological properties and commercial potential, d-allulose has attracted researchers' interests. Based on the Izumoring strategy, d-allulose is converted from d-fructose by d-psicose 3-epimerase (DPEase), while d-fructose is converted from d-glucose by d-glucose isomerase (GIase). In this study, we created a cellular system capable of converting d-glucose to d-allulose in a one-step process that co-expressed the GIase from Acidothermus cellulolyticus and the DPEase from Dorea sp. CAG. The co-expression plasmid pETDuet-Dosp-DPE/Acce-GI was generated and transformed into Escherichia coli BL21(DE3) cells. The recombinant co-expression cells exhibited maximum catalytic activity at pH 6.5 and 75 °C. These cells were thermostable at less than 60 °C. The addition of Co 2+ significantly increased the catalytic activity by 10.8-fold. When the reaction equilibrium was reached, the ratio of d-glucose, d-fructose and d-allulose was approximately 6.5:7:3, respectively. A recombinant co-expression strain that catalysed the bioconversion of d-allulose from d-glucose in a one-step process was created and characterised. When adding 500 g L -1 d-glucose as a substrate, 204.3 g L -1 d-fructose and 89.1 g L -1 d-allulose were produced. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  6. Identifying Country-Specific Cultures of Physics Education: A differential item functioning approach

    NASA Astrophysics Data System (ADS)

    Mesic, Vanes

    2012-11-01

    In international large-scale assessments of educational outcomes, student achievement is often represented by unidimensional constructs. This approach allows for drawing general conclusions about country rankings with respect to the given achievement measure, but it typically does not provide specific diagnostic information which is necessary for systematic comparisons and improvements of educational systems. Useful information could be obtained by exploring the differences in national profiles of student achievement between low-achieving and high-achieving countries. In this study, we aimed to identify the relative weaknesses and strengths of eighth graders' physics achievement in Bosnia and Herzegovina in comparison to the achievement of their peers from Slovenia. For this purpose, we ran a secondary analysis of Trends in International Mathematics and Science Study (TIMSS) 2007 data. The student sample consisted of 4,220 students from Bosnia and Herzegovina and 4,043 students from Slovenia. After analysing the cognitive demands of TIMSS 2007 physics items, the correspondent differential item functioning (DIF)/differential group functioning contrasts were estimated. Approximately 40% of items exhibited large DIF contrasts, indicating significant differences between cultures of physics education in Bosnia and Herzegovina and Slovenia. The relative strength of students from Bosnia and Herzegovina showed to be mainly associated with the topic area 'Electricity and magnetism'. Classes of items which required the knowledge of experimental method, counterintuitive thinking, proportional reasoning and/or the use of complex knowledge structures proved to be differentially easier for students from Slovenia. In the light of the presented results, the common practice of ranking countries with respect to universally established cognitive categories seems to be potentially misleading.

  7. Nicotinamide induces differentiation of embryonic stem cells into insulin-secreting cells

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

    Vaca, Pilar; Berna, Genoveva; Araujo, Raquel

    2008-03-10

    The poly(ADP-ribose) polymerase (PARP) inhibitor, nicotinamide, induces differentiation and maturation of fetal pancreatic cells. In addition, we have previously reported evidence that nicotinamide increases the insulin content of cells differentiated from embryonic stem (ES) cells, but the possibility of nicotinamide acting as a differentiating agent on its own has never been completely explored. Islet cell differentiation was studied by: (i) X-gal staining after neomycin selection; (ii) BrdU studies; (iii) single and double immunohistochemistry for insulin, C-peptide and Glut-2; (iv) insulin and C-peptide content and secretion assays; and (v) transplantation of differentiated cells, under the kidney capsule, into streptozotocin (STZ)-diabetic mice.more » Here we show that undifferentiated mouse ES cells treated with nicotinamide: (i) showed an 80% decrease in cell proliferation; (ii) co-expressed insulin, C-peptide and Glut-2; (iii) had values of insulin and C-peptide corresponding to 10% of normal mouse islets; (iv) released insulin and C-peptide in response to stimulatory glucose concentrations; and (v) after transplantation into diabetic mice, normalized blood glucose levels over 7 weeks. Our data indicate that nicotinamide decreases ES cell proliferation and induces differentiation into insulin-secreting cells. Both aspects are very important when thinking about cell therapy for the treatment of diabetes based on ES cells.« less

  8. Identification of differentially expressed genes through RNA sequencing in goats (Capra hircus) at different postnatal stages

    PubMed Central

    Li, Qian; Lin, Sen

    2017-01-01

    Intramuscular fat (IMF) content and fatty acid composition of longissimus dorsi muscle (LM) change with growth, which partially determines the flavor and nutritional value of goat (Capra hircus) meat. However, unlike cattle, little information is available on the transcriptome-wide changes during different postnatal stages in small ruminants, especially goats. In this study, the sequencing reads of goat LM tissues collected from kid, youth, and adult period were mapped to the goat genome. Results showed that out of total 24 689 Unigenes, 20 435 Unigenes were annotated. Based on expected number of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM), 111 annotated differentially expressed genes (DEGs) were identified among different postnatal stages, which were subsequently assigned to 16 possible expression patterns by series-cluster analysis. Functional classification by Gene Ontology (GO) analysis was used for selecting the genes showing highest expression related to lipid metabolism. Finally, we identified the node genes for lipid metabolism regulation using co-expression analysis. In conclusion, these data may uncover candidate genes having functional roles in regulation of goat muscle development and lipid metabolism during the various growth stages in goats. PMID:28800357

  9. Identification of differentially expressed genes through RNA sequencing in goats (Capra hircus) at different postnatal stages.

    PubMed

    Lin, Yaqiu; Zhu, Jiangjiang; Wang, Yong; Li, Qian; Lin, Sen

    2017-01-01

    Intramuscular fat (IMF) content and fatty acid composition of longissimus dorsi muscle (LM) change with growth, which partially determines the flavor and nutritional value of goat (Capra hircus) meat. However, unlike cattle, little information is available on the transcriptome-wide changes during different postnatal stages in small ruminants, especially goats. In this study, the sequencing reads of goat LM tissues collected from kid, youth, and adult period were mapped to the goat genome. Results showed that out of total 24 689 Unigenes, 20 435 Unigenes were annotated. Based on expected number of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM), 111 annotated differentially expressed genes (DEGs) were identified among different postnatal stages, which were subsequently assigned to 16 possible expression patterns by series-cluster analysis. Functional classification by Gene Ontology (GO) analysis was used for selecting the genes showing highest expression related to lipid metabolism. Finally, we identified the node genes for lipid metabolism regulation using co-expression analysis. In conclusion, these data may uncover candidate genes having functional roles in regulation of goat muscle development and lipid metabolism during the various growth stages in goats.

  10. Temporal Profiling and Pulsed SILAC Labeling Identify Novel Secreted Proteins During Ex Vivo Osteoblast Differentiation of Human Stromal Stem Cells*

    PubMed Central

    Kristensen, Lars P.; Chen, Li; Nielsen, Maria Overbeck; Qanie, Diyako W.; Kratchmarova, Irina; Kassem, Moustapha; Andersen, Jens S.

    2012-01-01

    It is well established that bone forming cells (osteoblasts) secrete proteins with autocrine, paracrine, and endocrine function. However, the identity and functional role for the majority of these secreted and differentially expressed proteins during the osteoblast (OB) differentiation process, is not fully established. To address these questions, we quantified the temporal dynamics of the human stromal (mesenchymal, skeletal) stem cell (hMSC) secretome during ex vivo OB differentiation using stable isotope labeling by amino acids in cell culture (SILAC). In addition, we employed pulsed SILAC labeling to distinguish genuine secreted proteins from intracellular contaminants. We identified 466 potentially secreted proteins that were quantified at 5 time-points during 14-days ex vivo OB differentiation including 41 proteins known to be involved in OB functions. Among these, 315 proteins exhibited more than 2-fold up or down-regulation. The pulsed SILAC method revealed a strong correlation between the fraction of isotope labeling and the subset of proteins known to be secreted and involved in OB differentiation. We verified SILAC data using qRT-PCR analysis of 9 identified potential novel regulators of OB differentiation. Furthermore, we studied the biological effects of one of these proteins, the hormone stanniocalcin 2 (STC2) and demonstrated its autocrine effects in enhancing osteoblastic differentiation of hMSC. In conclusion, combining complete and pulsed SILAC labeling facilitated the identification of novel factors produced by hMSC with potential role in OB differentiation. Our study demonstrates that the secretome of osteoblastic cells is more complex than previously reported and supports the emerging evidence that osteoblastic cells secrete proteins with endocrine functions and regulate cellular processes beyond bone formation. PMID:22801418

  11. Comparative Transcriptome Analysis Identifies Candidate Genes Related to Skin Color Differentiation in Red Tilapia.

    PubMed

    Zhu, Wenbin; Wang, Lanmei; Dong, Zaijie; Chen, Xingting; Song, Feibiao; Liu, Nian; Yang, Hui; Fu, Jianjun

    2016-08-11

    Red tilapia is becoming more popular for aquaculture production in China in recent years. However, the pigmentation differentiation in genetic breeding is the main problem limiting its development of commercial red tilapia culture and the genetic basis of skin color variation is still unknown. In this study, we conducted Illumina sequencing of transcriptome on three color variety red tilapia. A total of 224,895,758 reads were generated, resulting in 160,762 assembled contigs that were used as reference contigs. The contigs of red tilapia transcriptome had hits in the range of 53.4% to 86.7% of the unique proteins of zebrafish, fugu, medaka, three-spined stickleback and tilapia. And 44,723 contigs containing 77,423 simple sequence repeats (SSRs) were identified, with 16,646 contigs containing more than one SSR. Three skin transcriptomes were compared pairwise and the results revealed that there were 148 common significantly differentially expressed unigenes and several key genes related to pigment synthesis, i.e. tyr, tyrp1, silv, sox10, slc24a5, cbs and slc7a11, were included. The results will facilitate understanding the molecular mechanisms of skin pigmentation differentiation in red tilapia and accelerate the molecular selection of the specific strain with consistent skin colors.

  12. Ectopic expression of necdin induces differentiation of mouse neuroblastoma cells.

    PubMed

    Kobayashi, Masakatsu; Taniura, Hideo; Yoshikawa, Kazuaki

    2002-11-01

    Necdin is expressed predominantly in postmitotic neurons, and ectopic expression of this protein strongly suppresses cell growth. Necdin has been implicated in the pathogenesis of Prader-Willi syndrome, a human neurodevelopmental disorder associated with genomic imprinting. Here we demonstrate that ectopic expression of necdin induces a neuronal phenotype in neuroblastoma cells. Necdin was undetectable in mouse neuroblastoma N1E-115 cells under undifferentiated and differentiated conditions. N1E-115 cells transfected with necdin cDNA showed morphological differentiation such as neurite outgrowth and expression of the synaptic marker proteins synaptotagmin and synaptophysin. In addition, Western blot analysis of the retinoblastoma protein (Rb) family members Rb, p130, and p107 revealed that necdin cDNA transfectants contained an increased level of p130 and a reduced level of p107, a pattern seen in differentiated G(0) cells. The transcription factors E2F1 and E2F4 physically interacted with necdin via their carboxyl-terminal transactivation domains, but only E2F1 abrogated necdin-induced growth arrest and neurite outgrowth of neuroblastoma cells. Overexpression of E2F1 in differentiated N1E-115 cells induced apoptosis, which was antagonized by co-expression of necdin. These results suggest that necdin promotes the differentiation and survival of neurons through its antagonistic interactions with E2F1.

  13. New potential markers of in vitro tomato morphogenesis identified by mRNA differential display.

    PubMed

    Torelli, A; Soragni, E; Bolchi, A; Petrucco, S; Ottonello, S; Branca, C

    1996-12-01

    The identification of plant genes involved in early phases of in vitro morphogenesis can not only contribute to our understanding of the processes underlying growth regulator-controlled determination, but also provide novel markers for evaluating the outcome of in vitro regeneration experiments. To search for such genes and to monitor changes in gene expression accompanying in vitro regeneration, we have adapted the mRNA differential display technique to the comparative analysis of a model system of tomato cotyledons that can be driven selectively toward either shoot or callus formation by means of previously determined growth regulator supplementations. Hormone-independent transcriptional modulation (mainly down-regulation) has been found to be the most common event, indicating that a non-specific reprogramming of gene expression quantitatively predominates during the early phases of in vitro culture. However, cDNA fragments representative of genes that are either down-regulated or induced in a programme-specific manner could also be identified, and two of them (G35, G36) were further characterized. One of these cDNA fragments, G35, corresponds to an mRNA that is down-regulated much earlier in callus- (day 2) than in shoot-determined explants (day 6). The other, G36, identifies an mRNA that is transiently expressed in shoot-determined explants only, well before any macroscopic signs of differentiation become apparent, and thus exhibits typical features of a morphogenetic marker.

  14. Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

    PubMed

    Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

    2008-01-01

    Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

  15. 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

  16. Increased co-expression of genes harboring the damaging de novo mutations in Chinese schizophrenic patients during prenatal development.

    PubMed

    Wang, Qiang; Li, Miaoxin; Yang, Zhenxing; Hu, Xun; Wu, Hei-Man; Ni, Peiyan; Ren, Hongyan; Deng, Wei; Li, Mingli; Ma, Xiaohong; Guo, Wanjun; Zhao, Liansheng; Wang, Yingcheng; Xiang, Bo; Lei, Wei; Sham, Pak C; Li, Tao

    2015-12-15

    Schizophrenia is a heritable, heterogeneous common psychiatric disorder. In this study, we evaluated the hypothesis that de novo variants (DNVs) contribute to the pathogenesis of schizophrenia. We performed exome sequencing in Chinese patients (N = 45) with schizophrenia and their unaffected parents (N = 90). Forty genes were found to contain DNVs. These genes had enriched transcriptional co-expression profile in prenatal frontal cortex (Bonferroni corrected p < 9.1 × 10(-3)), and in prenatal temporal and parietal regions (Bonferroni corrected p < 0.03). Also, four prenatal anatomical subregions (VCF, MFC, OFC and ITC) have shown significant enrichment of connectedness in co-expression networks. Moreover, four genes (LRP1, MACF1, DICER1 and ABCA2) harboring the damaging de novo mutations are strongly prioritized as susceptibility genes by multiple evidences. Our findings in Chinese schizophrenic patients indicate the pathogenic role of DNVs, supporting the hypothesis that schizophrenia is a neurodevelopmental disease.

  17. Increased co-expression of genes harboring the damaging de novo mutations in Chinese schizophrenic patients during prenatal development

    PubMed Central

    Wang, Qiang; Li, Miaoxin; Yang, Zhenxing; Hu, Xun; Wu, Hei-Man; Ni, Peiyan; Ren, Hongyan; Deng, Wei; Li, Mingli; Ma, Xiaohong; Guo, Wanjun; Zhao, Liansheng; Wang, Yingcheng; Xiang, Bo; Lei, Wei; Sham, Pak C; Li, Tao

    2015-01-01

    Schizophrenia is a heritable, heterogeneous common psychiatric disorder. In this study, we evaluated the hypothesis that de novo variants (DNVs) contribute to the pathogenesis of schizophrenia. We performed exome sequencing in Chinese patients (N = 45) with schizophrenia and their unaffected parents (N = 90). Forty genes were found to contain DNVs. These genes had enriched transcriptional co-expression profile in prenatal frontal cortex (Bonferroni corrected p < 9.1 × 10−3), and in prenatal temporal and parietal regions (Bonferroni corrected p < 0.03). Also, four prenatal anatomical subregions (VCF, MFC, OFC and ITC) have shown significant enrichment of connectedness in co-expression networks. Moreover, four genes (LRP1, MACF1, DICER1 and ABCA2) harboring the damaging de novo mutations are strongly prioritized as susceptibility genes by multiple evidences. Our findings in Chinese schizophrenic patients indicate the pathogenic role of DNVs, supporting the hypothesis that schizophrenia is a neurodevelopmental disease. PMID:26666178

  18. In Search for Pheromone Receptors: Certain Members of the Odorant Receptor Family in the Desert Locust Schistocerca gregaria (Orthoptera: Acrididae) Are Co-expressed with SNMP1.

    PubMed

    Pregitzer, Pablo; Jiang, Xingcong; Grosse-Wilde, Ewald; Breer, Heinz; Krieger, Jürgen; Fleischer, Joerg

    2017-01-01

    Under given environmental conditions, the desert locust ( Schistocera gregaria ) forms destructive migratory swarms of billions of animals, leading to enormous crop losses in invaded regions. Swarm formation requires massive reproduction as well as aggregation of the animals. Pheromones that are detected via the olfactory system have been reported to control both reproductive and aggregation behavior. However, the molecular basis of pheromone detection in the antennae of Schistocerca gregaria is unknown. As an initial step to disclose pheromone receptors, we sequenced the antennal transcriptome of the desert locust. By subsequent bioinformatical approaches, 119 distinct nucleotide sequences encoding candidate odorant receptors (ORs) were identified. Phylogenetic analyses employing the identified ORs from Schistocerca gregaria (SgreORs) and OR sequences from the related species Locusta migratoria revealed a group of locust ORs positioned close to the root, i.e. at a basal site in a phylogenetic tree. Within this particular OR group (termed basal or b-OR group), the locust OR sequences were strictly orthologous, a trait reminiscent of pheromone receptors from lepidopteran species. In situ hybridization experiments with antennal tissue demonstrated expression of b-OR types from Schistocerca gregaria in olfactory sensory neurons (OSNs) of either sensilla trichodea or sensilla basiconica, both of which have been reported to respond to pheromonal substances. More importantly, two-color fluorescent in situ hybridization experiments showed that most b-OR types were expressed in cells co-expressing the "sensory neuron membrane protein 1" (SNMP1), a marker indicative of pheromone-sensitive OSNs in insects. Analyzing the expression of a larger number of SgreOR types outside the b-OR group revealed that only a few of them were co-expressed with SNMP1. In summary, we have identified several candidate pheromone receptors from Schistocerca gregaria that could mediate responses to

  19. Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction

    NASA Astrophysics Data System (ADS)

    Hansen, Matthew; Everett, Logan; Singh, Larry; Hannenhalli, Sridhar

    Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

  20. Co-expression of NCED and ALO improves vitamin C level and tolerance to drought and chilling in transgenic tobacco and stylo plants.

    PubMed

    Bao, Gegen; Zhuo, Chunliu; Qian, Chunmei; Xiao, Ting; Guo, Zhenfei; Lu, Shaoyun

    2016-01-01

    Abscisic acid (ABA) regulates plant adaptive responses to various environmental stresses, while L-ascorbic acid (AsA) that is also named vitamin C is an important antioxidant and involves in plant stress tolerance and the immune system in domestic animals. Transgenic tobacco (Nicotiana tabacum L.) and stylo [Stylosanthes guianensis (Aublet) Swartz], a forage legume, plants co-expressing stylo 9-cis-epoxycarotenoid dioxygenase (SgNCED1) and yeast D-arabinono-1,4-lactone oxidase (ALO) genes were generated in this study, and tolerance to drought and chilling was analysed in comparison with transgenic tobacco overexpressing SgNCED1 or ALO and the wild-type plants. Compared to the SgNCED1 or ALO transgenic plants, in which only ABA or AsA levels were increased, both ABA and AsA levels were increased in transgenic tobacco and stylo plants co-expressing SgNCED1 and ALO genes. Compared to the wild type, an enhanced drought tolerance was observed in SgNCED1 transgenic tobacco plants with induced expression of drought-responsive genes, but not in ALO plants, while an enhanced chilling tolerance was observed in ALO transgenic tobaccos with induced expression of cold-responsive genes, but not in SgNCED1 plants. Co-expression of SgNCED1 and ALO genes resulted in elevated tolerance to both drought and chilling in transgenic tobacco and stylo plants with induced expression of both drought and cold-responsive genes. Our result suggests that co-expression of SgNCED1 and ALO genes is an effective way for use in forage plant improvement for increased tolerance to drought and chilling and nutrition quality. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  1. A SoxC gene related to larval shell development and co-expression analysis of different shell formation genes in early larvae of oyster.

    PubMed

    Liu, Gang; Huan, Pin; Liu, Baozhong

    2017-06-01

    Among the potential larval shell formation genes in mollusks, most are expressed in cells surrounding the shell field during the early phase of shell formation. The only exception (cgi-tyr1) is expressed in the whole larval mantle and thus represents a novel type of expression pattern. This study reports another gene with such an expression pattern. The gene encoded a SoxC homolog of the Pacific oyster Crassostrea gigas and was named cgi-soxc. Whole-mount in situ hybridization revealed that the gene was highly expressed in the whole larval mantle of early larvae. Based on its spatiotemporal expression, cgi-soxc is hypothesized to be involved in periostracum biogenesis, biomineralization, and regulation of cell proliferation. Furthermore, we investigated the interrelationship between cgi-soxc expression and two additional potential shell formation genes, cgi-tyr1 and cgi-gata2/3. The results confirmed co-expression of the three genes in the larval mantle of early D-veliger. Nevertheless, cgi-gata2/3 was only expressed in the mantle edge, and the other two genes were expressed in all mantle cells. Based on the spatial expression patterns of the three genes, two cell groups were identified from the larval mantle (tyr1 + /soxc + /gata2/3 + cells and tyr1 + /soxc + /gata2/3 - cells) and are important to study the differentiation and function of this tissue. The results of this study enrich our knowledge on the structure and function of larval mantle and provide important information to understand the molecular mechanisms of larval shell formation.

  2. Schistosoma mansoni: resistant specific infection-induced gene expression in Biomphalaria glabrata identified by fluorescent-based differential display.

    PubMed

    Lockyer, Anne E; Noble, Leslie R; Rollinson, David; Jones, Catherine S

    2004-01-01

    The freshwater tropical snail Biomphalaria glabrata is an intermediate host for Schistosoma mansoni, the causative agent of human intestinal schistosomiasis, and strains differ in their susceptibility to parasite infection. Changes in gene expression in response to parasite infection have been simultaneously examined in a susceptible strain (NHM1742) and a resistant strain (NHM1981) using a newly developed fluorescent-based differential display method. Such RNA profiling techniques allow the examination of changes in gene expression in response to parasite infection, without requiring previous sequence knowledge, or selecting candidate genes that may be involved in the complex neuroendocrine or defence systems of the snail. Thus, novel genes may be identified. Ten transcripts were initially identified, present only in the profiles derived from snails of the resistant strain when exposed to infection. The differential expression of five of these genes, including HSP70 and several novel transcripts with one containing at least two globin-like domains, has been confirmed by semi-quantitative RT-PCR.

  3. 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.

  4. Enhanced in vivo selection of bone marrow cells by retroviral-mediated coexpression of mutant O6-methylguanine-DNA-methyltransferase and HOXB4.

    PubMed

    Milsom, Michael D; Woolford, Lorna B; Margison, Geoffrey P; Humphries, R Keith; Fairbairn, Leslie J

    2004-11-01

    To attain therapeutic levels of gene-modified hematopoietic stem cells, it may be necessary in the majority of disorders to provide an in vivo selective advantage that facilitates the expansion of their numbers. A popular strategy to achieve in vivo selection has been to employ drug selection while coexpressing a transgene that conveys chemoresistance, such as O6-methylguanine-DNA-methyltransferase (MGMT). An alternate approach is to confer an enhanced proliferative potential upon gene-modified hematopoietic stem cells through the delivery of the homeobox transcription factor HOXB4. By developing a novel tricistronic retroviral vector, we have facilitated the simultaneous coexpression of a mutant version of MGMT and HOXB4 in retrovirally transduced bone marrow. Using an in vivo competitive repopulation assay, we demonstrate that primary bone marrow cells containing this construct show enhanced reconstitution following transplant and improved selection subsequent to chemotherapeutic challenge in comparison to cells expressing either HOXB4 or MGMT alone. This selection advantage was evident even when HOXB4/MGMT-coexpressing cells were infused along with a large excess of unmodified cells. We propose that this selection cassette may facilitate the in vivo expansion of gene-modified hematopoietic stem cells at a level in excess of previous strategies.

  5. Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy

    PubMed Central

    Friedenberg, Steven G.; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M.

    2017-01-01

    OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions. PMID:27347821

  6. Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy.

    PubMed

    Friedenberg, Steven G; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M

    2016-07-01

    OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions.

  7. [Weighted gene co-expression network analysis in biomedicine research].

    PubMed

    Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

    2017-11-25

    High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

  8. Identification of differentially expressed lncRNAs involved in transient regeneration of the neonatal C57BL/6J mouse heart by next-generation high-throughput RNA sequencing.

    PubMed

    Chen, Yu-Mei; Li, Hua; Fan, Yi; Zhang, Qi-Jun; Li, Xing; Wu, Li-Jie; Chen, Zi-Jie; Zhu, Chun; Qian, Ling-Mei

    2017-04-25

    Previous studies have shown that mammalian cardiac tissue has a regenerative capacity. Remarkably, neonatal mice can regenerate their cardiac tissue for up to 6 days after birth, but this capacity is lost by day 7. In this study, we aimed to explore the expression pattern of long noncoding RNA (lncRNA) during this period and examine the mechanisms underlying this process. We found that 685 lncRNAs and 1833 mRNAs were differentially expressed at P1 and P7 by the next-generation high-throughput RNA sequencing. The coding genes associated with differentially expressed lncRNAs were mainly involved in metabolic processes and cell proliferation, and also were potentially associated with several key regeneration signalling pathways, including PI3K-Akt, MAPK, Hippo and Wnt. In addition, we identified some correlated targets of highly-dysregulated lncRNAs such as Igfbp3, Trnp1, Itgb6, and Pim3 by the coding-noncoding gene co-expression network. These data may offer a reference resource for further investigation about the mechanisms by which lncRNAs regulate cardiac regeneration.

  9. Identifying Differential Item Functioning of Rating Scale Items with the Rasch Model: An Introduction and an Application

    ERIC Educational Resources Information Center

    Myers, Nicholas D.; Wolfe, Edward W.; Feltz, Deborah L.; Penfield, Randall D.

    2006-01-01

    This study (a) provided a conceptual introduction to differential item functioning (DIF), (b) introduced the multifaceted Rasch rating scale model (MRSM) and an associated statistical procedure for identifying DIF in rating scale items, and (c) applied this procedure to previously collected data from American coaches who responded to the coaching…

  10. Identification and profiling of Cyprinus carpio microRNAs during ovary differentiation by deep sequencing.

    PubMed

    Wang, Fang; Jia, Yongfang; Wang, Po; Yang, Qianwen; Du, QiYan; Chang, ZhongJie

    2017-04-28

    MicroRNAs (miRNAs) are endogenous small non-coding RNAs that regulate gene expression by targeting specific mRNAs. However, the possible role of miRNAs in the ovary differentiation and development of fish is not well understood. In this study, we examined the expression profiles and differential expression of miRNAs during three key stages of ovarian development and different developmental stages in common carp Cyprinus carpio. A total of 8765 miRNAs were identified, including 2155 conserved miRNAs highly conserved among various species, 145 miRNAs registered in miRBase for common carp, and 6505 novel miRNAs identified in common carp for the first time. Comparison of miRNA expression profiles among the five libraries identified 714 co-expressed and 2382 specific expressed miRNAs. Overall, 150, 628, and 431 specifically expressed miRNAs were identified in primordial gonad, juvenile ovary, and adult ovary, respectively. MiR-6758-3p, miR-3050-5p, and miR-2985-3p were highly expressed in primordial gonad, miR-3544-5p, miR-6877-3p, and miR-9086-5p were highly expressed in juvenile ovary, and miR-154-3p, miR-5307-5p, and miR-3958-3p were highly expressed in adult ovary. Predicted target genes of specific miRNAs in primordial gonad were involved in many reproductive biology signaling pathways, including transforming growth factor-β, Wnt, oocyte meiosis, mitogen-activated protein kinase, Notch, p53, and gonadotropin-releasing hormone pathways. Target-gene prediction revealed upward trends in miRNAs targeting male-bias genes, including dmrt1, atm, gsdf, and sox9, and downward trends in miRNAs targeting female-bias genes including foxl2, smad3, and smad4. Other sex-related genes such as sf1 were also predicted to be miRNA target genes. This comprehensive miRNA transcriptome analysis demonstrated differential expression profiles of miRNAs during ovary development in common carp. These results could facilitate future exploitation of the sex-regulatory roles and mechanisms of

  11. Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

    PubMed

    Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

    2014-01-01

    The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

  12. Perivascular epithelioid cell tumor in the duodenum: challenge in differential diagnosis.

    PubMed

    Chen, Zehong; Shi, Huijuan; Peng, Jianjun; Yuan, Yujie; Chen, Jianhui; Song, Wu

    2015-01-01

    Defined as a family of scarce mesenchymal neoplasm which distinctively co-express melanocytic markers and muscle markers, perivascular epithelioid cell tumors (PEComas) have been reported almost everybody site. Perivascular epithelioid cell tumors-not otherwise specified (PEComas-NOS) arising in the gastrointestinal (GI) tract are still restricted into sporadic case reports. Herein we present a case of GI PEComas-NOS which occurs in the duodenum of a 27-year-old male. Our initial diagnosis tended to gastrointestinal stromal tumor or smooth muscle tumor till the correct diagnosis of perivascular epithelioid cell tumor (PEComa) was established by postoperative pathological examination. We also make a literature review of GI PEComas-NOS and highlight the challenge it brings to the differential diagnosis.

  13. Microarray Analysis of Long Noncoding RNAs in Female Diabetic Peripheral Neuropathy Patients.

    PubMed

    Luo, Lin; Ji, Lin-Dan; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Zhou, Wen-Hua

    2018-01-01

    Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus (DM). Because of its controversial pathogenesis, DPN is still not diagnosed or managed properly in most patients. In this study, human lncRNA microarrays were used to identify the differentially expressed lncRNAs in DM and DPN patients, and some of the discovered lncRNAs were further validated in additional 78 samples by quantitative realtime PCR (qRT-PCR). The microarray analysis identified 446 and 1327 differentially expressed lncRNAs in DM and DPN, respectively. The KEGG pathway analysis further revealed that the differentially expressed lncRNA-coexpressed mRNAs between DPN and DM groups were significantly enriched in the MAPK signaling pathway. The lncRNA/mRNA coexpression network indicated that BDNF and TRAF2 correlated with 6 lncRNAs. The qRT-PCR confirmed the initial microarray results. These findings demonstrated that the interplay between lncRNAs and mRNA may be involved in the pathogenesis of DPN, especially the neurotrophin-MAPK signaling pathway, thus providing relevant information for future studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

  14. Decreased Nucleotide and Expression Diversity and Modified Coexpression Patterns Characterize Domestication in the Common Bean[W][OPEN

    PubMed Central

    Bellucci, Elisa; Bitocchi, Elena; Ferrarini, Alberto; Benazzo, Andrea; Biagetti, Eleonora; Klie, Sebastian; Minio, Andrea; Rau, Domenico; Rodriguez, Monica; Panziera, Alex; Venturini, Luca; Attene, Giovanna; Albertini, Emidio; Jackson, Scott A.; Nanni, Laura; Fernie, Alisdair R.; Nikoloski, Zoran; Bertorelle, Giorgio; Delledonne, Massimo; Papa, Roberto

    2014-01-01

    Using RNA sequencing technology and de novo transcriptome assembly, we compared representative sets of wild and domesticated accessions of common bean (Phaseolus vulgaris) from Mesoamerica. RNA was extracted at the first true-leaf stage, and de novo assembly was used to develop a reference transcriptome; the final data set consists of ∼190,000 single nucleotide polymorphisms from 27,243 contigs in expressed genomic regions. A drastic reduction in nucleotide diversity (∼60%) is evident for the domesticated form, compared with the wild form, and almost 50% of the contigs that are polymorphic were brought to fixation by domestication. In parallel, the effects of domestication decreased the diversity of gene expression (18%). While the coexpression networks for the wild and domesticated accessions demonstrate similar seminal network properties, they show distinct community structures that are enriched for different molecular functions. After simulating the demographic dynamics during domestication, we found that 9% of the genes were actively selected during domestication. We also show that selection induced a further reduction in the diversity of gene expression (26%) and was associated with 5-fold enrichment of differentially expressed genes. While there is substantial evidence of positive selection associated with domestication, in a few cases, this selection has increased the nucleotide diversity in the domesticated pool at target loci associated with abiotic stress responses, flowering time, and morphology. PMID:24850850

  15. [Involvement of hydrogen peroxide in the regulation of coexpression of alternative oxidase and rotenone-insensitive NADH dehydrogenase in tomato leaves and calluses].

    PubMed

    Eprintsev, A T; Mal'tseva, E V; Shatskikh, A S; Popov, V N

    2011-01-01

    The involvement of active oxygen forms in the regulation of the expression of mitochondrial respiratory chain components, which are not related to energy storing, has been in vitro and in vivo studied in Lycopersicum esculentum L. The highest level of transcription of genes encoding alternative oxidase and NADH dehydrogenase has been observed in green tomato leaves. It has been shown that even low H2O2 concentrations activate both aoxlalpha and ndb1 genes, encoding alternative oxidase and external mitochondrial rotenone-insensitive NADH dehydrogenase, respectively. According to our results, in the case of an oxidative stress, alternative oxidase and NADH dehydrogenase are coexpressed in tomato plant tissues, and active oxygen forms serve as the secondary messengers of their coexpression.

  16. Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

    PubMed Central

    2011-01-01

    Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the

  17. Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.

    PubMed

    Piao, Guanying; Wu, Jiarui

    2013-11-01

    To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma. The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation. A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis. These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.

  18. Opsin expression in Limulus eyes: a UV opsin is expressed in each eye type and co-expressed with a visible light-sensitive opsin in ventral larval eyes.

    PubMed

    Battelle, Barbara-Anne; Kempler, Karen E; Harrison, Alexandra; Dugger, Donald R; Payne, Richard

    2014-09-01

    The eyes of the horseshoe crab, Limulus polyphemus, are a model for studies of visual function and the visual systems of euarthropods. Much is known about the structure and function of L. polyphemus photoreceptors, much less about their photopigments. Three visible-light-sensitive L. polyphemus opsins were characterized previously (LpOps1, 2 and 5). Here we characterize a UV opsin (LpUVOps1) that is expressed in all three types of L. polyphemus eyes. It is expressed in most photoreceptors in median ocelli, the only L. polyphemus eyes in which UV sensitivity was previously detected, and in the dendrite of eccentric cells in lateral compound eyes. Therefore, eccentric cells, previously thought to be non-photosensitive second-order neurons, may actually be UV-sensitive photoreceptors. LpUVOps1 is also expressed in small photoreceptors in L. polyphemus ventral larval eyes, and intracellular recordings from these photoreceptors confirm that LpUVOps1 is an active, UV-sensitive photopigment. These photoreceptors also express LpOps5, which we demonstrate is an active, long-wavelength-sensitive photopigment. Thus small photoreceptors in ventral larval eyes, and probably those of the other larval eyes, have dual sensitivity to UV and visible light. Interestingly, the spectral tuning of small ventral photoreceptors may change day to night, because the level of LpOps5 in their rhabdoms is lower during the day than during the night, whereas LpUVOps1 levels show no diurnal change. These and previous findings show that opsin co-expression and the differential regulation of co-expressed opsins in rhabdoms is a common feature of L. polyphemus photoreceptors. © 2014. Published by The Company of Biologists Ltd.

  19. Opsin expression in Limulus eyes: a UV opsin is expressed in each eye type and co-expressed with a visible light-sensitive opsin in ventral larval eyes

    PubMed Central

    Battelle, Barbara-Anne; Kempler, Karen E.; Harrison, Alexandra; Dugger, Donald R.; Payne, Richard

    2014-01-01

    The eyes of the horseshoe crab, Limulus polyphemus, are a model for studies of visual function and the visual systems of euarthropods. Much is known about the structure and function of L. polyphemus photoreceptors, much less about their photopigments. Three visible-light-sensitive L. polyphemus opsins were characterized previously (LpOps1, 2 and 5). Here we characterize a UV opsin (LpUVOps1) that is expressed in all three types of L. polyphemus eyes. It is expressed in most photoreceptors in median ocelli, the only L. polyphemus eyes in which UV sensitivity was previously detected, and in the dendrite of eccentric cells in lateral compound eyes. Therefore, eccentric cells, previously thought to be non-photosensitive second-order neurons, may actually be UV-sensitive photoreceptors. LpUVOps1 is also expressed in small photoreceptors in L. polyphemus ventral larval eyes, and intracellular recordings from these photoreceptors confirm that LpUVOps1 is an active, UV-sensitive photopigment. These photoreceptors also express LpOps5, which we demonstrate is an active, long-wavelength-sensitive photopigment. Thus small photoreceptors in ventral larval eyes, and probably those of the other larval eyes, have dual sensitivity to UV and visible light. Interestingly, the spectral tuning of small ventral photoreceptors may change day to night, because the level of LpOps5 in their rhabdoms is lower during the day than during the night, whereas LpUVOps1 levels show no diurnal change. These and previous findings show that opsin co-expression and the differential regulation of co-expressed opsins in rhabdoms is a common feature of L. polyphemus photoreceptors. PMID:24948643

  20. 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

  1. 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.

  2. Can Abdominal CT Imaging Help Accurately Identify a Dedifferentiated Component in a Well-Differentiated Liposarcoma?

    PubMed Central

    Bhosale, Priya; Wang, Jieqi; Varma, Datla G.K; Jensen, Corey; Patnana, Madhavi; Wei, Wei; Chauhan, Anil; Feig, Barry; Patel, Shreyaskumar; Somaiah, Neeta; Sagebiel, Tara

    2016-01-01

    Purpose To assess the ability of CT to differentiate an atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLPS) from a WDLPS with a dedifferentiated component (DDLPS) within it. Materials and Methods Forty-nine untreated patients with abdominal atypical lipomatous tumors/well-differentiated liposarcomas who had undergone contrast-enhanced CT were identified using an institutional database. Three radiologists who were blinded to the pathology findings evaluated all the images independently to determine whether a dedifferentiated component was present within the WDLPS. The CT images were evaluated for fat content (≤25% or >25%); presence of ground-glass density, enhancing and/or necrotic nodules; presence of a capsule surrounding the mass; septations; and presence and pattern of calcifications. A multivariate logistic regression model with generalized estimating equations was used to correlate imaging features with pathology findings. Kappa statistics were calculated to assess agreement between the three radiologists. Results On the basis of pathological findings, 12 patients had been diagnosed with DDLPS within a WDLPS and 37 had been diagnosed with WDLPS. The presence of an enhancing or a centrally necrotic nodule within the atypical lipomatous tumor was associated with dedifferentiated liposarcoma (p = 0.02 and p = 0.0003, respectively). The three readers showed almost perfect agreement in overall diagnosis (kappa r = 0.83; 95% confidence-interval 0.67 to 0.99). Conclusion An enhancing or centrally necrotic nodule may be indicative of a dedifferentiated component in well-differentiated liposarcoma. Ground-glass density nodules may not be indicative of dedifferentiation. PMID:27454788

  3. ChlamyNET: a Chlamydomonas gene co-expression network reveals global properties of the transcriptome and the early setup of key co-expression patterns in the green lineage.

    PubMed

    Romero-Campero, Francisco J; Perez-Hurtado, Ignacio; Lucas-Reina, Eva; Romero, Jose M; Valverde, Federico

    2016-03-12

    Chlamydomonas reinhardtii is the model organism that serves as a reference for studies in algal genomics and physiology. It is of special interest in the study of the evolution of regulatory pathways from algae to higher plants. Additionally, it has recently gained attention as a potential source for bio-fuel and bio-hydrogen production. The genome of Chlamydomonas is available, facilitating the analysis of its transcriptome by RNA-seq data. This has produced a massive amount of data that remains fragmented making necessary the application of integrative approaches based on molecular systems biology. We constructed a gene co-expression network based on RNA-seq data and developed a web-based tool, ChlamyNET, for the exploration of the Chlamydomonas transcriptome. ChlamyNET exhibits a scale-free and small world topology. Applying clustering techniques, we identified nine gene clusters that capture the structure of the transcriptome under the analyzed conditions. One of the most central clusters was shown to be involved in carbon/nitrogen metabolism and signalling, whereas one of the most peripheral clusters was involved in DNA replication and cell cycle regulation. The transcription factors and regulators in the Chlamydomonas genome have been identified in ChlamyNET. The biological processes potentially regulated by them as well as their putative transcription factor binding sites were determined. The putative light regulated transcription factors and regulators in the Chlamydomonas genome were analyzed in order to provide a case study on the use of ChlamyNET. Finally, we used an independent data set to cross-validate the predictive power of ChlamyNET. The topological properties of ChlamyNET suggest that the Chlamydomonas transcriptome posseses important characteristics related to error tolerance, vulnerability and information propagation. The central part of ChlamyNET constitutes the core of the transcriptome where most authoritative hub genes are located

  4. Differential effects of human SP-A1 and SP-A2 variants on phospholipid monolayers containing surfactant protein B

    PubMed Central

    Wang, Guirong; Taneva, Svetla; Keough, Kevin M.W.; Floros, Joanna

    2010-01-01

    Summary Surfactant protein A (SP-A), the most abundant protein in the lung alveolar surface, has multiple activities, including surfactant-related functions. SP-A is required for the formation of tubular myelin and the lung surface film. The human SP-A locus consists of two functional SP-A genes, SP-A1 and SP-A2, with a number of alleles characterized for each gene. We have found that the human in vitro expressed variants, SP-A1 (6A2) and SP-A2 (1A0), and the coexpressed SP-A1/SP-A2 (6A2/1A0) protein have a differential influence on the organization of phospholipid monolayers containing surfactant protein B (SP-B). Lipid films containing SP-B and SP-A2 (1A0) showed surface features similar to those observed in lipid films with SP-B and native human SP-A. Fluorescence images revealed the presence of characteristic fluorescent probe-excluding clusters coexisting with the traditional lipid liquid-expanded and liquid-condensed phase. Images of the films containing SP-B and SP-A1 (6A2) showed different distribution of the proteins. The morphology of lipid films containing SP-B and the coexpressed SP-A1/SP-A2 (6A2/1A0) combined features of the individual films containing the SP-A1 or SP-A2 variant. The results indicate that human SP-A1 and SP-A2 variants exhibit differential effects on characteristics of phospholipid monolayers containing SP-B. This may differentially impact surface film activity. PMID:17678872

  5. 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.

  6. Enhancement of γ-aminobutyric acid production in recombinant Corynebacterium glutamicum by co-expressing two glutamate decarboxylase genes from Lactobacillus brevis.

    PubMed

    Shi, Feng; Jiang, Junjun; Li, Yongfu; Li, Youxin; Xie, Yilong

    2013-11-01

    γ-Aminobutyric acid (GABA), a non-protein amino acid, is a bioactive component in the food, feed and pharmaceutical fields. To establish an effective single-step production system for GABA, a recombinant Corynebacterium glutamicum strain co-expressing two glutamate decarboxylase (GAD) genes (gadB1 and gadB2) derived from Lactobacillus brevis Lb85 was constructed. Compared with the GABA production of the gadB1 or gadB2 single-expressing strains, GABA production by the gadB1-gadB2 co-expressing strain increased more than twofold. By optimising urea supplementation, the total production of L-glutamate and GABA increased from 22.57 ± 1.24 to 30.18 ± 1.33 g L⁻¹, and GABA production increased from 4.02 ± 0.95 to 18.66 ± 2.11 g L⁻¹ after 84-h cultivation. Under optimal urea supplementation, L-glutamate continued to be consumed, GABA continued to accumulate after 36 h of fermentation, and the pH level fluctuated. GABA production increased to a maximum level of 27.13 ± 0.54 g L⁻¹ after 120-h flask cultivation and 26.32 g L⁻¹ after 60-h fed-batch fermentation. The conversion ratio of L-glutamate to GABA reached 0.60-0.74 mol mol⁻¹. By co-expressing gadB1 and gadB2 and optimising the urea addition method, C. glutamicum was genetically improved for de novo biosynthesis of GABA from its own accumulated L-glutamate.

  7. The use of open source bioinformatics tools to dissect transcriptomic data.

    PubMed

    Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

    2012-01-01

    Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

  8. Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

    PubMed

    Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

    2010-10-01

    The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of <3%, we identified 111 candidates from conditioned medium, including 44 proteins that have signal peptides or are described as secreted proteins in the UniProt database. As validation, we confirmed that one of these proteins, insulin-like growth factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

  9. Solexa Sequencing of Novel and Differentially Expressed MicroRNAs in Testicular and Ovarian Tissues in Holstein Cattle

    PubMed Central

    Huang, Jinming; Ju, Zhihua; Li, Qiuling; Hou, Qinlei; Wang, Changfa; Li, Jianbin; Li, Rongling; Wang, Lingling; Sun, Tao; Hang, Suqin; Gao, Yundong; Hou, Minghai; Zhong, Jifeng

    2011-01-01

    The posttranscriptional gene regulation mediated by microRNA plays an important role in the development and function of male and female reproductive organs and germ cells in mammals, including cattle. In the present study, we identified novel and differentially expressed miRNAs in the testis and ovary in Holstein cattle by combining the Solexa sequencing with bioinformatics. In total 100 and 104 novel pre-miRNAs were identified in testicular and ovarian tissues, encoding 122 and 136 mature miRNAs, respectively. Of these, 6 miRNAs appear to be bovine-specific. A total of 246 known miRNAs were co-expressed in the testicular and ovarian tissues. Of the known miRNAs, twenty-one testis-specific and nine ovary-specific (1-23 reads) were found. Approximately 30.5% of the known bovine miRNAs in this study were found to have >2-fold differential expression within the two respective reproductive organ systems. The putative miRNA target genes of miRNAs were involved in pathways associated with reproductive physiology. Both known and novel tissue-specific miRNAs are expressed by Real-time quantitative PCR analysis in dairy cattle. This study expands the number of miRNAs known to be expressed in cattle. The patterns of miRNAs expression differed significantly between the bovine testicular and ovarian tissues, which provide important information on sex differences in miRNA expression. Diverse miRNAs may play an important regulatory role in the development of the reproductive organs in Holstein cattle. PMID:21912509

  10. Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants

    PubMed Central

    Weston, David J; Gunter, Lee E; Rogers, Alistair; Wullschleger, Stan D

    2008-01-01

    Background One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Ecology currently lacks an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress duration and tolerance, fitness). Results Here, we demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying genes governing the phenotypic response. Using this approach, we confirm the existence of known stress responsive pathways and marker genes, report a common abiotic stress responsive transcriptome and relate phenotypic classification to stress duration. Conclusion Linking genomic signatures to gene coexpression analysis provides a unique method of relating an observed plant phenotype to changes in gene expression that underlie that phenotype. Such information is critical to current and future investigations in plant biology and, in particular, to evolutionary ecology, where a mechanistic understanding of adaptive physiological responses to abiotic stress can provide researchers with a tool of great predictive value in understanding species and population level adaptation to climate change. PMID:18248680

  11. A high-throughput screen for inhibitors of the prolyl isomerase, Pin1, identifies a seaweed polyphenol that reduces adipose cell differentiation.

    PubMed

    Mori, Tadashi; Hidaka, Masafumi; Ikuji, Hiroko; Yoshizawa, Ibuki; Toyohara, Haruhiko; Okuda, Toru; Uchida, Chiyoko; Asano, Tomoichiro; Yotsu-Yamashita, Mari; Uchida, Takafumi

    2014-01-01

    The peptidyl prolyl cis/trans isomerase Pin1 enhances the uptake of triglycerides and the differentiation of fibroblasts into adipose cells in response to insulin stimulation. Pin1 downregulation could be a potential approach to prevent and treat obesity-related disorders. In order to identify an inhibitor of Pin1 that exhibited minimal cytotoxicity, we established a high-throughput screen for Pin1 inhibitors and used this method to identify an inhibitor from 1,056 crude fractions of two natural product libraries. The candidate, a phlorotannin called 974-B, was isolated from the seaweed, Ecklonia kurome. 974-B inhibited the differentiation of mouse embryonic fibroblasts and 3T3-L1 cells into adipose cells without inducing cytotoxicity. We discovered the Pin1 inhibitor, 974-B, from the seaweed, E. kurome, and showed that it blocks the differentiation of fibroblasts into adipose cells, suggesting that 974-B could be a lead drug candidate for obesity-related disorders.

  12. Comparative transcriptome and gene co-expression network analysis reveal genes and signaling pathways adaptively responsive to varied adverse stresses in the insect fungal pathogen, Beauveria bassiana.

    PubMed

    He, Zhangjiang; Zhao, Xin; Lu, Zhuoyue; Wang, Huifang; Liu, Pengfei; Zeng, Fanqin; Zhang, Yongjun

    2018-01-01

    Sensing, responding, and adapting to the surrounding environment are crucial for all living organisms to survive, proliferate, and differentiate in their biological niches. Beauveria bassiana is an economically important insect-pathogenic fungus which is widely used as a biocontrol agent to control a variety of insect pests. The fungal pathogen unavoidably encounters a variety of adverse environmental stresses and defense response from the host insects during application of the fungal agents. However, few are known about the transcription response of the fungus to respond or adapt varied adverse stresses. Here, we comparatively analyzed the transcriptome of B. bassiana in globe genome under the varied stationary-phase stresses including osmotic agent (0.8 M NaCl), high temperature (32 °C), cell wall-perturbing agent (Congo red), and oxidative agents (H 2 O 2 or menadione). Total of 12,412 reads were obtained, and mapped to the 6767 genes of the B. bassiana. All of these stresses caused transcription responses involved in basal metabolism, cell wall construction, stress response or cell rescue/detoxification, signaling transduction and gene transcription regulation, and likely other cellular processes. An array of genes displayed similar transcription patterns in response to at least two of the five stresses, suggesting a shared transcription response to varied adverse stresses. Gene co-expression network analysis revealed that mTOR signaling pathway, but not HOG1 MAP kinase pathway, played a central role in regulation the varied adverse stress responses, which was verified by RNAi-mediated knockdown of TOR1. Our findings provided an insight of transcription response and gene co-expression network of B. bassiana in adaptation to varied environments. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Co-expression of monocarboxylate transporter 1 (MCT1) and its chaperone (CD147) is associated with low survival in patients with gastrointestinal stromal tumors (GISTs).

    PubMed

    de Oliveira, Antônio Talvane Torres; Pinheiro, Céline; Longatto-Filho, Adhemar; Brito, Maria Jose; Martinho, Olga; Matos, Delcio; Carvalho, André Lopes; Vazquez, Vinícius Lima; Silva, Thiago Buosi; Scapulatempo, Cristovam; Saad, Sarhan Sydney; Reis, Rui Manuel; Baltazar, Fátima

    2012-02-01

    Monocarboxylate transporters (MCTs) have been described to play an important role in cancer, but to date there are no reports on the significance of MCT expression in gastrointestinal stromal tumors (GISTs). The aim of the present work was to assess the value of MCT expression, as well as co-expression with the MCT chaperone CD147 in GISTs and evaluate their clinical-pathological significance. We analyzed the immunohistochemical expression of MCT1, MCT2, MCT4 and CD147 in a series of 64 GISTs molecularly characterized for KIT, PDGFRA and BRAF mutations. MCT1, MCT2 and MCT4 were highly expressed in GISTs. CD147 expression was associated with mutated KIT (p = 0.039), as well as a progressive increase in Fletcher's Risk of Malignancy (p = 0.020). Importantly, co-expression of MCT1 with CD147 was associated with low patient's overall survival (p = 0.037). These findings suggest that co-expression of MCT1 with its chaperone CD147 is involved in GISTs aggressiveness, pointing to a contribution of cancer cell metabolic adaptations in GIST development and/or progression.

  14. S187. SEARCHING FOR BRAIN CO-EXPRESSION MODULES THAT CONTRIBUTE DISPROPORTIONATELY TO THE COMMON POLYGENIC RISK FOR SCHIZOPHRENIA

    PubMed Central

    Costas, Javier; Paramo, Mario; Arrojo, Manuel

    2018-01-01

    Abstract Background Genomic research has revealed that schizophrenia is a highly polygenic disease. Recent estimates indicate that at least 71% of genomic segments of 1 Mb include one or more risk loci for schizophrenia (Loh et al., Nature Genet 2015). This extremely high polygenicity represents a challenge to decipher the biological basis of schizophrenia, as it is expected that any set of SNPs with enough size will be associated with the disorder. Among the different gene sets available for study (such as those from Gene Ontology, KEGG pathway, Reactome pathways or protein protein interaction datasets), those based on brain co-expression networks represent putative functional relationships in the relevant tissue. The aim of this work was to identify brain co-expression networks that contribute disproportionately to the common polygenic risk for schizophrenia to get more insight on schizophrenia etiopathology. Methods We analyzed a case -control dataset consisting of 582 schizophrenia patients from Galicia, NW Spain, and 591 ancestrally matched controls, genotyped with the Illumina PsychArray. Using as discovery sample the summary results from the largest GWAS of schizophrenia to date (Psychiatric Genomics Consortium, SCZ2), we generated polygenic risk scores (PRS) in our sample based on SNPs located at genes belonging to brain co-expression modules determined by the CommonMind Consortium (Fromer et al., Nature Neurosci 2016). PRS were generated using the clumping procedure of PLINK, considering several different thresholds to select SNPs from the discovery sample. In order to test if any specific module increased risk to schizophrenia more than expected by their size, we generated up to 10,000 random permutations of the same number of SNPs, matched by frequency, distance to nearest gene, number of SNPs in LD and gene density, using SNPsnap. Results As expected, most modules with enough number of independent SNPs belonging to them showed a significant increase in

  15. Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

    PubMed

    Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

    2013-03-23

    Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

  16. Mouse Cone Photoreceptors Co-express Two Functional Visual Arrestins

    PubMed Central

    Nikonov, Sergei S.; Brown, Bruce M.; Davis, Jason A.; Zuniga, Freddi I.; Bragin, Alvina; Pugh, Edward N.; Craft, Cheryl M.

    2008-01-01

    Arrestins are members of a superfamily of proteins that arrest the activity of G-protein coupled receptors. Mouse cone photoreceptors express two visual arrestins, Arr1 and Arr4 (Carr). We quantified their expression levels and subcellular distributions in mouse cones: total Arr1 was estimated to be in an ~ 6:1 ratio to cone opsin, about 50-fold higher than Arr4. Recordings from single cones of Arr1−/− and Arr4−/− mice establish that both proteins are competent to arrest the activity of photoactivated S- and M- cone opsins. Recordings from Arr1−/− , Arr4−/− double-knockout mice establish a requirement for at least one of the two visual arrestins for normal cone opsin inactivation at all flash intensities. These recordings also reveal low activity photoproducts of S- and M-opsins that are absent when Grk1 and an arrestin are co-expressed, but which decay 70-fold more rapidly than the comparable photoproducts of rhodopsin in rods. PMID:18701071

  17. Can Abdominal Computed Tomography Imaging Help Accurately Identify a Dedifferentiated Component in a Well-Differentiated Liposarcoma?

    PubMed

    Bhosale, Priya; Wang, Jieqi; Varma, Datla; Jensen, Corey; Patnana, Madhavi; Wei, Wei; Chauhan, Anil; Feig, Barry; Patel, Shreyaskumar; Somaiah, Neeta; Sagebiel, Tara

    To assess the ability of computed tomography (CT) to differentiate an atypical lipomatous tumor/well-differentiated liposarcoma (WDLPS) from a WDLPS with a dedifferentiated component (DDLPS) within it. Forty-nine untreated patients with abdominal atypical lipomatous tumors/well-differentiated liposarcomas who had undergone contrast-enhanced CT were identified using an institutional database. Three radiologists who were blinded to the pathology findings evaluated all the images independently to determine whether a dedifferentiated component was present within the WDLPS. The CT images were evaluated for fat content (≤25% or >25%); presence of ground-glass density, enhancing and/or necrotic nodules; presence of a capsule surrounding the mass; septations; and presence and pattern of calcifications. A multivariate logistic regression model with generalized estimating equations was used to correlate imaging features with pathology findings. Kappa statistics were calculated to assess agreement between the three radiologists. On the basis of pathological findings, 12 patients had been diagnosed with DDLPS within a WDLPS and 37 had been diagnosed with WDLPS. The presence of an enhancing or a centrally necrotic nodule within the atypical lipomatous tumor was associated with dedifferentiated liposarcoma (P = 0.02 and P = 0.0003, respectively). The three readers showed almost perfect agreement in overall diagnosis (κ r = 0.83; 95% confidence interval, 0.67-0.99). An enhancing or centrally necrotic nodule may be indicative of a dedifferentiated component in well-differentiated liposarcoma. Ground-glass density nodules may not be indicative of dedifferentiation.

  18. Altered interaction of HDAC5 with GATA-1 during MEL cell differentiation.

    PubMed

    Watamoto, Kouichi; Towatari, Masayuki; Ozawa, Yukiyasu; Miyata, Yasuhiko; Okamoto, Mitsunori; Abe, Akihiro; Naoe, Tomoki; Saito, Hidehiko

    2003-12-11

    The transcription factor GATA-1 plays a significant role in erythroid differentiation and association with CBP stimulates its activity by acetylation. It is possible that histone deacetylases (HDACs) repress the activity of GATA-1. In the present study, we investigated whether class I and class II HDACs interact with GATA-1 to regulate its function and indeed, GATA-1 is directly associated with HDAC3, HDAC4 and HDAC5. The expression profiling and our previous observation that GATA-2 interacts with members of the HDAC family prompted us to investigate further the biological relevance of the interaction between GATA-1 and HDAC5. Coexpression of HDAC5 suppressed the transcriptional potential of GATA-1. Our results demonstrated that GATA-1 and HDAC5 colocalized to the nucleus of murine erythroleukemia (MEL) cells. Furthermore, a portion of HDAC5 moved to the cytoplasm concomitant with MEL cell erythroid differentiation, which was induced by treatment with N,N'-hexamethylenebisacetamide. These observations support the suggestion that control of the HDAC5 nucleocytoplasmic distribution might be associated with MEL cell differentiation, possibly through regulated GATA-1 transactivation.

  19. Transcriptome interrogation of human myometrium identifies differentially expressed sense-antisense pairs of protein-coding and long non-coding RNA genes in spontaneous labor at term.

    PubMed

    Romero, Roberto; Tarca, Adi L; Chaemsaithong, Piya; Miranda, Jezid; Chaiworapongsa, Tinnakorn; Jia, Hui; Hassan, Sonia S; Kalita, Cynthia A; Cai, Juan; Yeo, Lami; Lipovich, Leonard

    2014-09-01

    To identify differentially expressed long non-coding RNA (lncRNA) genes in human myometrium in women with spontaneous labor at term. Myometrium was obtained from women undergoing cesarean deliveries who were not in labor (n = 19) and women in spontaneous labor at term (n = 20). RNA was extracted and profiled using an Illumina® microarray platform. We have used computational approaches to bound the extent of long non-coding RNA representation on this platform, and to identify co-differentially expressed and correlated pairs of long non-coding RNA genes and protein-coding genes sharing the same genomic loci. We identified co-differential expression and correlation at two genomic loci that contain coding-lncRNA gene pairs: SOCS2-AK054607 and LMCD1-NR_024065 in women in spontaneous labor at term. This co-differential expression and correlation was validated by qRT-PCR, an experimental method completely independent of the microarray analysis. Intriguingly, one of the two lncRNA genes differentially expressed in term labor had a key genomic structure element, a splice site, that lacked evolutionary conservation beyond primates. We provide, for the first time, evidence for coordinated differential expression and correlation of cis-encoded antisense lncRNAs and protein-coding genes with known as well as novel roles in pregnancy in the myometrium of women in spontaneous labor at term.

  20. 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.

  1. Loss of end-differentiated β-cell phenotype following pancreatic islet transplantation.

    PubMed

    Anderson, S J; White, M G; Armour, S L; Maheshwari, R; Tiniakos, D; Muller, Y D; Berishvili, E; Berney, T; Shaw, J A M

    2018-03-01

    Replacement of pancreatic β-cells through deceased donor islet transplantation is a proven therapy for preventing recurrent life-threatening hypoglycemia in type 1 diabetes. Although near-normal glucose levels and insulin independence can be maintained for many years following successful islet transplantation, restoration of normal functional β-cell mass has remained elusive. It has recently been proposed that dedifferentiation/plasticity towards other endocrine phenotypes may play an important role in stress-induced β-cell dysfunction in type 2 diabetes. Here we report loss of end-differentiated β-cell phenotype in 2 intraportal islet allotransplant recipients. Despite excellent graft function and sustained insulin independence, all examined insulin-positive cells had lost expression of the end-differentiation marker, urocortin-3, or appeared to co-express the α-cell marker, glucagon. In contrast, no insulin + /urocortin-3 - cells were seen in nondiabetic deceased donor control pancreatic islets. Loss of end-differentiated phenotype may facilitate β-cell survival during the stresses associated with islet isolation and culture, in addition to sustained hypoxia following engraftment. As further refinements in islet isolation and culture are made in parallel with exploration of alternative β-cell sources, graft sites, and ultimately fully vascularized bioengineered insulin-secreting microtissues, differentiation status immunostaining provides a novel tool to assess whether fully mature β-cell phenotype has been maintained. © 2017 The American Society of Transplantation and the American Society of Transplant Surgeons.

  2. Human Immunodeficiency Virus Type-1 Elite Controllers Maintain Low Co-Expression of Inhibitory Receptors on CD4+ T Cells.

    PubMed

    Noyan, Kajsa; Nguyen, Son; Betts, Michael R; Sönnerborg, Anders; Buggert, Marcus

    2018-01-01

    Human immunodeficiency virus type-1 (HIV-1) elite controllers (ELCs) represent a unique population that control viral replication in the absence of antiretroviral therapy (cART). It is well established that expression of multiple inhibitory receptors on CD8+ T cells is associated with HIV-1 disease progression. However, whether reduced co-expression of inhibitory receptors on CD4+ T cells is linked to natural viral control and slow HIV-1 disease progression remains undefined. Here, we report on the expression pattern of numerous measurable inhibitory receptors, associated with T cell exhaustion (programmed cell death-1, CTLA-4, and TIGIT), on different CD4+ T cell memory populations in ELCs and HIV-infected subjects with or without long-term cART. We found that the co-expression pattern of inhibitory receptors was significantly reduced in ELCs compared with HIV-1 cART-treated and viremic subjects, and similar to healthy controls. Markers associated with T cell exhaustion varied among different memory CD4+ T cell subsets and highest levels were found mainly on transitional memory T cells. CD4+ T cells co-expressing all inhibitory markers were positively correlated to T cell activation (CD38+ HLA-DR+) as well as the transcription factors Helios and FoxP3. Finally, clinical parameters such as CD4 count, HIV-1 viral load, and the CD4/CD8 ratio all showed significant associations with CD4+ T cell exhaustion. We demonstrate that ELCs are able to maintain lower levels of CD4+ T cell exhaustion despite years of ongoing viral replication compared with successfully cART-treated subjects. Our findings suggest that ELCs harbor a "healthy" state of inhibitory receptor expression on CD4+ T cells that might play part in maintenance of their control status.

  3. Co-expression of CD147 and GLUT-1 indicates radiation resistance and poor prognosis in cervical squamous cell carcinoma.

    PubMed

    Huang, Xin-Qiong; Chen, Xiang; Xie, Xiao-Xue; Zhou, Qin; Li, Kai; Li, Shan; Shen, Liang-Fang; Su, Juan

    2014-01-01

    The aim of this study was to investigate the association of CD147 and GLUT-1, which play important roles in glycolysis in response to radiotherapy and clinical outcomes in patients with locally advanced cervical squamous cell carcinoma (LACSCC). The records of 132 female patients who received primary radiation therapy to treat LACSCC at FIGO stages IB-IVA were retrospectively reviewed. Forty-seven patients with PFS (progression-free survival) of less than 36 months were regarded as radiation-resistant. Eighty-five patients with PFS longer than 36 months were regarded as radiation-sensitive. Using pretreatment paraffin-embedded tissues, we evaluated CD147 and GLUT-1 expression by immunohistochemistry. Overexpression of CD147, GLUT-1, and CD147 and GLUT-1 combined were 44.7%, 52.9% and 36.5%, respectively, in the radiation-sensitive group, and 91.5%, 89.4% and 83.0%, respectively, in the radiation-resistant group. The 5-year progress free survival (PFS) rates in the CD147-low, CD147-high, GLUT-1-low, GLUT-1-high, CD147- and/or GLUT-1-low and CD147- and GLUT-1- dual high expression groups were 66.79%, 87.10%, 52.78%, 85.82%, 55.94%, 82.90% and 50.82%, respectively. CD147 and GLUT-1 co-expression, FIGO stage and tumor diameter were independent poor prognostic factors for patients with LACSCC in multivariate Cox regression analysis. Patients with high expression of CD147 alone, GLUT-1 alone or co-expression of CD147 and GLUT-1 showed greater resistance to radiotherapy and a shorter PFS than those with low expression. In particular, co-expression of CD147 and GLUT-1 can be considered as a negative independent prognostic factor.

  4. Co-expression of CD147 and GLUT-1 indicates radiation resistance and poor prognosis in cervical squamous cell carcinoma

    PubMed Central

    Huang, Xin-Qiong; Chen, Xiang; Xie, Xiao-Xue; Zhou, Qin; Li, Kai; Li, Shan; Shen, Liang-Fang; Su, Juan

    2014-01-01

    The aim of this study was to investigate the association of CD147 and GLUT-1, which play important roles in glycolysis in response to radiotherapy and clinical outcomes in patients with locally advanced cervical squamous cell carcinoma (LACSCC). The records of 132 female patients who received primary radiation therapy to treat LACSCC at FIGO stages IB-IVA were retrospectively reviewed. Forty-seven patients with PFS (progression-free survival) of less than 36 months were regarded as radiation-resistant. Eighty-five patients with PFS longer than 36 months were regarded as radiation-sensitive. Using pretreatment paraffin-embedded tissues, we evaluated CD147 and GLUT-1 expression by immunohistochemistry. Overexpression of CD147, GLUT-1, and CD147 and GLUT-1 combined were 44.7%, 52.9% and 36.5%, respectively, in the radiation-sensitive group, and 91.5%, 89.4% and 83.0%, respectively, in the radiation-resistant group. The 5-year progress free survival (PFS) rates in the CD147-low, CD147-high, GLUT-1-low, GLUT-1-high, CD147- and/or GLUT-1-low and CD147- and GLUT-1- dual high expression groups were 66.79%, 87.10%, 52.78%, 85.82%, 55.94%, 82.90% and 50.82%, respectively. CD147 and GLUT-1 co-expression, FIGO stage and tumor diameter were independent poor prognostic factors for patients with LACSCC in multivariate Cox regression analysis. Patients with high expression of CD147 alone, GLUT-1 alone or co-expression of CD147 and GLUT-1 showed greater resistance to radiotherapy and a shorter PFS than those with low expression. In particular, co-expression of CD147 and GLUT-1 can be considered as a negative independent prognostic factor. PMID:24817962

  5. Swarming differentiation and swimming motility in Bacillus subtilis are controlled by swrA, a newly identified dicistronic operon.

    PubMed

    Calvio, Cinzia; Celandroni, Francesco; Ghelardi, Emilia; Amati, Giuseppe; Salvetti, Sara; Ceciliani, Fabrizio; Galizzi, Alessandro; Senesi, Sonia

    2005-08-01

    The number and disposition of flagella harbored by eubacteria are regulated by a specific trait successfully maintained over generations. The genes governing the number of flagella in Bacillus subtilis have never been identified, although the ifm locus has long been recognized to influence the motility phenotype of this microorganism. The characterization of a spontaneous ifm mutant of B. subtilis, displaying diverse degrees of cell flagellation in both liquid and solid media, raised the question of how the ifm locus governs the number and assembly of functional flagella. The major finding of this investigation is the characterization of a newly identified dicistronic operon, named swrA, that controls both swimming motility and swarming differentiation in B. subtilis. Functional analysis of the swrA operon allowed swrAA (previously named swrA [D. B. Kearns, F. Chu, R. Rudner, and R. Losick, Mol. Microbiol. 52:357-369, 2004]) to be the first gene identified in B. subtilis that controls the number of flagella in liquid environments and the assembly of flagella in response to cell contact with solid surfaces. Evidence is given that the second gene of the operon, swrAB, is essential for enabling the surface-adhering cells to undergo swarming differentiation. Preliminary data point to a molecular interaction between the two gene products.

  6. Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

    NASA Technical Reports Server (NTRS)

    Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

    2000-01-01

    Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

  7. Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

    DOE PAGES

    Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

    2005-01-01

    Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

  8. Keratitis-Ichthyosis-Deafness syndrome-associated Cx26 mutants produce nonfunctional gap junctions but hyperactive hemichannels when co-expressed with wild type Cx43

    PubMed Central

    García, Isaac E.; Maripillán, Jaime; Jara, Oscar; Ceriani, Ricardo; Palacios-Muñoz, Angelina; Ramachandran, Jayalakshimi; Olivero, Pablo; Pérez-Acle, Tomás; González, Carlos; Sáez, Juan C.; Contreras, Jorge E.; Martínez, Agustín D.

    2015-01-01

    Mutations in Cx26 gene are found in most cases of human genetic deafness. Some mutations produce syndromic deafness associated with skin disorders, like Keratitis Ichthyosis Deafness syndrome (KID). Because in the human skin Cx26 is co-expressed with other connexins, like Cx43 and Cx30, and since KID syndrome is inherited as autosomal dominant condition, it is possible that KID mutations change the way Cx26 interacts with other co-expressed connexins. Indeed, some Cx26 syndromic mutations showed gap junction dominant negative effect when co-expressed with wild type connexins, including Cx26 and Cx43. The nature of these interactions and the consequences on hemichannels and gap junction channels functions remain unknown. In this study we demonstrate that syndromic mutations at the N-terminus segment of Cx26, change connexin oligomerization compatibility, allowing aberrant interactions with Cx43. Strikingly, heteromeric oligomer formed by Cx43/Cx26 (syndromic mutants) show exacerbated hemichannel activity, but nonfunctional gap junction channels; this also occurs for those Cx26 KID mutants that do not show functional homomeric hemichannels. Heterologous expression of these hyperactive heteromeric hemichannels increases cell membrane permeability, favoring ATP release and Ca2+ overload. The functional paradox produced by oligomerization of Cx43 and Cx26 KID mutants could underlie the severe syndromic phenotype in human skin. PMID:25625422

  9. Perivascular epithelioid cell tumor in the duodenum: challenge in differential diagnosis

    PubMed Central

    Chen, Zehong; Shi, Huijuan; Peng, Jianjun; Yuan, Yujie; Chen, Jianhui; Song, Wu

    2015-01-01

    Defined as a family of scarce mesenchymal neoplasm which distinctively co-express melanocytic markers and muscle markers, perivascular epithelioid cell tumors (PEComas) have been reported almost everybody site. Perivascular epithelioid cell tumors-not otherwise specified (PEComas-NOS) arising in the gastrointestinal (GI) tract are still restricted into sporadic case reports. Herein we present a case of GI PEComas-NOS which occurs in the duodenum of a 27-year-old male. Our initial diagnosis tended to gastrointestinal stromal tumor or smooth muscle tumor till the correct diagnosis of perivascular epithelioid cell tumor (PEComa) was established by postoperative pathological examination. We also make a literature review of GI PEComas-NOS and highlight the challenge it brings to the differential diagnosis. PMID:26339433

  10. MCT1 modulates cancer cell pyruvate export and growth of tumors that co-express MCT1 and MCT4

    PubMed Central

    Hong, Candice Sun; Graham, Nicholas A.; Gu, Wen; Camacho, Carolina Espindola; Mah, Vei; Maresh, Erin L.; Alavi, Mohammed; Bagryanova, Lora; Krotee, Pascal A. L.; Gardner, Brian K.; Behbahan, Iman Saramipoor; Horvath, Steve; Chia, David; Mellinghoff, Ingo K.; Hurvitz, Sara A.; Dubinett, Steven M.; Critchlow, Susan E.; Kurdistani, Siavash K.; Goodglick, Lee; Braas, Daniel; Graeber, Thomas G.; Christofk, Heather R.

    2016-01-01

    SUMMARY Monocarboxylate Transporter 1 (MCT1) inhibition is thought to block tumor growth through disruption of lactate transport and glycolysis. Here we show MCT1 inhibition impairs proliferation of glycolytic breast cancer cells co-expressing MCT1 and MCT4 via disruption of pyruvate rather than lactate export. MCT1 expression is elevated in glycolytic breast tumors, and high MCT1 expression predicts poor prognosis in breast and lung cancer patients. Acute MCT1 inhibition reduces pyruvate export but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that co-express MCT1 and MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest MCT1 expression is elevated in glycolytic cancers to promote pyruvate export, which when inhibited enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors further supporting their use as anti-cancer therapeutics. PMID:26876179

  11. MCT1 Modulates Cancer Cell Pyruvate Export and Growth of Tumors that Co-express MCT1 and MCT4.

    PubMed

    Hong, Candice Sun; Graham, Nicholas A; Gu, Wen; Espindola Camacho, Carolina; Mah, Vei; Maresh, Erin L; Alavi, Mohammed; Bagryanova, Lora; Krotee, Pascal A L; Gardner, Brian K; Behbahan, Iman Saramipoor; Horvath, Steve; Chia, David; Mellinghoff, Ingo K; Hurvitz, Sara A; Dubinett, Steven M; Critchlow, Susan E; Kurdistani, Siavash K; Goodglick, Lee; Braas, Daniel; Graeber, Thomas G; Christofk, Heather R

    2016-02-23

    Monocarboxylate transporter 1 (MCT1) inhibition is thought to block tumor growth through disruption of lactate transport and glycolysis. Here, we show MCT1 inhibition impairs proliferation of glycolytic breast cancer cells co-expressing MCT1 and MCT4 via disruption of pyruvate rather than lactate export. MCT1 expression is elevated in glycolytic breast tumors, and high MCT1 expression predicts poor prognosis in breast and lung cancer patients. Acute MCT1 inhibition reduces pyruvate export but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that co-express MCT1 and MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest MCT1 expression is elevated in glycolytic cancers to promote pyruvate export that when inhibited, enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors, further supporting their use as anti-cancer therapeutics. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  12. 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.

  13. Transient Co-Expression of Post-Transcriptional Gene Silencing Suppressors for Increased in Planta Expression of a Recombinant Anthrax Receptor Fusion Protein

    PubMed Central

    Arzola, Lucas; Chen, Junxing; Rattanaporn, Kittipong; Maclean, James M.; McDonald, Karen A.

    2011-01-01

    Potential epidemics of infectious diseases and the constant threat of bioterrorism demand rapid, scalable, and cost-efficient manufacturing of therapeutic proteins. Molecular farming of tobacco plants provides an alternative for the recombinant production of therapeutics. We have developed a transient production platform that uses Agrobacterium infiltration of Nicotiana benthamiana plants to express a novel anthrax receptor decoy protein (immunoadhesin), CMG2-Fc. This chimeric fusion protein, designed to protect against the deadly anthrax toxins, is composed of the von Willebrand factor A (VWA) domain of human capillary morphogenesis 2 (CMG2), an effective anthrax toxin receptor, and the Fc region of human immunoglobulin G (IgG). We evaluated, in N. benthamiana intact plants and detached leaves, the expression of CMG2-Fc under the control of the constitutive CaMV 35S promoter, and the co-expression of CMG2-Fc with nine different viral suppressors of post-transcriptional gene silencing (PTGS): p1, p10, p19, p21, p24, p25, p38, 2b, and HCPro. Overall, transient CMG2-Fc expression was higher on intact plants than detached leaves. Maximum expression was observed with p1 co-expression at 3.5 days post-infiltration (DPI), with a level of 0.56 g CMG2-Fc per kg of leaf fresh weight and 1.5% of the total soluble protein, a ten-fold increase in expression when compared to absence of suppression. Co-expression with the p25 PTGS suppressor also significantly increased the CMG2-Fc expression level after just 3.5 DPI. PMID:21954339

  14. Transient co-expression of post-transcriptional gene silencing suppressors for increased in planta expression of a recombinant anthrax receptor fusion protein.

    PubMed

    Arzola, Lucas; Chen, Junxing; Rattanaporn, Kittipong; Maclean, James M; McDonald, Karen A

    2011-01-01

    Potential epidemics of infectious diseases and the constant threat of bioterrorism demand rapid, scalable, and cost-efficient manufacturing of therapeutic proteins. Molecular farming of tobacco plants provides an alternative for the recombinant production of therapeutics. We have developed a transient production platform that uses Agrobacterium infiltration of Nicotiana benthamiana plants to express a novel anthrax receptor decoy protein (immunoadhesin), CMG2-Fc. This chimeric fusion protein, designed to protect against the deadly anthrax toxins, is composed of the von Willebrand factor A (VWA) domain of human capillary morphogenesis 2 (CMG2), an effective anthrax toxin receptor, and the Fc region of human immunoglobulin G (IgG). We evaluated, in N. benthamiana intact plants and detached leaves, the expression of CMG2-Fc under the control of the constitutive CaMV 35S promoter, and the co-expression of CMG2-Fc with nine different viral suppressors of post-transcriptional gene silencing (PTGS): p1, p10, p19, p21, p24, p25, p38, 2b, and HCPro. Overall, transient CMG2-Fc expression was higher on intact plants than detached leaves. Maximum expression was observed with p1 co-expression at 3.5 days post-infiltration (DPI), with a level of 0.56 g CMG2-Fc per kg of leaf fresh weight and 1.5% of the total soluble protein, a ten-fold increase in expression when compared to absence of suppression. Co-expression with the p25 PTGS suppressor also significantly increased the CMG2-Fc expression level after just 3.5 DPI.

  15. GnRH neurons of young and aged female rhesus monkeys co-express GPER but are unaffected by long-term hormone replacement

    PubMed Central

    Naugle, Michelle M.; Gore, Andrea C.

    2014-01-01

    Menopause is caused by changes in the function of the hypothalamic-pituitary-gonadal (HPG) axis that controls reproduction. Hypophysiotropic gonadotropin-releasing hormone (GnRH) neurons in the hypothalamus orchestrate the activity of this axis and are regulated by hormonal feedback loops. The mechanisms by which GnRH responses to the primary regulatory sex-steroid hormone, estradiol (E2) are still poorly understood in the context of menopause. Our goal was to determine whether the G protein-coupled estrogen receptor (GPER) is co-expressed in adult primate GnRH neurons, and whether this changes with aging and/or E2 treatment. We used immunofluorescence double labeling to characterize the co-expression of GPER in GnRH perikarya and terminals in the hypothalamus. Young and aged rhesus macaques were ovariectomized and given long-term (~2 year) hormone treatments (E2, E2 + progesterone, or vehicle) selected to mimic currently prescribed hormone replacement therapies used for the alleviation of menopausal symptoms in women. We found that about half of GnRH perikarya co-expressed GPER, while only about 12% of GnRH processes and terminals in the median eminence (ME) were double labeled. Additionally, many GPER labeled processes were in direct contact with GnRH neurons, often wrapped around the perikarya and processes and in close proximity in the ME. These results extend prior work by showing robust colocalization of GPER in GnRH in a clinically relevant model, and support the possibility that GPER-mediated E2 regulation of GnRH occurs both in the soma and terminals in nonhuman primates. PMID:25428637

  16. Effect of two intermediate electron donors, NADPH and FADH(2), on Spirulina Delta (6)-desaturase co-expressed with two different immediate electron donors, cytochrome b (5) and ferredoxin, in Escherichia coli.

    PubMed

    Kurdrid, Pavinee; Subudhi, Sanjukta; Cheevadhanarak, Supapon; Tanticharoen, Morakot; Hongsthong, Apiradee

    2007-12-01

    When the gene desD encoding Spirulina Delta(6)-desaturase was heterologously expressed in E. coli, the enzyme was expressed without the ability to function. However, when this enzyme was co-expressed with an immediate electron donor, i.e. the cytochrome b (5) domain from Mucor rouxii, the results showed the production of GLA (gamma-linolenic acid), the product of the reaction catalyzed by Delta(6)-desaturase. The results revealed that in E. coli cells, where cytochrome b (5) is absent and ferredoxin, a natural electron donor of Delta(6)-desaturase, is present at a very low level, the cytochrome b (5) domain can complement for the function of ferredoxin in the host cells. In the present study, the Spirulina-ferredoxin gene was cloned and co-expressed with the Delta(6)-desaturase in E. coli. In comparison to the co-expression of cytochrome b ( 5 ) with the Delta(6)-desaturase, the co-expression with ferredoxin did not cause any differences in the GLA level. Moreover, the cultures containing the Delta(6)-desaturase co-expressed with cytochrome b (5) and ferredoxin were exogenously supplied with the intermediate electron donors, NADPH (nicotinamide adenine dinucleotide phosphate, reduced form) and FADH(2) (flavin adenine dinucleotide, reduced form), respectively. The GLA level in these host cells increased drastically, by approximately 50%, compared to the cells without the intermediate electron donors. The data indicated that besides the level of immediate electron donors, the level of intermediate electron donors is also critical for GLA production. Therefore, if the pools of the immediate and intermediate electron donors in the cells are manipulated, the GLA production in the heterologous host will be affected.

  17. Analytical Framework for Identifying and Differentiating Recent Hitchhiking and Severe Bottleneck Effects from Multi-Locus DNA Sequence Data

    DOE PAGES

    Sargsyan, Ori

    2012-05-25

    Hitchhiking and severe bottleneck effects have impact on the dynamics of genetic diversity of a population by inducing homogenization at a single locus and at the genome-wide scale, respectively. As a result, identification and differentiation of the signatures of such events from DNA sequence data at a single locus is challenging. This study develops an analytical framework for identifying and differentiating recent homogenization events at multiple neutral loci in low recombination regions. The dynamics of genetic diversity at a locus after a recent homogenization event is modeled according to the infinite-sites mutation model and the Wright-Fisher model of reproduction withmore » constant population size. In this setting, I derive analytical expressions for the distribution, mean, and variance of the number of polymorphic sites in a random sample of DNA sequences from a locus affected by a recent homogenization event. Based on this framework, three likelihood-ratio based tests are presented for identifying and differentiating recent homogenization events at multiple loci. Lastly, I apply the framework to two data sets. First, I consider human DNA sequences from four non-coding loci on different chromosomes for inferring evolutionary history of modern human populations. The results suggest, in particular, that recent homogenization events at the loci are identifiable when the effective human population size is 50000 or greater in contrast to 10000, and the estimates of the recent homogenization events are agree with the “Out of Africa” hypothesis. Second, I use HIV DNA sequences from HIV-1-infected patients to infer the times of HIV seroconversions. The estimates are contrasted with other estimates derived as the mid-time point between the last HIV-negative and first HIV-positive screening tests. Finally, the results show that significant discrepancies can exist between the estimates.« less

  18. Application of Think Aloud Protocols for Examining and Confirming Sources of Differential Item Functioning Identified by Expert Reviews

    ERIC Educational Resources Information Center

    Ercikan, Kadriye; Arim, Rubab; Law, Danielle; Domene, Jose; Gagnon, France; Lacroix, Serge

    2010-01-01

    This paper demonstrates and discusses the use of think aloud protocols (TAPs) as an approach for examining and confirming sources of differential item functioning (DIF). The TAPs are used to investigate to what extent surface characteristics of the items that are identified by expert reviews as sources of DIF are supported by empirical evidence…

  19. Gene Coexpression Analysis Reveals Complex Metabolism of the Monoterpene Alcohol Linalool in Arabidopsis Flowers[W][OPEN

    PubMed Central

    Ginglinger, Jean-François; Boachon, Benoit; Höfer, René; Paetz, Christian; Köllner, Tobias G.; Miesch, Laurence; Lugan, Raphael; Baltenweck, Raymonde; Mutterer, Jérôme; Ullmann, Pascaline; Beran, Franziska; Claudel, Patricia; Verstappen, Francel; Fischer, Marc J.C.; Karst, Francis; Bouwmeester, Harro; Miesch, Michel; Schneider, Bernd; Gershenzon, Jonathan; Ehlting, Jürgen; Werck-Reichhart, Danièle

    2013-01-01

    The cytochrome P450 family encompasses the largest family of enzymes in plant metabolism, and the functions of many of its members in Arabidopsis thaliana are still unknown. Gene coexpression analysis pointed to two P450s that were coexpressed with two monoterpene synthases in flowers and were thus predicted to be involved in monoterpenoid metabolism. We show that all four selected genes, the two terpene synthases (TPS10 and TPS14) and the two cytochrome P450s (CYP71B31 and CYP76C3), are simultaneously expressed at anthesis, mainly in upper anther filaments and in petals. Upon transient expression in Nicotiana benthamiana, the TPS enzymes colocalize in vesicular structures associated with the plastid surface, whereas the P450 proteins were detected in the endoplasmic reticulum. Whether they were expressed in Saccharomyces cerevisiae or in N. benthamiana, the TPS enzymes formed two different enantiomers of linalool: (−)-(R)-linalool for TPS10 and (+)-(S)-linalool for TPS14. Both P450 enzymes metabolize the two linalool enantiomers to form different but overlapping sets of hydroxylated or epoxidized products. These oxygenated products are not emitted into the floral headspace, but accumulate in floral tissues as further converted or conjugated metabolites. This work reveals complex linalool metabolism in Arabidopsis flowers, the ecological role of which remains to be determined. PMID:24285789

  20. Trigeminal Medullary Dorsal Horn Neurons Activated by Nasal Stimulation Coexpress AMPA, NMDA, and NK1 Receptors

    PubMed Central

    McCulloch, P. F.; DiNovo, K. M.; Westerhaus, D. J.; Vizinas, T. A.; Peevey, J. F.; Lach, M. A.; Czarnocki, P.

    2013-01-01

    Afferent information initiating the cardiorespiratory responses during nasal stimulation projects from the nasal passages to neurons within the trigeminal medullary dorsal horn (MDH) via the anterior ethmoidal nerve (AEN). Central AEN terminals are thought to release glutamate to activate the MDH neurons. This study was designed to determine which neurotransmitter receptors (AMPA, kainate, or NMDA glutamate receptor subtypes or the Substance P receptor NK1) are expressed by these activated MDH neurons. Fos was used as a neuronal marker of activated neurons, and immunohistochemistry combined with epifluorescent microscopy was used to determine which neurotransmitter receptor subunits were coexpressed by activated MDH neurons. Results indicate that, during nasal stimulation with ammonia vapors in urethane-anesthetized Sprague-Dawley rats, activated neurons within the superficial MDH coexpress the AMPA glutamate receptor subunits GluA1 (95.8%) and GluA2/3 (88.2%), the NMDA glutamate receptor subunits GluN1 (89.1%) and GluN2A (41.4%), and NK1 receptors (64.0%). It is therefore likely that during nasal stimulation the central terminals of the AEN release glutamate and substance P that then produces activation of these MDH neurons. The involvement of AMPA and NMDA receptors may mediate fast and slow neurotransmission, respectively, while NK1 receptor involvement may indicate activation of a nociceptive pathway. PMID:24967301

  1. Construction of differential mRNA-lncRNA crosstalk networks based on ceRNA hypothesis uncover key roles of lncRNAs implicated in esophageal squamous cell carcinoma

    PubMed Central

    Li, Yixue

    2016-01-01

    Increasing evidence has indicated that lncRNAs acting as competing endogenous RNAs (ceRNAs) play crucial roles in tumorigenesis, metastasis and diagnosis of cancer. However, the function of lncRNAs as ceRNAs involved in esophageal squamous cell carcinoma (ESCC) is still largely unknown. In this study, clinical implications of two intrinsic subtypes of ESCC were identified based on expression profiles of lncRNA and mRNA. ESCC subtype-specific differential co-expression networks between mRNAs and lncRNAs were constructed to reveal dynamic changes of their crosstalks mediated by miRNAs during tumorigenesis. Several well-known cancer-associated lncRNAs as the hubs of the two networks were firstly proposed in ESCC. Based on the ceRNA mechanism, we illustrated that the“loss” of miR-186-mediated PVT1-mRNA and miR-26b-mediated LINC00240-mRNA crosstalks were related to the two ESCC subtypes respectively. In addition, crosstalks between LINC00152 and EGFR, LINC00240 and LOX gene family were identified, which were associated with the function of “response to wounding” and “extracellular matrix-receptor interaction”. Furthermore, functional cooperation of multiple lncRNAs was discovered in the two differential mRNA-lncRNA crosstalk networks. These together systematically uncovered the roles of lncRNAs as ceRNAs implicated in ESCC. PMID:27966444

  2. Multicolor flow-cytometric analysis of milk allergen-specific T-helper type 2 cells revealed coexpression of interleukin-4 with Foxp3.

    PubMed

    Yamawaki, Kazuo; Inuo, Chisato; Nomura, Takayasu; Tanaka, Kenichi; Nakajima, Yoichi; Kondo, Yasuto; Yoshikawa, Tetsushi; Urisu, Atsuo; Tsuge, Ikuya

    2015-12-01

    Allergen-specific T-helper type 2 (TH2) cells play an important role in the development of allergic inflammation; however, investigations of the properties of allergen-specific T cells have been challenging in humans. Despite clear evidence that forkhead box p3 (Foxp3) is expressed in conventional effector T cells, its function has remained unknown. To characterize allergen-specific TH2 cells in milk allergy, with particular focus on the expression of Foxp3. Twenty-one children with milk allergy and 11 children without milk allergy were studied. Peripheral blood mononuclear cells from subjects were stimulated with milk allergen for 6 hours and analyzed using multicolor flow cytometry to identify CD154(+) allergen-specific T-helper cells. Simultaneously, the expression of intracellular cytokines and Foxp3 was analyzed. The milk allergy group had significantly larger numbers of milk allergen-specific interleukin (IL)-4- and IL-5-producing CD4(+) T cells than the control group. Subjects in the milk allergy group had significantly more CD154(+)CD4(+) IL-10-producing cells and CD154(+)Foxp3(+)CD4(+) cells than those in the control group. In addition, the number of milk allergen-specific CD154(+)Foxp3(+)CD4(+) cells strongly correlated with that of CD154(+)IL4(+)CD4(+) cells. Bcl-2 expression in CD154(+)IL-4(+)Foxp3(+) T-helper cells was significantly lower compared with that in total CD4 cells. Increased numbers of IL-4-producing allergen-specific T-helper cells were found in patients with milk allergy. In addition, Foxp3 was coexpressed with IL-4 in allergen-specific TH2 cells from patients. This coexpression was associated with lower Bcl-2 levels and could contribute to the phenotype and function of TH2 cells. Copyright © 2015 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  3. 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...

  4. Characterization of neuroendocrine differentiation in human benign prostate and prostatic adenocarcinoma.

    PubMed

    Aprikian, A G; Cordon-Cardo, C; Fair, W R; Reuter, V E

    1993-06-15

    This report describes an immunohistopathologic analysis characterizing the incidence, pattern of distribution, and hormonal content of neuroendocrine (NE) cells in human benign prostate and prostatic adenocarcinoma. Formaldehyde-fixed, paraffin-embedded material from 15 benign prostates, 31 primary prostatic adenocarcinomas, 16 metastatic lesions, 21 primary tumors treated with short-course diethylstilbestrol (DES), and 10 specimens from hormone-refractory patients were examined. NE cells were identified using silver histochemistry and a panel of immunohistochemical NE markers (chromogranin-A, serotonin, neuron-specific enolase), and specific peptide hormone antibodies. NE cells were identified in all benign prostates. NE cells were identified in 77% of primary untreated adenocarcinomas with no significant differences with respect to pathologic stage. NE cells were found isolated and dispersed in the tumor, composing the minority of malignant cells. Double-labeling and serial section immunohistochemistry demonstrated the coexpression of prostate-specific antigen (PSA) in NE cells. In addition to serotonin, some tumors expressed multiple hormone immunoreactivities. NE cells were identified in 56% of metastatic deposits, with a similar pattern of distribution. In DES-treated cases, NE cells were found consistently in the adjacent benign epithelium, whereas 52% of tumors contained NE cells. Hormone-refractory tumors contained NE cells in 60% of cases. This analysis demonstrates that a significant proportion of primary and metastatic prostatic adenocarcinomas contain a subpopulation of NE cells, the expression of which does not appear to be suppressed with androgen ablation and does not correlate with pathologic stage. Furthermore, NE cells coexpress PSA, suggesting a common precursor cell of origin. The elaboration of biogenic amines and neuropeptides suggests that NE cells dispersed in prostatic carcinoma may play a paracrine growth-regulatory role.

  5. Pigmentation Is Associated with Stemness Hierarchy of Progenitor Cells Within Cultured Limbal Epithelial Cells.

    PubMed

    Liu, Lei; Nielsen, Frederik Mølgaard; Emmersen, Jeppe; Bath, Chris; Hjortdal, Jesper Østergaard; Riis, Simone; Fink, Trine; Pennisi, Cristian Pablo; Zachar, Vladimir

    2018-05-20

    Ex-vivo cultured human limbal epithelial stem/progenitor cells (hLESCs) are the main source for regenerative therapy of limbal stem cell deficiency (LSCD), which is worldwide one of the major causes of corneal blindness. Despite many stemness-associated markers have been identified within the limbal niche, the phenotype of the earliest hLESCs has not been hitherto identified. We sought to confirm or refute the use of tumor protein p63 (p63) and ATP binding cassette subfamily B member 5 (ABCB5) as surrogate markers for hLESCs early within the limbal differentiation hierarchy. Based on a robust fluorescence-activated cell sorting (FACS) and subsequent RNA isolation protocol, a comprehensive transcriptomic profile was obtained from four subpopulations of cultured hLESCs. The subpopulations were defined by co-expression of two putative stem/progenitor markers, the p63 and ABCB5, and the corneal differentiation marker cytokeratin 3 (CK3). A comparative transcriptomic analysis yielded novel data that indicated association between pigmentation and differentiation, with the p63 positive populations being the most pigmented and immature of the progenitors. In contrast, ABCB5, either alone or in co-expression patterns, identified more committed progenitor cells with less pigmentation. In conclusion, p63 is superior to ABCB5 as a marker for stemness. This article is protected by copyright. All rights reserved. © 2018 AlphaMed Press.

  6. Repurposed drug screen identifies cardiac glycosides as inhibitors of TGF-β-induced cancer-associated fibroblast differentiation.

    PubMed

    Coleman, David T; Gray, Alana L; Stephens, Charles A; Scott, Matthew L; Cardelli, James A

    2016-05-31

    The tumor microenvironment, primarily composed of myofibroblasts, directly influences the progression of solid tumors. Through secretion of growth factors, extracellular matrix deposition, and contractile mechanotransduction, myofibroblasts, or cancer-associated fibroblasts (CAFs), support angiogenesis and cancer cell invasion and metastasis. The differentiation of fibroblasts to CAFs is primarily induced by TGF-β from cancer cells. To discover agents capable of blocking CAF differentiation, we developed a high content immunofluorescence-based assay to screen repurposed chemical libraries utilizing fibronectin expression as an initial CAF marker. Screening of the Prestwick chemical library and NIH Clinical Collection repurposed drug library, totaling over 1700 compounds, identified cardiac glycosides as particularly potent CAF blocking agents. Cardiac glycosides are traditionally used to regulate intracellular calcium by inhibiting the Na+/K+ ATPase to control cardiac contractility. Herein, we report that multiple cardiac glycoside compounds, including digoxin, are able to inhibit TGF-β-induced fibronectin expression at low nanomolar concentrations without undesirable cell toxicity. We found this inhibition to hold true for multiple fibroblast cell lines. Using real-time qPCR, we determined that digoxin prevented induction of multiple CAF markers. Furthermore, we report that digoxin is able to prevent TGF-β-induced fibroblast contraction of extracellular matrix, a major phenotypic consequence of CAF differentiation. Assessing the mechanism of inhibition, we found digoxin reduced SMAD promoter activity downstream of TGF-β, and we provide data that the effect is through inhibition of its known target, the Na+/K+ ATPase. These findings support a critical role for calcium signaling during CAF differentiation and highlight a novel, repurposable modality for cancer therapy.

  7. Arrested neural and advanced mesenchymal differentiation of glioblastoma cells-comparative study with neural progenitors

    PubMed Central

    2009-01-01

    Background Although features of variable differentiation in glioblastoma cell cultures have been reported, a comparative analysis of differentiation properties of normal neural GFAP positive progenitors, and those shown by glioblastoma cells, has not been performed. Methods Following methods were used to compare glioblastoma cells and GFAP+NNP (NHA): exposure to neural differentiation medium, exposure to adipogenic and osteogenic medium, western blot analysis, immunocytochemistry, single cell assay, BrdU incorporation assay. To characterize glioblastoma cells EGFR amplification analysis, LOH/MSI analysis, and P53 nucleotide sequence analysis were performed. Results In vitro differentiation of cancer cells derived from eight glioblastomas was compared with GFAP-positive normal neural progenitors (GFAP+NNP). Prior to exposure to differentiation medium, both types of cells showed similar multilineage phenotype (CD44+/MAP2+/GFAP+/Vimentin+/Beta III-tubulin+/Fibronectin+) and were positive for SOX-2 and Nestin. In contrast to GFAP+NNP, an efficient differentiation arrest was observed in all cell lines isolated from glioblastomas. Nevertheless, a subpopulation of cells isolated from four glioblastomas differentiated after serum-starvation with varying efficiency into derivatives indistinguishable from the neural derivatives of GFAP+NNP. Moreover, the cells derived from a majority of glioblastomas (7 out of 8), as well as GFAP+NNP, showed features of mesenchymal differentiation when exposed to medium with serum. Conclusion Our results showed that stable co-expression of multilineage markers by glioblastoma cells resulted from differentiation arrest. According to our data up to 95% of glioblastoma cells can present in vitro multilineage phenotype. The mesenchymal differentiation of glioblastoma cells is advanced and similar to mesenchymal differentiation of normal neural progenitors GFAP+NNP. PMID:19216795

  8. Interaction specificity and coexpression of rice NPR1 homologs 1 and 3 (NH1 and NH3), TGA transcription factors and Negative Regulator of Resistance (NRR) proteins.

    PubMed

    Chern, Mawsheng; Bai, Wei; Ruan, Deling; Oh, Taeyun; Chen, Xuewei; Ronald, Pamela C

    2014-06-11

    The nonexpressor of pathogenesis-related genes 1, NPR1 (also known as NIM1 and SAI1), is a key regulator of SA-mediated systemic acquired resistance (SAR) in Arabidopsis. In rice, the NPR1 homolog 1 (NH1) interacts with TGA transcriptional regulators and the Negative Regulator of Resistance (NRR) protein to modulate the SAR response. Though five NPR1 homologs (NHs) have been identified in rice, only NH1 and NH3 enhance immunity when overexpressed. To understand why NH1 and NH3, but not NH2, NH4, or NH5, contribute to the rice immune response, we screened TGA transcription factors and NRR-like proteins for interactions specific to NH1 and NH3. We also examined their co-expression patterns using publicly available microarray data. We tested five NHs, four NRR homologs (RHs), and 13 rice TGA proteins for pair-wise protein interactions using yeast two-hybrid (Y2H) and split YFP assays. A survey of 331 inter-family interactions revealed a broad, complex protein interaction network. To investigate preferred interaction partners when all three families of proteins were present, we performed a bridged split YFP assay employing YFPN-fused TGA, YFPC-fused RH, and NH proteins without YFP fusions. We found 64 tertiary interactions mediated by NH family members among the 120 sets we examined. In the yeast two-hybrid assay, each NH protein was capable of interacting with most TGA and RH proteins. In the split YFP assay, NH1 was the most prevalent interactor of TGA and RH proteins, NH3 ranked the second, and NH4 ranked the third. Based on their interaction with TGA proteins, NH proteins can be divided into two subfamilies: NH1, NH2, and NH3 in one family and NH4 and NH5 in the other.In addition to evidence of overlap in interaction partners, co-expression analyses of microarray data suggest a correlation between NH1 and NH3 expression patterns, supporting their common role in rice immunity. However, NH3 is very tightly co-expressed with RH1 and RH2, while NH1 is strongly

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

    PubMed

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

    2015-11-01

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

  10. Co-expression of the Follicle Stimulating Hormone Receptor and Stem Cell Markers: A Novel Approach to Target Ovarian Cancer Stem Cells

    DTIC Science & Technology

    2012-09-01

    ovarian cancer stem cell markers to consider it as a new experimental target for novel nanotechnology approaches capable of destroying ovarian cancer stem...FSHR mRNA after several generations in an amount consistent with stem cell characteristics. Nude mouse experiments to confirm co-expression in vivoare

  11. Novel glioblastoma markers with diagnostic and prognostic value identified through transcriptome analysis.

    PubMed

    Reddy, Sreekanth P; Britto, Ramona; Vinnakota, Katyayni; Aparna, Hebbar; Sreepathi, Hari Kishore; Thota, Balaram; Kumari, Arpana; Shilpa, B M; Vrinda, M; Umesh, Srikantha; Samuel, Cini; Shetty, Mitesh; Tandon, Ashwani; Pandey, Paritosh; Hegde, Sridevi; Hegde, A S; Balasubramaniam, Anandh; Chandramouli, B A; Santosh, Vani; Kondaiah, Paturu; Somasundaram, Kumaravel; Rao, M R Satyanarayana

    2008-05-15

    Current methods of classification of astrocytoma based on histopathologic methods are often subjective and less accurate. Although patients with glioblastoma have grave prognosis, significant variability in patient outcome is observed. Therefore, the aim of this study was to identify glioblastoma diagnostic and prognostic markers through microarray analysis. We carried out transcriptome analysis of 25 diffusely infiltrating astrocytoma samples [WHO grade II--diffuse astrocytoma, grade III--anaplastic astrocytoma, and grade IV--glioblastoma (GBM)] using cDNA microarrays containing 18,981 genes. Several of the markers identified were also validated by real-time reverse transcription quantitative PCR and immunohistochemical analysis on an independent set of tumor samples (n = 100). Survival analysis was carried out for two markers on another independent set of retrospective cases (n = 51). We identified several differentially regulated grade-specific genes. Independent validation by real-time reverse transcription quantitative PCR analysis found growth arrest and DNA-damage-inducible alpha (GADD45alpha) and follistatin-like 1 (FSTL1) to be up-regulated in most GBMs (both primary and secondary), whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 were up-regulated in the majority of primary GBM. Further, identification of the grade-specific expression of GADD45alpha and FSTL1 by immunohistochemical staining reinforced our findings. Analysis of retrospective GBM cases with known survival data revealed that cytoplasmic overexpression of GADD45alpha conferred better survival while the coexpression of FSTL1 with p53 was associated with poor survival. Our study reveals that GADD45alpha and FSTLI are GBM-specific whereas superoxide dismutase 2 and adipocyte enhancer binding protein 1 are primary GBM-specific diagnostic markers. Whereas GADD45alpha overexpression confers a favorable prognosis, FSTL1 overexpression is a hallmark of poor prognosis in GBM

  12. Identification of Crowding Stress Tolerance Co-Expression Networks Involved in Sweet Corn Yield

    PubMed Central

    Choe, Eunsoo; Drnevich, Jenny; Williams, Martin M.

    2016-01-01

    Tolerance to crowding stress has played a crucial role in improving agronomic productivity in field corn; however, commercial sweet corn hybrids vary greatly in crowding stress tolerance. The objectives were to 1) explore transcriptional changes among sweet corn hybrids with differential yield under crowding stress, 2) identify relationships between phenotypic responses and gene expression patterns, and 3) identify groups of genes associated with yield and crowding stress tolerance. Under conditions of crowding stress, three high-yielding and three low-yielding sweet corn hybrids were grouped for transcriptional and phenotypic analyses. Transcriptional analyses identified from 372 to 859 common differentially expressed genes (DEGs) for each hybrid. Large gene expression pattern variation among hybrids and only 26 common DEGs across all hybrid comparisons were identified, suggesting each hybrid has a unique response to crowding stress. Over-represented biological functions of DEGs also differed among hybrids. Strong correlation was observed between: 1) modules with up-regulation in high-yielding hybrids and yield traits, and 2) modules with up-regulation in low-yielding hybrids and plant/ear traits. Modules linked with yield traits may be important crowding stress response mechanisms influencing crop yield. Functional analysis of the modules and common DEGs identified candidate crowding stress tolerant processes in photosynthesis, glycolysis, cell wall, carbohydrate/nitrogen metabolic process, chromatin, and transcription regulation. Moreover, these biological functions were greatly inter-connected, indicating the importance of improving the mechanisms as a network. PMID:26796516

  13. Screening of biomarkers for prediction of response to and prognosis after chemotherapy for breast cancers.

    PubMed

    Bing, Feng; Zhao, Yu

    2016-01-01

    To screen the biomarkers having the ability to predict prognosis after chemotherapy for breast cancers. Three microarray data of breast cancer patients undergoing chemotherapy were collected from Gene Expression Omnibus database. After preprocessing, data in GSE41112 were analyzed using significance analysis of microarrays to screen the differentially expressed genes (DEGs). The DEGs were further analyzed by Differentially Coexpressed Genes and Links to construct a function module, the prognosis efficacy of which was verified by the other two datasets (GSE22226 and GSE58644) using Kaplan-Meier plots. The involved genes in function module were subjected to a univariate Cox regression analysis to confirm whether the expression of each prognostic gene was associated with survival. A total of 511 DEGs between breast cancer patients who received chemotherapy or not were obtained, consisting of 421 upregulated and 90 downregulated genes. Using the Differentially Coexpressed Genes and Links package, 1,244 differentially coexpressed genes (DCGs) were identified, among which 36 DCGs were regulated by the transcription factor complex NFY (NFYA, NFYB, NFYC). These 39 genes constructed a gene module to classify the samples in GSE22226 and GSE58644 into three subtypes and these subtypes exhibited significantly different survival rates. Furthermore, several genes of the 39 DCGs were shown to be significantly associated with good (such as CDC20) and poor (such as ARID4A) prognoses following chemotherapy. Our present study provided a serial of biomarkers for predicting the prognosis of chemotherapy or targets for development of alternative treatment (ie, CDC20 and ARID4A) in breast cancer patients.

  14. Genetic and pharmacological analysis identifies a physiological role for the AHR in epidermal differentiation

    PubMed Central

    van den Bogaard, Ellen; Podolsky, Michael; Smits, Jos; Cui, Xiao; John, Christian; Gowda, Krishne; Desai, Dhimant; Amin, Shantu; Schalkwijk, Joost; Perdew, Gary H.

    2015-01-01

    Stimulation of the aryl hydrocarbon receptor (AHR) by xenobiotics is known to affect epidermal differentiation and skin barrier formation. The physiological role of endogenous AHR signaling in keratinocyte differentiation is not known. We used murine and human skin models to address the hypothesis that AHR activation is required for normal keratinocyte differentiation. Using transcriptome analysis of Ahr-/- and Ahr+/+ murine keratinocytes, we found significant enrichment of differentially expressed genes linked to epidermal differentiation. Primary Ahr-/- keratinocytes showed a significant reduction in terminal differentiation gene and protein expression, similar to Ahr+/+ keratinocytes treated with AHR antagonists GNF351 and CH223191, or the selective AHR modulator (SAhRM), SGA360. In vitro keratinocyte differentiation led to increased AHR levels and subsequent nuclear translocation, followed by induced CYP1A1 gene expression. Monolayer cultured primary human keratinocytes treated with AHR antagonists also showed an impaired terminal differentiation program. Inactivation of AHR activity during human skin equivalent development severely impaired epidermal stratification, terminal differentiation protein expression and stratum corneum formation. As disturbed epidermal differentiation is a main feature of many skin diseases, pharmacological agents targeting AHR signaling or future identification of endogenous keratinocyte-derived AHR ligands should be considered as potential new drugs in dermatology. PMID:25602157

  15. Androgen Receptor Variant AR-V9 Is Coexpressed with AR-V7 in Prostate Cancer Metastases and Predicts Abiraterone Resistance.

    PubMed

    Kohli, Manish; Ho, Yeung; Hillman, David W; Van Etten, Jamie L; Henzler, Christine; Yang, Rendong; Sperger, Jamie M; Li, Yingming; Tseng, Elizabeth; Hon, Ting; Clark, Tyson; Tan, Winston; Carlson, Rachel E; Wang, Liguo; Sicotte, Hugues; Thai, Ho; Jimenez, Rafael; Huang, Haojie; Vedell, Peter T; Eckloff, Bruce W; Quevedo, Jorge F; Pitot, Henry C; Costello, Brian A; Jen, Jin; Wieben, Eric D; Silverstein, Kevin A T; Lang, Joshua M; Wang, Liewei; Dehm, Scott M

    2017-08-15

    Purpose: Androgen receptor (AR) variant AR-V7 is a ligand-independent transcription factor that promotes prostate cancer resistance to AR-targeted therapies. Accordingly, efforts are under way to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC). The purpose of this study was to understand whether other AR variants may be coexpressed with AR-V7 and promote resistance to AR-targeted therapies. Experimental Design: We utilized complementary short- and long-read sequencing of intact AR mRNA isoforms to characterize AR expression in CRPC models. Coexpression of AR-V7 and AR-V9 mRNA in CRPC metastases and circulating tumor cells was assessed by RNA-seq and RT-PCR, respectively. Expression of AR-V9 protein in CRPC models was evaluated with polyclonal antisera. Multivariate analysis was performed to test whether AR variant mRNA expression in metastatic tissues was associated with a 12-week progression-free survival endpoint in a prospective clinical trial of 78 CRPC-stage patients initiating therapy with the androgen synthesis inhibitor, abiraterone acetate. Results: AR-V9 was frequently coexpressed with AR-V7. Both AR variant species were found to share a common 3' terminal cryptic exon, which rendered AR-V9 susceptible to experimental manipulations that were previously thought to target AR-V7 uniquely. AR-V9 promoted ligand-independent growth of prostate cancer cells. High AR-V9 mRNA expression in CRPC metastases was predictive of primary resistance to abiraterone acetate (HR = 4.0; 95% confidence interval, 1.31-12.2; P = 0.02). Conclusions: AR-V9 may be an important component of therapeutic resistance in CRPC. Clin Cancer Res; 23(16); 4704-15. ©2017 AACR . ©2017 American Association for Cancer Research.

  16. Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus.

    PubMed

    Condon, David E; Tran, Phu V; Lien, Yu-Chin; Schug, Jonathan; Georgieff, Michael K; Simmons, Rebecca A; Won, Kyoung-Jae

    2018-02-05

    Identification of differentially methylated regions (DMRs) is the initial step towards the study of DNA methylation-mediated gene regulation. Previous approaches to call DMRs suffer from false prediction, use extreme resources, and/or require library installation and input conversion. We developed a new approach called Defiant to identify DMRs. Employing Weighted Welch Expansion (WWE), Defiant showed superior performance to other predictors in the series of benchmarking tests on artificial and real data. Defiant was subsequently used to investigate DNA methylation changes in iron-deficient rat hippocampus. Defiant identified DMRs close to genes associated with neuronal development and plasticity, which were not identified by its competitor. Importantly, Defiant runs between 5 to 479 times faster than currently available software packages. Also, Defiant accepts 10 different input formats widely used for DNA methylation data. Defiant effectively identifies DMRs for whole-genome bisulfite sequencing (WGBS), reduced-representation bisulfite sequencing (RRBS), Tet-assisted bisulfite sequencing (TAB-seq), and HpaII tiny fragment enrichment by ligation-mediated PCR-tag (HELP) assays.

  17. Differential DNA methylation marks and gene comethylation of COPD in African-Americans with COPD exacerbations.

    PubMed

    Busch, Robert; Qiu, Weiliang; Lasky-Su, Jessica; Morrow, Jarrett; Criner, Gerard; DeMeo, Dawn

    2016-11-05

    Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide. Identifying COPD-associated DNA methylation marks in African-Americans may contribute to our understanding of racial disparities in COPD susceptibility. We determined differentially methylated genes and co-methylation network modules associated with COPD in African-Americans recruited during exacerbations of COPD and smoking controls from the Pennsylvania Study of Chronic Obstructive Pulmonary Exacerbations (PA-SCOPE) cohort. We assessed DNA methylation from whole blood samples in 362 African-American smokers in the PA-SCOPE cohort using the Illumina Infinium HumanMethylation27 BeadChip Array. Final analysis included 19302 CpG probes annotated to the nearest gene transcript after quality control. We tested methylation associations with COPD case-control status using mixed linear models. Weighted gene comethylation networks were constructed using weighted gene coexpression network analysis (WGCNA) and network modules were analyzed for association with COPD. There were five differentially methylated CpG probes significantly associated with COPD among African-Americans at an FDR less than 5 %, and seven additional probes that approached significance at an FDR less than 10 %. The top ranked gene association was MAML1, which has been shown to affect NOTCH-dependent angiogenesis in murine lung. Network modeling yielded the "yellow" and "blue" comethylation modules which were significantly associated with COPD (p-value 4 × 10 -10 and 4 × 10 -9 , respectively). The yellow module was enriched for gene sets related to inflammatory pathways known to be relevant to COPD. The blue module contained the top ranked genes in the concurrent differential methylation analysis (FXYD1/LGI4, gene significance p-value 1.2 × 10 -26 ; MAML1, p-value 2.0 × 10 -26 ; CD72, p-value 2.1 × 10 -25 ; and LPO, p-value 7.2 × 10 -25 ), and was significantly associated with lung

  18. Differential proteomics analysis to identify proteins and pathways associated with male sterility of soybean using iTRAQ-based strategy.

    PubMed

    Li, Jiajia; Ding, Xianlong; Han, Shaohuai; He, Tingting; Zhang, Hao; Yang, Longshu; Yang, Shouping; Gai, Junyi

    2016-04-14

    To further elucidate the molecular mechanism of cytoplasmic male sterility (CMS) in soybean, a differential proteomic analysis was completed between the CMS line NJCMS1A and its maintainer NJCMS1B using iTRAQ-based strategy. As a result, 180 differential abundance proteins (DAPs) were identified, of which, 60 were down-regulated and 120 were up-regulated in NJCMS1A compared with NJCMS1B. Bioinformatic analysis showed that 167 DAPs were annotated in 41 Gene Ontology functional groups, 106 DAPs were classified into 20 clusters of orthologous groups of protein categories, and 128 DAPs were enrichment in 53 KEGG pathways. Fifteen differential level proteins/genes with the same expression pattern were identified in the further conjoint analysis of DAPs and the previously reported differential expression genes. Moreover, multiple reaction monitoring test, qRT-PCR analysis and enzyme activity assay validated that the iTRAQ results were reliable. Based on functional analysis of DAPs, we concluded that male sterility in NJCMS1A might be related to insufficiencies in energy supply, unbalance of protein synthesis and degradation, disruption of flavonoid synthesis, programmed cell death, abnormalities of substance metabolism, etc. These results might facilitate our understanding of the molecular mechanisms behind CMS in soybean. Soybean is an important global crop that provides protein and oil. Heterosis is a significantly potential approach to increase the yield of soybean. Cytoplasmic male sterility (CMS) plays a vital role in the production of hybrid seeds. However, the genetic and molecular mechanisms of male sterility in soybean still need to be further elucidated. In the present paper, a differential proteomic analysis was carried out and the results showed that several key proteins involved in key pathways were associated with male sterility in soybean. This work provides a new insight to understand the genetic and molecular mechanisms underlying CMS in soybean

  19. Increase in DNA vaccine efficacy by virosome delivery and co-expression of a cytolytic protein.

    PubMed

    Gargett, Tessa; Grubor-Bauk, Branka; Miller, Darren; Garrod, Tamsin; Yu, Stanley; Wesselingh, Steve; Suhrbier, Andreas; Gowans, Eric J

    2014-06-01

    The potential of DNA vaccines has not been realised due to suboptimal delivery, poor antigen expression and the lack of localised inflammation, essential for antigen presentation and an effective immune response to the immunogen. Initially, we examined the delivery of a DNA vaccine encoding a model antigen, luciferase (LUC), to the respiratory tract of mice by encapsulation in a virosome. Virosomes that incorporated influenza virus haemagglutinin effectively delivered DNA to cells in the mouse respiratory tract and resulted in antigen expression and systemic and mucosal immune responses to the immunogen after an intranasal (IN) prime/intradermal (ID) boost regimen, whereas a multidose ID regimen only generated systemic immunity. We also examined systemic immune responses to LUC after ID vaccination with a DNA vaccine, which also encoded one of the several cytolytic or toxic proteins. Although the herpes simplex virus thymidine kinase, in the presence of the prodrug, ganciclovir, resulted in cell death, this failed to increase the humoral or cell-mediated immune responses. In contrast, the co-expression of LUC with the rotavirus non-structural protein 4 (NSP4) protein or a mutant form of mouse perforin, proteins which are directly cytolytic, resulted in increased LUC-specific humoral and cell-mediated immunity. On the other hand, co-expression of LUC with diphtheria toxin subunit A or overexpression of perforin or NSP4 resulted in a lower level of immunity. In summary, the efficacy of DNA vaccines can be improved by targeted IN delivery of DNA or by the induction of cell death in vaccine-targeted cells after ID delivery.

  20. Continuous time Bayesian networks identify Prdm1 as a negative regulator of TH17 cell differentiation in humans

    PubMed Central

    Acerbi, Enzo; Viganò, Elena; Poidinger, Michael; Mortellaro, Alessandra; Zelante, Teresa; Stella, Fabio

    2016-01-01

    T helper 17 (TH17) cells represent a pivotal adaptive cell subset involved in multiple immune disorders in mammalian species. Deciphering the molecular interactions regulating TH17 cell differentiation is particularly critical for novel drug target discovery designed to control maladaptive inflammatory conditions. Using continuous time Bayesian networks over a time-course gene expression dataset, we inferred the global regulatory network controlling TH17 differentiation. From the network, we identified the Prdm1 gene encoding the B lymphocyte-induced maturation protein 1 as a crucial negative regulator of human TH17 cell differentiation. The results have been validated by perturbing Prdm1 expression on freshly isolated CD4+ naïve T cells: reduction of Prdm1 expression leads to augmentation of IL-17 release. These data unravel a possible novel target to control TH17 polarization in inflammatory disorders. Furthermore, this study represents the first in vitro validation of continuous time Bayesian networks as gene network reconstruction method and as hypothesis generation tool for wet-lab biological experiments. PMID:26976045

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

    PubMed

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

    2013-10-18

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

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

    PubMed Central

    2013-01-01

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

  3. Enhancement of CD4(+) T cell response and survival via coexpressed OX40/OX40L in Graves' disease.

    PubMed

    Wang, Qin; Shi, Bi-Min; Xie, Fang; Fu, Zhao-Yang; Chen, Yong-Jing; An, Jing-Nan; Ma, Yu; Liu, Cui-Ping; Zhang, Xue-Kun; Zhang, Xue-Guang

    2016-07-15

    OX40/OX40L pathway plays a very important role in the antigen priming T cells and effector T cells. In the present study, we aimed to examine the involvement of OX40/OX40L pathway in the activation of autoreactive T cells in patients with Grave's disease (GD). We found that OX40 and OX40L were constitutively coexpressed on peripheral CD4(+) T cells from GD patients using flow cytometry analysis. The levels of OX40 and OX40L coexpression on CD4(+) T cells were shown to be correlated with TRAbs. Cell proliferation assay showed that blocking OX40/OX40L signal inhibited T cell proliferation and survival, which suggested that OX40/OX40L could enhance CD4(+) T cell proliferation and maintain their long-term survival in GD by self-enhancing loop of T cell activation independent of APCs. Confocal microscopy and coimmunoprecipitation analysis further revealed that OX40 and OX40L formed a functional complex, which may facilitate signal transduction from OX40L to OX40 and contribute to the pathogenesis of GD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

    PubMed

    Oh, Sunghee; Song, Seongho

    2017-01-01

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

  5. Evolution of Daily Gene Co-expression Patterns from Algae to Plants

    PubMed Central

    de los Reyes, Pedro; Romero-Campero, Francisco J.; Ruiz, M. Teresa; Romero, José M.; Valverde, Federico

    2017-01-01

    Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions. PMID:28751903

  6. Transcriptome profiling of equine vitamin E deficient neuroaxonal dystrophy identifies upregulation of liver X receptor target genes

    PubMed Central

    Finno, Carrie J.; Bordbari, Matthew H.; Valberg, Stephanie J.; Lee, David; Herron, Josi; Hines, Kelly; Monsour, Tamer; Scott, Erica; Bannasch, Danika L.; Mickelson, James; Xu, Libin

    2016-01-01

    Specific spontaneous heritable neurodegenerative diseases have been associated with lower serum and cerebrospinal fluid α-tocopherol (α-TOH) concentrations. Equine neuroaxonal dystrophy (eNAD) has similar histologic lesions to human ataxia with vitamin E deficiency caused by mutations in the α-TOH transfer protein gene (TTPA). Mutations in TTPA are not present with eNAD and the molecular basis remains unknown. Given the neuropathologic phenotypic similarity of the conditions, we assessed the molecular basis of eNAD by global transcriptome sequencing of the cervical spinal cord. Differential gene expression analysis identified 157 significantly (FDR<0.05) dysregulated transcripts within the spinal cord of eNAD-affected horses. Statistical enrichment analysis identified significant downregulation of the ionotropic and metabotropic group III glutamate receptor, synaptic vesicle trafficking and cholesterol biosynthesis pathways. Gene co-expression analysis identified one module of upregulated genes significantly associated with the eNAD phenotype that included the liver X receptor (LXR) targets CYP7A1, APOE, PLTP and ABCA1. Validation of CYP7A1 and APOE dysregulation was performed in an independent biologic group and CYP7A1 was found to be additionally upregulated in the medulla oblongata of eNAD horses. Evidence of LXR activation supports a role for modulation of oxysterol-dependent LXR transcription factor activity by tocopherols. We hypothesize that the protective role of α-TOH in eNAD may reside in its ability to prevent oxysterol accumulation and subsequent activation of the LXR in order to decrease lipid peroxidation associated neurodegeneration. PMID:27751910

  7. The directed differentiation of human iPS cells into kidney podocytes.

    PubMed

    Song, Bi; Smink, Alexandra M; Jones, Christina V; Callaghan, Judy M; Firth, Stephen D; Bernard, Claude A; Laslett, Andrew L; Kerr, Peter G; Ricardo, Sharon D

    2012-01-01

    The loss of glomerular podocytes is a key event in the progression of chronic kidney disease resulting in proteinuria and declining function. Podocytes are slow cycling cells that are considered terminally differentiated. Here we provide the first report of the directed differentiation of induced pluripotent stem (iPS) cells to generate kidney cells with podocyte features. The iPS-derived podocytes share a morphological phenotype analogous with cultured human podocytes. Following 10 days of directed differentiation, iPS podocytes had an up-regulated expression of mRNA and protein localization for podocyte markers including synaptopodin, nephrin and Wilm's tumour protein (WT1), combined with a down-regulation of the stem cell marker OCT3/4. In contrast to human podocytes that become quiescent in culture, iPS-derived cells maintain a proliferative capacity suggestive of a more immature phenotype. The transduction of iPS podocytes with fluorescent labeled-talin that were immunostained with podocin showed a cytoplasmic contractile response to angiotensin II (AII). A permeability assay provided functional evidence of albumin uptake in the cytoplasm of iPS podocytes comparable to human podocytes. Moreover, labeled iPS-derived podocytes were found to integrate into reaggregated metanephric kidney explants where they incorporated into developing glomeruli and co-expressed WT1. This study establishes the differentiation of iPS cells to kidney podocytes that will be useful for screening new treatments, understanding podocyte pathogenesis, and offering possibilities for regenerative medicine.

  8. 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

  9. Differential nuclear staining assay for high-throughput screening to identify cytotoxic compounds.

    PubMed

    Lema, Carolina; Varela-Ramirez, Armando; Aguilera, Renato J

    As large quantities of novel synthetic molecules continue to be generated there is a challenge to identify therapeutic agents with cytotoxic activity. Here we introduce a Differential Nuclear Staining (DNS) assay adapted to live-cell imaging for high throughput screening (HTS) that utilizes two fluorescent DNA intercalators, Hoechst 33342 and Propidium iodide (PI). Since Hoechst can readily cross cell membranes to stain DNA of living and dead cells, it was used to label the total number of cells. In contrast, PI only enters cells with compromised plasma membranes, thus selectively labeling dead cells. The DNS assay was successfully validated by utilizing well known cytotoxic agents with fast or slow cytotoxic activities. The assay was found to be suitable for HTS with Z' factors ranging from 0.86 to 0.60 for 96 and 384-well formats, respectively. Furthermore, besides plate-to-plate reproducibility, assay quality performance was evaluated by determining ratios of signal-to-noise and signal-to-background, as well as coefficient of variation, which resulted in adequate values and validated the assay for HTS initiatives. As proof of concept, eighty structurally diverse compounds from a small molecule library were screened in a 96-well plate format using the DNS assay. Using this DNS assay, six hits with cytotoxic properties were identified and all of them were also successfully identified by using the commercially available MTS assay (CellTiter 96® Cell Proliferation Assay). In addition, the DNS and a flow cytometry assay were used to validate the activity of the cytotoxic compounds. The DNS assay was also used to generate dose-response curves and to obtain CC 50 values. The results indicate that the DNS assay is reliable and robust and suitable for primary and secondary screens of compounds with potential cytotoxic activity.

  10. Differential nuclear staining assay for high-throughput screening to identify cytotoxic compounds

    PubMed Central

    LEMA, Carolina; VARELA-RAMIREZ, Armando; AGUILERA, Renato J.

    2016-01-01

    As large quantities of novel synthetic molecules continue to be generated there is a challenge to identify therapeutic agents with cytotoxic activity. Here we introduce a Differential Nuclear Staining (DNS) assay adapted to live-cell imaging for high throughput screening (HTS) that utilizes two fluorescent DNA intercalators, Hoechst 33342 and Propidium iodide (PI). Since Hoechst can readily cross cell membranes to stain DNA of living and dead cells, it was used to label the total number of cells. In contrast, PI only enters cells with compromised plasma membranes, thus selectively labeling dead cells. The DNS assay was successfully validated by utilizing well known cytotoxic agents with fast or slow cytotoxic activities. The assay was found to be suitable for HTS with Z′ factors ranging from 0.86 to 0.60 for 96 and 384-well formats, respectively. Furthermore, besides plate-to-plate reproducibility, assay quality performance was evaluated by determining ratios of signal-to-noise and signal-to-background, as well as coefficient of variation, which resulted in adequate values and validated the assay for HTS initiatives. As proof of concept, eighty structurally diverse compounds from a small molecule library were screened in a 96-well plate format using the DNS assay. Using this DNS assay, six hits with cytotoxic properties were identified and all of them were also successfully identified by using the commercially available MTS assay (CellTiter 96® Cell Proliferation Assay). In addition, the DNS and a flow cytometry assay were used to validate the activity of the cytotoxic compounds. The DNS assay was also used to generate dose-response curves and to obtain CC50 values. The results indicate that the DNS assay is reliable and robust and suitable for primary and secondary screens of compounds with potential cytotoxic activity. PMID:27042697

  11. Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

    PubMed

    Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

    2010-06-01

    Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

  12. Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer.

    PubMed

    Wu, Yu; Davison, Jerry; Qu, Xiaoyu; Morrissey, Colm; Storer, Barry; Brown, Lisha; Vessella, Robert; Nelson, Peter; Fang, Min

    2016-04-02

    To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.

  13. Whole blood gene expression in adolescent chronic fatigue syndrome: an exploratory cross-sectional study suggesting altered B cell differentiation and survival.

    PubMed

    Nguyen, Chinh Bkrong; Alsøe, Lene; Lindvall, Jessica M; Sulheim, Dag; Fagermoen, Even; Winger, Anette; Kaarbø, Mari; Nilsen, Hilde; Wyller, Vegard Bruun

    2017-05-11

    Chronic fatigue syndrome (CFS) is a prevalent and disabling condition affecting adolescents. The pathophysiology is poorly understood, but immune alterations might be an important component. This study compared whole blood gene expression in adolescent CFS patients and healthy controls, and explored associations between gene expression and neuroendocrine markers, immune markers and clinical markers within the CFS group. CFS patients (12-18 years old) were recruited nation-wide to a single referral center as part of the NorCAPITAL project. A broad case definition of CFS was applied, requiring 3 months of unexplained, disabling chronic/relapsing fatigue of new onset, whereas no accompanying symptoms were necessary. Healthy controls having comparable distribution of gender and age were recruited from local schools. Whole blood samples were subjected to RNA sequencing. Immune markers were blood leukocyte counts, plasma cytokines, serum C-reactive protein and immunoglobulins. Neuroendocrine markers encompassed plasma and urine levels of catecholamines and cortisol, as well as heart rate variability indices. Clinical markers consisted of questionnaire scores for symptoms of post-exertional malaise, inflammation, fatigue, depression and trait anxiety, as well as activity recordings. A total of 29 CFS patients and 18 healthy controls were included. We identified 176 genes as differentially expressed in patients compared to controls, adjusting for age and gender factors. Gene set enrichment analyses suggested impairment of B cell differentiation and survival, as well as enhancement of innate antiviral responses and inflammation in the CFS group. A pattern of co-expression could be identified, and this pattern, as well as single gene transcripts, was significantly associated with indices of autonomic nervous activity, plasma cortisol, and blood monocyte and eosinophil counts. Also, an association with symptoms of post-exertional malaise was demonstrated. Adolescent CFS is

  14. Coexpression of the High Molecular Weight Glutenin Subunit 1Ax1 and Puroindoline Improves Dough Mixing Properties in Durum Wheat (Triticum turgidum L. ssp. durum)

    PubMed Central

    Li, Xiaoyan; Xiao, Xin; Sun, Fusheng; Wang, Cheng; Hu, Wei; Feng, Zhijuan; Chang, Junli; Chen, Mingjie; Wang, Yuesheng; Li, Kexiu; Yang, Guangxiao; He, Guangyuan

    2012-01-01

    Wheat end-use quality mainly derives from two interrelated characteristics: the compositions of gluten proteins and grain hardness. The composition of gluten proteins determines dough rheological properties and thus confers the unique viscoelastic property on dough. One group of gluten proteins, high molecular weight glutenin subunits (HMW-GS), plays an important role in dough functional properties. On the other hand, grain hardness, which influences the milling process of flour, is controlled by Puroindoline a (Pina) and Puroindoline b (Pinb) genes. However, little is known about the combined effects of HMW-GS and PINs on dough functional properties. In this study, we crossed a Pina-expressing transgenic line with a 1Ax1-expressing line of durum wheat and screened out lines coexpressing 1Ax1 and Pina or lines expressing either 1Ax1 or Pina. Dough mixing analysis of these lines demonstrated that expression of 1Ax1 improved both dough strength and over-mixing tolerance, while expression of PINA detrimentally affected the dough resistance to extension. In lines coexpressing 1Ax1 and Pina, faster hydration of flour during mixing was observed possibly due to the lower water absorption and damaged starch caused by PINA expression. In addition, expression of 1Ax1 appeared to compensate the detrimental effect of PINA on dough resistance to extension. Consequently, coexpression of 1Ax1 and PINA in durum wheat had combined effects on dough mixing behaviors with a better dough strength and resistance to extension than those from lines expressing either 1Ax1 or Pina. The results in our study suggest that simultaneous modulation of dough strength and grain hardness in durum wheat could significantly improve its breadmaking quality and may not even impair its pastamaking potential. Therefore, coexpression of 1Ax1 and PINA in durum wheat has useful implications for breeding durum wheat with dual functionality (for pasta and bread) and may improve the economic values of durum

  15. Coexpression of the high molecular weight glutenin subunit 1Ax1 and puroindoline improves dough mixing properties in durum wheat (Triticum turgidum L. ssp. durum).

    PubMed

    Li, Yin; Wang, Qiong; Li, Xiaoyan; Xiao, Xin; Sun, Fusheng; Wang, Cheng; Hu, Wei; Feng, Zhijuan; Chang, Junli; Chen, Mingjie; Wang, Yuesheng; Li, Kexiu; Yang, Guangxiao; He, Guangyuan

    2012-01-01

    Wheat end-use quality mainly derives from two interrelated characteristics: the compositions of gluten proteins and grain hardness. The composition of gluten proteins determines dough rheological properties and thus confers the unique viscoelastic property on dough. One group of gluten proteins, high molecular weight glutenin subunits (HMW-GS), plays an important role in dough functional properties. On the other hand, grain hardness, which influences the milling process of flour, is controlled by Puroindoline a (Pina) and Puroindoline b (Pinb) genes. However, little is known about the combined effects of HMW-GS and PINs on dough functional properties. In this study, we crossed a Pina-expressing transgenic line with a 1Ax1-expressing line of durum wheat and screened out lines coexpressing 1Ax1 and Pina or lines expressing either 1Ax1 or Pina. Dough mixing analysis of these lines demonstrated that expression of 1Ax1 improved both dough strength and over-mixing tolerance, while expression of PINA detrimentally affected the dough resistance to extension. In lines coexpressing 1Ax1 and Pina, faster hydration of flour during mixing was observed possibly due to the lower water absorption and damaged starch caused by PINA expression. In addition, expression of 1Ax1 appeared to compensate the detrimental effect of PINA on dough resistance to extension. Consequently, coexpression of 1Ax1 and PINA in durum wheat had combined effects on dough mixing behaviors with a better dough strength and resistance to extension than those from lines expressing either 1Ax1 or Pina. The results in our study suggest that simultaneous modulation of dough strength and grain hardness in durum wheat could significantly improve its breadmaking quality and may not even impair its pastamaking potential. Therefore, coexpression of 1Ax1 and PINA in durum wheat has useful implications for breeding durum wheat with dual functionality (for pasta and bread) and may improve the economic values of durum

  16. Threshold-dependent cooperativity of Pdx1 and Oc1 in pancreatic progenitors establishes competency for endocrine differentiation and β-cell function

    PubMed Central

    Wright, Christopher V.E.; Won, Kyoung-Jae

    2016-01-01

    Summary Pdx1 and Oc1 are co-expressed in multipotent pancreatic progenitors and regulate the pro-endocrine gene Neurog3. Their expression diverges in later organogenesis, with Oc1 absent from hormone+ cells and Pdx1 maintained in mature β cells. In a classical genetic test for cooperative functional interactions, we derived mice with combined Pdx1 and Oc1 heterozygosity. Endocrine development in double-heterozygous pancreata was normal at embryonic day (e)13.5, but defects in specification and differentiation were apparent at e15.5, the height of the second wave of differentiation. Pancreata from double heterozygotes showed alterations in the expression of genes crucial for β-cell development and function, decreased numbers and altered allocation of Neurog3-expressing endocrine progenitors, and defective endocrine differentiation. Defects in islet gene expression and β-cell function persisted in double heterozygous neonates. These results suggest that Oc1 and Pdx1 cooperate prior to their divergence, in pancreatic progenitors, to allow for proper differentiation and functional maturation of β cells. PMID:27292642

  17. Identification of conserved drought stress responsive gene-network across tissues and developmental stages in rice.

    PubMed

    Smita, Shuchi; Katiyar, Amit; Pandey, Dev Mani; Chinnusamy, Viswanathan; Archak, Sunil; Bansal, Kailash Chander

    2013-01-01

    Identification of genes that are coexpressed across various tissues and environmental stresses is biologically interesting, since they may play coordinated role in similar biological processes. Genes with correlated expression patterns can be best identified by using coexpression network analysis of transcriptome data. In the present study, we analyzed the temporal-spatial coordination of gene expression in root, leaf and panicle of rice under drought stress and constructed network using WGCNA and Cytoscape. Total of 2199 differentially expressed genes (DEGs) were identified in at least three or more tissues, wherein 88 genes have coordinated expression profile among all the six tissues under drought stress. These 88 highly coordinated genes were further subjected to module identification in the coexpression network. Based on chief topological properties we identified 18 hub genes such as ABC transporter, ATP-binding protein, dehydrin, protein phosphatase 2C, LTPL153 - Protease inhibitor, phosphatidylethanolaminebinding protein, lactose permease-related, NADP-dependent malic enzyme, etc. Motif enrichment analysis showed the presence of ABRE cis-elements in the promoters of > 62% of the coordinately expressed genes. Our results suggest that drought stress mediated upregulated gene expression was coordinated through an ABA-dependent signaling pathway across tissues, at least for the subset of genes identified in this study, while down regulation appears to be regulated by tissue specific pathways in rice.

  18. Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis

    PubMed Central

    Cañas, Rafael A.; Canales, Javier; Muñoz-Hernández, Carmen; Granados, Jose M.; Ávila, Concepción; García-Martín, María L.; Cánovas, Francisco M.

    2015-01-01

    Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles’ age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers’ adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development. PMID:25873654

  19. Cell-free Co-expression of Functional Membrane Proteins and Apolipoprotein, Forming Soluble Nanolipoprotein Particles*S⃞

    PubMed Central

    Cappuccio, Jenny A.; Blanchette, Craig D.; Sulchek, Todd A.; Arroyo, Erin S.; Kralj, Joel M.; Hinz, Angela K.; Kuhn, Edward A.; Chromy, Brett A.; Segelke, Brent W.; Rothschild, Kenneth J.; Fletcher, Julia E.; Katzen, Federico; Peterson, Todd C.; Kudlicki, Wieslaw A.; Bench, Graham; Hoeprich, Paul D.; Coleman, Matthew A.

    2008-01-01

    Here we demonstrate rapid production of solubilized and functional membrane protein by simultaneous cell-free expression of an apolipoprotein and a membrane protein in the presence of lipids, leading to the self-assembly of membrane protein-containing nanolipoprotein particles (NLPs). NLPs have shown great promise as a biotechnology platform for solubilizing and characterizing membrane proteins. However, current approaches are limited because they require extensive efforts to express, purify, and solubilize the membrane protein prior to insertion into NLPs. By the simple addition of a few constituents to cell-free extracts, we can produce membrane proteins in NLPs with considerably less effort. For this approach an integral membrane protein and an apolipoprotein scaffold are encoded by two DNA plasmids introduced into cell-free extracts along with lipids. For this study reported here we used plasmids encoding the bacteriorhodopsin (bR) membrane apoprotein and scaffold protein Δ1–49 apolipoprotein A-I fragment (Δ49A1). Cell free co-expression of the proteins encoded by these plasmids, in the presence of the cofactor all-trans-retinal and dimyristoylphosphatidylcholine, resulted in production of functional bR as demonstrated by a 5-nm shift in the absorption spectra upon light adaptation and characteristic time-resolved FT infrared difference spectra for the bR → M transition. Importantly the functional bR was solubilized in discoidal bR·NLPs as determined by atomic force microscopy. A survey study of other membrane proteins co-expressed with Δ49A1 scaffold protein also showed significantly increased solubility of all of the membrane proteins, indicating that this approach may provide a general method for expressing membrane proteins enabling further studies. PMID:18603642

  20. Biomarkers identified from serum proteomic analysis for the differential diagnosis of systemic lupus erythematosus.

    PubMed

    Kazemipour, N; Qazizadeh, H; Sepehrimanesh, M; Salimi, S

    2015-05-01

    Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves different organs. Its most important feature is the production of specific autoantibodies against nuclear or cytoplasmic antigens. Proteomic analysis of serum, as one of the most readily available body fluids, can be used as a method for clarifying the pathogenesis of SLE. In this study the serum proteome of 13 patients with SLE was evaluated and compared with seven healthy control participants. A specific kit was used to remove high-abundance proteins. After depletion, the protein expression patterns created by two-dimensional gel electrophoresis (2-DE) and MALDI-TOF/TOF-MS were used to identify disease-associated proteins. We found differential expression of 15 protein spots, including seven up-regulated and eight down-regulated proteins in SLE samples, in comparison with healthy participants. These spots were identified by MALDI-TOF/TOF-MS and classified into three groups include keratins, apolipoproteins and albumin, and individual proteins such as transthyretin, haptoglobin and prothrombin. These findings can help to clarify the pathophysiology and mechanism of SLE. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  1. Function of Hevea brasiliensis NAC1 in dehydration-induced laticifer differentiation and latex biosynthesis.

    PubMed

    Cao, Yuxin; Zhai, Jinling; Wang, Qichao; Yuan, Hongmei; Huang, Xi

    2017-01-01

    HbNAC1 is a transcription factor in rubber plants whose expression is induced by dehydration, leading to latex biosynthesis. Laticifer is a special tissue in Hevea brasiliensis where natural rubber is biosynthesized and accumulated. In young stems of epicormic shoots, the differentiation of secondary laticifers can be induced by wounding, which can be prevented when the wounding site is wrapped. Using this system, differentially expressed genes were screened by suppression subtractive hybridization (SSH) and macroarray analyses. This led to the identification of several dehydration-related genes that could be involved in laticifer differentiation and/or latex biosynthesis, including a NAC transcription factor (termed as HbNAC1). Tissue sections confirmed that local tissue dehydration was a key signal for laticifer differentiation. HbNAC1 was localized at the nucleus and showed strong transcriptional activity in yeast, suggesting that HbNAC1 is a transcription factor. Furthermore, HbNAC1 was found to bind to the cis-element CACG in the promoter region of the gene encoding the small rubber particle protein (SRPP). Transgenic experiments also confirmed that HbNAC1 interacted with the SRPP promoter when co-expressed, and enhanced expression of the reporter gene β-glucuronidase occurred in planta. In addition, overexpression of HbNAC1 in tobacco plants conferred drought tolerance. Together, the data suggest that HbNAC1 might be involved in dehydration-induced laticifer differentiation and latex biosynthesis.

  2. Algorithms for network-based identification of differential regulators from transcriptome data: a systematic evaluation

    PubMed Central

    Hui, YU; Ramkrishna, MITRA; Jing, YANG; YuanYuan, LI; ZhongMing, ZHAO

    2016-01-01

    Identification of differential regulators is critical to understand the dynamics of cellular systems and molecular mechanisms of diseases. Several computational algorithms have recently been developed for this purpose by using transcriptome and network data. However, it remains largely unclear which algorithm performs better under a specific condition. Such knowledge is important for both appropriate application and future enhancement of these algorithms. Here, we systematically evaluated seven main algorithms (TED, TDD, TFactS, RIF1, RIF2, dCSA_t2t, and dCSA_r2t), using both simulated and real datasets. In our simulation evaluation, we artificially inactivated either a single regulator or multiple regulators and examined how well each algorithm detected known gold standard regulators. We found that all these algorithms could effectively discern signals arising from regulatory network differences, indicating the validity of our simulation schema. Among the seven tested algorithms, TED and TFactS were placed first and second when both discrimination accuracy and robustness against data variation were considered. When applied to two independent lung cancer datasets, both TED and TFactS replicated a substantial fraction of their respective differential regulators. Since TED and TFactS rely on two distinct features of transcriptome data, namely differential co-expression and differential expression, both may be applied as mutual references during practical application. PMID:25326829

  3. Knocking down of heat-shock protein 27 directs differentiation of functional glutamatergic neurons from placenta-derived multipotent cells

    PubMed Central

    Cheng, Yu-Che; Huang, Chi-Jung; Lee, Yih-Jing; Tien, Lu-Tai; Ku, Wei-Chi; Chien, Raymond; Lee, Fa-Kung; Chien, Chih-Cheng

    2016-01-01

    This study presents human placenta-derived multipotent cells (PDMCs) as a source from which functional glutamatergic neurons can be derived. We found that the small heat-shock protein 27 (HSP27) was downregulated during the neuronal differentiation process. The in vivo temporal and spatial profiles of HSP27 expression were determined and showed inverted distributions with neuronal proteins during mouse embryonic development. Overexpression of HSP27 in stem cells led to the arrest of neuronal differentiation; however, the knockdown of HSP27 yielded a substantially enhanced ability of PDMCs to differentiate into neurons. These neurons formed synaptic networks and showed positive staining for multiple neuronal markers. Additionally, cellular phenomena including the absence of apoptosis and rare proliferation in HSP27-silenced PDMCs, combined with molecular events such as cleaved caspase-3 and the loss of stemness with cleaved Nanog, indicated that HSP27 is located upstream of neuronal differentiation and constrains that process. Furthermore, the induced neurons showed increasing intracellular calcium concentrations upon glutamate treatment. These differentiated cells co-expressed the N-methyl-D-aspartate receptor, vesicular glutamate transporter, and synaptosomal-associated protein 25 but did not show expression of tyrosine hydroxylase, choline acetyltransferase or glutamate decarboxylase 67. Therefore, we concluded that HSP27-silenced PDMCs differentiated into neurons possessing the characteristics of functional glutamatergic neurons. PMID:27444754

  4. Transcriptional profiling identifies differentially expressed genes in developing turkey skeletal muscle

    PubMed Central

    2011-01-01

    Background Skeletal muscle growth and development from embryo to adult consists of a series of carefully regulated changes in gene expression. Understanding these developmental changes in agriculturally important species is essential to the production of high quality meat products. For example, consumer demand for lean, inexpensive meat products has driven the turkey industry to unprecedented production through intensive genetic selection. However, achievements of increased body weight and muscle mass have been countered by an increased incidence of myopathies and meat quality defects. In a previous study, we developed and validated a turkey skeletal muscle-specific microarray as a tool for functional genomics studies. The goals of the current study were to utilize this microarray to elucidate functional pathways of genes responsible for key events in turkey skeletal muscle development and to compare differences in gene expression between two genetic lines of turkeys. To achieve these goals, skeletal muscle samples were collected at three critical stages in muscle development: 18d embryo (hyperplasia), 1d post-hatch (shift from myoblast-mediated growth to satellite cell-modulated growth by hypertrophy), and 16wk (market age) from two genetic lines: a randombred control line (RBC2) maintained without selection pressure, and a line (F) selected from the RBC2 line for increased 16wk body weight. Array hybridizations were performed in two experiments: Experiment 1 directly compared the developmental stages within genetic line, while Experiment 2 directly compared the two lines within each developmental stage. Results A total of 3474 genes were differentially expressed (false discovery rate; FDR < 0.001) by overall effect of development, while 16 genes were differentially expressed (FDR < 0.10) by overall effect of genetic line. Ingenuity Pathways Analysis was used to group annotated genes into networks, functions, and canonical pathways. The expression of 28 genes

  5. Co-Expression of Monodehydroascorbate Reductase and Dehydroascorbate Reductase from Brassica rapa Effectively Confers Tolerance to Freezing-Induced Oxidative Stress

    PubMed Central

    Shin, Sun-Young; Kim, Myung-Hee; Kim, Yul-Ho; Park, Hyang-Mi; Yoon, Ho-Sung

    2013-01-01

    Plants are exposed to various environmental stresses and have therefore developed antioxidant enzymes and molecules to protect their cellular components against toxicity derived from reactive oxygen species (ROS). Ascorbate is a very important antioxidant molecule in plants, and monodehydroascorbate reductase (MDHAR; EC 1.6.5.4) and dehydroascorbate reductase (DHAR; EC 1.8.5.1) are essential to regeneration of ascorbate for maintenance of ROS scavenging ability. The MDHAR and DHAR genes from Brassica rapa were cloned, transgenic plants overexpressing either BrMDHAR and BrDHAR were established, and then, each transgenic plant was hybridized to examine the effects of co-expression of both genes conferring tolerance to freezing. Transgenic plants co-overexpressing BrMDHAR and BrDHAR showed activated expression of relative antioxidant enzymes, and enhanced levels of glutathione and phenolics under freezing condition. Then, these alteration caused by co-expression led to alleviated redox status and lipid peroxidation and consequently conferred improved tolerance against severe freezing stress compared to transgenic plants overexpressing single gene. The results of this study suggested that although each expression of BrMDHAR or BrDHAR was available to according tolerance to freezing, the simultaneous expression of two genes generated synergistic effects conferring improved tolerance more effectively even severe freezing. PMID:24170089

  6. Screening of biomarkers for prediction of response to and prognosis after chemotherapy for breast cancers

    PubMed Central

    Bing, Feng; Zhao, Yu

    2016-01-01

    Objective To screen the biomarkers having the ability to predict prognosis after chemotherapy for breast cancers. Methods Three microarray data of breast cancer patients undergoing chemotherapy were collected from Gene Expression Omnibus database. After preprocessing, data in GSE41112 were analyzed using significance analysis of microarrays to screen the differentially expressed genes (DEGs). The DEGs were further analyzed by Differentially Coexpressed Genes and Links to construct a function module, the prognosis efficacy of which was verified by the other two datasets (GSE22226 and GSE58644) using Kaplan–Meier plots. The involved genes in function module were subjected to a univariate Cox regression analysis to confirm whether the expression of each prognostic gene was associated with survival. Results A total of 511 DEGs between breast cancer patients who received chemotherapy or not were obtained, consisting of 421 upregulated and 90 downregulated genes. Using the Differentially Coexpressed Genes and Links package, 1,244 differentially coexpressed genes (DCGs) were identified, among which 36 DCGs were regulated by the transcription factor complex NFY (NFYA, NFYB, NFYC). These 39 genes constructed a gene module to classify the samples in GSE22226 and GSE58644 into three subtypes and these subtypes exhibited significantly different survival rates. Furthermore, several genes of the 39 DCGs were shown to be significantly associated with good (such as CDC20) and poor (such as ARID4A) prognoses following chemotherapy. Conclusion Our present study provided a serial of biomarkers for predicting the prognosis of chemotherapy or targets for development of alternative treatment (ie, CDC20 and ARID4A) in breast cancer patients. PMID:27217777

  7. Coexpression of the Follicle Stimulating Hormone Receptor and Stem Cell Markers: A Novel Approach to Target Ovarian Cancer Stem Cells

    DTIC Science & Technology

    2016-03-01

    1 AD_____________ Award Number: W81XWH-11-1-0623 TITLE: Coexpression of the Follicle Stimulating Hormone Receptor and Stem Cell Markers: A...Novel Approach to Target Ovarian Cancer Stem Cells PRINCIPAL INVESTIGATOR: David W. Schomberg, PhD CONTRACTING ORGANIZATION: Duke University...Durham, NC 27705 REPORT DATE: March 2016 TYPE OF REPORT: Final PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick

  8. 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

  9. An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.

    PubMed

    Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

    2015-10-20

    Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we

  10. Proteomic analysis identifies differentially expressed proteins after red propolis treatment in Hep-2 cells.

    PubMed

    Frozza, Caroline Olivieri da Silva; Ribeiro, Tanara da Silva; Gambato, Gabriela; Menti, Caroline; Moura, Sidnei; Pinto, Paulo Marcos; Staats, Charley Christian; Padilha, Francine Ferreira; Begnini, Karine Rech; de Leon, Priscila Marques Moura; Borsuk, Sibele; Savegnago, Lucielli; Dellagostin, Odir; Collares, Tiago; Seixas, Fabiana Kömmling; Henriques, João Antonio Pêgas; Roesch-Ely, Mariana

    2014-01-01

    Here we investigated alterations in the protein profile of Hep-2 treated with red propolis using two-dimensional electrophoresis associated to mass spectrometry and apoptotic rates of cells treated with and without red propolis extracts through TUNEL and Annexin-V assays. A total of 325 spots were manually excised from the two-dimensional gel electrophoresis and 177 proteins were identified using LC-MS-MS. Among all proteins identified that presented differential expression, most were down-regulated in presence of red propolis extract at a concentration of 120 μg/mL (IC50): GRP78, PRDX2, LDHB, VIM and TUBA1A. Only two up-regulated proteins were identified in this study in the non-cytotoxic (6 μg/mL) red propolis treated group: RPLP0 and RAD23B. TUNEL staining assay showed a markedly increase in the mid- to late-stage apoptosis of Hep-2 cells induced by red propolis at concentrations of 60 and 120 μg/mL when compared with non-treated cells. The increase of late apoptosis was confirmed by in situ Annexin-V analysis in which red propolis extract induced late apoptosis in a dose-dependent manner. The differences in tumor cell protein profiles warrant further investigations including isolation of major bioactive compounds of red propolis in different cell lines using proteomics and molecular tests to validate the protein expression here observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling.

    PubMed

    Plaisier, Christopher L; Bare, J Christopher; Baliga, Nitin S

    2011-07-01

    Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3' un-translated region (UTR) sequences to mediate the observed co-regulation. The novelty of our approach is the miRvestigator hidden Markov model (HMM) algorithm which systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database miRBase to an overrepresented sequence motif identified within the 3'-UTR of the query genes. We have made this miRNA discovery tool accessible to the community by integrating our HMM algorithm with a proven algorithm for de novo discovery of miRNA seed sequences and wrapping these algorithms into a user-friendly interface. Additionally, the miRvestigator web server also produces a list of putative miRNA binding sites within 3'-UTRs of the query transcripts to facilitate the design of validation experiments. The miRvestigator is freely available at http://mirvestigator.systemsbiology.net.

  12. Improving methionine and ATP availability by MET6 and SAM2 co-expression combined with sodium citrate feeding enhanced SAM accumulation in Saccharomyces cerevisiae.

    PubMed

    Chen, Hailong; Wang, Zhou; Wang, Zhilai; Dou, Jie; Zhou, Changlin

    2016-04-01

    S-adenosyl-L-methionine (SAM), biosynthesized from methionine and ATP, exhibited diverse pharmaceutical applications. To enhance SAM accumulation in S. cerevisiae CGMCC 2842 (wild type), improvement of methionine and ATP availability through MET6 and SAM2 co-expression combined with sodium citrate feeding was investigated here. Feeding 6 g/L methionine at 12 h into medium was found to increase SAM accumulation by 38 % in wild type strain. Based on this result, MET6, encoding methionine synthase, was overexpressed, which caused a 59 % increase of SAM. To redirect intracellular methionine into SAM, MET6 and SAM2 (encoding methionine adenosyltransferase) were co-expressed to obtain the recombinant strain YGSPM in which the SAM accumulation was 2.34-fold of wild type strain. The data obtained showed that co-expression of MET6 and SAM2 improved intracellular methionine availability and redirected the methionine to SAM biosynthesis. To elevate intracellular ATP levels, 6 g/L sodium citrate, used as an auxiliary energy substrate, was fed into the batch fermentation medium, and an additional 19 % increase of SAM was observed after sodium citrate addition. Meanwhile, it was found that addition of sodium citrate improved the isocitrate dehydrogenase activity which was associated with the intracellular ATP levels. The results demonstrated that addition of sodium citrate improved intracellular ATP levels which promoted conversion of methionine into SAM. This study presented a feasible approach with considerable potential for developing highly SAM-productive strains based on improving methionine and ATP availability.

  13. Neurobiological Signatures of Alcohol Dependence Revealed by Protein Profiling

    PubMed Central

    Gorini, Giorgio; Roberts, Amanda J.; Mayfield, R. Dayne

    2013-01-01

    Alcohol abuse causes dramatic neuroadaptations in the brain, which contribute to tolerance, dependence, and behavioral modifications. Previous proteomic studies in human alcoholics and animal models have identified candidate alcoholism-related proteins. However, recent evidences suggest that alcohol dependence is caused by changes in co-regulation that are invisible to single protein-based analysis. Here, we analyze global proteomics data to integrate differential expression, co-expression networks, and gene annotations to unveil key neurobiological rearrangements associated with the transition to alcohol dependence modeled by a Chronic Intermittent Ethanol (CIE), two-bottle choice (2BC) paradigm. We analyzed cerebral cortices (CTX) and midbrains (MB) from male C57BL/6J mice subjected to a CIE, 2BC paradigm, which induces heavy drinking and represents one of the best available animal models for alcohol dependence and relapse drinking. CIE induced significant changes in protein levels in dependent mice compared with their non-dependent controls. Multiple protein isoforms showed region-specific differential regulation as a result of post-translational modifications. Our integrative analysis identified modules of co-expressed proteins that were highly correlated with CIE treatment. We found that modules most related to the effects of CIE treatment coordinate molecular imbalances in endocytic- and energy-related pathways, with specific proteins involved, such as dynamin-1. The qRT-PCR experiments validated both differential and co-expression analyses, and the correspondence among our data and previous genomic and proteomic studies in humans and rodents substantiates our findings. The changes identified above may play a key role in the escalation of ethanol consumption associated with dependence. Our approach to alcohol addiction will advance knowledge of brain remodeling mechanisms and adaptive changes in response to drug abuse, contribute to understanding of

  14. Differential expression of lncRNAs during the HIV replication cycle: an underestimated layer in the HIV-host interplay.

    PubMed

    Trypsteen, Wim; Mohammadi, Pejman; Van Hecke, Clarissa; Mestdagh, Pieter; Lefever, Steve; Saeys, Yvan; De Bleser, Pieter; Vandesompele, Jo; Ciuffi, Angela; Vandekerckhove, Linos; De Spiegelaere, Ward

    2016-10-26

    Studying the effects of HIV infection on the host transcriptome has typically focused on protein-coding genes. However, recent advances in the field of RNA sequencing revealed that long non-coding RNAs (lncRNAs) add an extensive additional layer to the cell's molecular network. Here, we performed transcriptome profiling throughout a primary HIV infection in vitro to investigate lncRNA expression at the different HIV replication cycle processes (reverse transcription, integration and particle production). Subsequently, guilt-by-association, transcription factor and co-expression analysis were performed to infer biological roles for the lncRNAs identified in the HIV-host interplay. Many lncRNAs were suggested to play a role in mechanisms relying on proteasomal and ubiquitination pathways, apoptosis, DNA damage responses and cell cycle regulation. Through transcription factor binding analysis, we found that lncRNAs display a distinct transcriptional regulation profile as compared to protein coding mRNAs, suggesting that mRNAs and lncRNAs are independently modulated. In addition, we identified five differentially expressed lncRNA-mRNA pairs with mRNA involvement in HIV pathogenesis with possible cis regulatory lncRNAs that control nearby mRNA expression and function. Altogether, the present study demonstrates that lncRNAs add a new dimension to the HIV-host interplay and should be further investigated as they may represent targets for controlling HIV replication.

  15. Gonad Transcriptome Analysis of the Pacific Oyster Crassostrea gigas Identifies Potential Genes Regulating the Sex Determination and Differentiation Process.

    PubMed

    Yue, Chenyang; Li, Qi; Yu, Hong

    2018-04-01

    The Pacific oyster Crassostrea gigas is a commercially important bivalve in aquaculture worldwide. C. gigas has a fascinating sexual reproduction system consisting of dioecism, sex change, and occasional hermaphroditism, while knowledge of the molecular mechanisms of sex determination and differentiation is still limited. In this study, the transcriptomes of male and female gonads at different gametogenesis stages were characterized by RNA-seq. Hierarchical clustering based on genes differentially expressed revealed that 1269 genes were expressed specifically in female gonads and 817 genes were expressed increasingly over the course of spermatogenesis. Besides, we identified two and one gene modules related to female and male gonad development, respectively, using weighted gene correlation network analysis (WGCNA). Interestingly, GO and KEGG enrichment analysis showed that neurotransmitter-related terms were significantly enriched in genes related to ovary development, suggesting that the neurotransmitters were likely to regulate female sex differentiation. In addition, two hub genes related to testis development, lncRNA LOC105321313 and Cg-Sh3kbp1, and one hub gene related to ovary development, Cg-Malrd1-like, were firstly investigated. This study points out the role of neurotransmitter and non-coding RNA regulation during gonad development and produces lists of novel relevant candidate genes for further studies. All of these provided valuable information to understand the molecular mechanisms of C. gigas sex determination and differentiation.

  16. Severe Malaria Infections Impair Germinal Center Responses by Inhibiting T Follicular Helper Cell Differentiation.

    PubMed

    Ryg-Cornejo, Victoria; Ioannidis, Lisa Julia; Ly, Ann; Chiu, Chris Yu; Tellier, Julie; Hill, Danika Lea; Preston, Simon Peter; Pellegrini, Marc; Yu, Di; Nutt, Stephen Laurence; Kallies, Axel; Hansen, Diana Silvia

    2016-01-05

    Naturally acquired immunity to malaria develops only after years of repeated exposure to Plasmodium parasites. Despite the key role antibodies play in protection, the cellular processes underlying the slow acquisition of immunity remain unknown. Using mouse models, we show that severe malaria infection inhibits the establishment of germinal centers (GCs) in the spleen. We demonstrate that infection induces high frequencies of T follicular helper (Tfh) cell precursors but results in impaired Tfh cell differentiation. Despite high expression of Bcl-6 and IL-21, precursor Tfh cells induced during infection displayed low levels of PD-1 and CXCR5 and co-expressed Th1-associated molecules such as T-bet and CXCR3. Blockade of the inflammatory cytokines TNF and IFN-γ or T-bet deletion restored Tfh cell differentiation and GC responses to infection. Thus, this study demonstrates that the same pro-inflammatory mediators that drive severe malaria pathology have detrimental effects on the induction of protective B cell responses. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Properties of human blood monocytes. I. CD91 expression and log orthogonal light scatter provide a robust method to identify monocytes that is more accurate than CD14 expression.

    PubMed

    Hudig, Dorothy; Hunter, Kenneth W; Diamond, W John; Redelman, Doug

    2014-03-01

    This study was designed to improve identification of human blood monocytes by using antibodies to molecules that occur consistently on all stages of monocyte development and differentiation. We examined blood samples from 200 healthy adults without clinically diagnosed immunological abnormalities by flow cytometry (FCM) with multiple combinations of antibodies and with a hematology analyzer (Beckman LH750). CD91 (α2 -macroglobulin receptor) was expressed only by monocytes and to a consistent level among subjects [mean median fluorescence intensity (MFI) = 16.2 ± 3.2]. Notably, only 85.7 ± 5.82% of the CD91(+) monocytes expressed high levels of the classical monocyte marker CD14, with some CD91(+) CD16(+) cells having negligible CD14, indicating that substantial FCM under-counts will occur when monocytes are identified by high CD14. CD33 (receptor for sialyl conjugates) was co-expressed with CD91 on monocytes but CD33 expression varied by nearly ten-fold among subjects (mean MFI = 17.4 ± 7.7). In comparison to FCM analyses, the hematology analyzer systematically over-counted monocytes and eosinophils while lymphocyte and neutrophil differential values generally agreed with FCM methods. CD91 is a better marker to identify monocytes than CD14 or CD33. Furthermore, FCM (with anti-CD91) identifies monocytes better than a currently used clinical CBC instrument. Use of anti-CD91 together with anti-CD14 and anti-CD16 supports the identification of the diagnostically significant monocyte populations with variable expression of CD14 and CD16. Copyright © 2013 Clinical Cytometry Society.

  18. Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

    PubMed Central

    Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

    2015-01-01

    The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

  19. Identifying the Viral Genes Encoding Envelope Glycoproteins for Differentiation of Cyprinid herpesvirus 3 Isolates

    PubMed Central

    Han, Jee Eun; Kim, Ji Hyung; Renault, Tristan; Choresca, Casiano; Shin, Sang Phil; Jun, Jin Woo; Park, Se Chang

    2013-01-01

    Cyprinid herpes virus 3 (CyHV-3) diseases have been reported around the world and are associated with high mortalities of koi (Cyprinus carpio). Although little work has been conducted on the molecular analysis of this virus, glycoprotein genes identified in the present study seem to be valuable targets for genetic comparison of this virus. Three envelope glycoprotein genes (ORF25, 65 and 116) of the CyHV-3 isolates from the USA, Israel, Japan and Korea were compared, and interestingly, sequence insertions or deletions were observed in these target regions. In addition, polymorphisms were presented in microsatellite zones from two glycoprotein genes (ORF65 and 116). In phylogenetic tree analysis, the Korean isolate was remarkably distinguished from USA, Israel, Japan isolates. These findings may be suitable for many applications including isolates differentiation and phylogeny studies. PMID:23435236

  20. Identifying the viral genes encoding envelope glycoproteins for differentiation of Cyprinid herpesvirus 3 isolates.

    PubMed

    Han, Jee Eun; Kim, Ji Hyung; Renault, Tristan; Choresca, Casiano; Shin, Sang Phil; Jun, Jin Woo; Park, Se Chang

    2013-01-31

    Cyprinid herpes virus 3 (CyHV-3) diseases have been reported around the world and are associated with high mortalities of koi (Cyprinus carpio). Although little work has been conducted on the molecular analysis of this virus, glycoprotein genes identified in the present study seem to be valuable targets for genetic comparison of this virus. Three envelope glycoprotein genes (ORF25, 65 and 116) of the CyHV-3 isolates from the USA, Israel, Japan and Korea were compared, and interestingly, sequence insertions or deletions were observed in these target regions. In addition, polymorphisms were presented in microsatellite zones from two glycoprotein genes (ORF65 and 116). In phylogenetic tree analysis, the Korean isolate was remarkably distinguished from USA, Israel, Japan isolates. These findings may be suitable for many applications including isolates differentiation and phylogeny studies.

  1. Mouse Mix gene is activated early during differentiation of ES and F9 stem cells and induces endoderm in frog embryos.

    PubMed

    Mohn, Deanna; Chen, Siming W; Dias, Dora Campos; Weinstein, Daniel C; Dyer, Michael A; Sahr, Kenneth; Ducker, Charles E; Zahradka, Elizabeth; Keller, Gordon; Zaret, Kenneth S; Gudas, Lorraine J; Baron, Margaret H

    2003-03-01

    In frog and zebrafish, the Mix/Bix family of paired type homeodomain proteins play key roles in specification and differentiation of mesendoderm. However, in mouse, only a single Mix gene (mMix) has been identified to date and its function is unknown. We have analyzed the expression of mouse Mix RNA and protein in embryos, embryoid bodies formed from embryonic stem cells and F9 teratocarcinoma cells, as well as several differentiated cell types. Expression in embryoid bodies in culture mirrors that in embryos, where Mix is transcribed transiently in primitive (visceral) endoderm (VE) and in nascent mesoderm. In F9 cells induced by retinoic acid to differentiate to VE, mMix is coordinately expressed with three other endodermal transcription factors, well before AFP, and its protein product is localized to the nucleus. In a subpopulation of nascent mesodermal cells from embryonic stem cell embryoid bodies, mMix is coexpressed with Brachyury. Intriguingly, mMix mRNA is detected in a population (T+Flk1+) of cells which may contain hemangioblasts, before the onset of hematopoiesis and activation of hematopoietic markers. In vitro and in vivo, mMix expression in nascent mesoderm is rapidly down-regulated and becomes undetectable in differentiated cell types. In the region of the developing gut, mMix expression is confined to the mesoderm of mid- and hindgut but is absent from definitive endoderm. Injection of mouse mMix RNA into early frog embryos results in axial truncation of developing tadpoles and, in animal cap assays, mMix alone is sufficient to activate expression of several endodermal (but not mesodermal) markers. Although these observations do not exclude a possible cell-autonomous function for mMix in mesendodermal progenitor cells, they do suggest an additional, non-cell autonomous role in nascent mesoderm in the formation and/or patterning of adjacent definitive endoderm. Copyright 2003 Wiley-Liss, Inc.

  2. RNA-seq reveals differentially expressed genes of rice (Oryza sativa) spikelet in response to temperature interacting with nitrogen at meiosis stage.

    PubMed

    Yang, Jun; Chen, Xiaorong; Zhu, Changlan; Peng, Xiaosong; He, Xiaopeng; Fu, Junru; Ouyang, Linjuan; Bian, Jianmin; Hu, Lifang; Sun, Xiaotang; Xu, Jie; He, Haohua

    2015-11-17

    Rice (Oryza sativa) is one of the most important cereal crops, providing food for more than half of the world's population. However, grain yields are challenged by various abiotic stresses such as drought, fertilizer, heat, and their interaction. Rice at reproductive stage is much more sensitive to environmental temperatures, and little is known about molecular mechanisms of rice spikelet in response to high temperature interacting with nitrogen (N). Here we reported the transcriptional profiling analysis of rice spikelet at meiosis stage using RNA sequencing (RNA-seq) as an attempt to gain insights into molecular events associated with temperature and nitrogen. This study received four treatments: 1) NN: normal nitrogen level (165 kg ha(-1)) with natural temperature (30 °C); 2) HH: high nitrogen level (330 kg ha(-1)) with high temperature (37 °C); 3) NH: normal nitrogen level and high temperature; and 4) HN: high nitrogen level and natural temperature, respectively. The de novo assembly generated 52,553,536 clean reads aligned with 72,667 unigenes. About 10 M reads were identified from each treatment. In these differentially expressed genes (DEGs), we found 151 and 323 temperature-responsive DEGs in NN-vs-NH and HN-vs-HH, and 114 DEGs were co-expressed. Meanwhile, 203 and 144 nitrogen-responsive DEGs were focused in NN-vs-HN and NH-vs-HH, and 111 DEGs were co-expressed. The temperature-responsive genes were principally associated with calcium-dependent protein, cytochrome, flavonoid, heat shock protein, peroxidase, ubiquitin, and transcription factor while the nitrogen-responsive genes were mainly involved in glutamine synthetase, transcription factor, anthocyanin, amino acid transporter, leucine zipper protein, and hormone. It is noted that, rice spikelet fertility was significantly decreased under high temperature, but it was more reduced under higher nitrogen. Accordingly, numerous spikelet genes involved in pollen development, pollen tube growth, pollen

  3. Identifying group-sensitive physical activities: a differential item functioning analysis of NHANES data.

    PubMed

    Gao, Yong; Zhu, Weimo

    2011-05-01

    The purpose of this study was to identify subgroup-sensitive physical activities (PA) using differential item functioning (DIF) analysis. A sub-unweighted sample of 1857 (men=923 and women=934) from the 2003-2004 National Health and Nutrition Examination Survey PA questionnaire data was used for the analyses. Using the Mantel-Haenszel, the simultaneous item bias test, and the ANOVA DIF methods, 33 specific leisure-time moderate and/or vigorous PA (MVPA) items were analyzed for DIF across race/ethnicity, gender, education, income, and age groups. Many leisure-time MVPA items were identified as large DIF items. When participating in the same amount of leisure-time MVPA, non-Hispanic blacks were more likely to participate in basketball and dance activities than non-Hispanic whites (NHW); NHW were more likely to participated in golf and hiking than non-Hispanic blacks; Hispanics were more likely to participate in dancing, hiking, and soccer than NHW, whereas NHW were more likely to engage in bicycling, golf, swimming, and walking than Hispanics; women were more likely to participate in aerobics, dancing, stretching, and walking than men, whereas men were more likely to engage in basketball, fishing, golf, running, soccer, weightlifting, and hunting than women; educated persons were more likely to participate in jogging and treadmill exercise than less educated persons; persons with higher incomes were more likely to engage in golf than those with lower incomes; and adults (20-59 yr) were more likely to participate in basketball, dancing, jogging, running, and weightlifting than older adults (60+ yr), whereas older adults were more likely to participate in walking and golf than younger adults. DIF methods are able to identify subgroup-sensitive PA and thus provide useful information to help design group-sensitive, targeted interventions for disadvantaged PA subgroups. © 2011 by the American College of Sports Medicine

  4. Deferential Differentiation: What Types of Differentiation Do Students Want?

    ERIC Educational Resources Information Center

    Kanevsky, Lannie

    2011-01-01

    Deferential differentiation occurs when the curriculum modification process defers to students' preferred ways of learning rather than relying on teachers' judgments. The preferences of 416 students identified as gifted (grades 3-8) for features of differentiated curriculum recommended for gifted students were compared with those of 230 students…

  5. Identifying Differential Item Functioning in Multi-Stage Computer Adaptive Testing

    ERIC Educational Resources Information Center

    Gierl, Mark J.; Lai, Hollis; Li, Johnson

    2013-01-01

    The purpose of this study is to evaluate the performance of CATSIB (Computer Adaptive Testing-Simultaneous Item Bias Test) for detecting differential item functioning (DIF) when items in the matching and studied subtest are administered adaptively in the context of a realistic multi-stage adaptive test (MST). MST was simulated using a 4-item…

  6. Gene networks associated with conditional fear in mice identified using a systems genetics approach

    PubMed Central

    2011-01-01

    Background Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. Results A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes. Conclusion Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior. PMID:21410935

  7. The biosynthetic gene cluster for the cyanogenic glucoside dhurrin in Sorghum bicolor contains its co-expressed vacuolar MATE transporter

    PubMed Central

    Darbani, Behrooz; Motawia, Mohammed Saddik; Olsen, Carl Erik; Nour-Eldin, Hussam H.; Møller, Birger Lindberg; Rook, Fred

    2016-01-01

    Genomic gene clusters for the biosynthesis of chemical defence compounds are increasingly identified in plant genomes. We previously reported the independent evolution of biosynthetic gene clusters for cyanogenic glucoside biosynthesis in three plant lineages. Here we report that the gene cluster for the cyanogenic glucoside dhurrin in Sorghum bicolor additionally contains a gene, SbMATE2, encoding a transporter of the multidrug and toxic compound extrusion (MATE) family, which is co-expressed with the biosynthetic genes. The predicted localisation of SbMATE2 to the vacuolar membrane was demonstrated experimentally by transient expression of a SbMATE2-YFP fusion protein and confocal microscopy. Transport studies in Xenopus laevis oocytes demonstrate that SbMATE2 is able to transport dhurrin. In addition, SbMATE2 was able to transport non-endogenous cyanogenic glucosides, but not the anthocyanin cyanidin 3-O-glucoside or the glucosinolate indol-3-yl-methyl glucosinolate. The genomic co-localisation of a transporter gene with the biosynthetic genes producing the transported compound is discussed in relation to the role self-toxicity of chemical defence compounds may play in the formation of gene clusters. PMID:27841372

  8. Co-expression, purification and characterization of the lipase and foldase of Burkholderia contaminans LTEB11.

    PubMed

    Alnoch, Robson Carlos; Stefanello, Adriano Alves; Paula Martini, Viviane; Richter, Jeferson Luiz; Mateo, Cesar; Souza, Emanuel Maltempi de; Mitchell, David Alexander; Muller-Santos, Marcelo; Krieger, Nadia

    2018-05-30

    Genes encoding lipase LipBC (lipA) and foldase LifBC (lipB) were identified in the genome of Burkholderia contaminans LTEB11. Analysis of the predicted amino acid sequence of lipA showed its high identity with lipases from Pseudomonas luteola (91%), Burkholderia cepacia (96%) and Burkholderia lata (97%), and classified LipBC lipase in the lipase subfamily I.2. The genes lipA and lipB were amplified and cloned into expression vectors pET28a(+) and pT7-7, respectively. His-tagged LipBC and native LifBC were co-expressed in Escherichia coli and purified. LipBC and LifBC have molecular weights of 35.9 kDa and 37 kDa, respectively, and remain complexed after purification. The Lip-LifBC complex was active and stable over a wide range of pH values (6.5-10) and temperatures (25-45 °C), with the highest specific activity (1426 U mg -1 ) being against tributyrin. The Lip-LifBC complex immobilized on Sepabeads was able to catalyze the synthesis of ethyl-oleate in n‑hexane with an activity of 4 U g -1 , maintaining high conversion (>80%) over 5 reaction cycles of 6 h at 45 °C. The results obtained in this work provide a basis for the development of applications of recombinant LipBC in biocatalysis. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. 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.

  10. lncRNA co-expression network model for the prognostic analysis of acute myeloid leukemia

    PubMed Central

    Pan, Jia-Qi; Zhang, Yan-Qing; Wang, Jing-Hua; Xu, Ping; Wang, Wei

    2017-01-01

    Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy with great variability of prognostic behaviors. Previous studies have reported that long non-coding RNAs (lncRNAs) play an important role in AML and may thus be used as potential prognostic biomarkers. However, thus use of lncRNAs as prognostic biomarkers in AML and their detailed mechanisms of action in this disease have not yet been well characterized. For this purpose, in the present study, the expression levels of lncRNAs and mRNAs were calculated using the RNA-seq V2 data for AML, following which a lncRNA-lncRNA co-expression network (LLCN) was constructed. This revealed a total of 8 AML prognosis-related lncRNA modules were identified, which displayed a significant correlation with patient survival (p≤0.05). Subsequently, a prognosis-related lncRNA module pathway network was constructed to interpret the functional mechanism of the prognostic modules in AML. The results indicated that these prognostic modules were involved in the AML pathway, chemokine signaling pathway and WNT signaling pathway, all of which play important roles in AML. Furthermore, the investigation of lncRNAs in these prognostic modules suggested that an lncRNA (ZNF571-AS1) may be involved in AML via the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling pathway by regulating KIT and STAT5. The results of the present study not only provide potential lncRNA modules as prognostic biomarkers, but also provide further insight into the molecular mechanisms of action of lncRNAs. PMID:28204819

  11. Coexpression patterns of vimentin and glial filament protein with cytokeratins in the normal, hyperplastic, and neoplastic breast.

    PubMed Central

    Gould, V. E.; Koukoulis, G. K.; Jansson, D. S.; Nagle, R. B.; Franke, W. W.; Moll, R.

    1990-01-01

    The authors studied by immunohistochemistry the intermediate filament (IF) protein profile of 66 frozen samples of breast tissue, including normal parenchyma, all variants of fibrocystic disease (FCD), fibroadenomas, cystosarcoma phylloides, and ductal and lobular carcinomas. Monoclonal antibodies (MAbs) to cytokeratins included MAb KA 1, which binds to polypeptide 5 in a complex with polypeptide 14 and recognizes preferentially myoepithelial cells; MAb KA4, which binds to polypeptides 14, 15, 16 and 19; individual MAbs to polypeptides 7, 13, and 16, 17, 18, and 19, and the MAb mixture AE1/AE3. The authors also applied three MAbs to vimentin (Vim), and three MAbs to glial filament protein (GFP). Selected samples were studied by double-label immunofluorescence microscopy and by staining sequential sections with some of the said MAbs, an MAb to alpha-smooth muscle actin, and well-characterized polyclonal antibodies for the possible coexpression of diverse types of cytoskeletal proteins. Gel electrophoresis and immunoblot analysis also were performed. All samples reacted for cytokeratins with MAbs AE1/AE3, although the reaction did not involve all cells. Monoclonal antibody KA4 stained preferentially the luminal-secretory cells in the normal breast and in FCD, whereas it stained the vast majority of cells in all carcinomas. Monoclonal antibody KA1 stained preferentially the basal-myoepithelial cells of the normal breast and FCD while staining tumor cell subpopulations in 4 of 31 carcinomas. Vimentin-positive cells were found in 8 of 12 normal breasts and in 12 of 20 FCD; in most cases, Vim-reactive cells appeared to be myoepithelial, but occasional luminal cells were also stained. Variable subpopulations of Vim-positive cells were noted in 9 of 20 ductal and in 1 of 7 lobular carcinomas. Glial filament protein-reactive cells were found in normal breast lobules and ducts and in 15 of 20 cases of FCD; with rare exceptions, GFP-reactivity was restricted to basally

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

    PubMed Central

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

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

  13. Identifying Hydrated Salts Using Simultaneous Thermogravimetric Analysis and Differential Scanning Calorimetry

    ERIC Educational Resources Information Center

    Harris, Jerry D.; Rusch, Aaron W.

    2013-01-01

    simultaneous thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) to characterize colorless, hydrated salts with anhydrous melting points less than 1100 degrees C. The experiment could be used to supplement the lecture discussing gravimetric techniques. It is…

  14. Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

    NASA Technical Reports Server (NTRS)

    Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.

    2003-01-01

    Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

  15. Comparative genomic analysis of Helicobacter pylori from Malaysia identifies three distinct lineages suggestive of differential evolution

    PubMed Central

    Kumar, Narender; Mariappan, Vanitha; Baddam, Ramani; Lankapalli, Aditya K.; Shaik, Sabiha; Goh, Khean-Lee; Loke, Mun Fai; Perkins, Tim; Benghezal, Mohammed; Hasnain, Seyed E.; Vadivelu, Jamuna; Marshall, Barry J.; Ahmed, Niyaz

    2015-01-01

    The discordant prevalence of Helicobacter pylori and its related diseases, for a long time, fostered certain enigmatic situations observed in the countries of the southern world. Variation in H. pylori infection rates and disease outcomes among different populations in multi-ethnic Malaysia provides a unique opportunity to understand dynamics of host–pathogen interaction and genome evolution. In this study, we extensively analyzed and compared genomes of 27 Malaysian H. pylori isolates and identified three major phylogeographic lineages: hspEastAsia, hpEurope and hpSouthIndia. The analysis of the virulence genes within the core genome, however, revealed a comparable pathogenic potential of the strains. In addition, we identified four genes limited to strains of East-Asian lineage. Our analyses identified a few strain-specific genes encoding restriction modification systems and outlined 311 core genes possibly under differential evolutionary constraints, among the strains representing different ethnic groups. The cagA and vacA genes also showed variations in accordance with the host genetic background of the strains. Moreover, restriction modification genes were found to be significantly enriched in East-Asian strains. An understanding of these variations in the genome content would provide significant insights into various adaptive and host modulation strategies harnessed by H. pylori to effectively persist in a host-specific manner. PMID:25452339

  16. Coexpression network analysis of the genes regulated by two types of resistance responses to powdery mildew in wheat

    PubMed Central

    Zhang, Juncheng; Zheng, Hongyuan; Li, Yiwen; Li, Hongjie; Liu, Xin; Qin, Huanju; Dong, Lingli; Wang, Daowen

    2016-01-01

    Powdery mildew disease caused by Blumeria graminis f. sp. tritici (Bgt) inflicts severe economic losses in wheat crops. A systematic understanding of the molecular mechanisms involved in wheat resistance to Bgt is essential for effectively controlling the disease. Here, using the diploid wheat Triticum urartu as a host, the genes regulated by immune (IM) and hypersensitive reaction (HR) resistance responses to Bgt were investigated through transcriptome sequencing. Four gene coexpression networks (GCNs) were developed using transcriptomic data generated for 20 T. urartu accessions showing IM, HR or susceptible responses. The powdery mildew resistance regulated (PMRR) genes whose expression was significantly correlated with Bgt resistance were identified, and they tended to be hubs and enriched in six major modules. A wide occurrence of negative regulation of PMRR genes was observed. Three new candidate immune receptor genes (TRIUR3_13045, TRIUR3_01037 and TRIUR3_06195) positively associated with Bgt resistance were discovered. Finally, the involvement of TRIUR3_01037 in Bgt resistance was tentatively verified through cosegregation analysis in a F2 population and functional expression assay in Bgt susceptible leaf cells. This research provides insights into the global network properties of PMRR genes. Potential molecular differences between IM and HR resistance responses to Bgt are discussed. PMID:27033636

  17. Tendencies for higher co-expression of EGFR and HER2 and downregulation of HER3 in prostate cancer lymph node metastases compared with corresponding primary tumors.

    PubMed

    Carlsson, J; Shen, L; Xiang, J; Xu, J; Wei, Q

    2013-01-01

    The epidermal growth factor receptor (EGFR) family members are potential targets for therapy using extra-cellular domain receptor binding agents, such as the antibodies trastuzumab and cetuximab, or antibodies labeled with therapeutically useful radionuclides or toxins. This is especially the case when the tumor cells are resistant to chemotherapy and tyrosine kinase inhibitors. Studies concerning the expression of these receptors in prostate cancer vary in the literature, possibly due to differences in patient inclusion, sample preparations and scoring criteria. In our study, EGFR, HER2 and HER3 expression was analyzed in prostate cancer samples from primary tumors and corresponding lymph node metastases from 12 patients. The expression of HER2 and EGFR was scored from immunohistochemical preparations and the HercepTest criteria (0, 1+, 2+ or 3+), while HER3 expression was scored as no, weak or strong staining. There were 5 EGFR-positive (2+ or 3+) primary tumors and 6 EGFR-positive lymph node metastases, and there was EGFR upregulation in one metastasis. Only 4 of the 12 patients had marked HER2 expression (2+ or 3+) in their primary tumors and there was one downregulation and 5 cases of upregulation in the metastases. Thus, a total of 8 out of 12 analyzed metastases were HER2-positive. Of the 12 primary tumors, 9 expressed HER3 while only 2 of the lymph node metastases expressed recognizable HER3 staining, so 7 metastases appeared to have downregulated HER3 expression. In one of the primary tumors there was positive co-expression of EGFR and HER2, while this co-expression was observed in 4 of the metastases. Thus, there were tendencies for upregulation of HER2, increased co-expression of EGFR and HER2 and downregulation of HER3 in the prostate cancer lymph node metastases in comparison to the primary tumors. The results are encouraging for studies involving more patients. Possible strategies for EGFR- and HER2-targeted therapy are briefly discussed in the

  18. Patterns of genetic differentiation at MHC class I genes and microsatellites identify conservation units in the giant panda.

    PubMed

    Zhu, Ying; Wan, Qiu-Hong; Yu, Bin; Ge, Yun-Fa; Fang, Sheng-Guo

    2013-10-22

    Evaluating patterns of genetic variation is important to identify conservation units (i.e., evolutionarily significant units [ESUs], management units [MUs], and adaptive units [AUs]) in endangered species. While neutral markers could be used to infer population history, their application in the estimation of adaptive variation is limited. The capacity to adapt to various environments is vital for the long-term survival of endangered species. Hence, analysis of adaptive loci, such as the major histocompatibility complex (MHC) genes, is critical for conservation genetics studies. Here, we investigated 4 classical MHC class I genes (Aime-C, Aime-F, Aime-I, and Aime-L) and 8 microsatellites to infer patterns of genetic variation in the giant panda (Ailuropoda melanoleuca) and to further define conservation units. Overall, we identified 24 haplotypes (9 for Aime-C, 1 for Aime-F, 7 for Aime-I, and 7 for Aime-L) from 218 individuals obtained from 6 populations of giant panda. We found that the Xiaoxiangling population had the highest genetic variation at microsatellites among the 6 giant panda populations and higher genetic variation at Aime-MHC class I genes than other larger populations (Qinling, Qionglai, and Minshan populations). Differentiation index (FST)-based phylogenetic and Bayesian clustering analyses for Aime-MHC-I and microsatellite loci both supported that most populations were highly differentiated. The Qinling population was the most genetically differentiated. The giant panda showed a relatively higher level of genetic diversity at MHC class I genes compared with endangered felids. Using all of the loci, we found that the 6 giant panda populations fell into 2 ESUs: Qinling and non-Qinling populations. We defined 3 MUs based on microsatellites: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. We also recommended 3 possible AUs based on MHC loci: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. Furthermore, we recommend

  19. RNA-seq methods for identifying differentially expressed gene in human pancreatic islet cells treated with pro-inflammatory cytokines.

    PubMed

    Li, Bo; Bi, Chang Long; Lang, Ning; Li, Yu Ze; Xu, Chao; Zhang, Ying Qi; Zhai, Ai Xia; Cheng, Zhi Feng

    2014-01-01

    Type 1 diabetes is a chronic autoimmune disease in which pancreatic beta cells are killed by the infiltrating immune cells as well as the cytokines released by these cells. Many studies indicate that inflammatory mediators have an essential role in this disease. In the present study, we profiled the transcriptome in human islets of langerhans under control conditions or following exposure to the pro-inflammatory cytokines based on the RNA sequencing dataset downloaded from SRA database. After filtered the low-quality ones, the RNA readers was aligned to human genome hg19 by TopHat and then assembled by Cufflinks. The expression value of each transcript was calculated and consequently differentially expressed genes were screened out. Finally, a total of 63 differentially expressed genes were identified including 60 up-regulated and three down-regulated genes. GBP5 and CXCL9 stood out as the top two most up-regulated genes in cytokines treated samples with the log2 fold change of 12.208 and 10.901, respectively. Meanwhile, PTF1A and REG3G were identified as the top two most down-regulated genes with the log2 fold change of -3.759 and -3.606, respectively. Of note, we also found 262 lncRNAs (long non-coding RNA), 177 of which were inferred as novel lncRNAs. Further in-depth follow-up analysis of the transcriptional regulation reported in this study may shed light on the specific function of these lncRNA.

  20. Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis.

    PubMed

    Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng

    2018-06-08

    Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.

  1. Genome-wide DNA methylation profile identified a unique set of differentially methylated immune genes in oral squamous cell carcinoma patients in India.

    PubMed

    Basu, Baidehi; Chakraborty, Joyeeta; Chandra, Aditi; Katarkar, Atul; Baldevbhai, Jadav Ritesh Kumar; Dhar Chowdhury, Debjit; Ray, Jay Gopal; Chaudhuri, Keya; Chatterjee, Raghunath

    2017-01-01

    Oral squamous cell carcinoma (OSCC) is one of the common malignancies in Southeast Asia. Epigenetic changes, mainly the altered DNA methylation, have been implicated in many cancers. Considering the varied environmental and genotoxic exposures among the Indian population, we conducted a genome-wide DNA methylation study on paired tumor and adjacent normal tissues of ten well-differentiated OSCC patients and validated in an additional 53 well-differentiated OSCC and adjacent normal samples. Genome-wide DNA methylation analysis identified several novel differentially methylated regions associated with OSCC. Hypermethylation is primarily enriched in the CpG-rich regions, while hypomethylation is mainly in the open sea. Distinct epigenetic drifts for hypo- and hypermethylation across CpG islands suggested independent mechanisms of hypo- and hypermethylation in OSCC development. Aberrant DNA methylation in the promoter regions are concomitant with gene expression. Hypomethylation of immune genes reflect the lymphocyte infiltration into the tumor microenvironment. Comparison of methylome data with 312 TCGA HNSCC samples identified a unique set of hypomethylated promoters among the OSCC patients in India. Pathway analysis of unique hypomethylated promoters indicated that the OSCC patients in India induce an anti-tumor T cell response, with mobilization of T lymphocytes in the neoplastic environment. Survival analysis of these epigenetically regulated immune genes suggested their prominent role in OSCC progression. Our study identified a unique set of hypomethylated regions, enriched in the promoters of immune response genes, and indicated the presence of a strong immune component in the tumor microenvironment. These methylation changes may serve as potential molecular markers to define risk and to monitor the prognosis of OSCC patients in India.

  2. Cellular Trafficking of Phospholamban and Formation of Functional Sarcoplasmic Reticulum During Myocyte DIfferentiation

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

    Stenoien, David L.; Knyushko, Tatyana V.; Londono, Monica P.

    2007-06-01

    The sarco/endoplasmic reticulum Ca-ATPase (SERCA) family members are transmembrane proteins that play an essential role in regulating intracellular calcium levels. Phospholamban (PLB), a 52 amino acid phosphoprotein, regulates SERCA activity in adult heart and skeletal muscle. Using the C2C12 myocyte cell line, we find endogenous PLB constitutively expressed in both myoblasts and myotubes, whereas SERCA expression coincides with activation of the differentiation program. PLB has a punctuate distribution in myoblasts changing to a reticular distribution in myotubes where it colocalizes with SERCAs. To examine the distribution and dynamics of PLB and SERCA, we expressed fluorescent fusion proteins (GFP, CFP, andmore » YFP) of PLB and SERCA in myoblasts. Coexpressed PLB and SERCA localize to distinct cellular compartments in myoblasts but begin to colocalize as cells differentiate. Fluorescence Recovery After Photobleaching (FRAP) studies show different recovery patterns for each protein in myoblasts confirming their localization to distinct compartments. To extend these studies, we created stable cell lines expressing O6-alkylguanine-DNA alkyltransferase (AGT) fusions with PLB or SERCA to track their localization as myocytes differentiate. These experiments demonstrate that PLB localizes to punctate vesicles in myoblasts and adopts a reticular distribution that coincides with SERCA distribution after differentiation. Colocalization experiments indicate that a subset of PLB in myoblasts colocalizes with endosomes, Golgi, and the plasma membrane however PLB also localizes to other, as yet unidentified vesicles. Our results indicate that differentiation plays a critical role in regulating PLB distribution to ensure its colocalization within the same cellular compartment as SERCA in differentiated cells. The presence and altered distribution of PLB in undifferentiated myoblasts raises the possibility that this protein has additional functions distinct from SERCA

  3. RNase-Resistant Virus-Like Particles Containing Long Chimeric RNA Sequences Produced by Two-Plasmid Coexpression System▿

    PubMed Central

    Wei, Yuxiang; Yang, Changmei; Wei, Baojun; Huang, Jie; Wang, Lunan; Meng, Shuang; Zhang, Rui; Li, Jinming

    2008-01-01

    RNase-resistant, noninfectious virus-like particles containing exogenous RNA sequences (armored RNA) are good candidates as RNA controls and standards in RNA virus detection. However, the length of RNA packaged in the virus-like particles with high efficiency is usually less than 500 bases. In this study, we describe a method for producing armored L-RNA. Armored L-RNA is a complex of MS2 bacteriophage coat protein and RNA produced in Escherichia coli by the induction of a two-plasmid coexpression system in which the coat protein and maturase are expressed from one plasmid and the target RNA sequence with modified MS2 stem-loop (pac site) is transcribed from another plasmid. A 3V armored L-RNA of 2,248 bases containing six gene fragments—hepatitis C virus, severe acute respiratory syndrome coronavirus (SARS-CoV1, SARS-CoV2, and SARS-CoV3), avian influenza virus matrix gene (M300), and H5N1 avian influenza virus (HA300)—was successfully expressed by the two-plasmid coexpression system and was demonstrated to have all of the characteristics of armored RNA. We evaluated the 3V armored L-RNA as a calibrator for multiple virus assays. We used the WHO International Standard for HCV RNA (NIBSC 96/790) to calibrate the chimeric armored L-RNA, which was diluted by 10-fold serial dilutions to obtain samples containing 106 to 102 copies. In conclusion, the approach we used for armored L-RNA preparation is practical and could reduce the labor and cost of quality control in multiplex RNA virus assays. Furthermore, we can assign the chimeric armored RNA with an international unit for quantitative detection. PMID:18305135

  4. Transcriptome Analysis of Gelatin Seed Treatment as a Biostimulant of Cucumber Plant Growth

    PubMed Central

    Wilson, H. T.; Xu, K.; Taylor, A. G.

    2015-01-01

    The beneficial effects of gelatin capsule seed treatment on enhanced plant growth and tolerance to abiotic stress have been reported in a number of crops, but the molecular mechanisms underlying such effects are poorly understood. Using mRNA sequencing based approach, transcriptomes of one- and two-week-old cucumber plants from gelatin capsule treated and nontreated seeds were characterized. The gelatin treated plants had greater total leaf area, fresh weight, frozen weight, and nitrogen content. Pairwise comparisons of the RNA-seq data identified 620 differentially expressed genes between treated and control two-week-old plants, consistent with the timing when the growth related measurements also showed the largest differences. Using weighted gene coexpression network analysis, significant coexpression gene network module of 208 of the 620 differentially expressed genes was identified, which included 16 hub genes in the blue module, a NAC transcription factor, a MYB transcription factor, an amino acid transporter, an ammonium transporter, a xenobiotic detoxifier-glutathione S-transferase, and others. Based on the putative functions of these genes, the identification of the significant WGCNA module and the hub genes provided important insights into the molecular mechanisms of gelatin seed treatment as a biostimulant to enhance plant growth. PMID:26558288

  5. Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

    PubMed

    Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

    2017-06-01

    To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

  6. Coexpression of the genes for interleukin 6 and its receptor without apparent involvement in the proliferation of acute myeloid leukemia cells.

    PubMed

    Lopez, M; Maroc, N; Kerangueven, F; Bardin, F; Courcoul, M; Lavezzi, C; Birg, F; Mannoni, P

    1991-09-01

    Leukemic cells isolated from patients with either acute myeloid leukemia (AML) or acute lymphoid leukemia (ALL) were screened for their capacity to express the interleukin 6 (IL-6) and IL-6 receptor genes, both at the RNA and protein levels. Variable levels (10 to greater than 600 U/ml) of an IL-6 activity, inhibited by neutralizing anti-IL-6 antibodies, were detected in AML cell supernatants using the B9 cell bioassay. High levels (greater than 100 U/ml) were observed in differentiated (M4 and M5 stages) AML, as well as in less mature (M1 and M2 stages) AML. Detection of the IL-6 transcript correlated with the biological activity. In addition, both IL-6 activity and IL-6 mRNA were detected in "fresh" leukemic cells, indicating that the glycoprotein was actually synthesized in vivo. In contrast, the IL-6 gene was less frequently expressed in ALL. The IL-6 receptor gene was transcribed in both AML and ALL; binding experiments showed that the protein was present at the cell surface. The spontaneous in vitro proliferation of leukemic cells coexpressing the transcripts for IL-6 and its receptor was not significantly inhibited by a neutralizing anti-IL-6 antibody, suggesting that IL-6 is not primarily implicated in the proliferation of the leukemic clone via an autocrine loop. Synthesis of IL-6 could, however, confer on leukemic cells a selective growth advantage through activation of the cytokine cascade.

  7. Neutralization of Bacterial YoeBSpn Toxicity and Enhanced Plant Growth in Arabidopsis thaliana via Co-Expression of the Toxin-Antitoxin Genes

    PubMed Central

    Abu Bakar, Fauziah; Yeo, Chew Chieng; Harikrishna, Jennifer Ann

    2016-01-01

    Bacterial toxin-antitoxin (TA) systems have various cellular functions, including as part of the general stress response. The genome of the Gram-positive human pathogen Streptococcus pneumoniae harbors several putative TA systems, including yefM-yoeBSpn, which is one of four systems that had been demonstrated to be biologically functional. Overexpression of the yoeBSpn toxin gene resulted in cell stasis and eventually cell death in its native host, as well as in Escherichia coli. Our previous work showed that induced expression of a yoeBSpn toxin-Green Fluorescent Protein (GFP) fusion gene apparently triggered apoptosis and was lethal in the model plant, Arabidopsis thaliana. In this study, we investigated the effects of co-expression of the yefMSpn antitoxin and yoeBSpn toxin-GFP fusion in transgenic A. thaliana. When co-expressed in Arabidopsis, the YefMSpn antitoxin was found to neutralize the toxicity of YoeBSpn-GFP. Interestingly, the inducible expression of both yefMSpn antitoxin and yoeBSpn toxin-GFP fusion in transgenic hybrid Arabidopsis resulted in larger rosette leaves and taller plants with a higher number of inflorescence stems and increased silique production. To our knowledge, this is the first demonstration of a prokaryotic antitoxin neutralizing its cognate toxin in plant cells. PMID:27104531

  8. Cancer stem cell markers in patterning differentiation and in prognosis of oral squamous cell carcinoma.

    PubMed

    Mohanta, Simple; Siddappa, Gangotri; Valiyaveedan, Sindhu Govindan; Dodda Thimmasandra Ramanjanappa, Ravindra; Das, Debashish; Pandian, Ramanan; Khora, Samanta Sekhar; Kuriakose, Moni Abraham; Suresh, Amritha

    2017-06-01

    Differentiation is a major histological parameter determining tumor aggressiveness and prognosis of the patient; cancer stem cells with their slow dividing and undifferentiated nature might be one of the factors determining the same. This study aims to correlate cancer stem cell markers (CD44 and CD147) with tumor differentiation and evaluate their subsequent effect on prognosis. Immunohistochemical analysis in treatment naïve oral cancer patients (n = 53) indicated that the expression of CD147 was associated with poorly differentiated squamous cell carcinoma and moderately differentiated squamous cell carcinoma (p < 0.01). Furthermore, co-expression analysis showed that 45% each of moderately differentiated squamous cell carcinoma and poorly differentiated squamous cell carcinoma patients were CD44 high /CD147 high as compared to only 10% of patients with well-differentiated squamous cell carcinoma. A three-way analysis indicated that differentiation correlated with recurrence and survival (p < 0.05) in only the patients with CD44 high /CD147 high cohort. Subsequently, relevance of these cancer stem cell markers in patterning the differentiation characteristics was evaluated in oral squamous cell carcinoma cell lines originating from different grades of oral cancer. Flowcytometry-based analysis indicated an increase in CD44 + /CD147 + cells in cell lines of poorly differentiated squamous cell carcinoma (94.35 ± 1.14%, p < 0.001) and moderately differentiated squamous cell carcinoma origin (93.49 ± 0.47%, p < 0.001) as compared to cell line of well-differentiated squamous cell carcinoma origin (23.12% ± 0.49%). Expression profiling indicated higher expression of cancer stem cell and epithelial-mesenchymal transition markers in SCC029B (poorly differentiated squamous cell carcinoma originated; p ≤ 0.001), which was further translated into increased spheroid formation, migration, and invasion (p < 0.001) as compared to cell line of well-differentiated squamous

  9. Transcriptome interrogation of human myometrium identifies differentially expressed sense-antisense pairs of protein-coding and long non-coding RNA genes in spontaneous labor at term

    PubMed Central

    Romero, Roberto; Tarca, Adi; Chaemsaithong, Piya; Miranda, Jezid; Chaiworapongsa, Tinnakorn; Jia, Hui; Hassan, Sonia S.; Kalita, Cynthia A.; Cai, Juan; Yeo, Lami; Lipovich, Leonard

    2014-01-01

    Objective The mechanisms responsible for normal and abnormal parturition are poorly understood. Myometrial activation leading to regular uterine contractions is a key component of labor. Dysfunctional labor (arrest of dilatation and/or descent) is a leading indication for cesarean delivery. Compelling evidence suggests that most of these disorders are functional in nature, and not the result of cephalopelvic disproportion. The methodology and the datasets afforded by the post-genomic era provide novel opportunities to understand and target gene functions in these disorders. In 2012, the ENCODE Consortium elucidated the extraordinary abundance and functional complexity of long non-coding RNA genes in the human genome. The purpose of the study was to identify differentially expressed long non-coding RNA genes in human myometrium in women in spontaneous labor at term. Materials and Methods Myometrium was obtained from women undergoing cesarean deliveries who were not in labor (n=19) and women in spontaneous labor at term (n=20). RNA was extracted and profiled using an Illumina® microarray platform. The analysis of the protein coding genes from this study has been previously reported. Here, we have used computational approaches to bound the extent of long non-coding RNA representation on this platform, and to identify co-differentially expressed and correlated pairs of long non-coding RNA genes and protein-coding genes sharing the same genomic loci. Results Upon considering more than 18,498 distinct lncRNA genes compiled nonredundantly from public experimental data sources, and interrogating 2,634 that matched Illumina microarray probes, we identified co-differential expression and correlation at two genomic loci that contain coding-lncRNA gene pairs: SOCS2-AK054607 and LMCD1-NR_024065 in women in spontaneous labor at term. This co-differential expression and correlation was validated by qRT-PCR, an independent experimental method. Intriguingly, one of the two lnc

  10. Identifying candidate driver genes by integrative ovarian cancer genomics data

    NASA Astrophysics Data System (ADS)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  11. ESR1 Is Co-Expressed with Closely Adjacent Uncharacterised Genes Spanning a Breast Cancer Susceptibility Locus at 6q25.1

    PubMed Central

    Dunbier, Anita K.; Anderson, Helen; Ghazoui, Zara; Lopez-Knowles, Elena; Pancholi, Sunil; Ribas, Ricardo; Drury, Suzanne; Sidhu, Kally; Leary, Alexandra; Martin, Lesley-Ann; Dowsett, Mitch

    2011-01-01

    Approximately 80% of human breast carcinomas present as oestrogen receptor α-positive (ER+ve) disease, and ER status is a critical factor in treatment decision-making. Recently, single nucleotide polymorphisms (SNPs) in the region immediately upstream of the ER gene (ESR1) on 6q25.1 have been associated with breast cancer risk. Our investigation of factors associated with the level of expression of ESR1 in ER+ve tumours has revealed unexpected associations between genes in this region and ESR1 expression that are important to consider in studies of the genetic causes of breast cancer risk. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with an aromatase (oestrogen synthase) inhibitor was analyzed on Illumina 48K microarrays. Multiple-testing corrected Spearman correlation revealed that three previously uncharacterized open reading frames (ORFs) located immediately upstream of ESR1, C6ORF96, C6ORF97, and C6ORF211 were highly correlated with ESR1 (Rs = 0.67, 0.64, and 0.55 respectively, FDR<1×10−7). Publicly available datasets confirmed this relationship in other groups of ER+ve tumours. DNA copy number changes did not account for the correlations. The correlations were maintained in cultured cells. An ERα antagonist did not affect the ORFs' expression or their correlation with ESR1, suggesting their transcriptional co-activation is not directly mediated by ERα. siRNA inhibition of C6ORF211 suppressed proliferation in MCF7 cells, and C6ORF211 positively correlated with a proliferation metagene in tumours. In contrast, C6ORF97 expression correlated negatively with the metagene and predicted for improved disease-free survival in a tamoxifen-treated published dataset, independently of ESR1. Our observations suggest that some of the biological effects previously attributed to ER could be mediated and/or modified by these co-expressed genes. The co-expression and function of these genes may be important influences

  12. Effect of Yiguanjian decoction on cell differentiation and proliferation in CCl4-treated mice

    PubMed Central

    Wang, Xiao-Ling; Jia, Dong-Wei; Liu, Hui-Yang; Yan, Xiao-Feng; Ye, Ting-Jie; Hu, Xu-Dong; Li, Bo-Qin; Chen, Yong-Liang; Liu, Ping

    2012-01-01

    AIM: To investigate the cellular mechanisms of action of Yiguanjian (YGJ) decoction in treatment of chronic hepatic injury. METHODS: One group of mice was irradiated, and received enhanced green fluorescent protein (EGFP)-positive bone marrow transplants followed by 13 wk of CCl4 injection and 6 wk of oral YGJ administration. A second group of Institute for Cancer Research mice was treated with 13 wk of CCl4 injection and 6 wk of oral YGJ administration. Liver function, histological changes in the liver, and Hyp content were analyzed. The expression of α-smooth muscle actin (α-SMA), F4/80, albumin (Alb), EGFP, mitogen-activated protein kinase-2 (PKM2), Ki-67, α fetoprotein (AFP), monocyte chemotaxis protein-1 and CC chemokine receptor 2 were assayed. RESULTS: As hepatic damage progressed, EGFP-positive marrow cells migrated into the liver and were mainly distributed along the fibrous septa. They showed a conspicuous coexpression of EGFP with α-SMA and F4/80 but no coexpression with Alb. Moreover, the expression of PKM2, AFP and Ki-67 was enhanced dynamically and steadily over the course of liver injury. YGJ abrogated the increases in the number of bone marrow-derived fibrogenic cells in the liver, inhibited expression of both progenitor and mature hepatocyte markers, and reduced fibrogenesis. CONCLUSION: YGJ decoction improves liver fibrosis by inhibiting the migration of bone marrow cells into the liver as well as inhibiting their differentiation and suppressing the proliferation of both progenitors and hepatocytes in the injured liver. PMID:22783047

  13. Sex hormone-binding globulin b expression in the rainbow trout ovary prior to sex differentiation.

    PubMed

    Pérez, Claudio; Araneda, Cristian; Estay, Francisco; Díaz, Nelson F; Vizziano-Cantonnet, Denise

    2018-04-01

    Salmonids have two sex hormone-binding globulin (Shbg) paralogs. Shbga is mainly expressed in the liver, while Shbgb is secreted by the granulosa cells of the rainbow trout ovary. Coexpression of shbgb and the gonadal aromatase cyp19a1a mRNAs been observed in granulosa cells, suggesting a physiological coordination between Shbgb expression and estrogen synthesis. As estrogens are essential for female sex determination in the fish ovary, we propose that Shbgb participates in early ovarian differentiation, either by binding with estrogen or through another mechanism that remains to be discovered. To elucidate this potential role, monosex populations of female trout were studied during the molecular ovarian differentiation period (28-56 dpf). shbgb mRNA expression was measured using qPCR and compared with expression of genes for other ovarian markers (cyp19a1a, foxl2, follistatin, and estrogen receptors). shbgb transcript expression was detected during the final stages of embryonic development (21-26 dpf) and during molecular ovarian differentiation (32-52 dpf) after hatching (which occurred at 31 dpf). In situ hybridization localized shbgb transcription to the undifferentiated ovary at 42 dpf, and shbgb and cyp19a1a mRNA showed similar expression patterns. These results suggest that Shbgb is involved in early ovarian differentiation, supporting an important role for the salmonid shbgb gene in sex determination. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

    PubMed Central

    Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

    2016-01-01

    The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration. PMID:27241320

  15. Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

    NASA Astrophysics Data System (ADS)

    Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

    2016-05-01

    The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

  16. Convergent roles of de novo mutations and common variants in schizophrenia in tissue-specific and spatiotemporal co-expression network.

    PubMed

    Jia, Peilin; Chen, Xiangning; Fanous, Ayman H; Zhao, Zhongming

    2018-05-24

    Genetic components susceptible to complex disease such as schizophrenia include a wide spectrum of variants, including common variants (CVs) and de novo mutations (DNMs). Although CVs and DNMs differ by origin, it remains elusive whether and how they interact at the gene, pathway, and network levels that leads to the disease. In this work, we characterized the genes harboring schizophrenia-associated CVs (CVgenes) and the genes harboring DNMs (DNMgenes) using measures from network, tissue-specific expression profile, and spatiotemporal brain expression profile. We developed an algorithm to link the DNMgenes and CVgenes in spatiotemporal brain co-expression networks. DNMgenes tended to have central roles in the human protein-protein interaction (PPI) network, evidenced in their high degree and high betweenness values. DNMgenes and CVgenes connected with each other significantly more often than with other genes in the networks. However, only CVgenes remained significantly connected after adjusting for their degree. In our gene co-expression PPI network, we found DNMgenes and CVgenes connected in a tissue-specific fashion, and such a pattern was similar to that in GTEx brain but not in other GTEx tissues. Importantly, DNMgene-CVgene subnetworks were enriched with pathways of chromatin remodeling, MHC protein complex binding, and neurotransmitter activities. In summary, our results unveiled that both DNMgenes and CVgenes contributed to a core set of biologically important pathways and networks, and their interactions may attribute to the risk for schizophrenia. Our results also suggested a stronger biological effect of DNMgenes than CVgenes in schizophrenia.

  17. Comparative genomic analysis of Helicobacter pylori from Malaysia identifies three distinct lineages suggestive of differential evolution.

    PubMed

    Kumar, Narender; Mariappan, Vanitha; Baddam, Ramani; Lankapalli, Aditya K; Shaik, Sabiha; Goh, Khean-Lee; Loke, Mun Fai; Perkins, Tim; Benghezal, Mohammed; Hasnain, Seyed E; Vadivelu, Jamuna; Marshall, Barry J; Ahmed, Niyaz

    2015-01-01

    The discordant prevalence of Helicobacter pylori and its related diseases, for a long time, fostered certain enigmatic situations observed in the countries of the southern world. Variation in H. pylori infection rates and disease outcomes among different populations in multi-ethnic Malaysia provides a unique opportunity to understand dynamics of host-pathogen interaction and genome evolution. In this study, we extensively analyzed and compared genomes of 27 Malaysian H. pylori isolates and identified three major phylogeographic lineages: hspEastAsia, hpEurope and hpSouthIndia. The analysis of the virulence genes within the core genome, however, revealed a comparable pathogenic potential of the strains. In addition, we identified four genes limited to strains of East-Asian lineage. Our analyses identified a few strain-specific genes encoding restriction modification systems and outlined 311 core genes possibly under differential evolutionary constraints, among the strains representing different ethnic groups. The cagA and vacA genes also showed variations in accordance with the host genetic background of the strains. Moreover, restriction modification genes were found to be significantly enriched in East-Asian strains. An understanding of these variations in the genome content would provide significant insights into various adaptive and host modulation strategies harnessed by H. pylori to effectively persist in a host-specific manner. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Acute leukemia coexpressing myeloid, B- and T-lineage associated markers: multiparameter analysis of criteria defining lineage commitment and maturational stage in a case of undifferentiated leukemia.

    PubMed

    Meckenstock, G; Heyll, A; Schneider, E M; Hildebrandt, B; Runde, V; Aul, C; Bartram, C R; Ludwig, W D; Schneider, W

    1995-02-01

    Coexpression of myeloid, B-, and T-lineage associated markers was found in a patient with morphologically and cytochemically undifferentiated acute leukemia. Surface marker analysis using two-color immunofluorescence staining characterized blast cells to express CD34, CD38, CD117, and class II antigens, coexpressing TdT, CD4, CD7, CD13, CD19, and CD33. Cytoplasmic expression of myeloperoxidase, CD3, and CD22 could not be demonstrated. Monosomy for chromosome 7 was found by cytogenetic analysis. The absence of clonal rearrangements of immunoglobulin or T-cell receptor genes was shown by Southern blot analysis. Using a 3H-thymidine incorporation assay, DNA synthesis of leukemic blasts could be stimulated by IL-3, IL-6 and G-CSF in vitro. The present case did not offer specific criteria of lineage commitment. Corresponding to an equivalent counterpart in normal hematopoiesis, the involved cell population may reflect an early, most immature developmental stage within a multipotent progenitor cell compartment.

  19. A recombinant pseudorabies virus co-expressing capsid proteins precursor P1-2A of FMDV and VP2 protein of porcine parvovirus: a trivalent vaccine candidate.

    PubMed

    Hong, Qi; Qian, Ping; Li, Xiang-Min; Yu, Xiao-Lan; Chen, Huan-Chun

    2007-11-01

    Pseudorabies (PR), foot-and-mouth disease (FMD), and porcine parvovirus disease are three important infectious diseases in swine worldwide. The gene-deleted pseudorabies virus (PRV) has been used as a live-viral vector to develop multivalent genetic engineering vaccine. In this study, a recombinant PRV, which could co-express protein precursor P1-2A of FMDV and VP2 protein of PPV, was constructed using PRV TK(-)/gE(-)/LacZ(+) mutant as the vector. After homologous recombination and plaque purification, recombinant virus PRV TK(-)/gE(-)/P1-2A-VP2 was acquired and identified. Immunogenicity, safety of the recombinant PRV and its protection against PRV were confirmed in a mouse model by indirect ELISA and serum neutralization test. The results show that the recombinant PRV is a candidate vaccine strain to develop a novel trivalent vaccine against PRV, FMDV and PPV in swine.

  20. miRNA Temporal Analyzer (mirnaTA): a bioinformatics tool for identifying differentially expressed microRNAs in temporal studies using normal quantile transformation.

    PubMed

    Cer, Regina Z; Herrera-Galeano, J Enrique; Anderson, Joseph J; Bishop-Lilly, Kimberly A; Mokashi, Vishwesh P

    2014-01-01

    Understanding the biological roles of microRNAs (miRNAs) is a an active area of research that has produced a surge of publications in PubMed, particularly in cancer research. Along with this increasing interest, many open-source bioinformatics tools to identify existing and/or discover novel miRNAs in next-generation sequencing (NGS) reads become available. While miRNA identification and discovery tools are significantly improved, the development of miRNA differential expression analysis tools, especially in temporal studies, remains substantially challenging. Further, the installation of currently available software is non-trivial and steps of testing with example datasets, trying with one's own dataset, and interpreting the results require notable expertise and time. Subsequently, there is a strong need for a tool that allows scientists to normalize raw data, perform statistical analyses, and provide intuitive results without having to invest significant efforts. We have developed miRNA Temporal Analyzer (mirnaTA), a bioinformatics package to identify differentially expressed miRNAs in temporal studies. mirnaTA is written in Perl and R (Version 2.13.0 or later) and can be run across multiple platforms, such as Linux, Mac and Windows. In the current version, mirnaTA requires users to provide a simple, tab-delimited, matrix file containing miRNA name and count data from a minimum of two to a maximum of 20 time points and three replicates. To recalibrate data and remove technical variability, raw data is normalized using Normal Quantile Transformation (NQT), and linear regression model is used to locate any miRNAs which are differentially expressed in a linear pattern. Subsequently, remaining miRNAs which do not fit a linear model are further analyzed in two different non-linear methods 1) cumulative distribution function (CDF) or 2) analysis of variances (ANOVA). After both linear and non-linear analyses are completed, statistically significant miRNAs (P < 0

  1. Analysis of global gene expression profiles to identify differentially expressed genes critical for embryo development in Brassica rapa.

    PubMed

    Zhang, Yu; Peng, Lifang; Wu, Ya; Shen, Yanyue; Wu, Xiaoming; Wang, Jianbo

    2014-11-01

    Embryo development represents a crucial developmental period in the life cycle of flowering plants. To gain insights into the genetic programs that control embryo development in Brassica rapa L., RNA sequencing technology was used to perform transcriptome profiling analysis of B. rapa developing embryos. The results generated 42,906,229 sequence reads aligned with 32,941 genes. In total, 27,760, 28,871, 28,384, and 25,653 genes were identified from embryos at globular, heart, early cotyledon, and mature developmental stages, respectively, and analysis between stages revealed a subset of stage-specific genes. We next investigated 9,884 differentially expressed genes with more than fivefold changes in expression and false discovery rate ≤ 0.001 from three adjacent-stage comparisons; 1,514, 3,831, and 6,633 genes were detected between globular and heart stage embryo libraries, heart stage and early cotyledon stage, and early cotyledon and mature stage, respectively. Large numbers of genes related to cellular process, metabolism process, response to stimulus, and biological process were expressed during the early and middle stages of embryo development. Fatty acid biosynthesis, biosynthesis of secondary metabolites, and photosynthesis-related genes were expressed predominantly in embryos at the middle stage. Genes for lipid metabolism and storage proteins were highly expressed in the middle and late stages of embryo development. We also identified 911 transcription factor genes that show differential expression across embryo developmental stages. These results increase our understanding of the complex molecular and cellular events during embryo development in B. rapa and provide a foundation for future studies on other oilseed crops.

  2. Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

    PubMed Central

    2013-01-01

    Background To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Methods Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Results Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration

  3. 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

  4. 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

  5. A Gene Co-Expression Network in Whole Blood of Schizophrenia Patients Is Independent of Antipsychotic-Use and Enriched for Brain-Expressed Genes

    PubMed Central

    de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.

    2012-01-01

    Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806

  6. Chilling Affects Phytohormone and Post-Embryonic Development Pathways during Bud Break and Fruit Set in Apple (Malus domestica Borkh.)

    PubMed Central

    Kumar, Gulshan; Gupta, Khushboo; Pathania, Shivalika; Swarnkar, Mohit Kumar; Rattan, Usha Kumari; Singh, Gagandeep; Sharma, Ram Kumar; Singh, Anil Kumar

    2017-01-01

    The availability of sufficient chilling during bud dormancy plays an important role in the subsequent yield and quality of apple fruit, whereas, insufficient chilling availability negatively impacts the apple production. The transcriptome profiling during bud dormancy release and initial fruit set under low and high chill conditions was performed using RNA-seq. The comparative high number of differentially expressed genes during bud break and fruit set under high chill condition indicates that chilling availability was associated with transcriptional reorganization. The comparative analysis reveals the differential expression of genes involved in phytohormone metabolism, particularly for Abscisic acid, gibberellic acid, ethylene, auxin and cytokinin. The expression of Dormancy Associated MADS-box, Flowering Locus C-like, Flowering Locus T-like and Terminal Flower 1-like genes was found to be modulated under differential chilling. The co-expression network analysis indentified two high chill specific modules that were found to be enriched for “post-embryonic development” GO terms. The network analysis also identified hub genes including Early flowering 7, RAF10, ZEP4 and F-box, which may be involved in regulating chilling-mediated dormancy release and fruit set. The results of transcriptome and co-expression network analysis indicate that chilling availability majorly regulates phytohormone-related pathways and post-embryonic development during bud break. PMID:28198417

  7. L-citrulline immunostaining identifies nitric oxide production sites within neurons

    NASA Technical Reports Server (NTRS)

    Martinelli, G. P. T.; Friedrich, V. L. Jr; Holstein, G. R.

    2002-01-01

    The cellular and subcellular localization of L-citrulline was analyzed in the adult rat brain and compared with that of traditional markers for the presence of nitric oxide synthase. Light, transmission electron, and confocal laser scanning microscopy were used to study tissue sections processed for immunocytochemistry employing a monoclonal antibody against L-citrulline or polyclonal anti-neuronal nitric oxide synthase sera, and double immunofluorescence to detect neuronal nitric oxide synthase and L-citrulline co-localization. The results demonstrate that the same CNS regions and cell types are labeled by neuronal nitric oxide synthase polyclonal antisera and L-citrulline monoclonal antibodies, using both immunocytochemistry and immunofluorescence. Short-term pretreatment with a nitric oxide synthase inhibitor reduces L-citrulline immunostaining, but does not affect neuronal nitric oxide synthase immunoreactivity. In the vestibular brainstem, double immunofluorescence studies show that many, but not all, neuronal nitric oxide synthase-positive cells co-express L-citrulline, and that local intracellular patches of intense L-citrulline accumulation are present in some neurons. Conversely, all L-citrulline-labeled neurons co-express neuronal nitric oxide synthase. Cells expressing neuronal nitric oxide synthase alone are interpreted as neurons with the potential to produce nitric oxide under other stimulus conditions, and the subcellular foci of enhanced L-citrulline staining are viewed as intracellular sites of nitric oxide production. This interpretation is supported by ultrastructural observations of subcellular foci with enhanced L-citrulline and/or neuronal nitric oxide synthase staining that are located primarily at postsynaptic densities and portions of the endoplasmic reticulum. We conclude that nitric oxide is produced and released at focal sites within neurons that are identifiable using L-citrulline as a marker. Copyright 2002 IBRO.

  8. Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood.

    PubMed

    Aspler, Anne L; Bolshin, Carly; Vernon, Suzanne D; Broderick, Gordon

    2008-09-26

    Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS) however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood. Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention) and unsupervised latent cluster analysis (LCA). Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in co-expression identified from topological evaluation of linear correlation networks. Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p = 0.01) due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p < 0.05, patterns of co-expression in each group differed markedly. Significant co-expression of CD14+ monocyte with CD16+ neutrophil (p = 0.01) and CD19+ B cell sets (p = 0.00) characterized CFS and fatigue phenotype groups. Also in CFS was a significant negative correlation between CD8+ and both CD19+ up-regulated (p = 0.02) and NK gene sets (p = 0.08). These patterns were absent in controls. Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

  9. Identifying interacting proteins of a Caenorhabditis elegans voltage-gated chloride channel CLH-1 using GFP-Trap and mass spectrometry.

    PubMed

    Zhou, Zi-Liang; Jiang, Jing; Yin, Jiang-An; Cai, Shi-Qing

    2014-06-25

    Chloride channels belong to a superfamily of ion channels that permit passive passage of anions, mainly chloride, across cell membrane. They play a variety of important physiological roles in regulation of cytosolic pH, cell volume homeostasis, organic solute transport, cell migration, cell proliferation, and differentiation. However, little is known about the functional regulation of these channels. In this study, we generated an integrated transgenic worm strain expressing green fluorescence protein (GFP) fused CLC-type chloride channel 1 (CLH-1::GFP), a voltage-gated chloride channel in Caenorhabditis elegans (C. elegans). CLH-1::GFP was expressed in some unidentified head neurons and posterior intestinal cells of C. elegans. Interacting proteins of CLH-1::GFP were purified by GFP-Trap, a novel system for efficient isolation of GFP fusion proteins and their interacting factors. Mass spectrometry (MS) analysis revealed that a total of 27 high probability interacting proteins were co-trapped with CLHp-1::GFP. Biochemical evidence showed that eukaryotic translation elongation factor 1 (EEF-1), one of these co-trapped proteins identified by MS, physically interacted with CLH-1, in consistent with GFP-Trap experiments. Further immunostaining data revealed that the protein level of CLH-1 was significantly increased upon co-expression with EEF-1. These results suggest that the combination of GFP-Trap purification with MS is an excellent tool to identify novel interacting proteins of voltage-gated chloride channels in C. elegans. Our data also show that EEF-1 is a regulator of voltage-gated chloride channel CLH-1.

  10. Alternating current electric fields of varying frequencies: effects on proliferation and differentiation of porcine neural progenitor cells.

    PubMed

    Lim, Ji-Hey; McCullen, Seth D; Piedrahita, Jorge A; Loboa, Elizabeth G; Olby, Natasha J

    2013-10-01

    Application of sinusoidal electric fields (EFs) has been observed to affect cellular processes, including alignment, proliferation, and differentiation. In the present study, we applied low-frequency alternating current (AC) EFs to porcine neural progenitor cells (pNPCs) and investigated the effects on cell patterning, proliferation, and differentiation. pNPCs were grown directly on interdigitated electrodes (IDEs) localizing the EFs to a region accessible visually for fluorescence-based assays. Cultures of pNPCs were exposed to EFs (1 V/cm) of 1 Hz, 10 Hz, and 50 Hz for 3, 7, and 14 days and compared to control cultures. Immunocytochemistry was performed to evaluate the expression of neural markers. pNPCs grew uniformly with no evidence of alignment to the EFs and no change in cell numbers when compared with controls. Nestin expression was shown in all groups at 3 and 7 days, but not at 14 days. NG2 expression was low in all groups. Co-expression of glial fibrillary acidic protein (GFAP) and TUJ1 was significantly higher in the cultures exposed to 10- and 50-Hz EFs than the controls. In summary, sinusoidal AC EFs via IDEs did not alter the alignment and proliferation of pNPCs, but higher frequency stimulation appeared to delay differentiation into mature astrocytes.

  11. Identifying and Exploring Relationships between Contextual Situations and Ordinary Differential Equations

    ERIC Educational Resources Information Center

    Camacho-Machín, M.; Guerrero-Ortiz, C.

    2015-01-01

    The aim of this paper is to present and discuss some of the evidence regarding the resources that students use when they establish relationships between a contextual situation and an ordinary differential equation (ODE). We present research results obtained from work by seven students in a graduate level course in mathematics education, where they…

  12. An efficient method to identify differentially expressed genes in microarray experiments

    PubMed Central

    Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

    2013-01-01

    Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

  13. Enhanced phytoremediation of mixed heavy metal (mercury)-organic pollutants (trichloroethylene) with transgenic alfalfa co-expressing glutathione S-transferase and human P450 2E1.

    PubMed

    Zhang, Yuanyuan; Liu, Junhong; Zhou, Yuanming; Gong, Tingyun; Wang, Jing; Ge, Yinlin

    2013-09-15

    Soil contamination is a global environmental problem and many efforts have been made to find efficient remediation methods over the last decade. Moreover, remediation of mixed contaminated soils are more difficult. In the present study, transgenic alfalfa plants pKHCG co-expressing glutathione S-transferase (GST) and human P450 2E1 (CYP2E1) genes were used for phytoremediation of mixed mercury (Hg)-trichloroethylene (TCE) contaminants. Simultaneous expression of GST and CYP2E1 may produce a significant synergistic effect, and leads to improved resistance and accumulation to heavy metal-organic complex contaminants. Based on the tolerance and accumulation assays, pKHCG transgenic plants were more resistant to Hg/TCE complex pollutants and many folds higher in Hg/TCE-accumulation than the non-transgenic control plants in mixed contaminated soil. It is confirmed that GST and CYP2E1 co-expression may be a useful strategy to help achieve mixed heavy metal-organic pollutants phytoremediation. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Differentiation therapy revisited.

    PubMed

    de Thé, Hugues

    2018-02-01

    The concept of differentiation therapy emerged from the fact that hormones or cytokines may promote differentiation ex vivo, thereby irreversibly changing the phenotype of cancer cells. Its hallmark success has been the treatment of acute promyelocytic leukaemia (APL), a condition that is now highly curable by the combination of retinoic acid (RA) and arsenic. Recently, drugs that trigger differentiation in a variety of primary tumour cells have been identified, suggesting that they are clinically useful. This Opinion article analyses the basis for the clinical successes of RA or arsenic in APL by assessing the respective roles of terminal maturation and loss of self-renewal. By reviewing other successful examples of drug-induced tumour cell differentiation, novel approaches to transform differentiating drugs into more efficient therapies are proposed.

  15. Integrated data analysis identifies potential inducers and pathways during the endothelial differentiation of bone-marrow stromal cells by DNA methyltransferase inhibitor, 5-aza-2'-deoxycytidine.

    PubMed

    Xu, Rui; Chen, Wenbin; Zhang, Zhifen; Qiu, Yang; Wang, Yong; Zhang, Bingchang; Lu, Wei

    2018-05-30

    Bone-Marrow Stromal Cells (BMSCs)-derived vascular endothelial cells (VECs) is regarded as an important therapeutic strategy for spinal cord injury, disc degeneration, cerebral ischemic disease and diabetes. The change in DNA methylation level is essential for stem cell differentiation. However, the DNA methylation related mechanisms underlying the endothelial differentiation of BMSCs are not well understood. In this study, DNA methyltransferase inhibitor, 5-aza-2'-deoxycytidine (5-aza-dC) significantly elevated the endothelial markers expression (CD31/PECAM1, CD105/ENG, eNOS and VE-cadherin), as well as promoted the capacity of angiogenesis on Matrigel. The result of Alexa 488-Ac-LDL uptake assay indicated that the differentiation ratio of BMSCs into VECs was 68.7% in 5-azaz-dC induced differentiation. And then we screened differentiation inducers with altered expression patterns and DNA methylation levels in four important families (VEGF, ANG, FGF and ETS). By integrating these data, five endothelial differentiation inducers (VEGFA, ANGPT2, FGF2, FGF9 and ETS1) which were directly upregulated by 5-aza-dC and five indirect factors (FGF1, FGF3, ETS2, ETV1 and ETV4) were identified. These data suggested that 5-aza-dC is an excellent chemical molecule for BMSCs differentiation into functional VECs and also provided essential clues for DNA methylation related signaling during 5-aza-dC induced endothelial differentiation of BMSCs. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. 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.

  17. 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

  18. Heuristic Bayesian segmentation for discovery of coexpressed genes within genomic regions.

    PubMed

    Pehkonen, Petri; Wong, Garry; Törönen, Petri

    2010-01-01

    Segmentation aims to separate homogeneous areas from the sequential data, and plays a central role in data mining. It has applications ranging from finance to molecular biology, where bioinformatics tasks such as genome data analysis are active application fields. In this paper, we present a novel application of segmentation in locating genomic regions with coexpressed genes. We aim at automated discovery of such regions without requirement for user-given parameters. In order to perform the segmentation within a reasonable time, we use heuristics. Most of the heuristic segmentation algorithms require some decision on the number of segments. This is usually accomplished by using asymptotic model selection methods like the Bayesian information criterion. Such methods are based on some simplification, which can limit their usage. In this paper, we propose a Bayesian model selection to choose the most proper result from heuristic segmentation. Our Bayesian model presents a simple prior for the segmentation solutions with various segment numbers and a modified Dirichlet prior for modeling multinomial data. We show with various artificial data sets in our benchmark system that our model selection criterion has the best overall performance. The application of our method in yeast cell-cycle gene expression data reveals potential active and passive regions of the genome.

  19. Redox-mediated enrichment of self-renewing adult human pancreatic cells that possess endocrine differentiation potential.

    PubMed

    Linning, Katrina D; Tai, Mei-Hui; Madhukar, Burra V; Chang, C C; Reed, Donald N; Ferber, Sarah; Trosko, James E; Olson, L Karl

    2004-10-01

    The limited availability of transplantable human islets has stimulated the development of methods needed to isolate adult pancreatic stem/progenitor cells capable of self-renewal and endocrine differentiation. The objective of this study was to determine whether modulation of intracellular redox state with N-acetyl-L-cysteine (NAC) would allow for the propagation of pancreatic stem/progenitor cells from adult human pancreatic tissue. Cells were propagated from human pancreatic tissue using a serum-free, low-calcium medium supplemented with NAC and tested for their ability to differentiate when cultured under different growth conditions. Human pancreatic cell (HPC) cultures coexpressed alpha-amylase, albumin, vimentin, and nestin. The HPC cultures, however, did not express other genes associated with differentiated pancreatic exocrine, duct, or endocrine cells. A number of transcription factors involved in endocrine cell development including Beta 2, Islet-1, Nkx6.1, Pax4, and Pax6 were expressed at variable levels in HPC cultures. In contrast, pancreatic duodenal homeobox factor 1 (Pdx-1) expression was extremely low and at times undetectable. Overexpression of Pdx-1 in HPC cultures stimulated somatostatin, glucagon, and carbonic anhydrase expression but had no effect on insulin gene expression. HPC cultures could form 3-dimensional islet-like cell aggregates, and this was associated with expression of somatostatin and glucagon but not insulin. Cultivation of HPCs in a differentiation medium supplemented with nicotinamide, exendin-4, and/or LY294002, an inhibitor of phosphatidylinositol-3 kinase, stimulated expression of insulin mRNA and protein. These data support the use of intracellular redox modulation for the enrichment of pancreatic stem/progenitor cells capable of self-renewal and endocrine differentiation.

  20. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

    PubMed

    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

    2015-10-01

    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 coexpression may also be enriched for additional EOC risk associations. 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 coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset 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). 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. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.