Gene coexpression measures in large heterogeneous samples using count statistics.

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

2014-11-18

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

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

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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

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

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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.

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

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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.

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

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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

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

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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

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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.

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

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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).

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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

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

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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.

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

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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

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

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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.

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

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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

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

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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.

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

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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.

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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.

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

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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.

Building gene co-expression networks using transcriptomics data for systems biology investigations

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Kadarmideen, Haja; Watson-Haigh, Nathan S.

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four......) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT...... (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended....

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

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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

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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.

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

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

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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.

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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.

Network statistics of genetically-driven gene co-expression modules in mouse crosses

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Marie-Pier eScott-Boyer

2013-12-01

Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

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

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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...

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

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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.

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

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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.

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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

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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.

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

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

2017-09-26

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

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

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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.

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

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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.

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...

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

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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.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

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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.

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

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

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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.

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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...

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

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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

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

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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

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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

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

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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/.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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

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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

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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.

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

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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.

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

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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.

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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

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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.

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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.

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

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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.

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

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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

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

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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.

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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.

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

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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.

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

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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.

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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.

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

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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.

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

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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.

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

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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

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

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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.

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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

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

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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

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.

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

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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.

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

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

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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

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.

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

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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.

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.

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...

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.

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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.

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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

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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.

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

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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

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.

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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.

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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.

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

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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.

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

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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.

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

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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.

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

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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

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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

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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

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

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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.

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

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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.

An MHC class I immune evasion gene of Marek׳s disease virus.

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Hearn, Cari; Preeyanon, Likit; Hunt, Henry D; York, Ian A

2015-01-15

Marek׳s disease virus (MDV) is a widespread α-herpesvirus of chickens that causes T cell tumors. Acute, but not latent, MDV infection has previously been shown to lead to downregulation of cell-surface MHC class I (Virology 282:198-205 (2001)), but the gene(s) involved have not been identified. Here we demonstrate that an MDV gene, MDV012, is capable of reducing surface expression of MHC class I on chicken cells. Co-expression of an MHC class I-binding peptide targeted to the endoplasmic reticulum (bypassing the requirement for the TAP peptide transporter) partially rescued MHC class I expression in the presence of MDV012, suggesting that MDV012 is a TAP-blocking MHC class I immune evasion protein. This is the first unique non-mammalian MHC class I immune evasion gene identified, and suggests that α-herpesviruses have conserved this function for at least 100 million years. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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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

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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

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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.

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

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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.

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

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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'.

Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

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Vinay Lanke

2018-05-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

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

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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.

Network-based identification of biomarkers coexpressed with multiple pathways.

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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.

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

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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).

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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.

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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.

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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.

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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.

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

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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.

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

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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.

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

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Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

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Recep Colak

2010-10-01

Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

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

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Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

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

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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.

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

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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.

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

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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.

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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.

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

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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.

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

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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.

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

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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

A subpopulation of dopaminergic neurons co-expresses serotonin in ventral mesencephalic cultures but not after intrastriatal transplantation in a rat model of Parkinsons disease

DEFF Research Database (Denmark)

Di Santo, Stefano; Seiler, Stefanie; Ducray, Angélique

2017-01-01

Cell replacement therapy is a promising avenue into the investigation and treatment of Parkinson’s disease (PD) and in some cases significant long-term motor improvements have been demonstrated. The main source of donor tissue is the human fetal ventral mesencephalon (VM), which consists...... 30% of the dopaminergic neurons in the donor tissue co-expressed serotonin, no co-localization could be detected in grafts one month after intrastriatal transplantation into hemi-parkinsonian rats. In conclusion, a significant and susceptible sub-population of dopaminergic neurons in fetal VM tissues...... both fetal rat and human dissociated, organotypic and neurosphere VM cultures as well as an animal model of PD were investigated. In dissociated rat VM cultures approximately 30% of the TH positive neurons co-expressed serotonin, while no co-localization with GABA was observed. Interestingly, co...

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

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

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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.

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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 .

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

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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.

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

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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.

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

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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

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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.

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

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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

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.

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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.

Effector genomics accelerates discovery and functional profiling of potato disease resistance and phytophthora infestans avirulence genes.

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Vivianne G A A Vleeshouwers

Full Text Available Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R genes into potato (Solanum tuberosum is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties.

Genetic architecture of gene expression in the chicken

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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.

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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.

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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.

Supplementing High-Density SNP Microarrays for Additional Coverage of Disease-Related Genes: Addiction as a Paradigm

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SacconePhD, Scott F [Washington University, St. Louis; Chesler, Elissa J [ORNL; Bierut, Laura J [Washington University, St. Louis; Kalivas, Peter J [Medical College of South Carolina, Charleston; Lerman, Caryn [University of Pennsylvania; Saccone, Nancy L [Washington University, St. Louis; Uhl, George R [Johns Hopkins University; Li, Chuan-Yun [Peking University; Philip, Vivek M [ORNL; Edenberg, Howard [Indiana University; Sherry, Steven [National Center for Biotechnology Information; Feolo, Michael [National Center for Biotechnology Information; Moyzis, Robert K [Johns Hopkins University; Rutter, Joni L [National Institute of Drug Abuse

2009-01-01

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well represented by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.

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

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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.

Domestication rewired gene expression and nucleotide diversity patterns in tomato.

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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.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

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Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

2018-03-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

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Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

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

2013-01-01

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

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

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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.

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

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

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

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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.

MicroRNAs Clustered within the 14q32 Locus Are Associated with Endothelial Damage and Microparticle Secretion in Bicuspid Aortic Valve Disease

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Neus Martínez-Micaelo

2017-09-01

Full Text Available Background: We previously described that PECAM+ circulating endothelial microparticles (EMPs are elevated in bicuspid aortic valve (BAV disease as a manifestation of endothelial damage. In this study, we hypothesized that this endothelial damage, is functionally related to the secretion of a specific pattern of EMP-associated miRNAs.Methods: We used a bioinformatics approach to correlate the PECAM+ EMP levels with the miRNA expression profile in plasma in healthy individuals and BAV patients (n = 36. In addition, using the miRNAs that were significantly associated with PECAM+ EMP levels, we inferred a miRNA co-expression network using a Gaussian graphical modeling approach to identify highly co-expressed miRNAs or miRNA clusters whose expression could functionally regulate endothelial damage.Results: We identified a co-expression network composed of 131 miRNAs whose circulating expression was significantly associated with PECAM+ EMP levels. Using a topological analysis, we found that miR-494 was the most important hub within the co-expression network. Furthermore, through positional gene enrichment analysis, we identified a cluster of 19 highly co-expressed miRNAs, including miR-494, that was located in the 14q32 locus on chromosome 14 (p = 1.9 × 10−7. We evaluated the putative biological role of this miRNA cluster by determining the biological significance of the genes targeted by the cluster using functional enrichment analysis. We found that this cluster was involved in the regulation of genes with various functions, specifically the “cellular nitrogen compound metabolic process” (p = 2.34 × 10−145, “immune system process” (p = 2.57 × 10−6, and “extracellular matrix organization” (p = 8.14 × 10−5 gene ontology terms and the “TGF-β signaling pathway” KEGG term (p = 2.59 × 10−8.Conclusions: Using an integrative bioinformatics approach, we identified the circulating miRNA expression profile associated with

MicroRNAs Clustered within the 14q32 Locus Are Associated with Endothelial Damage and Microparticle Secretion in Bicuspid Aortic Valve Disease

Science.gov (United States)

Martínez-Micaelo, Neus; Beltrán-Debón, Raúl; Aragonés, Gerard; Faiges, Marta; Alegret, Josep M.

2017-01-01

Background: We previously described that PECAM+ circulating endothelial microparticles (EMPs) are elevated in bicuspid aortic valve (BAV) disease as a manifestation of endothelial damage. In this study, we hypothesized that this endothelial damage, is functionally related to the secretion of a specific pattern of EMP-associated miRNAs. Methods: We used a bioinformatics approach to correlate the PECAM+ EMP levels with the miRNA expression profile in plasma in healthy individuals and BAV patients (n = 36). In addition, using the miRNAs that were significantly associated with PECAM+ EMP levels, we inferred a miRNA co-expression network using a Gaussian graphical modeling approach to identify highly co-expressed miRNAs or miRNA clusters whose expression could functionally regulate endothelial damage. Results: We identified a co-expression network composed of 131 miRNAs whose circulating expression was significantly associated with PECAM+ EMP levels. Using a topological analysis, we found that miR-494 was the most important hub within the co-expression network. Furthermore, through positional gene enrichment analysis, we identified a cluster of 19 highly co-expressed miRNAs, including miR-494, that was located in the 14q32 locus on chromosome 14 (p = 1.9 × 10−7). We evaluated the putative biological role of this miRNA cluster by determining the biological significance of the genes targeted by the cluster using functional enrichment analysis. We found that this cluster was involved in the regulation of genes with various functions, specifically the “cellular nitrogen compound metabolic process” (p = 2.34 × 10−145), “immune system process” (p = 2.57 × 10−6), and “extracellular matrix organization” (p = 8.14 × 10−5) gene ontology terms and the “TGF-β signaling pathway” KEGG term (p = 2.59 × 10−8). Conclusions: Using an integrative bioinformatics approach, we identified the circulating miRNA expression profile associated with secreted PECAM

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

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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.

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

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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

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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.

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

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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

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

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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.

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

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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.

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

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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

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

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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

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

Alshahrani, Mona

2018-04-30

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

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

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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.

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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.

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

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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.

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

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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

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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.

Norrie disease gene is distinct from the monoamine oxidase genes

OpenAIRE

Sims, Katherine B.; Ozelius, Laurie; Corey, Timothy; Rinehart, William B.; Liberfarb, Ruth; Haines, Jonathan; Chen, Wei Jane; Norio, Reijo; Sankila, Eeva; de la Chapelle, Albert; Murphy, Dennis L.; Gusella, James; Breakefield, Xandra O.

1989-01-01

The genes for MAO-A and MAO-B appear to be very close to the Norrie disease gene, on the basis of loss and /or disruption of the MAO genes and activities in atypical Norrie disease patients deleted for the DXS7 locus; linkage among the MAO genes, the Norrie disease gene, and the DXS7 locus; and mapping of all these loci to the chromosomal region Xp11. The present study provides evidence that the MAO genes are not disrupted in “classic” Norrie disease patients. Genomic DNA from these “nondelet...

Evolutionary dynamics of human autoimmune disease genes and malfunctioned immunological genes

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Podder Soumita

2012-01-01

Full Text Available Abstract Background One of the main issues of molecular evolution is to divulge the principles in dictating the evolutionary rate differences among various gene classes. Immunological genes have received considerable attention in evolutionary biology as candidates for local adaptation and for studying functionally important polymorphisms. The normal structure and function of immunological genes will be distorted when they experience mutations leading to immunological dysfunctions. Results Here, we examined the fundamental differences between the genes which on mutation give rise to autoimmune or other immune system related diseases and the immunological genes that do not cause any disease phenotypes. Although the disease genes examined are analogous to non-disease genes in product, expression, function, and pathway affiliation, a statistically significant decrease in evolutionary rate has been found in autoimmune disease genes relative to all other immune related diseases and non-disease genes. Possible ways of accumulation of mutation in the three steps of the central dogma (DNA-mRNA-Protein have been studied to trace the mutational effects predisposed to disease consequence and acquiring higher selection pressure. Principal Component Analysis and Multivariate Regression Analysis have established the predominant role of single nucleotide polymorphisms in guiding the evolutionary rate of immunological disease and non-disease genes followed by m-RNA abundance, paralogs number, fraction of phosphorylation residue, alternatively spliced exon, protein residue burial and protein disorder. Conclusions Our study provides an empirical insight into the etiology of autoimmune disease genes and other immunological diseases. The immediate utility of our study is to help in disease gene identification and may also help in medicinal improvement of immune related disease.

Gene therapy for ocular diseases.

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Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-05-01

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

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

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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

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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

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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.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

AlShahrani, Mona; Hoehndorf, Robert

2018-01-01

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

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

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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.

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

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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

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

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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.

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.

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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

Systems-level organization of non-alcoholic fatty liver disease progression network

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K. Shubham

2017-10-01

Full Text Available Non-Alcoholic Fatty Liver Disease (NAFLD is a hepatic metabolic disorder that is commonly associated with sedentary lifestyle and high fat diets. NAFLD is prevalent in individuals with obesity, insulin resistance and Type 2 Diabetes (T2D. The clinical spectrum of NAFLD ranges from simple steatosis to Non-Alcoholic Steatohepatitis (NASH with fibrosis, which can progress to cirrhosis and hepatocellular carcinoma.The pathogenesis of NAFLD is complex, involving crosstalk between multiple organs, cell-types, and environmental and genetic factors. Dysfunction of White Adipose Tissue (WAT plays a central role in the development of NAFLD and other metabolic disorders. WAT is an active endocrine organ that regulates whole-body energy homeostasis, lipid metabolism, insulin sensitivity and food intake by secreting biologically active molecules (lipokines, adipokines and cytokines. WAT dynamically reacts to nutrient excess or deprivation by remodelling the number (called hyperplasia and/or size (called hypertrophy of adipocytes to store fat or supply nutrients to other tissues by lipolysis, respectively. Adipose tissue remodelling is also accompanied by changes in the composition or function of stromal vascular cells and ECM. The major objective of our study was to identify and characterize the metabolic and signaling modules associated with the progression of NAFLD in the VAT. We performed Weighted Gene Co-expression Network Analysis (WGCNA to organize microarray data obtained from the VAT of patients at different stages of NAFLD into functional modules. In order to obtain insights into the metabolism and its regulation at the genome scale, a co-expression network of metabolic genes in the Human Metabolic Network (HMR2 was constructed and compared with the co-expression network constructed based on all the varying genes. We also used the prior network information on adipocyte metabolism (GEM to verify and extract reporter metabolites. Our analysis revealed

Norrie disease gene is distinct from the monoamine oxidase genes.

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Sims, K B; Ozelius, L; Corey, T; Rinehart, W B; Liberfarb, R; Haines, J; Chen, W J; Norio, R; Sankila, E; de la Chapelle, A

1989-09-01

The genes for MAO-A and MAO-B appear to be very close to the Norrie disease gene, on the basis of loss and/or disruption of the MAO genes and activities in atypical Norrie disease patients deleted for the DXS7 locus; linkage among the MAO genes, the Norrie disease gene, and the DXS7 locus; and mapping of all these loci to the chromosomal region Xp11. The present study provides evidence that the MAO genes are not disrupted in "classic" Norrie disease patients. Genomic DNA from these "nondeletion" Norrie disease patients did not show rearrangements at the MAOA or DXS7 loci. Normal levels of MAO-A activities, as well as normal amounts and size of the MAO-A mRNA, were observed in cultured skin fibroblasts from these patients, and MAO-B activity in their platelets was normal. Catecholamine metabolites evaluated in plasma and urine were in the control range. Thus, although some atypical Norrie disease patients lack both MAO-A and MAO-B activities, MAO does not appear to be an etiologic factor in classic Norrie disease.

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

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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

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

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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.

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

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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.

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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

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

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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.

Gene Therapy for Parkinson's Disease

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Rachel Denyer

2012-01-01

Full Text Available Current pharmacological and surgical treatments for Parkinson's disease offer symptomatic improvements to those suffering from this incurable degenerative neurological disorder, but none of these has convincingly shown effects on disease progression. Novel approaches based on gene therapy have several potential advantages over conventional treatment modalities. These could be used to provide more consistent dopamine supplementation, potentially providing superior symptomatic relief with fewer side effects. More radically, gene therapy could be used to correct the imbalances in basal ganglia circuitry associated with the symptoms of Parkinson's disease, or to preserve or restore dopaminergic neurons lost during the disease process itself. The latter neuroprotective approach is the most exciting, as it could theoretically be disease modifying rather than simply symptom alleviating. Gene therapy agents using these approaches are currently making the transition from the laboratory to the bedside. This paper summarises the theoretical approaches to gene therapy for Parkinson's disease and the findings of clinical trials in this rapidly changing field.

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

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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.

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

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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.

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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.

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

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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.

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

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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

Gene therapy for CNS diseases – Krabbe disease

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Mohammad A. Rafi

2016-06-01

Full Text Available This is a brief report of the 19th Annual Meeting of the American Society of Gene and Cell Therapy that took place from May 4th through May 7th, 2016 in Washington, DC, USA. While the meeting provided many symposiums, lectures, and scientific sessions this report mainly focuses on one of the sessions on the "Gene Therapy for central nervous system (CNS Diseases" and specifically on the "Gene Therapy for the globoid cell leukodystrophy or Krabbe disease. Two presentations focused on this subject utilizing two animal models of this disease: mice and dog models. Different serotypes of adeno-associate viral vectors (AAV alone or in combination with bone marrow transplantations were used in these research projects. The Meeting of the ASGCT reflected continuous growth in the fields of gene and cell therapy and brighter forecast for efficient treatment options for variety of human diseases.

A recombinant pseudorabies virus co-expressing capsid proteins precursor P1-2A of FMDV and VP2 protein of porcine parvovirus: a trivalent vaccine candidate.

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Hong, Qi; Qian, Ping; Li, Xiang-Min; Yu, Xiao-Lan; Chen, Huan-Chun

2007-11-01

Pseudorabies (PR), foot-and-mouth disease (FMD), and porcine parvovirus disease are three important infectious diseases in swine worldwide. The gene-deleted pseudorabies virus (PRV) has been used as a live-viral vector to develop multivalent genetic engineering vaccine. In this study, a recombinant PRV, which could co-express protein precursor P1-2A of FMDV and VP2 protein of PPV, was constructed using PRV TK(-)/gE(-)/LacZ(+) mutant as the vector. After homologous recombination and plaque purification, recombinant virus PRV TK(-)/gE(-)/P1-2A-VP2 was acquired and identified. Immunogenicity, safety of the recombinant PRV and its protection against PRV were confirmed in a mouse model by indirect ELISA and serum neutralization test. The results show that the recombinant PRV is a candidate vaccine strain to develop a novel trivalent vaccine against PRV, FMDV and PPV in swine.

Gene transfer therapy in vascular diseases.

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McKay, M J; Gaballa, M A

2001-01-01

Somatic gene therapy of vascular diseases is a promising new field in modern medicine. Recent advancements in gene transfer technology have greatly evolved our understanding of the pathophysiologic role of candidate disease genes. With this knowledge, the expression of selective gene products provides the means to test the therapeutic use of gene therapy in a multitude of medical conditions. In addition, with the completion of genome sequencing programs, gene transfer can be used also to study the biologic function of novel genes in vivo. Novel genes are delivered to targeted tissue via several different vehicles. These vectors include adenoviruses, retroviruses, plasmids, plasmid/liposomes, and oligonucleotides. However, each one of these vectors has inherent limitations. Further investigations into developing delivery systems that not only allow for efficient, targeted gene transfer, but also are stable and nonimmunogenic, will optimize the clinical application of gene therapy in vascular diseases. This review further discusses the available mode of gene delivery and examines six major areas in vascular gene therapy, namely prevention of restenosis, thrombosis, hypertension, atherosclerosis, peripheral vascular disease in congestive heart failure, and ischemia. Although we highlight some of the recent advances in the use of gene therapy in treating vascular disease discovered primarily during the past two years, many excellent studies published during that period are not included in this review due to space limitations. The following is a selective review of practical uses of gene transfer therapy in vascular diseases. This review primarily covers work performed in the last 2 years. For earlier work, the reader may refer to several excellent review articles. For instance, Belalcazer et al. (6) reviewed general aspects of somatic gene therapy and the different vehicles used for the delivery of therapeutic genes. Gene therapy in restenosis and stimulation of

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

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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.

Constructing an integrated gene similarity network for the identification of disease genes.

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Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

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

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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

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

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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.

Coexpression and Secretion of Endoglucanase and Phytase Genes in Lactobacillus reuteri

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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

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

Republished review: Gene therapy for ocular diseases.

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Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-07-01

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

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Nolan Priedigkeit

2015-02-01

Full Text Available Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC, is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting "disease map" network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.

Expression of the Bs2 pepper gene confers resistance to bacterial spot disease in tomato.

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Tai, T H; Dahlbeck, D; Clark, E T; Gajiwala, P; Pasion, R; Whalen, M C; Stall, R E; Staskawicz, B J

1999-11-23

The Bs2 resistance gene of pepper specifically recognizes and confers resistance to strains of Xanthomonas campestris pv. vesicatoria that contain the corresponding bacterial avirulence gene, avrBs2. The involvement of avrBs2 in pathogen fitness and its prevalence in many X. campestris pathovars suggests that the Bs2 gene may be durable in the field and provide resistance when introduced into other plant species. Employing a positional cloning strategy, the Bs2 locus was isolated and the gene was identified by coexpression with avrBs2 in an Agrobacterium-mediated transient assay. A single candidate gene, predicted to encode motifs characteristic of the nucleotide binding site-leucine-rich repeat class of resistance genes, was identified. This gene specifically controlled the hypersensitive response when transiently expressed in susceptible pepper and tomato lines and in a nonhost species, Nicotiana benthamiana, and was designated as Bs2. Functional expression of Bs2 in stable transgenic tomatoes supports its use as a source of resistance in other Solanaceous plant species.

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

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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.

The Bioinformatic Analysis of the Dysregulated Genes and MicroRNAs in Entorhinal Cortex, Hippocampus, and Blood for Alzheimer’s Disease

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Xiaocong Pang

2017-01-01

Full Text Available Aim. The incidence of Alzheimer’s disease (AD has been increasing in recent years, but there exists no cure and the pathological mechanisms are not fully understood. This study aimed to find out the pathogenesis of learning and memory impairment, new biomarkers, potential therapeutic targets, and drugs for AD. Methods. We downloaded the microarray data of entorhinal cortex (EC and hippocampus (HIP of AD and controls from Gene Expression Omnibus (GEO database, and then the differentially expressed genes (DEGs in EC and HIP regions were analyzed for functional and pathway enrichment. Furthermore, we utilized the DEGs to construct coexpression networks to identify hub genes and discover the small molecules which were capable of reversing the gene expression profile of AD. Finally, we also analyzed microarray and RNA-seq dataset of blood samples to find the biomarkers related to gene expression in brain. Results. We found some functional hub genes, such as ErbB2, ErbB4, OCT3, MIF, CDK13, and GPI. According to GO and KEGG pathway enrichment, several pathways were significantly dysregulated in EC and HIP. CTSD and VCAM1 were dysregulated significantly in blood, EC, and HIP, which were potential biomarkers for AD. Target genes of four microRNAs had similar GO_terms distribution with DEGs in EC and HIP. In addtion, small molecules were screened out for AD treatment. Conclusion. These biological pathways and DEGs or hub genes will be useful to elucidate AD pathogenesis and identify novel biomarkers or drug targets for developing improved diagnostics and therapeutics against AD.

Inductive matrix completion for predicting gene-disease associations.

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Natarajan, Nagarajan; Dhillon, Inderjit S

2014-06-15

Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has bigdata.ices.utexas.edu/project/gene-disease. © The Author 2014. Published by Oxford University Press.

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

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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.

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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.

Gene expression profiling in autoimmune diseases

DEFF Research Database (Denmark)

Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo

2007-01-01

A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific gene expression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...

Genes and Disease: Prader-Willi Syndrome

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... MD): National Center for Biotechnology Information (US); 1998-. Genes and Disease [Internet]. Show details National Center for ... 45K) PDF version of this title (3.8M) Gene sequence Genome view see gene locations Entrez Gene ...

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

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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.

Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

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Emre Guney

Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.

Ethylene-Related Gene Expression Networks in Wood Formation

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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

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

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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.

Tumor SHB gene expression affects disease characteristics in human acute myeloid leukemia.

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Jamalpour, Maria; Li, Xiujuan; Cavelier, Lucia; Gustafsson, Karin; Mostoslavsky, Gustavo; Höglund, Martin; Welsh, Michael

2017-10-01

The mouse Shb gene coding for the Src Homology 2-domain containing adapter protein B has recently been placed in context of BCRABL1-induced myeloid leukemia in mice and the current study was performed in order to relate SHB to human acute myeloid leukemia (AML). Publicly available AML databases were mined for SHB gene expression and patient survival. SHB gene expression was determined in the Uppsala cohort of AML patients by qPCR. Cell proliferation was determined after SHB gene knockdown in leukemic cell lines. Despite a low frequency of SHB gene mutations, many tumors overexpressed SHB mRNA compared with normal myeloid blood cells. AML patients with tumors expressing low SHB mRNA displayed longer survival times. A subgroup of AML exhibiting a favorable prognosis, acute promyelocytic leukemia (APL) with a PMLRARA translocation, expressed less SHB mRNA than AML tumors in general. When examining genes co-expressed with SHB in AML tumors, four other genes ( PAX5, HDAC7, BCORL1, TET1) related to leukemia were identified. A network consisting of these genes plus SHB was identified that relates to certain phenotypic characteristics, such as immune cell, vascular and apoptotic features. SHB knockdown in the APL PMLRARA cell line NB4 and the monocyte/macrophage cell line MM6 adversely affected proliferation, linking SHB gene expression to tumor cell expansion and consequently to patient survival. It is concluded that tumor SHB gene expression relates to AML survival and its subgroup APL. Moreover, this gene is included in a network of genes that plays a role for an AML phenotype exhibiting certain immune cell, vascular and apoptotic characteristics.

Neural Inductive Matrix Completion for Predicting Disease-Gene Associations

KAUST Repository

Hou, Siqing

2018-05-21

In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations, and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural inductive matrix completion (NIMC), in disease-gene prediction. Comparing to the state-of-the-art inductive matrix completion method, using neural networks allows us to learn latent features from non-linear functions of input features. Previous methods use disease features only from mining text. Comparing to text mining, disease ontology is a more informative way of discovering correlation of dis- eases, from which we can calculate the similarities between diseases and help increase the performance of predicting disease-gene associations. We compare the proposed method with other state-of-the-art methods for pre- dicting associated genes for diseases from the Online Mendelian Inheritance in Man (OMIM) database. Results show that both new features and the proposed NIMC model can improve the chance of recovering an unknown associated gene in the top 100 predicted genes. Best results are obtained by using both the new features and the new model. Results also show the proposed method does better in predicting associated genes for newly discovered diseases.

DISEASES: text mining and data integration of disease-gene associations.

Science.gov (United States)

Pletscher-Frankild, Sune; Pallejà, Albert; Tsafou, Kalliopi; Binder, Janos X; Jensen, Lars Juhl

2015-03-01

Text mining is a flexible technology that can be applied to numerous different tasks in biology and medicine. We present a system for extracting disease-gene associations from biomedical abstracts. The system consists of a highly efficient dictionary-based tagger for named entity recognition of human genes and diseases, which we combine with a scoring scheme that takes into account co-occurrences both within and between sentences. We show that this approach is able to extract half of all manually curated associations with a false positive rate of only 0.16%. Nonetheless, text mining should not stand alone, but be combined with other types of evidence. For this reason, we have developed the DISEASES resource, which integrates the results from text mining with manually curated disease-gene associations, cancer mutation data, and genome-wide association studies from existing databases. The DISEASES resource is accessible through a web interface at http://diseases.jensenlab.org/, where the text-mining software and all associations are also freely available for download. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Gene-wide analysis detects two new susceptibility genes for Alzheimer's disease.

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Escott-Price, Valentina; Bellenguez, Céline; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Jones, Lesley; Holmans, Peter; Gerrish, Amy; Vedernikov, Alexey; Richards, Alexander; DeStefano, Anita L; Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A; Naj, Adam C; Sims, Rebecca; Jun, Gyungah; Bis, Joshua C; Beecham, Gary W; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A; Denning, Nicola; Smith, Albert V; Chouraki, Vincent; Thomas, Charlene; Ikram, M Arfan; Zelenika, Diana; Vardarajan, Badri N; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L; Vronskaya, Maria; Johnson, Andrew D; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L; Buxbaum, Joseph D; Campion, Dominique; Crane, Paul K; Baldwin, Clinton; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L; De Jager, Philip L; Deramecourt, Vincent; Johnston, Janet A; Evans, Denis; Lovestone, Simon; Letenneur, Luc; Hernández, Isabel; Rubinsztein, David C; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M; Fiévet, Nathalie; Huentelman, Matthew J; Gill, Michael; Brown, Kristelle; Kamboh, M Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B; Myers, Amanda J; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleo, Alberto; Bayer, Anthony; Tsuang, Debby W; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick C; Hardy, John; Naranjo, Maria Candida Deniz; Bosco, Paolo; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Scarpini, Elio; Bonuccelli, Ubaldo; Mancuso, Michelangelo; Siciliano, Gabriele; Moebus, Susanne; Mecocci, Patrizia; Zompo, Maria Del; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Frank-García, Ana; Panza, Francesco; Solfrizzi, Vincenzo; Caffarra, Paolo; Nacmias, Benedetta; Perry, William; Mayhaus, Manuel; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M; Ingelsson, Martin; Beekly, Duane; Alvarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G; Coto, Eliecer; Hamilton-Nelson, Kara L; Gu, Wei; Razquin, Cristina; Pastor, Pau; Mateo, Ignacio; Owen, Michael J; Faber, Kelley M; Jonsson, Palmi V; Combarros, Onofre; O'Donovan, Michael C; Cantwell, Laura B; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H; Bennett, David A; Harris, Tamara B; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee F A G; Passmore, Peter; Montine, Thomas J; Bettens, Karolien; Rotter, Jerome I; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M; Kukull, Walter A; Hannequin, Didier; Powell, John F; Nalls, Michael A; Ritchie, Karen; Lunetta, Kathryn L; Kauwe, John S K; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M; Graff, Caroline; Psaty, Bruce M; Haines, Jonathan L; Lathrop, Mark; Pericak-Vance, Margaret A; Launer, Lenore J; Van Broeckhoven, Christine; Farrer, Lindsay A; van Duijn, Cornelia M; Ramirez, Alfredo; Seshadri, Sudha; Schellenberg, Gerard D; Amouyel, Philippe; Williams, Julie

2014-01-01

Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Gene-wide analysis detects two new susceptibility genes for Alzheimer's disease.

Directory of Open Access Journals (Sweden)

Valentina Escott-Price

Full Text Available Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6 and 14 (IGHV1-67 p = 7.9×10-8 which indexed novel susceptibility loci.The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Prioritization of candidate disease genes by topological similarity between disease and protein diffusion profiles.

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Zhu, Jie; Qin, Yufang; Liu, Taigang; Wang, Jun; Zheng, Xiaoqi

2013-01-01

Identification of gene-phenotype relationships is a fundamental challenge in human health clinic. Based on the observation that genes causing the same or similar phenotypes tend to correlate with each other in the protein-protein interaction network, a lot of network-based approaches were proposed based on different underlying models. A recent comparative study showed that diffusion-based methods achieve the state-of-the-art predictive performance. In this paper, a new diffusion-based method was proposed to prioritize candidate disease genes. Diffusion profile of a disease was defined as the stationary distribution of candidate genes given a random walk with restart where similarities between phenotypes are incorporated. Then, candidate disease genes are prioritized by comparing their diffusion profiles with that of the disease. Finally, the effectiveness of our method was demonstrated through the leave-one-out cross-validation against control genes from artificial linkage intervals and randomly chosen genes. Comparative study showed that our method achieves improved performance compared to some classical diffusion-based methods. To further illustrate our method, we used our algorithm to predict new causing genes of 16 multifactorial diseases including Prostate cancer and Alzheimer's disease, and the top predictions were in good consistent with literature reports. Our study indicates that integration of multiple information sources, especially the phenotype similarity profile data, and introduction of global similarity measure between disease and gene diffusion profiles are helpful for prioritizing candidate disease genes. Programs and data are available upon request.

Exploring the potential relevance of human-specific genes to complex disease

Directory of Open Access Journals (Sweden)

Cooper David N

2011-01-01

Full Text Available Abstract Although human disease genes generally tend to be evolutionarily more ancient than non-disease genes, complex disease genes appear to be represented more frequently than Mendelian disease genes among genes of more recent evolutionary origin. It is therefore proposed that the analysis of human-specific genes might provide new insights into the genetics of complex disease. Cross-comparison with the Human Gene Mutation Database (http://www.hgmd.org revealed a number of examples of disease-causing and disease-associated mutations in putatively human-specific genes. A sizeable proportion of these were missense polymorphisms associated with complex disease. Since both human-specific genes and genes associated with complex disease have often experienced particularly rapid rates of evolutionary change, either due to weaker purifying selection or positive selection, it is proposed that a significant number of human-specific genes may play a role in complex disease.

Interference, heterogeneity and disease gene mapping

Energy Technology Data Exchange (ETDEWEB)

Keats, B. [Louisiana State Univ. Medical Center, New Orleans, LA (United States)

1996-12-31

The Human Genome Project has had a major impact on genetic research over the past five years. The number of mapped genes is now over 3,000 compared with approximately 1,600 in 1989 and only about 260 ten years before that. The realization that extensive variation could be detected in anonymous DNA segments greatly enhanced the potential for mapping by linkage analysis. Previously, linkage studies had depended on polymorphisms that could be detected in red blood cell antigens, proteins (revealed by electrophoresis and isoelectric focusing), and cytogenetic heteromorphisms. The identification of thousands of polymorphic DNA markers throughout the human genome has led to the construction of high density genetic linkage maps. These maps provide the data necessary to test hypotheses concerning differences in recombination rates and levels of interference. They are also important for disease gene mapping because the existence of these genes must be inferred from the phenotype. Showing linkage of a disease gene to a DNA marker is the first step towards isolating the disease gene, determining its protein product, and developing effective therapies. However, interpretation of results is not always straightforward. Factors such as etiological heterogeneity and undetected irregular segregation can lead to confusing linkage results and incorrect conclusions about the locations of disease genes. This paper will discuss these phenomena and present examples that illustrate the problems, as well as approaches to dealing with them. 23 refs., 3 figs., 3 tabs.

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

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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

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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

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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.

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

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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.

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

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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.

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.

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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

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer

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Mary Qu Yang

Full Text Available Clear cell renal cell carcinoma (ccRCC is the most common and most aggressive form of renal cell cancer (RCC. The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1, as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways. Keywords: ccRCC, Causative mutation, Pathways, Protein-protein interaction, Gene module, eQTL

Biomedical Information Extraction: Mining Disease Associated Genes from Literature

Science.gov (United States)

Huang, Zhong

2014-01-01

Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

Science.gov (United States)

Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

2015-05-05

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

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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.

Gene therapy for Stargardt disease associated with ABCA4 gene.

Science.gov (United States)

Han, Zongchao; Conley, Shannon M; Naash, Muna I

2014-01-01

Mutations in the photoreceptor-specific flippase ABCA4 lead to accumulation of the toxic bisretinoid A2E, resulting in atrophy of the retinal pigment epithelium (RPE) and death of the photoreceptor cells. Many blinding diseases are associated with these mutations including Stargardt's disease (STGD1), cone-rod dystrophy, retinitis pigmentosa (RP), and increased susceptibility to age-related macular degeneration. There are no curative treatments for any of these dsystrophies. While the monogenic nature of many of these conditions makes them amenable to treatment with gene therapy, the ABCA4 cDNA is 6.8 kb and is thus too large for the AAV vectors which have been most successful for other ocular genes. Here we review approaches to ABCA4 gene therapy including treatment with novel AAV vectors, lentiviral vectors, and non-viral compacted DNA nanoparticles. Lentiviral and compacted DNA nanoparticles in particular have a large capacity and have been successful in improving disease phenotypes in the Abca4 (-/-) murine model. Excitingly, two Phase I/IIa clinical trials are underway to treat patients with ABCA4-associated Startgardt's disease (STGD1). As a result of the development of these novel technologies, effective therapies for ABCA4-associated diseases may finally be within reach.

Current status of gene therapy for motor neuron disease

Institute of Scientific and Technical Information of China (English)

Xingkai An; Rong Peng; Shanshan Zhao

2006-01-01

OBJECTIVE: Although the etiology and pathogenesis of motor neuron disease is still unknown, there are many hypotheses on motor neuron mitochondrion, cytoskeleton structure and functional injuries. Thus, gene therapy of motor neuron disease has become a hot topic to apply in viral vector, gene delivery and basic gene techniques.DATA SOURCES: The related articles published between January 2000 and October 2006 were searched in Medline database and ISl database by computer using the keywords "motor neuron disease, gene therapy", and the language is limited to English. Meanwhile, the related references of review were also searched by handiwork. STUDY SELECTION: Original articles and referred articles in review were chosen after first hearing, then the full text which had new ideas were found, and when refer to the similar study in the recent years were considered first.DATA EXTRACTION: Among the 92 related articles, 40 ones were accepted, and 52 were excluded because of repetitive study or reviews.DATA SYNTHESIS: The viral vectors of gene therapy for motor neuron disease include adenoviral, adeno-associated viral vectors, herpes simplex virus type 1 vectors and lentiviral vectors. The delivery of them can be achieved by direct injection into the brain, or by remote delivery after injection vectors into muscle or peripheral nerves, or by ex vivo gene transfer. The viral vectors of gene therapy for motor neuron disease have been successfully developed, but the gene delivery of them is hampered by some difficulties. The RNA interference and neuroprotection are the main technologies for gene-based therapy in motor neuron disease. CONCLUSION : The RNA interference for motor neuron disease has succeeded in animal models, and the neuroprotection also does. But, there are still a lot of questions for gene therapy in the clinical treatment of motor neuron disease.

HFE gene mutations and Wilson's disease in Sardinia.

Science.gov (United States)

Sorbello, Orazio; Sini, Margherita; Civolani, Alberto; Demelia, Luigi

2010-03-01

Hypocaeruloplasminaemia can lead to tissue iron storage in Wilson's disease and the possibility of iron overload in long-term overtreated patients should be considered. The HFE gene encodes a protein that is intimately involved in intestinal iron absorption. The aim of this study was to determine the prevalence of the HFE gene mutation, its role in iron metabolism of Wilson's disease patients and the interplay of therapy in copper and iron homeostasis. The records of 32 patients with Wilson's disease were reviewed for iron and copper indices, HFE gene mutations and liver biopsy. Twenty-six patients were negative for HFE gene mutations and did not present significant alterations of iron metabolism. The HFE mutation was significantly associated with increased hepatic iron content (PHFE gene wild-type. The HFE gene mutations may be an addictional factor in iron overload in Wilson's disease. Our results showed that an adjustment of dosage of drugs could prevent further iron overload induced by overtreatment only in patients HFE wild-type. 2009. Published by Elsevier Ltd.

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

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

2018-01-01

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

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

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Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Identification of human disease genes from interactome network using graphlet interaction.

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Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

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Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

beta. -Amyloid gene dosage in Alzheimer's disease

Energy Technology Data Exchange (ETDEWEB)

Murdoch, G H; Manuelidis, L; Kim, J H; Manuelidis, E E

1988-01-11

The 4-5 kd amyloid ..beta..-peptide is a major constituent of the characteristic amyloid plaque of Alzheimer's disease. It has been reported that some cases of sporatic Alzheimer's disease are associated with at least a partial duplication of chromosome 21 containing the gene corresponding to the 695 residue precursor of this peptide. To contribute to an understanding of the frequency to such a duplication event in the overall Alzheimer's population, the authors have determined the gene dosage of the ..beta..-amyloid gene in this collection of cases. All cases had a clinical diagnosis of Alzheimer's confirmed neuropathologically. Each Alzheimer's case had an apparent normal diploid ..beta..-amyloid gene dosage, while control Down's cases had the expected triploid dosage. Thus partial duplication of chromosome 21 may be a rare finding in Alzheimer's disease. Similar conclusions were just reported in several studies of the Harvard Alzheimer collection.

[Progress in research on pathogenic genes and gene therapy for inherited retinal diseases].

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Zhu, Ling; Cao, Cong; Sun, Jiji; Gao, Tao; Liang, Xiaoyang; Nie, Zhipeng; Ji, Yanchun; Jiang, Pingping; Guan, Minxin

2017-02-10

Inherited retinal diseases (IRDs), including retinitis pigmentosa, Usher syndrome, Cone-Rod degenerations, inherited macular dystrophy, Leber's congenital amaurosis, Leber's hereditary optic neuropathy are the most common and severe types of hereditary ocular diseases. So far more than 200 pathogenic genes have been identified. With the growing knowledge of the genetics and mechanisms of IRDs, a number of gene therapeutic strategies have been developed in the laboratory or even entered clinical trials. Here the progress of IRD research on the pathogenic genes and therapeutic strategies, particularly gene therapy, are reviewed.

Discovering disease-associated genes in weighted protein-protein interaction networks

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Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

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

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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.

Speeding disease gene discovery by sequence based candidate prioritization

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Porteous David J

2005-03-01

Full Text Available Abstract Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.

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

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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.

A hybrid network-based method for the detection of disease-related genes

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Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

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

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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

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

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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.

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

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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.

Parkinson's disease and mitochondrial gene variations

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Andalib, Sasan; Vafaee, Manouchehr Seyedi; Gjedde, Albert

2014-01-01

Parkinson's disease (PD) is a common disorder of the central nervous system in the elderly. The pathogenesis of PD is a complex process, with genetics as an important contributing factor. This factor may stem from mitochondrial gene variations and mutations as well as from nuclear gene variations...

Global developmental gene expression and pathway analysis of normal brain development and mouse models of human neuronal migration defects.

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Tiziano Pramparo

2011-03-01

Full Text Available Heterozygous LIS1 mutations are the most common cause of human lissencephaly, a human neuronal migration defect, and DCX mutations are the most common cause of X-linked lissencephaly. LIS1 is part of a protein complex including NDEL1 and 14-3-3ε that regulates dynein motor function and microtubule dynamics, while DCX stabilizes microtubules and cooperates with LIS1 during neuronal migration and neurogenesis. Targeted gene mutations of Lis1, Dcx, Ywhae (coding for 14-3-3ε, and Ndel1 lead to neuronal migration defects in mouse and provide models of human lissencephaly, as well as aid the study of related neuro-developmental diseases. Here we investigated the developing brain of these four mutants and wild-type mice using expression microarrays, bioinformatic analyses, and in vivo/in vitro experiments to address whether mutations in different members of the LIS1 neuronal migration complex lead to similar and/or distinct global gene expression alterations. Consistent with the overall successful development of the mutant brains, unsupervised clustering and co-expression analysis suggested that cell cycle and synaptogenesis genes are similarly expressed and co-regulated in WT and mutant brains in a time-dependent fashion. By contrast, focused co-expression analysis in the Lis1 and Ndel1 mutants uncovered substantial differences in the correlation among pathways. Differential expression analysis revealed that cell cycle, cell adhesion, and cytoskeleton organization pathways are commonly altered in all mutants, while synaptogenesis, cell morphology, and inflammation/immune response are specifically altered in one or more mutants. We found several commonly dysregulated genes located within pathogenic deletion/duplication regions, which represent novel candidates of human mental retardation and neurocognitive disabilities. Our analysis suggests that gene expression and pathway analysis in mouse models of a similar disorder or within a common pathway can

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

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Allan Peter Davis

Full Text Available Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/ manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and

Lack of association of the Norrie disease gene with retinoschisis phenotype.

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Shastry, B S; Hiraoka, M; Trese, M T

2000-01-01

It has been reported recently that mice carrying a disrupted Norrie disease gene produced alterations in the murine eye that are similar to congenital retinoschisis. Therefore, it was of interest to determine whether mutations in the Norrie disease gene can account for the disease in families with retinoschisis that do not carry mutations in the retinoschisis gene. The patient set comprised 5 cases of retinoschisis (1 familial and 4 sporadic), all unrelated to each other. Fundus examination of affected individuals showed foveal and peripheral schisis, and the visual acuity range was 20/40-20/60. Peripheral blood specimens were collected from affected and unaffected family members. DNA was extracted and amplified by polymerase chain reaction amplification of exons of the Norrie disease gene. The amplified products were sequenced by the dideoxy chain termination method. The data revealed no disease-specific sequence alterations in the Norrie disease gene. Although we cannot completely exclude the possibility of the Norrie disease gene as a candidate gene, the above results suggest that the structural and functional changes in the Norrie disease gene are not associated with clinically typical retinoschisis families that do not contain mutations in the coding regions and splice sites of the retinoschisis gene.

Gene-Environment Interaction in Parkinson's Disease

DEFF Research Database (Denmark)

Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen

2016-01-01

BACKGROUND AND PURPOSE: Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2...

Mining biological databases for candidate disease genes

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Braun, Terry A.; Scheetz, Todd; Webster, Gregg L.; Casavant, Thomas L.

2001-07-01

The publicly-funded effort to sequence the complete nucleotide sequence of the human genome, the Human Genome Project (HGP), has currently produced more than 93% of the 3 billion nucleotides of the human genome into a preliminary `draft' format. In addition, several valuable sources of information have been developed as direct and indirect results of the HGP. These include the sequencing of model organisms (rat, mouse, fly, and others), gene discovery projects (ESTs and full-length), and new technologies such as expression analysis and resources (micro-arrays or gene chips). These resources are invaluable for the researchers identifying the functional genes of the genome that transcribe and translate into the transcriptome and proteome, both of which potentially contain orders of magnitude more complexity than the genome itself. Preliminary analyses of this data identified approximately 30,000 - 40,000 human `genes.' However, the bulk of the effort still remains -- to identify the functional and structural elements contained within the transcriptome and proteome, and to associate function in the transcriptome and proteome to genes. A fortuitous consequence of the HGP is the existence of hundreds of databases containing biological information that may contain relevant data pertaining to the identification of disease-causing genes. The task of mining these databases for information on candidate genes is a commercial application of enormous potential. We are developing a system to acquire and mine data from specific databases to aid our efforts to identify disease genes. A high speed cluster of Linux of workstations is used to analyze sequence and perform distributed sequence alignments as part of our data mining and processing. This system has been used to mine GeneMap99 sequences within specific genomic intervals to identify potential candidate disease genes associated with Bardet-Biedle Syndrome (BBS).

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

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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

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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

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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.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

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Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

Science.gov (United States)

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

Science.gov (United States)

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile

2017-06-16

The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis

Inhibition of the Secretory pathway by Foot-and-Mouth disease virus 2BC protein is reproduced by co-expression of 2B with 2C, and the site of inhibition is determined by the subcellular location of 2C

DEFF Research Database (Denmark)

Moffat, Katy; Knox, Caroline; Howell, Gareth

2007-01-01

immune responses in vivo. Foot-and-mouth disease virus (FMDV), another picornavirus, can cause persistent infection of ruminants, suggesting it too may inhibit immune responses. Endoplasmic reticulum (ER)-to-Golgi apparatus transport of proteins is blocked by the FMDV 2BC protein. The observation that 2...... blocked in FMDV-infected cells. The block could be reconstituted by coexpression of 2B and 2C, showing that processing of 2BC did not compromise the ability of FMDV to slow secretion. Under these conditions, 2C was located to the Golgi apparatus, and the block in transport also occurred in the Golgi...... apparatus. Interestingly, the block in transport could be redirected to the ER when 2B was coexpressed with a 2C protein fused to an ER retention element. Thus, for FMDV a block in secretion is dependent on both 2B and 2C, with the latter determining the site of the block....

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

Science.gov (United States)

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

2014-01-01

Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

Disease candidate gene identification and prioritization using protein interaction networks

Directory of Open Access Journals (Sweden)

Aronow Bruce J

2009-02-01

Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

Gene-wide analysis detects two new susceptibility genes for Alzheimer's Disease

OpenAIRE

Escott-Price, Valentina; Bellenguez, Céline; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Jones, Lesley; Holmans, Peter Alan; Gerrish, Amy; Vedernikov, Alexey; Richards, Alexander; DeStefano, Anita L.; Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A.; Naj, Adam C.; Sims, Rebecca

2014-01-01

PUBLISHED BACKGROUND: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over...

Tagging of resistance gene(s) to rhizomania disease in sugar beet ...

African Journals Online (AJOL)

The rhizomania disease is one of the most important diseases in Iran and some other parts of the world which potentially could play a role in decreasing sugar yield in fields. One approach to combat with this disease is the use of resistance varieties. This varieties have been identified which are having resistance genes to ...

Retinoschisislike alterations in the mouse eye caused by gene targeting of the Norrie disease gene.

Science.gov (United States)

Ruether, K; van de Pol, D; Jaissle, G; Berger, W; Tornow, R P; Zrenner, E

1997-03-01

To investigate the retinal function and morphology of mice carrying a replacement mutation in exon 2 of the Norrie disease gene. Recently, Norrie disease mutant mice have been generated using gene targeting technology. The mutation removes the 56 N-terminal amino acids of the Norrie gene product. Ganzfeld electroretinograms (ERGs) were obtained in five animals hemizygous or homozygous for the mutant gene and in three female animals heterozygous for the mutant gene. As controls, three males carrying the wild-type gene were examined. Electroretinogram testing included rod a- and b-wave V-log I functions, oscillatory potentials, and cone responses. The fundus morphology has been visualized by scanning laser ophthalmoscopy. Rod and cone ERG responses and fundus morphology were not significantly different among female heterozygotes and wild-type mice. In contrast, the hemizygous mice displayed a severe loss of ERG b-wave, leading to a negatively shaped scotopic ERG and a marked reduction of oscillatory potentials. The a-wave was normal at low intensities, and only with brighter flashes was there a moderate amplitude loss. Cone amplitudes were barely recordable in the gene-targeted males. Ophthalmoscopy revealed snowflakelike vitreal changes, retinoschisis, and pigment epithelium irregularities in hemizygotes and homozygotes, but no changes in female heterozygotes. The negatively shaped scotopic ERG in male mice with a Norrie disease gene mutation probably was caused by retinoschisis. Pigment epithelial changes and degenerations of the outer retina are relatively mild. These findings may be a clue to the embryonal retinoschisislike pathogenesis of Norrie disease in humans or it may indicate a different expression of the Norrie disease gene defect in mice compared to that in humans.

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.

The SPINK gene family and celiac disease susceptibility

NARCIS (Netherlands)

Wapenaar, M.C.; Monsuur, A.J.; Poell, J.; Slot, R. van 't; Meijer, J.W.R.; Meijer, G.A.; Mulder, C.J.; Mearin, M.L.; Wijmenga, C.

2007-01-01

The gene family of serine protease inhibitors of the Kazal type (SPINK) are functional and positional candidate genes for celiac disease (CD). Our aim was to assess the gut mucosal gene expression and genetic association of SPINK1, -2, -4, and -5 in the Dutch CD population. Gene expression was

The SPINK gene family and celiac disease susceptibility

NARCIS (Netherlands)

Wapenaar, Martin C.; Monsuur, Alienke J.; Poell, Jos; Slot, Ruben Van 't; Meijer, Jos W. R.; Meijer, Gerrit A.; Mulder, Chris J.; Mearin, Maria Luisa; Wijmenga, Cisca

The gene family of serine protease inhibitors of the Kazal type (SPINK) are functional and positional candidate genes for celiac disease (CD). Our aim was to assess the gut mucosal gene expression and genetic association of SPINK1, -2, -4, and -5 in the Dutch CD population. Gene expression was

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

International Nuclear Information System (INIS)

Kalra, Rajkumar S.; Wadhwa, Renu

2015-01-01

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

Energy Technology Data Exchange (ETDEWEB)

Kalra, Rajkumar S., E-mail: renu-wadhwa@aist.go.jp; Wadhwa, Renu, E-mail: renu-wadhwa@aist.go.jp [Cell Proliferation Research Group and DBT-AIST International Laboratory for Advanced Biomedicine, National Institute of Advanced Industrial Science and Technology (AIST Central 4), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8562 (Japan)

2015-02-27

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein.

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

Gene editing as a promising approach for respiratory diseases.

Science.gov (United States)

Bai, Yichun; Liu, Yang; Su, Zhenlei; Ma, Yana; Ren, Chonghua; Zhao, Runzhen; Ji, Hong-Long

2018-03-01

Respiratory diseases, which are leading causes of mortality and morbidity in the world, are dysfunctions of the nasopharynx, the trachea, the bronchus, the lung and the pleural cavity. Symptoms of chronic respiratory diseases, such as cough, sneezing and difficulty breathing, may seriously affect the productivity, sleep quality and physical and mental well-being of patients, and patients with acute respiratory diseases may have difficulty breathing, anoxia and even life-threatening respiratory failure. Respiratory diseases are generally heterogeneous, with multifaceted causes including smoking, ageing, air pollution, infection and gene mutations. Clinically, a single pulmonary disease can exhibit more than one phenotype or coexist with multiple organ disorders. To correct abnormal function or repair injured respiratory tissues, one of the most promising techniques is to correct mutated genes by gene editing, as some gene mutations have been clearly demonstrated to be associated with genetic or heterogeneous respiratory diseases. Zinc finger nucleases (ZFN), transcription activator-like effector nucleases (TALEN) and clustered regulatory interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) systems are three innovative gene editing technologies developed recently. In this short review, we have summarised the structure and operating principles of the ZFNs, TALENs and CRISPR/Cas9 systems and their preclinical and clinical applications in respiratory diseases. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

Science.gov (United States)

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

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

A maize resistance gene functions against bacterial streak disease in rice.

Science.gov (United States)

Zhao, Bingyu; Lin, Xinghua; Poland, Jesse; Trick, Harold; Leach, Jan; Hulbert, Scot

2005-10-25

Although cereal crops all belong to the grass family (Poacea), most of their diseases are specific to a particular species. Thus, a given cereal species is typically resistant to diseases of other grasses, and this nonhost resistance is generally stable. To determine the feasibility of transferring nonhost resistance genes (R genes) between distantly related grasses to control specific diseases, we identified a maize R gene that recognizes a rice pathogen, Xanthomonas oryzae pv. oryzicola, which causes bacterial streak disease. Bacterial streak is an important disease of rice in Asia, and no simply inherited sources of resistance have been identified in rice. Although X. o. pv. oryzicola does not cause disease on maize, we identified a maize gene, Rxo1, that conditions a resistance reaction to a diverse collection of pathogen strains. Surprisingly, Rxo1 also controls resistance to the unrelated pathogen Burkholderia andropogonis, which causes bacterial stripe of sorghum and maize. The same gene thus controls resistance reactions to both pathogens and nonpathogens of maize. Rxo1 has a nucleotide-binding site-leucine-rich repeat structure, similar to many previously identified R genes. Most importantly, Rxo1 functions after transfer as a transgene to rice, demonstrating the feasibility of nonhost R gene transfer between cereals and providing a valuable tool for controlling bacterial streak disease.

Network-based association of hypoxia-responsive genes with cardiovascular diseases

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Oldham, William M; Loscalzo, Joseph

2014-01-01

Molecular oxygen is indispensable for cellular viability and function. Hypoxia is a stress condition in which oxygen demand exceeds supply. Low cellular oxygen content induces a number of molecular changes to activate regulatory pathways responsible for increasing the oxygen supply and optimizing cellular metabolism under limited oxygen conditions. Hypoxia plays critical roles in the pathobiology of many diseases, such as cancer, heart failure, myocardial ischemia, stroke, and chronic lung diseases. Although the complicated associations between hypoxia and cardiovascular (and cerebrovascular) diseases (CVD) have been recognized for some time, there are few studies that investigate their biological link from a systems biology perspective. In this study, we integrate hypoxia genes, CVD genes, and the human protein interactome in order to explore the relationship between hypoxia and cardiovascular diseases at a systems level. We show that hypoxia genes are much closer to CVD genes in the human protein interactome than that expected by chance. We also find that hypoxia genes play significant bridging roles in connecting different cardiovascular diseases. We construct a hypoxia-CVD bipartite network and find several interesting hypoxia-CVD modules with significant gene ontology similarity. Finally, we show that hypoxia genes tend to have more CVD interactors in the human interactome than in random networks of matching topology. Based on these observations, we can predict novel genes that may be associated with CVD. This network-based association study gives us a broad view of the relationships between hypoxia and cardiovascular diseases and provides new insights into the role of hypoxia in cardiovascular biology. (paper)

Understanding gene expression in coronary artery disease through ...

Indian Academy of Sciences (India)

Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

Norrie disease and MAO genes: nearest neighbors.

Science.gov (United States)

Chen, Z Y; Denney, R M; Breakefield, X O

1995-01-01

The Norrie disease and MAO genes are tandemly arranged in the p11.4-p11.3 region of the human X chromosome in the order tel-MAOA-MAOB-NDP-cent. This relationship is conserved in the mouse in the order tel-MAOB-MAOA-NDP-cent. The MAO genes appear to have arisen by tandem duplication of an ancestral MAO gene, but their positional relationship to NDP appears to be random. Distinctive X-linked syndromes have been described for mutations in the MAOA and NDP genes, and in addition, individuals have been identified with contiguous gene syndromes due to chromosomal deletions which encompass two or three of these genes. Loss of function of the NDP gene causes a syndrome of congenital blindness and progressive hearing loss, sometimes accompanied by signs of CNS dysfunction, including variable mental retardation and psychiatric symptoms. Other mutations in the NDP gene have been found to underlie another X-linked eye disease, exudative vitreo-retinopathy. An MAOA deficiency state has been described in one family to date, with features of altered amine and amine metabolite levels, low normal intelligence, apparent difficulty in impulse control and cardiovascular difficulty in affected males. A contiguous gene syndrome in which all three genes are lacking, as well as other as yet unidentified flanking genes, results in severe mental retardation, small stature, seizures and congenital blindness, as well as altered amine and amine metabolites. Issues that remain to be resolved are the function of the NDP gene product, the frequency and phenotype of the MAOA deficiency state, and the possible occurrence and phenotype of an MAOB deficiency state.

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.

Human gene therapy and imaging in neurological diseases

International Nuclear Information System (INIS)

Jacobs, Andreas H.; Winkler, Alexandra; Castro, Maria G.; Lowenstein, Pedro

2005-01-01

Molecular imaging aims to assess non-invasively disease-specific biological and molecular processes in animal models and humans in vivo. Apart from precise anatomical localisation and quantification, the most intriguing advantage of such imaging is the opportunity it provides to investigate the time course (dynamics) of disease-specific molecular events in the intact organism. Further, molecular imaging can be used to address basic scientific questions, e.g. transcriptional regulation, signal transduction or protein/protein interaction, and will be essential in developing treatment strategies based on gene therapy. Most importantly, molecular imaging is a key technology in translational research, helping to develop experimental protocols which may later be applied to human patients. Over the past 20 years, imaging based on positron emission tomography (PET) and magnetic resonance imaging (MRI) has been employed for the assessment and ''phenotyping'' of various neurological diseases, including cerebral ischaemia, neurodegeneration and brain gliomas. While in the past neuro-anatomical studies had to be performed post mortem, molecular imaging has ushered in the era of in vivo functional neuro-anatomy by allowing neuroscience to image structure, function, metabolism and molecular processes of the central nervous system in vivo in both health and disease. Recently, PET and MRI have been successfully utilised together in the non-invasive assessment of gene transfer and gene therapy in humans. To assess the efficiency of gene transfer, the same markers are being used in animals and humans, and have been applied for phenotyping human disease. Here, we review the imaging hallmarks of focal and disseminated neurological diseases, such as cerebral ischaemia, neurodegeneration and glioblastoma multiforme, as well as the attempts to translate gene therapy's experimental knowledge into clinical applications and the way in which this process is being promoted through the use of

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 ...

Keratinocyte Growth Factor Gene Electroporation into Skeletal Muscle as a Novel Gene Therapeutic Approach for Elastase-Induced Pulmonary Emphysema in Mice

International Nuclear Information System (INIS)

Tobinaga, Shuichi; Matsumoto, Keitaro; Nagayasu, Takeshi; Furukawa, Katsuro; Abo, Takafumi; Yamasaki, Naoya; Tsuchiya, Tomoshi; Miyazaki, Takuro; Koji, Takehiko

2015-01-01

Pulmonary emphysema is a progressive disease with airspace destruction and an effective therapy is needed. Keratinocyte growth factor (KGF) promotes pulmonary epithelial proliferation and has the potential to induce lung regeneration. The aim of this study was to determine the possibility of using KGF gene therapy for treatment of a mouse emphysema model induced by porcine pancreatic elastase (PPE). Eight-week-old BALB/c male mice treated with intra-tracheal PPE administration were transfected with 80 μg of a recombinant human KGF (rhKGF)-expressing FLAG-CMV14 plasmid (pKGF-FLAG gene), or with the pFLAG gene expressing plasmid as a control, into the quadriceps muscle by electroporation. In the lung, the expression of proliferating cell nuclear antigen (PCNA) was augmented, and surfactant protein A (SP-A) and KGF receptor (KGFR) were co-expressed in PCNA-positive cells. Moreover, endogenous KGF and KGFR gene expression increased significantly by pKGF-FLAG gene transfection. Arterial blood gas analysis revealed that the PaO 2 level was not significantly reduced on day 14 after PPE instillation with pKGF-FLAG gene transfection compared to that of normal mice. These results indicated that KGF gene therapy with electroporation stimulated lung epithelial proliferation and protected depression of pulmonary function in a mouse emphysema model, suggesting a possible method of treating pulmonary emphysema

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.

Retinitis pigmentosa: genes and disease mechanisms.

Science.gov (United States)

Ferrari, Stefano; Di Iorio, Enzo; Barbaro, Vanessa; Ponzin, Diego; Sorrentino, Francesco S; Parmeggiani, Francesco

2011-06-01

Retinitis pigmentosa (RP) is a group of inherited disorders affecting 1 in 3000-7000 people and characterized by abnormalities of the photoreceptors (rods and cones) or the retinal pigment epithelium of the retina which lead to progressive visual loss. RP can be inherited in an autosomal dominant, autosomal recessive or X-linked manner. While usually limited to the eye, RP may also occur as part of a syndrome as in the Usher syndrome and Bardet-Biedl syndrome. Over 40 genes have been associated with RP so far, with the majority of them expressed in either the photoreceptors or the retinal pigment epithelium. The tremendous heterogeneity of the disease makes the genetics of RP complicated, thus rendering genotype-phenotype correlations not fully applicable yet. In addition to the multiplicity of mutations, in fact, different mutations in the same gene may cause different diseases. We will here review which genes are involved in the genesis of RP and how mutations can lead to retinal degeneration. In the future, a more thorough analysis of genetic and clinical data together with a better understanding of the genotype-phenotype correlation might allow to reveal important information with respect to the likelihood of disease development and choices of therapy.

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

FocusHeuristics - expression-data-driven network optimization and disease gene prediction.

Science.gov (United States)

Ernst, Mathias; Du, Yang; Warsow, Gregor; Hamed, Mohamed; Endlich, Nicole; Endlich, Karlhans; Murua Escobar, Hugo; Sklarz, Lisa-Madeleine; Sender, Sina; Junghanß, Christian; Möller, Steffen; Fuellen, Georg; Struckmann, Stephan

2017-02-16

To identify genes contributing to disease phenotypes remains a challenge for bioinformatics. Static knowledge on biological networks is often combined with the dynamics observed in gene expression levels over disease development, to find markers for diagnostics and therapy, and also putative disease-modulatory drug targets and drugs. The basis of current methods ranges from a focus on expression-levels (Limma) to concentrating on network characteristics (PageRank, HITS/Authority Score), and both (DeMAND, Local Radiality). We present an integrative approach (the FocusHeuristics) that is thoroughly evaluated based on public expression data and molecular disease characteristics provided by DisGeNet. The FocusHeuristics combines three scores, i.e. the log fold change and another two, based on the sum and difference of log fold changes of genes/proteins linked in a network. A gene is kept when one of the scores to which it contributes is above a threshold. Our FocusHeuristics is both, a predictor for gene-disease-association and a bioinformatics method to reduce biological networks to their disease-relevant parts, by highlighting the dynamics observed in expression data. The FocusHeuristics is slightly, but significantly better than other methods by its more successful identification of disease-associated genes measured by AUC, and it delivers mechanistic explanations for its choice of genes.

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 ...

Genetics of sputum gene expression in chronic obstructive pulmonary disease.

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Weiliang Qiu

Full Text Available Previous expression quantitative trait loci (eQTL studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs. The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5, the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.

Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

Science.gov (United States)

Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

2011-01-01

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

Increased burden of deleterious variants in essential genes in autism spectrum disorder.

Science.gov (United States)

Ji, Xiao; Kember, Rachel L; Brown, Christopher D; Bućan, Maja

2016-12-27

Autism spectrum disorder (ASD) is a heterogeneous, highly heritable neurodevelopmental syndrome characterized by impaired social interaction, communication, and repetitive behavior. It is estimated that hundreds of genes contribute to ASD. We asked if genes with a strong effect on survival and fitness contribute to ASD risk. Human orthologs of genes with an essential role in pre- and postnatal development in the mouse [essential genes (EGs)] are enriched for disease genes and under strong purifying selection relative to human orthologs of mouse genes with a known nonlethal phenotype [nonessential genes (NEGs)]. This intolerance to deleterious mutations, commonly observed haploinsufficiency, and the importance of EGs in development suggest a possible cumulative effect of deleterious variants in EGs on complex neurodevelopmental disorders. With a comprehensive catalog of 3,915 mammalian EGs, we provide compelling evidence for a stronger contribution of EGs to ASD risk compared with NEGs. By examining the exonic de novo and inherited variants from 1,781 ASD quartet families, we show a significantly higher burden of damaging mutations in EGs in ASD probands compared with their non-ASD siblings. The analysis of EGs in the developing brain identified clusters of coexpressed EGs implicated in ASD. Finally, we suggest a high-priority list of 29 EGs with potential ASD risk as targets for future functional and behavioral studies. Overall, we show that large-scale studies of gene function in model organisms provide a powerful approach for prioritization of genes and pathogenic variants identified by sequencing studies of human disease.

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

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.

Blood Transcriptional Signatures for Disease Progression in a Rat Model of Osteoarthritis

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Michał Korostyński

2017-01-01

Full Text Available Biomarkers of osteoarthritis (OA that can accurately diagnose the disease at the earliest stage would significantly support efforts to develop treatments for prevention and early intervention. We have sought to determine the time course of alterations in peripheral blood gene expression profile associated with the development of OA. Blood samples were collected from a tail vein of individual rats with monosodium iodoacetate- (MIA- induced OA (2, 14, 21, and 28 days after the treatment. We used whole-genome microarrays to reveal OA-related transcriptional alterations of 72 transcripts. Three main groups of coexpressed genes revealed diverse time-dependent profiles of up- and downregulation. Functional links that connect expression of the gradually downregulated genes to the G13 signaling pathway were indicated. The mRNA abundance levels of the identified transcripts were further analyzed in publicly available gene expression dataset obtained from a GARP study cohort of OA patients. We revealed three-gene signature differentially expressed in both rat and human blood (TNK2, KCTD2, and WDR37. The alterations in expression of the selected transcripts in peripheral blood samples of the patients indicate heterogeneity of the OA profiles potentially related to disease progress and severity of clinical symptoms. Our study identifies several potential stage-specific biomarkers of OA progression.

Excessive burden of lysosomal storage disorder gene variants in Parkinson's disease

NARCIS (Netherlands)

Robak, L.A.; Jansen, I.E.; Rooij, J van; Uitterlinden, A.G.; Kraaij, R.; Jankovic, J.; Heutink, P.; Shulman, J.M.; Bloem, B.; Post, B.; Scheffer, H.; Warrenburg, B.P.C. van de; et al.,

2017-01-01

Mutations in the glucocerebrosidase gene (GBA), which cause Gaucher disease, are also potent risk factors for Parkinson's disease. We examined whether a genetic burden of variants in other lysosomal storage disorder genes is more broadly associated with Parkinson's disease susceptibility. The

Gene prioritization for livestock diseases by data integration

DEFF Research Database (Denmark)

Jiang, Li; Sørensen, Peter; Thomsen, Bo Stjerne

2012-01-01

in bovine mastitis. Gene-associated phenome profile and transcriptome profile in response to Escherichia coli infection in the mammary gland were integrated to make a global inference of bovine genes involved in mastitis. The top ranked genes were highly enriched for pathways and biological processes...... underlying inflammation and immune responses, which supports the validity of our approach for identifying genes that are relevant to animal health and disease. These gene-associated phenotypes were used for a local prioritization of candidate genes located in a QTL affecting the susceptibility to mastitis...

Pleiotropic Effects of Variants in Dementia Genes in Parkinson Disease

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Laura Ibanez

2018-04-01

Full Text Available Background: The prevalence of dementia in Parkinson disease (PD increases dramatically with advancing age, approaching 80% in patients who survive 20 years with the disease. Increasing evidence suggests clinical, pathological and genetic overlap between Alzheimer disease, dementia with Lewy bodies and frontotemporal dementia with PD. However, the contribution of the dementia-causing genes to PD risk, cognitive impairment and dementia in PD is not fully established.Objective: To assess the contribution of coding variants in Mendelian dementia-causing genes on the risk of developing PD and the effect on cognitive performance of PD patients.Methods: We analyzed the coding regions of the amyloid-beta precursor protein (APP, Presenilin 1 and 2 (PSEN1, PSEN2, and Granulin (GRN genes from 1,374 PD cases and 973 controls using pooled-DNA targeted sequence, human exome-chip and whole-exome sequencing (WES data by single variant and gene base (SKAT-O and burden tests analyses. Global cognitive function was assessed using the Mini-Mental State Examination (MMSE or the Montreal Cognitive Assessment (MoCA. The effect of coding variants in dementia-causing genes on cognitive performance was tested by multiple regression analysis adjusting for gender, disease duration, age at dementia assessment, study site and APOE carrier status.Results: Known AD pathogenic mutations in the PSEN1 (p.A79V and PSEN2 (p.V148I genes were found in 0.3% of all PD patients. There was a significant burden of rare, likely damaging variants in the GRN and PSEN1 genes in PD patients when compared with frequencies in the European population from the ExAC database. Multiple regression analysis revealed that PD patients carrying rare variants in the APP, PSEN1, PSEN2, and GRN genes exhibit lower cognitive tests scores than non-carrier PD patients (p = 2.0 × 10−4, independent of age at PD diagnosis, age at evaluation, APOE status or recruitment site.Conclusions: Pathogenic mutations in

Gene-Environment Interactions in the Development of Complex Disease Phenotypes

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Kenneth Olden

2008-03-01

Full Text Available The lack of knowledge about the earliest events in disease development is due to the multi-factorial nature of disease risk. This information gap is the consequence of the lack of appreciation for the fact that most diseases arise from the complex interactions between genes and the environment as a function of the age or stage of development of the individual. Whether an environmental exposure causes illness or not is dependent on the efficiency of the so-called “environmental response machinery” (i.e., the complex of metabolic pathways that can modulate response to environmental perturbations that one has inherited. Thus, elucidating the causes of most chronic diseases will require an understanding of both the genetic and environmental contribution to their etiology. Unfortunately, the exploration of the relationship between genes and the environment has been hampered in the past by the limited knowledge of the human genome, and by the inclination of scientists to study disease development using experimental models that consider exposure to a single environmental agent. Rarely in the past were interactions between multiple genes or between genes and environmental agents considered in studies of human disease etiology. The most critical issue is how to relate exposure-disease association studies to pathways and mechanisms. To understand how genes and environmental factors interact to perturb biological pathways to cause injury or disease, scientists will need tools with the capacity to monitor the global expression of thousands of genes, proteins and metabolites simultaneously. The generation of such data in multiple species can be used to identify conserved and functionally significant genes and pathways involved in geneenvironment interactions. Ultimately, it is this knowledge that will be used to guide agencies such as the U.S. Department of Health and Human Services in decisions regarding biomedical research funding

NDP gene mutations in 14 French families with Norrie disease.

Science.gov (United States)

Royer, Ghislaine; Hanein, Sylvain; Raclin, Valérie; Gigarel, Nadine; Rozet, Jean-Michel; Munnich, Arnold; Steffann, Julie; Dufier, Jean-Louis; Kaplan, Josseline; Bonnefont, Jean-Paul

2003-12-01

Norrie disease is a rare X-inked recessive condition characterized by congenital blindness and occasionally deafness and mental retardation in males. This disease has been ascribed to mutations in the NDP gene on chromosome Xp11.1. Previous investigations of the NDP gene have identified largely sixty disease-causing sequence variants. Here, we report on ten different NDP gene allelic variants in fourteen of a series of 21 families fulfilling inclusion criteria. Two alterations were intragenic deletions and eight were nucleotide substitutions or splicing variants, six of them being hitherto unreported, namely c.112C>T (p.Arg38Cys), c.129C>G (p.His43Gln), c.133G>A (p.Val45Met), c.268C>T (p.Arg90Cys), c.382T>C (p.Cys128Arg), c.23479-1G>C (unknown). No NDP gene sequence variant was found in seven of the 21 families. This observation raises the issue of misdiagnosis, phenocopies, or existence of other X-linked or autosomal genes, the mutations of which would mimic the Norrie disease phenotype. Copyright 2003 Wiley-Liss, Inc.

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.

LGscore: A method to identify disease-related genes using biological literature and Google data.

Science.gov (United States)

Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

2015-04-01

Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.

A maize resistance gene functions against bacterial streak disease in rice

OpenAIRE

Zhao, Bingyu; Lin, Xinghua; Poland, Jesse; Trick, Harold; Leach, Jan; Hulbert, Scot

2005-01-01

Although cereal crops all belong to the grass family (Poacea), most of their diseases are specific to a particular species. Thus, a given cereal species is typically resistant to diseases of other grasses, and this nonhost resistance is generally stable. To determine the feasibility of transferring nonhost resistance genes (R genes) between distantly related grasses to control specific diseases, we identified a maize R gene that recognizes a rice pathogen, Xanthomonas oryzae pv. oryzicola, wh...

ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data.

Science.gov (United States)

Zhou, Ke-Ren; Liu, Shun; Sun, Wen-Ju; Zheng, Ling-Ling; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2017-01-04

The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 (http://rna.sysu.edu.cn/chipbase/) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ∼10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed 'Regulator' module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ∼10 000 tumor samples and ∼9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Association between Polymorphisms in Antioxidant Genes and Inflammatory Bowel Disease.

Directory of Open Access Journals (Sweden)

Cristiana Costa Pereira

Full Text Available Inflammation is the driving force in inflammatory bowel disease (IBD and its link to oxidative stress and carcinogenesis has long been accepted. The antioxidant system of the intestinal mucosa in IBD is compromised resulting in increased oxidative injury. This defective antioxidant system may be the result of genetic variants in antioxidant genes, which can represent susceptibility factors for IBD, namely Crohn's disease (CD and ulcerative colitis (UC. Single nucleotide polymorphisms (SNPs in the antioxidant genes SOD2 (rs4880 and GPX1 (rs1050450 were genotyped in a Portuguese population comprising 436 Crohn's disease and 367 ulcerative colitis patients, and 434 healthy controls. We found that the AA genotype in GPX1 is associated with ulcerative colitis (OR = 1.93, adjusted P-value = 0.037. Moreover, we found nominal significant associations between SOD2 and Crohn's disease susceptibility and disease subphenotypes but these did not withstand the correction for multiple testing. These findings indicate a possible link between disease phenotypes and antioxidant genes. These results suggest a potential role for antioxidant genes in IBD pathogenesis and should be considered in future association studies.

Gene expression profiling in autoimmune diseases: chronic inflammation or disease specific patterns?

DEFF Research Database (Denmark)

Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo

2007-01-01

) patients and healthy individuals were specific for the arthritic process or likewise altered in other chronic inflammatory diseases such as chronic autoimmune thyroiditis (Hashimoto's thyroiditis, HT) and inflammatory bowel disease (IBD). Using qPCR for 18 RA-discriminative genes, there were no significant...

New Genes and New Insights from Old Genes: Update on Alzheimer Disease

Science.gov (United States)

Ringman, John M.; Coppola, Giovanni

2013-01-01

Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482

DRUMS: a human disease related unique gene mutation search engine.

Science.gov (United States)

Li, Zuofeng; Liu, Xingnan; Wen, Jingran; Xu, Ye; Zhao, Xin; Li, Xuan; Liu, Lei; Zhang, Xiaoyan

2011-10-01

With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html. © 2011 Wiley-Liss, Inc.

Role of T cell receptor delta gene in susceptibility to celiac disease.

Science.gov (United States)

Roschmann, E; Wienker, T F; Volk, B A

1996-02-01

There is a strong genetic influence on the susceptibility to celiac disease. Although in the vast majority of patients with celiac disease, the HLA-DQ(alpha1*0501, beta1*0201) heterodimer encoded by the alleles HLA-DQA1*0501 and HLA-DQB1*0201 seems to confer the primary disease susceptibility, it cannot be excluded that other genes contribute to disease susceptibility, as indicated by the difference in concordance rates between monozygotic twins and HLA identical siblings (70% vs. 30%). Obviously other genes involved in the genetic control of T cell mediated immune response could potentially influence susceptibility to celiac disease. The density of T cells using the gammadelta T cell receptor (TCR) is considerably increased in the jejunal epithelium of patients with celiac disease, an abnormality considered to be specific for celiac disease. This suggests an involvement of gammadelta T cells in the pathogenesis of the disease. To ascertain whether the TCR delta (TCRD) gene contributes to celiac disease susceptibility we carried out an association study and genetic linkage analysis using a highly polymorphic microsatellite marker at the TCRD locus on chromosome 14q11.2. The association study demonstrated no significant difference in allele frequencies of the TCRD gene marker between celiac disease patients and controls; accordingly, the relative risk estimates did not reach the level of statistical significance. In the linkage analysis, performed in 23 families, the logarithm of the odds (LOD) scores calculated for celiac disease versus the TCRD gene marker excluded linkage, suggesting that there is no determinant contributing to celiac disease status at or 5 cM distant to the analyzed TCRD gene marker. In conclusion, the results of the present study provide no evidence that the analyzed TCRD gene contributes substantially to celiac disease susceptibility.

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

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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.

Co-expression of putative stemness and epithelial-to-mesenchymal transition markers on single circulating tumour cells from patients with early and metastatic breast cancer.

Science.gov (United States)

Papadaki, Maria A; Kallergi, Galatea; Zafeiriou, Zafeiris; Manouras, Lefteris; Theodoropoulos, Panayiotis A; Mavroudis, Dimitris; Georgoulias, Vassilis; Agelaki, Sofia

2014-09-03

The detection of circulating tumor cells (CTCs) in peripheral blood (PB) of patients with breast cancer predicts poor clinical outcome. Cancer cells with stemness and epithelial-to-mesenchymal transition (EMT) features display enhanced malignant and metastatic potential. A new methodology was developed in order to investigate the co-expression of a stemness and an EMT marker (ALDH1 and TWIST, respectively) on single CTCs of patients with early and metastatic breast cancer. Triple immunofluorescence using anti-pancytokeratin (A45-B/B3), anti-ALDH1 and anti-TWIST antibodies was performed in cytospins prepared from hepatocellular carcinoma HepG2 cells and SKBR-3, MCF-7 and MDA.MB.231 breast cancer cell lines. Evaluation of ALDH1 expression levels (high, low or absent) and TWIST subcellular localization (nuclear, cytoplasmic or absent) was performed using the ARIOL system. Cytospins prepared from peripheral blood of patients with early (n = 80) and metastatic (n = 50) breast cancer were analyzed for CTC detection (based on pan-cytokeratin expression and cytomorphological criteria) and characterized according to ALDH1 and TWIST. CTCs were detected in 13 (16%) and 25 (50%) patients with early and metastatic disease, respectively. High ALDH1 expression (ALDH1high) and nuclear TWIST localization (TWISTnuc) on CTCs was confirmed in more patients with metastatic than early breast cancer (80% vs. 30.8%, respectively; p = 0.009). In early disease, ALDH1low/neg CTCs (p = 0.006) and TWISTcyt/neg CTCs (p = 0.040) were mainly observed. Regarding co-expression of these markers, ALDH1high/TWISTnuc CTCs were more frequently evident in the metastatic setting (76% vs. 15.4% of patients, p = 0.001; 61.5% vs. 12.9% of total CTCs), whereas in early disease ALDH1low/neg/TWISTcyt/neg CTCs were mainly detected (61.5% vs. 20% of patients, p = 0.078; 41.9% vs. 7.7% of total CTCs). A new assay is provided for the evaluation of ALDH1 and TWIST co-expression at the

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.

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.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

Science.gov (United States)

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

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.

Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease.

Science.gov (United States)

Johnson, Michael R; Shkura, Kirill; Langley, Sarah R; Delahaye-Duriez, Andree; Srivastava, Prashant; Hill, W David; Rackham, Owen J L; Davies, Gail; Harris, Sarah E; Moreno-Moral, Aida; Rotival, Maxime; Speed, Doug; Petrovski, Slavé; Katz, Anaïs; Hayward, Caroline; Porteous, David J; Smith, Blair H; Padmanabhan, Sandosh; Hocking, Lynne J; Starr, John M; Liewald, David C; Visconti, Alessia; Falchi, Mario; Bottolo, Leonardo; Rossetti, Tiziana; Danis, Bénédicte; Mazzuferi, Manuela; Foerch, Patrik; Grote, Alexander; Helmstaedter, Christoph; Becker, Albert J; Kaminski, Rafal M; Deary, Ian J; Petretto, Enrico

2016-02-01

Genetic determinants of cognition are poorly characterized, and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here we performed a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities, including memory. Using exome sequence data from 6,871 trios, we found that M3 genes were also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease-associated genes in the developed human brain, and provide empirical support for a convergent gene-regulatory network influencing cognition and neurodevelopmental disease.

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

In Search of 'Birth Month Genes': Using Existing Data Repositories to Locate Genes Underlying Birth Month-Disease Relationships.

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Boland, Mary Regina; Tatonetti, Nicholas P

2016-01-01

Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure. Epidemiologists often measure these changes using birth month as a proxy for seasonal variance. Likewise, Genome-Wide Association Studies have associated or implicated these same diseases with many genes. Both disparate data types (epidemiological and genetic) can provide key insights into the underlying disease biology. We developed an algorithm that links 1) epidemiological data from birth month studies with 2) genetic data from published gene-disease association studies. Our framework uses existing data repositories - PubMed, DisGeNET and Gene Ontology - to produce a bipartite network that connects enriched seasonally varying biofactorss with birth month dependent diseases (BMDDs) through their overlapping developmental gene sets. As a proof-of-concept, we investigate 7 known BMDDs and highlight three important biological networks revealed by our algorithm and explore some interesting genetic mechanisms potentially responsible for the seasonal contribution to BMDDs.

Polycistronic gene expression in Aspergillus niger.

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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

Green tissue-specific co-expression of chitinase and oxalate oxidase 4 genes in rice for enhanced resistance against sheath blight.

Science.gov (United States)

Karmakar, Subhasis; Molla, Kutubuddin Ali; Chanda, Palas K; Sarkar, Sailendra Nath; Datta, Swapan K; Datta, Karabi

2016-01-01

Green tissue-specific simultaneous overexpression of two defense-related genes ( OsCHI11 & OsOXO4 ) in rice leads to significant resistance against sheath blight pathogen ( R. solani ) without distressing any agronomically important traits. Overexpressing two defense-related genes (OsOXO4 and OsCHI11) cloned from rice is effective at enhancing resistance against sheath blight caused by Rhizoctonia solani. These genes were expressed under the control of two different green tissue-specific promoters, viz. maize phosphoenolpyruvate carboxylase gene promoter, PEPC, and rice cis-acting 544-bp DNA element, immediately upstream of the D54O translational start site, P D54O-544 . Putative T0 transgenic rice plants were screened by PCR and integration of genes was confirmed by Southern hybridization of progeny (T1) rice plants. Successful expression of OsOXO4 and OsCHI11 in all tested plants was confirmed. Expression of PR genes increased significantly following pathogen infection in overexpressing transgenic plants. Following infection, transgenic plants exhibited elevated hydrogen peroxide levels, significant changes in activity of ROS scavenging enzymes and reduced membrane damage when compared to their wild-type counterpart. In a Rhizoctonia solani toxin assay, a detached leaf inoculation test and an in vivo plant bioassay, transgenic plants showed a significant reduction in disease symptoms in comparison to non-transgenic control plants. This is the first report of overexpression of two different PR genes driven by two green tissue-specific promoters providing enhanced sheath blight resistance in transgenic rice.

Web tools for the prioritization of candidate disease genes.

NARCIS (Netherlands)

Oti, M.O.; Ballouz, S.; Wouters, M.A.

2011-01-01

Despite increasing sequencing capacity, genetic disease investigation still frequently results in the identification of loci containing multiple candidate disease genes that need to be tested for involvement in the disease. This process can be expedited by prioritizing the candidates prior to

Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

Science.gov (United States)

Wang, Lan; Wu, Long-Fei; Lu, Xin; Mo, Xing-Bo; Tang, Zai-Xiang; Lei, Shu-Feng; Deng, Fei-Yan

2015-01-01

Objective Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested. Methods We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis. Results We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation. Conclusion The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases. PMID:26352601

Dysregulation of RNA Mediated Gene Expression in Motor Neuron Diseases.

Science.gov (United States)

Gonçalves, Inês do Carmo G; Rehorst, Wiebke A; Kye, Min Jeong

2016-01-01

Recent findings indicate an important role for RNA-mediated gene expression in motor neuron diseases, including ALS (amyotrophic lateral sclerosis) and SMA (spinal muscular atrophy). ALS, also known as Lou Gehrig's disease, is an adult-onset progressive neurodegenerative disorder, whereby SMA or "children's Lou Gehrig's disease" is considered a pediatric neurodevelopmental disorder. Despite the difference in genetic causes, both ALS and SMA share common phenotypes; dysfunction/loss of motor neurons that eventually leads to muscle weakness and atrophy. With advanced techniques in molecular genetics and cell biology, current data suggest that these two distinct motor neuron diseases share more than phenotypes; ALS and SMA have similar cellular pathological mechanisms including mitochondrial dysfunction, oxidative stress and dysregulation in RNA-mediated gene expression. Here, we will discuss the current findings on these two diseases with specific focus on RNA-mediated gene regulation including miRNA expression, pre-mRNA processing and RNA binding proteins.

Aldosterone synthase gene is not a major susceptibility gene for progression of chronic kidney disease in patients with autosomal dominant polycystic kidney disease

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Gnanasambandan Ramanathan

2017-01-01

Full Text Available Autosomal dominant polycystic kidney disease (ADPKD is the most common heritable kidney disease and is characterized by bilateral renal cysts. Hypertension is a frequent cause of chronic kidney disease (CKD and mortality in patients with ADPKD. The aldosterone synthase gene polymorphisms of the renin-angiotensin-aldosterone system have been extensively studied as hypertension candidate genes. The present study is aimed to investigate the potential modifier effect of CYP11B2 gene on the progression of CKD in ADPKD. One hundred and two ADPKD patients and 106 healthy controls were recruited based on Ravine inclusion and exclusion criteria. The three tag-SNPs within CYP11B2 gene (rs3802230, rs4543, and rs4544 were genotyped using FRET-based KASPar method. Cochran-Armitage trend test was used to assess the potential associations between these polymorphisms and CKD stages. Mantel- Haenszel stratified analysis was used to explore confounding and interaction effects of these polymorphisms. Of the three tag-SNPs genotyped, rs4544 polymorphism was monomorphic and rs3802230 deviated Hardy-Weinberg equilibrium. The CYP11B2 tag-SNPs did not show significant association with ADPKD or CKD. Further, these polymorphisms did not exhibit confounding effect on the relationship between CKD progression and hypertension. Our results suggest that aldosterone synthase gene is not a major susceptibility gene for progression of CKD in South Indian ADPKD patients.

Comparative gene expression between two yeast species

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Guan Yuanfang