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

Science.gov (United States)

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.

Inequalities and Duality in Gene Coexpression Networks of HIV-1 Infection Revealed by the Combination of the Double-Connectivity Approach and the Gini's Method

Directory of Open Access Journals (Sweden)

Chuang Ma

2011-01-01

Full Text Available The symbiosis (Sym and pathogenesis (Pat is a duality problem of microbial infection, including HIV/AIDS. Statistical analysis of inequalities and duality in gene coexpression networks (GCNs of HIV-1 infection may gain novel insights into AIDS. In this study, we focused on analysis of GCNs of uninfected subjects and HIV-1-infected patients at three different stages of viral infection based on data deposited in the GEO database of NCBI. The inequalities and duality in these GCNs were analyzed by the combination of the double-connectivity (DC approach and the Gini's method. DC analysis reveals that there are significant differences between positive and negative connectivity in HIV-1 stage-specific GCNs. The inequality measures of negative connectivity and edge weight are changed more significantly than those of positive connectivity and edge weight in GCNs from the HIV-1 uninfected to the AIDS stages. With the permutation test method, we identified a set of genes with significant changes in the inequality and duality measure of edge weight. Functional analysis shows that these genes are highly enriched for the immune system, which plays an essential role in the Sym-Pat duality (SPD of microbial infections. Understanding of the SPD problems of HIV-1 infection may provide novel intervention strategies for AIDS.

Elucidating gene function and function evolution through comparison of co-expression networks in plants

Directory of Open Access Journals (Sweden)

Marek eMutwil

2014-08-01

Full Text Available The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23. In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We show that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that, in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.

Global similarity and local divergence in human and mouse gene co-expression networks

Directory of Open Access Journals (Sweden)

Koonin Eugene V

2006-09-01

Full Text Available Abstract Background A genome-wide comparative analysis of human and mouse gene expression patterns was performed in order to evaluate the evolutionary divergence of mammalian gene expression. Tissue-specific expression profiles were analyzed for 9,105 human-mouse orthologous gene pairs across 28 tissues. Expression profiles were resolved into species-specific coexpression networks, and the topological properties of the networks were compared between species. Results At the global level, the topological properties of the human and mouse gene coexpression networks are, essentially, identical. For instance, both networks have topologies with small-world and scale-free properties as well as closely similar average node degrees, clustering coefficients, and path lengths. However, the human and mouse coexpression networks are highly divergent at the local level: only a small fraction ( Conclusion The dissonance between global versus local network divergence suggests that the interspecies similarity of the global network properties is of limited biological significance, at best, and that the biologically relevant aspects of the architectures of gene coexpression are specific and particular, rather than universal. Nevertheless, there is substantial evolutionary conservation of the local network structure which is compatible with the notion that gene coexpression networks are subject to purifying selection.

Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity.

Science.gov (United States)

Penrod, Nadia M; Greene, Casey S; Moore, Jason H

2014-01-01

Molecularly targeted drugs promise a safer and more effective treatment modality than conventional chemotherapy for cancer patients. However, tumors are dynamic systems that readily adapt to these agents activating alternative survival pathways as they evolve resistant phenotypes. Combination therapies can overcome resistance but finding the optimal combinations efficiently presents a formidable challenge. Here we introduce a new paradigm for the design of combination therapy treatment strategies that exploits the tumor adaptive process to identify context-dependent essential genes as druggable targets. We have developed a framework to mine high-throughput transcriptomic data, based on differential coexpression and Pareto optimization, to investigate drug-induced tumor adaptation. We use this approach to identify tumor-essential genes as druggable candidates. We apply our method to a set of ER(+) breast tumor samples, collected before (n = 58) and after (n = 60) neoadjuvant treatment with the aromatase inhibitor letrozole, to prioritize genes as targets for combination therapy with letrozole treatment. We validate letrozole-induced tumor adaptation through coexpression and pathway analyses in an independent data set (n = 18). We find pervasive differential coexpression between the untreated and letrozole-treated tumor samples as evidence of letrozole-induced tumor adaptation. Based on patterns of coexpression, we identify ten genes as potential candidates for combination therapy with letrozole including EPCAM, a letrozole-induced essential gene and a target to which drugs have already been developed as cancer therapeutics. Through replication, we validate six letrozole-induced coexpression relationships and confirm the epithelial-to-mesenchymal transition as a process that is upregulated in the residual tumor samples following letrozole treatment. To derive the greatest benefit from molecularly targeted drugs it is critical to design combination

Characterization of chemically induced liver injuries using gene co-expression modules.

Directory of Open Access Journals (Sweden)

Gregory J Tawa

Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks

Directory of Open Access Journals (Sweden)

Kohane Isaac S

2005-09-01

Full Text Available Abstract Background Biological processes are carried out by coordinated modules of interacting molecules. As clustering methods demonstrate that genes with similar expression display increased likelihood of being associated with a common functional module, networks of coexpressed genes provide one framework for assigning gene function. This has informed the guilt-by-association (GBA heuristic, widely invoked in functional genomics. Yet although the idea of GBA is accepted, the breadth of GBA applicability is uncertain. Results We developed methods to systematically explore the breadth of GBA across a large and varied corpus of expression data to answer the following question: To what extent is the GBA heuristic broadly applicable to the transcriptome and conversely how broadly is GBA captured by a priori knowledge represented in the Gene Ontology (GO? Our study provides an investigation of the functional organization of five coexpression networks using data from three mammalian organisms. Our method calculates a probabilistic score between each gene and each Gene Ontology category that reflects coexpression enrichment of a GO module. For each GO category we use Receiver Operating Curves to assess whether these probabilistic scores reflect GBA. This methodology applied to five different coexpression networks demonstrates that the signature of guilt-by-association is ubiquitous and reproducible and that the GBA heuristic is broadly applicable across the population of nine hundred Gene Ontology categories. We also demonstrate the existence of highly reproducible patterns of coexpression between some pairs of GO categories. Conclusion We conclude that GBA has universal value and that transcriptional control may be more modular than previously realized. Our analyses also suggest that methodologies combining coexpression measurements across multiple genes in a biologically-defined module can aid in characterizing gene function or in characterizing

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Directory of Open Access Journals (Sweden)

Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Local coexpression domains of two to four genes in the genome of Arabidopsis

NARCIS (Netherlands)

Ren, X.Y.; Fiers, M.W.E.J.; Stiekema, W.J.; Nap, J.P.H.

2005-01-01

Expression of genes in eukaryotic genomes is known to cluster, but cluster size is generally loosely defined and highly variable. We have here taken a very strict definition of cluster as sets of physically adjacent genes that are highly coexpressed and form so-called local coexpression domains. The

Genes2FANs: connecting genes through functional association networks

Science.gov (United States)

2012-01-01

Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

Directory of Open Access Journals (Sweden)

Sapna Kumari

Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice.

Directory of Open Access Journals (Sweden)

Rafi Shaik

Full Text Available Plants are simultaneously exposed to multiple stresses resulting in enormous changes in the molecular landscape within the cell. Identification and characterization of the synergistic and antagonistic components of stress response mechanisms contributing to the cross talk between stresses is of high priority to explore and enhance multiple stress responses. To this end, we performed meta-analysis of drought (abiotic, bacterial (biotic stress response in rice and Arabidopsis by analyzing a total of 386 microarray samples belonging to 20 microarray studies and identified approximately 3100 and 900 DEGs in rice and Arabidopsis, respectively. About 38.5% (1214 and 28.7% (272 DEGs were common to drought and bacterial stresses in rice and Arabidopsis, respectively. A majority of these common DEGs showed conserved expression status in both stresses. Gene ontology enrichment analysis clearly demarcated the response and regulation of various plant hormones and related biological processes. Fatty acid metabolism and biosynthesis of alkaloids were upregulated and, nitrogen metabolism and photosynthesis was downregulated in both stress conditions. WRKY transcription family genes were highly enriched in all upregulated gene sets while 'CO-like' TF family showed inverse relationship of expression between drought and bacterial stresses. Weighted gene co-expression network analysis divided DEG sets into multiple modules that show high co-expression and identified stress specific hub genes with high connectivity. Detection of consensus modules based on DEGs common to drought and bacterial stress revealed 9 and 4 modules in rice and Arabidopsis, respectively, with conserved and reversed co-expression patterns.

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

Science.gov (United States)

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...

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

Directory of Open Access Journals (Sweden)

Meimei Liang

Full Text Available 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.

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

Science.gov (United States)

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

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean) Cattle.

Science.gov (United States)

Lim, Dajeong; Lee, Seung-Hwan; Kim, Nam-Kuk; Cho, Yong-Min; Chai, Han-Ha; Seong, Hwan-Hoo; Kim, Heebal

2013-01-01

Marbling (intramuscular fat) is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the 'marbling score' trait and systemically analyzed the network topology in Hanwoo (Korean cattle). As a result, we determined 3 modules (gene groups) that showed statistically significant results for marbling score. In particular, one module (denoted as red) has a statistically significant result for marbling score (p = 0.008) and intramuscular fat (p = 0.02) and water capacity (p = 0.006). From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA) have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean Cattle

Directory of Open Access Journals (Sweden)

Dajeong Lim

2013-01-01

Full Text Available Marbling (intramuscular fat is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the ‘marbling score’ trait and systemically analyzed the network topology in Hanwoo (Korean cattle. As a result, we determined 3 modules (gene groups that showed statistically significant results for marbling score. In particular, one module (denoted as red has a statistically significant result for marbling score (p = 0.008 and intramuscular fat (p = 0.02 and water capacity (p = 0.006. From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Analysis of the relationship between coexpression domains and chromatin 3D organization.

Directory of Open Access Journals (Sweden)

María E Soler-Oliva

2017-09-01

Full Text Available Gene order is not random in eukaryotic chromosomes, and co-regulated genes tend to be clustered. The mechanisms that determine co-regulation of large regions of the genome and its connection with chromatin three-dimensional (3D organization are still unclear however. Here we have adapted a recently described method for identifying chromatin topologically associating domains (TADs to identify coexpression domains (which we term "CODs". Using human normal breast and breast cancer RNA-seq data, we have identified approximately 500 CODs. CODs in the normal and breast cancer genomes share similar characteristics but differ in their gene composition. COD genes have a greater tendency to be coexpressed with genes that reside in other CODs than with non-COD genes. Such inter-COD coexpression is maintained over large chromosomal distances in the normal genome but is partially lost in the cancer genome. Analyzing the relationship between CODs and chromatin 3D organization using Hi-C contact data, we find that CODs do not correspond to TADs. In fact, intra-TAD gene coexpression is the same as random for most chromosomes. However, the contact profile is similar between gene pairs that reside either in the same COD or in coexpressed CODs. These data indicate that co-regulated genes in the genome present similar patterns of contacts irrespective of the frequency of physical chromatin contacts between them.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

OpenAIRE

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea 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 revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flav...

The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

DEFF Research Database (Denmark)

Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

2006-01-01

be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

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

Directory of Open Access Journals (Sweden)

Bao-Hong Liu

2017-01-01

Full Text Available 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.

A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

Directory of Open Access Journals (Sweden)

Mao Yu

2009-07-01

Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene

Directory of Open Access Journals (Sweden)

Raghunath Satpathy

2015-01-01

Full Text Available Context: Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential. Aims: In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets. Materials and Methods: In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3. Statistical Analysis Used: Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold. Results: The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology. Conclusions: The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis.

Novel Approach for Coexpression Analysis of E2F1–3 and MYC Target Genes in Chronic Myelogenous Leukemia

Directory of Open Access Journals (Sweden)

Fengfeng Wang

2014-01-01

Full Text Available Background. Chronic myelogenous leukemia (CML is characterized by tremendous amount of immature myeloid cells in the blood circulation. E2F1–3 and MYC are important transcription factors that form positive feedback loops by reciprocal regulation in their own transcription processes. Since genes regulated by E2F1–3 or MYC are related to cell proliferation and apoptosis, we wonder if there exists difference in the coexpression patterns of genes regulated concurrently by E2F1–3 and MYC between the normal and the CML states. Results. We proposed a method to explore the difference in the coexpression patterns of those candidate target genes between the normal and the CML groups. A disease-specific cutoff point for coexpression levels that classified the coexpressed gene pairs into strong and weak coexpression classes was identified. Our developed method effectively identified the coexpression pattern differences from the overall structure. Moreover, we found that genes related to the cell adhesion and angiogenesis properties were more likely to be coexpressed in the normal group when compared to the CML group. Conclusion. Our findings may be helpful in exploring the underlying mechanisms of CML and provide useful information in cancer treatment.

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

Science.gov (United States)

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 acidity. Overall, this study provides important insight into the Ma1-mediated gene network controlling acidity in mature apple fruit of diverse genetic background.

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

Science.gov (United States)

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/ .

Gene Coexpression Analysis Reveals Complex Metabolism of the Monoterpene Alcohol Linalool in Arabidopsis FlowersW

NARCIS (Netherlands)

Ginglinger, J.F.; Boachon, B.; Hofer, R.; Paetz, C.; Kollner, T.G.; Miesch, L.; Lugan, R.; Baltenweck, R.; Mutterer, J.; Ullman, P.; Verstappen, F.W.A.; Bouwmeester, H.J.

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

Characterization of Genes for Beef Marbling Based on Applying Gene Coexpression Network

Directory of Open Access Journals (Sweden)

Dajeong Lim

2014-01-01

Full Text Available Marbling is an important trait in characterization beef quality and a major factor for determining the price of beef in the Korean beef market. In particular, marbling is a complex trait and needs a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with marbling, we used a weighted gene coexpression network analysis from the expression value of bovine genes. Hub genes were identified; they were topologically centered with large degree and BC values in the global network. We performed gene expression analysis to detect candidate genes in M. longissimus with divergent marbling phenotype (marbling scores 2 to 7 using qRT-PCR. The results demonstrate that transmembrane protein 60 (TMEM60 and dihydropyrimidine dehydrogenase (DPYD are associated with increasing marbling fat. We suggest that the network-based approach in livestock may be an important method for analyzing the complex effects of candidate genes associated with complex traits like marbling or tenderness.

Two novel antimicrobial defensins from rice identified by gene coexpression network analyses.

Science.gov (United States)

Tantong, Supaluk; Pringsulaka, Onanong; Weerawanich, Kamonwan; Meeprasert, Arthitaya; Rungrotmongkol, Thanyada; Sarnthima, Rakrudee; Roytrakul, Sittiruk; Sirikantaramas, Supaart

2016-10-01

Defensins form an antimicrobial peptides (AMP) family, and have been widely studied in various plants because of their considerable inhibitory functions. However, their roles in rice (Oryza sativa L.) have not been characterized, even though rice is one of the most important staple crops that is susceptible to damaging infections. Additionally, a previous study identified 598 rice genes encoding cysteine-rich peptides, suggesting there are several uncharacterized AMPs in rice. We performed in silico gene expression and coexpression network analyses of all genes encoding defensin and defensin-like peptides, and determined that OsDEF7 and OsDEF8 are coexpressed with pathogen-responsive genes. Recombinant OsDEF7 and OsDEF8 could form homodimers. They inhibited the growth of the bacteria Xanthomonas oryzae pv. oryzae, X. oryzae pv. oryzicola, and Erwinia carotovora subsp. atroseptica with minimum inhibitory concentration (MIC) ranging from 0.6 to 63μg/mL. However, these OsDEFs are weakly active against the phytopathogenic fungi Helminthosporium oryzae and Fusarium oxysporum f.sp. cubense. This study describes a useful method for identifying potential plant AMPs with biological activities. Copyright © 2016 Elsevier Inc. All rights reserved.

Guidance for RNA-seq co-expression network construction and analysis: safety in numbers.

Science.gov (United States)

Ballouz, S; Verleyen, W; Gillis, J

2015-07-01

RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks. We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were >20 samples with read depth >10 M per sample. While the aggregate network constructed shows good performance (area under the receiver operator characteristic curve ∼0.71), the dependency on number of experiments used is nearly identical to that present in microarrays, suggesting thousands of samples are required to obtain 'gold-standard' co-expression. We find a major topological difference between RNA-seq and microarray co-expression in the form of low overlaps between hub-like genes from each network due to changes in the correlation of expression noise within each technology. jgillis@cshl.edu or sballouz@cshl.edu Networks are available at: http://gillislab.labsites.cshl.edu/supplements/rna-seq-networks/ and supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Chronic ethanol exposure produces time- and brain region-dependent changes in gene coexpression networks.

Directory of Open Access Journals (Sweden)

Elizabeth A Osterndorff-Kahanek

Full Text Available 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.

Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

Directory of Open Access Journals (Sweden)

DeYoung Joseph

2009-08-01

Full Text Available Abstract Background Amyotrophic Lateral Sclerosis (ALS is a lethal disorder characterized by progressive degeneration of motor neurons in the brain and spinal cord. Diagnosis is mainly based on clinical symptoms, and there is currently no therapy to stop the disease or slow its progression. Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients. Results Our transcriptional study showed dramatic changes in blood of ALS patients; 2,300 probes (9.4% showed significant differential expression in a discovery dataset consisting of 30 ALS patients and 30 healthy controls. Weighted gene co-expression network analysis (WGCNA was used to find disease-related networks (modules and disease related hub genes. Two large co-expression modules were found to be associated with ALS. Our findings were replicated in a second (30 patients and 30 controls and third dataset (63 patients and 63 controls, thereby demonstrating a highly significant and consistent association of two large co-expression modules with ALS disease status. Ingenuity Pathway Analysis of the ALS related module genes implicates enrichment of functional categories related to genetic disorders, neurodegeneration of the nervous system and inflammatory disease. The ALS related modules contain a number of candidate genes possibly involved in pathogenesis of ALS. Conclusion This first large-scale blood gene expression study in ALS observed distinct patterns between cases and controls which may provide opportunities for biomarker development as well as new insights into the molecular mechanisms of the disease.

A contribution to the study of plant development evolution based on gene co-expression networks

Directory of Open Access Journals (Sweden)

Francisco J. Romero-Campero

2013-08-01

Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

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

Science.gov (United States)

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.

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes.

Directory of Open Access Journals (Sweden)

Simone de Jong

Full Text Available 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.

A Predictive Coexpression Network Identifies Novel Genes Controlling the Seed-to-Seedling Phase Transition in Arabidopsis thaliana.

Science.gov (United States)

Silva, Anderson Tadeu; Ribone, Pamela A; Chan, Raquel L; Ligterink, Wilco; Hilhorst, Henk W M

2016-04-01

The transition from a quiescent dry seed to an actively growing photoautotrophic seedling is a complex and crucial trait for plant propagation. This study provides a detailed description of global gene expression in seven successive developmental stages of seedling establishment in Arabidopsis (Arabidopsis thaliana). Using the transcriptome signature from these developmental stages, we obtained a coexpression gene network that highlights interactions between known regulators of the seed-to-seedling transition and predicts the functions of uncharacterized genes in seedling establishment. The coexpressed gene data sets together with the transcriptional module indicate biological functions related to seedling establishment. Characterization of the homeodomain leucine zipper I transcription factor AtHB13, which is expressed during the seed-to-seedling transition, demonstrated that this gene regulates some of the network nodes and affects late seedling establishment. Knockout mutants for athb13 showed increased primary root length as compared with wild-type (Columbia-0) seedlings, suggesting that this transcription factor is a negative regulator of early root growth, possibly repressing cell division and/or cell elongation or the length of time that cells elongate. The signal transduction pathways present during the early phases of the seed-to-seedling transition anticipate the control of important events for a vigorous seedling, such as root growth. This study demonstrates that a gene coexpression network together with transcriptional modules can provide insights that are not derived from comparative transcript profiling alone. © 2016 American Society of Plant Biologists. All Rights Reserved.

Gene co-expression networks and profiles reveal potential biomarkers of boar taint in pigs

DEFF Research Database (Denmark)

Drag, Markus; Skinkyté-Juskiené, R.; Do, Duy Ngoc

synthesis. In testis, >80 DE genes were functionally classified by the PANTHER tool to “Gonadotropin releasing hormone receptor” and “Wnt signaling” pathways which play a role in reproductive maturation and proliferation of spermatogonia, respectively. WGCNA was used to build co-expression modules...

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

Science.gov (United States)

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

RNA Sequencing and Coexpression Analysis Reveal Key Genes Involved in α-Linolenic Acid Biosynthesis in Perilla frutescens Seed

Directory of Open Access Journals (Sweden)

Tianyuan Zhang

2017-11-01

Full Text Available Perilla frutescen is used as traditional food and medicine in East Asia. Its seeds contain high levels of α-linolenic acid (ALA, which is important for health, but is scarce in our daily meals. Previous reports on RNA-seq of perilla seed had identified fatty acid (FA and triacylglycerol (TAG synthesis genes, but the underlying mechanism of ALA biosynthesis and its regulation still need to be further explored. So we conducted Illumina RNA-sequencing in seven temporal developmental stages of perilla seeds. Sequencing generated a total of 127 million clean reads, containing 15.88 Gb of valid data. The de novo assembly of sequence reads yielded 64,156 unigenes with an average length of 777 bp. A total of 39,760 unigenes were annotated and 11,693 unigenes were found to be differentially expressed in all samples. According to Kyoto Encyclopedia of Genes and Genomes (KEGG pathway analysis, 486 unigenes were annotated in the “lipid metabolism” pathway. Of these, 150 unigenes were found to be involved in fatty acid (FA biosynthesis and triacylglycerol (TAG assembly in perilla seeds. A coexpression analysis showed that a total of 104 genes were highly coexpressed (r > 0.95. The coexpression network could be divided into two main subnetworks showing over expression in the medium or earlier and late phases, respectively. In order to identify the putative regulatory genes, a transcription factor (TF analysis was performed. This led to the identification of 45 gene families, mainly including the AP2-EREBP, bHLH, MYB, and NAC families, etc. After coexpression analysis of TFs with highly expression of FAD2 and FAD3 genes, 162 TFs were found to be significantly associated with two FAD genes (r > 0.95. Those TFs were predicted to be the key regulatory factors in ALA biosynthesis in perilla seed. The qRT-PCR analysis also verified the relevance of expression pattern between two FAD genes and partial candidate TFs. Although it has been reported that some TFs

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

Science.gov (United States)

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.

Dissection of regulatory networks that are altered in disease via differential co-expression.

Directory of Open Access Journals (Sweden)

David Amar

Full Text Available Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks. Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples. We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer's disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.

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

Science.gov (United States)

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/.

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

Science.gov (United States)

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

2009-02-01

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

G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

Directory of Open Access Journals (Sweden)

Lemay Danielle G

2012-09-01

Full Text Available Abstract Background 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 Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The

Bioinformatics Data Mining Approach Suggests Coexpression of AGTPBP1 with an ALS-linked Gene C9orf72

Directory of Open Access Journals (Sweden)

Shouta Kitano

2015-01-01

Full Text Available Background Expanded GGGGCC hexanucleotide repeats located in the noncoding region of the chromosome 9 open reading frame 72 ( C9orf72 gene represent the most common genetic abnormality for familial and sporadic amyotrophic lateral sclerosis (ALS and frontotemporal dementia (FTD. Formation of nuclear RNA foci, accumulation of repeat-associated non-ATG-translated dipeptide-repeat proteins, and haploinsufficiency of C9orf72 are proposed for pathological mechanisms of C9ALS/FTD. However, at present, the physiological function of C9orf72 remains largely unknown. Methods By searching on a bioinformatics database named COXPRESdb composed of the comprehensive gene coexpression data, we studied potential C9orf72 interactors. Results We identified the ATP/GTP binding protein 1 ( AGTPBP1 gene alternatively named NNA1 encoding a cytosolic carboxypeptidase whose mutation is causative of the degeneration of Purkinje cells and motor neurons as the most significant gene coexpressed with C9orf72. We verified coexpression and interaction of AGTPBP1 and C9orf72 in transfected cells by immunoprecipitation and in neurons of the human brain by double-labeling immunohistochemistry. Furthermore, we found a positive correlation between AGTPBP1 and C9orf72 mRNA expression levels in the set of 21 human brains examined. Conclusions These results suggest that AGTPBP1 serves as a C9orf72 interacting partner that plays a role in the regulation of neuronal function in a coordinated manner within the central nervous system.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Jie Luo

2018-04-01

Full Text Available 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.

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

Science.gov (United States)

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.

Matrix factorization reveals aging-specific co-expression gene modules in the fat and muscle tissues in nonhuman primates

Science.gov (United States)

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.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

Science.gov (United States)

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.

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

Science.gov (United States)

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.

Coexpression of nuclear receptors and histone methylation modifying genes in the testis: implications for endocrine disruptor modes of action.

Directory of Open Access Journals (Sweden)

Alison M Anderson

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

Science.gov (United States)

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea 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 revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus. PMID:27917194

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

Science.gov (United States)

Musungu, Bryan M; Bhatnagar, Deepak; Brown, Robert L; Payne, Gary A; OBrian, Greg; Fakhoury, Ahmad M; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea 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 revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus , a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays , and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays , there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus . Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus .

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

Directory of Open Access Journals (Sweden)

Saurav Mallik

2017-12-01

Full Text Available 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.

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

Science.gov (United States)

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.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

Science.gov (United States)

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

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

DEFF Research Database (Denmark)

Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

2014-01-01

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...... (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P ... 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...

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

The arabidopsis wall associated kinase-like 10 gene encodes a functional guanylyl cyclase and is co-expressed with pathogen defense related genes

KAUST Repository

Meier, Stuart; Ruzvidzo, Oziniel; Morse, Monique; Donaldson, Lara; Kwezi, Lusisizwe; Gehring, Christoph A

2010-01-01

Background: Second messengers have a key role in linking environmental stimuli to physiological responses. One such messenger, guanosine 3?,5?-cyclic monophosphate (cGMP), has long been known to be an essential signaling molecule in many different physiological processes in higher plants, including biotic stress responses. To date, however, the guanylyl cyclase (GC) enzymes that catalyze the formation of cGMP from GTP have largely remained elusive in higher plants. Principal Findings: We have identified an Arabidopsis receptor type wall associated kinase-like molecule (AtWAKL10) as a candidate GC and provide experimental evidence to show that the intracellular domain of AtWAKL10431-700 can generate cGMP in vitro. Further, we also demonstrate that the molecule has kinase activity indicating that AtWAKL10 is a twin-domain catalytic protein. A co-expression and stimulus-specific expression analysis revealed that AtWAKL10 is consistently coexpressed with well characterized pathogen defense related genes and along with these genes is induced early and sharply in response to a range of pathogens and their elicitors. Conclusions: We demonstrate that AtWAKL10 is a twin-domain, kinase-GC signaling molecule that may function in biotic stress responses that are critically dependent on the second messenger cGMP. © 2010 Meier et al.

The arabidopsis wall associated kinase-like 10 gene encodes a functional guanylyl cyclase and is co-expressed with pathogen defense related genes

KAUST Repository

Meier, Stuart

2010-01-26

Background: Second messengers have a key role in linking environmental stimuli to physiological responses. One such messenger, guanosine 3?,5?-cyclic monophosphate (cGMP), has long been known to be an essential signaling molecule in many different physiological processes in higher plants, including biotic stress responses. To date, however, the guanylyl cyclase (GC) enzymes that catalyze the formation of cGMP from GTP have largely remained elusive in higher plants. Principal Findings: We have identified an Arabidopsis receptor type wall associated kinase-like molecule (AtWAKL10) as a candidate GC and provide experimental evidence to show that the intracellular domain of AtWAKL10431-700 can generate cGMP in vitro. Further, we also demonstrate that the molecule has kinase activity indicating that AtWAKL10 is a twin-domain catalytic protein. A co-expression and stimulus-specific expression analysis revealed that AtWAKL10 is consistently coexpressed with well characterized pathogen defense related genes and along with these genes is induced early and sharply in response to a range of pathogens and their elicitors. Conclusions: We demonstrate that AtWAKL10 is a twin-domain, kinase-GC signaling molecule that may function in biotic stress responses that are critically dependent on the second messenger cGMP. © 2010 Meier et al.

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

Science.gov (United States)

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

Coexpression of bile salt hydrolase gene and catalase gene remarkably improves oxidative stress and bile salt resistance in Lactobacillus casei.

Science.gov (United States)

Wang, Guohong; Yin, Sheng; An, Haoran; Chen, Shangwu; Hao, Yanling

2011-08-01

Lactic acid bacteria (LAB) encounter various types of stress during industrial processes and gastrointestinal transit. Catalase (CAT) and bile salt hydrolase (BSH) can protect bacteria from oxidative stress or damage caused by bile salts by decomposing hydrogen peroxide (H(2)O(2)) or deconjugating the bile salts, respectively. Lactobacillus casei is a valuable probiotic strain and is often deficient in both CAT and BSH. In order to improve the resistance of L. casei to both oxidative and bile salts stress, the catalase gene katA from L. sakei and the bile salt hydrolase gene bsh1 from L. plantarum were coexpressed in L. casei HX01. The enzyme activities of CAT and BSH were 2.41 μmol H(2)O(2)/min/10(8) colony-forming units (CFU) and 2.11 μmol glycine/min/ml in the recombinant L. casei CB, respectively. After incubation with 8 mM H(2)O(2), survival ratio of L. casei CB was 40-fold higher than that of L. casei CK. Treatment of L. casei CB with various concentrations of sodium glycodeoxycholate (GDCA) showed that ~10(5) CFU/ml cells survived after incubation with 0.5% GDCA, whereas almost all the L. casei CK cells were killed when treaded with 0.4% GDCA. These results indicate that the coexpression of CAT and BSH confers high-level resistance to both oxidative and bile salts stress conditions in L. casei HX01.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Construction and identification of double-gene co-expression vector with radiation-inducible human TRAIL and endostatin

International Nuclear Information System (INIS)

Li Yanbo; Guo Caixia; Gong Pingsheng; Liu Yang; Liangshuo; Wang Hongfang; Wang Jianfeng; Gong Shouliang

2010-01-01

Objective: To construct a recombinant plasmid pshuttle-Egr1-shTRAIL-shES containing tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and endostatin double genes. Methods: The secretary endostatin gene (shES) fragment was amplified from the pMD19T-endostatin vector by PCR. The shES gene was ligated to pMD19Tand sequenced. Finally, using the gene recombinant technique, the recombinant plasmid pshuttle-Egr1- shTRAIL-shES with radiation-inducible Egr1 promoter, secretary TRAIL and endostatin double-gene was constructed. Results: The sequence of the shES gene was in concordance with that anticipated indicating shES gene was acquired successfully.Moreover, the results acquired by PCR and restrictive digestion identification of the recombinant plasmid pshuttle-Egr1-shTRAIL-shES and all the vectors refered to its construction confirmed that pshuttle-Egr1-shTRAIL-shES was constructed correctly. Conclusion: The radiation-inducible double-gene co-expression vector pshuttle-Egr1-shTRAIL-shES is constructed successfully, which would set the experimental foundation for further study on the anti-tumor effect of TRAIL and endostatin double-gene-radiotherapy and its related mechanisms. (authors)

Co-expression of interleukin 12 enhances antitumor effects of a novel chimeric promoter-mediated suicide gene therapy in an immunocompetent mouse model

International Nuclear Information System (INIS)

Xu, Yu; Liu, Zhengchun; Kong, Haiyan; Sun, Wenjie; Liao, Zhengkai; Zhou, Fuxiang; Xie, Conghua

2011-01-01

Highlights: → A novel chimeric promoter consisting of CArG element and hTERT promoter was developed. → The promoter was characterized with radiation-inducibility and tumor-specificity. → Suicide gene system driven by the promoter showed remarkable cytotoxicity in vitro. → Co-expression of IL12 enhanced the promoter mediated suicide gene therapy in vivo. -- Abstract: The human telomerase reverse transcriptase (hTERT) promoter has been widely used in target gene therapy of cancer. However, low transcriptional activity limited its clinical application. Here, we designed a novel dual radiation-inducible and tumor-specific promoter system consisting of CArG elements and the hTERT promoter, resulting in increased expression of reporter genes after gamma-irradiation. Therapeutic and side effects of adenovirus-mediated horseradish peroxidase (HRP)/indole-3-acetic (IAA) system downstream of the chimeric promoter were evaluated in mice bearing Lewis lung carcinoma, combining with or without adenovirus-mediated interleukin 12 (IL12) gene driven by the cytomegalovirus promoter. The combination treatment showed more effective suppression of tumor growth than those with single agent alone, being associated with pronounced intratumoral T-lymphocyte infiltration and minor side effects. Our results suggest that the combination treatment with HRP/IAA system driven by the novel chimeric promoter and the co-expression of IL12 might be an effective and safe target gene therapy strategy of cancer.

Co-expression of interleukin 12 enhances antitumor effects of a novel chimeric promoter-mediated suicide gene therapy in an immunocompetent mouse model

Energy Technology Data Exchange (ETDEWEB)

Xu, Yu, E-mail: xuyu1001@gmail.com [Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan 430071 (China); Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Liu, Zhengchun, E-mail: l135027@126.com [Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Kong, Haiyan, E-mail: suppleant@163.com [Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Sun, Wenjie, E-mail: wendy11240325@163.com [Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan 430071 (China); Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Liao, Zhengkai, E-mail: fastbeta@gmail.com [Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan 430071 (China); Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Zhou, Fuxiang, E-mail: happyzhoufx@sina.com [Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan 430071 (China); Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); Xie, Conghua, E-mail: chxie_65@hotmail.com [Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan 430071 (China); Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, 169 Donghu Road, Wuhan 430071 (China); and others

2011-09-09

Highlights: {yields} A novel chimeric promoter consisting of CArG element and hTERT promoter was developed. {yields} The promoter was characterized with radiation-inducibility and tumor-specificity. {yields} Suicide gene system driven by the promoter showed remarkable cytotoxicity in vitro. {yields} Co-expression of IL12 enhanced the promoter mediated suicide gene therapy in vivo. -- Abstract: The human telomerase reverse transcriptase (hTERT) promoter has been widely used in target gene therapy of cancer. However, low transcriptional activity limited its clinical application. Here, we designed a novel dual radiation-inducible and tumor-specific promoter system consisting of CArG elements and the hTERT promoter, resulting in increased expression of reporter genes after gamma-irradiation. Therapeutic and side effects of adenovirus-mediated horseradish peroxidase (HRP)/indole-3-acetic (IAA) system downstream of the chimeric promoter were evaluated in mice bearing Lewis lung carcinoma, combining with or without adenovirus-mediated interleukin 12 (IL12) gene driven by the cytomegalovirus promoter. The combination treatment showed more effective suppression of tumor growth than those with single agent alone, being associated with pronounced intratumoral T-lymphocyte infiltration and minor side effects. Our results suggest that the combination treatment with HRP/IAA system driven by the novel chimeric promoter and the co-expression of IL12 might be an effective and safe target gene therapy strategy of cancer.

Gene Coexpression and Evolutionary Conservation Analysis of the Human Preimplantation Embryos

Directory of Open Access Journals (Sweden)

Tiancheng Liu

2015-01-01

Full Text Available Evolutionary developmental biology (EVO-DEVO tries to decode evolutionary constraints on the stages of embryonic development. Two models—the “funnel-like” model and the “hourglass” model—have been proposed by investigators to illustrate the fluctuation of selective pressure on these stages. However, selective indices of stages corresponding to mammalian preimplantation embryonic development (PED were undetected in previous studies. Based on single cell RNA sequencing of stages during human PED, we used coexpression method to identify gene modules activated in each of these stages. Through measuring the evolutionary indices of gene modules belonging to each stage, we observed change pattern of selective constraints on PED for the first time. The selective pressure decreases from the zygote stage to the 4-cell stage and increases at the 8-cell stage and then decreases again from 8-cell stage to the late blastocyst stages. Previous EVO-DEVO studies concerning the whole embryo development neglected the fluctuation of selective pressure in these earlier stages, and the fluctuation was potentially correlated with events of earlier stages, such as zygote genome activation (ZGA. Such oscillation in an earlier stage would further affect models of the evolutionary constraints on whole embryo development. Therefore, these earlier stages should be measured intensively in future EVO-DEVO studies.

Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks.

Directory of Open Access Journals (Sweden)

Nicholas J Hudson

Full Text Available BACKGROUND: Despite modern technologies and novel computational approaches, decoding causal transcriptional regulation remains challenging. This is particularly true for less well studied organisms and when only gene expression data is available. In muscle a small number of well characterised transcription factors are proposed to regulate development. Therefore, muscle appears to be a tractable system for proposing new computational approaches. METHODOLOGY/PRINCIPAL FINDINGS: Here we report a simple algorithm that asks "which transcriptional regulator has the highest average absolute co-expression correlation to the genes in a co-expression module?" It correctly infers a number of known causal regulators of fundamental biological processes, including cell cycle activity (E2F1, glycolysis (HLF, mitochondrial transcription (TFB2M, adipogenesis (PIAS1, neuronal development (TLX3, immune function (IRF1 and vasculogenesis (SOX17, within a skeletal muscle context. However, none of the canonical pro-myogenic transcription factors (MYOD1, MYOG, MYF5, MYF6 and MEF2C were linked to muscle structural gene expression modules. Co-expression values were computed using developing bovine muscle from 60 days post conception (early foetal to 30 months post natal (adulthood for two breeds of cattle, in addition to a nutritional comparison with a third breed. A number of transcriptional landscapes were constructed and integrated into an always correlated landscape. One notable feature was a 'metabolic axis' formed from glycolysis genes at one end, nuclear-encoded mitochondrial protein genes at the other, and centrally tethered by mitochondrially-encoded mitochondrial protein genes. CONCLUSIONS/SIGNIFICANCE: The new module-to-regulator algorithm complements our recently described Regulatory Impact Factor analysis. Together with a simple examination of a co-expression module's contents, these three gene expression approaches are starting to illuminate the in vivo

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

Science.gov (United States)

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

2012-07-15

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

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

Directory of Open Access Journals (Sweden)

Luis Guillermo Leal

2014-10-01

Full Text Available 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.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

Science.gov (United States)

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.

Ethylene-Related Gene Expression Networks in Wood Formation

Directory of Open Access Journals (Sweden)

Carolin Seyfferth

2018-03-01

Full Text Available Thickening of tree stems is the result of secondary growth, accomplished by the meristematic activity of the vascular cambium. Secondary growth of the stem entails developmental cascades resulting in the formation of secondary phloem outwards and secondary xylem (i.e., wood inwards of the stem. Signaling and transcriptional reprogramming by the phytohormone ethylene modifies cambial growth and cell differentiation, but the molecular link between ethylene and secondary growth remains unknown. We addressed this shortcoming by analyzing expression profiles and co-expression networks of ethylene pathway genes using the AspWood transcriptome database which covers all stages of secondary growth in aspen (Populus tremula stems. ACC synthase expression suggests that the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC is synthesized during xylem expansion and xylem cell maturation. Ethylene-mediated transcriptional reprogramming occurs during all stages of secondary growth, as deduced from AspWood expression profiles of ethylene-responsive genes. A network centrality analysis of the AspWood dataset identified EIN3D and 11 ERFs as hubs. No overlap was found between the co-expressed genes of the EIN3 and ERF hubs, suggesting target diversification and hence independent roles for these transcription factor families during normal wood formation. The EIN3D hub was part of a large co-expression gene module, which contained 16 transcription factors, among them several new candidates that have not been earlier connected to wood formation and a VND-INTERACTING 2 (VNI2 homolog. We experimentally demonstrated Populus EIN3D function in ethylene signaling in Arabidopsis thaliana. The ERF hubs ERF118 and ERF119 were connected on the basis of their expression pattern and gene co-expression module composition to xylem cell expansion and secondary cell wall formation, respectively. We hereby establish data resources for ethylene-responsive genes and

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

Directory of Open Access Journals (Sweden)

Kai Wang

2009-12-01

Full Text Available Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis

Directory of Open Access Journals (Sweden)

Zhou X

2018-05-01

Full Text Available Xian-guo Zhou,1,2,* Xiao-liang Huang,1,2,* Si-yuan Liang,1–3 Shao-mei Tang,1,2 Si-kao Wu,1,2 Tong-tong Huang,1,2 Zeng-nan Mo,1,2,4 Qiu-yan Wang1,2,5 1Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 3Department of Colorectal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 4Department of Urology and Nephrology, The First Affiliated Hospital of Guangxi, Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 5Guangxi Colleges and Universities Key Laboratory of Biological Molecular Medicine Research, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China *These authors contributed equally to this work Introduction: Colorectal cancer (CRC is the fourth most common cause of cancer-related mortality worldwide. The tumor, node, metastasis (TNM stage remains the standard for CRC prognostication. Identification of meaningful microRNA (miRNA and gene modules or representative biomarkers related to the pathological stage of colon cancer helps to predict prognosis and reveal the mechanisms behind cancer progression.Materials and methods: We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA to detect the pathological stage-related miRNA and gene modules and construct a miRNA–gene network. The Cancer Genome Atlas (TCGA colon adenocarcinoma (CAC RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and

Weighted Gene Co-expression Network Analysis of the Dioscin Rich Medicinal Plant Dioscorea nipponica

Directory of Open Access Journals (Sweden)

Wei Sun

2017-06-01

Full Text Available Dioscorea contains critically important species which can be used as staple foods or sources of bioactive substances, including Dioscorea nipponica, which has been used to develop highly successful drugs to treat cardiovascular disease. Its major active ingredients are thought to be sterol compounds such as diosgenin, which has been called “medicinal gold” because of its valuable properties. However, reliance on naturally growing plants as a production system limits the potential use of D. nipponica, raising interest in engineering metabolic pathways to enhance the production of secondary metabolites. However, the biosynthetic pathway of diosgenin is still poorly understood, and D. nipponica is poorly characterized at a molecular level, hindering in-depth investigation. In the present work, the RNAs from five organs and seven methyl jasmonate treated D. nipponica rhizomes were sequenced using the Illumina high-throughput sequencing platform, yielding 52 gigabases of data, which were pooled and assembled into a reference transcriptome. Four hundred and eighty two genes were found to be highly expressed in the rhizomes, and these genes are mainly involved in stress response and transcriptional regulation. Based on their expression patterns, 36 genes were selected for further investigation as candidate genes involved in dioscin biosynthesis. Constructing co-expression networks based on significant changes in gene expression revealed 15 gene modules. Of these, four modules with properties correlating to dioscin regulation and biosynthesis, consisting of 4,665 genes in total, were selected for further functional investigation. These results improve our understanding of dioscin biosynthesis in this important medicinal plant and will help guide more intensive investigations.

Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue

Directory of Open Access Journals (Sweden)

Usadel Björn

2007-05-01

Full Text Available Abstract Background Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper insights into regulatory behavior and cellular responses, as will be discussed for expression data of developing barley endosperm tissue. For that purpose, high-throughput multidimensional scaling (HiT-MDS, a recent method for similarity-preserving data embedding, is substantially refined and used for (a assessing the quality and reliability of centroid gene expression patterns, and for (b derivation of functional relationships of coexpressed genes of endosperm tissue during barley grain development (0–26 days after flowering. Results Temporal expression profiles of 4824 genes at 14 time points are faithfully embedded into two-dimensional displays. Thereby, similar shapes of coexpressed genes get closely grouped by a correlation-based similarity measure. As a main result, by using power transformation of correlation terms, a characteristic cloud of points with bipolar sandglass shape is obtained that is inherently connected to expression patterns of pre-storage, intermediate and storage phase of endosperm development. Conclusion The new HiT-MDS-2 method helps to create global views of expression patterns and to validate centroids obtained from clustering programs. Furthermore, functional gene annotation for developing endosperm barley tissue is successfully mapped to the visualization, making easy localization of major centroids of enriched functional categories possible.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

Science.gov (United States)

Farber, Charles R

2010-11-01

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

Production of natural fragrance aromatic acids by coexpression of trans-anethole oxygenase and p-anisaldehyde dehydrogenase genes of Pseudomonas putida JYR-1 in Escherichia coli.

Science.gov (United States)

Han, Dongfei; Kurusarttra, Somwang; Ryu, Ji-Young; Kanaly, Robert A; Hur, Hor-Gil

2012-12-05

A gene encoding p-anisaldehyde dehydrogenase (PAADH), which catalyzes the oxidation of p-anisaldehyde to p-anisic acid, was identified to be clustered with the trans-anethole oxygenase (tao) gene in Pseudomonas putida JYR-1. Heterologously expressed PAADH in Escherichia coli catalyzed the oxidation of vanillin, veratraldehyde, and piperonal to the corresponding aromatic acids vanillic acid, veratric acid, and piperonylic acid, respectively. Coexpression of trans-anethole oxygenase (TAO) and PAADH in E. coli also resulted in the successful transformation of trans-anethole, isoeugenol, O-methyl isoeugenol, and isosafrole to p-anisic acid, vanillic acid, veratric acid, and piperonylic acid, respectively, which are compounds found in plants as secondary metabolites. Because of the relaxed substrate specificity and high transformation rates by coexpressed TAO and PAADH in E. coli , the engineered strain has potential to be applied in the fragrance industry.

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.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Assessing pathogenicity of MLH1 variants by co-expression of human MLH1 and PMS2 genes in yeast

Energy Technology Data Exchange (ETDEWEB)

Vogelsang, Matjaz; Comino, Aleksandra; Zupanec, Neja [Department for Biosynthesis and Biotransformation, National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana (Slovenia); Hudler, Petra [Medical Center for Molecular Biology, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana (Slovenia); Komel, Radovan [Department for Biosynthesis and Biotransformation, National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana (Slovenia); Medical Center for Molecular Biology, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana (Slovenia)

2009-10-28

Loss of DNA mismatch repair (MMR) in humans, mainly due to mutations in the hMLH1 gene, is linked to hereditary nonpolyposis colorectal cancer (HNPCC). Because not all MLH1 alterations result in loss of MMR function, accurate characterization of variants and their classification in terms of their effect on MMR function is essential for reliable genetic testing and effective treatment. To date, in vivo assays for functional characterization of MLH1 mutations performed in various model systems have used episomal expression of the modified MMR genes. We describe here a novel approach to determine accurately the functional significance of hMLH1 mutations in vivo, based on co-expression of human MLH1 and PMS2 in yeast cells. Yeast MLH1 and PMS1 genes, whose protein products form the MutLα complex, were replaced by human orthologs directly on yeast chromosomes by homologous recombination, and the resulting MMR activity was tested. The yeast strain co-expressing hMLH1 and hPMS2 exhibited the same mutation rate as the wild-type. Eight cancer-related MLH1 variants were introduced, using the same approach, into the prepared yeast model, and their effect on MMR function was determined. Five variants (A92P, S93G, I219V, K618R and K618T) were classified as non-pathogenic, whereas variants T117M, Y646C and R659Q were characterized as pathogenic. Results of our in vivo yeast-based approach correlate well with clinical data in five out of seven hMLH1 variants and the described model was thus shown to be useful for functional characterization of MLH1 variants in cancer patients found throughout the entire coding region of the gene.

Assessing pathogenicity of MLH1 variants by co-expression of human MLH1 and PMS2 genes in yeast

Directory of Open Access Journals (Sweden)

Hudler Petra

2009-10-01

Full Text Available Abstract Background Loss of DNA mismatch repair (MMR in humans, mainly due to mutations in the hMLH1 gene, is linked to hereditary nonpolyposis colorectal cancer (HNPCC. Because not all MLH1 alterations result in loss of MMR function, accurate characterization of variants and their classification in terms of their effect on MMR function is essential for reliable genetic testing and effective treatment. To date, in vivo assays for functional characterization of MLH1 mutations performed in various model systems have used episomal expression of the modified MMR genes. We describe here a novel approach to determine accurately the functional significance of hMLH1 mutations in vivo, based on co-expression of human MLH1 and PMS2 in yeast cells. Methods Yeast MLH1 and PMS1 genes, whose protein products form the MutLα complex, were replaced by human orthologs directly on yeast chromosomes by homologous recombination, and the resulting MMR activity was tested. Results The yeast strain co-expressing hMLH1 and hPMS2 exhibited the same mutation rate as the wild-type. Eight cancer-related MLH1 variants were introduced, using the same approach, into the prepared yeast model, and their effect on MMR function was determined. Five variants (A92P, S93G, I219V, K618R and K618T were classified as non-pathogenic, whereas variants T117M, Y646C and R659Q were characterized as pathogenic. Conclusion Results of our in vivo yeast-based approach correlate well with clinical data in five out of seven hMLH1 variants and the described model was thus shown to be useful for functional characterization of MLH1 variants in cancer patients found throughout the entire coding region of the gene.

Assessing pathogenicity of MLH1 variants by co-expression of human MLH1 and PMS2 genes in yeast

International Nuclear Information System (INIS)

Vogelsang, Matjaz; Comino, Aleksandra; Zupanec, Neja; Hudler, Petra; Komel, Radovan

2009-01-01

Loss of DNA mismatch repair (MMR) in humans, mainly due to mutations in the hMLH1 gene, is linked to hereditary nonpolyposis colorectal cancer (HNPCC). Because not all MLH1 alterations result in loss of MMR function, accurate characterization of variants and their classification in terms of their effect on MMR function is essential for reliable genetic testing and effective treatment. To date, in vivo assays for functional characterization of MLH1 mutations performed in various model systems have used episomal expression of the modified MMR genes. We describe here a novel approach to determine accurately the functional significance of hMLH1 mutations in vivo, based on co-expression of human MLH1 and PMS2 in yeast cells. Yeast MLH1 and PMS1 genes, whose protein products form the MutLα complex, were replaced by human orthologs directly on yeast chromosomes by homologous recombination, and the resulting MMR activity was tested. The yeast strain co-expressing hMLH1 and hPMS2 exhibited the same mutation rate as the wild-type. Eight cancer-related MLH1 variants were introduced, using the same approach, into the prepared yeast model, and their effect on MMR function was determined. Five variants (A92P, S93G, I219V, K618R and K618T) were classified as non-pathogenic, whereas variants T117M, Y646C and R659Q were characterized as pathogenic. Results of our in vivo yeast-based approach correlate well with clinical data in five out of seven hMLH1 variants and the described model was thus shown to be useful for functional characterization of MLH1 variants in cancer patients found throughout the entire coding region of the gene

An extensive (co-expression analysis tool for the cytochrome P450 superfamily in Arabidopsis thaliana

Directory of Open Access Journals (Sweden)

Provart Nicholas J

2008-04-01

Full Text Available Abstract Background Sequencing of the first plant genomes has revealed that cytochromes P450 have evolved to become the largest family of enzymes in secondary metabolism. The proportion of P450 enzymes with characterized biochemical function(s is however very small. If P450 diversification mirrors evolution of chemical diversity, this points to an unexpectedly poor understanding of plant metabolism. We assumed that extensive analysis of gene expression might guide towards the function of P450 enzymes, and highlight overlooked aspects of plant metabolism. Results We have created a comprehensive database, 'CYPedia', describing P450 gene expression in four data sets: organs and tissues, stress response, hormone response, and mutants of Arabidopsis thaliana, based on public Affymetrix ATH1 microarray expression data. P450 expression was then combined with the expression of 4,130 re-annotated genes, predicted to act in plant metabolism, for co-expression analyses. Based on the annotation of co-expressed genes from diverse pathway annotation databases, co-expressed pathways were identified. Predictions were validated for most P450s with known functions. As examples, co-expression results for P450s related to plastidial functions/photosynthesis, and to phenylpropanoid, triterpenoid and jasmonate metabolism are highlighted here. Conclusion The large scale hypothesis generation tools presented here provide leads to new pathways, unexpected functions, and regulatory networks for many P450s in plant metabolism. These can now be exploited by the community to validate the proposed functions experimentally using reverse genetics, biochemistry, and metabolic profiling.

Co-expression of G2-EPSPS and glyphosate acetyltransferase GAT genes conferring high tolerance to glyphosate in soybean

Directory of Open Access Journals (Sweden)

Bingfu eGuo

2015-10-01

Full Text Available Glyphosate is a widely used non-selective herbicide with broad spectrum of weed control around the world. At present, most of the commercial glyphosate tolerant soybeans utilize glyphosate tolerant gene CP4-EPSPS or glyphosate acetyltransferase gene GAT separately. In this study, both glyphosate tolerant gene G2-EPSPS and glyphosate degraded gene GAT were co-transferred into soybean and transgenic plants showed high tolerance to glyphosate. Molecular analysis including PCR, Sothern blot, qRT-PCR and Western blot revealed that target genes have been integrated into genome and expressed effectively at both mRNA and protein levels. Furthermore, the glyphosate tolerance analysis showed that no typical symptom was observed when compared with a glyphosate tolerant line HJ06-698 derived from GR1 transgenic soybean even at four-fold labeled rate of Roundup. Chlorophyll and shikimic acid content analysis of transgenic plant also revealed that these two indexes were not significantly altered after glyphosate application. These results indicated that co-expression of G2-EPSPS and GAT conferred high tolerance to the herbicide glyphosate in soybean. Therefore, combination of tolerant and degraded genes provides a new strategy for developing glyphosate tolerant transgenic crops.

Neutralization of Bacterial YoeBSpn Toxicity and Enhanced Plant Growth in Arabidopsis thaliana via Co-Expression of the Toxin-Antitoxin Genes

Science.gov (United States)

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

Neutralization of Bacterial YoeBSpn Toxicity and Enhanced Plant Growth in Arabidopsis thaliana via Co-Expression of the Toxin-Antitoxin Genes

Directory of Open Access Journals (Sweden)

Fauziah Abu Bakar

2016-04-01

Full Text Available 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.

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

Science.gov (United States)

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'.

Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.

Science.gov (United States)

Xi, W-D; Liu, Y-J; Sun, X-B; Shan, J; Yi, L; Zhang, T-T

2017-07-01

RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) 1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt. A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7. Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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).

Gene coexpression network analysis of fruit transcriptomes uncovers a possible mechanistically distinct class of sugar/acid ratio-associated genes in sweet orange.

Science.gov (United States)

Qiao, Liang; Cao, Minghao; Zheng, Jian; Zhao, Yihong; Zheng, Zhi-Liang

2017-10-30

The ratio of sugars to organic acids, two of the major metabolites in fleshy fruits, has been considered the most important contributor to fruit sweetness. Although accumulation of sugars and acids have been extensively studied, whether plants evolve a mechanism to maintain, sense or respond to the fruit sugar/acid ratio remains a mystery. In a prior study, we used an integrated systems biology tool to identify a group of 39 acid-associated genes from the fruit transcriptomes in four sweet orange varieties (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). We reanalyzed the prior sweet orange fruit transcriptome data, leading to the identification of 72 genes highly correlated with the fruit sugar/acid ratio. The majority of these sugar/acid ratio-related genes are predicted to be involved in regulatory functions such as transport, signaling and transcription or encode enzymes involved in metabolism. Surprisingly, only three of these sugar/acid ratio-correlated genes are weakly correlated with sugar level and none of them overlaps with the acid-associated genes. Weighted Gene Coexpression Network Analysis (WGCNA) has revealed that these genes belong to four modules, Blue, Grey, Brown and Turquoise, with the former two modules being unique to the sugar/acid ratio control. Our results indicate that orange fruits contain a possible mechanistically distinct class of genes that may potentially be involved in maintaining fruit sugar/acid ratios and/or responding to the cellular sugar/acid ratio status. Therefore, our analysis of orange transcriptomes provides an intriguing insight into the potentially novel genetic or molecular mechanisms controlling the sugar/acid ratio in fruits.

Co-expression of Exo-inulinase and Endo-inulinase Genes in the Oleaginous Yeast Yarrowia lipolytica for Efficient Single Cell Oil Production from Inulin.

Science.gov (United States)

Shi, Nianci; Mao, Weian; He, Xiaoxia; Chi, Zhe; Chi, Zhenming; Liu, Guanglei

2018-05-01

Yarrowia lipolytica is a promising platform for the single cell oil (SCO) production. In this study, a transformant X+N8 in which exo- and endo-inulinase genes were co-expressed could produce an inulinase activity of 124.33 U/mL within 72 h. However, the inulinase activity of a transformant X2 carrying a single exo-inulinase gene was only 47.33 U/mL within 72 h. Moreover, the transformant X+N8 could accumulate 48.13% (w/w) SCO from inulin and the cell dry weight reached 13.63 g/L within 78 h, which were significantly higher than those of the transformant X2 (41.87% (w/w) and 11.23 g/L) under the same conditions. In addition, inulin hydrolysis and utilization of the transformant X+N8 were also more efficient than those of the transformant X2 during the fermentation process. These results demonstrated that the co-expression of the exo- and endo-inulinase genes significantly enhanced the SCO production from inulin due to the improvement of the inulinase activity and the synergistic action of exo- and endo-inulinase. Besides, over 95.01% of the fatty acids from the transformant X+N8 were C16-C18, especially C18:1 (53.10%), suggesting that the fatty acids could be used as feedstock for biodiesel production.

Whole brain and brain regional coexpression network interactions associated with predisposition to alcohol consumption.

Directory of Open Access Journals (Sweden)

Lauren A Vanderlinden

Full Text Available To identify brain transcriptional networks that may predispose an animal to consume alcohol, we used weighted gene coexpression network analysis (WGCNA. Candidate coexpression modules are those with an eigengene expression level that correlates significantly with the level of alcohol consumption across a panel of BXD recombinant inbred mouse strains, and that share a genomic region that regulates the module transcript expression levels (mQTL with a genomic region that regulates alcohol consumption (bQTL. To address a controversy regarding utility of gene expression profiles from whole brain, vs specific brain regions, as indicators of the relationship of gene expression to phenotype, we compared candidate coexpression modules from whole brain gene expression data (gathered with Affymetrix 430 v2 arrays in the Colorado laboratories and from gene expression data from 6 brain regions (nucleus accumbens (NA; prefrontal cortex (PFC; ventral tegmental area (VTA; striatum (ST; hippocampus (HP; cerebellum (CB available from GeneNetwork. The candidate modules were used to construct candidate eigengene networks across brain regions, resulting in three "meta-modules", composed of candidate modules from two or more brain regions (NA, PFC, ST, VTA and whole brain. To mitigate the potential influence of chromosomal location of transcripts and cis-eQTLs in linkage disequilibrium, we calculated a semi-partial correlation of the transcripts in the meta-modules with alcohol consumption conditional on the transcripts' cis-eQTLs. The function of transcripts that retained the correlation with the phenotype after correction for the strong genetic influence, implicates processes of protein metabolism in the ER and Golgi as influencing susceptibility to variation in alcohol consumption. Integration of these data with human GWAS provides further information on the function of polymorphisms associated with alcohol-related traits.

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

Science.gov (United States)

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

2016-11-30

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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Kittipong Rattanaporn

2011-08-01

Full Text Available 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.

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

Science.gov (United States)

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.

Integration of liver gene co-expression networks and eGWAs analyses highlighted candidate regulators implicated in lipid metabolism in pigs.

Science.gov (United States)

Ballester, Maria; Ramayo-Caldas, Yuliaxis; Revilla, Manuel; Corominas, Jordi; Castelló, Anna; Estellé, Jordi; Fernández, Ana I; Folch, Josep M

2017-04-19

In the present study, liver co-expression networks and expression Genome Wide Association Study (eGWAS) were performed to identify DNA variants and molecular pathways implicated in the functional regulatory mechanisms of meat quality traits in pigs. With this purpose, the liver mRNA expression of 44 candidates genes related with lipid metabolism was analysed in 111 Iberian x Landrace backcross animals. The eGWAS identified 92 eSNPs located in seven chromosomal regions and associated with eight genes: CROT, CYP2U1, DGAT1, EGF, FABP1, FABP5, PLA2G12A, and PPARA. Remarkably, cis-eSNPs associated with FABP1 gene expression which may be determining the C18:2(n-6)/C18:3(n-3) ratio in backfat through the multiple interaction of DNA variants and genes were identified. Furthermore, a hotspot on SSC8 associated with the gene expression of eight genes was identified and the TBCK gene was pointed out as candidate gene regulating it. Our results also suggested that the PI3K-Akt-mTOR pathway plays an important role in the control of the analysed genes highlighting nuclear receptors as the NR3C1 or PPARA. Finally, sex-dimorphism associated with hepatic lipid metabolism was identified with over-representation of female-biased genes. These results increase our knowledge of the genetic architecture underlying fat composition traits.

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

Science.gov (United States)

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.

ESR1 Is Co-Expressed with Closely Adjacent Uncharacterised Genes Spanning a Breast Cancer Susceptibility Locus at 6q25.1

Science.gov (United States)

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, FDRaccount 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 on the recently identified relationship between SNPs in this region and breast cancer risk. PMID:21552322

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

Science.gov (United States)

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 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.

Co-expression of an Erwinia chrysanthemi pectate lyase-encoding gene (pelE) and an E. carotovora polygalacturonase-encoding gene (peh1) in Saccharomyces cerevisiae.

Science.gov (United States)

Laing, E; Pretorius, I S

1993-05-01

A pectate lyase (PL)-encoding gene (pelE) from Erwinia chrysanthemi and a polygalacturonase (PG)-encoding gene (peh1) from E. carotovora were each inserted between a novel yeast expression-secretion cassette and a yeast gene terminator, and cloned separately into a yeast-centromeric shuttle vector (YCp50), generating recombinant plasmids pAMS12 and pAMS13. Transcription initiation signals present in the expression-secretion cassette were derived from the yeast alcohol dehydrogenase gene promoter (ADC1P), whereas the transcription termination signals were derived from the yeast tryptophan synthase gene terminator (TRP5T). Secretion of PL and PG was directed by the signal sequence of the yeast mating pheromone alpha-factor (MF alpha 1s). A pectinase cassette comprising ADC1P-MF alpha 1s-pelE-TRP5T and ADC1P-MF alpha 1s-peh1-TRP5T was subcloned into YCp50, generating plasmid pAMS14. Subsequently, the dominant selectable Geneticin G418-resistance (GtR) marker, APH1, inserted between the yeast uridine diphosphoglucose 4-epimerase gene promoter (GAL10P) and yeast orotidine-5'-phosphate carboxylase gene terminator (URA3T), was cloned into pAMS14, resulting in plasmid pAMS15. Plasmids pAMS12, pAMS13 and pAMS14 were transformed into a laboratory strain of Saccharomyces cerevisiae, whereas pAMS15 was stably introduced into two commercial wine yeast strains. DNA-DNA and DNA-RNA hybridization analyses revealed the presence of these plasmids, and the pelE and peh1 transcripts in the yeast transformants, respectively. A polypectate agarose assay indicated the extracellular production of biologically active PL and PG by the S. cerevisiae transformants and confirmed that co-expression of the pelE and peh1 genes synergistically enhanced pectate degradation.

Connective tissue growth factor activates pluripotency genes and mesenchymal-epithelial transition in head and neck cancer cells.

Science.gov (United States)

Chang, Cheng-Chi; Hsu, Wen-Hao; Wang, Chen-Chien; Chou, Chun-Hung; Kuo, Mark Yen-Ping; Lin, Been-Ren; Chen, Szu-Ta; Tai, Shyh-Kuan; Kuo, Min-Liang; Yang, Muh-Hwa

2013-07-01

The epithelial-mesenchymal transition (EMT) is a key mechanism in both embryonic development and cancer metastasis. The EMT introduces stem-like properties to cancer cells. However, during somatic cell reprogramming, mesenchymal-epithelial transition (MET), the reverse process of EMT, is a crucial step toward pluripotency. Connective tissue growth factor (CTGF) is a multifunctional secreted protein that acts as either an oncoprotein or a tumor suppressor among different cancers. Here, we show that in head and neck squamous cell carcinoma (HNSCC), CTGF promotes the MET and reduces invasiveness. Moreover, we found that CTGF enhances the stem-like properties of HNSCC cells and increases the expression of multiple pluripotency genes. Mechanistic studies showed that CTGF induces c-Jun expression through αvβ3 integrin and that c-Jun directly activates the transcription of the pluripotency genes NANOG, SOX2, and POU5F1. Knockdown of CTGF in TW2.6 cells was shown to reduce tumor formation and attenuate E-cadherin expression in xenotransplanted tumors. In HNSCC patient samples, CTGF expression was positively correlated with the levels of CDH1, NANOG, SOX2, and POU5F1. Coexpression of CTGF and the pluripotency genes was found to be associated with a worse prognosis. These findings are valuable in elucidating the interplay between epithelial plasticity and stem-like properties during cancer progression and provide useful information for developing a novel classification system and therapeutic strategies for HNSCC. ©2013 AACR.

In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

Science.gov (United States)

Zinati, Zahra; Shamloo-Dashtpagerdi, Roohollah; Behpouri, Ali

2016-01-01

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co- expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways. EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem- looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites. PMID:28261627

ESR1 is co-expressed with closely adjacent uncharacterised genes spanning a breast cancer susceptibility locus at 6q25.1.

Directory of Open Access Journals (Sweden)

Anita K Dunbier

2011-04-01

Full Text Available 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

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

Directory of Open Access Journals (Sweden)

Cihat Erdoğan

Full Text Available 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.

Different substrate regimes determine transcriptional profiles and gene co-expression in Methanosarcina barkeri (DSM 800)

Czech Academy of Sciences Publication Activity Database

Lin, Qiang; Fang, X.; Ho, A.; Li, J.; Yan, X.; Tu, B.; Li, Ch.; Li, J.; Yao, M.; Li, X.

2017-01-01

Roč. 101, č. 19 (2017), s. 7303-7316 ISSN 0175-7598 Institutional support: RVO:60077344 Keywords : Methanosarcina barkeri * substrate regimes * diversity * co-expression * ecological strategies Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 3.420, year: 2016

Connected Gene Communities Underlie Transcriptional Changes in Cornelia de Lange Syndrome.

Science.gov (United States)

Boudaoud, Imène; Fournier, Éric; Baguette, Audrey; Vallée, Maxime; Lamaze, Fabien C; Droit, Arnaud; Bilodeau, Steve

2017-09-01

Cornelia de Lange syndrome (CdLS) is a complex multisystem developmental disorder caused by mutations in cohesin subunits and regulators. While its precise molecular mechanisms are not well defined, they point toward a global deregulation of the transcriptional gene expression program. Cohesin is associated with the boundaries of chromosome domains and with enhancer and promoter regions connecting the three-dimensional genome organization with transcriptional regulation. Here, we show that connected gene communities, structures emerging from the interactions of noncoding regulatory elements and genes in the three-dimensional chromosomal space, provide a molecular explanation for the pathoetiology of CdLS associated with mutations in the cohesin-loading factor NIPBL and the cohesin subunit SMC1A NIPBL and cohesin are important constituents of connected gene communities that are centrally positioned at noncoding regulatory elements. Accordingly, genes deregulated in CdLS are positioned within reach of NIPBL- and cohesin-occupied regions through promoter-promoter interactions. Our findings suggest a dynamic model where NIPBL loads cohesin to connect genes in communities, offering an explanation for the gene expression deregulation in the CdLS. Copyright © 2017 by the Genetics Society of America.

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

Science.gov (United States)

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.

Gene Expression Analysis in Tubule Interstitial Compartments Reveals Candidate Agents for IgA Nephropathy

Directory of Open Access Journals (Sweden)

Jinling Wang

2014-09-01

Full Text Available Background/Aims: Our aim was to explore the molecular mechanism underlying development of IgA nephropathy and discover candidate agents for IgA nephropathy. Methods: The differentially expressed genes (DEGs between patients with IgA nephropathy and normal controls were identified by the data of GSE35488 downloaded from GEO (Gene Expression Omnibus database. The co-expressed gene pairs among DEGs were screened to construct the gene-gene interaction network. Gene Ontology (GO enrichment analysis was performed to analyze the functions of DEGs. The biologically active small molecules capable of targeting IgA nephropathy were identified using the Connectivity Map (cMap database. Results: A total of 55 genes involved in response to organic substance, transcription factor activity and response to steroid hormone stimulus were identified to be differentially expressed in IgA nephropathy patients compared to healthy individuals. A network with 45 co-expressed gene pairs was constructed. DEGs in the network were significantly enriched in response to organic substance. Additionally, a group of small molecules were identified, such as doxorubicin and thapsigargin. Conclusion: Our work provided a systematic insight in understanding the mechanism of IgA nephropathy. Small molecules such as thapsigargin might be potential candidate agents for the treatment of IgA nephropathy.

Genome-wide expression of transcriptomes and their co-expression pattern in subtropical maize (Zea mays L. under waterlogging stress.

Directory of Open Access Journals (Sweden)

Nepolean Thirunavukkarasu

Full Text Available Waterlogging causes extensive damage to maize crops in tropical and subtropical regions. The identification of tolerance genes and their interactions at the molecular level will be helpful to engineer tolerant genotypes. A whole-genome transcriptome assay revealed the specific role of genes in response to waterlogging stress in susceptible and tolerant genotypes. Genes involved in the synthesis of ethylene and auxin, cell wall metabolism, activation of G-proteins and formation of aerenchyma and adventitious roots, were upregulated in the tolerant genotype. Many transcription factors, particularly ERFs, MYB, HSPs, MAPK, and LOB-domain protein were involved in regulation of these traits. Genes responsible for scavenging of ROS generated under stress were expressed along with those involved in carbohydrate metabolism. The physical locations of 21 genes expressed in the tolerant genotype were found to correspond with the marker intervals of known QTLs responsible for development of adaptive traits. Among the candidate genes, most showed synteny with genes of sorghum and foxtail millet. Co-expression analysis of 528 microarray samples including 16 samples from the present study generated seven functional modules each in the two genotypes, with differing characteristics. In the tolerant genotype, stress genes were co-expressed along with peroxidase and fermentation pathway genes.

Microarray profiling and co-expression network analysis of circulating lncRNAs and mRNAs associated with major depressive disorder.

Directory of Open Access Journals (Sweden)

Zhifen Liu

Full Text Available LncRNAs, which represent one of the most highly expressed classes of ncRNAs in the brain, are becoming increasingly interesting with regard to brain functions and disorders. However, changes in the expression of regulatory lncRNAs in Major Depressive Disorder (MDD have not yet been reported. Using microarrays, we profiled the expression of 34834 lncRNAs and 39224 mRNAs in peripheral blood sampled from MDD patients as well as demographically-matched controls. Among these, we found that 2007 lncRNAs and 1667 mRNAs were differentially expressed, 17 of which were documented as depression-related gene in previous studies. Gene Ontology (GO and pathway analyses indicated that the biological functions of differentially expressed mRNAs were related to fundamental metabolic processes and neurodevelopment diseases. To investigate the potential regulatory roles of the differentially expressed lncRNAs on the mRNAs, we also constructed co-expression networks composed of the lncRNAs and mRNAs, which shows significant correlated patterns of expression. In the MDD-derived network, there were a greater number of nodes and connections than that in the control-derived network. The lncRNAs located at chr10:874695-874794, chr10:75873456-75873642, and chr3:47048304-47048512 may be important factors regulating the expression of mRNAs as they have previously been reported associations with MDD. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in MDD using microarray technology. We identified circulating lncRNAs that are aberrantly expressed in MDD and the results suggest that lncRNAs may contribute to the molecular pathogenesis of MDD.

A Genome-Wide Association Study for Culm Cellulose Content in Barley Reveals Candidate Genes Co-Expressed with Members of the CELLULOSE SYNTHASE A Gene Family

Science.gov (United States)

Houston, Kelly; Burton, Rachel A.; Sznajder, Beata; Rafalski, Antoni J.; Dhugga, Kanwarpal S.; Mather, Diane E.; Taylor, Jillian; Steffenson, Brian J.; Waugh, Robbie; Fincher, Geoffrey B.

2015-01-01

Cellulose is a fundamentally important component of cell walls of higher plants. It provides a scaffold that allows the development and growth of the plant to occur in an ordered fashion. Cellulose also provides mechanical strength, which is crucial for both normal development and to enable the plant to withstand both abiotic and biotic stresses. We quantified the cellulose concentration in the culm of 288 two – rowed and 288 six – rowed spring type barley accessions that were part of the USDA funded barley Coordinated Agricultural Project (CAP) program in the USA. When the population structure of these accessions was analysed we identified six distinct populations, four of which we considered to be comprised of a sufficient number of accessions to be suitable for genome-wide association studies (GWAS). These lines had been genotyped with 3072 SNPs so we combined the trait and genetic data to carry out GWAS. The analysis allowed us to identify regions of the genome containing significant associations between molecular markers and cellulose concentration data, including one region cross-validated in multiple populations. To identify candidate genes we assembled the gene content of these regions and used these to query a comprehensive RNA-seq based gene expression atlas. This provided us with gene annotations and associated expression data across multiple tissues, which allowed us to formulate a supported list of candidate genes that regulate cellulose biosynthesis. Several regions identified by our analysis contain genes that are co-expressed with CELLULOSE SYNTHASE A (HvCesA) across a range of tissues and developmental stages. These genes are involved in both primary and secondary cell wall development. In addition, genes that have been previously linked with cellulose synthesis by biochemical methods, such as HvCOBRA, a gene of unknown function, were also associated with cellulose levels in the association panel. Our analyses provide new insights into the

The functional landscape of mouse gene expression

Directory of Open Access Journals (Sweden)

Zhang Wen

2004-12-01

Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

Co-expression of the Thermotoga neapolitana aglB gene with an upstream 3'-coding fragment of the malG gene improves enzymatic characteristics of recombinant AglB cyclomaltodextrinase.

Science.gov (United States)

Lunina, Natalia A; Agafonova, Elena V; Chekanovskaya, Lyudmila A; Dvortsov, Igor A; Berezina, Oksana V; Shedova, Ekaterina N; Kostrov, Sergey V; Velikodvorskaya, Galina A

2007-07-01

A cluster of Thermotoga neapolitana genes participating in starch degradation includes the malG gene of sugar transport protein and the aglB gene of cyclomaltodextrinase. The start and stop codons of these genes share a common overlapping sequence, aTGAtg. Here, we compared properties of expression products of three different constructs with aglB from T. neapolitana. The first expression vector contained the aglB gene linked to an upstream 90-bp 3'-terminal region of the malG gene with the stop codon overlapping with the start codon of aglB. The second construct included the isolated coding sequence of aglB with two tandem potential start codons. The expression product of this construct in Escherichia coli had two tandem Met residues at its N terminus and was characterized by low thermostability and high tendency to aggregate. In contrast, co-expression of aglB and the 3'-terminal region of malG (the first construct) resulted in AglB with only one N-terminal Met residue and a much higher specific activity of cyclomaltodextrinase. Moreover, the enzyme expressed by such a construct was more thermostable and less prone to aggregation. The third construct was the same as the second one except that it contained only one ATG start codon. The product of its expression had kinetic and other properties similar to those of the enzyme with only one N-terminal Met residue.

Genetic architecture of gene expression in the chicken

Directory of Open Access Journals (Sweden)

Stanley Dragana

2013-01-01

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

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

Science.gov (United States)

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.

Gene-Transformation-Induced Changes in Chemical Functional Group Features and Molecular Structure Conformation in Alfalfa Plants Co-Expressing Lc-bHLH and C1-MYB Transcriptive Flavanoid Regulatory Genes: Effects of Single-Gene and Two-Gene Insertion.

Science.gov (United States)

Heendeniya, Ravindra G; Yu, Peiqiang

2017-03-20

Alfalfa ( Medicago sativa L.) genotypes transformed with Lc-bHLH and Lc transcription genes were developed with the intention of stimulating proanthocyanidin synthesis in the aerial parts of the plant. To our knowledge, there are no studies on the effect of single-gene and two-gene transformation on chemical functional groups and molecular structure changes in these plants. The objective of this study was to use advanced molecular spectroscopy with multivariate chemometrics to determine chemical functional group intensity and molecular structure changes in alfalfa plants when co-expressing Lc-bHLH and C1-MYB transcriptive flavanoid regulatory genes in comparison with non-transgenic (NT) and AC Grazeland (ACGL) genotypes. The results showed that compared to NT genotype, the presence of double genes ( Lc and C1 ) increased ratios of both the area and peak height of protein structural Amide I/II and the height ratio of α-helix to β-sheet. In carbohydrate-related spectral analysis, the double gene-transformed alfalfa genotypes exhibited lower peak heights at 1370, 1240, 1153, and 1020 cm -1 compared to the NT genotype. Furthermore, the effect of double gene transformation on carbohydrate molecular structure was clearly revealed in the principal component analysis of the spectra. In conclusion, single or double transformation of Lc and C1 genes resulted in changing functional groups and molecular structure related to proteins and carbohydrates compared to the NT alfalfa genotype. The current study provided molecular structural information on the transgenic alfalfa plants and provided an insight into the impact of transgenes on protein and carbohydrate properties and their molecular structure's changes.

Mediator and Cohesin Connect Gene Expression and Chromatin Architecture

Science.gov (United States)

Kagey, Michael H.; Newman, Jamie J.; Bilodeau, Steve; Zhan, Ye; Orlando, David A.; van Berkum, Nynke L.; Ebmeier, Christopher C.; Goossens, Jesse; Rahl, Peter B.; Levine, Stuart S.; Taatjes, Dylan J.; Dekker, Job; Young, Richard A.

2010-01-01

Summary Transcription factors control cell specific gene expression programs through interactions with diverse coactivators and the transcription apparatus. Gene activation may involve DNA loop formation between enhancer-bound transcription factors and the transcription apparatus at the core promoter, but this process is not well understood. We report here that Mediator and Cohesin physically and functionally connect the enhancers and core promoters of active genes in embryonic stem cells. Mediator, a transcriptional coactivator, forms a complex with Cohesin, which can form rings that connect two DNA segments. The Cohesin loading factor Nipbl is associated with Mediator/Cohesin complexes, providing a means to load Cohesin at promoters. DNA looping is observed between the enhancers and promoters occupied by Mediator and Cohesin. Mediator and Cohesin occupy different promoters in different cells, thus generating cell-type specific DNA loops linked to the gene expression program of each cell. PMID:20720539

Domestication rewired gene expression and nucleotide diversity patterns in tomato.

Science.gov (United States)

Sauvage, Christopher; Rau, Andrea; Aichholz, Charlotte; Chadoeuf, Joël; Sarah, Gautier; Ruiz, Manuel; Santoni, Sylvain; Causse, Mathilde; David, Jacques; Glémin, Sylvain

2017-08-01

Plant domestication has led to considerable phenotypic modifications from wild species to modern varieties. However, although changes in key traits have been well documented, less is known about the underlying molecular mechanisms, such as the reduction of molecular diversity or global gene co-expression patterns. In this study, we used a combination of gene expression and population genetics in wild and crop tomato to decipher the footprints of domestication. We found a set of 1729 differentially expressed genes (DEG) between the two genetic groups, belonging to 17 clusters of co-expressed DEG, suggesting that domestication affected not only individual genes but also regulatory networks. Five co-expression clusters were enriched in functional terms involving carbohydrate metabolism or epigenetic regulation of gene expression. We detected differences in nucleotide diversity between the crop and wild groups specific to DEG. Our study provides an extensive profiling of the rewiring of gene co-expression induced by the domestication syndrome in one of the main crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

Directory of Open Access Journals (Sweden)

Nepolean Thirunavukkarasu

2017-01-01

Full Text Available A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype than in PC3 (a drought sensitive genotype, indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.

Successful recombinant production of Allochromatium vinosum cytochrome c' requires coexpression of cmm genes in heme-rich Escherichia coli JCB712

International Nuclear Information System (INIS)

Evers, Toon H.; Merkx, Maarten

2005-01-01

Cytochrome c' from the purple photosynthetic bacterium Allochromatium vinosum (CCP) displays a unique, reversible dimer-to-monomer transition upon binding of NO, CO, and CN - . This small, four helix bundle protein represents an attractive model for the study of other heme protein biosensors, provided a recombinant expression system is available. Here we report the development of an efficient expression system for CCP that makes use of a maltose binding protein fusion strategy to enhance periplasmic expression and allow easy purification by affinity chromatography. Coexpression of cytochrome c maturase genes and the use of a heme-rich Escherichia coli strain were found to be necessary to obtain reasonable yields of cytochrome c'. Characterization using circular dichroism, UV-vis spectroscopy, and size-exclusion chromatography confirms the native-like properties of the recombinant protein, including its ligand-induced monomerization

Mining tissue specificity, gene connectivity and disease association to reveal a set of genes that modify the action of disease causing genes

Directory of Open Access Journals (Sweden)

Reverter Antonio

2008-09-01

Full Text Available Abstract Background The tissue specificity of gene expression has been linked to a number of significant outcomes including level of expression, and differential rates of polymorphism, evolution and disease association. Recent studies have also shown the importance of exploring differential gene connectivity and sequence conservation in the identification of disease-associated genes. However, no study relates gene interactions with tissue specificity and disease association. Methods We adopted an a priori approach making as few assumptions as possible to analyse the interplay among gene-gene interactions with tissue specificity and its subsequent likelihood of association with disease. We mined three large datasets comprising expression data drawn from massively parallel signature sequencing across 32 tissues, describing a set of 55,606 true positive interactions for 7,197 genes, and microarray expression results generated during the profiling of systemic inflammation, from which 126,543 interactions among 7,090 genes were reported. Results Amongst the myriad of complex relationships identified between expression, disease, connectivity and tissue specificity, some interesting patterns emerged. These include elevated rates of expression and network connectivity in housekeeping and disease-associated tissue-specific genes. We found that disease-associated genes are more likely to show tissue specific expression and most frequently interact with other disease genes. Using the thresholds defined in these observations, we develop a guilt-by-association algorithm and discover a group of 112 non-disease annotated genes that predominantly interact with disease-associated genes, impacting on disease outcomes. Conclusion We conclude that parameters such as tissue specificity and network connectivity can be used in combination to identify a group of genes, not previously confirmed as disease causing, that are involved in interactions with disease causing

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Directory of Open Access Journals (Sweden)

Gant Timothy W

2008-06-01

Full Text Available Abstract Background Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006, Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures. Results Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively. Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method. Conclusion The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.

Bcl-2 and N-Myc Coexpression Increases IGF-IR and Features of Malignant Growth in Neuroblastoma Cell Lines

Directory of Open Access Journals (Sweden)

Rama Jasty

2001-01-01

Full Text Available The bcl-2 and c-myc oncogenes cooperate to transform multiple cell types. In the pediatric malignancy NB2, Bcl2 is highly expressed. In tumors with a poor prognosis, N-Myc, a protein homologous to c-Myc, is overexpressed as a result of gene amplification. The present study was designed to determine whether Bcl-2 cooperates with N-Myc to bestow a tumorigenic phenotype to neuroblastoma (NB cells. NB cell lines that at baseline express neither Bcl-2 nor N-Myc were stably transfected to express these gene products. In this model, we found Bcl-2 rescues N-Myc-expressing cells from apoptosis induced by serum withdrawal. Coexpression of Bcl-2 and N-Myc supports growth in low serum conditions and anchorage-independent growth in soft agar. Similarly, in vivo tumorigenic and angiogenic activity was dependent on coexpression. Our data further suggests that the mechanism underlying these changes involves the receptor for insulin growth factor type I (IGF-IR.

Enforcing Co-expression Within a Brain-Imaging Genomics Regression Framework.

Science.gov (United States)

Zille, Pascal; Calhoun, Vince D; Wang, Yu-Ping

2017-06-28

Among the challenges arising in brain imaging genetic studies, estimating the potential links between neurological and genetic variability within a population is key. In this work, we propose a multivariate, multimodal formulation for variable selection that leverages co-expression patterns across various data modalities. Our approach is based on an intuitive combination of two widely used statistical models: sparse regression and canonical correlation analysis (CCA). While the former seeks multivariate linear relationships between a given phenotype and associated observations, the latter searches to extract co-expression patterns between sets of variables belonging to different modalities. In the following, we propose to rely on a 'CCA-type' formulation in order to regularize the classical multimodal sparse regression problem (essentially incorporating both CCA and regression models within a unified formulation). The underlying motivation is to extract discriminative variables that are also co-expressed across modalities. We first show that the simplest formulation of such model can be expressed as a special case of collaborative learning methods. After discussing its limitation, we propose an extended, more flexible formulation, and introduce a simple and efficient alternating minimization algorithm to solve the associated optimization problem.We explore the parameter space and provide some guidelines regarding parameter selection. Both the original and extended versions are then compared on a simple toy dataset and a more advanced simulated imaging genomics dataset in order to illustrate the benefits of the latter. Finally, we validate the proposed formulation using single nucleotide polymorphisms (SNP) data and functional magnetic resonance imaging (fMRI) data from a population of adolescents (n = 362 subjects, age 16.9 ± 1.9 years from the Philadelphia Neurodevelopmental Cohort) for the study of learning ability. Furthermore, we carry out a significance

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

Directory of Open Access Journals (Sweden)

Xiao Chang

Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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

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

Science.gov (United States)

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.

Iron homeostasis in Arabidopsis thaliana: transcriptomic analyses reveal novel FIT-regulated genes, iron deficiency marker genes and functional gene networks.

Science.gov (United States)

Mai, Hans-Jörg; Pateyron, Stéphanie; Bauer, Petra

2016-10-03

FIT (FER-LIKE IRON DEFICIENCY-INDUCED TRANSCRIPTION FACTOR) is the central regulator of iron uptake in Arabidopsis thaliana roots. We performed transcriptome analyses of six day-old seedlings and roots of six week-old plants using wild type, a fit knock-out mutant and a FIT over-expression line grown under iron-sufficient or iron-deficient conditions. We compared genes regulated in a FIT-dependent manner depending on the developmental stage of the plants. We assembled a high likelihood dataset which we used to perform co-expression and functional analysis of the most stably iron deficiency-induced genes. 448 genes were found FIT-regulated. Out of these, 34 genes were robustly FIT-regulated in root and seedling samples and included 13 novel FIT-dependent genes. Three hundred thirty-one genes showed differential regulation in response to the presence and absence of FIT only in the root samples, while this was the case for 83 genes in the seedling samples. We assembled a virtual dataset of iron-regulated genes based on a total of 14 transcriptomic analyses of iron-deficient and iron-sufficient wild-type plants to pinpoint the best marker genes for iron deficiency and analyzed this dataset in depth. Co-expression analysis of this dataset revealed 13 distinct regulons part of which predominantly contained functionally related genes. We could enlarge the list of FIT-dependent genes and discriminate between genes that are robustly FIT-regulated in roots and seedlings or only in one of those. FIT-regulated genes were mostly induced, few of them were repressed by FIT. With the analysis of a virtual dataset we could filter out and pinpoint new candidates among the most reliable marker genes for iron deficiency. Moreover, co-expression and functional analysis of this virtual dataset revealed iron deficiency-induced and functionally distinct regulons.

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Xiaolin Xiao

2014-01-01

Full Text Available 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

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

Science.gov (United States)

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

Extracellular NGFR Spacers Allow Efficient Tracking and Enrichment of Fully Functional CAR-T Cells Co-Expressing a Suicide Gene.

Science.gov (United States)

Casucci, Monica; Falcone, Laura; Camisa, Barbara; Norelli, Margherita; Porcellini, Simona; Stornaiuolo, Anna; Ciceri, Fabio; Traversari, Catia; Bordignon, Claudio; Bonini, Chiara; Bondanza, Attilio

2018-01-01

Chimeric antigen receptor (CAR)-T cell immunotherapy is at the forefront of innovative cancer therapeutics. However, lack of standardization of cellular products within the same clinical trial and lack of harmonization between different trials have hindered the clear identification of efficacy and safety determinants that should be unveiled in order to advance the field. With the aim of facilitating the isolation and in vivo tracking of CAR-T cells, we here propose the inclusion within the CAR molecule of a novel extracellular spacer based on the low-affinity nerve-growth-factor receptor (NGFR). We screened four different spacer designs using as target antigen the CD44 isoform variant 6 (CD44v6). We successfully generated NGFR-spaced CD44v6 CAR-T cells that could be efficiently enriched with clinical-grade immuno-magnetic beads without negative consequences on subsequent expansion, immuno-phenotype, in vitro antitumor reactivity, and conditional ablation when co-expressing a suicide gene. Most importantly, these cells could be tracked with anti-NGFR monoclonal antibodies in NSG mice, where they expanded, persisted, and exerted potent antitumor effects against both high leukemia and myeloma burdens. Similar results were obtained with NGFR-enriched CAR-T cells specific for CD19 or CEA, suggesting the universality of this strategy. In conclusion, we have demonstrated that the incorporation of the NGFR marker gene within the CAR sequence allows for a single molecule to simultaneously work as a therapeutic and selection/tracking gene. Looking ahead, NGFR spacer enrichment might allow good manufacturing procedures-manufacturing of standardized CAR-T cell products with high therapeutic potential, which could be harmonized in different clinical trials and used in combination with a suicide gene for future application in the allogeneic setting.

Extracellular NGFR Spacers Allow Efficient Tracking and Enrichment of Fully Functional CAR-T Cells Co-Expressing a Suicide Gene

Science.gov (United States)

Casucci, Monica; Falcone, Laura; Camisa, Barbara; Norelli, Margherita; Porcellini, Simona; Stornaiuolo, Anna; Ciceri, Fabio; Traversari, Catia; Bordignon, Claudio; Bonini, Chiara; Bondanza, Attilio

2018-01-01

Chimeric antigen receptor (CAR)-T cell immunotherapy is at the forefront of innovative cancer therapeutics. However, lack of standardization of cellular products within the same clinical trial and lack of harmonization between different trials have hindered the clear identification of efficacy and safety determinants that should be unveiled in order to advance the field. With the aim of facilitating the isolation and in vivo tracking of CAR-T cells, we here propose the inclusion within the CAR molecule of a novel extracellular spacer based on the low-affinity nerve-growth-factor receptor (NGFR). We screened four different spacer designs using as target antigen the CD44 isoform variant 6 (CD44v6). We successfully generated NGFR-spaced CD44v6 CAR-T cells that could be efficiently enriched with clinical-grade immuno-magnetic beads without negative consequences on subsequent expansion, immuno-phenotype, in vitro antitumor reactivity, and conditional ablation when co-expressing a suicide gene. Most importantly, these cells could be tracked with anti-NGFR monoclonal antibodies in NSG mice, where they expanded, persisted, and exerted potent antitumor effects against both high leukemia and myeloma burdens. Similar results were obtained with NGFR-enriched CAR-T cells specific for CD19 or CEA, suggesting the universality of this strategy. In conclusion, we have demonstrated that the incorporation of the NGFR marker gene within the CAR sequence allows for a single molecule to simultaneously work as a therapeutic and selection/tracking gene. Looking ahead, NGFR spacer enrichment might allow good manufacturing procedures-manufacturing of standardized CAR-T cell products with high therapeutic potential, which could be harmonized in different clinical trials and used in combination with a suicide gene for future application in the allogeneic setting. PMID:29619024

Extracellular NGFR Spacers Allow Efficient Tracking and Enrichment of Fully Functional CAR-T Cells Co-Expressing a Suicide Gene

Directory of Open Access Journals (Sweden)

Monica Casucci

2018-03-01

Full Text Available Chimeric antigen receptor (CAR-T cell immunotherapy is at the forefront of innovative cancer therapeutics. However, lack of standardization of cellular products within the same clinical trial and lack of harmonization between different trials have hindered the clear identification of efficacy and safety determinants that should be unveiled in order to advance the field. With the aim of facilitating the isolation and in vivo tracking of CAR-T cells, we here propose the inclusion within the CAR molecule of a novel extracellular spacer based on the low-affinity nerve-growth-factor receptor (NGFR. We screened four different spacer designs using as target antigen the CD44 isoform variant 6 (CD44v6. We successfully generated NGFR-spaced CD44v6 CAR-T cells that could be efficiently enriched with clinical-grade immuno-magnetic beads without negative consequences on subsequent expansion, immuno-phenotype, in vitro antitumor reactivity, and conditional ablation when co-expressing a suicide gene. Most importantly, these cells could be tracked with anti-NGFR monoclonal antibodies in NSG mice, where they expanded, persisted, and exerted potent antitumor effects against both high leukemia and myeloma burdens. Similar results were obtained with NGFR-enriched CAR-T cells specific for CD19 or CEA, suggesting the universality of this strategy. In conclusion, we have demonstrated that the incorporation of the NGFR marker gene within the CAR sequence allows for a single molecule to simultaneously work as a therapeutic and selection/tracking gene. Looking ahead, NGFR spacer enrichment might allow good manufacturing procedures-manufacturing of standardized CAR-T cell products with high therapeutic potential, which could be harmonized in different clinical trials and used in combination with a suicide gene for future application in the allogeneic setting.

Characterization of claustral neurons by comparative gene expression profiling and dye-injection analyses

Directory of Open Access Journals (Sweden)

Akiya eWatakabe

2014-05-01

Full Text Available The identity of the claustrum as a part of cerebral cortex, and in particular of the adjacent insular cortex, has been investigated by connectivity features and patterns of gene expression. In the present paper, we mapped the cortical and claustral expression of several cortical genes in rodent and macaque monkey brains (nurr1, latexin, cux2, and netrinG2 to further assess shared features between cortex and claustrum. In mice, these genes were densely expressed in the claustrum, but very sparsely in the cortex and not present in the striatum. To test whether the cortical vs. claustral cell types can be distinguished by co-expression of these genes, we performed a panel of double ISH in mouse and macaque brain. NetrinG2 and nurr1 genes were co-expressed across entire cortex and claustrum, but cux2 and nurr1 were co-expressed only in the insular cortex and claustrum. Latexin was expressed, in the macaque, only in the claustrum. The nurr1+ claustral neurons expressed VGluT1, a marker for cortical glutamatergic cells and send cortical projections. Taken together, our data suggest a partial commonality between claustral neurons and a subtype of cortical neurons in the monkey brain. Moreover, in the embryonic (E110 macaque brain, many nurr1+ neurons were scattered in the white matter between the claustrum and the insular cortex, possibly representing their migratory history. In a second set of experiments, we injected Lucifer Yellow intracellularly in mouse and rat slices to investigate whether dendrites of insular and claustral neurons can cross the border of the two brain regions. Dendrites of claustral neurons did not invade the overlying insular territory. In summary, gene expression profile of the claustrum is similar to that of the neocortex, in both rodent and macaque brains, but with modifications in density of expression and cellular co-localization of specific genes.

Preservation Analysis of Macrophage Gene Coexpression Between Human and Mouse Identifies PARK2 as a Genetically Controlled Master Regulator of Oxidative Phosphorylation in Humans

Directory of Open Access Journals (Sweden)

Veronica Codoni

2016-10-01

Full Text Available Macrophages are key players involved in numerous pathophysiological pathways and an in-depth characterization of their gene regulatory networks can help in better understanding how their dysfunction may impact on human diseases. We here conducted a cross-species network analysis of macrophage gene expression data between human and mouse to identify conserved networks across both species, and assessed whether such networks could reveal new disease-associated regulatory mechanisms. From a sample of 684 individuals processed for genome-wide macrophage gene expression profiling, we identified 27 groups of coexpressed genes (modules. Six modules were found preserved (P < 10−4 in macrophages from 86 mice of the Hybrid Mouse Diversity Panel. One of these modules was significantly [false discovery rate (FDR = 8.9 × 10−11] enriched for genes belonging to the oxidative phosphorylation (OXPHOS pathway. This pathway was also found significantly (FDR < 10−4 enriched in susceptibility genes for Alzheimer, Parkinson, and Huntington diseases. We further conducted an expression quantitative trait loci analysis to identify SNP that could regulate macrophage OXPHOS gene expression in humans. This analysis identified the PARK2 rs192804963 as a trans-acting variant influencing (minimal P-value = 4.3 × 10−8 the expression of most OXPHOS genes in humans. Further experimental work demonstrated that PARK2 knockdown expression was associated with increased OXPHOS gene expression in THP1 human macrophages. This work provided strong new evidence that PARK2 participates to the regulatory networks associated with oxidative phosphorylation and suggested that PARK2 genetic variations could act as a trans regulator of OXPHOS gene macrophage expression in humans.

cMapper: gene-centric connectivity mapper for EBI-RDF platform.

Science.gov (United States)

Shoaib, Muhammad; Ansari, Adnan Ahmad; Ahn, Sung-Min

2017-01-15

In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL. cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats. cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at

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

Directory of Open Access Journals (Sweden)

Sahra Uygun

2016-12-01

Full Text Available 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.

Disease gene characterization through large-scale co-expression analysis.

Directory of Open Access Journals (Sweden)

Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

A moth pheromone brewery: production of (Z)-11-hexadecenol by heterologous co-expression of two biosynthetic genes from a noctuid moth in a yeast cell factory.

Science.gov (United States)

Hagström, Åsa K; Wang, Hong-Lei; Liénard, Marjorie A; Lassance, Jean-Marc; Johansson, Tomas; Löfstedt, Christer

2013-12-13

Moths (Lepidoptera) are highly dependent on chemical communication to find a mate. Compared to conventional unselective insecticides, synthetic pheromones have successfully served to lure male moths as a specific and environmentally friendly way to control important pest species. However, the chemical synthesis and purification of the sex pheromone components in large amounts is a difficult and costly task. The repertoire of enzymes involved in moth pheromone biosynthesis in insecta can be seen as a library of specific catalysts that can be used to facilitate the synthesis of a particular chemical component. In this study, we present a novel approach to effectively aid in the preparation of semi-synthetic pheromone components using an engineered vector co-expressing two key biosynthetic enzymes in a simple yeast cell factory. We first identified and functionally characterized a ∆11 Fatty-Acyl Desaturase and a Fatty-Acyl Reductase from the Turnip moth, Agrotis segetum. The ∆11-desaturase produced predominantly Z11-16:acyl, a common pheromone component precursor, from the abundant yeast palmitic acid and the FAR transformed a series of saturated and unsaturated fatty acids into their corresponding alcohols which may serve as pheromone components in many moth species. Secondly, when we co-expressed the genes in the Brewer's yeast Saccharomyces cerevisiae, a set of long-chain fatty acids and alcohols that are not naturally occurring in yeast were produced from inherent yeast fatty acids, and the presence of (Z)-11-hexadecenol (Z11-16:OH), demonstrated that both heterologous enzymes were active in concert. A 100 ml batch yeast culture produced on average 19.5 μg Z11-16:OH. Finally, we demonstrated that oxidized extracts from the yeast cells containing (Z)-11-hexadecenal and other aldehyde pheromone compounds elicited specific electrophysiological activity from male antennae of the Tobacco budworm, Heliothis virescens, supporting the idea that genes from different

Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

Directory of Open Access Journals (Sweden)

Ettore Mosca

2017-09-01

Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

Directory of Open Access Journals (Sweden)

Chaoqun Li

2018-01-01

Full Text Available 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

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

Science.gov (United States)

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

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

Science.gov (United States)

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

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

Science.gov (United States)

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.

Heterologous co-expression of accA, fabD, and thioesterase genes for improving long-chain fatty acid production in Pseudomonas aeruginosa and Escherichia coli.

Science.gov (United States)

Lee, Sunhee; Jeon, Eunyoung; Jung, Yeontae; Lee, Jinwon

2012-05-01

The goal of the present study was to increase the content of intracellular long-chain fatty acids in two bacterial strains, Pseudomonas aeruginosa PA14 and Escherichia coli K-12 MG1655, by co-overexpressing essential enzymes that are involved in the fatty acid synthesis metabolic pathway. Recently, microbial fatty acids and their derivatives have been receiving increasing attention as an alternative source of fuel. By introducing two genes (accA and fabD) of P. aeruginosa into the two bacterial strains and by co-expressing with them the fatty acyl-acyl carrier protein thioesterase gene of Streptococcus pyogenes (strain MGAS10270), we have engineered recombinant strains that are efficient producers of long-chain fatty acids (C16 and C18). The recombinant strains exhibit a 1.3-1.7-fold increase in the production of long-chain fatty acids over the wild-type strains. To enhance the production of total long-chain fatty acids, we researched the carbon sources for optimized culture conditions and results were used for post-culture incubation period. E. coli SGJS17 (containing the accA, fabD, and thioesterase genes) produced the highest content of intracellular total fatty acids; in particular, the unsaturated fatty acid content was about 20-fold higher than that in the wild-type E. coli.

Comprehensive analysis of differential co-expression patterns reveal transcriptional dysregulation mechanism and identify novel prognostic lncRNAs in esophageal squamous cell carcinoma

Directory of Open Access Journals (Sweden)

Li Z

2017-06-01

Full Text Available Zhen Li,1 Qianlan Yao,1 Songjian Zhao,1 Yin Wang,2,3 Yixue Li,1,4 Zhen Wang4 1School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 2Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 3Collaborative Innovation Center for Genetics and Development, Fudan University, 4Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China Abstract: Esophageal squamous cell carcinoma (ESCC is one of the most common malignancies worldwide and occurs at a relatively high frequency in People’s Republic of China. However, the molecular mechanism underlying ESCC is still unclear. In this study, the mRNA and long non-coding RNA (lncRNA expression profiles of ESCC were downloaded from the Gene Expression Omnibus database, and then differential co-expression analysis was used to reveal the altered co-expression relationship of gene pairs in ESCC tumors. A total of 3,709 mRNAs and 923 lncRNAs were differentially co-expressed between normal and tumor tissues, and we found that most of the gene pairs lost associations in the tumor tissues. The differential regulatory networking approach deciphered that transcriptional dysregulation was ubiquitous in ESCC, and most of the differentially regulated links were modulated by 37 TFs. Our study also found that two novel lncRNAs (ADAMTS9-AS1 and AP000696.2 might be essential in the development of ectoderm and epithelial cells, which could significantly stratify ESCC patients into high-risk and low-risk groups, and were much better than traditional clinical tumor markers. Further inspection of two risk groups showed that the changes in TF-target regulation in the high-risk patients were significantly higher than those in the low-risk patients. In addition, four signal transduction-related DCmRNAs (ERBB3, ENSA, KCNK7, MFSD5

Genome-wide strategies identify downstream target genes of chick connective tissue-associated transcription factors.

Science.gov (United States)

Orgeur, Mickael; Martens, Marvin; Leonte, Georgeta; Nassari, Sonya; Bonnin, Marie-Ange; Börno, Stefan T; Timmermann, Bernd; Hecht, Jochen; Duprez, Delphine; Stricker, Sigmar

2018-03-29

Connective tissues support organs and play crucial roles in development, homeostasis and fibrosis, yet our understanding of their formation is still limited. To gain insight into the molecular mechanisms of connective tissue specification, we selected five zinc-finger transcription factors - OSR1, OSR2, EGR1, KLF2 and KLF4 - based on their expression patterns and/or known involvement in connective tissue subtype differentiation. RNA-seq and ChIP-seq profiling of chick limb micromass cultures revealed a set of common genes regulated by all five transcription factors, which we describe as a connective tissue core expression set. This common core was enriched with genes associated with axon guidance and myofibroblast signature, including fibrosis-related genes. In addition, each transcription factor regulated a specific set of signalling molecules and extracellular matrix components. This suggests a concept whereby local molecular niches can be created by the expression of specific transcription factors impinging on the specification of local microenvironments. The regulatory network established here identifies common and distinct molecular signatures of limb connective tissue subtypes, provides novel insight into the signalling pathways governing connective tissue specification, and serves as a resource for connective tissue development. © 2018. Published by The Company of Biologists Ltd.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

Science.gov (United States)

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics.

Science.gov (United States)

O'Reilly, Paul G; Wen, Qing; Bankhead, Peter; Dunne, Philip D; McArt, Darragh G; McPherson, Suzanne; Hamilton, Peter W; Mills, Ken I; Zhang, Shu-Dong

2016-05-04

Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. We describe QUADrATiC ( http://go.qub.ac.uk/QUADrATiC ), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts. QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than

Clustering approaches to identifying gene expression patterns from DNA microarray data.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Network-based identification of biomarkers coexpressed with multiple pathways.

Science.gov (United States)

Guo, Nancy Lan; Wan, Ying-Wooi

2014-01-01

Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

Directory of Open Access Journals (Sweden)

Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

The order of expression is a key factor in the production of active transglutaminase in Escherichia coli by co-expression with its pro-peptide

Directory of Open Access Journals (Sweden)

Liu Song

2011-12-01

Full Text Available Abstract Background Streptomyces transglutaminase (TGase is naturally synthesized as zymogen (pro-TGase, which is then processed to produce active enzyme by the removal of its N-terminal pro-peptide. This pro-peptide is found to be essential for overexpression of soluble TGase in E. coli. However, expression of pro-TGase by E. coli requires protease-mediated activation in vitro. In this study, we developed a novel co- expression method for the direct production of active TGase in E. coli. Results A TGase from S. hygroscopicus was expressed in E. coli only after fusing with the pelB signal peptide, but fusion with the signal peptide induced insoluble enzyme. Therefore, alternative protocol was designed by co-expressing the TGase and its pro-peptide as independent polypeptides under a single T7 promoter using vector pET-22b(+. Although the pro-peptide was co-expressed, the TGase fused without the signal peptide was undetectable in both soluble and insoluble fractions of the recombinant cells. Similarly, when both genes were expressed in the order of the TGase and the pro-peptide, the solubility of TGase fused with the signal peptide was not improved by the co-expression with its pro-peptide. Interestingly, active TGase was only produced by the cells in which the pro-peptide and the TGase were fused with the signal peptide and sequentially expressed. The purified recombinant and native TGase shared the similar catalytic properties. Conclusions Our results indicated that the pro-peptide can assist correct folding of the TGase inter-molecularly in E. coli, and expression of pro-peptide prior to that of TGase was essential for the production of active TGase. The co-expression strategy based on optimizing the order of gene expression could be useful for the expression of other functional proteins that are synthesized as a precursor.

Connections between EM2-containing terminals and GABA/μ-opioid receptor co-expressing neurons in the rat spinal trigeminal caudal nucleus

Science.gov (United States)

Li, Meng-Ying; Wu, Zhen-Yu; Lu, Ya-Cheng; Yin, Jun-Bin; Wang, Jian; Zhang, Ting; Dong, Yu-Lin; Wang, Feng

2014-01-01

Endomorphin-2 (EM2) demonstrates a potent antinociceptive effect via the μ-opioid receptor (MOR). To provide morphological evidence for the pain control effect of EM2, the synaptic connections between EM2-immunoreactive (IR) axonal terminals and γ-amino butyric acid (GABA)/MOR co-expressing neurons in lamina II of the spinal trigeminal caudal nucleus (Vc) were investigated in the rat. Dense EM2-, MOR- and GABA-IR fibers and terminals were mainly observed in lamina II of the Vc. Within lamina II, GABA- and MOR-neuronal cell bodies were also encountered. The results of immunofluorescent histochemical triple-staining showed that approximately 14.2 or 18.9% of GABA-IR or MOR-IR neurons also showed MOR- or GABA-immunopositive staining in lamina II; approximately 45.2 and 36.1% of the GABA-IR and MOR-IR neurons, respectively, expressed FOS protein in their nuclei induced by injecting formalin into the left lower lip of the mouth. Most of the GABA/MOR, GABA/FOS, and MOR/FOS double-labeled neurons made close contacts with EM2-IR fibers and terminals. Immuno-electron microscopy confirmed that the EM2-IR terminals formed synapses with GABA-IR or MOR-IR dendritic processes and neuronal cell bodies in lamina II of the Vc. These results suggest that EM2 might participate in pain transmission and modulation by binding to MOR-IR and GABAergic inhibitory interneuron in lamina II of the Vc to exert inhibitory effect on the excitatory interneuron in lamina II and projection neurons in laminae I and III. PMID:25386121

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

Directory of Open Access Journals (Sweden)

Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

Science.gov (United States)

Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Co-expression of the transcription factors CEH-14 and TTX-1 regulates AFD neuron-specific genes gcy-8 and gcy-18 in C. elegans.

Science.gov (United States)

Kagoshima, Hiroshi; Kohara, Yuji

2015-03-15

A wide variety of cells are generated by the expression of characteristic sets of genes, primarily those regulated by cell-specific transcription. To elucidate the mechanism regulating cell-specific gene expression in a highly specialized cell, AFD thermosensory neuron in Caenorhabditis elegans, we analyzed the promoter sequences of guanylyl cyclase genes, gcy-8 and gcy-18, exclusively expressed in AFD. In this study, we showed that AFD-specific expression of gcy-8 and gcy-18 requires the co-expression of homeodomain proteins, CEH-14/LHX3 and TTX-1/OTX1. We observed that mutation of ttx-1 or ceh-14 caused a reduction in the expression of gcy-8 and gcy-18 and that the expression was completely lost in double mutants. This synergy effect was also observed with other AFD marker genes, such as ntc-1, nlp-21and cng-3. Electrophoretic mobility shift assays revealed direct interaction of CEH-14 and TTX-1 proteins with gcy-8 and gcy-18 promoters in vitro. The binding sites of CEH-14 and TTX-1 proteins were confirmed to be essential for AFD-specific expression of gcy-8 and gcy-18 in vivo. We also demonstrated that forced expression of CEH-14 and TTX-1 in AWB chemosensory neurons induced ectopic expression of gcy-8 and gcy-18 reporters in this neuron. Finally, we showed that the regulation of gcy-8 and gcy-18 expression by ceh-14 and ttx-1 is evolutionally conserved in five Caenorhabditis species. Taken together, ceh-14 and ttx-1 expression determines the fate of AFD as terminal selector genes at the final step of cell specification. Copyright © 2015 Elsevier Inc. All rights reserved.

cudaMap: a GPU accelerated program for gene expression connectivity mapping.

Science.gov (United States)

McArt, Darragh G; Bankhead, Peter; Dunne, Philip D; Salto-Tellez, Manuel; Hamilton, Peter; Zhang, Shu-Dong

2013-10-11

Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take > 2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping. cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance. Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

Science.gov (United States)

Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Nenadic, Igor; Deco, Gustavo; Fañanás, Lourdes

2015-10-01

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. © 2015 Wiley Periodicals, Inc.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Coexpression of EGFR and CXCR4 predicts poor prognosis in resected pancreatic ductal adenocarcinoma.

Directory of Open Access Journals (Sweden)

Huanwen Wu

Full Text Available Epidermal growth factor receptor (EGFR is highly expressed in pancreatic ductal adenocarcinoma (PDAC and is involved in tumorigenesis and development. However, EGFR expression alone has limited clinical and prognostic significance. Recently, the cross-talk between EGFR and G-protein-coupled chemokine receptor CXCR4 has become increasingly recognized.In the present study, immunohistochemical staining of EGFR and CXCR4 was performed on paraffin-embedded specimens from 131 patients with surgically resected PDAC. Subsequently, the associations between EGFR expression, CXCR4 expression, EGFR/CXCR4 coexpression and clinicopathologic factors were assessed, and survival analyses were performed.In total, 64 (48.9% patients expressed EGFR, 68 (51.9% expressed CXCR4, and 33 (25.2% coexpressed EGFR and CXCR4. No significant association between EGFR and CXCR4 expression was observed (P = 0.938. EGFR expression significantly correlated with tumor differentiation (P = 0.031, whereas CXCR4 expression significantly correlated with lymph node metastasis (P = 0.001. EGFR/CXCR4 coexpression was significantly associated with lymph node metastasis (P = 0.026, TNM stage (P = 0.048, and poor tumor differentiation (P = 0.004. By univariate survival analysis, both CXCR4 expression and EGFR/CXCR4 coexpression were significant prognostic factors for poor disease-free survival (DFS and overall survival (OS. Moreover, EGFR/CXCR4 coexpression significantly increased the hazard ratio for both recurrence and death compared with EGFR or CXCR4 protein expression alone. Multivariate survival analysis demonstrated that EGFR/CXCR4 coexpression was an independent prognostic factor for DFS (HR = 2.33, P<0.001 and OS (HR = 2.48, P = 0.001.In conclusion, our data indicate that although EGFR expression alone has limited clinical and prognostic significance, EGFR/CXCR4 coexpression identified a subset of PDAC patients with more aggressive tumor characteristics and a significantly worse

Identification of conserved drought stress responsive gene-network across tissues and developmental stages in rice.

Science.gov (United States)

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.

Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

Directory of Open Access Journals (Sweden)

Fei Long

2015-01-01

Full Text Available Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC and non-small-cell lung cancer (NSCLC that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

Directory of Open Access Journals (Sweden)

Ning Ye

2015-01-01

Full Text Available 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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Parameswaran Ramachandran

Full Text Available 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.

Connecting protein and mRNA burst distributions for stochastic models of gene expression

International Nuclear Information System (INIS)

Elgart, Vlad; Jia, Tao; Fenley, Andrew T; Kulkarni, Rahul

2011-01-01

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

Divergent and convergent modes of interaction between wheat and Puccinia graminis f. sp. tritici isolates revealed by the comparative gene co-expression network and genome analyses.

Science.gov (United States)

Rutter, William B; Salcedo, Andres; Akhunova, Alina; He, Fei; Wang, Shichen; Liang, Hanquan; Bowden, Robert L; Akhunov, Eduard

2017-04-12

Two opposing evolutionary constraints exert pressure on plant pathogens: one to diversify virulence factors in order to evade plant defenses, and the other to retain virulence factors critical for maintaining a compatible interaction with the plant host. To better understand how the diversified arsenals of fungal genes promote interaction with the same compatible wheat line, we performed a comparative genomic analysis of two North American isolates of Puccinia graminis f. sp. tritici (Pgt). The patterns of inter-isolate divergence in the secreted candidate effector genes were compared with the levels of conservation and divergence of plant-pathogen gene co-expression networks (GCN) developed for each isolate. Comprative genomic analyses revealed substantial level of interisolate divergence in effector gene complement and sequence divergence. Gene Ontology (GO) analyses of the conserved and unique parts of the isolate-specific GCNs identified a number of conserved host pathways targeted by both isolates. Interestingly, the degree of inter-isolate sub-network conservation varied widely for the different host pathways and was positively associated with the proportion of conserved effector candidates associated with each sub-network. While different Pgt isolates tended to exploit similar wheat pathways for infection, the mode of plant-pathogen interaction varied for different pathways with some pathways being associated with the conserved set of effectors and others being linked with the diverged or isolate-specific effectors. Our data suggest that at the intra-species level pathogen populations likely maintain divergent sets of effectors capable of targeting the same plant host pathways. This functional redundancy may play an important role in the dynamic of the "arms-race" between host and pathogen serving as the basis for diverse virulence strategies and creating conditions where mutations in certain effector groups will not have a major effect on the pathogen

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

Science.gov (United States)

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Hydroxylation of recombinant human collagen type I alpha 1 in transgenic maize co-expressed with a recombinant human prolyl 4-hydroxylase

Directory of Open Access Journals (Sweden)

Pappu Kameshwari M

2011-06-01

Full Text Available Abstract Background Collagens require the hydroxylation of proline (Pro residues in their triple-helical domain repeating sequence Xaa-Pro-Gly to function properly as a main structural component of the extracellular matrix in animals at physiologically relevant conditions. The regioselective proline hydroxylation is catalyzed by a specific prolyl 4-hydroxylase (P4H as a posttranslational processing step. Results A recombinant human collagen type I α-1 (rCIα1 with high percentage of hydroxylated prolines (Hyp was produced in transgenic maize seeds when co-expressed with both the α- and β- subunits of a recombinant human P4H (rP4H. Germ-specific expression of rCIα1 using maize globulin-1 gene promoter resulted in an average yield of 12 mg/kg seed for the full-length rCIα1 in seeds without co-expression of rP4H and 4 mg/kg seed for the rCIα1 (rCIα1-OH in seeds with co-expression of rP4H. High-resolution mass spectrometry (HRMS analysis revealed that nearly half of the collagenous repeating triplets in rCIα1 isolated from rP4H co-expressing maize line had the Pro residues changed to Hyp residues. The HRMS analysis determined the Hyp content of maize-derived rCIα1-OH as 18.11%, which is comparable to the Hyp level of yeast-derived rCIα1-OH (17.47% and the native human CIa1 (14.59%, respectively. The increased Hyp percentage was correlated with a markedly enhanced thermal stability of maize-derived rCIα1-OH when compared to the non-hydroxylated rCIα1. Conclusions This work shows that maize has potential to produce adequately modified exogenous proteins with mammalian-like post-translational modifications that may be require for their use as pharmaceutical and industrial products.

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

Science.gov (United States)

Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

Science.gov (United States)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Recombinant amyloid beta-peptide production by coexpression with an affibody ligand

Science.gov (United States)

Macao, Bertil; Hoyer, Wolfgang; Sandberg, Anders; Brorsson, Ann-Christin; Dobson, Christopher M; Härd, Torleif

2008-01-01

Background Oligomeric and fibrillar aggregates of the amyloid β-peptide (Aβ) have been implicated in the pathogenesis of Alzheimer's disease (AD). The characterization of Aβ assemblies is essential for the elucidation of the mechanisms of Aβ neurotoxicity, but requires large quantities of pure peptide. Here we describe a novel approach to the recombinant production of Aβ. The method is based on the coexpression of the affibody protein ZAβ3, a selected affinity ligand derived from the Z domain three-helix bundle scaffold. ZAβ3 binds to the amyloidogenic central and C-terminal part of Aβ with nanomolar affinity and consequently inhibits aggregation. Results Coexpression of ZAβ3 affords the overexpression of both major Aβ isoforms, Aβ(1–40) and Aβ(1–42), yielding 4 or 3 mg, respectively, of pure 15N-labeled peptide per liter of culture. The method does not rely on a protein-fusion or -tag and thus does not require a cleavage reaction. The purified peptides were characterized by NMR, circular dichroism, SDS-PAGE and size exclusion chromatography, and their aggregation propensities were assessed by thioflavin T fluorescence and electron microscopy. The data coincide with those reported previously for monomeric, largely unstructured Aβ. ZAβ3 coexpression moreover permits the recombinant production of Aβ(1–42) carrying the Arctic (E22G) mutation, which causes early onset familial AD. Aβ(1–42)E22G is obtained in predominantly monomeric form and suitable, e.g., for NMR studies. Conclusion The coexpression of an engineered aggregation-inhibiting binding protein offers a novel route to the recombinant production of amyloidogenic Aβ peptides that can be advantageously employed to study the molecular basis of AD. The presented expression system is the first for which expression and purification of the aggregation-prone Arctic variant (E22G) of Aβ(1–42) is reported. PMID:18973685

Recombinant amyloid beta-peptide production by coexpression with an affibody ligand

Directory of Open Access Journals (Sweden)

Dobson Christopher M

2008-10-01

Full Text Available Abstract Background Oligomeric and fibrillar aggregates of the amyloid β-peptide (Aβ have been implicated in the pathogenesis of Alzheimer's disease (AD. The characterization of Aβ assemblies is essential for the elucidation of the mechanisms of Aβ neurotoxicity, but requires large quantities of pure peptide. Here we describe a novel approach to the recombinant production of Aβ. The method is based on the coexpression of the affibody protein ZAβ3, a selected affinity ligand derived from the Z domain three-helix bundle scaffold. ZAβ3 binds to the amyloidogenic central and C-terminal part of Aβ with nanomolar affinity and consequently inhibits aggregation. Results Coexpression of ZAβ3 affords the overexpression of both major Aβ isoforms, Aβ(1–40 and Aβ(1–42, yielding 4 or 3 mg, respectively, of pure 15N-labeled peptide per liter of culture. The method does not rely on a protein-fusion or -tag and thus does not require a cleavage reaction. The purified peptides were characterized by NMR, circular dichroism, SDS-PAGE and size exclusion chromatography, and their aggregation propensities were assessed by thioflavin T fluorescence and electron microscopy. The data coincide with those reported previously for monomeric, largely unstructured Aβ. ZAβ3 coexpression moreover permits the recombinant production of Aβ(1–42 carrying the Arctic (E22G mutation, which causes early onset familial AD. Aβ(1–42E22G is obtained in predominantly monomeric form and suitable, e.g., for NMR studies. Conclusion The coexpression of an engineered aggregation-inhibiting binding protein offers a novel route to the recombinant production of amyloidogenic Aβ peptides that can be advantageously employed to study the molecular basis of AD. The presented expression system is the first for which expression and purification of the aggregation-prone Arctic variant (E22G of Aβ(1–42 is reported.

Expression of lycopene biosynthesis genes fused in line with Shine-Dalgarno sequences improves the stress-tolerance of Lactococcus lactis.

Science.gov (United States)

Dong, Xiangrong; Wang, Yanping; Yang, Fengyuan; Zhao, Shanshan; Tian, Bing; Li, Tao

2017-01-01

Lycopene biosynthetic genes from Deinococcus radiodurans were co-expressed in Lactococcus lactis to produce lycopene and improve its tolerance to stress. Lycopene-related genes from D. radiodurans, DR1395 (crtE), DR0862 (crtB), and DR0861 (crtI), were fused in line with S hine-Dalgarno (SD) sequences and co-expressed in L. lactis. The recombinant strain produced 0.36 mg lycopene g -1  dry cell wt after 48 h fermentation. The survival rate to UV irradiation of the recombinant strain was higher than that of the non-transformed strain. The L. lactis with co-expressed genes responsible for lycopene biosynthesis from D. radiodurans produced lycopene and exhibited increased resistance to UV stress, suggesting that the recombinant strain has important application potential in food industry.

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

Science.gov (United States)

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

Discovery of cis-elements between sorghum and rice using co-expression and evolutionary conservation

Directory of Open Access Journals (Sweden)

Haberer Georg

2009-06-01

Full Text Available Abstract Background The spatiotemporal regulation of gene expression largely depends on the presence and absence of cis-regulatory sites in the promoter. In the economically highly important grass family, our knowledge of transcription factor binding sites and transcriptional networks is still very limited. With the completion of the sorghum genome and the available rice genome sequence, comparative promoter analyses now allow genome-scale detection of conserved cis-elements. Results In this study, we identified thousands of phylogenetic footprints conserved between orthologous rice and sorghum upstream regions that are supported by co-expression information derived from three different rice expression data sets. In a complementary approach, cis-motifs were discovered by their highly conserved co-occurrence in syntenic promoter pairs. Sequence conservation and matches to known plant motifs support our findings. Expression similarities of gene pairs positively correlate with the number of motifs that are shared by gene pairs and corroborate the importance of similar promoter architectures for concerted regulation. This strongly suggests that these motifs function in the regulation of transcript levels in rice and, presumably also in sorghum. Conclusion Our work provides the first large-scale collection of cis-elements for rice and sorghum and can serve as a paradigm for cis-element analysis through comparative genomics in grasses in general.

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

Science.gov (United States)

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.

Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine.

Science.gov (United States)

Kim, Jihye; Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kang, Jaewoo; Tan, Aik Choon

2018-01-01

Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.

Transcriptional dynamics of a conserved gene expression network associated with craniofacial divergence in Arctic charr.

Science.gov (United States)

Ahi, Ehsan Pashay; Kapralova, Kalina Hristova; Pálsson, Arnar; Maier, Valerie Helene; Gudbrandsson, Jóhannes; Snorrason, Sigurdur S; Jónsson, Zophonías O; Franzdóttir, Sigrídur Rut

2014-01-01

Understanding the molecular basis of craniofacial variation can provide insights into key developmental mechanisms of adaptive changes and their role in trophic divergence and speciation. Arctic charr (Salvelinus alpinus) is a polymorphic fish species, and, in Lake Thingvallavatn in Iceland, four sympatric morphs have evolved distinct craniofacial structures. We conducted a gene expression study on candidates from a conserved gene coexpression network, focusing on the development of craniofacial elements in embryos of two contrasting Arctic charr morphotypes (benthic and limnetic). Four Arctic charr morphs were studied: one limnetic and two benthic morphs from Lake Thingvallavatn and a limnetic reference aquaculture morph. The presence of morphological differences at developmental stages before the onset of feeding was verified by morphometric analysis. Following up on our previous findings that Mmp2 and Sparc were differentially expressed between morphotypes, we identified a network of genes with conserved coexpression across diverse vertebrate species. A comparative expression study of candidates from this network in developing heads of the four Arctic charr morphs verified the coexpression relationship of these genes and revealed distinct transcriptional dynamics strongly correlated with contrasting craniofacial morphologies (benthic versus limnetic). A literature review and Gene Ontology analysis indicated that a significant proportion of the network genes play a role in extracellular matrix organization and skeletogenesis, and motif enrichment analysis of conserved noncoding regions of network candidates predicted a handful of transcription factors, including Ap1 and Ets2, as potential regulators of the gene network. The expression of Ets2 itself was also found to associate with network gene expression. Genes linked to glucocorticoid signalling were also studied, as both Mmp2 and Sparc are responsive to this pathway. Among those, several transcriptional

Heat Shock Protein 70 Enhances Mucosal Immunity against Human Norovirus When Coexpressed from a Vesicular Stomatitis Virus Vector

Science.gov (United States)

Ma, Yuanmei; Duan, Yue; Wei, Yongwei; Liang, Xueya; Niewiesk, Stefan; Oglesbee, Michael

2014-01-01

uncultivable. Thus, a live vector-based vaccine may provide an alternative vaccine strategy. In this study, we developed a vesicular stomatitis virus (VSV)-based human NoV vaccine candidate. We constructed rVSV-HSP70-VP1, coexpressing heat shock protein (HSP70) and capsid (VP1) genes of human NoV, and rVSV-Luc-VP1, coexpressing firefly luciferase (Luc) and VP1 genes. We found that VSVs with a double gene insertion were significantly more attenuated than VSV with a single VP1 insertion (rVSV-VP1). Furthermore, we found that coexpression or coadministration of HSP70 from VSV vector significantly enhanced human NoV-specific mucosal immunity. Collectively, we developed an improved live vectored vaccine candidate for human NoV which will be useful for future clinical studies. PMID:24574391

Once for All: A Novel Robust System for Co-expression of Multiple Chimeric Fluorescent Fusion Proteins in Plants

Directory of Open Access Journals (Sweden)

Guitao Zhong

2017-06-01

Full Text Available Chimeric fluorescent fusion proteins have been employed as a powerful tool to reveal the subcellular localizations and dynamics of proteins in living cells. Co-expression of a fluorescent fusion protein with well-known organelle markers in the same cell is especially useful in revealing its spatial and temporal functions of the protein in question. However, the conventional methods for co-expressing multiple fluorescent tagged proteins in plants have the drawbacks of low expression efficiency, variations in the expression level and time-consuming genetic crossing. Here, we have developed a novel robust system that allows for high-efficient co-expression of multiple chimeric fluorescent fusion proteins in plants in a time-saving fashion. This system takes advantage of employing a single expression vector which consists of multiple semi-independent expressing cassettes for the protein co-expression thereby overcoming the limitations of using multiple independent expressing plasmids. In addition, it is a highly manipulable DNA assembly system, in which modification and recombination of DNA molecules are easily achieved through an optimized one-step assembly reaction. By employing this effective system, we demonstrated that co-expression of two chimeric fluorescent fusion reporter proteins of vacuolar sorting receptor and secretory carrier membrane protein gave rise to their perspective subcellular localizations in plants via both transient expression and stable transformation. Thus, we believed that this technical advance represents a promising approach for multi-color-protein co-expression in plant cells.

Characterization of differentially expressed genes involved in pathways associated with gastric cancer.

Directory of Open Access Journals (Sweden)

Hao Li

Full Text Available To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR value was 2. Subsequently, Gene Ontology (GO categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular networks

NARCIS (Netherlands)

R. Colak; F. Moser; J. Shu; A. Schönhuth (Alexander); N. Chen; M. Ester

2010-01-01

htmlabstractBackground 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

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

Science.gov (United States)

Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

Science.gov (United States)

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Novel algorithms reveal streptococcal transcriptomes and clues about undefined genes.

Science.gov (United States)

Ryan, Patricia A; Kirk, Brian W; Euler, Chad W; Schuch, Raymond; Fischetti, Vincent A

2007-07-01

Bacteria-host interactions are dynamic processes, and understanding transcriptional responses that directly or indirectly regulate the expression of genes involved in initial infection stages would illuminate the molecular events that result in host colonization. We used oligonucleotide microarrays to monitor (in vitro) differential gene expression in group A streptococci during pharyngeal cell adherence, the first overt infection stage. We present neighbor clustering, a new computational method for further analyzing bacterial microarray data that combines two informative characteristics of bacterial genes that share common function or regulation: (1) similar gene expression profiles (i.e., co-expression); and (2) physical proximity of genes on the chromosome. This method identifies statistically significant clusters of co-expressed gene neighbors that potentially share common function or regulation by coupling statistically analyzed gene expression profiles with the chromosomal position of genes. We applied this method to our own data and to those of others, and we show that it identified a greater number of differentially expressed genes, facilitating the reconstruction of more multimeric proteins and complete metabolic pathways than would have been possible without its application. We assessed the biological significance of two identified genes by assaying deletion mutants for adherence in vitro and show that neighbor clustering indeed provides biologically relevant data. Neighbor clustering provides a more comprehensive view of the molecular responses of streptococci during pharyngeal cell adherence.

Connective tissue growth factor is a substrate of ADAM28

International Nuclear Information System (INIS)

Mochizuki, Satsuki; Tanaka, Rena; Shimoda, Masayuki; Onuma, Junko; Fujii, Yutaka; Jinno, Hiromitsu; Okada, Yasunori

2010-01-01

Research highlights: → The hyper-variable region in the cysteine-rich domain of ADAM28 binds to C-terminal domain of CTGF. → ADAM28 cleaves CTGF alone and CTGF in the CTGF/VEGF 165 complex. → CTGF digestion by ADAM28 releases biologically active VEGF 165 from the complex. → ADAM28, CTGF and VEGF 165 are commonly co-expressed by carcinoma cells in human breast carcinoma tissues. → These suggest that ADAM28 promotes VEGF 165 -induced angiogenesis in the breast carcinomas by selective CTGF digestion in the CTGF/VEGF 165 complex. -- Abstract: ADAM28, a member of the ADAM (a disintegrin and metalloproteinase) gene family, is over-expressed by carcinoma cells and the expression correlates with carcinoma cell proliferation and progression in human lung and breast carcinomas. However, information about substrates of ADAM28 is limited. We screened interacting molecules of ADAM28 in human lung cDNA library by yeast two-hybrid system and identified connective tissue growth factor (CTGF). Binding of CTGF to proADAM28 was demonstrated by yeast two-hybrid assay and protein binding assay. ADAM28 cleaved CTGF in dose- and time-dependent manners at the Ala 181 -Tyr 182 and Asp 191 -Pro 192 bonds in the hinge region of the molecule. ADAM28 selectively digested CTGF in the complex of CTGF and vascular endothelial growth factor 165 (VEGF 165 ), releasing biologically active VEGF 165 from the complex. RT-PCR and immunohistochemical analyses demonstrated that ADAM28, CTGF and VEGF are commonly co-expressed in the breast carcinoma tissues. These data provide the first evidence that CTGF is a novel substrate of ADAM28 and suggest that ADAM28 may promote VEGF 165 -induced angiogenesis in the breast carcinomas by the CTGF digestion in the CTGF/VEGF 165 complex.

Coexpression of β-D-galactosidase and L-arabinose isomerase in the production of D-tagatose: a functional sweetener.

Science.gov (United States)

Zhan, Yijing; Xu, Zheng; Li, Sha; Liu, Xiaoliu; Xu, Lu; Feng, Xiaohai; Xu, Hong

2014-03-19

The functional sweetener, d-tagatose, is commonly transformed from galactose by l-arabinose isomerase. To make use of a much cheaper starting material, lactose, hydrolization, and isomerization are required to take place collaboratively. Therefore, a single-step method involving β-d-galactosidase was explored for d-tagatose production. The two vital genes, β-d-galactosidase gene (lacZ) and l-arabinose isomerase mutant gene (araA') were extracted separately from Escherichia coli strains and incorporated into E. coli simultaneously. This gave us E. coli-ZY, a recombinant producing strain capable of coexpressing the two key enzymes. The resulted cells exhibited maximum d-tagatose producing activity at 34 °C and pH 6.5 and in the presence of borate, 10 mM Fe(2+), and 1 mM Mn(2+). Further monitoring showed that the recombinant cells could hydrolyze more than 95% lactose and convert 43% d-galactose into d-tagatose. This research has verified the feasibility of single-step d-tagatose fermentation, thereby laying down the foundation for industrial usage of lactose.

The Epstein-Barr virus BFRF1 and BFLF2 proteins interact and coexpression alters their cellular localization

International Nuclear Information System (INIS)

Lake, Cathleen M.; Hutt-Fletcher, Lindsey M.

2004-01-01

The BFRF1 protein of Epstein-Barr virus (EBV) is a recently identified membrane protein that is the homolog of the alphaherpesvirus UL34 gene product. We report here that a yeast two-hybrid screen identified the BFLF2 gene product, a homolog of alphaherpesvirus UL31, as a protein that interacts with BFRF1. Expression of BFLF2 in mammalian cells revealed a protein of approximately 28 kDa that associated with BFRF1 in a noncovalently linked complex. When expressed alone, the BFRF1 protein was found in the cytoplasm and perinuclear region. BFLF2 was found diffusely in the nucleus in the absence of BFRF1, but coexpression of BFRF1 and BFLF2 resulted in colocalization of the two proteins at the nuclear rim. These data recapitulate the behavior of the alphaherpesvirus homologs of BFRF1 and BFLF2 and suggest that functional as well as structural and positional homology may be conserved

In vivo modification of tyrosine residues in recombinant mussel adhesive protein by tyrosinase co-expression in Escherichia coli

Directory of Open Access Journals (Sweden)

Choi Yoo

2012-10-01

Full Text Available Abstract Background In nature, mussel adhesive proteins (MAPs show remarkable adhesive properties, biocompatibility, and biodegradability. Thus, they have been considered promising adhesive biomaterials for various biomedical and industrial applications. However, limited production of natural MAPs has hampered their practical applications. Recombinant production in bacterial cells could be one alternative to obtain useable amounts of MAPs, although additional post-translational modification of tyrosine residues into 3,4-dihydroxyphenyl-alanine (Dopa and Dopaquinone is required. The superior properties of MAPs are mainly attributed to the introduction of quinone-derived intermolecular cross-links. To solve this problem, we utilized a co-expression strategy of recombinant MAP and tyrosinase in Escherichia coli to successfully modify tyrosine residues in vivo. Results A recombinant hybrid MAP, fp-151, was used as a target for in vivo modification, and a dual vector system of pET and pACYC-Duet provided co-expression of fp-151 and tyrosinase. As a result, fp-151 was over-expressed and mainly obtained from the soluble fraction in the co-expression system. Without tyrosinase co-expression, fp-151 was over-expressed in an insoluble form in inclusion bodies. The modification of tyrosine residues in the soluble-expressed fp-151 was clearly observed from nitroblue tetrazolium staining and liquid-chromatography-mass/mass spectrometry analyses. The purified, in vivo modified, fp-151 from the co-expression system showed approximately 4-fold higher bulk-scale adhesive strength compared to in vitro tyrosinase-treated fp-151. Conclusion Here, we reported a co-expression system to obtain in vivo modified MAP; additional in vitro tyrosinase modification was not needed to obtain adhesive properties and the in vivo modified MAP showed superior adhesive strength compared to in vitro modified protein. It is expected that this co-expression strategy will accelerate

Protein Coexpression Using FMDV 2A: Effect of “Linker” Residues

Directory of Open Access Journals (Sweden)

Ekaterina Minskaia

2013-01-01

Full Text Available Many biomedical applications absolutely require, or are substantially enhanced by, coexpression of multiple proteins from a single vector. Foot-and-mouth disease virus 2A (F2A and “2A-like” sequences (e.g., Thosea asigna virus 2A; T2A are used widely for this purpose since multiple proteins can be coexpressed by linking open reading frames (ORFs to form a single cistron. The activity of F2A “cleavage” may, however, be compromised by both the use of shorter versions of F2A and the sequences (derived from multiple-purpose cloning sites used to link F2A to the upstream protein. To characterise these effects, different lengths of F2A and T2A were inserted between green and cherry fluorescent proteins. Mutations were introduced in the linker region immediately upstream of both F2A- and T2A-based constructs and activities determined using both cell-free translation systems and transfected cells. In shorter versions of F2A, activity may be affected by both the C-terminal sequence of the protein upstream and, equally strikingly, the residues immediately upstream introduced during cloning. Mutations significantly improved activity for shorter versions of F2A but could decrease activity in the case of T2A. These data will aid the design of cloning strategies for the co-expression of multiple proteins in biomedical/biotechnological applications.

TESTING HIGH-DIMENSIONAL COVARIANCE MATRICES, WITH APPLICATION TO DETECTING SCHIZOPHRENIA RISK GENES.

Science.gov (United States)

Zhu, Lingxue; Lei, Jing; Devlin, Bernie; Roeder, Kathryn

2017-09-01

Scientists routinely compare gene expression levels in cases versus controls in part to determine genes associated with a disease. Similarly, detecting case-control differences in co-expression among genes can be critical to understanding complex human diseases; however statistical methods have been limited by the high dimensional nature of this problem. In this paper, we construct a sparse-Leading-Eigenvalue-Driven (sLED) test for comparing two high-dimensional covariance matrices. By focusing on the spectrum of the differential matrix, sLED provides a novel perspective that accommodates what we assume to be common, namely sparse and weak signals in gene expression data, and it is closely related with Sparse Principal Component Analysis. We prove that sLED achieves full power asymptotically under mild assumptions, and simulation studies verify that it outperforms other existing procedures under many biologically plausible scenarios. Applying sLED to the largest gene-expression dataset obtained from post-mortem brain tissue from Schizophrenia patients and controls, we provide a novel list of genes implicated in Schizophrenia and reveal intriguing patterns in gene co-expression change for Schizophrenia subjects. We also illustrate that sLED can be generalized to compare other gene-gene "relationship" matrices that are of practical interest, such as the weighted adjacency matrices.

VSNL1 Co-expression networks in aging include calcium signaling, synaptic plasticity, and Alzheimer’s disease pathways

Directory of Open Access Journals (Sweden)

C W Lin

2015-03-01

Full Text Available The Visinin-like 1 (VSNL1 gene encodes Visinin-like protein 1, a peripheral biomarker for Alzheimer disease (AD. Little is known, however, about normal VSNL1 expression in brain and the biologic networks in which it participates. Frontal cortex gray matter from 209 subjects without neurodegenerative or psychiatric illness, ranging in age from 16–91, were processed on Affymetrix GeneChip 1.1 ST and Human SNP Array 6.0. VSNL1 expression was unaffected by age and sex, and not significantly associated with SNPs in cis or trans. VSNL1 was significantly co-expressed with genes in pathways for Calcium Signaling, AD, Long Term Potentiation, Long Term Depression, and Trafficking of AMPA Receptors. The association with AD was driven, in part, by correlation with amyloid precursor protein (APP expression. These findings provide an unbiased link between VSNL1 and molecular mechanisms of AD, including pathways implicated in synaptic pathology in AD. Whether APP may drive increased VSNL1 expression, VSNL1 drives increased APP expression, or both are downstream of common pathogenic regulators will need to be evaluated in model systems.

Functionally enigmatic genes: a case study of the brain ignorome.

Directory of Open Access Journals (Sweden)

Ashutosh K Pandey

Full Text Available What proportion of genes with intense and selective expression in specific tissues, cells, or systems are still almost completely uncharacterized with respect to biological function? In what ways do these functionally enigmatic genes differ from well-studied genes? To address these two questions, we devised a computational approach that defines so-called ignoromes. As proof of principle, we extracted and analyzed a large subset of genes with intense and selective expression in brain. We find that publications associated with this set are highly skewed--the top 5% of genes absorb 70% of the relevant literature. In contrast, approximately 20% of genes have essentially no neuroscience literature. Analysis of the ignorome over the past decade demonstrates that it is stubbornly persistent, and the rapid expansion of the neuroscience literature has not had the expected effect on numbers of these genes. Surprisingly, ignorome genes do not differ from well-studied genes in terms of connectivity in coexpression networks. Nor do they differ with respect to numbers of orthologs, paralogs, or protein domains. The major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum--a genomic bandwagon effect. Finally we ask to what extent massive genomic, imaging, and phenotype data sets can be used to provide high-throughput functional annotation for an entire ignorome. In a majority of cases we have been able to extract and add significant information for these neglected genes. In several cases--ELMOD1, TMEM88B, and DZANK1--we have exploited sequence polymorphisms, large phenome data sets, and reverse genetic methods to evaluate the function of ignorome genes.

Functionally enigmatic genes: a case study of the brain ignorome.

Science.gov (United States)

Pandey, Ashutosh K; Lu, Lu; Wang, Xusheng; Homayouni, Ramin; Williams, Robert W

2014-01-01

What proportion of genes with intense and selective expression in specific tissues, cells, or systems are still almost completely uncharacterized with respect to biological function? In what ways do these functionally enigmatic genes differ from well-studied genes? To address these two questions, we devised a computational approach that defines so-called ignoromes. As proof of principle, we extracted and analyzed a large subset of genes with intense and selective expression in brain. We find that publications associated with this set are highly skewed--the top 5% of genes absorb 70% of the relevant literature. In contrast, approximately 20% of genes have essentially no neuroscience literature. Analysis of the ignorome over the past decade demonstrates that it is stubbornly persistent, and the rapid expansion of the neuroscience literature has not had the expected effect on numbers of these genes. Surprisingly, ignorome genes do not differ from well-studied genes in terms of connectivity in coexpression networks. Nor do they differ with respect to numbers of orthologs, paralogs, or protein domains. The major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum--a genomic bandwagon effect. Finally we ask to what extent massive genomic, imaging, and phenotype data sets can be used to provide high-throughput functional annotation for an entire ignorome. In a majority of cases we have been able to extract and add significant information for these neglected genes. In several cases--ELMOD1, TMEM88B, and DZANK1--we have exploited sequence polymorphisms, large phenome data sets, and reverse genetic methods to evaluate the function of ignorome genes.

Interactions between co-expressed Arabidopsis sucrose transporters in the split-ubiquitin system

Directory of Open Access Journals (Sweden)

Lalonde Sylvie

2003-03-01

Full Text Available Abstract Background The Arabidopsis genome contains nine sucrose transporter paralogs falling into three clades: SUT1-like, SUT2 and SUT4. The carriers differ in their kinetic properties. Many transport proteins are known to exist as oligomers. The yeast-based split ubiquitin system can be used to analyze the ability of membrane proteins to interact. Results Promoter-GUS fusions were used to analyze the cellular expression of the three transporter genes in transgenic Arabidopsis plants. All three fusion genes are co-expressed in companion cells. Protein-protein interactions between Arabidopsis sucrose transporters were tested using the split ubiquitin system. Three paralogous sucrose transporters are capable of interacting as either homo- or heteromers. The interactions are specific, since a potassium channel and a glucose transporter did not show interaction with sucrose transporters. Also the biosynthetic and metabolizing enzymes, sucrose phosphate phosphatase and sucrose synthase, which were found to be at least in part bound to the plasma membrane, did not specifically interact with sucrose transporters. Conclusions The split-ubiquitin system provides a powerful tool to detect potential interactions between plant membrane proteins by heterologous expression in yeast, and can be used to screen for interactions with membrane proteins as baits. Like other membrane proteins, the Arabidopsis sucrose transporters are able to form oligomers. The biochemical approaches are required to confirm the in planta interaction.

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

Directory of Open Access Journals (Sweden)

Shuchi eSmita

2015-12-01

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

Co-expression of the C-terminal domain of Yersinia enterocolitica ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Biosciences; Volume 40; Issue 1. Co-expression of the C-terminal domain of Yersinia enterocolitica invasin enhances the efficacy of classical swine-fever-vectored vaccine based on human adenovirus. Helin Li Pengbo Ning Zhi Lin Wulong Liang Kai Kang Lei He Yanming Zhang. Articles Volume ...

Identification and network-enabled characterization of auxin response factor genes in Medicago truncatula

Directory of Open Access Journals (Sweden)

David J. Burks

2016-12-01

Full Text Available The Auxin Response Factor (ARF family of transcription factors is an important regulator of environmental response and symbiotic nodulation in the legume Medicago truncatula. While previous studies have identified members of this family, a recent spurt in gene expression data coupled with genome update and reannotation calls for a reassessment of the prevalence of ARF genes and their interaction networks in M. truncatula. We performed a comprehensive analysis of the M. truncatula genome and transcriptome that entailed search for novel ARF genes and the co-expression networks. Our investigation revealed 8 novel M. truncatula ARF (MtARF genes, of the total 22 identified, and uncovered novel gene co-expression networks as well. Furthermore, the topological clustering and single enrichment analysis of several network models revealed the roles of individual members of the MtARF family in nitrogen regulation, nodule initiation, and post-embryonic development through a specialized protein packaging and secretory pathway. In summary, this study not just shines new light on an important gene family, but also provides a guideline for identification of new members of gene families and their functional characterization through network analyses.

Genome-Scale Co-Expression Network Comparison across Escherichia coli and Salmonella enterica Serovar Typhimurium Reveals Significant Conservation at the Regulon Level of Local Regulators Despite Their Dissimilar Lifestyles

Science.gov (United States)

Zarrineh, Peyman; Sánchez-Rodríguez, Aminael; Hosseinkhan, Nazanin; Narimani, Zahra; Marchal, Kathleen; Masoudi-Nejad, Ali

2014-01-01

Availability of genome-wide gene expression datasets provides the opportunity to study gene expression across different organisms under a plethora of experimental conditions. In our previous work, we developed an algorithm called COMODO (COnserved MODules across Organisms) that identifies conserved expression modules between two species. In the present study, we expanded COMODO to detect the co-expression conservation across three organisms by adapting the statistics behind it. We applied COMODO to study expression conservation/divergence between Escherichia coli, Salmonella enterica, and Bacillus subtilis. We observed that some parts of the regulatory interaction networks were conserved between E. coli and S. enterica especially in the regulon of local regulators. However, such conservation was not observed between the regulatory interaction networks of B. subtilis and the two other species. We found co-expression conservation on a number of genes involved in quorum sensing, but almost no conservation for genes involved in pathogenicity across E. coli and S. enterica which could partially explain their different lifestyles. We concluded that despite their different lifestyles, no significant rewiring have occurred at the level of local regulons involved for instance, and notable conservation can be detected in signaling pathways and stress sensing in the phylogenetically close species S. enterica and E. coli. Moreover, conservation of local regulons seems to depend on the evolutionary time of divergence across species disappearing at larger distances as shown by the comparison with B. subtilis. Global regulons follow a different trend and show major rewiring even at the limited evolutionary distance that separates E. coli and S. enterica. PMID:25101984

Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

Science.gov (United States)

Zhang, Ao; Tian, Suyan

2018-05-01

Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Usage of U7 snRNA in gene therapy of hemoglobin C disorder ...

African Journals Online (AJOL)

Here, a bioinformatic analysis was performed to study the effect of co-expression between human Hb C b-globin chain gene and U7.623. The gene ontological results show that full recovery of hemoglobin function and biological process can be derived. This confirms that U7 snRNA can be a good tool for gene therapy in Hb ...

The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

DEFF Research Database (Denmark)

Corwin, Jason A; Copeland, Daniel; Feusier, Julie

2016-01-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabido......The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used....... cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence...... genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance...

An efficient co-expression and purification system for the complex of Stx4 and C-terminal domain of Synip

International Nuclear Information System (INIS)

Tian Wei; Ma Cong; Liu Yingfang; Xu Tao

2008-01-01

Synip and Stx4 complex plays a key role in GLUT4 vesicle trafficking and fusion with plasma membrane. The interaction of Synip with Stx4 prevents interaction of VAMP2 located in GLUT4 vesicle with Stx4 in basal state. Insulin induces the dissociation of the Synip and Stx4 complex, and then triggers VAMP2 to interact with Stx4 to form the SNARE complex, thus promoting the vesicle fusion. In this report, we adopt a novel system for co-expression of the Synip and Stx4 by using two common vectors pGEX6p-1 and pET28a(+) to investigate their expression, purification, and interaction. Through this co-expression system, we successfully co-expressed the Synip and Stx4 complex with high yield, and co-purified at an approximate 1:1 molar ratio with high purity (95%). We also demonstrate that the 1-28 residues of Stx4 are dispensable for interaction with Synip using this co-expression system

Efficient androst-1,4-diene-3,17-dione production by co-expressing 3-ketosteroid-Δ1 -dehydrogenase and catalase in Bacillus subtilis.

Science.gov (United States)

Shao, M; Sha, Z; Zhang, X; Rao, Z; Xu, M; Yang, T; Xu, Z; Yang, S

2017-01-01

3-ketosteroid-Δ 1 -dehydrogenase (KSDD), a flavin adenine dinucleotide (FAD)-dependent enzyme involved in sterol metabolism, specifically catalyses the conversion of androst-4-ene-3,17-dione (AD) to androst-1,4-diene-3,17-dione (ADD). However, the low KSDD activity and the toxic effects of hydrogen peroxide (H 2 O 2 ) generated during the biotransformation of AD to ADD with FAD regeneration hinder its application on AD conversion. The aim of this work was to improve KSDD activity and eliminate the toxic effects of the generated H 2 O 2 to enhance ADD production. The ksdd gene obtained from Mycobacterium neoaurum JC-12 was codon-optimized to increase its expression level in Bacillus subtilis, and the KSDD activity reached 12·3 U mg -1 , which was sevenfold of that of codon-unoptimized gene. To improve AD conversion, catalase was co-expressed with KSDD in B. subtilis 168/pMA5-ksdd opt -katA to eliminate the toxic effects of H 2 O 2 generated during AD conversion. Finally, under optimized bioconversion conditions, fed-batch strategy was carried out and the ADD yield improved to 8·76 g l -1 . This work demonstrates the potential to improve enzyme activity by codon-optimization and eliminate the toxic effects of H 2 O 2 by co-expressing catalase. This study showed the highest ADD productivity ever reported and provides a promising strain for efficient ADD production in the pharmaceutical industry. © 2016 The Society for Applied Microbiology.

Autosomal dominant Marfan-like connective-tissue disorder with aortic dilation and skeletal anomaslies not linked to the Fibrillin genes

Energy Technology Data Exchange (ETDEWEB)

Boileau, C.; Coulon, M.; Alexandre, J.-A.; Junien, C. (Laboratorie Central de Biochimie et de Genetique Moleculaire (France)); Jondeau, G.; Delorme, G.; Dubourg, O.; Bourdarias, J.-P. (CHU Ambroise Pare, Boulogne (France)); Babron, M.-C.; Bonaieti-Pellie, C. (INSERM, Chateau de Longchamp, Paris (France)); Sakai, L. (Shriners' Hospital for Crippled Children, Portland, OR (United States)); Melki, J. (Hopital Necker-Enfants Malades, Paris (France))

1993-07-01

The authors describe a large family with a connective-tissue disorder that exhibits some of the skeletal and cardiovascular features seen in Marfan syndrome. However, none of the 19 affected individuals displayed ocular abnormalities and therefore did not comply with recognized criteria for this disease. These patients could alternatively be diagnosed as MASS (mitral valve, aorta, skeleton, and skin) phenotype patients or represent a distinct clinical entity, i.e., a new autosomal dominant connective-tissue disorder. The fibrillin genes located on chromosomes 15 and 5 are clearly involved in the classic form of Marfan syndrome and a clinically related disorder (congenital contractural arachnodactyly), respectively. To test whether one of these genes was also implicated in this French family, the authors performed genetic analyses. Blood samples were obtained for 56 family members, and four polymorphic fibrillin gene markers, located on chromosomes 15 (Fib15) and 5 (Fib5), respectively, were tested. Linkage between the disease allele and the markers of these two genes was excluded with lod scores of [minus]11.39 (for Fib15) and [minus]13.34 (for Fib5), at 0 = .001, indicating that the mutation is at a different locus. This phenotype thus represents a new connective-tissue disorder, overlapping but different from classic Marfan syndrome. 33 refs., 1 fig. 2 tabs.

Phenotypic characterization of neurotensin messenger RNA-expressing cells in the neuroleptic-treated rat striatum: a detailed cellular co-expression study

Energy Technology Data Exchange (ETDEWEB)

Emson, P C; Westmore, K; Augood, S J [MRC Molecular Neuroscience Group, The Department of Neurobiology, The Babraham Institute, Babraham, Cambridge (United Kingdom)

1996-12-11

The chemical phenotype of proneurotensin messenger RNA-expressing cells was determined in the acute haloperidol-treated rat striatum using a combination of [{sup 35}S]-labelled and alkaline phosphatase-labelled oligonucleotides. Cellular sites of proneurotensin messenger RNA expression were visualized simultaneously on tissue sections processed to reveal cellular sites of preproenkephalin A messenger RNA or the dopamine and adenylate cyclase phosphoprotein-32, messenger RNA. The cellular co-expression of preproenkepahlin A and preprotachykinin messenger RNA was also examined within forebrain structures. Cellular sites of preproenkephalin A and dopamine and adenylate cyclase phosphoprotein-32 messenger RNAs were visualized using alkaline phosphatase-labelled oligonucleotides whilst sites of preprotachykinin and proneurotensin messenger RNA expression were detected using [{sup 35}S]-labelled oligos. Cellular sites of enkephalin and dopamine and adenylate cyclase phosphoprotein-32 gene expression were identified microscopically by the concentration of purple alkaline phosphatase reaction product within the cell cytoplasm, whereas sites of substance P and proneurotensin gene expression were identified by the dense clustering of silver grains overlying cells.An intense hybridization signal was detected for all three neuropeptide messenger RNAs in the striatum, the nucleus accumbens and septum. Dopamine and adenylate cyclase phosphoprotein-32 messenger RNA was detected within the neostriatum but not within the septum. In all forebrain regions examined, with the exception of the islands of Cajella, the cellular expression of enkephalin messenger RNA and substance P messenger RNA was discordant; the two neuropeptide messenger RNAs were detected essentially in different cells, although in the striatum and nucleus accumbens occasional isolated cells were detected which contained both hybridization signals; dense clusters of silver grains overlay alkaline phosphatase

Phenotypic characterization of neurotensin messenger RNA-expressing cells in the neuroleptic-treated rat striatum: a detailed cellular co-expression study

International Nuclear Information System (INIS)

Emson, P.C.; Westmore, K.; Augood, S.J.

1996-01-01

The chemical phenotype of proneurotensin messenger RNA-expressing cells was determined in the acute haloperidol-treated rat striatum using a combination of [ 35 S]-labelled and alkaline phosphatase-labelled oligonucleotides. Cellular sites of proneurotensin messenger RNA expression were visualized simultaneously on tissue sections processed to reveal cellular sites of preproenkephalin A messenger RNA or the dopamine and adenylate cyclase phosphoprotein-32, messenger RNA. The cellular co-expression of preproenkepahlin A and preprotachykinin messenger RNA was also examined within forebrain structures. Cellular sites of preproenkephalin A and dopamine and adenylate cyclase phosphoprotein-32 messenger RNAs were visualized using alkaline phosphatase-labelled oligonucleotides whilst sites of preprotachykinin and proneurotensin messenger RNA expression were detected using [ 35 S]-labelled oligos. Cellular sites of enkephalin and dopamine and adenylate cyclase phosphoprotein-32 gene expression were identified microscopically by the concentration of purple alkaline phosphatase reaction product within the cell cytoplasm, whereas sites of substance P and proneurotensin gene expression were identified by the dense clustering of silver grains overlying cells.An intense hybridization signal was detected for all three neuropeptide messenger RNAs in the striatum, the nucleus accumbens and septum. Dopamine and adenylate cyclase phosphoprotein-32 messenger RNA was detected within the neostriatum but not within the septum. In all forebrain regions examined, with the exception of the islands of Cajella, the cellular expression of enkephalin messenger RNA and substance P messenger RNA was discordant; the two neuropeptide messenger RNAs were detected essentially in different cells, although in the striatum and nucleus accumbens occasional isolated cells were detected which contained both hybridization signals; dense clusters of silver grains overlay alkaline phosphatase-positive cells

Radiochemotherapy of hepatocarcinoma via lentivirus-mediated transfer of human sodium iodide symporter gene and herpes simplex virus thymidine kinase gene

Energy Technology Data Exchange (ETDEWEB)

Chen Libo, E-mail: libochen888@hotmail.com [Department of Nuclear Medicine, Shanghai Sixth People' s Hospital, Shanghai Jiao Tong University, Shanghai 200233 (China); Guo Guoying [Xinyuan Institute of Medicine and Biotechnology, School of Life Sciences, Zhejiang Sci-Tech University, Hangzhou 310018 (China); Liu Tianjing; Guo Lihe [Division of Biochemistry and Cell Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031 (China); Zhu Ruisen [Department of Nuclear Medicine, Shanghai Sixth People' s Hospital, Shanghai Jiao Tong University, Shanghai 200233 (China)

2011-07-15

Herpes simplex virus thymidine kinase (HSV-TK) gene/ganciclovir (GCV) system has been widely used as a traditional gene therapy modality, and the sodium/iodide symporter gene (NIS) has been found to be a novel therapeutic gene. Since the therapeutic effects of radioiodine therapy or prodrug chemotherapy on cancers following NIS or HSV-TK gene transfer need to be enhanced, this study was designed to investigate the feasibility of radiochemotherapy for hepatocarcinoma via coexpression of NIS gene and HSV-TK gene. Methods: HepG2 cells were stably transfected with NIS, TK and GFP gene via recombinant lentiviral vector and named HepG2/NTG. Gene expression was examined by reverse transcriptase polymerase chain reaction, fluorescence imaging and iodide uptake. The therapeutic effects were assessed by MTT assay and clonogenic assay. Results: HepG2/NTG cells concentrated {sup 125}I{sup -} up to 76-fold higher than the wild-type cells within 20 min, and the efflux happened with a T{sub 1/2eff} of less than 10 min. The iodide uptake in HepG2/NTG cells was specifically inhibited by sodium perchlorate. Dose-dependent toxicity to HepG2/NTG cells by either GCV or {sup 131}I was revealed by clonogenic assay and MTT assay, respectively. The survival rate of HepG2/NTG cells decreased to 49.7%{+-}2.5%, 43.4%{+-}2.8% and 8.6%{+-}1.2% after exposure to {sup 131}I, GCV and combined therapy, respectively. Conclusion: We demonstrate that radiochemotherapy of hepatocarcinoma via lentiviral-mediated coexpression of NIS gene and HSV-TK gene leads to stronger killing effect than single treatment, and in vivo studies are needed to verify these findings.

Radiochemotherapy of hepatocarcinoma via lentivirus-mediated transfer of human sodium iodide symporter gene and herpes simplex virus thymidine kinase gene

International Nuclear Information System (INIS)

Chen Libo; Guo Guoying; Liu Tianjing; Guo Lihe; Zhu Ruisen

2011-01-01

Herpes simplex virus thymidine kinase (HSV-TK) gene/ganciclovir (GCV) system has been widely used as a traditional gene therapy modality, and the sodium/iodide symporter gene (NIS) has been found to be a novel therapeutic gene. Since the therapeutic effects of radioiodine therapy or prodrug chemotherapy on cancers following NIS or HSV-TK gene transfer need to be enhanced, this study was designed to investigate the feasibility of radiochemotherapy for hepatocarcinoma via coexpression of NIS gene and HSV-TK gene. Methods: HepG2 cells were stably transfected with NIS, TK and GFP gene via recombinant lentiviral vector and named HepG2/NTG. Gene expression was examined by reverse transcriptase polymerase chain reaction, fluorescence imaging and iodide uptake. The therapeutic effects were assessed by MTT assay and clonogenic assay. Results: HepG2/NTG cells concentrated 125 I - up to 76-fold higher than the wild-type cells within 20 min, and the efflux happened with a T 1/2eff of less than 10 min. The iodide uptake in HepG2/NTG cells was specifically inhibited by sodium perchlorate. Dose-dependent toxicity to HepG2/NTG cells by either GCV or 131 I was revealed by clonogenic assay and MTT assay, respectively. The survival rate of HepG2/NTG cells decreased to 49.7%±2.5%, 43.4%±2.8% and 8.6%±1.2% after exposure to 131 I, GCV and combined therapy, respectively. Conclusion: We demonstrate that radiochemotherapy of hepatocarcinoma via lentiviral-mediated coexpression of NIS gene and HSV-TK gene leads to stronger killing effect than single treatment, and in vivo studies are needed to verify these findings.

Enhanced phytoremediation of mixed heavy metal (mercury)-organic pollutants (trichloroethylene) with transgenic alfalfa co-expressing glutathione S-transferase and human P450 2E1.

Science.gov (United States)

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.

Co-Expression and Co-Localization of Cartilage Glycoproteins CHI3L1 and Lubricin in Osteoarthritic Cartilage: Morphological, Immunohistochemical and Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Marta Anna Szychlinska

2016-03-01

Full Text Available Osteoarthritis is the most common human arthritis characterized by degeneration of articular cartilage. Several studies reported that levels of human cartilage glycoprotein chitinase 3-like-1 (CHI3L1 are known as a potential marker for the activation of chondrocytes and the progression of Osteoarthritis (OA, whereas lubricin appears to be chondroprotective. The aim of this study was to investigate the co-expression and co-localization of CHI3L1 and lubricin in normal and osteoarthritic rat articular cartilage to correlate their modified expression to a specific grade of OA. Samples of normal and osteoarthritic rat articular cartilage were analyzed by the Kellgren–Lawrence OA severity scores, the Kraus’ modified Mankin score and the Histopathology Osteoarthritis Research Society International (OARSI system for histomorphometric evaluations, and through CHI3L1 and lubricin gene expression, immunohistochemistry and double immuno-staining analysis. The immunoexpression and the mRNA levels of lubricin increased in normal cartilage and decreased in OA cartilage (normal vs. OA, p < 0.01. By contrast, the immunoexpression and the mRNA levels of CHI3L1 increased in OA cartilage and decreased in normal cartilage (normal vs. OA, p < 0.01. Our findings are consistent with reports suggesting that these two glycoproteins are functionally associated with the development of OA and in particular with grade 2/3 of OA, suggesting that in the future they could be helpful to stage the severity and progression of the disease.

NorWood: a gene expression resource for evo-devo studies of conifer wood development.

Science.gov (United States)

Jokipii-Lukkari, Soile; Sundell, David; Nilsson, Ove; Hvidsten, Torgeir R; Street, Nathaniel R; Tuominen, Hannele

2017-10-01

The secondary xylem of conifers is composed mainly of tracheids that differ anatomically and chemically from angiosperm xylem cells. There is currently no high-spatial-resolution data available profiling gene expression during wood formation for any coniferous species, which limits insight into tracheid development. RNA-sequencing data from replicated, high-spatial-resolution section series throughout the cambial and woody tissues of Picea abies were used to generate the NorWood.conGenIE.org web resource, which facilitates exploration of the associated gene expression profiles and co-expression networks. Integration within PlantGenIE.org enabled a comparative regulomics analysis, revealing divergent co-expression networks between P. abies and the two angiosperm species Arabidopsis thaliana and Populus tremula for the secondary cell wall (SCW) master regulator NAC Class IIB transcription factors. The SCW cellulose synthase genes (CesAs) were located in the neighbourhoods of the NAC factors in A. thaliana and P. tremula, but not in P. abies. The NorWood co-expression network enabled identification of potential SCW CesA regulators in P. abies. The NorWood web resource represents a powerful community tool for generating evo-devo insights into the divergence of wood formation between angiosperms and gymnosperms and for advancing understanding of the regulation of wood development in P. abies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Coexpression of the high molecular weight glutenin subunit 1Ax1 and puroindoline improves dough mixing properties in durum wheat (Triticum turgidum L. ssp. durum).

Science.gov (United States)

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

Coexpression of the high molecular weight glutenin subunit 1Ax1 and puroindoline improves dough mixing properties in durum wheat (Triticum turgidum L. ssp. durum.

Directory of Open Access Journals (Sweden)

Yin Li

Full Text Available 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

Polycistronic gene expression in Aspergillus niger.

Science.gov (United States)

Schuetze, Tabea; Meyer, Vera

2017-09-25

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

Comparative gene expression between two yeast species

Directory of Open Access Journals (Sweden)

Guan Yuanfang

2013-01-01

Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Extracting Gene Networks for Low-Dose Radiation Using Graph Theoretical Algorithms

Energy Technology Data Exchange (ETDEWEB)

Voy, Brynn H [ORNL; Scharff, Jon [University of Tennessee, Knoxville (UTK); Perkins, Andy [University of Tennessee, Knoxville (UTK); Saxton, Arnold [University of Tennessee, Knoxville (UTK); Borate, Bhavesh [University of Tennessee, Knoxville (UTK); Chesler, Elissa J [ORNL; Branstetter, Lisa R [ORNL; Langston, Michael A [University of Tennessee, Knoxville (UTK)

2006-01-01

Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., ''guilt-by-association''). We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.

Extracting gene networks for low-dose radiation using graph theoretical algorithms.

Directory of Open Access Journals (Sweden)

Brynn H Voy

2006-07-01

Full Text Available Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., "guilt-by-association". We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.

Identification of estrogen receptor dimer selective ligands reveals growth-inhibitory effects on cells that co-express ERα and ERβ.

Directory of Open Access Journals (Sweden)

Emily Powell

Full Text Available Estrogens play essential roles in the progression of mammary and prostatic diseases. The transcriptional effects of estrogens are transduced by two estrogen receptors, ERα and ERβ, which elicit opposing roles in regulating proliferation: ERα is proliferative while ERβ is anti-proliferative. Exogenous expression of ERβ in ERα-positive cancer cell lines inhibits cell proliferation in response to estrogen and reduces xenografted tumor growth in vivo, suggesting that ERβ might oppose ERα's proliferative effects via formation of ERα/β heterodimers. Despite biochemical and cellular evidence of ERα/β heterodimer formation in cells co-expressing both receptors, the biological roles of the ERα/β heterodimer remain to be elucidated. Here we report the identification of two phytoestrogens that selectively activate ERα/β heterodimers at specific concentrations using a cell-based, two-step high throughput small molecule screen for ER transcriptional activity and ER dimer selectivity. Using ERα/β heterodimer-selective ligands at defined concentrations, we demonstrate that ERα/β heterodimers are growth inhibitory in breast and prostate cells which co-express the two ER isoforms. Furthermore, using Automated Quantitative Analysis (AQUA to examine nuclear expression of ERα and ERβ in human breast tissue microarrays, we demonstrate that ERα and ERβ are co-expressed in the same cells in breast tumors. The co-expression of ERα and ERβ in the same cells supports the possibility of ERα/β heterodimer formation at physio- and pathological conditions, further suggesting that targeting ERα/β heterodimers might be a novel therapeutic approach to the treatment of cancers which co-express ERα and ERβ.

Functional modules by relating protein interaction networks and gene expression.

Science.gov (United States)

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Uncovering the liver’s role in immunity through RNA co-expression networks

Czech Academy of Sciences Publication Activity Database

Harrall, K. K.; Kechris, K. J.; Tabakoff, B.; Hoffman, P.L.; Hines, L. M.; Tsukamoto, H.; Pravenec, Michal; Printz, M.; Saba, L. M.

2016-01-01

Roč. 27, 9-10 (2016), s. 469-484 ISSN 0938-8990 R&D Projects: GA ČR(CZ) GAP301/12/0696 Institutional support: RVO:67985823 Keywords : RNA coexpression networks * liver * immunity * rat * recombinant inbred strains Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.509, year: 2016

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

Science.gov (United States)

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

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different

Radionuclide reporter gene imaging for cardiac gene therapy

International Nuclear Information System (INIS)

Inubushi, Masayuki; Tamaki, Nagara

2007-01-01

In the field of cardiac gene therapy, angiogenic gene therapy has been most extensively investigated. The first clinical trial of cardiac angiogenic gene therapy was reported in 1998, and at the peak, more than 20 clinical trial protocols were under evaluation. However, most trials have ceased owing to the lack of decisive proof of therapeutic effects and the potential risks of viral vectors. In order to further advance cardiac angiogenic gene therapy, remaining open issues need to be resolved: there needs to be improvement of gene transfer methods, regulation of gene expression, development of much safer vectors and optimisation of therapeutic genes. For these purposes, imaging of gene expression in living organisms is of great importance. In radionuclide reporter gene imaging, ''reporter genes'' transferred into cell nuclei encode for a protein that retains a complementary ''reporter probe'' of a positron or single-photon emitter; thus expression of the reporter genes can be imaged with positron emission tomography or single-photon emission computed tomography. Accordingly, in the setting of gene therapy, the location, magnitude and duration of the therapeutic gene co-expression with the reporter genes can be monitored non-invasively. In the near future, gene therapy may evolve into combination therapy with stem/progenitor cell transplantation, so-called cell-based gene therapy or gene-modified cell therapy. Radionuclide reporter gene imaging is now expected to contribute in providing evidence on the usefulness of this novel therapeutic approach, as well as in investigating the molecular mechanisms underlying neovascularisation and safety issues relevant to further progress in conventional gene therapy. (orig.)

The dynamic landscape of gene regulation during Bombyx mori oogenesis.

Science.gov (United States)

Zhang, Qiang; Sun, Wei; Sun, Bang-Yong; Xiao, Yang; Zhang, Ze

2017-09-11

Oogenesis in the domestic silkworm (Bombyx mori) is a complex process involving previtellogenesis, vitellogenesis and choriogenesis. During this process, follicles show drastic morphological and physiological changes. However, the genome-wide regulatory profiles of gene expression during oogenesis remain to be determined. In this study, we obtained time-series transcriptome data and used these data to reveal the dynamic landscape of gene regulation during oogenesis. A total of 1932 genes were identified to be differentially expressed among different stages, most of which occurred during the transition from late vitellogenesis to early choriogenesis. Using weighted gene co-expression network analysis, we identified six stage-specific gene modules that correspond to multiple regulatory pathways. Strikingly, the biosynthesis pathway of the molting hormone 20-hydroxyecdysone (20E) was enriched in one of the modules. Further analysis showed that the ecdysteroid 20-hydroxylase gene (CYP314A1) of steroidgenesis genes was mainly expressed in previtellogenesis and early vitellogenesis. However, the 20E-inactivated genes, particularly the ecdysteroid 26-hydroxylase encoding gene (Cyp18a1), were highly expressed in late vitellogenesis. These distinct expression patterns between 20E synthesis and catabolism-related genes might ensure the rapid decline of the hormone titer at the transition point from vitellogenesis to choriogenesis. In addition, we compared landscapes of gene regulation between silkworm (Lepidoptera) and fruit fly (Diptera) oogeneses. Our results show that there is some consensus in the modules of gene co-expression during oogenesis in these insects. The data presented in this study provide new insights into the regulatory mechanisms underlying oogenesis in insects with polytrophic meroistic ovaries. The results also provide clues for further investigating the roles of epigenetic reconfiguration and circadian rhythm in insect oogenesis.

Connections between Transcription Downstream of Genes and cis-SAGe Chimeric RNA.

Science.gov (United States)

Chwalenia, Katarzyna; Qin, Fujun; Singh, Sandeep; Tangtrongstittikul, Panjapon; Li, Hui

2017-11-22

cis-Splicing between adjacent genes (cis-SAGe) is being recognized as one way to produce chimeric fusion RNAs. However, its detail mechanism is not clear. Recent study revealed induction of transcriptions downstream of genes (DoGs) under osmotic stress. Here, we investigated the influence of osmotic stress on cis-SAGe chimeric RNAs and their connection to DoGs. We found,the absence of induction of at least some cis-SAGe fusions and/or their corresponding DoGs at early time point(s). In fact, these DoGs and their cis-SAGe fusions are inversely correlated. This negative correlation was changed to positive at a later time point. These results suggest a direct competition between the two categories of transcripts when total pool of readthrough transcripts is limited at an early time point. At a later time point, DoGs and corresponding cis-SAGe fusions are both induced, indicating that total readthrough transcripts become more abundant. Finally, we observed overall enhancement of cis-SAGe chimeric RNAs in KCl-treated samples by RNA-Seq analysis.

Coexpression and Secretion of Endoglucanase and Phytase Genes in Lactobacillus reuteri

Science.gov (United States)

Wang, Lei; Yang, Yuxin; Cai, Bei; Cao, Pinghua; Yang, Mingming; Chen, Yulin

2014-01-01

A multifunctional transgenic Lactobacillus with probiotic characteristics and an ability to degrade β-glucan and phytic acid (phytate) was engineered to improve nutrient utilization, increase production performance and decrease digestive diseases in broiler chickens. The Bacillus subtilis WL001 endoglucanase gene (celW) and Aspergillus fumigatus WL002 phytase gene (phyW) mature peptide (phyWM) were cloned into an expression vector with the lactate dehydrogenase promoter of Lactobacillus casei and the secretion signal peptide of the Lactococcus lactis usp45 gene. This construct was then transformed into Lactobacillus reuteri XC1 that had been isolated from the gastrointestinal tract of broilers. Heterologous enzyme production and feed effectiveness of this genetically modified L. reuteri strain were investigated and evaluated. Sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis showed that the molecular mass of phyWM and celW was approximately 48.2 and 55 kDa, respectively, consistent with their predicted molecular weights. Endoglucanase and phytase activities in the extracellular fraction of the transformed L. reuteri culture were 0.68 and 0.42 U/mL, respectively. Transformed L. reuteri improved the feed conversion ratio of broilers from 21 to 42 days of age and over the whole feeding period. However, there was no effect on body weight gain and feed intake of chicks. Transformed L. reuteri supplementation improved levels of ash, calcium and phosphorus in tibiae at day 21 and of phosphorus at day 42. In addition, populations of Escherichia coli, Veillonella spp. and Bacteroides vulgatus were decreased, while populations of Bifidobacterium genus and Lactobacillus spp. were increased in the cecum at day 21. PMID:25050780

A searchable cross-platform gene expression database reveals connections between drug treatments and disease

Directory of Open Access Journals (Sweden)

Williams Gareth

2012-01-01

Full Text Available Abstract Background Transcriptional data covering multiple platforms and species is collected and processed into a searchable platform independent expression database (SPIED. SPIED consists of over 100,000 expression fold profiles defined independently of control/treatment assignment and mapped to non-redundant gene lists. The database is thus searchable with query profiles defined over genes alone. The motivation behind SPIED is that transcriptional profiles can be quantitatively compared and ranked and thus serve as effective surrogates for comparing the underlying biological states across multiple experiments. Results Drug perturbation, cancer and neurodegenerative disease derived transcriptional profiles are shown to be effective descriptors of the underlying biology as they return related drugs and pathologies from SPIED. In the case of Alzheimer's disease there is high transcriptional overlap with other neurodegenerative conditions and rodent models of neurodegeneration and nerve injury. Combining the query signature with correlating profiles allows for the definition of a tight neurodegeneration signature that successfully highlights many neuroprotective drugs in the Broad connectivity map. Conclusions Quantitative querying of expression data from across the totality of deposited experiments is an effective way of discovering connections between different biological systems and in particular that between drug action and biological disease state. Examples in cancer and neurodegenerative conditions validate the utility of SPIED.

Integration of omic networks in a developmental atlas of maize.

Science.gov (United States)

Walley, Justin W; Sartor, Ryan C; Shen, Zhouxin; Schmitz, Robert J; Wu, Kevin J; Urich, Mark A; Nery, Joseph R; Smith, Laurie G; Schnable, James C; Ecker, Joseph R; Briggs, Steven P

2016-08-19

Coexpression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting functional roles of individual genes at a system-wide scale. To enable network reconstructions, we built a large-scale gene expression atlas composed of 62,547 messenger RNAs (mRNAs), 17,862 nonmodified proteins, and 6227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. Networks in which nodes are genes connected on the basis of highly correlated expression patterns of mRNAs were very different from networks that were based on coexpression of proteins. Roughly 85% of highly interconnected hubs were not conserved in expression between RNA and protein networks. However, networks from either data type were enriched in similar ontological categories and were effective in predicting known regulatory relationships. Integration of mRNA, protein, and phosphoprotein data sets greatly improved the predictive power of GRNs. Copyright © 2016, American Association for the Advancement of Science.

Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes

DEFF Research Database (Denmark)

Min, Josine L; Nicholson, George; Halgrimsdottir, Ingileif

2012-01-01

Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abdominal (ABD) and gluteal (GLU) adipose tissue...... and 51 (0.6%) in GLU only. Differential eigengene network analysis of 8,256 shared probesets detected 22 shared modules with high preservation across adipose depots (D(ABD-GLU) = 0.89), seven of which were associated with MetS (FDR P100,000 individuals; rs10282458, affecting expression of RARRES2...... and their interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations....

Array2BIO: from microarray expression data to functional annotation of co-regulated genes

Directory of Open Access Journals (Sweden)

Rasley Amy

2006-06-01

Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

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

Directory of Open Access Journals (Sweden)

Takayuki eTohge

2014-03-01

Full Text Available 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.

Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon

Directory of Open Access Journals (Sweden)

Satoru Koda

2017-11-01

Full Text Available We report the comprehensive identification of periodic genes and their network inference, based on a gene co-expression analysis and an Auto-Regressive eXogenous (ARX model with a group smoothly clipped absolute deviation (SCAD method using a time-series transcriptome dataset in a model grass, Brachypodium distachyon. To reveal the diurnal changes in the transcriptome in B. distachyon, we performed RNA-seq analysis of its leaves sampled through a diurnal cycle of over 48 h at 4 h intervals using three biological replications, and identified 3,621 periodic genes through our wavelet analysis. The expression data are feasible to infer network sparsity based on ARX models. We found that genes involved in biological processes such as transcriptional regulation, protein degradation, and post-transcriptional modification and photosynthesis are significantly enriched in the periodic genes, suggesting that these processes might be regulated by circadian rhythm in B. distachyon. On the basis of the time-series expression patterns of the periodic genes, we constructed a chronological gene co-expression network and identified putative transcription factors encoding genes that might be involved in the time-specific regulatory transcriptional network. Moreover, we inferred a transcriptional network composed of the periodic genes in B. distachyon, aiming to identify genes associated with other genes through variable selection by grouping time points for each gene. Based on the ARX model with the group SCAD regularization using our time-series expression datasets of the periodic genes, we constructed gene networks and found that the networks represent typical scale-free structure. Our findings demonstrate that the diurnal changes in the transcriptome in B. distachyon leaves have a sparse network structure, demonstrating the spatiotemporal gene regulatory network over the cyclic phase transitions in B. distachyon diurnal growth.

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

Science.gov (United States)

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%.

Improved soluble expression and characterization of the Hc domain of Clostridium botulinum neurotoxin serotype A in Escherichia coli by using a PCR-synthesized gene and a Trx co-expression strain.

Science.gov (United States)

Chen, Rongchang; Shi, Jing; Cai, Kun; Tu, Wei; Hou, Xiaojun; Liu, Hao; Xiao, Le; Wang, Qin; Tang, Yunming; Wang, Hui

2010-05-01

Botulinum neurotoxin serotype A (BoNT/A) is an extremely potent bacterial protein toxin. The Hc fragment of BoNT/A (AHc) was shown to be non-toxic, antigenic, and capable of eliciting a protective immunity in animals challenged with homologous BoNT. In this study, we synthesized AHc gene by using T4 DNA ligase and PCR. The AHc was expressed at a high level in Escherichia coli successfully. Because of using the Trx co-expression strain, the expressed AHc is in a soluble and active form. The yield of the purified AHc was about 70mg/L, and its purity was up to 90% through one-step affinity chromatography. The AHc was positively identified by the antibodies raised against BoNT/A using immunological-dot-blot and Western blot assays. AHc was shown to bind with gangliosides and elicit immunity against BoNT/A, indicating that the expressed and purified AHc protein retains a functionally active conformation. Furthermore, the purified AHc has a strong immunogenicity and can be used as a potential subunit candidate vaccine for botulinum toxin serotype A. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease.

Science.gov (United States)

Modena, Brian D; Bleecker, Eugene R; Busse, William W; Erzurum, Serpil C; Gaston, Benjamin M; Jarjour, Nizar N; Meyers, Deborah A; Milosevic, Jadranka; Tedrow, John R; Wu, Wei; Kaminski, Naftali; Wenzel, Sally E

2017-06-01

Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Identify networks of genes reflective of underlying biological processes that define SA. Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

Developmental Connectivity and Molecular Phenotypes of Unique Cortical Projection Neurons that Express a Synapse-Associated Receptor Tyrosine Kinase.

Science.gov (United States)

Kast, Ryan J; Wu, Hsiao-Huei; Levitt, Pat

2017-11-28

The complex circuitry and cell-type diversity of the cerebral cortex are required for its high-level functions. The mechanisms underlying the diversification of cortical neurons during prenatal development have received substantial attention, but understanding of neuronal heterogeneity is more limited during later periods of cortical circuit maturation. To address this knowledge gap, connectivity analysis and molecular phenotyping of cortical neuron subtypes that express the developing synapse-enriched MET receptor tyrosine kinase were performed. Experiments used a MetGFP transgenic mouse line, combined with coexpression analysis of class-specific molecular markers and retrograde connectivity mapping. The results reveal that MET is expressed by a minor subset of subcerebral and a larger number of intratelencephalic projection neurons. Remarkably, MET is excluded from most layer 6 corticothalamic neurons. These findings are particularly relevant for understanding the maturation of discrete cortical circuits, given converging evidence that MET influences dendritic elaboration and glutamatergic synapse maturation. The data suggest that classically defined cortical projection classes can be further subdivided based on molecular characteristics that likely influence synaptic maturation and circuit wiring. Additionally, given that MET is classified as a high confidence autism risk gene, the data suggest that projection neuron subpopulations may be differentially vulnerable to disorder-associated genetic variation. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Partial antiviral activities detection of chicken Mx jointing with neuraminidase gene (NA against Newcastle disease virus.

Directory of Open Access Journals (Sweden)

Yani Zhang

Full Text Available As an attempt to increase the resistance to Newcastle Disease Virus (NDV and so further reduction of its risk on the poultry industry. This work aimed to build the eukaryotic gene co-expression plasmid of neuraminidase (NA gene and myxo-virus resistance (Mx and detect the gene expression in transfected mouse fibroblasts (NIH-3T3 cells, it is most important to investigate the influence of the recombinant plasmid on the chicken embryonic fibroblasts (CEF cells. cDNA fragment of NA and mutant Mx gene were derived from pcDNA3.0-NA and pcDNA3.0-Mx plasmid via PCR, respectively, then NA and Mx cDNA fragment were inserted into the multiple cloning sites of pVITRO2 to generate the eukaryotic co-expression plasmid pVITRO2-Mx-NA. The recombinant plasmid was confirmed by restriction endonuclease treatment and sequencing, and it was transfected into the mouse fibroblasts (NIH-3T3 cells. The expression of genes in pVITRO2-Mx-NA were measured by RT-PCR and indirect immunofluorescence assay (IFA. The recombinant plasmid was transfected into CEF cells then RT-PCR and the micro-cell inhibition tests were used to test the antiviral activity for NDV. Our results showed that co-expression vector pVITRO2-Mx-NA was constructed successfully; the expression of Mx and NA could be detected in both NIH-3T3 and CEF cells. The recombinant proteins of Mx and NA protect CEF cells from NDV infection until after 72 h of incubation but the individually mutagenic Mx protein or NA protein protects CEF cells from NDV infection till 48 h post-infection, and co-transfection group decreased significantly NDV infection compared with single-gene transfection group (P<0. 05, indicating that Mx-NA jointing contributed to delaying the infection of NDV in single-cell level and the co-transfection of the jointed genes was more powerful than single one due to their synergistic effects.

Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

Directory of Open Access Journals (Sweden)

Hyun-Seob Song

2015-03-01

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

Gene networks specific for innate immunity define post-traumatic stress disorder.

Science.gov (United States)

Breen, M S; Maihofer, A X; Glatt, S J; Tylee, D S; Chandler, S D; Tsuang, M T; Risbrough, V B; Baker, D G; O'Connor, D T; Nievergelt, C M; Woelk, C H

2015-12-01

The molecular factors involved in the development of Post-Traumatic Stress Disorder (PTSD) remain poorly understood. Previous transcriptomic studies investigating the mechanisms of PTSD apply targeted approaches to identify individual genes under a cross-sectional framework lack a holistic view of the behaviours and properties of these genes at the system-level. Here we sought to apply an unsupervised gene-network based approach to a prospective experimental design using whole-transcriptome RNA-Seq gene expression from peripheral blood leukocytes of U.S. Marines (N=188), obtained both pre- and post-deployment to conflict zones. We identified discrete groups of co-regulated genes (i.e., co-expression modules) and tested them for association to PTSD. We identified one module at both pre- and post-deployment containing putative causal signatures for PTSD development displaying an over-expression of genes enriched for functions of innate-immune response and interferon signalling (Type-I and Type-II). Importantly, these results were replicated in a second non-overlapping independent dataset of U.S. Marines (N=96), further outlining the role of innate immune and interferon signalling genes within co-expression modules to explain at least part of the causal pathophysiology for PTSD development. A second module, consequential of trauma exposure, contained PTSD resiliency signatures and an over-expression of genes involved in hemostasis and wound responsiveness suggesting that chronic levels of stress impair proper wound healing during/after exposure to the battlefield while highlighting the role of the hemostatic system as a clinical indicator of chronic-based stress. These findings provide novel insights for early preventative measures and advanced PTSD detection, which may lead to interventions that delay or perhaps abrogate the development of PTSD.

Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.

Science.gov (United States)

Bhatlekar, Seema; Addya, Sankar; Salunek, Moreh; Orr, Christopher R; Surrey, Saul; McKenzie, Steven; Fields, Jeremy Z; Boman, Bruce M

2014-01-15

Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis.

BDNF genotype modulates resting functional connectivity in children

Directory of Open Access Journals (Sweden)

Moriah E Thomason

2009-11-01

Full Text Available A specific polymorphism of the brain-derived neurotrophic factor (BDNF gene is associated with alterations in brain anatomy and memory; its relevance to the functional connectivity of brain networks, however, is unclear. Given that altered hippocampal function and structure has been found in adults who carry the methionine (met allele of the BDNF gene and the molecular studies elucidating the role of BDNF in neurogenesis and synapse formation, we examined in the association between BDNF gene variants and neural resting connectivity in children and adolescents. We observed a reduction in hippocampal and parahippocampal to cortical connectivity in met-allele carriers within each of three resting networks: the default-mode, executive, and paralimbic networks. In contrast, we observed increased connectivity to amygdala, insula and striatal regions in met-carriers, within the paralimbic network. Because the BDNF met-allele has been linked to increased susceptibility to neuropsychiatric disorders, this latter finding of greater connectivity in circuits important for emotion processing may indicate a new neural mechanism through which these gene-related psychiatric differences are manifest. Here we show that the BDNF gene, known to regulate synaptic plasticity and connectivity in the brain, affects functional connectivity at the neural systems level. Additionally, we provide the first demonstration that the spatial topography of multiple high-level resting state networks in healthy children and adolescents is similar to that observed in adults.

Biobibliometrics (UGDH-TP53-BRCA1) Genes Connections in the Possible Relationship Between Breast Cancer and EEG.

Science.gov (United States)

Martzoukos, Yannis; Papavlasopoulos, Sozon; Poulos, Marios; Syrrou, Maria

2017-01-01

In recent years there has been an increasingly amount of data stored in biomedical Databases due to the breakthroughs in biology and bioinformatics, biomedical information is growing exponentially making efficient information retrieval from scientist more and more challenging. New Scientific fields as Bioinformatics seem to be the tool needed to extract scientifically important data based on experimental results and information provided by papers and journals. In this paper we are going to implement a custom made IT system in order to find connections between genes in the breast cancer pathways such the BRCA1 with the electrical energy in the human brain with UGDH gene via the TP53 tumor gene. The proposed system will be able to identify the appearance of each gene ID and compare the coexistence of two genes in PubMed articles/papers. The final system could become a useful tool against the struggle of scientists and medical professionals in the near future.

The structural and functional connectivity of the grassland plant Lychnis flos-cuculi

Science.gov (United States)

Aavik, T; Holderegger, R; Bolliger, J

2014-01-01

Understanding the relationship between structural and functional connectivity is essential for successful restoration and conservation management, particularly in intensely managed agricultural landscapes. We evaluated the relationship between structural and functional connectivity of the wetland plant Lychnis flos-cuculi in a fragmented agricultural landscape using landscape genetic and network approaches. First, we studied the effect of structural connectivity, such as geographic distance and various landscape elements (forest, agricultural land, settlements and ditch verges), on gene flow among populations as a measurement of functional connectivity. Second, we examined the effect of structural graph-theoretic connectivity measures on gene flow among populations and on genetic diversity within populations of L. flos-cuculi. Among landscape elements, forests hindered gene flow in L. flos-cuculi, whereas gene flow was independent of geographic distance. Among the structural graph-theoretic connectivity variables, only intrapopulation connectivity, which was based on population size, had a significant positive effect on gene flow, that is, more gene flow took place among larger populations. Unexpectedly, interpopulation connectivity of populations, which takes into account the spatial location and distance among populations, did not influence gene flow in L. flos-cuculi. However, higher observed heterozygosity and lower inbreeding was observed in populations characterised by higher structural interpopulation connectivity. This finding shows that a spatially coherent network of populations is significant for maintaining the genetic diversity of populations. Nevertheless, lack of significant relationships between gene flow and most of the structural connectivity measures suggests that structural connectivity does not necessarily correspond to functional connectivity. PMID:24253937

Characterization of Chemically Induced Liver Injuries Using Gene Co-Expression Modules

Science.gov (United States)

2014-09-16

evaluated the periportal fibrosis gene signature in the GEO dataset - GSE13747 [34]. In this dataset, liver fibrosis was induced by bile duct ...dataset, liver fibrosis was induced by bile duct ligation. Figure 10-D shows the observed correlation between log-ratios of periportal fibrosis...at 15 days of exposure obtained from TG-GATEs, and D) liver fibrosis produced by bile duct ligation obtained from GSE13747. doi:10.1371/journal.pone

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

Science.gov (United States)

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

2011-01-01

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

Co-expression of Nisin Z and Leucocin C as a Basis for Effective Protection Against Listeria monocytogenes in Pasteurized Milk

Directory of Open Access Journals (Sweden)

Yuxin Fu

2018-03-01

Full Text Available Nisin, an important bacteriocin from Lactococcus lactis subsp., is primarily active against various Gram-positive bacteria. Leucocin C, produced by Leuconostoc carnosum 4010, is a class IIa bacteriocin used to inhibit the growth of Listeria monocytogenes. Because two bacteriocins have different modes of action, the combined use of them could be a potential strategy for effective inhibition of foodborne pathogens. In this study, L. lactis N8-r-lecCI (N8 harboring lecCI gene coexpressing nisin–leucocin C was constructed based on the food-grade carrier L. lactis N8. Production of both bacteriocins was stably maintained. Antimicrobial measurements showed that the recombinant strain is effectively against Listeria monocytogenes and Staphylococcus aureus and moderately against Salmonella enterica serovar Enteritidis and Escherichia coli because of its stronger antibacterial activity than the parental strain, this result first demonstrated that the co-expression of nisin and leucocin C results in highly efficient antimicrobial activity. The checkerboard assay showed that the antibacterial activity of L. lactis N8-r-lecCI supernatant was enhanced in the presence of low concentration of EDTA. Analysis of the scanning electron microscope image showed the biggest cellular morphology change in L. monocytogenes treated with a mixture of EDTA and L. lactis N8-r-lecCI supernatant. The practical effect was verified in pasteurized milk through time-kill assay. The L. lactis N8-r-lecCI strain expressing both nisin and leucocin C has a promising application prospect in pasteurized milk processing and preservation because of its strong antibacterial activity.

When Is Hub Gene Selection Better than Standard Meta-Analysis?

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Peter Langfelder

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

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

Science.gov (United States)

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

2013-01-01

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

Systems Toxicology of Chemically Induced Liver and Kidney Injuries: Histopathology-Associated Gene Co-Expression Modules

Science.gov (United States)

2016-01-04

Research article Received: 9 October 2015, Revised: 18 November 2015, Accepted: 23 November 2015 Published online in Wiley Online Library: 4 January...Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort...ISAIterate, which requires a starter gene set that is typically built using existing gene-related knowledge; here we used ~200 starter gene sets from

Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes

OpenAIRE

Kreiman, Gabriel

2004-01-01

Sequence information and high‐throughput methods to measure gene expression levels open the door to explore transcriptional regulation using computational tools. Combinatorial regulation and sparseness of regulatory elements throughout the genome allow organisms to control the spatial and temporal patterns of gene expression. Here we study the organization of cis‐regulatory elements in sets of co‐regulated genes. We build an algorithm to search for combinations of transcription factor binding...

A transcriptional analysis of carotenoid, chlorophyll and plastidial isoprenoid biosynthesis genes during development and osmotic stress responses in Arabidopsis thaliana

KAUST Repository

Meier, Stuart; Tzfadia, Oren; Vallabhaneni, Ratnakar; Gehring, Christoph A; Wurtzel, Eleanore T

2011-01-01

Background: The carotenoids are pure isoprenoids that are essential components of the photosynthetic apparatus and are coordinately synthesized with chlorophylls in chloroplasts. However, little is known about the mechanisms that regulate carotenoid biosynthesis or the mechanisms that coordinate this synthesis with that of chlorophylls and other plastidial synthesized isoprenoid-derived compounds, including quinones, gibberellic acid and abscisic acid. Here, a comprehensive transcriptional analysis of individual carotenoid and isoprenoid-related biosynthesis pathway genes was performed in order to elucidate the role of transcriptional regulation in the coordinated synthesis of these compounds and to identify regulatory components that may mediate this process in Arabidopsis thaliana.Results: A global microarray expression correlation analysis revealed that the phytoene synthase gene, which encodes the first dedicated and rate-limiting enzyme of carotenogenesis, is highly co-expressed with many photosynthesis-related genes including many isoprenoid-related biosynthesis pathway genes. Chemical and mutant analysis revealed that induction of the co-expressed genes following germination was dependent on gibberellic acid and brassinosteroids (BR) but was inhibited by abscisic acid (ABA). Mutant analyses further revealed that expression of many of the genes is suppressed in dark grown plants by Phytochrome Interacting transcription Factors (PIFs) and activated by photoactivated phytochromes, which in turn degrade PIFs and mediate a coordinated induction of the genes. The promoters of PSY and the co-expressed genes were found to contain an enrichment in putative BR-auxin response elements and G-boxes, which bind PIFs, further supporting a role for BRs and PIFs in regulating expression of the genes. In osmotically stressed root tissue, transcription of Calvin cycle, methylerythritol 4-phosphate pathway and carotenoid biosynthesis genes is induced and uncoupled from that of

A transcriptional analysis of carotenoid, chlorophyll and plastidial isoprenoid biosynthesis genes during development and osmotic stress responses in Arabidopsis thaliana

KAUST Repository

Meier, Stuart

2011-05-19

Background: The carotenoids are pure isoprenoids that are essential components of the photosynthetic apparatus and are coordinately synthesized with chlorophylls in chloroplasts. However, little is known about the mechanisms that regulate carotenoid biosynthesis or the mechanisms that coordinate this synthesis with that of chlorophylls and other plastidial synthesized isoprenoid-derived compounds, including quinones, gibberellic acid and abscisic acid. Here, a comprehensive transcriptional analysis of individual carotenoid and isoprenoid-related biosynthesis pathway genes was performed in order to elucidate the role of transcriptional regulation in the coordinated synthesis of these compounds and to identify regulatory components that may mediate this process in Arabidopsis thaliana.Results: A global microarray expression correlation analysis revealed that the phytoene synthase gene, which encodes the first dedicated and rate-limiting enzyme of carotenogenesis, is highly co-expressed with many photosynthesis-related genes including many isoprenoid-related biosynthesis pathway genes. Chemical and mutant analysis revealed that induction of the co-expressed genes following germination was dependent on gibberellic acid and brassinosteroids (BR) but was inhibited by abscisic acid (ABA). Mutant analyses further revealed that expression of many of the genes is suppressed in dark grown plants by Phytochrome Interacting transcription Factors (PIFs) and activated by photoactivated phytochromes, which in turn degrade PIFs and mediate a coordinated induction of the genes. The promoters of PSY and the co-expressed genes were found to contain an enrichment in putative BR-auxin response elements and G-boxes, which bind PIFs, further supporting a role for BRs and PIFs in regulating expression of the genes. In osmotically stressed root tissue, transcription of Calvin cycle, methylerythritol 4-phosphate pathway and carotenoid biosynthesis genes is induced and uncoupled from that of

A transcriptional analysis of carotenoid, chlorophyll and plastidial isoprenoid biosynthesis genes during development and osmotic stress responses in Arabidopsis thaliana

Directory of Open Access Journals (Sweden)

Vallabhaneni Ratnakar

2011-05-01

Full Text Available Abstract Background The carotenoids are pure isoprenoids that are essential components of the photosynthetic apparatus and are coordinately synthesized with chlorophylls in chloroplasts. However, little is known about the mechanisms that regulate carotenoid biosynthesis or the mechanisms that coordinate this synthesis with that of chlorophylls and other plastidial synthesized isoprenoid-derived compounds, including quinones, gibberellic acid and abscisic acid. Here, a comprehensive transcriptional analysis of individual carotenoid and isoprenoid-related biosynthesis pathway genes was performed in order to elucidate the role of transcriptional regulation in the coordinated synthesis of these compounds and to identify regulatory components that may mediate this process in Arabidopsis thaliana. Results A global microarray expression correlation analysis revealed that the phytoene synthase gene, which encodes the first dedicated and rate-limiting enzyme of carotenogenesis, is highly co-expressed with many photosynthesis-related genes including many isoprenoid-related biosynthesis pathway genes. Chemical and mutant analysis revealed that induction of the co-expressed genes following germination was dependent on gibberellic acid and brassinosteroids (BR but was inhibited by abscisic acid (ABA. Mutant analyses further revealed that expression of many of the genes is suppressed in dark grown plants by Phytochrome Interacting transcription Factors (PIFs and activated by photoactivated phytochromes, which in turn degrade PIFs and mediate a coordinated induction of the genes. The promoters of PSY and the co-expressed genes were found to contain an enrichment in putative BR-auxin response elements and G-boxes, which bind PIFs, further supporting a role for BRs and PIFs in regulating expression of the genes. In osmotically stressed root tissue, transcription of Calvin cycle, methylerythritol 4-phosphate pathway and carotenoid biosynthesis genes is induced

The duplicated genes database: identification and functional annotation of co-localised duplicated genes across genomes.

Directory of Open Access Journals (Sweden)

Marion Ouedraogo

Full Text Available BACKGROUND: There has been a surge in studies linking genome structure and gene expression, with special focus on duplicated genes. Although initially duplicated from the same sequence, duplicated genes can diverge strongly over evolution and take on different functions or regulated expression. However, information on the function and expression of duplicated genes remains sparse. Identifying groups of duplicated genes in different genomes and characterizing their expression and function would therefore be of great interest to the research community. The 'Duplicated Genes Database' (DGD was developed for this purpose. METHODOLOGY: Nine species were included in the DGD. For each species, BLAST analyses were conducted on peptide sequences corresponding to the genes mapped on a same chromosome. Groups of duplicated genes were defined based on these pairwise BLAST comparisons and the genomic location of the genes. For each group, Pearson correlations between gene expression data and semantic similarities between functional GO annotations were also computed when the relevant information was available. CONCLUSIONS: The Duplicated Gene Database provides a list of co-localised and duplicated genes for several species with the available gene co-expression level and semantic similarity value of functional annotation. Adding these data to the groups of duplicated genes provides biological information that can prove useful to gene expression analyses. The Duplicated Gene Database can be freely accessed through the DGD website at http://dgd.genouest.org.

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

Science.gov (United States)

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

Identification and expression analyses of MYB and WRKY transcription factor genes in Papaver somniferum L.

Science.gov (United States)

Kakeshpour, Tayebeh; Nayebi, Shadi; Rashidi Monfared, Sajad; Moieni, Ahmad; Karimzadeh, Ghasem

2015-10-01

Papaver somniferum L. is an herbaceous, annual and diploid plant that is important from pharmacological and strategic point of view. The cDNA clones of two putative MYB and WRKY genes were isolated (GeneBank accession numbers KP411870 and KP203854, respectively) from this plant, via the nested-PCR method, and characterized. The MYB transcription factor (TF) comprises 342 amino acids, and exhibits the structural features of the R2R3MYB protein family. The WRKY TF, a 326 amino acid-long polypeptide, falls structurally into the group II of WRKY protein family. Quantitative real-time PCR (qRT-PCR) analyses indicate the presence of these TFs in all organs of P. somniferum L. and Papaver bracteatum L. Highest expression levels of these two TFs were observed in the leaf tissues of P. somniferum L. while in P. bracteatum L. the espression levels were highest in the root tissues. Promoter analysis of the 10 co-expressed gene clustered involved in noscapine biosynthesis pathway in P. somniferum L. suggested that not only these 10 genes are co-expressed, but also share common regulatory motifs and TFs including MYB and WRKY TFs, and that may explain their common regulation.

The chimeric gene CHRFAM7A, a partial duplication of the CHRNA7 gene, is a dominant negative regulator of α7*nAChR function.

Science.gov (United States)

Araud, Tanguy; Graw, Sharon; Berger, Ralph; Lee, Michael; Neveu, Estele; Bertrand, Daniel; Leonard, Sherry

2011-10-15

The human α7 neuronal nicotinic acetylcholine receptor gene (CHRNA7) is a candidate gene for schizophrenia and an important drug target for cognitive deficits in the disorder. Activation of the α7*nAChR, results in opening of the channel and entry of mono- and divalent cations, including Ca(2+), that presynaptically participates to neurotransmitter release and postsynaptically to down-stream changes in gene expression. Schizophrenic patients have low levels of α7*nAChR, as measured by binding of the ligand [(125)I]-α-bungarotoxin (I-BTX). The structure of the gene, CHRNA7, is complex. During evolution, CHRNA7 was partially duplicated as a chimeric gene (CHRFAM7A), which is expressed in the human brain and elsewhere in the body. The association between a 2bp deletion in CHRFAM7A and schizophrenia suggested that this duplicate gene might contribute to cognitive impairment. To examine the putative contribution of CHRFAM7A on receptor function, co-expression of α7 and the duplicate genes was carried out in cell lines and Xenopus oocytes. Expression of the duplicate alone yielded protein expression but no functional receptor and co-expression with α7 caused a significant reduction of the amplitude of the ACh-evoked currents. Reduced current amplitude was not correlated with a reduction of I-BTX binding, suggesting the presence of non-functional (ACh-silent) receptors. This hypothesis is supported by a larger increase of the ACh-evoked current by the allosteric modulator 1-(5-chloro-2,4-dimethoxy-phenyl)-3-(5-methyl-isoxazol-3-yl)-urea (PNU-120596) in cells expressing the duplicate than in the control. These results suggest that CHRFAM7A acts as a dominant negative modulator of CHRNA7 function and is critical for receptor regulation in humans. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification of Photosynthesis-Associated C4 Candidate Genes through Comparative Leaf Gradient Transcriptome in Multiple Lineages of C3 and C4 Species

Science.gov (United States)

Ding, Zehong; Weissmann, Sarit; Wang, Minghui; Du, Baijuan; Huang, Lei; Wang, Lin; Tu, Xiaoyu; Zhong, Silin; Myers, Christopher; Brutnell, Thomas P.; Sun, Qi; Li, Pinghua

2015-01-01

Leaves of C4 crops usually have higher radiation, water and nitrogen use efficiencies compared to the C3 species. Engineering C4 traits into C3 crops has been proposed as one of the most promising ways to repeal the biomass yield ceiling. To better understand the function of C4 photosynthesis, and to identify candidate genes that are associated with the C4 pathways, a comparative transcription network analysis was conducted on leaf developmental gradients of three C4 species including maize, green foxtail and sorghum and one C3 species, rice. By combining the methods of gene co-expression and differentially co-expression networks, we identified a total of 128 C4 specific genes. Besides the classic C4 shuttle genes, a new set of genes associated with light reaction, starch and sucrose metabolism, metabolites transportation, as well as transcription regulation, were identified as involved in C4 photosynthesis. These findings will provide important insights into the differential gene regulation between C3 and C4 species, and a good genetic resource for establishing C4 pathways in C3 crops. PMID:26465154

Identification of Photosynthesis-Associated C4 Candidate Genes through Comparative Leaf Gradient Transcriptome in Multiple Lineages of C3 and C4 Species.

Science.gov (United States)

Ding, Zehong; Weissmann, Sarit; Wang, Minghui; Du, Baijuan; Huang, Lei; Wang, Lin; Tu, Xiaoyu; Zhong, Silin; Myers, Christopher; Brutnell, Thomas P; Sun, Qi; Li, Pinghua

2015-01-01

Leaves of C4 crops usually have higher radiation, water and nitrogen use efficiencies compared to the C3 species. Engineering C4 traits into C3 crops has been proposed as one of the most promising ways to repeal the biomass yield ceiling. To better understand the function of C4 photosynthesis, and to identify candidate genes that are associated with the C4 pathways, a comparative transcription network analysis was conducted on leaf developmental gradients of three C4 species including maize, green foxtail and sorghum and one C3 species, rice. By combining the methods of gene co-expression and differentially co-expression networks, we identified a total of 128 C4 specific genes. Besides the classic C4 shuttle genes, a new set of genes associated with light reaction, starch and sucrose metabolism, metabolites transportation, as well as transcription regulation, were identified as involved in C4 photosynthesis. These findings will provide important insights into the differential gene regulation between C3 and C4 species, and a good genetic resource for establishing C4 pathways in C3 crops.

Identification of Photosynthesis-Associated C4 Candidate Genes through Comparative Leaf Gradient Transcriptome in Multiple Lineages of C3 and C4 Species.

Directory of Open Access Journals (Sweden)

Zehong Ding

Full Text Available Leaves of C4 crops usually have higher radiation, water and nitrogen use efficiencies compared to the C3 species. Engineering C4 traits into C3 crops has been proposed as one of the most promising ways to repeal the biomass yield ceiling. To better understand the function of C4 photosynthesis, and to identify candidate genes that are associated with the C4 pathways, a comparative transcription network analysis was conducted on leaf developmental gradients of three C4 species including maize, green foxtail and sorghum and one C3 species, rice. By combining the methods of gene co-expression and differentially co-expression networks, we identified a total of 128 C4 specific genes. Besides the classic C4 shuttle genes, a new set of genes associated with light reaction, starch and sucrose metabolism, metabolites transportation, as well as transcription regulation, were identified as involved in C4 photosynthesis. These findings will provide important insights into the differential gene regulation between C3 and C4 species, and a good genetic resource for establishing C4 pathways in C3 crops.

Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

Directory of Open Access Journals (Sweden)

Vandepoele Klaas

2009-06-01

Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

Co-expression and characterization of enterocin CRL35 and its mutant in Escherichia coli Rosetta

Directory of Open Access Journals (Sweden)

Masías Emilse

2014-01-01

Full Text Available Even though many sequences and structures of bacteriocins from lactic acid bacteria have been fully characterized so far, little information is currently available about bacteriocins heterologously produced by Escherichia coli. For this purpose, the structural gene of enterocin CRL35, munA, was PCR-amplified using specific primers and cloned downstream of PelB sequence in the pET22b (+ expression vector. E. coli Rosetta (DE3 pLysS was chosen as the host for production and enterocin was purified by an easy two-step protocol. The bacteriocin was correctly expressed with the expected intramolecular disulfide bond. Nevertheless, it was found that a variant of the enterocin, differing by 12 Da from the native polypeptide, was co-expressed by E. coli Rosetta in comparable amount. Indeed, the mutant bacteriocin contained two amino acid substitutions that were characterized by matrix assisted laser desorption ionization-time of flight (MALDI-TOF and HPLCelectrospray (ESI-Q-TOF tandem mass spectrometry (MS/ MS sequencing. This is the first report regarding the production of mutants of pediocin-like bacteriocins in the E. coli expression system.

Putative carotenoid genes expressed under the regulation of Shine-Dalgarno regions in Escherichia coli for efficient lycopene production.

Science.gov (United States)

Jin, Weiyue; Xu, Xian; Jiang, Ling; Zhang, Zhidong; Li, Shuang; Huang, He

2015-11-01

Putative genes crtE, crtB, and crtI from Deinococcus wulumiqiensis R12, a novel species, were identified by genome mining and were co-expressed using the optimized Shine-Dalgarno (SD) regions to improve lycopene yield. A lycopene biosynthesis pathway was constructed by co-expressing these three genes in Escherichia coli. After optimizing the upstream SD regions and the culture medium, the recombinant strain EDW11 produced 88 mg lycopene g(-1) dry cell wt (780 mg lycopene l(-1)) after 40 h fermentation without IPTG induction, while the strain EDW without optimized SD regions only produced 49 mg lycopene g(-1) dry cell wt (417 mg lycopene l(-1)). Based on the optimization of the upstream SD regions and culture medium, the yield of the strain EDW11 reached a high level during microbial lycopene production until now.

Co-expression of TIMP-1 and its cell surface binding partner CD63 in glioblastomas

DEFF Research Database (Denmark)

Aaberg-Jessen, Charlotte; Sørensen, Mia D.; Matos, Ana L.S.A.

2018-01-01

scoring. CD63 expression in tumor-associated microglia/macrophages was examined by double-immunofluorescence with ionized calcium-binding adapter molecule 1 (Iba1). The association between CD63 and TIMP-1 was investigated using previously obtained TIMP-1 data from our astrocytoma cohort. Cellular co-expression...... of CD63 was widely distributed in astrocytomas with a significantly increased level in glioblastomas. CD63 levels did not significantly correlate with patient survival at a protein level, and CD63 did not augment the prognostic significance of TIMP-1. Up to 38% of the CD63+ cells expressed Iba1; however......, Iba1 did not appear to impact the prognostic value of CD63. A significant correlation was found between TIMP-1 and CD63, and the TIMP-1 and CD63 proteins were co-expressed at the cellular level and located in close molecular proximity, suggesting that TIMP-1 and CD63 could be co...

Pathways of Lipid Metabolism in Marine Algae, Co-Expression Network, Bottlenecks and Candidate Genes for Enhanced Production of EPA and DHA in Species of Chromista

Directory of Open Access Journals (Sweden)

Alice Mühlroth

2013-11-01

Full Text Available The importance of n-3 long chain polyunsaturated fatty acids (LC-PUFAs for human health has received more focus the last decades, and the global consumption of n-3 LC-PUFA has increased. Seafood, the natural n-3 LC-PUFA source, is harvested beyond a sustainable capacity, and it is therefore imperative to develop alternative n-3 LC-PUFA sources for both eicosapentaenoic acid (EPA, 20:5n-3 and docosahexaenoic acid (DHA, 22:6n-3. Genera of algae such as Nannochloropsis, Schizochytrium, Isochrysis and Phaedactylum within the kingdom Chromista have received attention due to their ability to produce n-3 LC-PUFAs. Knowledge of LC-PUFA synthesis and its regulation in algae at the molecular level is fragmentary and represents a bottleneck for attempts to enhance the n-3 LC-PUFA levels for industrial production. In the present review, Phaeodactylum tricornutum has been used to exemplify the synthesis and compartmentalization of n-3 LC-PUFAs. Based on recent transcriptome data a co-expression network of 106 genes involved in lipid metabolism has been created. Together with recent molecular biological and metabolic studies, a model pathway for n-3 LC-PUFA synthesis in P. tricornutum has been proposed, and is compared to industrialized species of Chromista. Limitations of the n-3 LC-PUFA synthesis by enzymes such as thioesterases, elongases, acyl-CoA synthetases and acyltransferases are discussed and metabolic bottlenecks are hypothesized such as the supply of the acetyl-CoA and NADPH. A future industrialization will depend on optimization of chemical compositions and increased biomass production, which can be achieved by exploitation of the physiological potential, by selective breeding and by genetic engineering.

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

DEFF Research Database (Denmark)

de Jong, Simone; Boks, Marco P M; Fuller, Tova F

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......, 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...

Gene flow connects coastal populations of a habitat specialist, the Clapper Rail Rallus crepitans

Science.gov (United States)

Coster, Stephanie S.; Welsh, Amy B.; Costanzo, Gary R.; Harding, Sergio R.; Anderson, James T.; Katzner, Todd

2018-01-01

Examining population genetic structure can reveal patterns of reproductive isolation or population mixing and inform conservation management. Some avian species are predicted to exhibit minimal genetic differentiation among populations as a result of the species high mobility, with habitat specialists tending to show greater fine‐scale genetic structure. To explore the relationship between habitat specialization and gene flow, we investigated the genetic structure of a saltmarsh specialist with high potential mobility across a wide geographic range of fragmented habitat. Little variation among mitochondrial sequences (620 bp from ND2) was observed among 149 individual Clapper Rails Rallus crepitans sampled along the Atlantic coast of North America, with the majority of individuals at all sampling sites sharing a single haplotype. Genotyping of nine microsatellite loci across 136 individuals revealed moderate genetic diversity, no evidence of bottlenecks, and a weak pattern of genetic differentiation that increased with geographic distance. Multivariate analyses, Bayesian clustering and an AMOVA all suggested a lack of genetic structuring across the North American Atlantic coast, with all individuals grouped into a single interbreeding population. Spatial autocorrelation analyses showed evidence of weak female philopatry and a lack of male philopatry. We conclude that high gene flow connecting populations of this habitat specialist may result from the interaction of ecological and behavioral factors that promote dispersal and limit natal philopatry and breeding‐site fidelity. As climate change threatens saltmarshes, the genetic diversity and population connectivity of Clapper Rails may promote resilience of their populations. This finding helps inform about potential fates of other similarly behaving saltmarsh specialists on the Atlantic coast.

Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

Directory of Open Access Journals (Sweden)

Xiaoke Ma

2015-06-01

Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

A temperature-sensitive allele of a putative mRNA splicing helicase down-regulates many cell wall genes and causes radial swelling in Arabidopsis thaliana.

Science.gov (United States)

Howles, Paul A; Gebbie, Leigh K; Collings, David A; Varsani, Arvind; Broad, Ronan C; Ohms, Stephen; Birch, Rosemary J; Cork, Ann H; Arioli, Tony; Williamson, Richard E

2016-05-01

The putative RNA helicase encoded by the Arabidopsis gene At1g32490 is a homolog of the yeast splicing RNA helicases Prp2 and Prp22. We isolated a temperature-sensitive allele (rsw12) of the gene in a screen for root radial swelling mutants. Plants containing this allele grown at the restrictive temperature showed weak radial swelling, were stunted with reduced root elongation, and contained reduced levels of cellulose. The role of the protein was further explored by microarray analysis. By using both fold change cutoffs and a weighted gene coexpression network analysis (WGCNA) to investigate coexpression of genes, we found that the radial swelling phenotype was not linked to genes usually associated with primary cell wall biosynthesis. Instead, the mutation has strong effects on expression of secondary cell wall related genes. Many genes potentially associated with secondary walls were present in the most significant WGCNA module, as were genes coding for arabinogalactans and proteins with GPI anchors. The proportion of up-regulated genes that possess introns in rsw12 was above that expected if splicing was unrelated to the activity of the RNA helicase, suggesting that the helicase does indeed play a role in splicing in Arabidopsis. The phenotype may be due to a change in the expression of one or more genes coding for cell wall proteins.

How does farmer connectivity influence livestock genetic structure?

DEFF Research Database (Denmark)

Berthouly, C; Do, Duy Ngoc; Thévenon, S

2009-01-01

Assessing how genes flow across populations is a key component of conservation genetics. Gene flow in a natural population depends on ecological traits and the local environment, whereas for a livestock population, gene flow is driven by human activities. Spatial organization, relationships between...... farmers and their husbandry practices will define the farmer's network and so determine farmer connectivity. It is thus assumed that farmer connectivity will affect the genetic structure of their livestock. To test this hypothesis, goats reared by four different ethnic groups in a Vietnamese province were......, ethnicity and husbandry practices. In this study, we clearly linked the livestock genetic pattern to farmer connectivity and showed the importance of taking into account spatial information in genetic studies....

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

OpenAIRE

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

2009-01-01

Abstract 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...

Fto colocalizes with a satiety mediator oxytocin in the brain and upregulates oxytocin gene expression

Energy Technology Data Exchange (ETDEWEB)

Olszewski, Pawel K., E-mail: olsze005@umn.edu [Department of Neuroscience, Functional Pharmacology, Uppsala University, 75124 Uppsala (Sweden); Minnesota Obesity Center, Saint Paul, MN 55108 (United States); Fredriksson, Robert; Eriksson, Jenny D. [Department of Neuroscience, Functional Pharmacology, Uppsala University, 75124 Uppsala (Sweden); Mitra, Anaya [Department of Food Science and Nutrition, Saint Paul, MN 55108 (United States); Radomska, Katarzyna J. [Department of Neuroscience, Functional Pharmacology, Uppsala University, 75124 Uppsala (Sweden); Gosnell, Blake A. [Department of Food Science and Nutrition, Saint Paul, MN 55108 (United States); Solvang, Maria N. [Department of Neuroscience, Functional Pharmacology, Uppsala University, 75124 Uppsala (Sweden); Levine, Allen S. [Minnesota Obesity Center, Saint Paul, MN 55108 (United States); Department of Food Science and Nutrition, Saint Paul, MN 55108 (United States); Schioeth, Helgi B. [Department of Neuroscience, Functional Pharmacology, Uppsala University, 75124 Uppsala (Sweden)

2011-05-13

Highlights: {yields} The majority of neurons synthesizing a satiety mediator, oxytocin, coexpress Fto. {yields} The level of colocalization is similar in the male and female brain. {yields} Fto overexpression in hypothalamic neurons increases oxytocin mRNA levels by 50%. {yields} Oxytocin does not affect Fto expression through negative feedback mechanisms. -- Abstract: Single nucleotide polymorphisms in the fat mass and obesity-associated (FTO) gene have been associated with obesity in humans. Alterations in Fto expression in transgenic animals affect body weight, energy expenditure and food intake. Fto, a nuclear protein and proposed transcription co-factor, has been speculated to affect energy balance through a functional relationship with specific genes encoding feeding-related peptides. Herein, we employed double immunohistochemistry and showed that the majority of neurons synthesizing a satiety mediator, oxytocin, coexpress Fto in the brain of male and female mice. We then overexpressed Fto in a murine hypothalamic cell line and, using qPCR, detected a 50% increase in the level of oxytocin mRNA. Expression levels of several other feeding-related genes, including neuropeptide Y (NPY) and Agouti-related protein (AgRP), were unaffected by the FTO transfection. Addition of 10 and 100 nmol oxytocin to the cell culture medium did not affect Fto expression in hypothalamic cells. We conclude that Fto, a proposed transcription co-factor, influences expression of the gene encoding a satiety mediator, oxytocin.

Fto colocalizes with a satiety mediator oxytocin in the brain and upregulates oxytocin gene expression

International Nuclear Information System (INIS)

Olszewski, Pawel K.; Fredriksson, Robert; Eriksson, Jenny D.; Mitra, Anaya; Radomska, Katarzyna J.; Gosnell, Blake A.; Solvang, Maria N.; Levine, Allen S.; Schioeth, Helgi B.

2011-01-01

Highlights: → The majority of neurons synthesizing a satiety mediator, oxytocin, coexpress Fto. → The level of colocalization is similar in the male and female brain. → Fto overexpression in hypothalamic neurons increases oxytocin mRNA levels by 50%. → Oxytocin does not affect Fto expression through negative feedback mechanisms. -- Abstract: Single nucleotide polymorphisms in the fat mass and obesity-associated (FTO) gene have been associated with obesity in humans. Alterations in Fto expression in transgenic animals affect body weight, energy expenditure and food intake. Fto, a nuclear protein and proposed transcription co-factor, has been speculated to affect energy balance through a functional relationship with specific genes encoding feeding-related peptides. Herein, we employed double immunohistochemistry and showed that the majority of neurons synthesizing a satiety mediator, oxytocin, coexpress Fto in the brain of male and female mice. We then overexpressed Fto in a murine hypothalamic cell line and, using qPCR, detected a 50% increase in the level of oxytocin mRNA. Expression levels of several other feeding-related genes, including neuropeptide Y (NPY) and Agouti-related protein (AgRP), were unaffected by the FTO transfection. Addition of 10 and 100 nmol oxytocin to the cell culture medium did not affect Fto expression in hypothalamic cells. We conclude that Fto, a proposed transcription co-factor, influences expression of the gene encoding a satiety mediator, oxytocin.

Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC mouse

Directory of Open Access Journals (Sweden)

Belknap John

2010-10-01

Full Text Available Abstract Background The current study focused on the extent genetic diversity within a species (Mus musculus affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS formed from the same eight inbred strains that have been used to create the collaborative cross (CC. The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6 × DBA/2J (D2 F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA. Results Genes reliably detected as expressed were similar in all three data sets as was the variability of expression. As measured by the WGCNA, the modular structure of the transcriptome networks was also preserved both on the basis of module assignment and from the perspective of the topological overlap maps. Details of the HS-CC gene modules are provided; essentially identical results were obtained for the HS4 and F2 modules. Gene ontology annotation of the modules revealed a significant overrepresentation in some modules for neuronal processes, e.g., central nervous system development. Integration with known protein-protein interactions data indicated significant enrichment among co-expressed genes. We also noted significant overlap with markers of central nervous system cell types (neurons, oligodendrocytes and astrocytes. Using the Allen Brain Atlas, we found evidence of spatial co-localization within the striatum for several modules. Finally, for some modules it was possible to detect an enrichment of transcription binding sites. The binding site for Wt1, which is associated with neurodegeneration, was the most significantly overrepresented. Conclusions Despite the marked

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

Science.gov (United States)

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.

Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

Science.gov (United States)

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

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

Science.gov (United States)

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

2012-09-01

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

GOBO: gene expression-based outcome for breast cancer online.

Directory of Open Access Journals (Sweden)

Markus Ringnér

Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Genome-scale analysis of positional clustering of mouse testis-specific genes

Directory of Open Access Journals (Sweden)

Lee Bernett TK

2005-01-01

Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

Globalisation reaches gene regulation: the case for vertebrate limb development.

Science.gov (United States)

Zuniga, Aimée

2005-08-01

Analysis of key regulators of vertebrate limb development has revealed that the cis-regulatory regions controlling their expression are often located several hundred kilobases upstream of the transcription units. These far up- or down-stream cis-regulatory regions tend to reside within rather large, functionally and structurally unrelated genes. Molecular analysis is beginning to reveal the complexity of these large genomic landscapes, which control the co-expression of clusters of diverse genes by this novel type of long-range and globally acting cis-regulatory region. An increasing number of spontaneous mutations in vertebrates, including humans, are being discovered inactivating or altering such global control regions. Thereby, the functions of a seemingly distant but essential gene are disrupted rather than the closest.

Association between plasma metabolites and gene expression profiles in five porcine endocrine tissues

Directory of Open Access Journals (Sweden)

Bassols Anna

2011-07-01

Full Text Available Abstract Background Endocrine tissues play a fundamental role in maintaining homeostasis of plasma metabolites such as non-esterified fatty acids and glucose, the levels of which reflect the energy balance or the health status of animals. However, the relationship between the transcriptome of endocrine tissues and plasma metabolites has been poorly studied. Methods We determined the blood levels of 12 plasma metabolites in 27 pigs belonging to five breeds, each breed consisting of both females and males. The transcriptome of five endocrine tissues i.e. hypothalamus, adenohypophysis, thyroid gland, gonads and backfat tissues from 16 out of the 27 pigs was also determined. Sex and breed effects on the 12 plasma metabolites were investigated and associations between genes expressed in the five endocrine tissues and the 12 plasma metabolites measured were analyzed. A probeset was defined as a quantitative trait transcript (QTT when its association with a particular metabolic trait achieved a nominal P value Results A larger than expected number of QTT was found for non-esterified fatty acids and alanine aminotransferase in at least two tissues. The associations were highly tissue-specific. The QTT within the tissues were divided into co-expression network modules enriched for genes in Kyoto Encyclopedia of Genes and Genomes or gene ontology categories that are related to the physiological functions of the corresponding tissues. We also explored a multi-tissue co-expression network using QTT for non-esterified fatty acids from the five tissues and found that a module, enriched in hypothalamus QTT, was positioned at the centre of the entire multi-tissue network. Conclusions These results emphasize the relationships between endocrine tissues and plasma metabolites in terms of gene expression. Highly tissue-specific association patterns suggest that candidate genes or gene pathways should be investigated in the context of specific tissues.

Construction and use of gene expression covariation matrix

Directory of Open Access Journals (Sweden)

Bellis Michel

2009-07-01

Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

Improved production of biohydrogen in light-powered Escherichia coli by co-expression of proteorhodopsin and heterologous hydrogenase

Directory of Open Access Journals (Sweden)

Kim Jaoon YH

2012-01-01

Full Text Available Abstract Background Solar energy is the ultimate energy source on the Earth. The conversion of solar energy into fuels and energy sources can be an ideal solution to address energy problems. The recent discovery of proteorhodopsin in uncultured marine γ-proteobacteria has made it possible to construct recombinant Escherichia coli with the function of light-driven proton pumps. Protons that translocate across membranes by proteorhodopsin generate a proton motive force for ATP synthesis by ATPase. Excess protons can also be substrates for hydrogen (H2 production by hydrogenase in the periplasmic space. In the present work, we investigated the effect of the co-expression of proteorhodopsin and hydrogenase on H2 production yield under light conditions. Results Recombinant E. coli BL21(DE3 co-expressing proteorhodopsin and [NiFe]-hydrogenase from Hydrogenovibrio marinus produced ~1.3-fold more H2 in the presence of exogenous retinal than in the absence of retinal under light conditions (70 μmole photon/(m2·s. We also observed the synergistic effect of proteorhodopsin with endogenous retinal on H2 production (~1.3-fold more with a dual plasmid system compared to the strain with a single plasmid for the sole expression of hydrogenase. The increase of light intensity from 70 to 130 μmole photon/(m2·s led to an increase (~1.8-fold in H2 production from 287.3 to 525.7 mL H2/L-culture in the culture of recombinant E. coli co-expressing hydrogenase and proteorhodopsin in conjunction with endogenous retinal. The conversion efficiency of light energy to H2 achieved in this study was ~3.4%. Conclusion Here, we report for the first time the potential application of proteorhodopsin for the production of biohydrogen, a promising alternative fuel. We showed that H2 production was enhanced by the co-expression of proteorhodopsin and [NiFe]-hydrogenase in recombinant E. coli BL21(DE3 in a light intensity-dependent manner. These results demonstrate that E. coli

Systematic Analysis of Gene Expression Alterations and Clinical Outcomes for Long-Chain Acyl-Coenzyme A Synthetase Family in Cancer.

Directory of Open Access Journals (Sweden)

Wei-Ching Chen

Full Text Available Dysregulated lipid metabolism contributes to cancer progression. Our previous study indicates that long-chain fatty acyl-Co A synthetase (ACSL 3 is essential for lipid upregulation induced by endoplasmic reticulum stress. In this report, we aimed to identify the role of ACSL family in cancer with systematic analysis and in vitro experiment. We explored the ACSL expression using Oncomine database to determine the gene alteration during carcinogenesis and identified the association between ACSL expression and the survival of cancer patient using PrognoScan database. ACSL1 may play a potential oncogenic role in colorectal and breast cancer and play a potential tumor suppressor role in lung cancer. Co-expression analysis revealed that ACSL1 was coexpressed with MYBPH, PTPRE, PFKFB3, SOCS3 in colon cancer and with LRRFIP1, TSC22D1 in lung cancer. In accordance with PrognoScan analysis, downregulation of ACSL1 in colon and breast cancer cell line inhibited proliferation, migration, and anchorage-independent growth. In contrast, increase of oncogenic property was observed in lung cancer cell line by attenuating ACSL1. High ACSL3 expression predicted a better prognosis in ovarian cancer; in contrast, high ACSL3 predicted a worse prognosis in melanoma. ACSL3 was coexpressed with SNUPN, TRIP13, and SEMA5A in melanoma. High expression of ACSL4 predicted a worse prognosis in colorectal cancer, but predicted better prognosis in breast, brain and lung cancer. ACSL4 was coexpressed with SERPIN2, HNRNPCL1, ITIH2, PROCR, LRRFIP1. High expression of ACSL5 predicted good prognosis in breast, ovarian, and lung cancers. ACSL5 was coexpressed with TMEM140, TAPBPL, BIRC3, PTPRE, and SERPINB1. Low ACSL6 predicted a worse prognosis in acute myeloid leukemia. ACSL6 was coexpressed with SOX6 and DARC. Altogether, different members of ACSLs are implicated in diverse types of cancer development. ACSL-coexpressed molecules may be used to further investigate the role of ACSL

Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems.

Directory of Open Access Journals (Sweden)

Josep M Mercader

Full Text Available Type 2 Diabetes (T2D is a highly prevalent chronic metabolic disease with strong co-morbidity with obesity and cardiovascular diseases. There is growing evidence supporting the notion that a crosstalk between mitochondria and the insulin signaling cascade could be involved in the etiology of T2D and insulin resistance. In this study we investigated the molecular basis of this crosstalk by using systems biology approaches. We combined, filtered, and interrogated different types of functional interaction data, such as direct protein-protein interactions, co-expression analyses, and metabolic and signaling dependencies. As a result, we constructed the mitochondria-insulin (MITIN network, which highlights 286 genes as candidate functional linkers between these two systems. The results of internal gene expression analysis of three independent experimental models of mitochondria and insulin signaling perturbations further support the connecting roles of these genes. In addition, we further assessed whether these genes are involved in the etiology of T2D using the genome-wide association study meta-analysis from the DIAGRAM consortium, involving 8,130 T2D cases and 38,987 controls. We found modest enrichment of genes associated with T2D amongst our linker genes (p = 0.0549, including three already validated T2D SNPs and 15 additional SNPs, which, when combined, were collectively associated to increased fasting glucose levels according to MAGIC genome wide meta-analysis (p = 8.12×10(-5. This study highlights the potential of combining systems biology, experimental, and genome-wide association data mining for identifying novel genes and related variants that increase vulnerability to complex diseases.

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

Science.gov (United States)

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.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

Science.gov (United States)

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.

Principles for the organization of gene-sets.

Science.gov (United States)

Li, Wentian; Freudenberg, Jan; Oswald, Michaela

2015-12-01

A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrative analysis of many weighted co-expression networks using tensor computation.

Directory of Open Access Journals (Sweden)

Wenyuan Li

2011-06-01

Full Text Available 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.

Pathway enrichment and co-expression cluster analysis - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM...lusters File URL: ftp://ftp.biosciencedbc.jp/archive/fantom5/datafiles/phase1.3/extra/Co-expression_clusters...ite Policy | Contact Us Pathway enrichment and co-expression cluster analysis - FANTOM5 | LSDB Archive ...

Immunohistochemical Observation of Co-expression of E- and N-cadherins in Rat Organogenesis

International Nuclear Information System (INIS)

Sakamoto, Atsushi; Murata, Kazumoto; Suzuki, Hideto; Yatabe, Megumi; Kikuchi, Motoshi

2008-01-01

Cadherins are a family of transmembrane glycoproteins that mediate cell-to-cell adhesion. Isoforms, including E- and N-cadherin, have been identified and shown to regulate morphogenesis through homophilic binding. In the ontogeny, the expressions of E- and N-cadherin change spatiotemporally, and the changes in cadherin isoforms, called cadherin switching, impact the mechanical adhesion of cells. Furthermore, cadherin functions as a receptor that transfers information from outside to inside cells, and in terms of switching, it affects cell phenotypes. To observe the expression patterns of E- and N-cadherins during embryogenesis and to identify cells that transiently coexpress both cadherins, we employed a recently developed immunohistochemical double staining technique in rat fetuses. At embryonic day 9, embryonic ectodermal cells more dominantly expressed E-cadherin, while mesodermal cells more dominantly expressed N-cadherin. At embryonic day 10, the expression pattern of E-cadherin in the surface ectoderm and endoderm and that of N-cadherin in the neuroectoderm were established. After embryonic day 10, unique co-expression of E- and N-cadherin was observed in primordia, such as the bulbus cordis, otic pit, notochord, and Rathke’s pouch. In the present study, it was possible to visualize the expression patterns of E- and N-cadherin during early fetal development, which enabled us to morphologically clarify cadherin switching

Meta-analysis of peripheral blood gene expression modules for COPD phenotypes.

Directory of Open Access Journals (Sweden)

Dominik Reinhold

Full Text Available Chronic obstructive pulmonary disease (COPD occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002, and two had some association with emphysema (meta p ≤ 0.06; some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included "immune response" and "defense response." The cell types whose type-specific genes were overrepresented in modules (p < 0.05 included

An Analysis of Cosecretion and Coexpression of Gut Hormones From Male Rat Proximal and Distal Small Intestine

DEFF Research Database (Denmark)

Svendsen, Berit; Pedersen, Jens; Albrechtsen, Nicolai Jacob Wewer

2015-01-01

Gut endocrine cells are generally thought to have distinct localization and secretory products. Recent studies suggested that the cells are highly related and have potential to express more than one hormone. We studied co-expression and co-secretion of gut hormones in separate segments of rat sma...

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

Science.gov (United States)

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

Identifying candidate driver genes by integrative ovarian cancer genomics data

Science.gov (United States)

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.

Development of stable Vibrio cholerae O1 Hikojima type vaccine strains co-expressing the Inaba and Ogawa lipopolysaccharide antigens.

Directory of Open Access Journals (Sweden)

Stefan L Karlsson

Full Text Available We describe here the development of stable classical and El Tor V. cholerae O1 strains of the Hikojima serotype that co-express the Inaba and Ogawa antigens of O1 lipopolysaccharide (LPS. Mutation of the wbeT gene reduced LPS perosamine methylation and thereby gave only partial transformation into Ogawa LPS on the cell surface. The strains express approximately equal amounts of Inaba- and Ogawa-LPS antigens which are preserved after formalin-inactivation of the bacteria. Oral immunizations of both inbred and outbred mice with formalin-inactivated whole-cell vaccine preparations of these strains elicited strong intestinal IgA anti-LPS as well as serum vibriocidal antibody responses against both Inaba and Ogawa that were fully comparable to the responses induced by the licensed Dukoral vaccine. Passive protection studies in infant mice showed that immune sera raised against either of the novel Hikojima vaccine strains protected baby mice against infection with virulent strains of both serotypes. This study illustrates the power of using genetic manipulation to improve the properties of bacteria strains for use in killed whole-cell vaccines.

Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood

Directory of Open Access Journals (Sweden)

Vernon Suzanne D

2008-09-01

Full Text Available Abstract Background 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. Methods 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. Results 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 Conclusion 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.

Multi-species genetic connectivity in a terrestrial habitat network.

Science.gov (United States)

Marrotte, Robby R; Bowman, Jeff; Brown, Michael G C; Cordes, Chad; Morris, Kimberley Y; Prentice, Melanie B; Wilson, Paul J

2017-01-01

Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx ( Lynx canadensis ), American marten ( Martes americana ), fisher ( Pekania pennanti ), and southern flying squirrel ( Glaucomys volans ) to evaluate multi-species genetic connectivity across Ontario, Canada. We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow. Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area

Ascorbate peroxidase-related (APx-R) is not a duplicable gene.

Science.gov (United States)

Dunand, Christophe; Mathé, Catherine; Lazzarotto, Fernanda; Margis, Rogério; Margis-Pinheiro, Marcia

2011-12-01

Phylogenetic, genomic and functional analyses have allowed the identification of a new class of putative heme peroxidases, so called APx-R (APx-Related). These new class, mainly present in the green lineage (including green algae and land plants), can also be detected in other unicellular chloroplastic organisms. Except for recent polyploid organisms, only single-copy of APx-R gene was detected in each genome, suggesting that the majority of the APx-R extra-copies were lost after chromosomal or segmental duplications. In a similar way, most APx-R co-expressed genes in Arabidopsis genome do not have conserved extra-copies after chromosomal duplications and are predicted to be localized in organelles, as are the APx-R. The member of this gene network can be considered as unique gene, well conserved through the evolution due to a strong negative selection pressure and a low evolution rate. © 2011 Landes Bioscience

Is human blood a good surrogate for brain tissue in transcriptional studies?

Directory of Open Access Journals (Sweden)

van den Berg Leonard H

2010-10-01

Full Text Available Abstract Background Since human brain tissue is often unavailable for transcriptional profiling studies, blood expression data is frequently used as a substitute. The underlying hypothesis in such studies is that genes expressed in brain tissue leave a transcriptional footprint in blood. We tested this hypothesis by relating three human brain expression data sets (from cortex, cerebellum and caudate nucleus to two large human blood expression data sets (comprised of 1463 individuals. Results We found mean expression levels were weakly correlated between the brain and blood data (r range: [0.24,0.32]. Further, we tested whether co-expression relationships were preserved between the three brain regions and blood. Only a handful of brain co-expression modules showed strong evidence of preservation and these modules could be combined into a single large blood module. We also identified highly connected intramodular "hub" genes inside preserved modules. These preserved intramodular hub genes had the following properties: first, their expression levels tended to be significantly more heritable than those from non-preserved intramodular hub genes (p -90; second, they had highly significant positive correlations with the following cluster of differentiation genes: CD58, CD47, CD48, CD53 and CD164; third, a significant number of them were known to be involved in infection mechanisms, post-transcriptional and post-translational modification and other basic processes. Conclusions Overall, we find transcriptome organization is poorly preserved between brain and blood. However, the subset of preserved co-expression relationships characterized here may aid future efforts to identify blood biomarkers for neurological and neuropsychiatric diseases when brain tissue samples are unavailable.

EasyClone: method for iterative chromosomal integration of multiple genes in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Jensen, Niels Bjerg; Strucko, Tomas; Kildegaard, Kanchana Rueksomtawin

2014-01-01

of multiple genes with an option of recycling selection markers. The vectors combine the advantage of efficient uracil excision reaction-based cloning and Cre-LoxP-mediated marker recycling system. The episomal and integrative vector sets were tested by inserting genes encoding cyan, yellow, and red...... fluorescent proteins into separate vectors and analyzing for co-expression of proteins by flow cytometry. Cells expressing genes encoding for the three fluorescent proteins from three integrations exhibited a much higher level of simultaneous expression than cells producing fluorescent proteins encoded...... on episomal plasmids, where correspondingly 95% and 6% of the cells were within a fluorescence interval of Log10 mean ± 15% for all three colors. We demonstrate that selective markers can be simultaneously removed using Cre-mediated recombination and all the integrated heterologous genes remain...

Co-expression of G2-EPSPS and glyphosate acetyltransferase GAT genes conferring high tolerance to glyphosate in soybean

OpenAIRE

Guo, Bingfu; Guo, Yong; Hong, Huilong; Jin, Longguo; Zhang, Lijuan; Chang, Ru-Zhen; Lu, Wei; Lin, Min; Qiu, Li-Juan

2015-01-01

Glyphosate is a widely used non-selective herbicide with broad spectrum of weed control around the world. At present, most of the commercial glyphosate tolerant soybeans utilize glyphosate tolerant gene CP4-EPSPS or glyphosate acetyltransferase gene GAT separately. In this study, both glyphosate tolerant gene G2-EPSPS and glyphosate degraded gene GAT were co-transferred into soybean and transgenic plants showed high tolerance to glyphosate. Molecular analysis including PCR, Sothern blot, qRT-...

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

Science.gov (United States)

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Improvisation and co-expression in explorative digital music systems

DEFF Research Database (Denmark)

Hansen, Anne-Marie Skriver

relationships. The benefit of the digitally networked electronic musical instruments is that particular patterns of co-expression can be found and mediated by the music system (that also contains all individual instruments) in ways that make players aware of their mutual play and perhaps will encourage players...... other when they are given a number of creative restrictions in the sonic/musical material that they interact with. The benefit with digital musical instruments is that non-musicians and novices can get access to limited musical material that they are immediately able to master without any musical...... be developed in future designs. The Wacom® pen tablet, a simple drawing interface, was turned into an array of digital musical instruments in order to investigate the benefit of networked musical instruments in the context of the genre of casual games. Through qualitative and quantitative studies of player...

De novo Assembly of the Camellia nitidissima Transcriptome Reveals Key Genes of Flower Pigment Biosynthesis

Directory of Open Access Journals (Sweden)

Xingwen Zhou

2017-09-01

Full Text Available The golden camellia, Camellia nitidissima Chi., is a well-known ornamental plant that is known as “the queen of camellias” because of its golden yellow flowers. The principal pigments in the flowers are carotenoids and flavonol glycosides. Understanding the biosynthesis of the golden color and its regulation is important in camellia breeding. To obtain a comprehensive understanding of flower development in C. nitidissima, a number of cDNA libraries were independently constructed during flower development. Using the Illumina Hiseq2500 platform, approximately 71.8 million raw reads (about 10.8 gigabase pairs were obtained and assembled into 583,194 transcripts and 466, 594 unigenes. A differentially expressed genes (DEGs and co-expression network was constructed to identify unigenes correlated with flower color. The analysis of DEGs and co-expressed network involved in the carotenoid pathway indicated that the biosynthesis of carotenoids is regulated mainly at the transcript level and that phytoene synthase (PSY, β -carotene 3-hydroxylase (CrtZ, and capsanthin synthase (CCS1 exert synergistic effects in carotenoid biosynthesis. The analysis of DEGs and co-expressed network involved in the flavonoid pathway indicated that chalcone synthase (CHS, naringenin 3-dioxygenase (F3H, leucoanthocyanidin dioxygenase(ANS, and flavonol synthase (FLS play critical roles in regulating the formation of flavonols and anthocyanidin. Based on the gene expression analysis of the carotenoid and flavonoid pathways, and determinations of the pigments, we speculate that the high expression of PSY and CrtZ ensures the production of adequate levels of carotenoids, while the expression of CHS, FLS ensures the production of flavonols. The golden yellow color is then the result of the accumulation of carotenoids and flavonol glucosides in the petals. This study of the mechanism of color formation in golden camellia points the way to breeding strategies that exploit gene

Additional file 9: Figure S2. of Uncovering co-expression gene network modules regulating fruit acidity in diverse apples

OpenAIRE

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

2015-01-01

Regulator M190273 and its other five assigned tight clusters. Elements and their contents, formats and messages are same as those noted in Fig. 8a. (A) Cluster 8 of 31 genes. (B) Cluster 9 of 28 genes. (C) Cluster 40 of 55 genes. (D) Cluster 21 of 11 genes. (E) Cluster 45 of 10 genes. (PPTX 238 kb)

Repressor-mediated tissue-specific gene expression in plants

Science.gov (United States)

Meagher, Richard B [Athens, GA; Balish, Rebecca S [Oxford, OH; Tehryung, Kim [Athens, GA; McKinney, Elizabeth C [Athens, GA

2009-02-17

Plant tissue specific gene expression by way of repressor-operator complexes, has enabled outcomes including, without limitation, male sterility and engineered plants having root-specific gene expression of relevant proteins to clean environmental pollutants from soil and water. A mercury hyperaccumulation strategy requires that mercuric ion reductase coding sequence is strongly expressed. The actin promoter vector, A2pot, engineered to contain bacterial lac operator sequences, directed strong expression in all plant vegetative organs and tissues. In contrast, the expression from the A2pot construct was restricted primarily to root tissues when a modified bacterial repressor (LacIn) was coexpressed from the light-regulated rubisco small subunit promoter in above-ground tissues. Also provided are analogous repressor operator complexes for selective expression in other plant tissues, for example, to produce male sterile plants.

Identification of Key Pathways and Genes in the Dynamic Progression of HCC Based on WGCNA.

Science.gov (United States)

Yin, Li; Cai, Zhihui; Zhu, Baoan; Xu, Cunshuan

2018-02-14

Hepatocellular carcinoma (HCC) is a devastating disease worldwide. Though many efforts have been made to elucidate the process of HCC, its molecular mechanisms of development remain elusive due to its complexity. To explore the stepwise carcinogenic process from pre-neoplastic lesions to the end stage of HCC, we employed weighted gene co-expression network analysis (WGCNA) which has been proved to be an effective method in many diseases to detect co-expressed modules and hub genes using eight pathological stages including normal, cirrhosis without HCC, cirrhosis, low-grade dysplastic, high-grade dysplastic, very early and early, advanced HCC and very advanced HCC. Among the eight consecutive pathological stages, five representative modules are selected to perform canonical pathway enrichment and upstream regulator analysis by using ingenuity pathway analysis (IPA) software. We found that cell cycle related biological processes were activated at four neoplastic stages, and the degree of activation of the cell cycle corresponded to the deterioration degree of HCC. The orange and yellow modules enriched in energy metabolism, especially oxidative metabolism, and the expression value of the genes decreased only at four neoplastic stages. The brown module, enriched in protein ubiquitination and ephrin receptor signaling pathways, correlated mainly with the very early stage of HCC. The darkred module, enriched in hepatic fibrosis/hepatic stellate cell activation, correlated with the cirrhotic stage only. The high degree hub genes were identified based on the protein-protein interaction (PPI) network and were verified by Kaplan-Meier survival analysis. The novel five high degree hub genes signature that was identified in our study may shed light on future prognostic and therapeutic approaches. Our study brings a new perspective to the understanding of the key pathways and genes in the dynamic changes of HCC progression. These findings shed light on further investigations.

Rapid and tunable method to temporally control gene editing based on conditional Cas9 stabilization. | Office of Cancer Genomics

Science.gov (United States)

The CRISPR/Cas9 system is a powerful tool for studying gene function. Here, we describe a method that allows temporal control of CRISPR/Cas9 activity based on conditional Cas9 destabilization. We demonstrate that fusing an FKBP12-derived destabilizing domain to Cas9 (DD-Cas9) enables conditional Cas9 expression and temporal control of gene editing in the presence of an FKBP12 synthetic ligand. This system can be easily adapted to co-express, from the same promoter, DD-Cas9 with any other gene of interest without co-modulation of the latter.

miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling.

Science.gov (United States)

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.

Additional file 10: Figure S3. of Uncovering co-expression gene network modules regulating fruit acidity in diverse apples

OpenAIRE

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

2015-01-01

Other regulators from modules Turquoise and Brown and their assigned tight clusters. Elements and their contents, formats and messages are same as those noted in Fig. 8a. (A) Regulator M239684 and Cluster 41 of 68 genes. (B) Regulator M239684 and Cluster 5 of 14 genes. (C) Regulator M239684 and Cluster 7 of 14 genes. (D) Regulator M753318 and Cluster 23 of 11 genes. (E) Regulator M753318 and Cluster 32 of 11 genes. (F) Regulator M175481 and Cluster 2 of 16 genes. (G) Regulator M134341 and Cl...

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

Science.gov (United States)

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.

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org.

Science.gov (United States)

Bubier, Jason A; Langston, Michael A; Baker, Erich J; Chesler, Elissa J

2017-01-01

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

Sensing coral reef connectivity pathways from space

KAUST Repository

Raitsos, Dionysios E.; Brewin, Robert J. W.; Zhan, Peng; Dreano, Denis; Pradhan, Yaswant; Nanninga, Gerrit B.; Hoteit, Ibrahim

2017-01-01

Coral reefs rely on inter-habitat connectivity to maintain gene flow, biodiversity and ecosystem resilience. Coral reef communities of the Red Sea exhibit remarkable genetic homogeneity across most of the Arabian Peninsula coastline, with a genetic break towards the southern part of the basin. While previous studies have attributed these patterns to environmental heterogeneity, we hypothesize that they may also emerge as a result of dynamic circulation flow; yet, such linkages remain undemonstrated. Here, we integrate satellite-derived biophysical observations, particle dispersion model simulations, genetic population data and ship-borne in situ profiles to assess reef connectivity in the Red Sea. We simulated long-term (>20 yrs.) connectivity patterns driven by remotely-sensed sea surface height and evaluated results against estimates of genetic distance among populations of anemonefish, Amphiprion bicinctus, along the eastern Red Sea coastline. Predicted connectivity was remarkably consistent with genetic population data, demonstrating that circulation features (eddies, surface currents) formulate physical pathways for gene flow. The southern basin has lower physical connectivity than elsewhere, agreeing with known genetic structure of coral reef organisms. The central Red Sea provides key source regions, meriting conservation priority. Our analysis demonstrates a cost-effective tool to estimate biophysical connectivity remotely, supporting coastal management in data-limited regions.

Sensing coral reef connectivity pathways from space

KAUST Repository

Raitsos, Dionysios E.

2017-08-18

Coral reefs rely on inter-habitat connectivity to maintain gene flow, biodiversity and ecosystem resilience. Coral reef communities of the Red Sea exhibit remarkable genetic homogeneity across most of the Arabian Peninsula coastline, with a genetic break towards the southern part of the basin. While previous studies have attributed these patterns to environmental heterogeneity, we hypothesize that they may also emerge as a result of dynamic circulation flow; yet, such linkages remain undemonstrated. Here, we integrate satellite-derived biophysical observations, particle dispersion model simulations, genetic population data and ship-borne in situ profiles to assess reef connectivity in the Red Sea. We simulated long-term (>20 yrs.) connectivity patterns driven by remotely-sensed sea surface height and evaluated results against estimates of genetic distance among populations of anemonefish, Amphiprion bicinctus, along the eastern Red Sea coastline. Predicted connectivity was remarkably consistent with genetic population data, demonstrating that circulation features (eddies, surface currents) formulate physical pathways for gene flow. The southern basin has lower physical connectivity than elsewhere, agreeing with known genetic structure of coral reef organisms. The central Red Sea provides key source regions, meriting conservation priority. Our analysis demonstrates a cost-effective tool to estimate biophysical connectivity remotely, supporting coastal management in data-limited regions.

A 3,000-Loci Transcription Map of Chromosome 3B Unravels the Structural and Functional Features of Gene Islands in Hexaploid Wheat

Czech Academy of Sciences Publication Activity Database

Rustenholz, C.; Choulet, F.; Laugier, Ch.; Šafář, Jan; Šimková, Hana; Doležel, Jaroslav; Magni, F.; Scalabrin, S.; Cattonaro, F.; Vautrin, S.; Bellec, A.; Berges, H.; Feuillet, C.; Paux, E.

2011-01-01

Roč. 157, č. 4 (2011), s. 1596-1608 ISSN 0032-0889 R&D Projects: GA MŠk ED0007/01/01 Institutional research plan: CEZ:AV0Z50380511 Keywords : LOCAL COEXPRESSION DOMAINS * ARABIDOPSIS-THALIANA * NEIGHBORING GENES Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 6.535, year: 2011

HFE gene variants, iron, and lipids: a novel connection in Alzheimer's disease.

Science.gov (United States)

Ali-Rahmani, Fatima; Schengrund, Cara-Lynne; Connor, James R

2014-01-01

Iron accumulation and associated oxidative stress in the brain have been consistently found in several neurodegenerative diseases. Multiple genetic studies have been undertaken to try to identify a cause of neurodegenerative diseases but direct connections have been rare. In the iron field, variants in the HFE gene that give rise to a protein involved in cellular iron regulation, are associated with iron accumulation in multiple organs including the brain. There is also substantial epidemiological, genetic, and molecular evidence of disruption of cholesterol homeostasis in several neurodegenerative diseases, in particular Alzheimer's disease (AD). Despite the efforts that have been made to identify factors that can trigger the pathological events associated with neurodegenerative diseases they remain mostly unknown. Because molecular phenotypes such as oxidative stress, synaptic failure, neuronal loss, and cognitive decline, characteristics associated with AD, have been shown to result from disruption of a number of pathways, one can easily argue that the phenotype seen may not arise from a linear sequence of events. Therefore, a multi-targeted approach is needed to understand a complex disorder like AD. This can be achieved only when knowledge about interactions between the different pathways and the potential influence of environmental factors on them becomes available. Toward this end, this review discusses what is known about the roles and interactions of iron and cholesterol in neurodegenerative diseases. It highlights the effects of gene variants of HFE (H63D- and C282Y-HFE) on iron and cholesterol metabolism and how they may contribute to understanding the etiology of complex neurodegenerative diseases.

l-Arabinose Isomerase and d-Xylose Isomerase from Lactobacillus reuteri: Characterization, Coexpression in the Food Grade Host Lactobacillus plantarum, and Application in the Conversion of d-Galactose and d-Glucose

Science.gov (United States)

2014-01-01

The l-arabinose isomerase (l-AI) and the d-xylose isomerase (d-XI) encoding genes from Lactobacillus reuteri (DSMZ 17509) were cloned and overexpressed in Escherichia coli BL21 (DE3). The proteins were purified to homogeneity by one-step affinity chromatography and characterized biochemically. l-AI displayed maximum activity at 65 °C and pH 6.0, whereas d-XI showed maximum activity at 65 °C and pH 5.0. Both enzymes require divalent metal ions. The genes were also ligated into the inducible lactobacillal expression vectors pSIP409 and pSIP609, the latter containing a food grade auxotrophy marker instead of an antibiotic resistance marker, and the l-AI- and d-XI-encoding sequences/genes were coexpressed in the food grade host Lactobacillus plantarum. The recombinant enzymes were tested for applications in carbohydrate conversion reactions of industrial relevance. The purified l-AI converted d-galactose to d-tagatose with a maximum conversion rate of 35%, and the d-XI isomerized d-glucose to d-fructose with a maximum conversion rate of 48% at 60 °C. PMID:24443973

Remodeling of Sensorimotor Brain Connectivity in Gpr88-Deficient Mice.

Science.gov (United States)

Arefin, Tanzil Mahmud; Mechling, Anna E; Meirsman, Aura Carole; Bienert, Thomas; Hübner, Neele Saskia; Lee, Hsu-Lei; Ben Hamida, Sami; Ehrlich, Aliza; Roquet, Dan; Hennig, Jürgen; von Elverfeldt, Dominik; Kieffer, Brigitte Lina; Harsan, Laura-Adela

2017-10-01

Recent studies have demonstrated that orchestrated gene activity and expression support synchronous activity of brain networks. However, there is a paucity of information on the consequences of single gene function on overall brain functional organization and connectivity and how this translates at the behavioral level. In this study, we combined mouse mutagenesis with functional and structural magnetic resonance imaging (MRI) to determine whether targeted inactivation of a single gene would modify whole-brain connectivity in live animals. The targeted gene encodes GPR88 (G protein-coupled receptor 88), an orphan G protein-coupled receptor enriched in the striatum and previously linked to behavioral traits relevant to neuropsychiatric disorders. Connectivity analysis of Gpr88-deficient mice revealed extensive remodeling of intracortical and cortico-subcortical networks. Most prominent modifications were observed at the level of retrosplenial cortex connectivity, central to the default mode network (DMN) whose alteration is considered a hallmark of many psychiatric conditions. Next, somatosensory and motor cortical networks were most affected. These modifications directly relate to sensorimotor gating deficiency reported in mutant animals and also likely underlie their hyperactivity phenotype. Finally, we identified alterations within hippocampal and dorsal striatum functional connectivity, most relevant to a specific learning deficit that we previously reported in Gpr88 -/- animals. In addition, amygdala connectivity with cortex and striatum was weakened, perhaps underlying the risk-taking behavior of these animals. This is the first evidence demonstrating that GPR88 activity shapes the mouse brain functional and structural connectome. The concordance between connectivity alterations and behavior deficits observed in Gpr88-deficient mice suggests a role for GPR88 in brain communication.

Protection of chickens against infectious bronchitis by a recombinant fowlpox virus co-expressing IBV-S1 and chicken IFNgamma.

Science.gov (United States)

Wang, Yun-Feng; Sun, Yong-Ke; Tian, Zhan-Cheng; Shi, Xing-Ming; Tong, Guang-Zhi; Liu, Sheng-Wang; Zhi, Hai-Dong; Kong, Xian-Gang; Wang, Mei

2009-11-23

A fowlpox virus expressing the chicken infectious bronchitis virus (IBV) S1 gene of the LX4 strain (rFPV-IBVS1) and a fowlpox virus co-expressing the S1 gene and the chicken type II interferon gene (rFPV-IBVS1-ChIFNgamma) were constructed. These viruses were assessed for their immunological efficacy on specific-pathogen-free (SPF) chickens challenged with a virulent IBV. Although the antibody levels in the rFPV-IBVS1-ChIFNgamma-vaccinated group were lower than those in the attenuated live IB vaccine H120 group and the rFPV-IBVS1 group, the rFPV-IBVS1-ChIFNgamma provided the strongest protection against an IBV LX4 virus challenge (15 out of 16 chickens immunized with rFPV-IBVS1-ChIFNgamma were protected), followed by the attenuated live IB vaccine (13/16 protected) and the rFPV-IBVS1 (12/16 protected). Compared to those of the rFPV-IBVS1 and the attenuated live IB vaccine groups, chickens in the rFPV-IBVS1-ChIFNgamma group eliminated virus more quickly and decreased the presence of viral antigen more significantly in renal tissue. Examination of affected tissues revealed abnormalities in the liver, spleen, kidney, lung and trachea of chickens vaccinated with the attenuated live IB vaccine and the rFPV-IBVS1 vaccine. In rFPV-IBVS1-ChIFNgamma-vaccinated chickens, pathological changes were also observed in those organs, but were milder and lasted shorter. The lesions in the mock control group were the most severe and lasted for at least 20 days. This study demonstrated that chicken type II interferon increased the immunoprotective efficacy of rFPV-IBVS1-ChIFNgamma and normal weight gain in vaccinated chickens although it inhibited serum antibody production.

An Org-1-Tup transcriptional cascade reveals different types of alary muscles connecting internal organs in Drosophila.

Science.gov (United States)

Boukhatmi, Hadi; Schaub, Christoph; Bataillé, Laetitia; Reim, Ingolf; Frendo, Jean-Louis; Frasch, Manfred; Vincent, Alain

2014-10-01

The T-box transcription factor Tbx1 and the LIM-homeodomain transcription factor Islet1 are key components in regulatory circuits that generate myogenic and cardiogenic lineage diversity in chordates. We show here that Org-1 and Tup, the Drosophila orthologs of Tbx1 and Islet1, are co-expressed and required for formation of the heart-associated alary muscles (AMs) in the abdomen. The same holds true for lineage-related muscles in the thorax that have not been described previously, which we name thoracic alary-related muscles (TARMs). Lineage analyses identified the progenitor cell for each AM and TARM. Three-dimensional high-resolution analyses indicate that AMs and TARMs connect the exoskeleton to the aorta/heart and to different regions of the midgut, respectively, and surround-specific tracheal branches, pointing to an architectural role in the internal anatomy of the larva. Org-1 controls tup expression in the AM/TARM lineage by direct binding to two regulatory sites within an AM/TARM-specific cis-regulatory module, tupAME. The contributions of Org-1 and Tup to the specification of Drosophila AMs and TARMs provide new insights into the transcriptional control of Drosophila larval muscle diversification and highlight new parallels with gene regulatory networks involved in the specification of cardiopharyngeal mesodermal derivatives in chordates. © 2014. Published by The Company of Biologists Ltd.

Attenuation of eph receptor kinase activation in cancer cells by coexpressed ephrin ligands.

Directory of Open Access Journals (Sweden)

Giulia Falivelli

Full Text Available The Eph receptor tyrosine kinases mediate juxtacrine signals by interacting "in trans" with ligands anchored to the surface of neighboring cells via a GPI-anchor (ephrin-As or a transmembrane segment (ephrin-Bs, which leads to receptor clustering and increased kinase activity. Additionally, soluble forms of the ephrin-A ligands released from the cell surface by matrix metalloproteases can also activate EphA receptor signaling. Besides these trans interactions, recent studies have revealed that Eph receptors and ephrins coexpressed in neurons can also engage in lateral "cis" associations that attenuate receptor activation by ephrins in trans with critical functional consequences. Despite the importance of the Eph/ephrin system in tumorigenesis, Eph receptor-ephrin cis interactions have not been previously investigated in cancer cells. Here we show that in cancer cells, coexpressed ephrin-A3 can inhibit the ability of EphA2 and EphA3 to bind ephrins in trans and become activated, while ephrin-B2 can inhibit not only EphB4 but also EphA3. The cis inhibition of EphA3 by ephrin-B2 implies that in some cases ephrins that cannot activate a particular Eph receptor in trans can nevertheless inhibit its signaling ability through cis association. We also found that an EphA3 mutation identified in lung cancer enhances cis interaction with ephrin-A3. These results suggest a novel mechanism that may contribute to cancer pathogenesis by attenuating the tumor suppressing effects of Eph receptor signaling pathways activated by ephrins in trans.

Signal Network Analysis of Plant Genes Responding to Ionizing Radiation

International Nuclear Information System (INIS)

Kim, Dong Sub; Kim, Jinbaek; Kim, Sang Hoon

2012-12-01

In this project, we irradiated Arabidopsis plants with various doses of gamma-rays at the vegetative and reproductive stages to assess their radiation sensitivity. After the gene expression profiles and an analysis of the antioxidant response, we selected several Arabidopsis genes for uses of 'Radio marker genes (RMG)' and conducted over-expression and knock-down experiments to confirm the radio sensitivity. Based on these results, we applied two patents for the detection of two RMG (At3g28210 and At4g37990) and development of transgenic plants. Also, we developed a Genechip for use of high-throughput screening of Arabidopsis genes responding only to ionizing radiation and identified RMG to detect radiation leaks. Based on these results, we applied two patents associated with the use of Genechip for different types of radiation and different growth stages. Also, we conducted co-expression network study of specific expressed probes against gamma-ray stress and identified expressed patterns of duplicated genes formed by whole/500kb segmental genome duplication

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

Science.gov (United States)

Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2018-02-09

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

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

International Nuclear Information System (INIS)

Vormittag, Laurenz; Thurnher, Dietmar; Geleff, Silvana; Pammer, Johannes; Heiduschka, Gregor; Brunner, Markus; Grasl, Matthaeus Ch.; Erovic, Boban M.

2009-01-01

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. In 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

Coordinated gene expression between Trichodesmium and its microbiome over day-night cycles in the North Pacific Subtropical Gyre.

Science.gov (United States)

Frischkorn, Kyle R; Haley, Sheean T; Dyhrman, Sonya T

2018-04-01

Trichodesmium is a widespread, N 2 fixing marine cyanobacterium that drives inputs of newly fixed nitrogen and carbon into the oligotrophic ecosystems where it occurs. Colonies of Trichodesmium ubiquitously occur with heterotrophic bacteria that make up a diverse microbiome, and interactions within this Trichodesmium holobiont could influence the fate of fixed carbon and nitrogen. Metatranscriptome sequencing was performed on Trichodesmium colonies collected during high-frequency Lagrangian sampling in the North Pacific Subtropical Gyre (NPSG) to identify possible interactions between the Trichodesmium host and microbiome over day-night cycles. Here we show significantly coordinated patterns of gene expression between host and microbiome, many of which had significant day-night periodicity. The functions of the co-expressed genes suggested a suite of interactions within the holobiont linked to key resources including nitrogen, carbon, and iron. Evidence of microbiome reliance on Trichodesmium-derived vitamin B12 was also detected in co-expression patterns, highlighting a dependency that could shape holobiont community structure. Collectively, these patterns of expression suggest that biotic interactions could influence colony cycling of resources like nitrogen and vitamin B12, and decouple activities, like N 2 fixation, from typical abiotic drivers of Trichodesmium physiological ecology.

High Incidence of ACE/PAI-1 in Association to a Spectrum of Other Polymorphic Cardiovascular Genes Involving PBMCs Proinflammatory Cytokines in Hypertensive Hypercholesterolemic Patients: Reversibility with a Combination of ACE Inhibitor and Statin.

Science.gov (United States)

AlBacha, Jeanne d'Arc; Khoury, Mira; Mouawad, Charbel; Haddad, Katia; Hamoui, Samar; Azar, Albert; Fajloun, Ziad; Makdissy, Nehman

2015-01-01

Cardiovascular diseases (CVDs) are significantly high in the Lebanese population with the two most predominant forms being atherosclerosis and venous thrombosis. The purpose of our study was to assess the association of a spectrum of CVD related genes and combined state of hypertension hypercholesterolemia (HH) in unrelated Lebanese. Twelve polymorphisms were studied by multiplex PCR and reverse hybridization of DNA from 171 healthy individuals and 144 HH subjects. Two genes were significantly associated with HH: ACE (OR: 9.20, PACE activity and PAI-I increased significantly with Del/Del and 4G/5G genotypes. The co-expression of Del/4G(+/+) was detected in 113 out of 171 (66.0%) controls and 125 out of 144 (86.8%) HH subjects. Del/4G(-/-) was detected in only 6 (3.5%) controls and undetected in the HH group. Three venous thrombosis related genes [FV(Leiden), MTHFR(A1298C) and FXIII(V34L)] were significantly related to the prominence of the co-expression of Del/4G(+/+). A range of 2 to 8 combined polymorphisms co-expressed per subject where 5 mutations were the most detected. In Del/4G(+/+) subjects, peripheral blood mononuclear cells (PBMCs) produced significant elevated levels of IFN-γ and TNF-α contrary to IL-10, and no variations occurred for IL-4. ACE inhibitor (ramipril) in combination with statin (atorvastatin) and not alone reversed significantly the situation. This first report from Lebanon sheds light on an additional genetic predisposition of a complex spectrum of genes involved in CVD and suggests that the most requested gene FVL by physicians may not be sufficient to diagnose eventual future problems that can occur in the cardiovascular system. Subjects expressing the double mutations (Del/4G) are at high risk for the onset of CVDs.

Reprogramming energy metabolism and inducing angiogenesis: co-expression of monocarboxylate transporters with VEGF family members in cervical adenocarcinomas

International Nuclear Information System (INIS)

Pinheiro, Céline; Garcia, Eduardo A.; Morais-Santos, Filipa; Moreira, Marise A. R.; Almeida, Fábio M.; Jubé, Luiz F.; Queiroz, Geraldo S.; Paula, Élbio C.; Andreoli, Maria A.; Villa, Luisa L.; Longatto-Filho, Adhemar; Baltazar, Fátima

2015-01-01

Deregulation of cellular energetic metabolism was recently pointed out as a hallmark of cancer cells. This deregulation involves a metabolic reprogramming that leads to a high production of lactate. Lactate efflux, besides contributing for the glycolytic flux, also acts in the extracellular matrix, contributing for cancer malignancy, by, among other effects, induction of angiogenesis. However, studies on the interplay between cancer metabolism and angiogenesis are scarce. Therefore, the aim of the present study was to evaluate the metabolic and vascular molecular profiles of cervical adenocarcinomas, their co-expression, and their relation to the clinical and pathological behavior. The immunohistochemical expression of metabolism-related proteins (MCT1, MCT4, CD147, GLUT1 and CAIX) as well as VEGF family members (VEGF-A, VEGF-C, VEGF-D, VEGFR-1, VEGFR-2 and VEGFR-3) was assessed in a series of 232 cervical adenocarcinomas. The co-expression among proteins was assessed and the expression profiles were associated with patients’ clinicopathological parameters. Among the metabolism-related proteins, MCT4 and CAIX were the most frequently expressed in cervical adenocarcinomas while CD147 was the less frequently expressed protein. Overall, VEGF family members showed a strong and extended expression with VEGF-C and VEGFR-2 as the most frequently expressed and VEGFR-1 as the less expressed member. Co-expression of MCT isoforms with VEGF family members was demonstrated. Finally, MCT4 was associated with parametrial invasion and HPV18 infection, CD147 and GLUT1 with distant metastasis, CAIX with tumor size and HPV18 infection, and VEGFR-1 with local and lymphnode metastasis. The results herein presented provide additional evidence for a crosstalk between deregulating cellular energetics and inducing angiogenesis. Also, the metabolic remodeling and angiogenic switch are relevant to cancer progression and aggressiveness in adenocarcinomas

Differential network analysis reveals evolutionary complexity in secondary metabolism of Rauvolfia serpentina over Catharanthus roseus

Directory of Open Access Journals (Sweden)

Shivalika Pathania

2016-08-01

Full Text Available 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. Towards 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 mechanisms 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 Rauvolfia serpentina, and key genes that contribute towards diversification of specific metabolites.

Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

Science.gov (United States)

Weber, Kristina L; Welly, Bryan T; Van Eenennaam, Alison L; Young, Amy E; Porto-Neto, Laercio R; Reverter, Antonio; Rincon, Gonzalo

2016-01-01

Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

Directory of Open Access Journals (Sweden)

Kristina L Weber

Full Text Available Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI. Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg. Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT, including differentially expressed (DE genes, tissue specific (TS genes, transcription factors (TF, and genes associated with RFI from a genome-wide association study (GWAS. Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05, -1.08 finishing period feed conversion ratio (P = 0.01, +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04, +28.8 kg final body weight (P = 0.01, -12.9 feed bunk visits per day (P = 0.02 with +0.60 min/visit duration (P = 0.01, and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03. RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

Neurotensin Is Co-Expressed, Co-Released And Acts Together With Glp-1 And Pyy In Enteroendocrine Control Of Metabolism

DEFF Research Database (Denmark)

Grunddal, Kaare Villum; Ratner, Cecilia F; Svendsen, Berit

2016-01-01

increasingly multi-hormonal, i.e. co-expressing PYY and neurotensin as they move up the villus. Pro-glucagon promoter and pertussis toxin receptor driven cell ablation and reappearance studies indicated that although all the cells die, the GLP-1 cells reappear more quickly than PYY and neurotensin positive...

Pathway analysis for identification of potential biomarkers in severe ...

African Journals Online (AJOL)

It was found by geneMANIA database search that majority of these genes were coexpressed yielding 84.63 % co-expression. It was found that ten genes were in Physical interactions comprising almost 14.33 %. There were < 1 % pathway and genetic interactions with values of 0.97 and 0.06 %, respectively. Final analyses ...

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

Science.gov (United States)

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.

The Influence of the Coexpression of CD4 and CD8 in Cutaneous Lesions on Prognosis of Mycosis Fungoides: A Preliminary Study

Directory of Open Access Journals (Sweden)

Sergio Umberto De Marchi

2014-01-01

Full Text Available Background. Although techniques of immunophenotyping have been successful in characterizing the cells in the cutaneous infiltrates of mycosis fungoides little evidence suggests that variations in the phenotypic characterization correlate with prognosis. Objectives. In a preliminary prospective, single-centre, study we correlated the T-cell phenotype in cutaneous biopsies with the progression of the disease to determine whether the coexpression of CD4 and CD8 has an impact on prognosis. Methods. Skin biopsy specimens from 30 newly diagnosed patients were stained with immunoperoxidase techniques to determine their phenotypic characteristics. After a median followup of 42 months patients were divided into two groups with stable and progressive disease. Results. Eighteen patients had the conventional CD4+CD8− T-cell phenotype. Ten patients showed the coexpression of CD4 and CD8 and had a slightly lower rate of progressive disease. Conclusions. The coexpression of CD4 and CD8 in cutaneous lesions is not rare and is associated with a slightly lower rate of progressive disease. Since double positive CD4/CD8 phenotype is rarely reported in mycosis fungoides the presence on conventional immunophenotyping of both CD may be due to a “mixture” of neoplastic cells and inflammatory CD8+ tumor infiltrating lymphocytes. Immunohistochemical study combined with confocal microscopy could clarify this issue.

Inferring biological functions of guanylyl cyclases with computational methods

KAUST Repository

Alquraishi, May Majed; Meier, Stuart Kurt

2013-01-01

A number of studies have shown that functionally related genes are often co-expressed and that computational based co-expression analysis can be used to accurately identify functional relationships between genes and by inference, their encoded proteins. Here we describe how a computational based co-expression analysis can be used to link the function of a specific gene of interest to a defined cellular response. Using a worked example we demonstrate how this methodology is used to link the function of the Arabidopsis Wall-Associated Kinase-Like 10 gene, which encodes a functional guanylyl cyclase, to host responses to pathogens. © Springer Science+Business Media New York 2013.

Transcriptome data modeling for targeted plant metabolic engineering.

Science.gov (United States)

Yonekura-Sakakibara, Keiko; Fukushima, Atsushi; Saito, Kazuki

2013-04-01

The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering. Copyright © 2012 Elsevier Ltd. All rights reserved.

Inferring biological functions of guanylyl cyclases with computational methods

KAUST Repository

Alquraishi, May Majed

2013-09-03

A number of studies have shown that functionally related genes are often co-expressed and that computational based co-expression analysis can be used to accurately identify functional relationships between genes and by inference, their encoded proteins. Here we describe how a computational based co-expression analysis can be used to link the function of a specific gene of interest to a defined cellular response. Using a worked example we demonstrate how this methodology is used to link the function of the Arabidopsis Wall-Associated Kinase-Like 10 gene, which encodes a functional guanylyl cyclase, to host responses to pathogens. © Springer Science+Business Media New York 2013.

Aspirin exposure reveals novel genes associated with platelet function and cardiovascular events.

Science.gov (United States)

Voora, Deepak; Cyr, Derek; Lucas, Joseph; Chi, Jen-Tsan; Dungan, Jennifer; McCaffrey, Timothy A; Katz, Richard; Newby, L Kristin; Kraus, William E; Becker, Richard C; Ortel, Thomas L; Ginsburg, Geoffrey S

2013-10-01

The aim of this study was to develop ribonucleic acid (RNA) profiles that could serve as novel biomarkers for the response to aspirin. Aspirin reduces death and myocardial infarction (MI), suggesting that aspirin interacts with biological pathways that may underlie these events. Aspirin was administered, followed by whole-blood RNA microarray profiling, in a discovery cohort of healthy volunteers (HV1) (n = 50) and 2 validation cohorts of healthy volunteers (HV2) (n = 53) and outpatient cardiology patients (OPC) (n = 25). Platelet function was assessed using the platelet function score (PFS) in HV1 and HV2 and the VerifyNow Aspirin Test (Accumetrics, Inc., San Diego, California) in OPC. Bayesian sparse factor analysis identified sets of coexpressed transcripts, which were examined for associations with PFS in HV1 and validated in HV2 and OPC. Proteomic analysis confirmed the association of validated transcripts in platelet proteins. Validated gene sets were tested for association with death or MI in 2 patient cohorts (n = 587 total) from RNA samples collected at cardiac catheterization. A set of 60 coexpressed genes named the "aspirin response signature" (ARS) was associated with PFS in HV1 (r = -0.31, p = 0.03), HV2 (r = -0.34, Bonferroni p = 0.03), and OPC (p = 0.046). Corresponding proteins for the 17 ARS genes were identified in the platelet proteome, of which 6 were associated with PFS. The ARS was associated with death or MI in both patient cohorts (odds ratio: 1.2 [p = 0.01]; hazard ratio: 1.5 [p = 0.001]), independent of cardiovascular risk factors. Compared with traditional risk factors, reclassification (net reclassification index = 31% to 37%, p ≤ 0.0002) was improved by including the ARS or 1 of its genes, ITGA2B. RNA profiles of platelet-specific genes are novel biomarkers for identifying patients who do not respond adequately to aspirin and who are at risk for death or MI. Copyright © 2013 American College of Cardiology Foundation. Published by